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Baars DP, Fondevila MF, Meijnikman AS, Nieuwdorp M. The central role of the gut microbiota in the pathophysiology and management of type 2 diabetes. Cell Host Microbe 2024; 32:1280-1300. [PMID: 39146799 DOI: 10.1016/j.chom.2024.07.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/15/2024] [Accepted: 07/18/2024] [Indexed: 08/17/2024]
Abstract
The inhabitants of our intestines, collectively called the gut microbiome, comprise fungi, viruses, and bacterial strains. These microorganisms are involved in the fermentation of dietary compounds and the regulation of our adaptive and innate immune systems. Less known is the reciprocal interaction between the gut microbiota and type 2 diabetes mellitus (T2DM), as well as their role in modifying therapies to reduce associated morbidity and mortality. In this review, we aim to discuss the existing literature on gut microbial strains and their diet-derived metabolites involved in T2DM. We also explore the potential diagnostics and therapeutic avenues the gut microbiota presents for targeted T2DM management. Personalized treatment plans, driven by diet and medication based on the patient's microbiome and clinical markers, could optimize therapy.
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Affiliation(s)
- Daniel P Baars
- Departments of Internal and Experimental Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, the Netherlands
| | - Marcos F Fondevila
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Abraham S Meijnikman
- Departments of Internal and Experimental Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, the Netherlands
| | - Max Nieuwdorp
- Departments of Internal and Experimental Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, the Netherlands; Diabetes Center Amsterdam, Amsterdam, the Netherlands.
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Safari-Alighiarloo N, Bostanghadiri N, Sedighi M, Mohebbi A, Vafaei E, Mirshekar M, Razavi S, Alaei-Shahmiri F. Quantification and Correlation Analysis of Bacteroides Species with Diabetes-Related Amino Acids in Individuals with Prediabetes and Type 2 Diabetes Mellitus. Metab Syndr Relat Disord 2024. [PMID: 39133120 DOI: 10.1089/met.2024.0071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2024] Open
Abstract
Background: The relationship between gut microbiota and diabetes-related amino acids significantly impacts insulin resistance and obesity. We aimed to quantify two Bacteroidetes species and their correlation with branched-chain amino acids, aromatic amino acids, and glutamate in prediabetes (preDM) and type 2 diabetes mellitus (T2DM). Methods: Fecal samples were collected from 68 participants, including 21 with T2DM, 23 with preDM, and 24 with normal glycemic tolerance (NGT). The abundance of Bacteroides vulgatus and Bacteroides thetaiotaomicron was determined by quantitative real-time polymerase chain reaction. Plasma amino acid measurements were performed using liquid chromatography coupled with tandem mass spectrometry. Results: The quantities of B. vulgatus and B. thetaiotaomicron were reduced in preDM and T2DM than in NGT subjects, but it was not statistically significant. The concentrations of leucine, valine, and tyrosine were significantly higher in preDM and T2DM than in NGT subjects (P < 0.05). A negative correlation was observed between B. thetaiotaomicron abundance and two aromatic amino acids (tyrosine, r = -0.28, P = 0.04; phenylalanine, r = -0.26, P = 0.05). Conclusions: These findings imply that, since gut microbiota varies throughout ethnic groups, further research with many participants will be required to determine the abundance of B. vulgatus and B. thetaiotaomicron in preDM and T2DM and their association with diabetes-related amino acids.
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Affiliation(s)
- Nahid Safari-Alighiarloo
- Institute of Endocrinology and Metabolism, Endocrine Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Narjess Bostanghadiri
- Department of Microbiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mansour Sedighi
- Department of Microbiology, School of Medicine, Kurdistan University of Medical Sciences, Tehran, Iran
- Research Institute for Health Development, Zoonoses Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Ali Mohebbi
- Stem Cell and Regenerative Medicine Innovation Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Elahe Vafaei
- Fetal and Pediatric Cardiovascular Research Center, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Mirshekar
- Department of Microbiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Shabnam Razavi
- Department of Microbiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Fariba Alaei-Shahmiri
- Institute of Endocrinology and Metabolism, Endocrine Research Center, Iran University of Medical Sciences, Tehran, Iran
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3
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Mei Z, Wang F, Bhosle A, Dong D, Mehta R, Ghazi A, Zhang Y, Liu Y, Rinott E, Ma S, Rimm EB, Daviglus M, Willett WC, Knight R, Hu FB, Qi Q, Chan AT, Burk RD, Stampfer MJ, Shai I, Kaplan RC, Huttenhower C, Wang DD. Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes. Nat Med 2024; 30:2265-2276. [PMID: 38918632 DOI: 10.1038/s41591-024-03067-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 05/14/2024] [Indexed: 06/27/2024]
Abstract
The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus. These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale. In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D.
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Affiliation(s)
- Zhendong Mei
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fenglei Wang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Amrisha Bhosle
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Danyue Dong
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Raaj Mehta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Andrew Ghazi
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yancong Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yuxi Liu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ehud Rinott
- Department of Medicine, Hebrew University and Hadassah Medical Center, Jerusalem, Israel
| | - Siyuan Ma
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric B Rimm
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
| | - Walter C Willett
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rob Knight
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Frank B Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Qibin Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Andrew T Chan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Robert D Burk
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Obstetrics, Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Meir J Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Iris Shai
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Faculty of Health Sciences, The Health and Nutrition Innovative International Research Center, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Curtis Huttenhower
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Harvard Chan Microbiome in Public Health Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Dong D Wang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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Tanca A, Deledda MA, De Diego L, Abbondio M, Uzzau S. Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics. mSystems 2024; 9:e0066124. [PMID: 38934547 PMCID: PMC11265449 DOI: 10.1128/msystems.00661-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 06/06/2024] [Indexed: 06/28/2024] Open
Abstract
The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.
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Affiliation(s)
- Alessandro Tanca
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- Unit of Microbiology and Virology, University Hospital of Sassari, Sassari, Italy
| | | | - Laura De Diego
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | - Marcello Abbondio
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- Unit of Microbiology and Virology, University Hospital of Sassari, Sassari, Italy
| | - Sergio Uzzau
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- Unit of Microbiology and Virology, University Hospital of Sassari, Sassari, Italy
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Ye Z, So T, Zhang T, Gao X. Association between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1361440. [PMID: 39027478 PMCID: PMC11254691 DOI: 10.3389/fendo.2024.1361440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 06/20/2024] [Indexed: 07/20/2024] Open
Abstract
Background To clarify the causal relationship between gut microbiota and diabetic nephropathy (DN), we employed Mendelian randomization (MR). Despite a strong correlation observed, establishing causality is still unclear. By utilizing MR, we aimed to investigate this relationship further and shed light on the potential causal effect of gut microbiota on DN. Methods Genetic instrumental variables for gut microbiota were obtained from a GWAS with 18340 participants. DN summary statistics (1032 cases, 451248 controls) were sourced from a separate GWAS. The primary analysis used the inverse-variance weighted (IVW) method. Reverse MR analysis was conducted to explore reverse causation. Rigorous sensitivity analyses were performed to ensure the resilience and reliability of the study's findings. Results We found two bacterial traits associated with an increased risk of DN: genus LachnospiraceaeUCG008 (OR: 1.4210; 95% CI: 1.0450, 1.9322; p = 0.0250) and genus Terrisporobacter (OR: 1.9716; 95% CI: 1.2040, 3.2285; p = 0.0070). Additionally, phylum Proteobacteria (OR: 0.4394; 95% CI: 0.2721, 0.7096; p = 0.0008) and genus Dialister (OR: 0.4841; 95% CI: 0.3171, 0.7390; p = 0.0008) were protective against DN. Sensitivity analyses consistently supported these results. In the reverse MR analysis, no statistically significant associations were observed between DN and these four bacterial traits. Conclusions Our analyses confirmed a potential causal relationship between certain gut microbiota taxa and the risk of DN. However, additional studies are required to elucidate the underlying mechanisms through which gut microbiota influences the development of DN.
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Affiliation(s)
- Zhitao Ye
- Department of Nephrology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Tikyeung So
- Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China
| | - Tianyou Zhang
- Department of Urology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xia Gao
- Department of Nephrology, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
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6
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Hwang CH, Kim SH, Lee CH. Bacterial Growth Modulatory Effects of Two Branched-Chain Hydroxy Acids and Their Production Level by Gut Microbiota. J Microbiol Biotechnol 2024; 34:1314-1321. [PMID: 38938006 PMCID: PMC11239411 DOI: 10.4014/jmb.2404.04009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 04/25/2024] [Indexed: 06/29/2024]
Abstract
Branched-chain hydroxy acids (BCHAs), produced by lactic acid bacteria, have recently been suggested as bioactive compounds contributing to the systemic metabolism and modulation of the gut microbiome. However, the relationship between BCHAs and gut microbiome remains unclear. In this study, we investigated the effects of BCHAs on the growth of seven different families in the gut microbiota. Based on in vitro screening, both 2-hydroxyisovaleric acid (HIVA) and 2-hydroxyisocaproic acid (HICA) stimulated the growth of Lactobacillaceae and Bifidobacteriaceae, with HIVA showing a significant growth promotion. Additionally, we observed not only the growth promotion of probiotic Lactobacillaceae strains but also growth inhibition of pathogenic B. fragilis in a dosedependent manner. The production of HIVA and HICA varied depending on the family of the gut microbiota and was relatively high in case of Lactobacillaceae and Lachnosporaceae. Furthermore, HIVA and HICA production by each strain positively correlated with their growth variation. These results demonstrated gut microbiota-derived BCHAs as active metabolites that have bacterial growth modulatory effects. We suggest that BCHAs can be utilized as active metabolites, potentially contributing to the treatment of diseases associated with gut dysbiosis.
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Affiliation(s)
- Chan Hyuk Hwang
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Republic of Korea
| | - Su-Hyun Kim
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Republic of Korea
- MetaMass Corp., Seoul 05029, Republic of Korea
| | - Choong Hwan Lee
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Republic of Korea
- MetaMass Corp., Seoul 05029, Republic of Korea
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Liu T, Cao Y, Liang N, Ma X, Fang JA, Zhang X. Investigating the causal association between gut microbiota and type 2 diabetes: a meta-analysis and Mendelian randomization. Front Public Health 2024; 12:1342313. [PMID: 38962766 PMCID: PMC11220316 DOI: 10.3389/fpubh.2024.1342313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 05/27/2024] [Indexed: 07/05/2024] Open
Abstract
Background Studies have shown that gut dysbiosis contributes to the pathophysiology of type 2 diabetes mellitus (T2DM). Identifying specific gut microbiota dysbiosis may provide insight into the pathogenesis of T2DM. Purpose This study investigated the causal relationship between gut microbiota and T2DM using meta-analysis and Mendelian randomization (MR). Methods In the first part, we searched for literature on gut microbiota and T2DM, and conducted a meta-analysis. We observed differences in glycosylated hemoglobin and fasting blood glucose levels in both groups. Second, we obtained GWAS data from genome-wide association study database 19 (GWAS). We used two-sample MR analysis to verify the forward and reverse causal associations between gut microbiota and T2DM. Additionally, we selected the European GWAS data from the European Bioinformatics Institute (EBI) as a validation set for external validation of the MR analysis. In the third part, we aimed to clarify which gut microbiota contribute to the degree of causal association between group disorders and T2DM through multivariate MR analysis and Bayesian model averaging (MR-BMA). Results 1. According to the meta-analysis results, the glycated hemoglobin concentration in the gut probiotic intervention group was significantly lower than in the control group. Following treatment, fasting blood glucose levels in the intervention group were significantly lower than those in the control group. 2. The results of two samples MR analysis revealed that there were causal relationships between six gut microbiota and T2DM. Genus Haemophilus and order Pasteurellaceae were negatively correlated with T2DM. Genus Actinomycetes, class Melanobacteria and genus Lactobacillus were positively correlated. Reverse MR analysis demonstrated that T2DM and gut microbiota did not have any reverse causal relationship. The external validation data set showed a causal relationship between gut microbiota and T2DM. 3. Multivariate MR analysis and MR-BMA results showed that the independent genus Haemophilus collection had the largest PP. Conclusion Our research results suggest that gut microbiota is closely related to T2DM pathogenesis. The results of further MR research and an analysis of the prediction model indicate that a variety of gut microbiota disorders, including genus Haemophilus, are causally related to the development of T2DM. The findings of this study may provide some insight into the diagnosis and treatment of T2DM. Systematic review registration https://www.crd.york.ac.uk/PROSPERO.
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Affiliation(s)
- Ting Liu
- Department of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yang Cao
- Department of Nephrology, Shanxi Medical University, Taiyuan, China
| | - Ning Liang
- Department of Nephrology, Shanxi Medical University, Taiyuan, China
| | - Xiaoqi Ma
- Department of Nephrology, Shanxi Medical University, Taiyuan, China
| | - Jing-ai Fang
- Department of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiaodong Zhang
- Department of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, China
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Yan Q, Li S, Yan Q, Huo X, Wang C, Wang X, Sun Y, Zhao W, Yu Z, Zhang Y, Guo R, Lv Q, He X, Yao C, Li Z, Chen F, Ji Q, Zhang A, Jin H, Wang G, Feng X, Feng L, Wu F, Ning J, Deng S, An Y, Guo DA, Martin FM, Ma X. A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases. Cell 2024; 187:2969-2989.e24. [PMID: 38776919 DOI: 10.1016/j.cell.2024.04.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 02/17/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.
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Affiliation(s)
- Qiulong Yan
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Shenghui Li
- Puensum Genetech Institute, Wuhan 430076, China; Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100091, China
| | - Qingsong Yan
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Xiaokui Huo
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Chao Wang
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; First Affiliated Hospital, Dalian Medical University, Dalian 116044, China.
| | - Xifan Wang
- Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100091, China; Department of Obstetrics and Gynecology, Columbia University, New York, NY 10027, USA
| | - Yan Sun
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Wenyu Zhao
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Zhenlong Yu
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Yue Zhang
- Puensum Genetech Institute, Wuhan 430076, China
| | - Ruochun Guo
- Puensum Genetech Institute, Wuhan 430076, China
| | - Qingbo Lv
- Puensum Genetech Institute, Wuhan 430076, China
| | - Xin He
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China; Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China
| | - Changliang Yao
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China
| | | | - Fang Chen
- College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Qianru Ji
- Puensum Genetech Institute, Wuhan 430076, China
| | - Aiqin Zhang
- Puensum Genetech Institute, Wuhan 430076, China
| | - Hao Jin
- Puensum Genetech Institute, Wuhan 430076, China
| | - Guangyang Wang
- College of Basic Medical Sciences, Dalian Medical University, Dalian 116044, China
| | - Xiaoying Feng
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Lei Feng
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Fan Wu
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - Jing Ning
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Sa Deng
- Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China
| | - Yue An
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201210, China.
| | - Francis M Martin
- Université de Lorraine, Institut national de recherche pour l'agriculture, l'alimentation et l'environnement, UMR Interactions Arbres/Microorganismes, Centre INRAE Grand Est-Nancy, Champenoux 54280, France; Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing 100091, China.
| | - Xiaochi Ma
- Second Affiliated Hospital, Dalian Medical University, Dalian 116044, China; Dalian Key Laboratory of Metabolic Target Characterization and Traditional Chinese Medicine Intervention, School of Pharmacy, Dalian Medical University, Dalian 116044, China.
