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Ren YM, Zhuang ZY, Xie YH, Yang PJ, Xia TX, Xie YL, Liu ZH, Kang ZR, Leng XX, Lu SY, Zhang L, Chen JX, Xu J, Zhao EH, Wang Z, Wang M, Cui Y, Tan J, Liu Q, Jiang WH, Xiong H, Hong J, Chen YX, Chen HY, Fang JY. BCAA-producing Clostridium symbiosum promotes colorectal tumorigenesis through the modulation of host cholesterol metabolism. Cell Host Microbe 2024; 32:1519-1535.e7. [PMID: 39106870 DOI: 10.1016/j.chom.2024.07.012] [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: 06/02/2023] [Revised: 01/21/2024] [Accepted: 07/11/2024] [Indexed: 08/09/2024]
Abstract
Identification of potential bacterial players in colorectal tumorigenesis has been a focus of intense research. Herein, we find that Clostridium symbiosum (C. symbiosum) is selectively enriched in tumor tissues of patients with colorectal cancer (CRC) and associated with higher colorectal adenoma recurrence after endoscopic polypectomy. The tumorigenic effect of C. symbiosum is observed in multiple murine models. Single-cell transcriptome profiling along with functional assays demonstrates that C. symbiosum promotes the proliferation of colonic stem cells and enhances cancer stemness. Mechanistically, C. symbiosum intensifies cellular cholesterol synthesis by producing branched-chain amino acids (BCAAs), which sequentially activates Sonic hedgehog signaling. Low dietary BCAA intake or blockade of cholesterol synthesis by statins could partially abrogate the C. symbiosum-induced cell proliferation in vivo and in vitro. Collectively, we reveal C. symbiosum as a bacterial driver of colorectal tumorigenesis, thus identifying a potential target in CRC prediction, prevention, and treatment.
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Affiliation(s)
- Yi-Meng Ren
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Zi-Yan Zhuang
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Yuan-Hong Xie
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Peng-Jie Yang
- Chinese Academy of Sciences Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Tian-Xue Xia
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Yi-Le Xie
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Zhu-Hui Liu
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Zi-Ran Kang
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Xiao-Xu Leng
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Shi-Yuan Lu
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Lu Zhang
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Jin-Xian Chen
- Division of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Jia Xu
- Division of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - En-Hao Zhao
- Division of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Zheng Wang
- Division of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Ming Wang
- Division of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Yun Cui
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Juan Tan
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Qiang Liu
- Department of Pathology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Wei-Hong Jiang
- Chinese Academy of Sciences Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Hua Xiong
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Jie Hong
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China
| | - Ying-Xuan Chen
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China.
| | - Hao-Yan Chen
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China.
| | - Jing-Yuan Fang
- Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 145 Middle Shandong Road, Shanghai 200001, China.
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2
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Cao C, Yue S, Lu A, Liang C. Host-Gut Microbiota Metabolic Interactions and Their Role in Precision Diagnosis and Treatment of Gastrointestinal Cancers. Pharmacol Res 2024; 207:107321. [PMID: 39038631 DOI: 10.1016/j.phrs.2024.107321] [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: 02/24/2024] [Revised: 06/30/2024] [Accepted: 07/17/2024] [Indexed: 07/24/2024]
Abstract
The critical role of the gut microbiome in gastrointestinal cancers is becoming increasingly clear. Imbalances in the gut microbial community, referred to as dysbiosis, are linked to increased risks for various forms of gastrointestinal cancers. Pathogens like Fusobacterium and Helicobacter pylori relate to the onset of esophageal and gastric cancers, respectively, while microbes such as Porphyromonas gingivalis and Clostridium species have been associated with a higher risk of pancreatic cancer. In colorectal cancer, bacteria such as Fusobacterium nucleatum are known to stimulate the growth of tumor cells and trigger cancer-promoting pathways. On the other hand, beneficial microbes like Bifidobacteria offer a protective effect, potentially inhibiting the development of gastrointestinal cancers. The potential for therapeutic interventions that manipulate the gut microbiome is substantial, including strategies to engineer anti-tumor metabolites and employ microbiota-based treatments. Despite the progress in understanding the influence of the microbiome on gastrointestinal cancers, significant challenges remain in identifying and understanding the precise contributions of specific microbial species and their metabolic products. This knowledge is essential for leveraging the role of the gut microbiome in the development of precise diagnostics and targeted therapies for gastrointestinal cancers.
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Affiliation(s)
- Chunhao Cao
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China; Institute of Integrated Bioinfomedicine and Translational Science (IBTS), School of Chinese Medicine, Hong Kong Baptist University, 999077, Hong Kong Special Administrative Region of China
| | - Siran Yue
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China; Institute of Integrated Bioinfomedicine and Translational Science (IBTS), School of Chinese Medicine, Hong Kong Baptist University, 999077, Hong Kong Special Administrative Region of China
| | - Aiping Lu
- Institute of Integrated Bioinfomedicine and Translational Science (IBTS), School of Chinese Medicine, Hong Kong Baptist University, 999077, Hong Kong Special Administrative Region of China; Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou 510006, China; Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China.
| | - Chao Liang
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China; Institute of Integrated Bioinfomedicine and Translational Science (IBTS), School of Chinese Medicine, Hong Kong Baptist University, 999077, Hong Kong Special Administrative Region of China; State Key Laboratory of Proteomics, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 100850, China.
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3
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Murovec B, Deutsch L, Stres B. Predictive modeling of colorectal cancer using exhaustive analysis of microbiome information layers available from public metagenomic data. Front Microbiol 2024; 15:1426407. [PMID: 39252839 PMCID: PMC11381387 DOI: 10.3389/fmicb.2024.1426407] [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: 05/01/2024] [Accepted: 08/09/2024] [Indexed: 09/11/2024] Open
Abstract
This study aimed to compare the microbiome profiles of patients with colorectal cancer (CRC, n = 380) and colorectal adenomas (CRA, n = 110) against generally healthy participants (n = 2,461) from various studies. The overarching objective was to conduct a real-life experiment and develop a robust machine learning model applicable to the general population. A total of 2,951 stool samples underwent a comprehensive analysis using the in-house MetaBakery pipeline. This included various data matrices such as microbial taxonomy, functional genes, enzymatic reactions, metabolic pathways, and predicted metabolites. The study found no statistically significant difference in microbial diversity among individuals. However, distinct clusters were identified for healthy, CRC, and CRA groups through linear discriminant analysis (LDA). Machine learning analysis demonstrated consistent model performance, indicating the potential of microbiome layers (microbial taxa, functional genes, enzymatic reactions, and metabolic pathways) as prediagnostic indicators for CRC and CRA. Notable biomarkers on the taxonomy level and microbial functionality (gene families, enzymatic reactions, and metabolic pathways) associated with CRC were identified. The research presents promising avenues for practical clinical applications, with potential validation on external clinical datasets in future studies.
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Affiliation(s)
- Boštjan Murovec
- Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
| | - Leon Deutsch
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
- The NU, The NU B.V., Leiden, Netherlands
| | - Blaž Stres
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
- D13 Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Ljubljana, Slovenia
- Faculty of Civil and Geodetic Engineering, Institute of Sanitary Engineering, Ljubljana, Slovenia
- Department of Automation, Biocybernetics and Robotics, Jožef Stefan Institute, Ljubljana, Slovenia
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4
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Liddicoat C, Edwards RA, Roach M, Robinson JM, Wallace KJ, Barnes AD, Brame J, Heintz-Buschart A, Cavagnaro TR, Dinsdale EA, Doane MP, Eisenhauer N, Mitchell G, Rai B, Ramesh SA, Breed MF. Bioenergetic mapping of 'healthy microbiomes' via compound processing potential imprinted in gut and soil metagenomes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 940:173543. [PMID: 38821286 DOI: 10.1016/j.scitotenv.2024.173543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/24/2024] [Accepted: 05/24/2024] [Indexed: 06/02/2024]
Abstract
Despite mounting evidence of their importance in human health and ecosystem functioning, the definition and measurement of 'healthy microbiomes' remain unclear. More advanced knowledge exists on health associations for compounds used or produced by microbes. Environmental microbiome exposures (especially via soils) also help shape, and may supplement, the functional capacity of human microbiomes. Given the synchronous interaction between microbes, their feedstocks, and micro-environments, with functional genes facilitating chemical transformations, our objective was to examine microbiomes in terms of their capacity to process compounds relevant to human health. Here we integrate functional genomics and biochemistry frameworks to derive new quantitative measures of in silico potential for human gut and environmental soil metagenomes to process a panel of major compound classes (e.g., lipids, carbohydrates) and selected biomolecules (e.g., vitamins, short-chain fatty acids) linked to human health. Metagenome functional potential profile data were translated into a universal compound mapping 'landscape' based on bioenergetic van Krevelen mapping of function-level meta-compounds and corresponding functional relative abundances, reflecting imprinted genetic capacity of microbiomes to metabolize an array of different compounds. We show that measures of 'compound processing potential' associated with human health and disease (examining atherosclerotic cardiovascular disease, colorectal cancer, type 2 diabetes and anxious-depressive behavior case studies), and displayed seemingly predictable shifts along gradients of ecological disturbance in plant-soil ecosystems (three case studies). Ecosystem quality explained 60-92 % of variation in soil metagenome compound processing potential measures in a post-mining restoration case study dataset. With growing knowledge of the varying proficiency of environmental microbiota to process human health associated compounds, we might design environmental interventions or nature prescriptions to modulate our exposures, thereby advancing microbiota-oriented approaches to human health. Compound processing potential offers a simplified, integrative approach for applying metagenomics in ongoing efforts to understand and quantify the role of microbiota in environmental- and human-health.
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Affiliation(s)
- Craig Liddicoat
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia.
| | - Robert A Edwards
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Michael Roach
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Jake M Robinson
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Kiri Joy Wallace
- Environmental Research Institute, University of Waikato, Hamilton, Aotearoa, New Zealand
| | - Andrew D Barnes
- Environmental Research Institute, University of Waikato, Hamilton, Aotearoa, New Zealand
| | - Joel Brame
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Anna Heintz-Buschart
- Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 XH Amsterdam, the Netherlands
| | - Timothy R Cavagnaro
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Elizabeth A Dinsdale
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Michael P Doane
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Nico Eisenhauer
- German Centre for Integrative Biodiversity Research (iDiv), 04103 Leipzig, Germany; Institute of Biology, Leipzig University, 04103 Leipzig, Germany
| | - Grace Mitchell
- Environmental Research Institute, University of Waikato, Hamilton, Aotearoa, New Zealand; Manaaki Whenua - Landcare Research, Hamilton, Aotearoa, New Zealand
| | - Bibishan Rai
- Environmental Research Institute, University of Waikato, Hamilton, Aotearoa, New Zealand
| | - Sunita A Ramesh
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Martin F Breed
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
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Jin DM, Morton JT, Bonneau R. Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases. mSystems 2024; 9:e0029524. [PMID: 39078158 PMCID: PMC11334437 DOI: 10.1128/msystems.00295-24] [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: 02/26/2024] [Accepted: 05/08/2024] [Indexed: 07/31/2024] Open
Abstract
Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings, detected by our pipeline, provide valuable insights into these diseases. IMPORTANCE Assessing disease similarity is an essential initial step preceding a disease-based approach for drug repositioning. Our study provides a modest first step in underscoring the potential of integrating microbiome insights into the disease similarity assessment. Recent microbiome research has predominantly focused on analyzing individual diseases to understand their unique characteristics, which by design excludes comorbidities in individuals. We analyzed shotgun metagenomic data from existing studies and identified previously unknown similarities between diseases. Our research represents a pioneering effort that utilizes both interpretable machine learning and differential abundance analysis to assess microbial similarity between diseases.
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Affiliation(s)
- Dong-Min Jin
- Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - James T. Morton
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York, USA
| | - Richard Bonneau
- Center for Genomics and Systems Biology, New York University, New York, New York, USA
- Genentech, New York, New York, USA
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Huang P, Ji F, Cheung AHK, Fu K, Zhou Q, Ding X, Chen D, Lin Y, Wang L, Jiao Y, Chu ESH, Kang W, To KF, Yu J, Wong CC. Peptostreptococcus stomatis promotes colonic tumorigenesis and receptor tyrosine kinase inhibitor resistance by activating ERBB2-MAPK. Cell Host Microbe 2024; 32:1365-1379.e10. [PMID: 39059397 DOI: 10.1016/j.chom.2024.07.001] [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: 03/11/2024] [Revised: 05/23/2024] [Accepted: 07/02/2024] [Indexed: 07/28/2024]
Abstract
Peptostreptococcus stomatis (P. stomatis) is enriched in colorectal cancer (CRC), but its causality and translational implications in CRC are unknown. Here, we show that P. stomatis accelerates colonic tumorigenesis in ApcMin/+ and azoxymethane/dextran sodium sulfate (AOM-DSS) models by inducing cell proliferation, suppressing apoptosis, and impairing gut barrier function. P. stomatis adheres to CRC cells through its surface protein fructose-1,6-bisphosphate aldolase (FBA) that binds to the integrin α6/β4 receptor on CRC cells, leading to the activation of ERBB2 and the downstream MEK-ERK-p90 cascade. Blockade of the FBA-integrin α6/β4 abolishes ERBB2-mitogen-activated protein kinase (MAPK) activation and the protumorigenic effect of P. stomatis. P. stomatis-driven ERBB2 activation bypasses receptor tyrosine kinase (RTK) blockade by EGFR inhibitors (cetuximab, erlotinib), leading to drug resistance in xenograft and spontaneous CRC models of KRAS-wild-type CRC. P. stomatis also abrogates BRAF inhibitor (vemurafenib) efficacy in BRAFV600E-mutant CRC xenografts. Thus, we identify P. stomatis as an oncogenic bacterium and a contributory factor for non-responsiveness to RTK inhibitors in CRC.