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Zhang J, Yu Z, Li S, Zhang Q, Chen W, Wang J, He S, Liu Y, Chen S, Xu J. Causal relationship between T2DM microvascular complications and gut microbiota: a Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1349465. [PMID: 38887269 PMCID: PMC11180823 DOI: 10.3389/fendo.2024.1349465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 05/17/2024] [Indexed: 06/20/2024] Open
Abstract
Background Gowing number of studies have demonstrated the association between gut microbiome and T2DM microvascular complications, however the causal relationship remains unclear. Therefore, we using the Mendelian randomization (MR) approach to investigate this causal relation. Methods Using gut microbiome data from the International MiBioGen Consortium genome-wide association study (GWAS) and T2DM microvascular complications data from the FinnGen Consortium GWAS to perform MR analyses. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs), the inverse variance weighting (IVW) method was used as the primary analysis method, and the results were tested for heterogeneity and horizontal pleiotropy. Results Our research identified that there are 5 known microbial species and 2 unknown microbial species in the gut microbiome that were causally related to T2DM retinopathy. Besides, three and seven known microbial species causal relationships between the gut microbiome and T2DM neuropathy and T2DM nephropathy, respectively. Conclusions Using MR methods, we demonstrated the causal relationship between gut microbiome and microvascular complications in T2DM, providing a new strategy for the prevention and treatment of it.
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Affiliation(s)
- Junping Zhang
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Zilu Yu
- Queen Mary School, Medical College, Nanchang University, Nanchang, China
| | - Shanshan Li
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Qingfang Zhang
- Queen Mary School, Medical College, Nanchang University, Nanchang, China
| | - Wen Chen
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jingying Wang
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Shasha He
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Jiangxi Clinical Research Center for Endocrine and Metabolic Disease, Nanchang, Jiangxi, China
- Jiangxi Branch of National Clinical Research Center for Metabolic Disease, Nanchang, Jiangxi, China
| | - Ying Liu
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Jiangxi Clinical Research Center for Endocrine and Metabolic Disease, Nanchang, Jiangxi, China
- Jiangxi Branch of National Clinical Research Center for Metabolic Disease, Nanchang, Jiangxi, China
| | - Shen Chen
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
| | - Jixiong Xu
- Department of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Jiangxi, China
- Jiangxi Clinical Research Center for Endocrine and Metabolic Disease, Nanchang, Jiangxi, China
- Jiangxi Branch of National Clinical Research Center for Metabolic Disease, Nanchang, Jiangxi, China
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Wang T, Shi Z, Ren H, Xu M, Lu J, Yang F, Ye C, Wu K, Chen M, Xu X, Liu D, Kong L, Zheng R, Zheng J, Li M, Xu Y, Zhao Z, Chen Y, Yang H, Wang J, Ning G, Li J, Zhong H, Bi Y, Wang W. Divergent age-associated and metabolism-associated gut microbiome signatures modulate cardiovascular disease risk. Nat Med 2024; 30:1722-1731. [PMID: 38844795 DOI: 10.1038/s41591-024-03038-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 04/30/2024] [Indexed: 06/13/2024]
Abstract
Insight into associations between the gut microbiome with metabolism and aging is crucial for tailoring interventions to promote healthy longevity. In a discovery cohort of 10,207 individuals aged 40-93 years, we used 21 metabolic parameters to classify individuals into five clusters, termed metabolic multimorbidity clusters (MCs), that represent different metabolic subphenotypes. Compared to the cluster classified as metabolically healthy (MC1), clusters classified as 'obesity-related mixed' (MC4) and 'hyperglycemia' (MC5) exhibited an increased 11.1-year cardiovascular disease (CVD) risk by 75% (multivariable-adjusted hazard ratio (HR): 1.75, 95% confidence interval (CI): 1.43-2.14) and by 117% (2.17, 1.72-2.74), respectively. These associations were replicated in a second cohort of 9,061 individuals with a 10.0-year follow-up. Based on analysis of 4,491 shotgun fecal metagenomes from the discovery cohort, we found that gut microbial composition was associated with both MCs and age. Next, using 55 age-specific microbial species to capture biological age, we developed a gut microbial age (MA) metric, which was validated in four external cohorts comprising 4,425 metagenomic samples. Among individuals aged 60 years or older, the increased CVD risk associated with MC4 or MC5, as compared to MC1, MC2 or MC3, was exacerbated in individuals with high MA but diminished in individuals with low MA, independent of age, sex and other lifestyle and dietary factors. This pattern, in which younger MA appears to counteract the CVD risk attributable to metabolic dysfunction, implies a modulating role of MA in cardiovascular health for metabolically unhealthy older people.
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Affiliation(s)
- Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhun Shi
- BGI Research, Shenzhen, China
- Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen, China
| | - Huahui Ren
- BGI Research, Shenzhen, China
- Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Chaojie Ye
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kui Wu
- BGI Research, Shenzhen, China
- Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen, China
- Guangdong Provincial Key Laboratory of Human Disease Genomics, BGI Research, Shenzhen, China
| | - Mingling Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xun Xu
- BGI Research, Shenzhen, China
| | - Dong Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lijie Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruizhi Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | | | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Huanzi Zhong
- BGI Research, Shenzhen, China.
- Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen, China.
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Zhang LM, Zhou SW, Huang XS, Chen YF, Mwangi J, Fang YQ, Du T, Zhao M, Shi L, Lu QM. Blap-6, a Novel Antifungal Peptide from the Chinese Medicinal Beetle Blaps rhynchopetera against Cryptococcus neoformans. Int J Mol Sci 2024; 25:5336. [PMID: 38791374 PMCID: PMC11121495 DOI: 10.3390/ijms25105336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 05/09/2024] [Accepted: 05/12/2024] [Indexed: 05/26/2024] Open
Abstract
Cryptococcus neoformans (C. neoformans) is a pathogenic fungus that can cause life-threatening meningitis, particularly in individuals with compromised immune systems. The current standard treatment involves the combination of amphotericin B and azole drugs, but this regimen often leads to inevitable toxicity in patients. Therefore, there is an urgent need to develop new antifungal drugs with improved safety profiles. We screened antimicrobial peptides from the hemolymph transcriptome of Blaps rhynchopetera (B. rhynchopetera), a folk Chinese medicine. We found an antimicrobial peptide named blap-6 that exhibited potent activity against bacteria and fungi. Blap-6 is composed of 17 amino acids (KRCRFRIYRWGFPRRRF), and it has excellent antifungal activity against C. neoformans, with a minimum inhibitory concentration (MIC) of 0.81 μM. Blap-6 exhibits strong antifungal kinetic characteristics. Mechanistic studies revealed that blap-6 exerts its antifungal activity by penetrating and disrupting the integrity of the fungal cell membrane. In addition to its direct antifungal effect, blap-6 showed strong biofilm inhibition and scavenging activity. Notably, the peptide exhibited low hemolytic and cytotoxicity to human cells and may be a potential candidate antimicrobial drug for fungal infection caused by C. neoformans.
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Affiliation(s)
- La-Mei Zhang
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming 650224, China; (L.-M.Z.); (T.D.); (M.Z.)
- Key Laboratory of Breeding and Utilization of Resource Insects, National Forestry and Grassland Administration, Kunming 650224, China
| | - Sheng-Wen Zhou
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao-Shan Huang
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yi-Fan Chen
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - James Mwangi
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
- Kunming College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ya-Qun Fang
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
| | - Ting Du
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming 650224, China; (L.-M.Z.); (T.D.); (M.Z.)
- Key Laboratory of Breeding and Utilization of Resource Insects, National Forestry and Grassland Administration, Kunming 650224, China
| | - Min Zhao
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming 650224, China; (L.-M.Z.); (T.D.); (M.Z.)
- Key Laboratory of Breeding and Utilization of Resource Insects, National Forestry and Grassland Administration, Kunming 650224, China
| | - Lei Shi
- Institute of Highland Forest Science, Chinese Academy of Forestry, Kunming 650224, China; (L.-M.Z.); (T.D.); (M.Z.)
- Key Laboratory of Breeding and Utilization of Resource Insects, National Forestry and Grassland Administration, Kunming 650224, China
| | - Qiu-Min Lu
- Engineering Laboratory of Peptides of Chinese Academy of Sciences, Key Laboratory of Bioactive Peptides of Yunnan Province, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Key Laboratory of Genetic Evolution & Animal Models, Sino-African Joint Research Center, and New Cornerstone Science Laboratory, Kunming Institute of Zoology, the Chinese Academy of Sciences, No.17 Longxin Road, Kunming 650201, China; (S.-W.Z.); (X.-S.H.); (Y.-F.C.); (J.M.); (Y.-Q.F.)
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12
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Luo K, Peters BA, Moon JY, Xue X, Wang Z, Usyk M, Hanna DB, Landay AL, Schneider MF, Gustafson D, Weber KM, French A, Sharma A, Anastos K, Wang T, Brown T, Clish CB, Kaplan RC, Knight R, Burk RD, Qi Q. Metabolic and inflammatory perturbation of diabetes associated gut dysbiosis in people living with and without HIV infection. Genome Med 2024; 16:59. [PMID: 38643166 PMCID: PMC11032597 DOI: 10.1186/s13073-024-01336-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 04/16/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Gut dysbiosis has been linked with both HIV infection and diabetes, but its interplay with metabolic and inflammatory responses in diabetes, particularly in the context of HIV infection, remains unclear. METHODS We first conducted a cross-sectional association analysis to characterize the gut microbial, circulating metabolite, and immune/inflammatory protein features associated with diabetes in up to 493 women (~ 146 with prevalent diabetes with 69.9% HIV +) of the Women's Interagency HIV Study. Prospective analyses were then conducted to determine associations of identified metabolites with incident diabetes over 12 years of follow-up in 694 participants (391 women from WIHS and 303 men from the Multicenter AIDS Cohort Study; 166 incident cases were recorded) with and without HIV infection. Mediation analyses were conducted to explore whether gut bacteria-diabetes associations are explained by altered metabolites and proteins. RESULTS Seven gut bacterial genera were identified to be associated with diabetes (FDR-q < 0.1), with positive associations for Shigella, Escherichia, Megasphaera, and Lactobacillus, and inverse associations for Adlercreutzia, Ruminococcus, and Intestinibacter. Importantly, the associations of most species, especially Adlercreutzia and Ruminococcus, were largely independent of antidiabetic medications use. Meanwhile, 18 proteins and 76 metabolites, including 3 microbially derived metabolites (trimethylamine N-oxide, phenylacetylglutamine (PAGln), imidazolepropionic acid (IMP)), 50 lipids (e.g., diradylglycerols (DGs) and triradylglycerols (TGs)) and 23 non-lipid metabolites, were associated with diabetes (FDR-q < 0.1), with the majority showing positive associations and more than half of them (59/76) associated with incident diabetes. In mediation analyses, several proteins, especially interleukin-18 receptor 1 and osteoprotegerin, IMP and PAGln partially mediate the observed bacterial genera-diabetes associations, particularly for those of Adlercreutzia and Escherichia. Many diabetes-associated metabolites and proteins were altered in HIV, but no effect modification on their associations with diabetes was observed by HIV. CONCLUSION Among individuals with and without HIV, multiple gut bacterial genera, blood metabolites, and proinflammatory proteins were associated with diabetes. The observed mediated effects by metabolites and proteins in genera-diabetes associations highlighted the potential involvement of inflammatory and metabolic perturbations in the link between gut dysbiosis and diabetes in the context of HIV infection.
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Affiliation(s)
- Kai Luo
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Brandilyn A Peters
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Xiaonan Xue
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Zheng Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Mykhaylo Usyk
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - David B Hanna
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Alan L Landay
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Michael F Schneider
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Deborah Gustafson
- Department of Neurology, State University of New York-Downstate Medical Center, Brooklyn, NY, USA
| | | | - Audrey French
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Anjali Sharma
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kathryn Anastos
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Todd Brown
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rob Knight
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Robert D Burk
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Obstetrics and Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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Li L, Mayne J, Beltran A, Zhang X, Ning Z, Figeys D. RapidAIM 2.0: a high-throughput assay to study functional response of human gut microbiome to xenobiotics. MICROBIOME RESEARCH REPORTS 2024; 3:26. [PMID: 38841404 PMCID: PMC11149095 DOI: 10.20517/mrr.2023.57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 03/03/2024] [Accepted: 03/25/2024] [Indexed: 06/07/2024]
Abstract
Aim: Our gut microbiome has its own functionalities which can be modulated by various xenobiotic and biotic components. The development and application of a high-throughput functional screening approach of individual gut microbiomes accelerates drug discovery and our understanding of microbiome-drug interactions. We previously developed the rapid assay of individual microbiome (RapidAIM), which combined an optimized culturing model with metaproteomics to study gut microbiome responses to xenobiotics. In this study, we aim to incorporate automation and multiplexing techniques into RapidAIM to develop a high-throughput protocol. Methods: To develop a 2.0 version of RapidAIM, we automated the protein analysis protocol, and introduced a tandem mass tag (TMT) multiplexing technique. To demonstrate the typical outcome of the protocol, we used RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows. Results: We describe the protocol of RapidAIM 2.0 with extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, sample processing, metaproteomics measurement, and data analysis. The analysis depth of 5,014 ± 142 protein groups per multiplexed sample was achieved. A test on five biobanking methods using RapidAIM 2.0 showed the minimal effect of sample processing on live microbiota functional responses to kestose. Conclusions: Depth and reproducibility of RapidAIM 2.0 are comparable to previous manual label-free metaproteomic analyses. In the meantime, the protocol realizes culturing and sample preparation of 320 samples in six days, opening the door to extensively understanding the effects of xenobiotic and biotic factors on our internal ecology.
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Affiliation(s)
| | | | | | | | | | - Daniel Figeys
- Correspondence to: Prof. Daniel Figeys, School of Pharmaceutical Sciences, Ottawa Institute of Systems Biology and Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa K1H 8M5, Ontario, Canada. E-mail:
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14
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Tzemah-Shahar R, Turjeman S, Sharon E, Gamliel G, Hochner H, Koren O, Agmon M. Signs of aging in midlife: physical function and sex differences in microbiota. GeroScience 2024; 46:1477-1488. [PMID: 37610596 PMCID: PMC10828485 DOI: 10.1007/s11357-023-00905-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/04/2023] [Indexed: 08/24/2023] Open
Abstract
Microbiota composition has been linked to physical activity, health measures, and biological age, but a shared profile has yet to be shown. The aim of this study was to examine the associations between microbiota composition and measures of function, such as a composite measure of physical capacity, and biological age in midlife, prior to onset of age-related diseases. Seventy healthy midlife individuals (age 44.58 ± 0.18) were examined cross-sectionally, and their gut-microbiota profile was characterized from stool samples using 16SrRNA gene sequencing. Biological age was measured using the Klemera-Doubal method and a composition of blood and physiological biomarkers. Physical capacity was calculated based on sex-standardized functional tests. We demonstrate that the women had significantly richer microbiota, p = 0.025; however, microbiota diversity was not linked with chronological age, biological age, or physical capacity for either women or men. Men had slightly greater β-diversity; however, β-diversity was positively associated with biological age and with physical capacity for women only (p = 0.01 and p = 0.04; respectively). For women, an increase in abundance of Roseburia faecis and Collinsella aerofaciens, as well as genus Ruminococcus and Dorea, was significantly associated with higher biological age and lower physical capacity; an increase in abundance of Akkermansia muciniphila and genera Bacteroides and Alistipes was associated with younger biological age and increased physical capacity. Differentially abundant taxa were also associated with non-communicable diseases. These findings suggest that microbiota composition is a potential mechanism linking physical capacity and health status; personalized probiotics may serve as a new means to support health-promoting interventions in midlife. Investigating additional factors underlying this link may facilitate the development of a more accurate method to estimate the rate of aging.