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Affiliation(s)
- Pingmei Huang
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Fenfen Ji
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Alvin Ho-Kwan Cheung
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Kaili Fu
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Qiming Zhou
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Xiao Ding
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Danyu Chen
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yufeng Lin
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Luyao Wang
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Ying Jiao
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Eagle S H Chu
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Wei Kang
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Ka Fai To
- Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jun Yu
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
| | - Chi Chun Wong
- Institute of Digestive Disease and Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
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7
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Wang S, Jiang Y, Che L, Wang RH, Li SC. Enhancing insights into diseases through horizontal gene transfer event detection from gut microbiome. Nucleic Acids Res 2024; 52:e61. [PMID: 38884260 DOI: 10.1093/nar/gkae515] [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: 09/28/2023] [Revised: 04/23/2024] [Accepted: 06/04/2024] [Indexed: 06/18/2024] Open
Abstract
Horizontal gene transfer (HGT) phenomena pervade the gut microbiome and significantly impact human health. Yet, no current method can accurately identify complete HGT events, including the transferred sequence and the associated deletion and insertion breakpoints from shotgun metagenomic data. Here, we develop LocalHGT, which facilitates the reliable and swift detection of complete HGT events from shotgun metagenomic data, delivering an accuracy of 99.4%-verified by Nanopore data-across 200 gut microbiome samples, and achieving an average F1 score of 0.99 on 100 simulated data. LocalHGT enables a systematic characterization of HGT events within the human gut microbiome across 2098 samples, revealing that multiple recipient genome sites can become targets of a transferred sequence, microhomology is enriched in HGT breakpoint junctions (P-value = 3.3e-58), and HGTs can function as host-specific fingerprints indicated by the significantly higher HGT similarity of intra-personal temporal samples than inter-personal samples (P-value = 4.3e-303). Crucially, HGTs showed potential contributions to colorectal cancer (CRC) and acute diarrhoea, as evidenced by the enrichment of the butyrate metabolism pathway (P-value = 3.8e-17) and the shigellosis pathway (P-value = 5.9e-13) in the respective associated HGTs. Furthermore, differential HGTs demonstrated promise as biomarkers for predicting various diseases. Integrating HGTs into a CRC prediction model achieved an AUC of 0.87.
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Affiliation(s)
- Shuai Wang
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Yiqi Jiang
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Lijia Che
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Ruo Han Wang
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Shuai Cheng Li
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
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8
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Ota G, Inoue R, Saito A, Kono Y, Kitayama J, Sata N, Horie H. Reduced Abundance of Phocaeicola in Mucosa-associated Microbiota Is Associated with Distal Colorectal Cancer Metastases Possibly through an Altered Local Immune Environment. J Anus Rectum Colon 2024; 8:235-245. [PMID: 39086872 PMCID: PMC11286368 DOI: 10.23922/jarc.2024-014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 05/17/2024] [Indexed: 08/02/2024] Open
Abstract
Objectives The aim of this study was to identify the microbiota whose decrease in tumor area was associated with the metastatic process of distal colorectal cancer (CRC). Methods Twenty-eight consecutive patients with distal CRC undergoing surgical resection in our hospital were enrolled. Microbiota in 28 specimens from surgically resected colorectal cancers were analyzed using 16S ribosomal ribonucleic acid gene amplicon sequencing and the relative abundance (RA) of microbiota was evaluated. The densities of tumor-infiltrating lymphocytes (TIL) and tumor associated macrophages (TAM) in the colorectal cancers were immunohistochemically evaluated. Results Phocaeicola was the most abundant microbiota in normal mucosa. The RA of Phocaeicola in tumor tissues tended to be lower than that in normal mucosa although the difference was not significant (p=0.0732). The RA of Phocaeicola at tumor sites did not correlate either with depth of tumor invasion (pT-stage) or tumor size, however they were significantly reduced in patients with nodal metastases (p<0.05) and those with distant metastases (p<0.001). The RA of Phocaeicola at tumor sites showed positive correlation with the densities of CD3(+) or CD8(+) TIL. Since P. vulgatus was the most dominant species (47%) of the Phocaeicola, the RA of P. vulgatus and CRC metastasis and its association with TIL and TAM were also investigated. P. vulgatus showed a similar trend to genus Phocaeicola but was not statistically significant. Conclusions A relative reduction of Phocaeicola attenuates the local anti-tumor immune response in distal CRC, which may facilitate metastatic spread.
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Affiliation(s)
- Gaku Ota
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
| | - Ryo Inoue
- Laboratory of Animal Science, Department of Applied Biological Sciences, Faculty of Agriculture, Setsunan University, Hirakata, Japan
| | - Akira Saito
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
| | - Yoshihiko Kono
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
| | - Joji Kitayama
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
- Clinical Research Center, Division of Translational Research, Jichi Medical University, Shimotsuke, Japan
| | - Naohiro Sata
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
| | - Hisanaga Horie
- Department of Surgery, Jichi Medical University, Shimotsuke, Japan
- Department of Operating Room Management, Jichi Medical University Hospital, Shimotsuke, Japan
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9
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Corrigan A, McCooey P, Taylor-Pickard J, Stockdale S, Murphy R. Breaking the Cycle: A Yeast Mannan-Rich Fraction Beneficially Modulates Egg Quality and the Antimicrobial Resistome Associated with Layer Hen Caecal Microbiomes under Commercial Conditions. Microorganisms 2024; 12:1562. [PMID: 39203404 PMCID: PMC11356413 DOI: 10.3390/microorganisms12081562] [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: 07/16/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 09/03/2024] Open
Abstract
Antibiotics and antibiotic growth promoters have been extensively employed in poultry farming to enhance growth performance, maintain bird health, improve nutrient uptake efficiency, and mitigate enteric diseases at both sub-therapeutic and therapeutic doses. However, the extensive use of antimicrobials in poultry farming has led to the emergence of antimicrobial resistance (AMR) in microbial reservoirs, representing a significant global public health concern. In response, non-antibiotic dietary interventions, such as yeast mannan-rich fraction (MRF), have emerged as a promising alternative to modulate the gut microbiota and combat the AMR crisis. This study investigated whether a yeast mannan-rich fraction containing feed supplement impacted the performance of laying hens, their microbiomes, and the associated carriage of antimicrobial resistance genes under commercial conditions. High-throughput DNA sequencing was utilised to profile the bacterial community and assess changes in the antibiotic resistance genomes detected in the metagenome, the "resistome", in response to MRF supplementation. It was found that supplementation favourably influenced laying hen performance and microbial composition. Notably, there was a compositional shift in the MRF supplemented group associated with a lower relative abundance of pathobionts, e.g., Escherichia, Brachyspira and Trueperella, and their AMR-encoded genes, relative to beneficial microbes. Overall, the findings further demonstrate the ability of prebiotics to improve laying hen performance through changes associated with their microbiome and resistome.
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Affiliation(s)
- Aoife Corrigan
- Alltech Bioscience Centre, A86 X006 Dunboyne, Co. Meath, Ireland; (P.M.); (R.M.)
| | - Paula McCooey
- Alltech Bioscience Centre, A86 X006 Dunboyne, Co. Meath, Ireland; (P.M.); (R.M.)
| | | | - Stephen Stockdale
- Novogene (UK) Company Ltd., 25 Cambridge Science Park, Cambridge CB4 0FW, UK;
- BioFigR, Ballyvoloon, P24 N524 Cobh, Cork, Ireland
| | - Richard Murphy
- Alltech Bioscience Centre, A86 X006 Dunboyne, Co. Meath, Ireland; (P.M.); (R.M.)
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10
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Bars-Cortina D, Ramon E, Rius-Sansalvador B, Guinó E, Garcia-Serrano A, Mach N, Khannous-Lleiffe O, Saus E, Gabaldón T, Ibáñez-Sanz G, Rodríguez-Alonso L, Mata A, García-Rodríguez A, Obón-Santacana M, Moreno V. Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota. BMC Genomics 2024; 25:730. [PMID: 39075388 PMCID: PMC11285316 DOI: 10.1186/s12864-024-10621-7] [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: 04/08/2024] [Accepted: 07/15/2024] [Indexed: 07/31/2024] Open
Abstract
BACKGROUND Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models. RESULTS As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra. CONCLUSIONS Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.
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Affiliation(s)
- David Bars-Cortina
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
| | - Elies Ramon
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
| | - Blanca Rius-Sansalvador
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Doctoral Programme in Biomedicine, University of Barcelona (UB), Barcelona, 08907, Spain
| | - Elisabet Guinó
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, 28029, Spain
| | - Ainhoa Garcia-Serrano
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, 14186, Sweden
| | - Núria Mach
- IHAP, Université de Toulouse, INRAE, ENVT, Toulouse, France
| | - Olfat Khannous-Lleiffe
- Barcelona Supercomputing Centre (BSC-CNS), Barcelona, 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, 08028, Spain
| | - Ester Saus
- Barcelona Supercomputing Centre (BSC-CNS), Barcelona, 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, 08028, Spain
| | - Toni Gabaldón
- Barcelona Supercomputing Centre (BSC-CNS), Barcelona, 08034, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, 08028, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, 08010, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Barcelona, 08028, Spain
| | - Gemma Ibáñez-Sanz
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Gastroenterology Department, Bellvitge University Hospital, L'Hospitalet de Llobregat, Barcelona, 08907, Spain
| | - Lorena Rodríguez-Alonso
- Gastroenterology Department, Bellvitge University Hospital, L'Hospitalet de Llobregat, Barcelona, 08907, Spain
| | - Alfredo Mata
- Digestive System Service, Moisés Broggi Hospital, Sant Joan Despí, 08970, Spain
| | - Ana García-Rodríguez
- Endoscopy Unit, Digestive System Service, Viladecans Hospital-IDIBELL, Viladecans, 08840, Spain
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain.
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain.
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, 28029, Spain.
| | - Victor Moreno
- Unit of Biomarkers and Susceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona, 08908, Spain.
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain.
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, 28029, Spain.
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences, Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L'Hospitalet de Llobregat, Barcelona, 08908, Spain.
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11
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Li Y, Li J, Li S, Zhou S, Yang J, Xu K, Chen Y. Exploring the gut microbiota's crucial role in acute pancreatitis and the novel therapeutic potential of derived extracellular vesicles. Front Pharmacol 2024; 15:1437894. [PMID: 39130638 PMCID: PMC11310017 DOI: 10.3389/fphar.2024.1437894] [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: 05/24/2024] [Accepted: 07/15/2024] [Indexed: 08/13/2024] Open
Abstract
During acute pancreatitis, intestinal permeability increases due to intestinal motility dysfunction, microcirculatory disorders, and ischemia-reperfusion injury, and disturbances in the intestinal flora make bacterial translocation easier, which consequently leads to local or systemic complications such as pancreatic and peripancreatic necrotic infections, acute lung injury, systemic inflammatory response syndrome, and multiple organ dysfunction syndrome. Therefore, adjusting intestinal ecosystem balance may be a promising approach to control local and systemic complications of acute pancreatitis. In this paper, we reviewed the causes and manifestations of intestinal flora disorders during acute pancreatitis and their complications, focused on the reduction of acute pancreatitis and its complications by adjusting the intestinal microbial balance, and innovatively proposed the treatment of acute pancreatitis and its complications by gut microbiota-derived extracellular vesicles.
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Affiliation(s)
- Yijie Li
- Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jie Li
- Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Sen Li
- Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Shumin Zhou
- Wenzhou Institute of Shanghai University, Wenzhou, China
| | - Jiahua Yang
- Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ke Xu
- Wenzhou Institute of Shanghai University, Wenzhou, China
- Institute of Translational Medicine, Shanghai University, Shanghai, China
| | - Yafeng Chen
- Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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12
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Xiang Y, Zhang C, Wang J, Cheng Y, Wang K, Wang L, Tong Y, Yan D. Role of blood metabolites in mediating the effect of gut microbiome on the mutated-RAS/BRAF metastatic colorectal cancer-specific survival. Int J Colorectal Dis 2024; 39:116. [PMID: 39046546 PMCID: PMC11269474 DOI: 10.1007/s00384-024-04686-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/09/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Recent studies have linked alterations in the gut microbiome and metabolic disruptions to the invasive behavior and metastasis of colorectal cancer (CRC), thus affecting patient prognosis. However, the specific relationship among gut microbiome, metabolite profiles, and mutated-RAS/BRAF metastatic colorectal cancer (M-mCRC) remains unclear. Furthermore, the potential mechanisms and prognostic implications of metabolic changes induced by gut microbiome alterations in patients with M-mCRC still need to be better understood. METHODS We conducted Mendelian randomization (MR) to evaluate the causal relationship of genetically predicted 196 gut microbiome features and 1400 plasma metabolites/metabolite ratios on M-mCRC-specific survival. Additionally, we identified significant gut microbiome-metabolites/metabolite ratio associations based on M-mCRC. Metabolite information was annotated, and functional annotation and pathway enrichment analyses were performed on shared proteins corresponding to significant metabolite ratios, aiming to reveal potential mechanisms by which gut microbiome influences M-mCRC prognosis via modulation of human metabolism. RESULTS We identified 11 gut microbiome features and 49 known metabolites/metabolite ratios correlated with M-mCRC-specific survival. Furthermore, we identified 17 gut microbiome-metabolite/metabolite ratio associations specific to M-mCRC, involving eight lipid metabolites and three bilirubin degradation products. The shared proteins corresponding to significant metabolite ratios were predominantly localized within the integral component of the membrane and exhibited enzymatic activities such as glucuronosyltransferase and UDP-glucuronosyltransferase, crucial in processes such as glucuronidation, bile secretion, and lipid metabolism. Moreover, these proteins were significantly enriched in pathways related to ascorbate and aldarate metabolism, pentose and glucuronate interconversions, steroid hormone biosynthesis, and bile secretion. CONCLUSION Our study offers novel insights into the potential mechanisms underlying the impact of the gut microbiome on the prognosis of M-mCRC. These findings serve as a meaningful reference for exploring potential therapeutic targets and strategies in the future.