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Affiliation(s)
- Roy Tzemah-Shahar
- Faculty of Social Welfare and Health Sciences, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
| | - Sondra Turjeman
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Efrat Sharon
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Gila Gamliel
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Hagit Hochner
- Epidemiology Unit, Hebrew University School of Public Health, Jerusalem, Israel
| | - Omry Koren
- Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Maayan Agmon
- Faculty of Social Welfare and Health Sciences, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel.
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15
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Liu J, Yan Q, Li S, Jiao J, Hao Y, Zhang G, Zhang Q, Luo F, Zhang Y, Lv Q, Zhang W, Zhang A, Song H, Xin Y, Ma Y, Owusu L, Ma X, Yin P, Shang D. Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis. NPJ Biofilms Microbiomes 2024; 10:29. [PMID: 38514648 PMCID: PMC10957925 DOI: 10.1038/s41522-024-00499-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 03/13/2024] [Indexed: 03/23/2024] Open
Abstract
Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential pathobionts, and host metabolome in individuals with AP remains elusive. Hence, we employed fecal whole-metagenome shotgun sequencing in 82 AP patients and 115 matched healthy controls, complemented by untargeted serum metabolome and lipidome profiling in a subset of participants. Analyses of the gut microbiome in AP patients revealed reduced diversity, disrupted microbial functions, and altered abundance of 77 species, influenced by both etiology and severity. AP-enriched species, mostly potential pathobionts, correlated positively with host liver function and serum lipid indicators. Conversely, many AP-depleted species were short-chain fatty acid producers. Gut microflora changes were accompanied by shifts in the serum metabolome and lipidome. Specifically, certain gut species, like enriched Bilophila wadsworthia and depleted Bifidobacterium spp., appeared to contribute to elevated triglyceride levels in biliary or hyperlipidemic AP patients. Through culturing and whole-genome sequencing of bacterial isolates, we identified virulence factors and clinically relevant antibiotic resistance in patient-derived strains, suggesting a predisposition to opportunistic infections. Finally, our study demonstrated that gavage of specific pathobionts could exacerbate pancreatitis in a caerulein-treated mouse model. In conclusion, our comprehensive analysis sheds light on the gut microbiome and serum metabolome in AP, elucidating the role of pathobionts in disease progression. These insights offer valuable perspectives for etiologic diagnosis, prevention, and intervention in AP and related conditions.
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Affiliation(s)
- Jianjun Liu
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- College of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Qiulong Yan
- Department of Microbiology, College of Basic Medical Sciences, Dalian Medical University, Dalian, China
| | | | - Juying Jiao
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- College of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Yiming Hao
- Department of Gastrointestinal Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Guixin Zhang
- Pancreaticobiliary Centre, Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingkai Zhang
- Pancreaticobiliary Centre, Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Fei Luo
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- College of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Yue Zhang
- Puensum Genetech Institute, Wuhan, China
| | - Qingbo Lv
- Puensum Genetech Institute, Wuhan, China
| | - Wenzhe Zhang
- Department of Microbiology, College of Basic Medical Sciences, Dalian Medical University, Dalian, China
| | | | - Huiyi Song
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yi Xin
- Department of Biotechnology, College of Basic Medical Sciences, Dalian Medical University, Dalian, China
| | - Yufang Ma
- Department of Microbiology, College of Basic Medical Sciences, Dalian Medical University, Dalian, China
| | - Lawrence Owusu
- College of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Xiaochi Ma
- Second Affiliated Hospital, Dalian Medical University, Dalian, China.
| | - Peiyuan Yin
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
- College of Integrative Medicine, Dalian Medical University, Dalian, China.
| | - Dong Shang
- Clinical Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
- College of Integrative Medicine, Dalian Medical University, Dalian, China.
- Pancreaticobiliary Centre, Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
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16
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Castañeda-Monsalve V, Fröhlich LF, Haange SB, Homsi MN, Rolle-Kampczyk U, Fu Q, von Bergen M, Jehmlich N. High-throughput screening of the effects of 90 xenobiotics on the simplified human gut microbiota model (SIHUMIx): a metaproteomic and metabolomic study. Front Microbiol 2024; 15:1349367. [PMID: 38444810 PMCID: PMC10912515 DOI: 10.3389/fmicb.2024.1349367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/05/2024] [Indexed: 03/07/2024] Open
Abstract
The human gut microbiota is a complex microbial community with critical functions for the host, including the transformation of various chemicals. While effects on microorganisms has been evaluated using single-species models, their functional effects within more complex microbial communities remain unclear. In this study, we investigated the response of a simplified human gut microbiota model (SIHUMIx) cultivated in an in vitro bioreactor system in combination with 96 deep-well plates after exposure to 90 different xenobiotics, comprising 54 plant protection products and 36 food additives and dyes, at environmentally relevant concentrations. We employed metaproteomics and metabolomics to evaluate changes in bacterial abundances, the production of Short Chain Fatty Acids (SCFAs), and the regulation of metabolic pathways. Our findings unveiled significant changes induced by 23 out of 54 plant protection products and 28 out of 36 food additives across all three categories assessed. Notable highlights include azoxystrobin, fluroxypyr, and ethoxyquin causing a substantial reduction (log2FC < -0.5) in the concentrations of the primary SCFAs: acetate, butyrate, and propionate. Several food additives had significant effects on the relative abundances of bacterial species; for example, acid orange 7 and saccharin led to a 75% decrease in Clostridium butyricum, with saccharin causing an additional 2.5-fold increase in E. coli compared to the control. Furthermore, both groups exhibited up- and down-regulation of various pathways, including those related to the metabolism of amino acids such as histidine, valine, leucine, and isoleucine, as well as bacterial secretion systems and energy pathways like starch, sucrose, butanoate, and pyruvate metabolism. This research introduces an efficient in vitro technique that enables high-throughput screening of the structure and function of a simplified and well-defined human gut microbiota model against 90 chemicals using metaproteomics and metabolomics. We believe this approach will be instrumental in characterizing chemical-microbiota interactions especially important for regulatory chemical risk assessments.
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Affiliation(s)
- Victor Castañeda-Monsalve
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Laura-Fabienne Fröhlich
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Sven-Bastiaan Haange
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Masun Nabhan Homsi
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Ulrike Rolle-Kampczyk
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Qiuguo Fu
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
| | - Martin von Bergen
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
- Institute of Biochemistry, Faculty of Biosciences, Pharmacy and Psychology, University of Leipzig, Leipzig, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Nico Jehmlich
- Department of Molecular Toxicology, Helmholtz Centre for Environmental Research GmbH (UFZ), Leipzig, Germany
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17
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Zhang Y, Hu J, Zhong Y, Liu S, Liu L, Mu X, Chen C, Yang S, Li G, Zhang D, Huang X, Yang J, Huang X, Bian S, Nie S. Insoluble/soluble fraction ratio determines effects of dietary fiber on gut microbiota and serum metabolites in healthy mice. Food Funct 2024; 15:338-354. [PMID: 38088096 DOI: 10.1039/d3fo04068b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Both soluble dietary fiber (SDF) and insoluble dietary fiber (IDF) play pivotal roles in maintaining gut microbiota homeostasis; whether the effects of the different ratios of IDF and SDF are consistent remains unclear. Consequently, we selected SDFs and IDFs from six representative foods (apple, celery, kale, black fungus, oats, and soybeans) and formulated nine dietary fiber recipes composed of IDF and SDF with a ratio from 1 : 9 to 9 : 1 (NDFR) to compare their impact on microbial effects with healthy mice. We discovered that NDFR treatment decreased the abundance of Proteobacteria and the ratio of Firmicutes/Bacteroidetes at the phylum level. The α diversity and relative richness of Parabacteroides and Prevotella at the genus level showed an upward trend along with the ratio of IDF increasing, while the relative abundance of Akkermansia at the genus level and the production of acetic acid and propionic acid exhibited an increased trend along with the ratio of SDF increasing. The relative abundance of Parabacteroides and Prevotella in the I9S1DF group (the ratio of IDF and SDF was 9 : 1) was 1.72 times and 5.92 times higher than that in the I1S9DF group (the ratio of IDF and SDF was 1 : 9), respectively. The relative abundance of Akkermansia in the I1S9DF group was 17.18 times higher than that in the I9S1DF group. Moreover, a high ratio of SDF (SDF reaches 60% or more) enriched the glycerophospholipid metabolism pathway; however, a high ratio of IDF (IDF reaches 80% or more) regulated the tricarboxylic acid cycle. These findings are helpful in the development of dietary fiber supplements based on gut microbiota and metabolites.
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Affiliation(s)
- Yanli Zhang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Jielun Hu
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Yadong Zhong
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Shuai Liu
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Liandi Liu
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Xinyi Mu
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Chunhua Chen
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Shenji Yang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Guohao Li
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Duoduo Zhang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Xinru Huang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Jinrui Yang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Xiaojun Huang
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Shuigen Bian
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
| | - Shaoping Nie
- State Key Laboratory of Food Science and Resources, China-Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University, 235 Nanjing East Road, Nanchang 330047, China.
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18
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Zhang B, Zhang X, Luo Z, Ren J, Yu X, Zhao H, Wang Y, Zhang W, Tian W, Wei X, Ding Q, Yang H, Jin Z, Tong X, Wang J, Zhao L. Microbiome and metabolome dysbiosis analysis in impaired glucose tolerance for the prediction of progression to diabetes mellitus. J Genet Genomics 2024; 51:75-86. [PMID: 37652264 DOI: 10.1016/j.jgg.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/02/2023]
Abstract
Gut microbiota and circulating metabolite dysbiosis predate important pathological changes in glucose metabolic disorders; however, comprehensive studies on impaired glucose tolerance (IGT), a diabetes mellitus (DM) precursor, are lacking. Here, we perform metagenomic sequencing and metabolomics on 47 pairs of individuals with IGT and newly diagnosed DM and 46 controls with normal glucose tolerance (NGT); patients with IGT are followed up after 4 years for progression to DM. Analysis of baseline data reveals significant differences in gut microbiota and serum metabolites among the IGT, DM, and NGT groups. In addition, 13 types of gut microbiota and 17 types of circulating metabolites showed significant differences at baseline before IGT progressed to DM, including higher levels of Eggerthella unclassified, Coprobacillus unclassified, Clostridium ramosum, L-valine, L-norleucine, and L-isoleucine, and lower levels of Eubacterium eligens, Bacteroides faecis, Lachnospiraceae bacterium 3_1_46FAA, Alistipes senegalensis, Megaspaera elsdenii, Clostridium perfringens, α-linolenic acid, 10E,12Z-octadecadienoic acid, and dodecanoic acid. A random forest model based on differential intestinal microbiota and circulating metabolites can predict the progression from IGT to DM (AUC = 0.87). These results suggest that microbiome and metabolome dysbiosis occur in individuals with IGT and have important predictive values and potential for intervention in preventing IGT from progressing to DM.
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Affiliation(s)
- Boxun Zhang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xuan Zhang
- Faculty of Biological Science and Technology, Baotou Teacher's College, Baotou, Inner Mongolia 014030, China; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhen Luo
- Infinitus (China) Company Ltd, Guangzhou, Guangdong 510405, China
| | - Jixiang Ren
- Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin 130021, China
| | - Xiaotong Yu
- Department of Endocrinology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Haiyan Zhao
- Xinjiekou Community Health Service Center in Xicheng District, Beijing 100035, China
| | - Yitian Wang
- Department of Spleen and Stomach, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong 518033, China
| | - Wenhui Zhang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiwei Tian
- Xinjiekou Community Health Service Center in Xicheng District, Beijing 100035, China
| | - Xiuxiu Wei
- Beijing University of Chinese Medicine, Beijing 100105, China
| | - Qiyou Ding
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Haoyu Yang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Zishan Jin
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China; Beijing University of Chinese Medicine, Beijing 100105, China
| | - Xiaolin Tong
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China; Northeast Asia Institute of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, Jilin 130117, China.
| | - Jun Wang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Linhua Zhao
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
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19
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Zeng Z, Qiu J, Chen Y, Liang D, Wei F, Fu Y, Zhang J, Wei X, Zhang X, Tao J, Lin L, Zheng J. Altered Gut Microbiota as a Potential Risk Factor for Coronary Artery Disease in Diabetes: A Two-Sample Bi-Directional Mendelian Randomization Study. Int J Med Sci 2024; 21:376-395. [PMID: 38169662 PMCID: PMC10758148 DOI: 10.7150/ijms.92131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
The current body of research points to a notable correlation between an imbalance in gut microbiota and the development of type 2 diabetes mellitus (T2D) as well as its consequential ailment, coronary artery disease (CAD). The complexities underlying the association, especially in the context of diabetic coronary artery disease (DCAD), are not yet fully understood, and the causal links require further clarification. In this study, a bidirectional Mendelian randomization (MR) methodology was utilized to explore the causal relationships between gut microbiota, T2D, and CAD. By analyzing data from the DIAGRAM, GERA, UKB, FHS, and mibioGen cohorts and examining GWAS databases, we sought to uncover genetic variants linked to T2D, CAD, and variations in gut microbiota and metabolites, aiming to shed light on the potential mechanisms connecting gut microbiota with DCAD. Our investigation uncovered a marked causal link between the presence of Oxalobacter formigenes and an increased incidence of both T2D and CAD. Specifically, a ten-unit genetic predisposition towards T2D was found to be associated with a 6.1% higher probability of an increase in the Oxalobacteraceae family's presence (β = 0.061, 95% CI = 0.002-0.119). In a parallel finding, an augmented presence of Oxalobacter was related to an 8.2% heightened genetic likelihood of CAD (β = 0.082, 95% CI = 0.026-0.137). This evidence indicates a critical pathway by which T2D can potentially raise the risk of CAD via alterations in gut microbiota. Additionally, our analyses reveal a connection between CAD risk and Methanobacteria, thus providing fresh perspectives on the roles of TMAO and carnitine in the etiology of CAD. The data also suggest a direct causal relationship between increased levels of certain metabolites - proline, lysophosphatidylcholine, asparagine, and salicylurate - and the prevalence of both T2D and CAD. Sensitivity assessments reinforce the notion that changes in Oxalobacter formigenes could pose a risk for DCAD. There is also evidence to suggest that DCAD may, in turn, affect the gut microbiota's makeup. Notably, a surge in serum TMAO levels in individuals with CAD, coinciding with a reduced presence of methanogens, has been identified as a potentially significant factor for future examination.
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Affiliation(s)
- Zhaopei Zeng
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Junxiong Qiu
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yu Chen
- Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Diefei Liang
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Feng Wei
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Cardiothoracic Surgery, Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Shanwei, China
| | - Yuan Fu
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jiarui Zhang
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiexiao Wei
- Department of Cardiology, Chinese PLA General Hospital, Beijing, China
| | - Xinyi Zhang
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jun Tao
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Liling Lin
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Anesthesiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Junmeng Zheng
- Department of Cardiovascular Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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20
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Rondanelli M, Barrile GC, Cavioni A, Donati P, Genovese E, Mansueto F, Mazzola G, Patelli Z, Pirola M, Razza C, Russano S, Sivieri C, Tartara A, Valentini EM, Perna S. A Narrative Review on Strategies for the Reversion of Prediabetes to Normoglycemia: Food Pyramid, Physical Activity, and Self-Monitoring Innovative Glucose Devices. Nutrients 2023; 15:4943. [PMID: 38068801 PMCID: PMC10707766 DOI: 10.3390/nu15234943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/18/2023] Open
Abstract
In 2019, "Nutrition Therapy for Adults with Diabetes or Prediabetes: A Consensus Report" was published. This consensus report, however, did not provide an easy way to illustrate to subjects with prediabetes (SwPs) how to follow a correct dietary approach. The purpose of this review is to evaluate current evidence on optimum dietary treatment of SwPs and to provide a food pyramid for this population. The pyramid built shows that everyday consumption should consist of: whole-grain bread or potatoes eaten with their skins (for fiber and magnesium) and low glycemic index carbohydrates (GI < 55%) (three portions); fruit and vegetables (5 portions), in particular, green leafy vegetables (for fiber, magnesium, and polyphenols); EVO oil (almost 8 g); nuts (30 g, in particular, pistachios and almonds); three portions of dairy products (milk/yogurt: 300-400 g/day); mineral water (almost 1, 5 L/day for calcium intake); one glass of wine (125 mL); and three cups of coffee. Weekly portions should include fish (four portions), white meat (two portions), protein plant-based food (four portions), eggs (egg portions), and red/processed meats (once/week). At the top of the pyramid, there are two pennants: a green one means that SwPs need some personalized supplementation (if daily requirements cannot be satisfied through diet, vitamin D, omega-3, and vitamin B supplements), and a red one means there are some foods and factors that are banned (simple sugar, refined carbohydrates, and a sedentary lifestyle). Three to four times a week of aerobic and resistance exercises must be performed for 30-40 min. Finally, self-monitoring innovative salivary glucose devices could contribute to the reversion of prediabetes to normoglycemia.
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Affiliation(s)
- Mariangela Rondanelli
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Gaetan Claude Barrile
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Alessandro Cavioni
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Paolo Donati
- AICUBE srl, 20090 Trezzano sul Naviglio, Italy; (P.D.); (S.R.)
| | - Elisa Genovese
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Francesca Mansueto
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Giuseppe Mazzola
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Zaira Patelli
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Martina Pirola
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Claudia Razza
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Stefano Russano
- AICUBE srl, 20090 Trezzano sul Naviglio, Italy; (P.D.); (S.R.)
| | - Claudia Sivieri
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Alice Tartara
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Eugenio Marzio Valentini
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (G.C.B.); (A.C.); (E.G.); (F.M.); (G.M.); (Z.P.); (M.P.); (C.R.); (C.S.); (A.T.); (E.M.V.)
| | - Simone Perna
- Department of Food, Environmental and Nutritional Sciences, Division of Human Nutrition, University of Milan, 20133 Milan, Italy;
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Petakh P, Kamyshna I, Kamyshnyi A. Unveiling the potential pleiotropic effects of metformin in treating COVID-19: a comprehensive review. Front Mol Biosci 2023; 10:1260633. [PMID: 37881440 PMCID: PMC10595158 DOI: 10.3389/fmolb.2023.1260633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 09/28/2023] [Indexed: 10/27/2023] Open
Abstract
This review article explores the potential of metformin, a medication commonly used for type 2 diabetes, as an antiviral and anti-inflammatory agent in the context of coronavirus disease 2019 (COVID-19). Metformin has demonstrated inhibitory effects on the growth of SARS-CoV-2 in cell culture models and has shown promising results in reducing viral load and achieving undetectable viral levels in clinical trials. Additionally, metformin exhibits anti-inflammatory properties by reducing the production of pro-inflammatory cytokines and modulating immune cell function, which may help prevent cytokine storms associated with severe COVID-19. The drug's ability to regulate the balance between pro-inflammatory Th17 cells and anti-inflammatory Treg cells suggests its potential in mitigating inflammation and restoring T cell functionality. Furthermore, metformin's modulation of the gut microbiota, particularly changes in bacterial taxa and the production of short-chain fatty acids, may contribute to its therapeutic effects. The interplay between metformin, bile acids, the gut microbiome, glucagon-like peptide-1 secretion, and glycemic control has implications for the management of diabetes and potential interventions in COVID-19. By refreshing the current evidence, this review highlights the potential of metformin as a therapeutic option in the management of COVID-19, while also exploring its effects on the gut microbiome and immunometabolism.
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Affiliation(s)
- Pavlo Petakh
- Department of Biochemistry and Pharmacology, Uzhhorod National University, Uzhhorod, Ukraine
- Department of Microbiology, Virology, and Immunology, I. Horbachevsky Ternopil National Medical University, Ternopil, Ukraine
| | - Iryna Kamyshna
- Department of Medical Rehabilitation, I. Horbachevsky Ternopil National Medical University, Ternopil, Ukraine
| | - Aleksandr Kamyshnyi
- Department of Microbiology, Virology, and Immunology, I. Horbachevsky Ternopil National Medical University, Ternopil, Ukraine
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Huang R, Yao Y, Tong X, Wang L, Qian W, Lu J, Zhang W, Liu Y, Wang S, Xian S, Zhu Y, Huang J, Guo X, Gu M, Lv H, Bi W, Meng C, Chang Z, Zhang J, Xu D, Ji S. Tracing the evolving dynamics and research hotspots of microbiota and immune microenvironment from the past to the new era. Microbiol Spectr 2023; 11:e0013523. [PMID: 37768071 PMCID: PMC10581186 DOI: 10.1128/spectrum.00135-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/31/2023] [Indexed: 09/29/2023] Open
Abstract
Gut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like the inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. This article aims to review the documents in this field and summarize the research hotspots as well as developing processes. Gut microbiota and immune microenvironment-related documents from 1976 to 2022 were obtained from the Web of Science Core Collection database. Bibliometrics was used to assess the core authors and journals, most contributive countries and affiliations together with hotspots in this field and keyword co-occurrence analysis. Data were visualized to help comprehension. Nine hundred and twelve documents about gut microbiota and immune microenvironment were retrieved, and the annual publications increased gradually. The most productive author, country, and affiliation were "Zitvogel L," USA and "UNIV TEXAS MD ANDERSON CANC CTR," respectively. FRONTIERS IN IMMUNOLOGY, CANCERS, and INTERNATIONAL JOURNAL OF MOLECULAR SCIENCE were the periodicals with most publications. Keyword co-occurrence analysis identified three clusters, including gut microbiota, inflammation, and IBD. Combined with the visualized analysis of documents and keyword co-occurrence as well as literature reading, we recognized three key topics of gut microbiota: cancer and therapy; immunity, inflammation and IBD; acute injuries and metabolic diseases. This article revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.IMPORTANCEGut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. While the application of bibliometrics in the field of gut microbiota and immune microenvironment still remains blank, which focused more on the regulation of the gut microbiota on the immune microenvironment of different kinds of diseases. Here, we intended to review and summarize the presented documents in gut microbiota and immune microenvironment field by bibliometrics. And we revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.
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Affiliation(s)
- Runzhi Huang
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Yuntao Yao
- Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xirui Tong
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Lei Wang
- Beijing Genomics Institute (BGI), Shenzhen, China
| | - Weijin Qian
- Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianyu Lu
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Wei Zhang
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Yifan Liu
- Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Siqiao Wang
- Tongji University School of Medicine, Tongji University, Shanghai, China
| | - Shuyuan Xian
- Tongji University School of Medicine, Tongji University, Shanghai, China
| | - Yushu Zhu
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Jie Huang
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Xinya Guo
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Minyi Gu
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Hanlin Lv
- Beijing Genomics Institute (BGI), Shenzhen, China
| | - Wenshuai Bi
- Beijing Genomics Institute (BGI), Shenzhen, China
| | - Chenwei Meng
- Beijing Genomics Institute (BGI), Shenzhen, China
| | - Zhengyan Chang
- Department of Pathology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jie Zhang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Orthopaedic Department of Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Dayuan Xu
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
| | - Shizhao Ji
- Department of Burn Surgery, First Affiliated Hospital of Naval Medical University, and Research Unit of Key Techniques for Treatment of Burns and Combined Burns and Trauma Injury, Chinese Academy of Medical Sciences, Shanghai, China
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Jiang S, Wang T, Zhang KH. Data-driven decision-making for precision diagnosis of digestive diseases. Biomed Eng Online 2023; 22:87. [PMID: 37658345 PMCID: PMC10472739 DOI: 10.1186/s12938-023-01148-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 08/15/2023] [Indexed: 09/03/2023] Open
Abstract
Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.
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Affiliation(s)
- Song Jiang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
| | - Ting Wang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
| | - Kun-He Zhang
- Department of Gastroenterology, The First Affiliated Hospital of Nanchang University, No. 17, Yongwai Zheng Street, Nanchang, 330006 China
- Jiangxi Institute of Gastroenterology and Hepatology, Nanchang, 330006 China
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24
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Li P, Roos S, Luo H, Ji B, Nielsen J. Metabolic engineering of human gut microbiome: Recent developments and future perspectives. Metab Eng 2023; 79:1-13. [PMID: 37364774 DOI: 10.1016/j.ymben.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 06/10/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023]
Abstract
Many studies have demonstrated that the gut microbiota is associated with human health and disease. Manipulation of the gut microbiota, e.g. supplementation of probiotics, has been suggested to be feasible, but subject to limited therapeutic efficacy. To develop efficient microbiota-targeted diagnostic and therapeutic strategies, metabolic engineering has been applied to construct genetically modified probiotics and synthetic microbial consortia. This review mainly discusses commonly adopted strategies for metabolic engineering in the human gut microbiome, including the use of in silico, in vitro, or in vivo approaches for iterative design and construction of engineered probiotics or microbial consortia. Especially, we highlight how genome-scale metabolic models can be applied to advance our understanding of the gut microbiota. Also, we review the recent applications of metabolic engineering in gut microbiome studies as well as discuss important challenges and opportunities.
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Affiliation(s)
- Peishun Li
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE41296, Gothenburg, Sweden
| | - Stefan Roos
- Department of Molecular Sciences, Uppsala BioCenter, Swedish University of Agricultural Sciences, SE75007, Uppsala, Sweden
| | - Hao Luo
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE41296, Gothenburg, Sweden
| | - Boyang Ji
- BioInnovation Institute, Ole Maaløes Vej 3, DK2200, Copenhagen, Denmark
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE41296, Gothenburg, Sweden; BioInnovation Institute, Ole Maaløes Vej 3, DK2200, Copenhagen, Denmark.
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Wu X, Lin D, Li Q, Cai J, Huang H, Xiang T, Tan H. Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study. Aging (Albany NY) 2023; 15:8345-8366. [PMID: 37616057 PMCID: PMC10497006 DOI: 10.18632/aging.204973] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/20/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Previous studies have shown that gut microbiota (GM) and gut microbiota-derived metabolites are associated with gestational diabetes mellitus (GDM). However, the causal associations need to be treated with caution due to confounding factors and reverse causation. METHODS This study obtained genetic variants from genome-wide association study including GM (N = 18,340), GM-derived metabolites (N = 7,824), and GDM (5,687 cases and 117,89 controls). To examine the causal association, several methods were utilized, including inverse variance weighted, maximum likelihood, weighted median, MR-Egger, and MR.RAPS. Additionally, reverse Mendelian Randomization (MR) analysis and multivariable MR were conducted to confirm the causal direction and account for potential confounders, respectively. Furthermore, sensitivity analyses were performed to identify any potential heterogeneity and horizontal pleiotropy. RESULTS Greater abundance of Collinsella was detected to increase the risk of GDM. Our study also found suggestive associations among Coprobacter, Olsenella, Lachnoclostridium, Prevotella9, Ruminococcus2, Oscillibacte, and Methanobrevibacter with GDM. Besides, eight GM-derived metabolites were found to be causally associated with GDM. For the phenylalanine metabolism pathway, phenylacetic acid was found to be related to the risk of GDM. CONCLUSIONS The study first used the MR approach to explore the causal associations among GM, GM-derived metabolites, and GDM. Our findings may contribute to the prevention and treatment strategies for GDM by targeting GM and metabolites, and offer novel insights into the underlying mechanism of the disease.
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Affiliation(s)
- Xinrui Wu
- School of Medicine, Jishou University, Jishou, China
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Dihui Lin
- School of Medicine, Jishou University, Jishou, China
| | - Qi Li
- Xiangxi Center for Disease Control and Prevention, Jishou, China
| | - Jiawang Cai
- School of Medicine, Jishou University, Jishou, China
| | | | - Tianyu Xiang
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Hongzhuan Tan
- Xiangya School of Public Health, Central South University, Changsha, China
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Boopathi S, Priya PS, Haridevamuthu B, Nayak SPRR, Chandrasekar M, Arockiaraj J, Jia AQ. Expanding germ-organ theory: Understanding non-communicable diseases through enterobacterial translocation. Pharmacol Res 2023; 194:106856. [PMID: 37460001 DOI: 10.1016/j.phrs.2023.106856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 07/02/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
Diverse microbial communities colonize different habitats of the human body, including gut, oral cavity, nasal cavity and tissues. These microbial communities are known as human microbiome, plays a vital role in maintaining the health. However, changes in the composition and functions of human microbiome can result in chronic low-grade inflammation, which can damage the epithelial cells and allows pathogens and their toxic metabolites to translocate into other organs such as the liver, heart, and kidneys, causing metabolic inflammation. This dysbiosis of human microbiome has been directly linked to the onset of several non-communicable diseases. Recent metabolomics studies have revealed that pathogens produce several uraemic toxins. These metabolites can serve as inter-kingdom signals, entering the circulatory system and altering host metabolism, thereby aggravating a variety of diseases. Interestingly, Enterobacteriaceae, a critical member of Proteobacteria, has been commonly associated with several non-communicable diseases, and the abundance of this family has been positively correlated with uraemic toxin production. Hence, this review provides a comprehensive overview of Enterobacterial translocation and their metabolites role in non-communicable diseases. This understanding may lead to the identification of novel biomarkers for each metabolic disease as well as the development of novel therapeutic drugs.