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Affiliation(s)
- Yaoxian Xiang
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Chan Zhang
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Jing Wang
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Yurong Cheng
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Kangjie Wang
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Li Wang
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Yingying Tong
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China
| | - Dong Yan
- Department of Oncology, Beijing Luhe Hospital Affiliated to Capital Medical University, Beijing, 101149, China.
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13
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Yang Z, Ma J, Han J, Li A, Liu G, Sun Y, Zheng J, Zhang J, Chen G, Xu R, Sun L, Meng C, Gao J, Bai Z, Deng W, Zhang C, Su J, Yao H, Zhang Z. Gut microbiome model predicts response to neoadjuvant immunotherapy plus chemoradiotherapy in rectal cancer. MED 2024:S2666-6340(24)00261-7. [PMID: 39047732 DOI: 10.1016/j.medj.2024.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/18/2024] [Accepted: 07/01/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND Accurate evaluation of the response to preoperative treatment enables the provision of a more appropriate personalized therapeutic schedule for locally advanced rectal cancer (LARC), which remains an enormous challenge, especially neoadjuvant immunotherapy plus chemoradiotherapy (nICRT). METHODS This prospective, multicenter cohort study enrolled patients with LARC from 6 centers who received nICRT. The dynamic variation in the gut microbiome during nICRT was evaluated. A species-level gut microbiome prediction (SPEED) model was developed and validated to predict the pathological complete response (pCR) to nICRT. FINDINGS A total of 50 patients were enrolled, 75 fecal samples were collected from 33 patients at different time points, and the pCR rate reached 42.4% (14/33). Lactobacillus and Eubacterium were observed to increase after nICRT. Additionally, significant differences in the gut microbiome were observed between responders and non-responders at baseline. Significantly higher abundances of Lachnospiraceaebacterium and Blautiawexlerae were found in responders, while Bacteroides, Prevotella, and Porphyromonas were found in non-responders. The SPEED model showcased a superior predictive performance with areas under the curve of 98.80% (95% confidence interval [CI]: 95.67%-100%) in the training cohort and 77.78% (95% CI: 65.42%-88.29%) in the validation cohort. CONCLUSIONS Programmed death 1 (PD-1) blockade plus concurrent long-course CRT showed a favorable pCR rate and is well tolerated in microsatellite-stable (MSS)/mismatch repair-proficient (pMMR) patients with LARC. The SPEED model can be used to predict the pCR to nICRT based on the baseline gut microbiome with high robustness and accuracy, thereby assisting clinical physicians in providing individualized management for patients with LARC. FUNDING This research was funded by the China National Natural Science Foundation (82202884).
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Affiliation(s)
- Zhengyang Yang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Jingxin Ma
- Department of Clinical Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jiagang Han
- Department of General Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Ang Li
- Department of General Surgery, Beijing Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Gang Liu
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Yi Sun
- Department of Anorectal, Tianjin People's Hospital, Tianjin, China
| | - Jianyong Zheng
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Air Force Medical University, Xi'an, China
| | - Jie Zhang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Guangyong Chen
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Rui Xu
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Liting Sun
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Cong Meng
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Jiale Gao
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Zhigang Bai
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Wei Deng
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Chenlin Zhang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China
| | - Jianrong Su
- Department of Clinical Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| | - Hongwei Yao
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China.
| | - Zhongtao Zhang
- Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, State Key Lab of Digestive Health, National Clinical Research Center for Digestive Diseases, Beijing, China.
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14
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Lee S, Portlock T, Le Chatelier E, Garcia-Guevara F, Clasen F, Oñate FP, Pons N, Begum N, Harzandi A, Proffitt C, Rosario D, Vaga S, Park J, von Feilitzen K, Johansson F, Zhang C, Edwards LA, Lombard V, Gauthier F, Steves CJ, Gomez-Cabrero D, Henrissat B, Lee D, Engstrand L, Shawcross DL, Proctor G, Almeida M, Nielsen J, Mardinoglu A, Moyes DL, Ehrlich SD, Uhlen M, Shoaie S. Global compositional and functional states of the human gut microbiome in health and disease. Genome Res 2024; 34:967-978. [PMID: 39038849 PMCID: PMC11293553 DOI: 10.1101/gr.278637.123] [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: 10/19/2023] [Accepted: 06/05/2024] [Indexed: 07/24/2024]
Abstract
The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses. Using interpreted machine learning classification models and statistical methods, we identified Fusobacterium nucleatum and Anaerostipes hadrus with the highest frequencies, enriched and depleted, respectively, across different disease cohorts. Distinct functional distributions were observed in the gut microbiomes of both westernized and nonwesternized populations. These compositional and functional analyses are presented in the open-access Human Gut Microbiome Atlas, allowing for the exploration of the richness, disease, and regional signatures of the gut microbiota across different cohorts.
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Affiliation(s)
- Sunjae Lee
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), 61005, Gwangju, Republic of Korea
| | - Theo Portlock
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | | | - Fernando Garcia-Guevara
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - Frederick Clasen
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | | | - Nicolas Pons
- University Paris-Saclay, INRAE, MetaGenoPolis, 78350 Jouy-en-Josas, France
| | - Neelu Begum
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Azadeh Harzandi
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Ceri Proffitt
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Dorines Rosario
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Stefania Vaga
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Junseok Park
- Department of Bio and Brain Engineering, KAIST, Yuseong-gu, Daejeon 305-701, Republic of Korea
| | - Kalle von Feilitzen
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - Fredric Johansson
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - Cheng Zhang
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - Lindsey A Edwards
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
- Institute of Liver Studies, Department of Inflammation Biology, School of Immunology and Microbial Sciences, King's College London, London SE5 9NU, United Kingdom
| | - Vincent Lombard
- INRAE, USC1408 Architecture et Fonction des Macromolécules Biologiques (AFMB), Marseille 13288, France
- Architecture et Fonction des Macromolécules Biologiques (AFMB), CNRS, Aix-Marseille University, Marseille 13288, France
| | - Franck Gauthier
- University Paris-Saclay, INRAE, MetaGenoPolis, 78350 Jouy-en-Josas, France
| | - Claire J Steves
- Department of Twin Research & Genetic Epidemiology, King's College London, London WC2R 2LS, United Kingdom
| | - David Gomez-Cabrero
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
- Translational Bioinformatics Unit, Navarrabiomed, Universidad Pública de Navarra (UPNA), IdiSNA, 31008 Pamplona, Spain
- Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
| | - Bernard Henrissat
- Department of Biological Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Department of Biotechnology and Biomedicine, Technical University of Denmark, DK-2800 Lyngby, Denmark
| | - Doheon Lee
- Department of Bio and Brain Engineering, KAIST, Yuseong-gu, Daejeon 305-701, Republic of Korea
| | - Lars Engstrand
- Centre for Translational Microbiome Research (CTMR), Department of Microbiology, Tumour and Cell Biology, Karolinska Institutet, 171 65 Stockholm, Sweden
| | - Debbie L Shawcross
- Institute of Liver Studies, Department of Inflammation Biology, School of Immunology and Microbial Sciences, King's College London, London SE5 9NU, United Kingdom
| | - Gordon Proctor
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Mathieu Almeida
- University Paris-Saclay, INRAE, MetaGenoPolis, 78350 Jouy-en-Josas, France
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden
- BioInnovation Institute, DK-2200 Copenhagen N, Denmark
| | - Adil Mardinoglu
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
| | - David L Moyes
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom
| | - Stanislav Dusko Ehrlich
- University Paris-Saclay, INRAE, MetaGenoPolis, 78350 Jouy-en-Josas, France
- Department of Clinical and Movement Neurosciences, University College London, London NW3 2PF, United Kingdom
| | - Mathias Uhlen
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden;
| | - Saeed Shoaie
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, SE1 9RT, United Kingdom;
- Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm, SE-171 21, Sweden
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15
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Kulecka M, Czarnowski P, Bałabas A, Turkot M, Kruczkowska-Tarantowicz K, Żeber-Lubecka N, Dąbrowska M, Paszkiewicz-Kozik E, Walewski J, Ługowska I, Koseła-Paterczyk H, Rutkowski P, Kluska A, Piątkowska M, Jagiełło-Gruszfeld A, Tenderenda M, Gawiński C, Wyrwicz L, Borucka M, Krzakowski M, Zając L, Kamiński M, Mikula M, Ostrowski J. Microbial and Metabolic Gut Profiling across Seven Malignancies Identifies Fecal Faecalibacillus intestinalis and Formic Acid as Commonly Altered in Cancer Patients. Int J Mol Sci 2024; 25:8026. [PMID: 39125593 PMCID: PMC11311272 DOI: 10.3390/ijms25158026] [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: 06/24/2024] [Revised: 07/18/2024] [Accepted: 07/19/2024] [Indexed: 08/12/2024] Open
Abstract
The key association between gut dysbiosis and cancer is already known. Here, we used whole-genome shotgun sequencing (WGS) and gas chromatography/mass spectrometry (GC/MS) to conduct metagenomic and metabolomic analyses to identify common and distinct taxonomic configurations among 40, 45, 71, 34, 50, 60, and 40 patients with colorectal cancer, stomach cancer, breast cancer, lung cancer, melanoma, lymphoid neoplasms and acute myeloid leukemia (AML), respectively, and compared the data with those from sex- and age-matched healthy controls (HC). α-diversity differed only between the lymphoid neoplasm and AML groups and their respective HC, while β-diversity differed between all groups and their HC. Of 203 unique species, 179 and 24 were under- and over-represented, respectively, in the case groups compared with HC. Of these, Faecalibacillus intestinalis was under-represented in each of the seven groups studied, Anaerostipes hadrus was under-represented in all but the stomach cancer group, and 22 species were under-represented in the remaining five case groups. There was a marked reduction in the gut microbiome cancer index in all case groups except the AML group. Of the short-chain fatty acids and amino acids tested, the relative concentration of formic acid was significantly higher in each of the case groups than in HC, and the abundance of seven species of Faecalibacterium correlated negatively with most amino acids and formic acid, and positively with the levels of acetic, propanoic, and butanoic acid. We found more differences than similarities between the studied malignancy groups, with large variations in diversity, taxonomic/metabolomic profiles, and functional assignments. While the results obtained may demonstrate trends rather than objective differences that correlate with different types of malignancy, the newly developed gut microbiota cancer index did distinguish most of the cancer cases from HC. We believe that these data are a promising step forward in the search for new diagnostic and predictive tests to assess intestinal dysbiosis among cancer patients.
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Affiliation(s)
- Maria Kulecka
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Paweł Czarnowski
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Aneta Bałabas
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Maryla Turkot
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland
- Department of Cancer Prevention, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Kamila Kruczkowska-Tarantowicz
- Department of Internal Medicine and Hematology, Military Institute of Medicine—National Research Institute, 04-141 Warsaw, Poland
| | - Natalia Żeber-Lubecka
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Michalina Dąbrowska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Ewa Paszkiewicz-Kozik
- Department of Lymphoid Malignancies, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Jan Walewski
- Department of Lymphoid Malignancies, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Iwona Ługowska
- Early Phase Clinical Trials Unit, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Hanna Koseła-Paterczyk
- Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Piotr Rutkowski
- Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Anna Kluska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Magdalena Piątkowska
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Agnieszka Jagiełło-Gruszfeld
- Department of Breast Cancer & Reconstructive Surgery, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Michał Tenderenda
- Department of Oncological Surgery and Neuroendocrine Tumors, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Cieszymierz Gawiński
- Department of Oncology and Radiotherapy, Maria Sklodowska-Curie National Cancer Research Institute, 02-781 Warsaw, Poland
| | - Lucjan Wyrwicz
- Department of Oncology and Radiotherapy, Maria Sklodowska-Curie National Cancer Research Institute, 02-781 Warsaw, Poland
| | - Magdalena Borucka
- Department of Lung and Chest Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Maciej Krzakowski
- Department of Lung and Chest Cancer, Maria Skłodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Leszek Zając
- Department of Gastrointestinal Surgical Oncology, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Michał Kamiński
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland
- Department of Cancer Prevention, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Michał Mikula
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Jerzy Ostrowski
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, 02-781 Warsaw, Poland
- Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
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16
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Herlo LF, Salcudean A, Sirli R, Iurciuc S, Herlo A, Nelson-Twakor A, Alexandrescu L, Dumache R. Gut Microbiota Signatures in Colorectal Cancer as a Potential Diagnostic Biomarker in the Future: A Systematic Review. Int J Mol Sci 2024; 25:7937. [PMID: 39063179 PMCID: PMC11276678 DOI: 10.3390/ijms25147937] [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: 06/05/2024] [Revised: 07/06/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
The gut microbiota has acquired significant attention in recent years for its potential as a diagnostic biomarker for colorectal cancer (CRC). In this literature review, we looked at the studies exploring alterations in gut microbiota composition associated with CRC, the potential mechanisms linking gut dysbiosis to CRC development, and the diagnostic approaches utilizing gut microbiota analysis. Our research has led to the conclusion that individuals with CRC often display alterations in their gut microbiota composition compared to healthy individuals. These alterations can include changes in the diversity, abundance, and type of bacteria present in the gut. While the use of gut microbiota as a diagnostic biomarker for CRC holds promise, further research is needed to validate its effectiveness and standardize testing protocols. Additionally, considerations such as variability in the microbiota composition among individuals and potential factors must be addressed before microbiota-based tests can be widely implemented in clinical practice.
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Affiliation(s)
- Lucian-Flavius Herlo
- Doctoral School, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania;
| | - Andreea Salcudean
- Discipline of Sociobiology, Department of Ethics and Social Sciences, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540136 Targu Mures, Romania;
| | - Roxana Sirli
- Advanced Regional Research Center in Gastroenterology and Hepatology, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania;
| | - Stela Iurciuc
- Cardiology Department, Victor Babes University of Medicine and Pharmacy, 300041 Timisoara, Romania;
| | - Alexandra Herlo
- Department XIII, Discipline of Infectious Diseases, Victor Babes University of Medicine and Pharmacy Timisoara, 2 Eftimie Murgu Square, 300041 Timisoara, Romania
| | - Andreea Nelson-Twakor
- Department of Internal Medicine, County Clinical Emergency Hospital of Constanta, 900647 Constanta, Romania;
| | - Luana Alexandrescu
- Department of Gastroenterology, County Clinical Emergency Hospital of Constanta, 900647 Constanta, Romania;
| | - Raluca Dumache
- Department of Forensic Medicine, Bioethics, Medical ethics and Medical Law, Victor Babes University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania;
- Center for Ethics in Human Genetic Identifications, Victor Babes University of Medicine and Pharmacy Timisoara, E. Murgu Square, Nr. 2, 300041 Timisoara, Romania
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17
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Salim F, Mizutani S, Shiba S, Takamaru H, Yamada M, Nakajima T, Yachida T, Soga T, Saito Y, Fukuda S, Yachida S, Yamada T. Fusobacterium species are distinctly associated with patients with Lynch syndrome colorectal cancer. iScience 2024; 27:110181. [PMID: 38993678 PMCID: PMC11237946 DOI: 10.1016/j.isci.2024.110181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/11/2024] [Accepted: 06/01/2024] [Indexed: 07/13/2024] Open
Abstract
Accumulating evidence demonstrates clear correlation between the gut microbiota and sporadic colorectal cancer (CRC). Despite this, there is limited understanding of the association between the gut microbiota and CRC in Lynch Syndrome (LS), a hereditary type of CRC. Here, we analyzed fecal shotgun metagenomic and targeted metabolomic of 71 Japanese LS subjects. A previously published Japanese sporadic CRC cohort, which includes non-LS controls, was utilized as a non-LS cohort (n = 437). LS subjects exhibited reduced microbial diversity and low-Faecalibacterium enterotypes compared to non-LS. Patients with LS-CRC had higher levels of Fusobacterium nucleatum and fap2. Differential fecal metabolites and functional genes suggest heightened degradation of lysine and arginine in LS-CRC. A comparison between LS and non-LS subjects prior to adenoma formation revealed distinct fecal metabolites of LS subjects. These findings suggest that the gut microbiota plays a more responsive role in CRC tumorigenesis in patients with LS than those without LS.
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Affiliation(s)
- Felix Salim
- School of Life Science and Technology, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
| | - Sayaka Mizutani
- School of Life Science and Technology, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
- Research Fellow of Japan Society for the Promotion of Science, Tokyo, Japan
| | - Satoshi Shiba
- Division of Cancer Genomics, National Cancer Center Research Institute, Chuo-ku, Tokyo 104-0045, Japan
| | - Hiroyuki Takamaru
- Endoscopy Division, National Cancer Center Hospital, Chuo-ku 104-0045, Tokyo, Japan
| | - Masayoshi Yamada
- Endoscopy Division, National Cancer Center Hospital, Chuo-ku 104-0045, Tokyo, Japan
| | - Takeshi Nakajima
- Endoscopy Division, National Cancer Center Hospital, Chuo-ku 104-0045, Tokyo, Japan
| | - Tatsuo Yachida
- Department of Gastroenterology & Neurology, Faculty of Medicine, Kagawa University, Miki-cho, Kagawa 761-0793, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
| | - Yutaka Saito
- Endoscopy Division, National Cancer Center Hospital, Chuo-ku 104-0045, Tokyo, Japan
| | - Shinji Fukuda
- Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0052, Japan
- Gut Environmental Design Group, Kanagawa Institute of Industrial Science and Technology, Kawasaki, Kanagawa 210-0821, Japan
- Transborder Medical Research Center, University of Tsukuba, Tsukuba, Ibaraki 305-8575, Japan
- Laboratory for Regenerative Microbiology, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421, Japan
- Metagen, Inc., Tsuruoka, Yamagata 997-0052, Japan
- Metagen Theurapeutics, Inc., Tsuruoka, Yamagata 997-0052, Japan
| | - Shinichi Yachida
- Department of Cancer Genome Informatics, Graduate School of Medicine, Osaka University, Suita, Osaka 565-0871, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University, Suita, Osaka 565-0871, Japan
| | - Takuji Yamada
- School of Life Science and Technology, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
- Metagen, Inc., Tsuruoka, Yamagata 997-0052, Japan
- Metagen Theurapeutics, Inc., Tsuruoka, Yamagata 997-0052, Japan
- digzyme, Inc., Minato-ku, Tokyo 105-0004, Japan
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18
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Covello C, Becherucci G, Di Vincenzo F, Del Gaudio A, Pizzoferrato M, Cammarota G, Gasbarrini A, Scaldaferri F, Mentella MC. Parenteral Nutrition, Inflammatory Bowel Disease, and Gut Barrier: An Intricate Plot. Nutrients 2024; 16:2288. [PMID: 39064731 PMCID: PMC11279609 DOI: 10.3390/nu16142288] [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: 05/26/2024] [Revised: 07/14/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024] Open
Abstract
Malnutrition poses a critical challenge in inflammatory bowel disease, with the potential to detrimentally impact medical treatment, surgical outcomes, and general well-being. Parenteral nutrition is crucial in certain clinical scenarios, such as with patients suffering from short bowel syndrome, intestinal insufficiency, high-yielding gastrointestinal fistula, or complete small bowel obstruction, to effectively manage malnutrition. Nevertheless, research over the years has attempted to define the potential effects of parenteral nutrition on the intestinal barrier and the composition of the gut microbiota. In this narrative review, we have gathered and analyzed findings from both preclinical and clinical studies on this topic. Based on existing evidence, there is a clear correlation between short- and long-term parenteral nutrition and negative effects on the intestinal system. These include mucosal atrophic damage and immunological and neuroendocrine dysregulation, as well as alterations in gut barrier permeability and microbiota composition. However, the mechanistic role of these changes in inflammatory bowel disease remains unclear. Therefore, further research is necessary to effectively address the numerous gaps and unanswered questions pertaining to these issues.
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Affiliation(s)
- Carlo Covello
- Gastroenterology Department, Centro di Malattie dell’Apparato Digerente (CEMAD), Center for Diagnosis and Treatment of Digestive Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (C.C.); (F.D.V.); (A.D.G.); (A.G.)
| | - Guia Becherucci
- UOS Malattie Infiammatorie Croniche Intestinali, Centro di Malattie dell’Apparato Digerente (CEMAD), Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.B.); (F.S.)
| | - Federica Di Vincenzo
- Gastroenterology Department, Centro di Malattie dell’Apparato Digerente (CEMAD), Center for Diagnosis and Treatment of Digestive Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (C.C.); (F.D.V.); (A.D.G.); (A.G.)
| | - Angelo Del Gaudio
- Gastroenterology Department, Centro di Malattie dell’Apparato Digerente (CEMAD), Center for Diagnosis and Treatment of Digestive Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (C.C.); (F.D.V.); (A.D.G.); (A.G.)
| | - Marco Pizzoferrato
- UOC Gastroenterologia, Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy; (M.P.); (G.C.)
| | - Giovanni Cammarota
- UOC Gastroenterologia, Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168 Rome, Italy; (M.P.); (G.C.)
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Antonio Gasbarrini
- Gastroenterology Department, Centro di Malattie dell’Apparato Digerente (CEMAD), Center for Diagnosis and Treatment of Digestive Diseases, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (C.C.); (F.D.V.); (A.D.G.); (A.G.)
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Franco Scaldaferri
- UOS Malattie Infiammatorie Croniche Intestinali, Centro di Malattie dell’Apparato Digerente (CEMAD), Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.B.); (F.S.)
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Maria Chiara Mentella
- Department of Translational Medicine and Surgery, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
- UOC di Nutrizione Clinica, Dipartimento Scienze Mediche e Chirurgiche Addominali ed Endocrino-Metaboliche, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
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19
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Chen W, Li Y, Wang W, Gao S, Hu J, Xiang B, Wu D, Jiao N, Xu T, Zhi M, Zhu L, Zhu R. Enhanced microbiota profiling in patients with quiescent Crohn's disease through comparison with paired healthy first-degree relatives. Cell Rep Med 2024; 5:101624. [PMID: 38942021 PMCID: PMC11293350 DOI: 10.1016/j.xcrm.2024.101624] [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: 11/04/2023] [Revised: 04/09/2024] [Accepted: 06/07/2024] [Indexed: 06/30/2024]
Abstract
Prior studies indicate no correlation between the gut microbes of healthy first-degree relatives (HFDRs) of patients with Crohn's disease (CD) and the development of CD. Here, we utilize HFDRs as controls to examine the microbiota and metabolome in individuals with active (CD-A) and quiescent (CD-R) CD, thereby minimizing the influence of genetic and environmental factors. When compared to non-relative controls, the use of HFDR controls identifies fewer differential taxa. Faecalibacterium, Dorea, and Fusicatenibacter are decreased in CD-R, independent of inflammation, and correlated with fecal short-chain fatty acids (SCFAs). Validation with a large multi-center cohort confirms decreased Faecalibacterium and other SCFA-producing genera in CD-R. Classification models based on these genera distinguish CD from healthy individuals and demonstrate superior diagnostic power than models constructed with markers identified using unrelated controls. Furthermore, these markers exhibited limited discriminatory capabilities for other diseases. Finally, our results are validated across multiple cohorts, underscoring their robustness and potential for diagnostic and therapeutic applications.
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Affiliation(s)
- Wanning Chen
- Department of Gastroenterology, the Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P.R. China
| | - Yichen Li
- Medical College, Jiaying University, Meizhou 514031, P. R. China; Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, P.R. China; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China
| | - Wenxia Wang
- Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China
| | - Sheng Gao
- Department of Gastroenterology, the Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P.R. China
| | - Jun Hu
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China; Department of Gastroenterology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China
| | - Bingjie Xiang
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China; Department of Gastroenterology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China
| | - Dingfeng Wu
- Department of Nephrology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310058, Zhejiang, P.R. China
| | - Na Jiao
- Department of Nephrology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310058, Zhejiang, P.R. China
| | - Tao Xu
- Medical College, Jiaying University, Meizhou 514031, P. R. China; Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, P.R. China
| | - Min Zhi
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China; Department of Gastroenterology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China.
| | - Lixin Zhu
- Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P.R. China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology; Biomedical Innovation Center; The Sixth Affiliated Hospital, Sun Yat-sen University; Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou 510655, P.R. China.
| | - Ruixin Zhu
- Department of Gastroenterology, the Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P.R. China.
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20
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Güven Gülhan Ü, Nikerel E, Çakır T, Erdoğan Sevilgen F, Durmuş S. Species-level identification of enterotype-specific microbial markers for colorectal cancer and adenoma. Mol Omics 2024; 20:397-416. [PMID: 38780313 DOI: 10.1039/d4mo00016a] [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: 05/25/2024]
Abstract
Enterotypes have been shown to be an important factor for population stratification based on gut microbiota composition, leading to a better understanding of human health and disease states. Classifications based on compositional patterns will have implications for personalized microbiota-based solutions. There have been limited enterotype based studies on colorectal adenoma and cancer. Here, an enterotype-based meta-analysis of fecal shotgun metagenomic studies was performed, including 1579 samples of healthy controls (CTR), colorectal adenoma (ADN) and colorectal cancer (CRC) in total. Gut microbiota of healthy people were clustered into three enterotypes (Ruminococcus-, Bacteroides- and Prevotella-dominated enterotypes). Reference-based enterotype assignments were performed for CRC and ADN samples, using the supervised machine learning algorithm, K-nearest neighbors. Differential abundance analyses and random forest classification were conducted on each enterotype between healthy controls and CRC-ADN groups, revealing novel enterotype-specific microbial markers for non-invasive CRC screening strategies. Furthermore, we identified microbial species unique to each enterotype that play a role in the production of secondary bile acids and short-chain fatty acids, unveiling the correlation between cancer-associated gut microbes and dietary patterns. The enterotype-based approach in this study is promising in elucidating the mechanisms of differential gut microbiome profiles, thereby improving the efficacy of personalized microbiota-based solutions.
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Affiliation(s)
- Ünzile Güven Gülhan
- Department of Bioengineering, Gebze Technical University, Gebze, TR 41400, Turkey.
| | - Emrah Nikerel
- Department of Genetics and Bioengineering, Yeditepe University, Istanbul, TR 34755, Turkey
| | - Tunahan Çakır
- Department of Bioengineering, Gebze Technical University, Gebze, TR 41400, Turkey.
- PhiTech Bioinformatics, Gebze, TR 41470, Turkey
| | - Fatih Erdoğan Sevilgen
- The Institute for Data Science & Artificial Intelligence, Boğaziçi University, Istanbul, TR 34342, Turkey
- PhiTech Bioinformatics, Gebze, TR 41470, Turkey
| | - Saliha Durmuş
- Department of Bioengineering, Gebze Technical University, Gebze, TR 41400, Turkey.