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Affiliation(s)
- Seenivasan Boopathi
- Hainan General Hospital, Hainan affiliated hospital of Hainan Medical University, Haikou 570311, China; Toxicology and Pharmacology Laboratory, Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur 603 203, Chengalpattu District, Tamil Nadu, India
| | - P Snega Priya
- Toxicology and Pharmacology Laboratory, Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur 603 203, Chengalpattu District, Tamil Nadu, India
| | - B Haridevamuthu
- Toxicology and Pharmacology Laboratory, Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur 603 203, Chengalpattu District, Tamil Nadu, India
| | - S P Ramya Ranjan Nayak
- Toxicology and Pharmacology Laboratory, Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur 603 203, Chengalpattu District, Tamil Nadu, India
| | - Munisamy Chandrasekar
- Department of Veterinary Clinical Medicine, Madras Veterinary College, Chennai, Tamil Nadu, India
| | - Jesu Arockiaraj
- Toxicology and Pharmacology Laboratory, Department of Biotechnology, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur 603 203, Chengalpattu District, Tamil Nadu, India.
| | - Ai-Qun Jia
- Hainan General Hospital, Hainan affiliated hospital of Hainan Medical University, Haikou 570311, China.
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Ascandari A, Aminu S, Safdi NEH, El Allali A, Daoud R. A bibliometric analysis of the global impact of metaproteomics research. Front Microbiol 2023; 14:1217727. [PMID: 37476667 PMCID: PMC10354264 DOI: 10.3389/fmicb.2023.1217727] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 06/20/2023] [Indexed: 07/22/2023] Open
Abstract
Background Metaproteomics is a subfield in meta-omics that is used to characterize the proteome of a microbial community. Despite its importance and the plethora of publications in different research area, scientists struggle to fully comprehend its functional impact on the study of microbiomes. In this study, bibliometric analyses are used to evaluate the current state of metaproteomic research globally as well as evaluate the specific contribution of Africa to this burgeoning research area. In this study, we use bibliometric analyses to evaluate the current state of metaproteomic research globally, identify research frontiers and hotspots, and further predict future trends in metaproteomics. The specific contribution of Africa to this research area was evaluated. Methods Relevant documents from 2004 to 2022 were extracted from the Scopus database. The documents were subjected to bibliometric analyses and visualization using VOS viewer and Biblioshiny package in R. Factors such as the trends in publication, country and institutional cooperation networks, leading scientific journals, author's productivity, and keywords analyses were conducted. The African publications were ranked using Field-Weighted Citation Impact (FWCI) scores. Results A total of 1,138 documents were included and the number of publications increased drastically from 2004 to 2022 with more publications (170) reported in 2021. In terms of publishers, Frontiers in Microbiology had the highest number of total publications (62). The United States of America (USA), Germany, China, and Canada, together with other European countries were the most productive. Institution-wise, the Helmholtz Zentrum für Umweltforschung, Germany had more publications while Max Plank Institute had the highest total collaborative link strength. Jehmlich N. was the most productive author whereas Hettich RL had the highest h-index of 63. Regarding Africa, only 2.2% of the overall publications were from the continent with more publication outputs from South Africa. More than half of the publications from the continent had an FWCI score ≥ 1. Conclusion The scientific outputs of metaproteomics are rapidly evolving with developed countries leading the way. Although Africa showed prospects for future progress, this could only be accelerated by providing funding, increased collaborations, and mentorship programs.
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Affiliation(s)
- AbdulAziz Ascandari
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
| | - Suleiman Aminu
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
- Department of Biochemistry, Ahmadu Bello University, Zaria, Nigeria
| | - Nour El Houda Safdi
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
| | - Achraf El Allali
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
| | - Rachid Daoud
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
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Houttu N, Benchraka C, Lotankar M, Muhli E, Niinikoski H, Lahti L, Laitinen K. Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum. Acta Diabetol 2023:10.1007/s00592-023-02064-5. [PMID: 37115265 DOI: 10.1007/s00592-023-02064-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/23/2023] [Indexed: 04/29/2023]
Abstract
AIMS Deep metagenomics offers an advanced tool for examining the relationship between gut microbiota composition and function and the onset of disease; in this case, does the composition and function of gut microbiota during pregnancy differ in women who develop prediabetes and those who do not at two-year postpartum, and whether the gut microbiota composition associates with glycemic traits. METHODS In total, 439 women were recruited in early pregnancy. Gut microbiota was assessed by metagenomics analysis in early (13.9 ± 2.0 gestational weeks) and late pregnancy (35.1 ± 1.0 gestational weeks). Prediabetes was determined using American Diabetes Association criteria as fasting plasma glucose 5.6-6.9 mmol/l analyzed by an enzymatic hexokinase method. Of the women, 39 (22.1%) developed prediabetes by two-year postpartum. RESULTS The relative abundances of Escherichia unclassified (FDR < 0.05), Clostridiales bacterium 1_7_ 47FAA (FDR < 0.25) and Parabacteroides (FDR < 0.25) were higher, and those of Ruminococcaceae bacterium D16 (FDR < 0.25), Anaerotruncus unclassified (FDR < 0.25) and Ruminococcaceae noname (FDR < 0.25) were lower in early pregnancy in those women who later developed prediabetes. In late pregnancy, Porphyromonas was higher and Ruminococcus sp 5_1_39BFAA was lower in prediabetes (FDR < 0.25). Furthermore, fasting glucose concentrations associated inversely with Anaerotruncus unclassified in early pregnancy and directly with Ruminococcus sp 5_1_39BFAA in late pregnancy (FDR < 0.25). α-Diversity or β-diversity did not differ significantly between the groups. Predictions of community function during pregnancy were not associated with prediabetes. CONCLUSIONS Our study shows that some bacterial species during pregnancy contributed to the onset of prediabetes within two-year postpartum. These were attributable primarily to a lower abundance of short-chain fatty acids-producing bacteria.
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Affiliation(s)
- Noora Houttu
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland.
| | - Chouaib Benchraka
- Department of Computing, Faculty of Technology, University of Turku, Turku, Finland
| | - Mrunalini Lotankar
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
| | - Ella Muhli
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
- Department of Obstetrics and Gynecology, University of Turku, Turku, Finland
| | - Harri Niinikoski
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
- Department of Pediatrics and Adolescent Medicine, Turku University Hospital, Turku, Finland
| | - Leo Lahti
- Department of Computing, Faculty of Technology, University of Turku, Turku, Finland
| | - Kirsi Laitinen
- Institute of Biomedicine, Research Centre for Integrative Physiology and Pharmacology, University of Turku, Turku, Finland
- Functional Foods Forum, University of Turku, Turku, Finland
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Ren Y, Hao L, Liu J, Wang P, Ding Q, Chen C, Song Y. Alterations in the Gut Microbiota in Pregnant Women with Pregestational Type 2 Diabetes Mellitus. mSystems 2023; 8:e0114622. [PMID: 36853013 PMCID: PMC10134876 DOI: 10.1128/msystems.01146-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 01/17/2023] [Indexed: 03/01/2023] Open
Abstract
Human gut dysbiosis is associated with type 2 diabetes mellitus (T2DM); however, the gut microbiome in pregnant women with pregestational type 2 diabetes mellitus (PGDM) remains unexplored. We investigated the alterations in the gut microbiota composition in pregnant women with or without PGDM. The gut microbiota was examined using 16S rRNA sequencing data of 234 maternal fecal samples that were collected during the first (T1), second (T2), and third (T3) trimesters. The PGDM group presented a reduction in the number of gut bacteria taxonomies as the pregnancies progressed. Linear discriminant analyses revealed that Megamonas, Bacteroides, and Roseburia intestinalis were enriched in the PGDM group, whereas Bacteroides vulgatus, Faecalibacterium prausnitzii, Eubacterium rectale, Bacteroides uniformis, Eubacterium eligens, Subdoligranulum, Bacteroides fragilis, Dialister, Lachnospiraceae, Christensenellaceae R-7, Roseburia inulinivorans, Streptococcus oralis, Prevotella melaninogenica, Neisseria perflava, Bacteroides ovatus, Bacteroides caccae, Veillonella dispar, and Haemophilus parainfluenzae were overrepresented in the control group. Correlation analyses showed that the PGDM-enriched taxa were correlated with higher blood glucose levels during pregnancy, whereas the taxonomic biomarkers of normoglycemic pregnancies exhibited negative correlations with glycemic traits. The microbial networks in the PGDM group comprised weaker microbial interactions than those in the control group. Our study reveals the distinct characteristics of the gut microbiota composition based on gestational ages between normoglycemic and PGDM pregnancies. Further longitudinal research involving women with T2DM at preconception stages and investigations using shotgun metagenomic sequencing should be performed to elucidate the relationships between specific bacterial functions and PGDM metabolic statuses during pregnancy and to identify potential therapeutic targets. IMPORTANCE The incidence of pregestational type 2 diabetes mellitus (PGDM) is increasing, with high rates of serious adverse maternal and neonatal outcomes that are strongly correlated with hyperglycemia. Recent studies have shown that type 2 diabetes mellitus is associated with gut microbial dysbiosis; however, the gut microbiome composition and its associations with the metabolic features of patients with PGDM remain largely unknown. In this study, we investigated the changes in the gut microbiota composition in pregnant women with and without PGDM. We identified differential taxa that may be correlated with maternal metabolic statuses during pregnancy. Additionally, we observed that the number of taxonomic and microbial networks of gut bacteria were distinctly reduced in women with hyperglycemia as their pregnancies progressed. These results extend our understanding of the associations between the gut microbial composition, PGDM-related metabolic changes, and pregnancy outcomes.
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Affiliation(s)
- Yuan Ren
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | | | - Juntao Liu
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Pei Wang
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | | | | | - Yingna Song
- Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
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Ďásková N, Modos I, Krbcová M, Kuzma M, Pelantová H, Hradecký J, Heczková M, Bratová M, Videňská P, Šplíchalová P, Králová M, Heniková M, Potočková J, Ouřadová A, Landberg R, Kühn T, Cahová M, Gojda J. Multi-omics signatures in new-onset diabetes predict metabolic response to dietary inulin: findings from an observational study followed by an interventional trial. Nutr Diabetes 2023; 13:7. [PMID: 37085526 PMCID: PMC10121613 DOI: 10.1038/s41387-023-00235-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 03/22/2023] [Accepted: 04/06/2023] [Indexed: 04/23/2023] Open
Abstract
AIM The metabolic performance of the gut microbiota contributes to the onset of type 2 diabetes. However, targeted dietary interventions are limited by the highly variable inter-individual response. We hypothesized (1) that the composition of the complex gut microbiome and metabolome (MIME) differ across metabolic spectra (lean-obese-diabetes); (2) that specific MIME patterns could explain the differential responses to dietary inulin; and (3) that the response can be predicted based on baseline MIME signature and clinical characteristics. METHOD Forty-nine patients with newly diagnosed pre/diabetes (DM), 66 metabolically healthy overweight/obese (OB), and 32 healthy lean (LH) volunteers were compared in a cross-sectional case-control study integrating clinical variables, dietary intake, gut microbiome, and fecal/serum metabolomes (16 S rRNA sequencing, metabolomics profiling). Subsequently, 27 DM were recruited for a predictive study: 3 months of dietary inulin (10 g/day) intervention. RESULTS MIME composition was different between groups. While the DM and LH groups represented opposite poles of the abundance spectrum, OB was closer to DM. Inulin supplementation was associated with an overall improvement in glycemic indices, though the response was very variable, with a shift in microbiome composition toward a more favorable profile and increased serum butyric and propionic acid concentrations. The improved glycemic outcomes of inulin treatment were dependent on better baseline glycemic status and variables related to the gut microbiota, including the abundance of certain bacterial taxa (i.e., Blautia, Eubacterium halii group, Lachnoclostridium, Ruminiclostridium, Dialister, or Phascolarctobacterium), serum concentrations of branched-chain amino acid derivatives and asparagine, and fecal concentrations of indole and several other volatile organic compounds. CONCLUSION We demonstrated that obesity is a stronger determinant of different MIME patterns than impaired glucose metabolism. The large inter-individual variability in the metabolic effects of dietary inulin was explained by differences in baseline glycemic status and MIME signatures. These could be further validated to personalize nutritional interventions in patients with newly diagnosed diabetes.
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Affiliation(s)
- N Ďásková
- First Faculty of Medicine, Charles University, Prague, Czech Republic
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - I Modos
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - M Krbcová
- Department of Internal Medicine, Kralovske Vinohrady University Hospital and Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - M Kuzma
- Institute of Microbiology of the CAS, Prague, Czech Republic
| | - H Pelantová
- Institute of Microbiology of the CAS, Prague, Czech Republic
| | - J Hradecký
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - M Heczková
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - M Bratová
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - P Videňská
- Mendel University, Department of Chemistry and Biochemistry, Brno, Czech Republic
| | - P Šplíchalová
- RECETOX, Faculty of Science Masaryk University, Brno, Czech Republic
| | - M Králová
- Ambis University, Department of Economics and Management, Prague, Czech Republic
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - M Heniková
- Department of Internal Medicine, Kralovske Vinohrady University Hospital and Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - J Potočková
- Department of Internal Medicine, Kralovske Vinohrady University Hospital and Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - A Ouřadová
- Department of Internal Medicine, Kralovske Vinohrady University Hospital and Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - R Landberg
- Division of Food and Nutrition Science, Department of Biology and Biological Engineering, Chalmers University of Technology, Goteborg, Sweden
| | - T Kühn
- Institute of Global Food Security, Queen's University Belfast, Belfast, UK
- Heidelberg Institute of Global Health (HIGH), Medical Faculty and University Hospital, Heidelberg University, Heidelberg, Germany
| | - M Cahová
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
| | - J Gojda
- Department of Internal Medicine, Kralovske Vinohrady University Hospital and Third Faculty of Medicine, Charles University, Prague, Czech Republic
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Lupu VV, Adam Raileanu A, Mihai CM, Morariu ID, Lupu A, Starcea IM, Frasinariu OE, Mocanu A, Dragan F, Fotea S. The Implication of the Gut Microbiome in Heart Failure. Cells 2023; 12:1158. [PMID: 37190067 PMCID: PMC10136760 DOI: 10.3390/cells12081158] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/05/2023] [Accepted: 04/10/2023] [Indexed: 05/17/2023] Open
Abstract
Heart failure is a worldwide health problem with important consequences for the overall wellbeing of affected individuals as well as for the healthcare system. Over recent decades, numerous pieces of evidence have demonstrated that the associated gut microbiota represent an important component of human physiology and metabolic homeostasis, and can affect one's state of health or disease directly, or through their derived metabolites. The recent advances in human microbiome studies shed light on the relationship between the gut microbiota and the cardiovascular system, revealing its contribution to the development of heart failure-associated dysbiosis. HF has been linked to gut dysbiosis, low bacterial diversity, intestinal overgrowth of potentially pathogenic bacteria and a decrease in short chain fatty acids-producing bacteria. An increased intestinal permeability allowing microbial translocation and the passage of bacterial-derived metabolites into the bloodstream is associated with HF progression. A more insightful understanding of the interactions between the human gut microbiome, HF and the associated risk factors is mandatory for optimizing therapeutic strategies based on microbiota modulation and offering individualized treatment. The purpose of this review is to summarize the available data regarding the influence of gut bacterial communities and their derived metabolites on HF, in order to obtain a better understanding of this multi-layered complex relationship.
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Affiliation(s)
- Vasile Valeriu Lupu
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | - Anca Adam Raileanu
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | | | - Ionela Daniela Morariu
- Faculty of Pharmacy, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ancuta Lupu
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | - Iuliana Magdalena Starcea
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | - Otilia Elena Frasinariu
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | - Adriana Mocanu
- Faculty of General Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania (I.M.S.)
| | - Felicia Dragan
- Faculty of Medicine and Pharmacy, University of Oradea, 410087 Oradea, Romania
| | - Silvia Fotea
- Medical Department, Faculty of Medicine and Pharmacy, “Dunarea de Jos” University of Galati, 800008 Galati, Romania
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Chen S, Xi M, Gao F, Li M, Dong T, Geng Z, Liu C, Huang F, Wang J, Li X, Wei P, Miao F. Evaluation of mulberry leaves’ hypoglycemic properties and hypoglycemic mechanisms. Front Pharmacol 2023; 14:1045309. [PMID: 37089923 PMCID: PMC10117911 DOI: 10.3389/fphar.2023.1045309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 03/31/2023] [Indexed: 04/08/2023] Open
Abstract
The effectiveness of herbal medicine in treating diabetes has grown in recent years, but the precise mechanism by which it does so is still unclear to both medical professionals and diabetics. In traditional Chinese medicine, mulberry leaf is used to treat inflammation, colds, and antiviral illnesses. Mulberry leaves are one of the herbs with many medicinal applications, and as mulberry leaf study grows, there is mounting evidence that these leaves also have potent anti-diabetic properties. The direct role of mulberry leaf as a natural remedy in the treatment of diabetes has been proven in several studies and clinical trials. However, because mulberry leaf is a more potent remedy for diabetes, a deeper understanding of how it works is required. The bioactive compounds flavonoids, alkaloids, polysaccharides, polyphenols, volatile oils, sterols, amino acids, and a variety of inorganic trace elements and vitamins, among others, have been found to be abundant in mulberry leaves. Among these compounds, flavonoids, alkaloids, polysaccharides, and polyphenols have a stronger link to diabetes. Of course, trace minerals and vitamins also contribute to blood sugar regulation. Inhibiting alpha glucosidase activity in the intestine, regulating lipid metabolism in the body, protecting pancreatic -cells, lowering insulin resistance, accelerating glucose uptake by target tissues, and improving oxidative stress levels in the body are some of the main therapeutic properties mentioned above. These mechanisms can effectively regulate blood glucose levels. The therapeutic effects of the bioactive compounds found in mulberry leaves on diabetes mellitus and their associated molecular mechanisms are the main topics of this paper’s overview of the state of the art in mulberry leaf research for the treatment of diabetes mellitus.
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Affiliation(s)
- Sikai Chen
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Miaomiao Xi
- The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
- Xi’an TANK Medicinal Biology Institute, Xi’an, China
| | - Feng Gao
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Min Li
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - TaiWei Dong
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Zhixin Geng
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Chunyu Liu
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Fengyu Huang
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Jing Wang
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Xingyu Li
- Shaanxi University of Chinese Medicine, Xianyang, China
| | - Peifeng Wei
- Shaanxi University of Chinese Medicine, Xianyang, China
- The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
- *Correspondence: Peifeng Wei, ; Feng Miao,
| | - Feng Miao
- The Second Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, China
- *Correspondence: Peifeng Wei, ; Feng Miao,
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Cheng TY, Chang CC, Luo CS, Chen KY, Yeh YK, Zheng JQ, Wu SM. Targeting Lung-Gut Axis for Regulating Pollution Particle-Mediated Inflammation and Metabolic Disorders. Cells 2023; 12:901. [PMID: 36980242 PMCID: PMC10047528 DOI: 10.3390/cells12060901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 03/09/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Cigarette smoking (CS) or ambient particulate matter (PM) exposure is a risk factor for metabolic disorders, such as insulin resistance (IR), increased plasma triglycerides, hyperglycemia, and diabetes mellitus (DM); it can also cause gut microbiota dysbiosis. In smokers with metabolic disorders, CS cessation decreases the risks of serious pulmonary events, inflammation, and metabolic disorder. This review included recent studies examining the mechanisms underlying the effects of CS and PM on gut microbiota dysbiosis and metabolic disorder development; one of the potential mechanisms is the disruption of the lung-gut axis, leading to gut microbiota dysbiosis, intestinal dysfunction, systemic inflammation, and metabolic disease. Short-chain fatty acids (SCFAs) are the primary metabolites of gut bacteria, which are derived from the fermentation of dietary fibers. They activate G-protein-coupled receptor (GPCR) signaling, suppress histone deacetylase (HDAC) activity, and inhibit inflammation, facilitating the maintenance of gut health and biofunction. The aforementioned gut microbiota dysbiosis reduces SCFA levels. Treatment targeting SCFA/GPCR signaling may alleviate air pollution-associated inflammation and metabolic disorders, which involve lung-gut axis disruption.
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Affiliation(s)
- Tzu-Yu Cheng
- Division of Cardiovascular Surgery, Department of Surgery, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan;
- Division of Cardiology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Chih-Cheng Chang
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Ching-Shan Luo
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
- International Ph.D. Program in Cell Therapy and Regenerative Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Kuan-Yuan Chen
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Yun-Kai Yeh
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Jing-Quan Zheng
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
| | - Sheng-Ming Wu
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan; (C.-C.C.); (C.-S.L.); (K.-Y.C.); (Y.-K.Y.); (J.-Q.Z.)
- Division of Pulmonary Medicine, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- TMU Research Center for Thoracic Medicine, Taipei Medical University, Taipei 11031, Taiwan
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Hendricks SA, Vella CA, New DD, Aunjum A, Antush M, Geidl R, Andrews KR, Balemba OB. High-Resolution Taxonomic Characterization Reveals Novel Human Microbial Strains with Potential as Risk Factors and Probiotics for Prediabetes and Type 2 Diabetes. Microorganisms 2023; 11:758. [PMID: 36985331 PMCID: PMC10051885 DOI: 10.3390/microorganisms11030758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 02/27/2023] [Accepted: 03/11/2023] [Indexed: 03/18/2023] Open
Abstract
Alterations in the composition of the gut microbiota is thought to play a key role in causing type 2 diabetes, yet is not fully understood, especially at the strain level. Here, we used long-read DNA sequencing technology of 16S-ITS-23S rRNA genes for high-resolution characterization of gut microbiota in the development of type 2 diabetes. Gut microbiota composition was characterized from fecal DNA from 47 participants divided into 4 cohorts based on glycemic control: normal glycemic control (healthy; n = 21), reversed prediabetes (prediabetes/healthy; n = 8), prediabetes (n = 8), or type 2 diabetes (n = 10). A total of 46 taxa were found to be possibly related to progression from healthy state to type 2 diabetes. Bacteroides coprophilus DSM 18228, Bifidobacterium pseudocatenulatum DSM 20438, and Bifidobacterium adolescentis ATCC 15703 could confer resistance to glucose intolerance. On the other hand, Odoribacter laneus YIT 12061 may be pathogenic as it was found to be more abundant in type 2 diabetes participants than other cohorts. This research increases our understanding of the structural modulation of gut microbiota in the pathogenesis of type 2 diabetes and highlights gut microbiota strains, with the potential for targeted opportunistic pathogen control or consideration for probiotic prophylaxis and treatment.
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Affiliation(s)
- Sarah A. Hendricks
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID 83843, USA
| | - Chantal A. Vella
- Department of Movement Sciences, University of Idaho, Moscow, ID 83843, USA
- WWAMI Medical Education Program, University of Idaho, Moscow, ID 83843, USA
| | - Daniel D. New
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID 83843, USA
| | - Afiya Aunjum
- Department of Movement Sciences, University of Idaho, Moscow, ID 83843, USA
| | - Maximilian Antush
- Department of Movement Sciences, University of Idaho, Moscow, ID 83843, USA
| | - Rayme Geidl
- WWAMI Medical Education Program, University of Idaho, Moscow, ID 83843, USA
| | - Kimberly R. Andrews
- Institute for Interdisciplinary Data Sciences, University of Idaho, Moscow, ID 83843, USA
| | - Onesmo B. Balemba
- WWAMI Medical Education Program, University of Idaho, Moscow, ID 83843, USA
- Department of Biological Sciences, University of Idaho, Moscow, ID 83843, USA
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Adjunctive Probio-X Treatment Enhances the Therapeutic Effect of a Conventional Drug in Managing Type 2 Diabetes Mellitus by Promoting Short-Chain Fatty Acid-Producing Bacteria and Bile Acid Pathways. mSystems 2023; 8:e0130022. [PMID: 36688679 PMCID: PMC9948714 DOI: 10.1128/msystems.01300-22] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Metformin is a common drug for the management of type 2 diabetes mellitus; however, it causes various adverse gastrointestinal effects, especially after prolonged treatment. It is thus of interest to identify an adjuvant treatment that synergizes with the efficacy of metformin while mitigating its adverse effects. Since previous evidence supports that the gut microbiota is a target of metformin, this study investigated the beneficial effect and mechanism of the coadministration of probiotics with metformin in the management of type 2 diabetes mellitus by conducting a 3-month randomized, double-blind, placebo-controlled clinical trial (n = 27 and 21 in the probiotic and placebo groups, respectively, who completed the trial). Clinical results showed that the coadministration of probiotics with metformin significantly reduced glycated hemoglobin compared with metformin taken alone (P < 0.05). Metagenomic and metabolomic analyses showed that the coadministration of probiotics increased the abundance of gut short-chain fatty acid (SCFA)-producing bacteria and bile acids. Significantly or marginally more bile acids and related metabolites were detected in the probiotic group than in the placebo group postintervention. Taken together, the results of our study showed that the coadministration of probiotics with metformin synergized with the hypoglycemic effect in patients with type 2 diabetes mellitus, which was likely through modulating the gut microbiome and, subsequently, SCFA and bile acid metabolism. Our findings support that cotreatment with probiotics and metformin is beneficial to patients with type 2 diabetes mellitus. IMPORTANCE Metformin causes variable adverse gastrointestinal effects, especially after prolonged treatment. We found that cotreatment with Probio-X and metformin for the management of type 2 diabetes mellitus may promote gut SCFA-producing bacteria and the levels of specific bile acids, thus increasing the secretion of related gastrointestinal hormones and ultimately improving glucose homeostasis.
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Abstract
Studies of the human microbiome share both technical and conceptual similarities with genome-wide association studies and genetic epidemiology. However, the microbiome has many features that differ from genomes, such as its temporal and spatial variability, highly distinct genetic architecture and person-to-person variation. Moreover, there are various potential mechanisms by which distinct aspects of the human microbiome can relate to health outcomes. Recent advances, including next-generation sequencing and the proliferation of multi-omic data types, have enabled the exploration of the mechanisms that connect microbial communities to human health. Here, we review the ways in which features of the microbiome at various body sites can influence health outcomes, and we describe emerging opportunities and future directions for advanced microbiome epidemiology.
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Li Y, Chen Y, Fan Y, Chen Y, Chen Y. Dynamic network modeling of gut microbiota during Alzheimer's disease progression in mice. Gut Microbes 2023; 15:2172672. [PMID: 36724123 PMCID: PMC9897752 DOI: 10.1080/19490976.2023.2172672] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
The intimate association between the gut microbiota (GM) and the central nervous system points to potential intervention strategies for neurological diseases. Nevertheless, there is currently no theoretical framework for selecting the window period and target bacteria for GM interventions owing to the complexity of the gut microecosystem. In this study, we constructed a complex network-based modeling approach to evaluate the topological features of the GM and infer the window period and bacterial candidates for GM interventions. We used Alzheimer's disease (AD) as an example and traced the GM dynamic changes in AD and wild-type mice at one, two, three, six, and nine months of age. The results revealed alterations of the topological features of the GM from a scale-free network into a random network during AD progression, indicating severe GM disequilibrium at the late stage of AD. Through stability and vulnerability assessments of the GM networks, we identified the third month after birth as the optimal window period for GM interventions in AD mice. Further computational simulations and robustness evaluations determined that the hub bacteria were potential candidates for GM interventions. Moreover, our GM functional analysis suggested that Lachnospiraceae UCG-001 - the hub and enriched bacterium in AD mice - was the keystone bacterium for GM interventions owing to its contributions to quinolinic acid synthesis. In conclusion, this study established a complex network-based modeling approach as a practical strategy for disease interventions from the perspective of the gut microecosystem.
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Affiliation(s)
- Yinhu Li
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science–Shenzhen Fundamental Research Institutions, Shenzhen, China,Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, China
| | - Yijing Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science–Shenzhen Fundamental Research Institutions, Shenzhen, China,Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, China
| | - Yingying Fan
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science–Shenzhen Fundamental Research Institutions, Shenzhen, China,Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, China
| | - Yuewen Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science–Shenzhen Fundamental Research Institutions, Shenzhen, China,Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, China
| | - Yu Chen
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen–Hong Kong Institute of Brain Science–Shenzhen Fundamental Research Institutions, Shenzhen, China,Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen, China,CONTACT Yu Chen Chinese Academy of Sciences, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Shenzhen, China
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Li P, Luo H, Ji B, Nielsen J. Machine learning for data integration in human gut microbiome. Microb Cell Fact 2022; 21:241. [PMID: 36419034 PMCID: PMC9685977 DOI: 10.1186/s12934-022-01973-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 11/15/2022] [Indexed: 11/25/2022] Open
Abstract
Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.
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Affiliation(s)
- Peishun Li
- grid.5371.00000 0001 0775 6028Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Hao Luo
- grid.5371.00000 0001 0775 6028Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Boyang Ji
- grid.5371.00000 0001 0775 6028Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden ,grid.510909.4BioInnovation Institute, Ole Maaløes Vej 3, DK2200 Copenhagen, Denmark
| | - Jens Nielsen
- grid.5371.00000 0001 0775 6028Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden ,grid.510909.4BioInnovation Institute, Ole Maaløes Vej 3, DK2200 Copenhagen, Denmark
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Dong Y, Wang P, Yang X, Chen M, Li J. Potential of gut microbiota for lipopolysaccharide biosynthesis in European women with type 2 diabetes based on metagenome. Front Cell Dev Biol 2022; 10:1027413. [PMID: 36303603 PMCID: PMC9592851 DOI: 10.3389/fcell.2022.1027413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 09/27/2022] [Indexed: 11/16/2022] Open
Abstract
The abnormal accumulation of lipopolysaccharide (LPS) plays a crucial role in promoting type 2 diabetes (T2D). However, the capability of the gut microbiota to produce LPS in patients with T2D is still unclear, and evidence characterizing the patterns of gut microbiota with LPS productivity remains rare. This study aimed to uncover the profiles of LPS-biosynthesis-related enzymes and pathways, and explore the potential of LPS-producing gut microbiota in T2D. The gut metagenomic sequencing data from a European female cohort with normal glucose tolerance or untreated T2D were analyzed in this study. The sequence search revealed that the relative abundance of the critical enzymes responsible for LPS biosynthesis was significantly high in patients with T2D, especially for N-acetylglucosamine deacetylase, 3-deoxy-D-manno-octulosonic-acid transferase, and lauroyl-Kdo2-lipid IVA myristoyltransferase. The functional analysis indicated that a majority of pathways involved in LPS biosynthesis were augmented in patients with T2D. A total of 1,173 species from 335 genera containing the gene sequences of LPS enzymes, including LpxA/B/C/D/H/K/L/M and/or WaaA, coexisted in controls and patients with T2D. Critical taxonomies with discriminative fecal abundance between groups were revealed, which exhibited different associations with enzymes. Moreover, the identified gut microbial markers had correlations with LPS enzymes and were subsequently associated with microbial pathways. The present findings delineated the potential capability of gut microbiota toward LPS biosynthesis in European women and highlighted a gut microbiota−based mechanistic link between the disturbance in LPS biosynthesis and T2D. The restoration of LPS levels through gut microbiota manipulation might offer potential approaches for preventing and treating T2D.