- PhiTech Bioinformatics, Gebze, TR 41470, Turkey
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21
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Senthakumaran T, Tannæs TM, Moen AEF, Brackmann SA, Jahanlu D, Rounge TB, Bemanian V, Tunsjø HS. Detection of colorectal-cancer-associated bacterial taxa in fecal samples using next-generation sequencing and 19 newly established qPCR assays. Mol Oncol 2024. [PMID: 38970464 DOI: 10.1002/1878-0261.13700] [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: 12/12/2023] [Revised: 05/15/2024] [Accepted: 06/28/2024] [Indexed: 07/08/2024] Open
Abstract
We have previously identified increased levels of distinct bacterial taxa within mucosal biopsies from colorectal cancer (CRC) patients. Following prior research, the aim of this study was to investigate the detection of the same CRC-associated bacteria in fecal samples and to evaluate the suitability of fecal samples as a non-invasive material for the detection of CRC-associated bacteria. Next-generation sequencing (NGS) of the 16S ribosomal RNA (rRNA) V4 region was performed to evaluate the detection of the CRC-associated bacteria in the fecal microbiota of cancer patients, patients with adenomatous polyp and healthy controls. Furthermore, 19 novel species-specific quantitative PCR (qPCR) assays were established to detect the CRC-associated bacteria. Approximately, 75% of the bacterial taxa identified in biopsies were reflected in fecal samples. NGS failed to detect low-abundance CRC-associated taxa in fecal samples, whereas qPCR exhibited high sensitivity and specificity in identifying all targeted taxa. Comparison of fecal microbial composition between the different patient groups showed enrichment of Fusobacterium nucleatum, Parvimonas micra, and Gemella morbillorum in cancer patients. Our findings suggest that low-abundance mucosa-associated bacteria can be detected in fecal samples using sensitive qPCR assays.
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Affiliation(s)
| | - Tone M Tannæs
- Section for Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway
- Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, Norway
| | - Aina E F Moen
- Section for Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway
- Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, Norway
- Department of Methods Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephan A Brackmann
- Department of Gastroenterology, Division of Medicine, Akershus University Hospital, Lørenskog, Norway
- Institute for Clinical Medicine, University of Oslo, Norway
| | - David Jahanlu
- Department of Life Sciences and Health, Oslo Metropolitan University, Norway
| | - Trine B Rounge
- Department of Pharmacy, Centre for Bioinformatics, University of Oslo, Norway
- Department of Research, Cancer Registry of Norway, Oslo, Norway
| | - Vahid Bemanian
- Department of Pathology, Akershus University Hospital, Lørenskog, Norway
| | - Hege S Tunsjø
- Department of Life Sciences and Health, Oslo Metropolitan University, Norway
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22
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Oh E, Lee H. DeepPIG: deep neural network architecture with pairwise connected layers and stochastic gates using knockoff frameworks for feature selection. Sci Rep 2024; 14:15582. [PMID: 38971807 PMCID: PMC11227546 DOI: 10.1038/s41598-024-66061-6] [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: 03/28/2024] [Accepted: 06/26/2024] [Indexed: 07/08/2024] Open
Abstract
Selecting relevant feature subsets is essential for machine learning applications. Among the feature selection techniques, the knockoff filter procedure proposes a unique framework that minimizes false discovery rates (FDR). However, employing a deep neural network architecture for a knockoff filter framework requires higher detection power. Using the knockoff filter framework, we present a Deep neural network with PaIrwise connected layers integrated with stochastic Gates (DeepPIG) for the feature selection model. DeepPIG exhibited better detection power in synthetic data than the baseline and recent models such as Deep feature selection using Paired-Input Nonlinear Knockoffs (DeepPINK), Stochastic Gates (STG), and SHapley Additive exPlanations (SHAP) while not violating the preselected FDR level, especially when the signal of the features were weak. The selected features determined by DeepPIG demonstrated superior classification performance compared with the baseline model in real-world data analyses, including the prediction of certain cancer prognosis and classification tasks using microbiome and single-cell datasets. In conclusion, DeepPIG is a robust feature selection approach even when the signals of features are weak. Source code is available at https://github.com/DMCB-GIST/DeepPIG .
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Affiliation(s)
- Euiyoung Oh
- Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science, Gwangju, 61005, South Korea
| | - Hyunju Lee
- Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science, Gwangju, 61005, South Korea.
- Gwangju Institute of Science and Technology, Artificial Intelligence Graduate School, Gwangju, 61005, South Korea.
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23
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Ryu EP, Gautam Y, Proctor DM, Bhandari D, Tandukar S, Gupta M, Gautam GP, Relman DA, Shibl AA, Sherchand JB, Jha AR, Davenport ER. Nepali oral microbiomes reflect a gradient of lifestyles from traditional to industrialized. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.01.601557. [PMID: 39005279 PMCID: PMC11244963 DOI: 10.1101/2024.07.01.601557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Background Lifestyle plays an important role in shaping the gut microbiome. However, its contributions to the oral microbiome remains less clear, due to the confounding effects of geography and methodology in investigations of populations studied to date. Furthermore, while the oral microbiome seems to differ between foraging and industrialized populations, we lack insight into whether transitions to and away from agrarian lifestyles shape the oral microbiota. Given the growing interest in so-called 'vanishing microbiomes' potentially being a risk factor for increased disease prevalence in industrialized populations, it is important that we distinguish lifestyle from geography in the study of microbiomes across populations. Results Here, we investigate salivary microbiomes of 63 Nepali individuals representing a spectrum of lifestyles: foraging, subsistence farming (individuals that transitioned from foraging to farming within the last 50 years), agriculturalists (individuals that have transitioned to farming for at least 300 years), and industrialists (expatriates that immigrated to the United States within the last 20 years). We characterize the role of lifestyle in microbial diversity, identify microbes that differ between lifestyles, and pinpoint specific lifestyle factors that may be contributing to differences in the microbiomes across populations. Contrary to prevailing views, when geography is controlled for, oral microbiome alpha diversity does not differ significantly across lifestyles. Microbiome composition, however, follows the gradient of lifestyles from foraging through agrarianism to industrialism, supporting the notion that lifestyle indeed plays a role in the oral microbiome. Relative abundances of several individual taxa, including Streptobacillus and an unclassified Porphyromonadaceae genus, also mirror lifestyle. Finally, we identify specific lifestyle factors associated with microbiome composition across the gradient of lifestyles, including smoking and grain source. Conclusion Our findings demonstrate that by controlling for geography, we can isolate an important role for lifestyle in determining oral microbiome composition. In doing so, we highlight the potential contributions of several lifestyle factors, underlining the importance of carefully examining the oral microbiome across lifestyles to improve our understanding of global microbiomes.
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Affiliation(s)
- Erica P. Ryu
- Department of Biology, Pennsylvania State University, University Park, PA
| | - Yoshina Gautam
- Genetic Heritage Group, Program in Biology, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Diana M. Proctor
- Microbial Genomics Section, Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Dinesh Bhandari
- Public Health Research Laboratory, Institute of Medicine, Maharajgunj, Kathmandu, Nepal
- School of Public Health, University of Adelaide, South Australia, Australia
| | - Sarmila Tandukar
- Public Health Research Laboratory, Institute of Medicine, Maharajgunj, Kathmandu, Nepal
- Organization for Public Health and Environment Management, Lalitpur, Bagmati, Nepal
| | - Meera Gupta
- Department of Biology, Pennsylvania State University, University Park, PA
| | | | - David A. Relman
- Departments of Medicine, and of Microbiology & Immunology, Stanford University, Stanford, CA
- Section of Infectious Diseases, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA
| | - Ahmed A. Shibl
- Genetic Heritage Group, Program in Biology, New York University Abu Dhabi, Abu Dhabi, UAE
- Center for Genomics and Systems Biology, and Public Health Research Center, New York University Abu Dhabi, Abu Dhabi, UAE
| | | | - Aashish R. Jha
- Genetic Heritage Group, Program in Biology, New York University Abu Dhabi, Abu Dhabi, UAE
- Center for Genomics and Systems Biology, and Public Health Research Center, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Emily R. Davenport
- Department of Biology, Pennsylvania State University, University Park, PA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA
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24
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Nakatsu G, Andreeva N, MacDonald MH, Garrett WS. Interactions between diet and gut microbiota in cancer. Nat Microbiol 2024; 9:1644-1654. [PMID: 38907007 DOI: 10.1038/s41564-024-01736-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 05/20/2024] [Indexed: 06/23/2024]
Abstract
Dietary patterns and specific dietary components, in concert with the gut microbiota, can jointly shape susceptibility, resistance and therapeutic response to cancer. Which diet-microbial interactions contribute to or mitigate carcinogenesis and how they work are important questions in this growing field. Here we interpret studies of diet-microbial interactions to assess dietary determinants of intestinal colonization by opportunistic and oncogenic bacteria. We explore how diet-induced expansion of specific gut bacteria might drive colonic epithelial tumorigenesis or create immuno-permissive tumour milieus and introduce recent findings that provide insight into these processes. Additionally, we describe available preclinical models that are widely used to study diet, microbiome and cancer interactions. Given the rising clinical interest in dietary modulations in cancer treatment, we highlight promising clinical trials that describe the effects of different dietary alterations on the microbiome and cancer outcomes.
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Affiliation(s)
- Geicho Nakatsu
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Boston, MA, USA
| | - Natalia Andreeva
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Boston, MA, USA
| | - Meghan H MacDonald
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Harvard Chan Microbiome in Public Health Center, Boston, MA, USA
| | - Wendy S Garrett
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Harvard Chan Microbiome in Public Health Center, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
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25
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Ran Z, Yang J, Liu L, Wu S, An Y, Hou W, Cheng T, Zhang Y, Zhang Y, Huang Y, Zhang Q, Wan J, Li X, Xing B, Ye Y, Xu P, Chen Z, Zhao J, Li R. Chronic PM 2.5 exposure disrupts intestinal barrier integrity via microbial dysbiosis-triggered TLR2/5-MyD88-NLRP3 inflammasome activation. ENVIRONMENTAL RESEARCH 2024; 258:119415. [PMID: 38906446 DOI: 10.1016/j.envres.2024.119415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 05/31/2024] [Accepted: 06/11/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND PM2.5, a known public health risk, is increasingly linked to intestinal disorders, however, the mechanisms of its impact are not fully understood. PURPOSE This study aimed to explore the impact of chronic PM2.5 exposure on intestinal barrier integrity and to uncover the underlying molecular mechanisms. METHODS C57BL/6 J mice were exposed to either concentrated ambient PM2.5 (CPM) or filtered air (FA) for six months to simulate urban pollution conditions. We evaluated intestinal barrier damage, microbial shifts, and metabolic changes through histopathology, metagenomics, and metabolomics. Analysis of the TLR signaling pathway was also conducted. RESULTS The mean concentration of PM2.5 in the CPM exposure chamber was consistently measured at 70.9 ± 26.8 μg/m³ throughout the study period. Our findings show that chronic CPM exposure significantly compromises intestinal barrier integrity, as indicated by reduced expression of the key tight junction proteins Occludin and Tjp1/Zo-1. Metagenomic sequencing revealed significant shifts in the microbial landscape, identifying 35 differentially abundant species. Notably, there was an increase in pro-inflammatory nongastric Helicobacter species and a decrease in beneficial bacteria, such as Lactobacillus intestinalis, Lactobacillus sp. ASF360, and Eubacterium rectale. Metabolomic analysis further identified 26 significantly altered metabolites commonly associated with intestinal diseases. A strong correlation between altered bacterial species and metabolites was also observed. For example, 4 Helicobacter species all showed positive correlations with 13 metabolites, including Lactate, Bile acids, Pyruvate and Glutamate. Additionally, increased expression levels of TLR2, TLR5, Myd88, and NLRP3 proteins were noted, and their expression patterns showed a strong correlation, suggesting a possible involvement of the TLR2/5-MyD88-NLRP3 signaling pathway. CONCLUSIONS Chronic CPM exposure induces intestinal barrier dysfunction, microbial dysbiosis, metabolic imbalance, and activation of the TLR2/5-MyD88-NLRP3 inflammasome. These findings highlight the urgent need for intervention strategies to mitigate the detrimental effects of air pollution on intestinal health and identify potential therapeutic targets.
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Affiliation(s)
- Zihan Ran
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Department of Pathology, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Road, Shanghai 201318, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Science, Fudan University, 2005 Songhu Road, Shanghai 200438, China; Greater Bay Area Institute of Precision Medicine, 115 Jiaoxi Road, Guangzhou 511458, China
| | - Liang Liu
- Clinical Research Unit, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shaobo Wu
- Department of Laboratory Medicine, Tinglin Hospital of Jinshan District, No. 80 Siping North Road, Shanghai 201505, China
| | - YanPeng An
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Science, Fudan University, 2005 Songhu Road, Shanghai 200438, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Science, Fudan University, 2005 Songhu Road, Shanghai 200438, China
| | - Tianyuan Cheng
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Youyi Zhang
- School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yiqing Zhang
- Department of Pathology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China
| | - Yechao Huang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Science, Fudan University, 2005 Songhu Road, Shanghai 200438, China
| | - Qianyue Zhang
- The Core Laboratory in Medical Center of Clinical Research, Department of Molecular Diagnostic & Endocrinology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine, Shanghai 200011, China
| | - Jiaping Wan
- The Core Laboratory in Medical Center of Clinical Research, Department of Molecular Diagnostic & Endocrinology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine, Shanghai 200011, China
| | - Xuemei Li
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Department of Pathology, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Road, Shanghai 201318, China
| | - Baoling Xing
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Department of Pathology, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Road, Shanghai 201318, China
| | - Yuchen Ye
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Department of Pathology, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Road, Shanghai 201318, China
| | - Penghao Xu
- School of Biological Sciences, Georgia Insitute of Technology, Atlanta, GA, USA
| | - Zhenghu Chen
- Shanghai Key Laboratory of Molecular Imaging, Zhoupu Hospital, Department of Pathology, Shanghai University of Medicine and Health Sciences, 279 Zhouzhu Road, Shanghai 201318, China.
| | - Jinzhuo Zhao
- School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China.
| | - Rui Li
- The Core Laboratory in Medical Center of Clinical Research, Department of Molecular Diagnostic & Endocrinology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University (SJTU) School of Medicine, Shanghai 200011, China.
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26
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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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27
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Wang B, Luan Y. Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis. Front Genet 2024; 15:1369628. [PMID: 38903761 PMCID: PMC11188486 DOI: 10.3389/fgene.2024.1369628] [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: 01/12/2024] [Accepted: 05/13/2024] [Indexed: 06/22/2024] Open
Abstract
Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods that aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes in three simulation scenarios and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in Root Mean Squared Error (RMSE) of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.
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Affiliation(s)
- Beibei Wang
- Frontier Science Center for Nonlinear Expectations, Ministry of Education, Qingdao, China
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
- School of Mathematics, Shandong University, Jinan, China
| | - Yihui Luan
- Frontier Science Center for Nonlinear Expectations, Ministry of Education, Qingdao, China
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
- School of Mathematics, Shandong University, Jinan, China
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28
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Liu Z, Zhang Q, Zhang H, Yi Z, Ma H, Wang X, Wang J, Liu Y, Zheng Y, Fang W, Huang P, Liu X. Colorectal cancer microbiome programs DNA methylation of host cells by affecting methyl donor metabolism. Genome Med 2024; 16:77. [PMID: 38840170 PMCID: PMC11151592 DOI: 10.1186/s13073-024-01344-1] [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: 09/12/2023] [Accepted: 05/09/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) arises from complex interactions between host and environment, which include the gut and tissue microbiome. It is hypothesized that epigenetic regulation by gut microbiota is a fundamental interface by which commensal microbes dynamically influence intestinal biology. The aim of this study is to explore the interplay between gut and tissue microbiota and host DNA methylation in CRC. METHODS Metagenomic sequencing of fecal samples was performed on matched CRC patients (n = 18) and healthy controls (n = 18). Additionally, tissue microbiome was profiled with 16S rRNA gene sequencing on tumor (n = 24) and tumor-adjacent normal (n = 24) tissues of CRC patients, while host DNA methylation was assessed through whole-genome bisulfite sequencing (WGBS) in a subset of 13 individuals. RESULTS Our analysis revealed substantial alterations in the DNA methylome of CRC tissues compared to adjacent normal tissues. An extensive meta-analysis, incorporating publicly available and in-house data, identified significant shifts in microbial-derived methyl donor-related pathways between tumor and adjacent normal tissues. Of note, we observed a pronounced enrichment of microbial-associated CpGs within the promoter regions of genes in adjacent normal tissues, a phenomenon notably absent in tumor tissues. Furthermore, we established consistent and recurring associations between methylation patterns of tumor-related genes and specific bacterial taxa. CONCLUSIONS This study emphasizes the pivotal role of the gut microbiota and pathogenic bacteria in dynamically shaping DNA methylation patterns, impacting physiological homeostasis, and contributing to CRC tumorigenesis. These findings provide valuable insights into the intricate host-environment interactions in CRC development and offer potential avenues for therapeutic interventions in this disease.
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Affiliation(s)
- Zhi Liu
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Qingqing Zhang
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Hong Zhang
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Zhongyuan Yi
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Huihui Ma
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xiaoyi Wang
- Core Facility Center, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China
| | - Jingjing Wang
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China
| | - Yang Liu
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yi Zheng
- Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Weijia Fang
- Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Ping Huang
- Department of Surgery, The Third Affiliated Hospital, Nanjing Medical University, Nanjing, 211166, China.
| | - Xingyin Liu
- Department of Pathogen Biology-Microbiology Division, State Key Laboratory of Reproductive Medicine, Key Laboratory of Pathogen of Jiangsu Province, Key Laboratory of Human Functional Genomics of Jiangsu Province, Center of Global Health, Nanjing Medical University, Nanjing, 211166, China.
- The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, China.
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29
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Pulvirenti F, Giufrè M, Pentimalli TM, Camilli R, Milito C, Villa A, Sculco E, Cerquetti M, Pantosti A, Quinti I. Oropharyngeal microbial ecosystem perturbations influence the risk for acute respiratory infections in common variable immunodeficiency. Front Immunol 2024; 15:1371118. [PMID: 38873612 PMCID: PMC11169596 DOI: 10.3389/fimmu.2024.1371118] [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: 01/15/2024] [Accepted: 05/13/2024] [Indexed: 06/15/2024] Open
Abstract
Background The respiratory tract microbiome is essential for human health and well-being and is determined by genetic, lifestyle, and environmental factors. Patients with Common Variable Immunodeficiency (CVID) suffer from respiratory and intestinal tract infections, leading to chronic diseases and increased mortality rates. While CVID patients' gut microbiota have been analyzed, data on the respiratory microbiome ecosystem are limited. Objective This study aims to analyze the bacterial composition of the oropharynx of adults with CVID and its link with clinical and immunological features and risk for respiratory acute infections. Methods Oropharyngeal samples from 72 CVID adults and 26 controls were collected in a 12-month prospective study. The samples were analyzed by metagenomic bacterial 16S ribosomal RNA sequencing and processed using the Quantitative Insights Into Microbial Ecology (QIME) pipeline. Differentially abundant species were identified and used to build a dysbiosis index. A machine learning model trained on microbial abundance data was used to test the power of microbiome alterations to distinguish between healthy individuals and CVID patients. Results Compared to controls, the oropharyngeal microbiome of CVID patients showed lower alpha- and beta-diversity, with a relatively increased abundance of the order Lactobacillales, including the family Streptococcaceae. Intra-CVID analysis identified age >45 years, COPD, lack of IgA, and low residual IgM as associated with a reduced alpha diversity. Expansion of Haemophilus and Streptococcus genera was observed in patients with undetectable IgA and COPD, independent from recent antibiotic use. Patients receiving azithromycin as antibiotic prophylaxis had a higher dysbiosis score. Expansion of Haemophilus and Anoxybacillus was associated with acute respiratory infections within six months. Conclusions CVID patients showed a perturbed oropharynx microbiota enriched with potentially pathogenic bacteria and decreased protective species. Low residual levels of IgA/IgM, chronic lung damage, anti antibiotic prophylaxis contributed to respiratory dysbiosis.
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Affiliation(s)
- Federica Pulvirenti
- Reference Center for Primary Immune Deficiencies, Azienda Ospedaliero Universitaria (AOU) Policlinico Umberto I, Rome, Italy
| | - Maria Giufrè
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Tancredi M. Pentimalli
- Laboratory for Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin School of Integrative Oncology (BSIO), Berlin, Germany
| | - Romina Camilli
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Cinzia Milito
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Annalisa Villa
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Eleonora Sculco
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Marina Cerquetti
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Annalisa Pantosti
- Department of Infectious Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Isabella Quinti
- Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy
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30
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Teixeira M, Silva F, Ferreira RM, Pereira T, Figueiredo C, Oliveira HP. A review of machine learning methods for cancer characterization from microbiome data. NPJ Precis Oncol 2024; 8:123. [PMID: 38816569 PMCID: PMC11139966 DOI: 10.1038/s41698-024-00617-7] [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: 01/15/2024] [Accepted: 05/17/2024] [Indexed: 06/01/2024] Open
Abstract
Recent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.
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Affiliation(s)
- Marco Teixeira
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal.
- Faculty of Engineering, University of Porto, Porto, Portugal.
| | - Francisco Silva
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Science, University of Porto, Porto, Portugal
| | - Rui M Ferreira
- Ipatimup - Institute of Molecular Pathology and Immunology of the University of Porto, Porto, Portugal
- Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
| | - Tania Pereira
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal
| | - Ceu Figueiredo
- Ipatimup - Institute of Molecular Pathology and Immunology of the University of Porto, Porto, Portugal
- Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal
- Faculty of Medicine, University of Porto, Porto, Portugal
| | - Hélder P Oliveira
- Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal
- Faculty of Science, University of Porto, Porto, Portugal
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31
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Messaritakis I, Koulouris A, Boukla E, Vogiatzoglou K, Lagkouvardos I, Intze E, Sfakianaki M, Chondrozoumaki M, Karagianni M, Athanasakis E, Xynos E, Tsiaoussis J, Christodoulakis M, Flamourakis ME, Tsagkataki ES, Giannikaki L, Chliara E, Mavroudis D, Tzardi M, Souglakos J. Exploring Gut Microbiome Composition and Circulating Microbial DNA Fragments in Patients with Stage II/III Colorectal Cancer: A Comprehensive Analysis. Cancers (Basel) 2024; 16:1923. [PMID: 38792001 PMCID: PMC11119035 DOI: 10.3390/cancers16101923] [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: 03/31/2024] [Revised: 05/15/2024] [Accepted: 05/17/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) significantly contributes to cancer-related mortality, necessitating the exploration of prognostic factors beyond TNM staging. This study investigates the composition of the gut microbiome and microbial DNA fragments in stage II/III CRC. METHODS A cohort of 142 patients with stage II/III CRC and 91 healthy controls underwent comprehensive microbiome analysis. Fecal samples were collected for 16S rRNA sequencing, and blood samples were tested for the presence of microbial DNA fragments. De novo clustering analysis categorized individuals based on their microbial profiles. Alpha and beta diversity metrics were calculated, and taxonomic profiling was conducted. RESULTS Patients with CRC exhibited distinct microbial composition compared to controls. Beta diversity analysis confirmed CRC-specific microbial profiles. Taxonomic profiling revealed unique taxonomies in the patient cohort. De novo clustering separated individuals into distinct groups, with specific microbial DNA fragment detection associated with certain patient clusters. CONCLUSIONS The gut microbiota can differentiate patients with CRC from healthy individuals. Detecting microbial DNA fragments in the bloodstream may be linked to CRC prognosis. These findings suggest that the gut microbiome could serve as a prognostic factor in stage II/III CRC. Identifying specific microbial markers associated with CRC prognosis has potential clinical implications, including personalized treatment strategies and reduced healthcare costs. Further research is needed to validate these findings and uncover underlying mechanisms.
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Affiliation(s)
- Ippokratis Messaritakis
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Andreas Koulouris
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Eleni Boukla
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Konstantinos Vogiatzoglou
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Ilias Lagkouvardos
- Department of Clinical Microbiology, School of Medicine, University of Crete, 70013 Heraklion, Greece; (I.L.); (E.I.)
| | - Evangelia Intze
- Department of Clinical Microbiology, School of Medicine, University of Crete, 70013 Heraklion, Greece; (I.L.); (E.I.)
| | - Maria Sfakianaki
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Maria Chondrozoumaki
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Michaela Karagianni
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
| | - Elias Athanasakis
- Department of General Surgery, Heraklion University Hospital, 71100 Heraklion, Greece;
| | - Evangelos Xynos
- Department of Surgery, Creta Interclinic Hospital of Heraklion, 71305 Heraklion, Greece
| | - John Tsiaoussis
- Department of Anatomy, School of Medicine, University of Crete, 70013 Heraklion, Greece;
| | | | | | - Eleni S. Tsagkataki
- Department of General Surgery, Venizeleio General Hospital, 71409 Heraklion, Greece (M.E.F.)
| | - Linda Giannikaki
- Histopathology, Venizeleio General Hospital, 71409 Heraklion, Greece
| | - Evdoxia Chliara
- Histopathology, Venizeleio General Hospital, 71409 Heraklion, Greece
| | - Dimitrios Mavroudis
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
- Department of Medical Oncology, University Hospital of Heraklion, 71110 Heraklion, Greece
| | - Maria Tzardi
- Laboratory of Pathology, University General Hospital of Heraklion, 70013 Heraklion, Greece;
| | - John Souglakos
- Laboratory of Translational Oncology, Medical School, University of Crete, 70013 Heraklion, Greece; (A.K.); (M.C.); (D.M.)
- Department of Medical Oncology, University Hospital of Heraklion, 71110 Heraklion, Greece
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Simeon A, Radovanović M, Lončar-Turukalo T, Ceci M, Brdar S, Pio G. Multi-class boosting for the analysis of multiple incomplete views on microbiome data. BMC Bioinformatics 2024; 25:188. [PMID: 38745112 PMCID: PMC11092168 DOI: 10.1186/s12859-024-05767-w] [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: 08/16/2023] [Accepted: 04/04/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Microbiome dysbiosis has recently been associated with different diseases and disorders. In this context, machine learning (ML) approaches can be useful either to identify new patterns or learn predictive models. However, data to be fed to ML methods can be subject to different sampling, sequencing and preprocessing techniques. Each different choice in the pipeline can lead to a different view (i.e., feature set) of the same individuals, that classical (single-view) ML approaches may fail to simultaneously consider. Moreover, some views may be incomplete, i.e., some individuals may be missing in some views, possibly due to the absence of some measurements or to the fact that some features are not available/applicable for all the individuals. Multi-view learning methods can represent a possible solution to consider multiple feature sets for the same individuals, but most existing multi-view learning methods are limited to binary classification tasks or cannot work with incomplete views. RESULTS We propose irBoost.SH, an extension of the multi-view boosting algorithm rBoost.SH, based on multi-armed bandits. irBoost.SH solves multi-class classification tasks and can analyze incomplete views. At each iteration, it identifies one winning view using adversarial multi-armed bandits and uses its predictions to update a shared instance weight distribution in a learning process based on boosting. In our experiments, performed on 5 multi-view microbiome datasets, the model learned by irBoost.SH always outperforms the best model learned from a single view, its closest competitor rBoost.SH, and the model learned by a multi-view approach based on feature concatenation, reaching an improvement of 11.8% of the F1-score in the prediction of the Autism Spectrum disorder and of 114% in the prediction of the Colorectal Cancer disease. CONCLUSIONS The proposed method irBoost.SH exhibited outstanding performances in our experiments, also compared to competitor approaches. The obtained results confirm that irBoost.SH can fruitfully be adopted for the analysis of microbiome data, due to its capability to simultaneously exploit multiple feature sets obtained through different sequencing and preprocessing pipelines.