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40
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Wang L, Wang S, Zhang Q, He C, Fu C, Wei Q. The role of the gut microbiota in health and cardiovascular diseases. MOLECULAR BIOMEDICINE 2022; 3:30. [PMID: 36219347 PMCID: PMC9554112 DOI: 10.1186/s43556-022-00091-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/05/2022] [Indexed: 11/17/2022] Open
Abstract
The gut microbiota is critical to human health, such as digesting nutrients, forming the intestinal epithelial barrier, regulating immune function, producing vitamins and hormones, and producing metabolites to interact with the host. Meanwhile, increasing evidence indicates that the gut microbiota has a strong correlation with the occurrence, progression and treatment of cardiovascular diseases (CVDs). In patients with CVDs and corresponding risk factors, the composition and ratio of gut microbiota have significant differences compared with their healthy counterparts. Therefore, gut microbiota dysbiosis, gut microbiota-generated metabolites, and the related signaling pathway may serve as explanations for some of the mechanisms about the occurrence and development of CVDs. Several studies have also demonstrated that many traditional and latest therapeutic treatments of CVDs are associated with the gut microbiota and its generated metabolites and related signaling pathways. Given that information, we summarized the latest advances in the current research regarding the effect of gut microbiota on health, the main cardiovascular risk factors, and CVDs, highlighted the roles and mechanisms of several metabolites, and introduced corresponding promising treatments for CVDs regarding the gut microbiota. Therefore, this review mainly focuses on exploring the role of gut microbiota related metabolites and their therapeutic potential in CVDs, which may eventually provide better solutions in the development of therapeutic treatment as well as the prevention of CVDs.
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Affiliation(s)
- Lu Wang
- grid.412901.f0000 0004 1770 1022Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, People’s Republic of China
| | - Shiqi Wang
- grid.412901.f0000 0004 1770 1022Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, People’s Republic of China
| | - Qing Zhang
- grid.412901.f0000 0004 1770 1022Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, People’s Republic of China
| | - Chengqi He
- grid.412901.f0000 0004 1770 1022Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, People’s Republic of China
| | - Chenying Fu
- grid.412901.f0000 0004 1770 1022National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,grid.412901.f0000 0004 1770 1022Aging and Geriatric Mechanism Laboratory, West China Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Quan Wei
- grid.412901.f0000 0004 1770 1022Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, People’s Republic of China ,Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, People’s Republic of China
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41
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Zhang X, Ren H, Zhao C, Shi Z, Qiu L, Yang F, Zhou X, Han X, Wu K, Zhong H, Li Y, Li J, Ji L. Metagenomic analysis reveals crosstalk between gut microbiota and glucose-lowering drugs targeting the gastrointestinal tract in Chinese patients with type 2 diabetes: a 6 month, two-arm randomised trial. Diabetologia 2022; 65:1613-1626. [PMID: 35930018 PMCID: PMC9477956 DOI: 10.1007/s00125-022-05768-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022]
Abstract
AIMS/HYPOTHESIS The use of oral glucose-lowering drugs, particularly those designed to target the gut ecosystem, is often observed in association with altered gut microbial composition or functional capacity in individuals with type 2 diabetes. The gut microbiota, in turn, plays crucial roles in the modulation of drug efficacy. We aimed to assess the impacts of acarbose and vildagliptin on human gut microbiota and the relationships between pre-treatment gut microbiota and therapeutic responses. METHODS This was a randomised, open-labelled, two-arm trial in treatment-naive type 2 diabetes patients conducted in Beijing between December 2016 and December 2017. One hundred participants with overweight/obesity and newly diagnosed type 2 diabetes were recruited from the Pinggu Hospital and randomly assigned to the acarbose (n=50) or vildagliptin (n=50) group using sealed envelopes. The treatment period was 6 months. Blood, faecal samples and visceral fat data from computed tomography images were collected before and after treatments to measure therapeutic outcomes and gut microbiota. Metagenomic datasets from a previous type 2 diabetes cohort receiving acarbose or glipizide for 3 months were downloaded and processed. Statistical analyses were applied to identify the treatment-related changes in clinical variables, gut microbiota and associations. RESULTS Ninety-two participants were analysed. After 6 months of acarbose (n=44) or vildagliptin (n=48) monotherapy, both groups achieved significant reductions in HbA1c (from 60 to 46 mmol/mol [from 7.65% to 6.40%] in the acarbose group and from 59 to 44 mmol/mol [from 7.55% to 6.20%] in the vildagliptin group) and visceral fat areas (all adjusted p values for pre-post comparisons <0.05). Both arms showed drug-specific and shared changes in relative abundances of multiple gut microbial species and pathways, especially the common reductions in Bacteroidetes species. Three months and 6 months of acarbose-induced changes in microbial composition were highly similar in type 2 diabetes patients from the two independent studies. Vildagliptin treatment significantly enhanced fasting active glucagon-like peptide-1 (GLP-1) levels. Baseline gut microbiota, rather than baseline GLP-1 levels, were strongly associated with GLP-1 response to vildagliptin, and to a lesser extent with GLP-1 response to acarbose. CONCLUSIONS/INTERPRETATION This study reveals common microbial responses in type 2 diabetes patients treated with two glucose-lowering drugs targeting the gut differently and acceptable performance of baseline gut microbiota in classifying individuals with different GLP-1 responses to vildagliptin. Our findings highlight bidirectional interactions between gut microbiota and glucose-lowering drugs. TRIAL REGISTRATION ClinicalTrials.gov NCT02999841 FUNDING: National Key Research and Development Project: 2016YFC1304901.
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Affiliation(s)
- Xiuying Zhang
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, China
| | - Huahui Ren
- BGI-Shenzhen, Shenzhen, China
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Cuiling Zhao
- Department of Endocrinology, Beijing Friendship Hospital Pinggu Campus, Capital Medical University, Beijing, China
| | | | - Li Qiu
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, China
| | | | - Xianghai Zhou
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, China
| | - Xueyao Han
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, China
| | - Kui Wu
- BGI-Shenzhen, Shenzhen, China
- Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI-Shenzhen, Shenzhen, China
| | | | - Yufeng Li
- Department of Endocrinology, Beijing Friendship Hospital Pinggu Campus, Capital Medical University, Beijing, China.
| | - Junhua Li
- BGI-Shenzhen, Shenzhen, China.
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China.
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Peking University Diabetes Centre, Beijing, China.
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Palmnäs-Bédard MSA, Costabile G, Vetrani C, Åberg S, Hjalmarsson Y, Dicksved J, Riccardi G, Landberg R. The human gut microbiota and glucose metabolism: a scoping review of key bacteria and the potential role of SCFAs. Am J Clin Nutr 2022; 116:862-874. [PMID: 36026526 PMCID: PMC9535511 DOI: 10.1093/ajcn/nqac217] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/16/2022] [Indexed: 01/26/2023] Open
Abstract
The gut microbiota plays a fundamental role in human nutrition and metabolism and may have direct implications for type 2 diabetes and associated preconditions. An improved understanding of relations between human gut microbiota and glucose metabolism could lead to novel opportunities for type 2 diabetes prevention, but human observational studies reporting on such findings have not been extensively reviewed. Here, we review the literature on associations between gut microbiota and markers and stages of glucose dysregulation and insulin resistance in healthy adults and in adults with metabolic disease and risk factors. We present the current evidence for identified key bacteria and their potential roles in glucose metabolism independent of overweight, obesity, and metabolic drugs. We provide support for SCFAs mediating such effects and discuss the role of diet, as well as metabolites derived from diet and gut microbiota interactions. From 5983 initially identified PubMed records, 45 original studies were eligible and reviewed. α Diversity and 45 bacterial taxa were associated with selected outcomes. Six taxa were most frequently associated with glucose metabolism: Akkermansia muciniphila, Bifidobacterium longum, Clostridium leptum group, Faecalibacterium prausnitzii, and Faecalibacterium (inversely associated) and Dorea (directly associated). For Dorea and A. muciniphila, associations were independent of metabolic drugs and body measures. For A. muciniphila and F. prausnitzii, limited evidence supported SCFA mediation of potential effects on glucose metabolism. We conclude that observational studies applying metagenomics sequencing to identify species-level relations are warranted, as are studies accounting for confounding factors and investigating SCFA and postprandial glucose metabolism. Such advances in the field will, together with mechanistic and prospective studies and investigations into diet-gut microbiota interactions, have the potential to bring critical insight into roles of gut microbiota and microbial metabolites in human glucose metabolism and to contribute toward the development of novel prevention strategies for type 2 diabetes, including precision nutrition.
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Affiliation(s)
| | - Giuseppina Costabile
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy,Task Force on Microbiome Studies, University of Naples Federico II, Naples, Italy
| | - Claudia Vetrani
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Sebastian Åberg
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Yommine Hjalmarsson
- Department of Communication and Learning in Science, Chalmers University of Technology, Gothenburg, Sweden
| | - Johan Dicksved
- Department of Animal Nutrition and Management, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Gabriele Riccardi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy,Task Force on Microbiome Studies, University of Naples Federico II, Naples, Italy
| | - Rikard Landberg
- Department of Biology and Biological Engineering, Division of Food and Nutrition Science, Chalmers University of Technology, Gothenburg, Sweden,Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
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Luo H, Li M, Wang F, Yang Y, Wang Q, Zhao Y, Du F, Chen Y, Shen J, Zhao Q, Zeng J, Wang S, Chen M, Li X, Li W, Sun Y, Gu L, Wen Q, Xiao Z, Wu X. The role of intestinal stem cell within gut homeostasis: Focusing on its interplay with gut microbiota and the regulating pathways. Int J Biol Sci 2022; 18:5185-5206. [PMID: 35982910 PMCID: PMC9379405 DOI: 10.7150/ijbs.72600] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/29/2022] [Indexed: 12/05/2022] Open
Abstract
Intestinal stem cells (ISCs) play an important role in maintaining intestinal homeostasis via promoting a healthy gut barrier. Within the stem cell niche, gut microbiota linking the crosstalk of dietary influence and host response has been identified as a key regulator of ISCs. Emerging insights from recent research reveal that ISC and gut microbiota interplay regulates epithelial self-renewal. This article reviews the recent knowledge on the key role of ISC in their local environment (stem cell niche) associating with gut microbiota and their metabolites as well as the signaling pathways. The current progress of intestinal organoid culture is further summarized. Subsequently, the key challenges and future directions are discussed.
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Affiliation(s)
- Haoming Luo
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Mingxing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Fang Wang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Yifei Yang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Qin Wang
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Yueshui Zhao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China.,South Sichuan Institute of Translational Medicine, Luzhou 646000, Sichuan, China
| | - Fukuan Du
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China.,South Sichuan Institute of Translational Medicine, Luzhou 646000, Sichuan, China
| | - Yu Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China.,South Sichuan Institute of Translational Medicine, Luzhou 646000, Sichuan, China
| | - Jing Shen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China.,South Sichuan Institute of Translational Medicine, Luzhou 646000, Sichuan, China
| | - Qianyun Zhao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Jiuping Zeng
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,Cell Therapy & Cell Drugs of Luzhou Key Laboratory, Luzhou 646000, Sichuan, China
| | - Shengpeng Wang
- State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macao, China
| | - Meijuan Chen
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Xiaobing Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Wanping Li
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Yuhong Sun
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Li Gu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Qinglian Wen
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Zhangang Xiao
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.,Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Xu Wu
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou 646000, Sichuan, China.,State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macao, China
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Letchumanan G, Abdullah N, Marlini M, Baharom N, Lawley B, Omar MR, Mohideen FBS, Addnan FH, Nur Fariha MM, Ismail Z, Pathmanathan SG. Gut Microbiota Composition in Prediabetes and Newly Diagnosed Type 2 Diabetes: A Systematic Review of Observational Studies. Front Cell Infect Microbiol 2022; 12:943427. [PMID: 36046745 PMCID: PMC9422273 DOI: 10.3389/fcimb.2022.943427] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Evidence of gut microbiota involvement in regulating glucose metabolism and type 2 diabetes mellitus (T2DM) progression is accumulating. The understanding of microbial dysbiosis and specific alterations of gut microbiota composition that occur during the early stages of glucose intolerance, unperturbed by anti-diabetic medications, is especially essential. Hence, this systematic review was conducted to summarise the existing evidence related to microbiota composition and diversity in individuals with prediabetes (preDM) and individuals newly diagnosed with T2DM (newDM) in comparison to individuals with normal glucose tolerance (nonDM). A systematic search of the PubMed, MEDLINE and CINAHL databases were conducted from inception to February 2021 supplemented with manual searches of the list of references. The primary keywords of “type 2 diabetes”, “prediabetes”, “newly-diagnosed” and “gut microbiota” were used. Observational studies that conducted analysis of the gut microbiota of respondents with preDM and newDM were included. The quality of the studies was assessed using the modified Newcastle-Ottawa scale by independent reviewers. A total of 18 studies (5,489 participants) were included. Low gut microbial diversity was generally observed in preDM and newDM when compared to nonDM. Differences in gut microbiota composition between the disease groups and nonDM were inconsistent across the included studies. Four out of the 18 studies found increased abundance of phylum Firmicutes along with decreased abundance of Bacteroidetes in newDM. At the genus/species levels, decreased abundance of Faecalibacterium prausnitzii, Roseburia, Dialister, Flavonifractor, Alistipes, Haemophilus and Akkermansia muciniphila and increased abundance of Lactobacillus, Streptococcus, Escherichia, Veillonella and Collinsella were observed in the disease groups in at least two studies. Lactobacillus was also found to positively correlate with fasting plasma glucose (FPG), HbA1c and/or homeostatic assessment of insulin resistance (HOMA-IR) in four studies. This renders a need for further investigations on the species/strain-specific role of endogenously present Lactobacillus in glucose regulation mechanism and T2DM disease progression. Differences in dietary intake caused significant variation in specific bacterial abundances. More studies are needed to establish more consistent associations, between clinical biomarkers or dietary intake and specific gut bacterial composition in prediabetes and early T2DM.