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Affiliation(s)
- Andrea Simeon
- BioSense Institute, University of Novi Sad, dr Zorana Djindjića 1, Novi Sad, 21000, Serbia.
| | - Miloš Radovanović
- Faculty of Sciences, University of Novi Sad, Trg Dositeja Obradovića 3, Novi Sad, 21000, Serbia
| | - Tatjana Lončar-Turukalo
- Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, Novi Sad, 21000, Serbia
| | - Michelangelo Ceci
- Department of Computer Science, University Bari Aldo Moro, Via Orabona 4, 70125, Bari, Italy
- Big Data Laboratory, National Interuniversity Consortium for Informatics (CINI), Via Ariosto 25, 00185, Rome, Italy
- Department of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia
| | - Sanja Brdar
- BioSense Institute, University of Novi Sad, dr Zorana Djindjića 1, Novi Sad, 21000, Serbia
| | - Gianvito Pio
- Department of Computer Science, University Bari Aldo Moro, Via Orabona 4, 70125, Bari, Italy.
- Big Data Laboratory, National Interuniversity Consortium for Informatics (CINI), Via Ariosto 25, 00185, Rome, Italy.
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Huang Q, Butaye P, Ng PH, Zhang J, Cai W, St-Hilaire S. Impact of low-dose ozone nanobubble treatments on antimicrobial resistance genes in pond water. Front Microbiol 2024; 15:1393266. [PMID: 38812692 PMCID: PMC11136503 DOI: 10.3389/fmicb.2024.1393266] [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: 02/28/2024] [Accepted: 04/22/2024] [Indexed: 05/31/2024] Open
Abstract
Antimicrobial resistance (AMR) poses a significant global health threat as the silent pandemic. Because of the use of antimicrobials in aquaculture systems, fish farms may be potential reservoirs for the dissemination of antimicrobial resistance genes (ARGs). Treatments with disinfectants have been promoted to reduce the use of antibiotics; however, the effect of these types of treatments on AMR or ARGs is not well known. This study aimed to evaluate the effects of low dose ozone treatments (0.15 mg/L) on ARG dynamics in pond water using metagenomic shotgun sequencing analysis. The results suggested that ozone disinfection can increase the relative abundance of acquired ARGs and intrinsic efflux mediated ARGs found in the resistance nodulation cell division (RND) family. Notably, a co-occurrence of efflux and non-efflux ARGs within the same bacterial genera was also observed, with most of these genera dominating the bacterial population following ozone treatments. These findings suggest that ozone treatments may selectively favor the survival of bacterial genera harboring efflux ARGs, which may also have non-efflux ARGs. This study underscores the importance of considering the potential impacts of disinfection practices on AMR gene dissemination particularly in aquaculture settings where disinfectants are frequently used at low levels. Future endeavors should prioritize the evaluation of these strategies, as they may be associated with an increased risk of AMR in aquatic environments.
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Affiliation(s)
- Qianjun Huang
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Patrick Butaye
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
- Department of Pathobiology, Pharmacology and Zoological Medicine, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Pok Him Ng
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Ju Zhang
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Wenlong Cai
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Sophie St-Hilaire
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
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Jin M, Fan Q, Shang F, Zhang T, Ogino S, Liu H. Fusobacteria alterations are associated with colorectal cancer liver metastasis and a poor prognosis. Oncol Lett 2024; 27:235. [PMID: 38596264 PMCID: PMC11003219 DOI: 10.3892/ol.2024.14368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 02/01/2024] [Indexed: 04/11/2024] Open
Abstract
Liver metastasis is a major cause of mortality in patients with advanced stages of colorectal cancer (CRC). The gut microbiota has been demonstrated to influence the progression of liver diseases, potentially providing novel perspectives for diagnosis, treatment and research. However, the gut microbial characteristics in CRC with liver metastasis (LM) and with no liver metastasis (NLM) have not yet been fully established. In the present study, high-throughput 16S RNA sequencing technology was employed, in order to examine the gut microbial richness and composition in patients with CRC with LM or NLM. A discovery cohort (cohort 2; LM=18; NLM=36) and a validation cohort (cohort 3; LM=13; NLM=41) were established using fresh feces. In addition, primary carcinoma tissue samples were also analyzed (LM=8 and NLM=10) as a supplementary discovery cohort (cohort 1). The findings of the present study indicated that the intestinal microbiota richness and diversity were increased in the LM group as compared to the NLM group. A significant difference was observed in species composition between the LM and NLM group. In the two discovery cohorts with two different samples, the dominant phyla were consistent, but varied at lower taxonomic levels. Phylum Fusobacteria presented consistent and significant enrichment in LM group in both discovery cohorts. Furthermore, with the application of a random forest model and receiver operator characteristic curve analysis, Fusobacteria was identified as a potential biomarker for LM. Moreover, Fusobacteria was also a poor prognosis factor for survival. Importantly, the findings were reconfirmed in the validation cohort. On the whole, the findings of the present study demonstrated that CRC with LM and NLM exhibit distinct gut microbiota characteristics. Fusobacteria detection thus has potential for use in predicting LM and a poor prognosis of patients with CRC.
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Affiliation(s)
- Min Jin
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
| | - Qilin Fan
- Department of Gastroenterology, General Hospital of Central Theater Command, Wuhan, Hubei 430070, P.R. China
| | - Fumei Shang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
| | - Tao Zhang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
| | - Shuji Ogino
- Program in Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02212, USA
| | - Hongli Liu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China
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Conde‐Pérez K, Aja‐Macaya P, Buetas E, Trigo‐Tasende N, Nasser‐Ali M, Rumbo‐Feal S, Nión P, Arribas EM, Estévez LS, Otero‐Alén B, Noguera JF, Concha Á, Pardiñas‐López S, Carda‐Diéguez M, Gómez‐Randulfe I, Martínez‐Lago N, Ladra S, Aparicio LMA, Bou G, Mira Á, Vallejo JA, Poza M. The multispecies microbial cluster of Fusobacterium, Parvimonas, Bacteroides and Faecalibacterium as a precision biomarker for colorectal cancer diagnosis. Mol Oncol 2024; 18:1093-1122. [PMID: 38366793 PMCID: PMC11076999 DOI: 10.1002/1878-0261.13604] [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: 08/24/2023] [Revised: 12/27/2023] [Accepted: 01/26/2024] [Indexed: 02/18/2024] Open
Abstract
The incidence of colorectal cancer (CRC) has increased worldwide, and early diagnosis is crucial to reduce mortality rates. Therefore, new noninvasive biomarkers for CRC are required. Recent studies have revealed an imbalance in the oral and gut microbiomes of patients with CRC, as well as impaired gut vascular barrier function. In the present study, the microbiomes of saliva, crevicular fluid, feces, and non-neoplastic and tumor intestinal tissue samples of 93 CRC patients and 30 healthy individuals without digestive disorders (non-CRC) were analyzed by 16S rRNA metabarcoding procedures. The data revealed that Parvimonas, Fusobacterium, and Bacteroides fragilis were significantly over-represented in stool samples of CRC patients, whereas Faecalibacterium and Blautia were significantly over-abundant in the non-CRC group. Moreover, the tumor samples were enriched in well-known periodontal anaerobes, including Fusobacterium, Parvimonas, Peptostreptococcus, Porphyromonas, and Prevotella. Co-occurrence patterns of these oral microorganisms were observed in the subgingival pocket and in the tumor tissues of CRC patients, where they also correlated with other gut microbes, such as Hungatella. This study provides new evidence that oral pathobionts, normally located in subgingival pockets, can migrate to the colon and probably aggregate with aerobic bacteria, forming synergistic consortia. Furthermore, we suggest that the group composed of Fusobacterium, Parvimonas, Bacteroides, and Faecalibacterium could be used to design an excellent noninvasive fecal test for the early diagnosis of CRC. The combination of these four genera would significantly improve the reliability of a discriminatory test with respect to others that use a single species as a unique CRC biomarker.
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Affiliation(s)
- Kelly Conde‐Pérez
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Pablo Aja‐Macaya
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Elena Buetas
- Genomic and Health Department, FISABIO FoundationCenter for Advanced Research in Public HealthValenciaSpain
| | - Noelia Trigo‐Tasende
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Mohammed Nasser‐Ali
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Soraya Rumbo‐Feal
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Paula Nión
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Elsa Martín‐De Arribas
- Database Laboratory, Research Center for Information and Communication Technologies (CITIC)University of A Coruña (UDC)A CoruñaSpain
| | - Lara S. Estévez
- Pathology Service and BiobankUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Begoña Otero‐Alén
- Pathology Service and BiobankUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - José F. Noguera
- Surgery ServiceUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Ángel Concha
- Pathology Service and BiobankUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Simón Pardiñas‐López
- Periodontology and Oral Surgery, Pardiñas Medical Dental Clinic – Cell Therapy and Regenerative Medicine GroupInstitute of Biomedical Research (INIBIC)A CoruñaSpain
| | - Miguel Carda‐Diéguez
- Genomic and Health Department, FISABIO FoundationCenter for Advanced Research in Public HealthValenciaSpain
| | - Igor Gómez‐Randulfe
- Medical Oncology DepartmentUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | | | - Susana Ladra
- Database Laboratory, Research Center for Information and Communication Technologies (CITIC)University of A Coruña (UDC)A CoruñaSpain
| | - Luis M. A. Aparicio
- Medical Oncology DepartmentUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Germán Bou
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Álex Mira
- Genomic and Health Department, FISABIO FoundationCenter for Advanced Research in Public HealthValenciaSpain
| | - Juan A. Vallejo
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
| | - Margarita Poza
- Microbiome and Health Group (meiGAbiome), Microbiology Research Group, Institute of Biomedical Research (INIBIC) – Interdisciplinary Center for Chemistry and Biology (CICA) – University of A Coruña (UDC) – CIBER de Enfermedades Infecciosas (CIBERINFEC‐ISCIII), Servicio de MicrobiologíaUniversity Hospital of A Coruña (CHUAC)A CoruñaSpain
- Microbiome and Health Group, Faculty of SciencesUniversity of A Coruña (UDC)A CoruñaSpain
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36
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Ratiner K, Ciocan D, Abdeen SK, Elinav E. Utilization of the microbiome in personalized medicine. Nat Rev Microbiol 2024; 22:291-308. [PMID: 38110694 DOI: 10.1038/s41579-023-00998-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2023] [Indexed: 12/20/2023]
Abstract
Inter-individual human variability, driven by various genetic and environmental factors, complicates the ability to develop effective population-based early disease detection, treatment and prognostic assessment. The microbiome, consisting of diverse microorganism communities including viruses, bacteria, fungi and eukaryotes colonizing human body surfaces, has recently been identified as a contributor to inter-individual variation, through its person-specific signatures. As such, the microbiome may modulate disease manifestations, even among individuals with similar genetic disease susceptibility risks. Information stored within microbiomes may therefore enable early detection and prognostic assessment of disease in at-risk populations, whereas microbiome modulation may constitute an effective and safe treatment tailored to the individual. In this Review, we explore recent advances in the application of microbiome data in precision medicine across a growing number of human diseases. We also discuss the challenges, limitations and prospects of analysing microbiome data for personalized patient care.
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Affiliation(s)
- Karina Ratiner
- Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel
| | - Dragos Ciocan
- Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel
| | - Suhaib K Abdeen
- Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel.
| | - Eran Elinav
- Systems Immunology Department, Weizmann Institute of Science, Rehovot, Israel.
- Division of Cancer-Microbiome Research, DKFZ, Heidelberg, Germany.
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37
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Geistlinger L, Mirzayi C, Zohra F, Azhar R, Elsafoury S, Grieve C, Wokaty J, Gamboa-Tuz SD, Sengupta P, Hecht I, Ravikrishnan A, Gonçalves RS, Franzosa E, Raman K, Carey V, Dowd JB, Jones HE, Davis S, Segata N, Huttenhower C, Waldron L. BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures. Nat Biotechnol 2024; 42:790-802. [PMID: 37697152 PMCID: PMC11098749 DOI: 10.1038/s41587-023-01872-y] [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: 10/24/2022] [Accepted: 06/20/2023] [Indexed: 09/13/2023]
Abstract
The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut.
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Affiliation(s)
- Ludwig Geistlinger
- Center for Computational Biomedicine, Harvard Medical School, Boston, MA, USA
| | - Chloe Mirzayi
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Fatima Zohra
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Rimsha Azhar
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Shaimaa Elsafoury
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Clare Grieve
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Jennifer Wokaty
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Samuel David Gamboa-Tuz
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Pratyay Sengupta
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, India
- Robert Bosch Centre for Data Science and Artificial Intelligence, Indian Institute of Technology (IIT) Madras, Chennai, India
- Centre for Integrative Biology and Systems mEdicine (IBSE), Indian Institute of Technology (IIT) Madras, Chennai, India
| | | | - Aarthi Ravikrishnan
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore, Republic of Singapore
| | - Rafael S Gonçalves
- Center for Computational Biomedicine, Harvard Medical School, Boston, MA, USA
| | - Eric Franzosa
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, 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
| | - Karthik Raman
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology (IIT) Madras, Chennai, India
- Robert Bosch Centre for Data Science and Artificial Intelligence, Indian Institute of Technology (IIT) Madras, Chennai, India
- Centre for Integrative Biology and Systems mEdicine (IBSE), Indian Institute of Technology (IIT) Madras, Chennai, India
| | - Vincent Carey
- Channing Division of Network Medicine, Mass General Brigham, Harvard Medical School, Boston, MA, USA
| | - Jennifer B Dowd
- Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK
| | - Heidi E Jones
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA
| | - Sean Davis
- Departments of Biomedical Informatics and Medicine, University of Colorado Anschutz School of Medicine, Denver, CO, USA
| | - Nicola Segata
- Department CIBIO, University of Trento, Trento, Italy
- Istituto Europeo di Oncologia (IEO) IRCSS, Milan, Italy
| | - Curtis Huttenhower
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, 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
| | - Levi Waldron
- Institute for Implementation Science in Population Health, City University of New York School of Public Health, New York, NY, USA.