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Affiliation(s)
- Geetha Letchumanan
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Natasya Abdullah
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Muhamad Marlini
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Nizam Baharom
- Public Health Unit, Department of Primary Health Care, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Blair Lawley
- Department of Microbiology and Immunology, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Mohd Rahman Omar
- Medical-based Department, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Fathima Begum Syed Mohideen
- Family Medicine Unit, Department of Primary Health Care, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Faizul Helmi Addnan
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Mohd Manzor Nur Fariha
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Zarini Ismail
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
| | - Siva Gowri Pathmanathan
- Department of Medical Sciences, Faculty of Medicine & Health Sciences, Universiti Sains Islam Malaysia (USIM), Negeri Sembilan, Malaysia
- *Correspondence: Siva Gowri Pathmanathan,
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45
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Sugino KY, Hernandez TL, Barbour LA, Kofonow JM, Frank DN, Friedman JE. A maternal higher-complex carbohydrate diet increases bifidobacteria and alters early life acquisition of the infant microbiome in women with gestational diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:921464. [PMID: 35966074 PMCID: PMC9366142 DOI: 10.3389/fendo.2022.921464] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is associated with considerable imbalances in intestinal microbiota that may underlie pathological conditions in both mothers and infants. To more definitively identify these alterations, we evaluated the maternal and infant gut microbiota through the shotgun metagenomic analysis of a subset of stool specimens collected from a randomized, controlled trial in diet-controlled women with GDM. The women were fed either a CHOICE diet (60% complex carbohydrate/25% fat/15% protein, n=18) or a conventional diet (CONV, 40% complex carbohydrate/45% fat/15% protein, n=16) from 30 weeks' gestation through delivery. In contrast to other published studies, we designed the study to minimize the influence of other dietary sources by providing all meals, which were eucaloric and similar in fiber content. At 30 and 37 weeks' gestation, we collected maternal stool samples; performed the fasting measurements of glucose, glycerol, insulin, free fatty acids, and triglycerides; and administered an oral glucose tolerance test (OGTT) to measure glucose clearance and insulin response. Infant stool samples were collected at 2 weeks, 2 months, and 4-5 months of age. Maternal glucose was controlled to conventional targets in both diets, with no differences in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). No differences in maternal alpha or beta diversity between the two diets from baseline to 37 weeks' gestation were observed. However, women on CHOICE diet had higher levels of Bifidobacteriaceae, specifically Bifidobacterium adolescentis, compared with women on CONV. Species-level taxa varied significantly with fasting glycerol, fasting glucose, and glucose AUC after the OGTT challenge. Maternal diet significantly impacted the patterns of infant colonization over the first 4 months of life, with CHOICE infants showing increased microbiome alpha diversity (richness), greater Clostridiaceae, and decreased Enterococcaceae over time. Overall, these results suggest that an isocaloric GDM diet containing greater complex carbohydrates with reduced fat leads to an ostensibly beneficial effect on the maternal microbiome, improved infant gut microbiome diversity, and reduced opportunistic pathogens capable of playing a role in obesity and immune system development. These results highlight the critical role a maternal diet has in shaping the maternal and infant microbiome in women with GDM.
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Affiliation(s)
- Kameron Y. Sugino
- Harold Hamm Diabetes Center, The University of Oklahoma Health Science Center, Oklahoma City, OK, United States
| | - Teri L. Hernandez
- Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
- College of Nursing, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
| | - Linda A. Barbour
- Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
- Department of Obstetrics and Gynecology, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
| | - Jennifer M. Kofonow
- Department of Medicine, Division of Infectious Diseases, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
| | - Daniel N. Frank
- Department of Medicine, Division of Infectious Diseases, The University of Colorado Anschutz Medical Center, Aurora, CO, United States
| | - Jacob E. Friedman
- Harold Hamm Diabetes Center, The University of Oklahoma Health Science Center, Oklahoma City, OK, United States
- Department of Pathology, The University of Oklahoma Health Science Center, Oklahoma City, OK, United States
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Milton-Laskibar I, Cuevas-Sierra A, Portillo MP, Martínez JA. Effects of Resveratrol Administration in Liver Injury Prevention as Induced by an Obesogenic Diet: Role of Ruminococcaceae. Biomedicines 2022; 10:biomedicines10081797. [PMID: 35892696 PMCID: PMC9330856 DOI: 10.3390/biomedicines10081797] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/22/2022] [Accepted: 07/23/2022] [Indexed: 12/14/2022] Open
Abstract
Gut microbiota dysbiosis has been described in several metabolic disruptions, such as non-alcoholic fatty liver disease (NAFLD). Administration of resveratrol has been claimed to elicit benefits against NAFLD along with modulating gut microbiota composition. This investigation aims to study the putative mediating role of gut microbiota in the potential hepato-protective effects of resveratrol in a diet-induced NAFLD rat model. The involvement of bacteria from the Ruminococcaceae family in such effects was also addressed. Resveratrol administration resulted in lowered liver weight and serum total and non-HDL cholesterol concentrations, as well as in increased serum HDL cholesterol levels. The administration of this polyphenol also prevented obesogenic diet-induced serum transaminase increases. In addition, histopathological analysis revealed that resveratrol administration ameliorated the dietary-induced liver steatosis and hepatic inflammation. Gut microbiota sequencing showed an inverse relationship between some bacteria from the Ruminococcaceae family and the screened hepatic markers, whereas in other cases the opposite relationship was also found. Interestingly, an interaction was found between UBA-1819 abundance and resveratrol induced liver weight decrease, suggesting that for this marker resveratrol induced effects were greater when the abundance of this bacteria was high, while no actions were found when UBA-1819 abundance was low.
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Affiliation(s)
- Iñaki Milton-Laskibar
- Precision Nutrition and Cardiometabolic Health, IMDEA-Food Institute (Madrid Institute for Advanced Studies), Campus of International Excellence (CEI) UAM+CSIC, Spanish National Research Council, 28049 Madrid, Spain; (I.M.-L.); (A.C.-S.); (J.A.M.)
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28222 Madrid, Spain
- BIOARABA Institute of Health, 01006 Vitoria-Gasteiz, Spain
| | - Amanda Cuevas-Sierra
- Precision Nutrition and Cardiometabolic Health, IMDEA-Food Institute (Madrid Institute for Advanced Studies), Campus of International Excellence (CEI) UAM+CSIC, Spanish National Research Council, 28049 Madrid, Spain; (I.M.-L.); (A.C.-S.); (J.A.M.)
| | - María P. Portillo
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28222 Madrid, Spain
- BIOARABA Institute of Health, 01006 Vitoria-Gasteiz, Spain
- Nutrition and Obesity Group, Department of Pharmacy and Food Sciences, Faculty of Pharmacy and LuciLascaray Research Center, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gasteiz, Spain
- Correspondence: ; Tel.: +34-945-01-30-67
| | - J. Alfredo Martínez
- Precision Nutrition and Cardiometabolic Health, IMDEA-Food Institute (Madrid Institute for Advanced Studies), Campus of International Excellence (CEI) UAM+CSIC, Spanish National Research Council, 28049 Madrid, Spain; (I.M.-L.); (A.C.-S.); (J.A.M.)
- CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28222 Madrid, Spain
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Wang J, Liu Z, Xu Y, Wang Y, Wang F, Zhang Q, Ni C, Zhen Y, Xu R, Liu Q, Fang W, Huang P, Liu X. Enterobacterial LPS-inducible LINC00152 is regulated by histone lactylation and promotes cancer cells invasion and migration. Front Cell Infect Microbiol 2022; 12:913815. [PMID: 35959377 PMCID: PMC9359126 DOI: 10.3389/fcimb.2022.913815] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/30/2022] [Indexed: 11/26/2022] Open
Abstract
Gut microbes participate in pathogenesis by interacting with the host genome through epigenetic mechanisms, such as long non-coding RNAs. However, the mechanisms by which the microbiota induce expression alteration of long non-coding RNAs remains unclear. Here, we quantified the transcriptome alteration of human colon cell lines after being infected by a common enteric pathogen Salmonella typhimurium SL1344. We observed a widespread lncRNAs expression alteration. Among them, the elevated expression of LINC00152 was verified and proved to be induced by enteric bacteria-derived lipopolysaccharide (LPS). The inducible LINC00152 were found to inhibit Salmonella invasion and inflammation response. LINC00152 was overexpressed in tumors of the clinical CRC samples compared with adjacent normal tissues. Accordingly, we also demonstrated that overexpression of LINC00152 promoted the migration and invasion of colorectal cancer cells. Consistently, we observed an increased abundance of gram-negative bacteria and LPS in tumors tissue. Taken together, the above data implicated that enriched gram-negative bacteria in tumor tissue might promote tumor growth through modulating the expression of LINC00152. Furthermore, we demonstrated that LPS upregulated the expression of LINC00152 by introducing histone lactylation on its promoter and decreasing the binding efficiency of the repressor, YY1, to it. Our results provide new insights into how enterobacteria affect host epigenetics in human disease.
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Affiliation(s)
- Jianwei Wang
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
- Institute of Pediatric Research, Children’s Hospital of Soochow University, Suzhou, China
| | - Zhi Liu
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Yuyu Xu
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Yipeng Wang
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Fei Wang
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
| | - Qingqing Zhang
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Chunhua Ni
- Department of Surgery , the Third Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Yi Zhen
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Rui Xu
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Qisha Liu
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
| | - Weijia Fang
- Cancer Biotherapy Center, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Ping Huang
- Department of Surgery , the Third Affiliated Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Xingyin Liu, ; Ping Huang,
| | - Xingyin Liu
- Department of Pathogen Biology-Microbiology Division, Globe of health center, Nanjing Medical University, Nanjing, China
- Key Laboratory of Pathogen of Jiangsu Province and Key Laboratory of Human Functional Genomics of Jiangsu Province, Nanjing Medical University, Nanjing, China
- Key Laboratory of Holistic Integrative Enterology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Xingyin Liu, ; Ping Huang,
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Wang L, Li F, Gu B, Qu P, Liu Q, Wang J, Tang J, Cai S, Zhao Q, Ming Z. Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis. Front Microbiol 2022; 13:883734. [PMID: 35783436 PMCID: PMC9247514 DOI: 10.3389/fmicb.2022.883734] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.
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Affiliation(s)
- Liang Wang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Fen Li
- Department of Laboratory Medicine, Huaiyin Hospital, Huai’an, China
| | - Bin Gu
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Pengfei Qu
- The First School of Clinical Medicine, Xuzhou Medical University, Xuzhou, China
| | - Qinghua Liu
- State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, Macao SAR, China
| | - Junjiao Wang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Jiawei Tang
- Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Shubin Cai
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
| | - Qi Zhao
- School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, China
- *Correspondence: Qi Zhao,
| | - Zhong Ming
- College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
- Zhong Ming,
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Zhang X, Zhao A, Sandhu AK, Edirisinghe I, Burton-Freeman BM. Red Raspberry and Fructo-Oligosaccharide Supplementation, Metabolic Biomarkers, and the Gut Microbiota in Adults with Prediabetes: A Randomized Crossover Clinical Trial. J Nutr 2022; 152:1438-1449. [PMID: 35421233 DOI: 10.1093/jn/nxac037] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 09/02/2021] [Accepted: 02/14/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Evidence suggests that the gut microbiota and cardiometabolic status are associated, suggesting dietary interventions that alter the microbiota may affect metabolic health. OBJECTIVES We investigated whether supplementation with (poly)phenol-dense red raspberries (RRB), alone or with a fructo-oligosaccharide (FOS) prebiotic, would improve biomarkers of cardiometabolic risk in individuals with prediabetes (PreDM) and insulin resistance (IR) and whether the effects are related to modulation of the gut microbiota. METHODS Adults with PreDM-IR (n = 26; mean ± SEM age, 35 ± 2 years; fasting glucose, 5.7 ± 0.1 mmol/L; HOMA-IR, 3.3 ± 0.3) or who were metabolically healthy (reference group; n = 10; age, 31 ± 3 years; fasting glucose, 5.1 ± 0.2 mmol/L; HOMA-IR, 1.1 ± 0.1) participated in a randomized crossover trial with two 4-week supplementation periods, in which they consumed either RRB (125 g fresh equivalents) daily or RRB + 8g FOS daily, separated by a 4-week washout. The primary outcome variable was the change in the gut microbiota composition, assessed by shotgun sequencing before (baseline) and at the end of each supplementation period. Secondary outcomes were changes in glucoregulation, lipid metabolism, anti-inflammatory status, and anthropometry. The trial is registered at ClinicalTrials.gov, NCT03049631. RESULTS In PreDM-IR, RRB supplementation reduced hepatic-IR (-30.1% ± 14.6%; P = 0.04) and reduced plasma total and LDL cholesterol [-4.9% ± 1.8% (P = 0.04) and -7.2% ± 2.3% (P = 0.003), respectively] from baseline. Adding FOS (RRB + FOS) improved β-cell function [insulin secretion rate, +70.2% ± 32.8% (P = 0.02); Disposition Index, +94.4% ± 50.2% (P = 0.04)], but had no significant effect on plasma cholesterol compared to baseline. RRB increased Eubacterium eligens (2-fold) and decreased Ruminococcus gnavus (-60% ± 34%), whereas RRB + FOS increased Bifidobacterium spp. (4-fold) and decreased Blautia wexlerae (-23% ± 12%) from baseline (all P values ≤ 0.05). R. gnavus was positively correlated with hepatic-IR, and E. eligens and Bifidobacterium catenulatum were negatively correlated with cholesterol concentrations (P ≤ 0.05). CONCLUSIONS Increased Bifidobacterium spp., concurrently with reduced R. gnavus, was associated with metabolic improvements in adults with PreDM-IR, warranting further research on the mechanisms involved in (poly)phenol/FOS-microbial interactions with host metabolism.
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Affiliation(s)
- Xuhuiqun Zhang
- Department of Food Science and Nutrition, Center for Nutrition Research and the Institute for Food Safety and Health, Illinois Institute of Technology, Chicago, IL, USA
| | - Anqi Zhao
- Department of Food Science and Nutrition, Center for Nutrition Research and the Institute for Food Safety and Health, Illinois Institute of Technology, Chicago, IL, USA
| | - Amandeep K Sandhu
- Department of Food Science and Nutrition, Center for Nutrition Research and the Institute for Food Safety and Health, Illinois Institute of Technology, Chicago, IL, USA
| | - Indika Edirisinghe
- Department of Food Science and Nutrition, Center for Nutrition Research and the Institute for Food Safety and Health, Illinois Institute of Technology, Chicago, IL, USA
| | - Britt M Burton-Freeman
- Department of Food Science and Nutrition, Center for Nutrition Research and the Institute for Food Safety and Health, Illinois Institute of Technology, Chicago, IL, USA
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50
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Lee JH, Park JH. Host-microbial interactions in metabolic diseases: from diet to immunity. JOURNAL OF MICROBIOLOGY (SEOUL, KOREA) 2022; 60:561-575. [PMID: 35511325 DOI: 10.1007/s12275-022-2087-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 03/23/2022] [Accepted: 04/01/2022] [Indexed: 12/14/2022]
Abstract
Growing evidence suggests that the gut microbiome is an important contributor to metabolic diseases. Alterations in microbial communities are associated with changes in lipid metabolism, glucose homeostasis, intestinal barrier functions, and chronic inflammation, all of which can lead to metabolic disorders. Therefore, the gut microbiome may represent a novel therapeutic target for obesity, type 2 diabetes, and nonalcoholic fatty liver disease. This review discusses how gut microbes and their products affect metabolic diseases and outlines potential treatment approaches via manipulation of the gut microbiome. Increasing our understanding of the interactions between the gut microbiome and host metabolism may help restore the healthy symbiotic relationship between them.
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Affiliation(s)
- Ju-Hyung Lee
- School of Biological Sciences and Institute of Microbiology, Seoul National University, Seoul, 08826, Republic of Korea
| | - Joo-Hong Park
- School of Biological Sciences and Institute of Microbiology, Seoul National University, Seoul, 08826, Republic of Korea.
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