- Department of Epidemiology and Biostatistics, City University of New York School of Public Health, New York, NY, USA.
- Department CIBIO, University of Trento, Trento, Italy.
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38
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Tito RY, Verbandt S, Aguirre Vazquez M, Lahti L, Verspecht C, Lloréns-Rico V, Vieira-Silva S, Arts J, Falony G, Dekker E, Reumers J, Tejpar S, Raes J. Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development. Nat Med 2024; 30:1339-1348. [PMID: 38689063 PMCID: PMC11108775 DOI: 10.1038/s41591-024-02963-2] [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: 11/18/2022] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises concerns regarding potential spurious associations. Here we study the fecal microbiota of 589 patients at different colorectal cancer (CRC) stages and compare observations with up to 15 published studies (4,439 patients and controls total). Using quantitative microbiome profiling based on 16S ribosomal RNA amplicon sequencing, combined with rigorous confounder control, we identified transit time, fecal calprotectin (intestinal inflammation) and body mass index as primary microbial covariates, superseding variance explained by CRC diagnostic groups. Well-established microbiome CRC targets, such as Fusobacterium nucleatum, did not significantly associate with CRC diagnostic groups (healthy, adenoma and carcinoma) when controlling for these covariates. In contrast, the associations of Anaerococcus vaginalis, Dialister pneumosintes, Parvimonas micra, Peptostreptococcus anaerobius, Porphyromonas asaccharolytica and Prevotella intermedia remained robust, highlighting their future target potential. Finally, control individuals (age 22-80 years, mean 57.7 years, standard deviation 11.3) meeting criteria for colonoscopy (for example, through a positive fecal immunochemical test) but without colonic lesions are enriched for the dysbiotic Bacteroides2 enterotype, emphasizing uncertainties in defining healthy controls in cancer microbiome research. Together, these results indicate the importance of quantitative microbiome profiling and covariate control for biomarker identification in CRC microbiome studies.
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Affiliation(s)
- Raúl Y Tito
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium
| | - Sara Verbandt
- Digestive Oncology, Department of Oncology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Marta Aguirre Vazquez
- Digestive Oncology, Department of Oncology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Leo Lahti
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Department of Computing, University of Turku, Turku, Finland
| | - Chloe Verspecht
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium
| | - Verónica Lloréns-Rico
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium
- Systems Biology of Host-Microbiome Interactions Laboratory, Principe Felipe Research Center (CIPF), Valencia, Spain
| | - Sara Vieira-Silva
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Institute of Medical Microbiology and Hygiene and Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Molecular Biology, Mainz, Germany
| | - Janine Arts
- Oncology, Janssen Pharmaceutica NV, Beerse, Belgium
| | - Gwen Falony
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium
- Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium
- Institute of Medical Microbiology and Hygiene and Research Center for Immunotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Joke Reumers
- Therapeutics Discovery, Janssen Pharmaceutica NV, Beerse, Belgium
| | - Sabine Tejpar
- Digestive Oncology, Department of Oncology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Jeroen Raes
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, Katholieke Universiteit Leuven, Leuven, Belgium.
- Center for Microbiology, Vlaams Instituut voor Biotechnologie, Leuven, Belgium.
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Ahmad A, Mahmood N, Raza MA, Mushtaq Z, Saeed F, Afzaal M, Hussain M, Amjad HW, Al-Awadi HM. Gut microbiota and their derivatives in the progression of colorectal cancer: Mechanisms of action, genome and epigenome contributions. Heliyon 2024; 10:e29495. [PMID: 38655310 PMCID: PMC11035079 DOI: 10.1016/j.heliyon.2024.e29495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 04/26/2024] Open
Abstract
Gut microbiota interacts with host epithelial cells and regulates many physiological functions such as genetics, epigenetics, metabolism of nutrients, and immune functions. Dietary factors may also be involved in the etiology of colorectal cancer (CRC), especially when an unhealthy diet is consumed with excess calorie intake and bad practices like smoking or consuming a great deal of alcohol. Bacteria including Fusobacterium nucleatum, Enterotoxigenic Bacteroides fragilis (ETBF), and Escherichia coli (E. coli) actively participate in the carcinogenesis of CRC. Gastrointestinal tract with chronic inflammation and immunocompromised patients are at high risk for CRC progression. Further, the gut microbiota is also involved in Geno-toxicity by producing toxins like colibactin and cytolethal distending toxin (CDT) which cause damage to double-stranded DNA. Specific microRNAs can act as either tumor suppressors or oncogenes depending on the cellular environment in which they are expressed. The current review mainly highlights the role of gut microbiota in CRC, the mechanisms of several factors in carcinogenesis, and the role of particular microbes in colorectal neoplasia.
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Affiliation(s)
- Awais Ahmad
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Nasir Mahmood
- Department of Zoology, University of Central Punjab Bahawalpur, Bahawalpur, Pakistan
| | - Muhammad Ahtisham Raza
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Zarina Mushtaq
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Farhan Saeed
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Muhammad Afzaal
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Muzzamal Hussain
- Department of Food Science, Government College University Faisalabad, Faisalabad, Pakistan
| | - Hafiz Wasiqe Amjad
- International Medical School, Jinggangshan University, Ji'an, Jiangxi, China
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40
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Chen Q, Huang X, Zhang H, Jiang X, Zeng X, Li W, Su H, Chen Y, Lin F, Li M, Gu X, Jin H, Wang R, Diao D, Wang W, Li J, Wei S, Zhang W, Liu W, Huang Z, Deng Y, Luo W, Liu Z, Zhang B. Characterization of tongue coating microbiome from patients with colorectal cancer. J Oral Microbiol 2024; 16:2344278. [PMID: 38686186 PMCID: PMC11057396 DOI: 10.1080/20002297.2024.2344278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 04/13/2024] [Indexed: 05/02/2024] Open
Abstract
Background Tongue coating microbiota has aroused particular interest in profiling oral and digestive system cancers. However, little is known on the relationship between tongue coating microbiome and colorectal cancer (CRC). Methods Metagenomic shotgun sequencing was performed on tongue coating samples collected from 30 patients with CRC, 30 patients with colorectal polyps (CP), and 30 healthy controls (HC). We further validated the potential of the tongue coating microbiota to predict the CRC by a random forest model. Results We found a greater species diversity in CRC samples, and the nucleoside and nucleotide biosynthesis pathway was more apparent in the CRC group. Importantly, various species across participants jointly shaped three distinguishable fur types.The tongue coating microbiome profiling data gave an area under the receiver operating characteristic curve (AUC) of 0.915 in discriminating CRC patients from control participants; species such as Atopobium rimae, Streptococcus sanguinis, and Prevotella oris aided differentiation of CRC patients from healthy participants. Conclusion These results elucidate the use of tongue coating microbiome in CRC patients firstly, and the fur-types observed contribute to a better understanding of the microbial community in human. Furthermore, the tongue coating microbiota-based biomarkers provide a valuable reference for CRC prediction and diagnosis.
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Affiliation(s)
- Qubo Chen
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Biological Resource Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, China
| | - Xiaoting Huang
- Medical Research Center, Huazhong University of Science and Technology Union Shenzhen, Shenzhen, China
| | - Haiyan Zhang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Department of Gastroenterology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xuanting Jiang
- Department of Scientific Research, KMHD, Shenzhen, China
| | - Xuan Zeng
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Biological Resource Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, China
| | - Wanhua Li
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hairong Su
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ying Chen
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Fengye Lin
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Man Li
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Biological Resource Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, China
| | - Xiangyu Gu
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Huihui Jin
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ruohan Wang
- Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Dechang Diao
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Colorectal surgery of Guangdong Provincial Hospital of TCM, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wei Wang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Gastrointestinal Surgery Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jin Li
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Gastrointestinal Surgery Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Sufen Wei
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Department of Gastroenterology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Weizheng Zhang
- Medical Laboratory, Guangzhou Cadre Health Management Center, Guangzhou No.11 People’s Hospital, Guangzhou, China
| | - Wofeng Liu
- Medical Laboratory, Guangzhou Cadre Health Management Center, Guangzhou No.11 People’s Hospital, Guangzhou, China
| | - Zhiping Huang
- Information Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yusheng Deng
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Biological Resource Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong-Hong Kong-Macau Joint Lab on Chinese Medicine and Immune Disease Research, Guangzhou, China
- Department of Scientific Research, KMHD, Shenzhen, China
| | - Wen Luo
- Department of Scientific Research, KMHD, Shenzhen, China
| | - Zuofeng Liu
- Department of Scientific Research, KMHD, Shenzhen, China
| | - Beiping Zhang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, Department of Gastroenterology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
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41
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Park G, Kim S, Lee W, Kim G, Shin H. Deciphering the Impact of Defecation Frequency on Gut Microbiome Composition and Diversity. Int J Mol Sci 2024; 25:4657. [PMID: 38731876 PMCID: PMC11083994 DOI: 10.3390/ijms25094657] [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: 02/20/2024] [Revised: 04/02/2024] [Accepted: 04/18/2024] [Indexed: 05/13/2024] Open
Abstract
This study explores the impact of defecation frequency on the gut microbiome structure by analyzing fecal samples from individuals categorized by defecation frequency: infrequent (1-3 times/week, n = 4), mid-frequent (4-6 times/week, n = 7), and frequent (daily, n = 9). Utilizing 16S rRNA gene-based sequencing and LC-MS/MS metabolome profiling, significant differences in microbial diversity and community structures among the groups were observed. The infrequent group showed higher microbial diversity, with community structures significantly varying with defecation frequency, a pattern consistent across all sampling time points. The Ruminococcus genus was predominant in the infrequent group, but decreased with more frequent defecation, while the Bacteroides genus was more common in the frequent group, decreasing as defecation frequency lessened. The infrequent group demonstrated enriched biosynthesis genes for aromatic amino acids and branched-chain amino acids (BCAAs), in contrast to the frequent group, which had a higher prevalence of genes for BCAA catabolism. Metabolome analysis revealed higher levels of metabolites derived from aromatic amino acids and BCAA metabolism in the infrequent group, and lower levels of BCAA-derived metabolites in the frequent group, consistent with their predicted metagenomic functions. These findings underscore the importance of considering stool consistency/frequency in understanding the factors influencing the gut microbiome.
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Affiliation(s)
- Gwoncheol Park
- Department of Food Science & Biotechnology, College of Life Science, Sejong University, Seoul 05006, Republic of Korea; (G.P.); (S.K.); (W.L.); (G.K.)
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea
- Department of Health, Nutrition & Food Sciences, College of Education, Health & Human Sciences, Florida State University, Tallahassee, FL 32306, USA
| | - Seongok Kim
- Department of Food Science & Biotechnology, College of Life Science, Sejong University, Seoul 05006, Republic of Korea; (G.P.); (S.K.); (W.L.); (G.K.)
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea
| | - WonJune Lee
- Department of Food Science & Biotechnology, College of Life Science, Sejong University, Seoul 05006, Republic of Korea; (G.P.); (S.K.); (W.L.); (G.K.)
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea
| | - Gyungcheon Kim
- Department of Food Science & Biotechnology, College of Life Science, Sejong University, Seoul 05006, Republic of Korea; (G.P.); (S.K.); (W.L.); (G.K.)
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea
| | - Hakdong Shin
- Department of Food Science & Biotechnology, College of Life Science, Sejong University, Seoul 05006, Republic of Korea; (G.P.); (S.K.); (W.L.); (G.K.)
- Carbohydrate Bioproduct Research Center, Sejong University, Seoul 05006, Republic of Korea
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42
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Qin Y, Tong X, Mei WJ, Cheng Y, Zou Y, Han K, Yu J, Jie Z, Zhang T, Zhu S, Jin X, Wang J, Yang H, Xu X, Zhong H, Xiao L, Ding PR. Consistent signatures in the human gut microbiome of old- and young-onset colorectal cancer. Nat Commun 2024; 15:3396. [PMID: 38649355 PMCID: PMC11035630 DOI: 10.1038/s41467-024-47523-x] [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: 06/01/2023] [Accepted: 04/03/2024] [Indexed: 04/25/2024] Open
Abstract
The incidence of young-onset colorectal cancer (yCRC) has been increasing in recent decades, but little is known about the gut microbiome of these patients. Most studies have focused on old-onset CRC (oCRC), and it remains unclear whether CRC signatures derived from old patients are valid in young patients. To address this, we assembled the largest yCRC gut metagenomes to date from two independent cohorts and found that the CRC microbiome had limited association with age across adulthood. Differential analysis revealed that well-known CRC-associated taxa, such as Clostridium symbiosum, Peptostreptococcus stomatis, Parvimonas micra and Hungatella hathewayi were significantly enriched (false discovery rate <0.05) in both old- and young-onset patients. Similar strain-level patterns of Fusobacterium nucleatum, Bacteroides fragilis and Escherichia coli were observed for oCRC and yCRC. Almost all oCRC-associated metagenomic pathways had directionally concordant changes in young patients. Importantly, CRC-associated virulence factors (fadA, bft) were enriched in both oCRC and yCRC compared to their respective controls. Moreover, the microbiome-based classification model had similar predication accuracy for CRC status in old- and young-onset patients, underscoring the consistency of microbial signatures across different age groups.
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Affiliation(s)
- Youwen Qin
- BGI Research, Shenzhen, 518083, China.
- BGI Genomics, Shenzhen, 518083, China.
| | - Xin Tong
- BGI Research, Shenzhen, 518083, China
| | - Wei-Jian Mei
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, 510060, China
| | - Yanshuang Cheng
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, 510060, China
| | - Yuanqiang Zou
- BGI Research, Shenzhen, 518083, China
- Shenzhen Engineering Laboratory of Detection and Intervention of Human Intestinal Microbiome, Shenzhen, China
| | - Kai Han
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, 510060, China
| | - Jiehai Yu
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, 510060, China
| | - Zhuye Jie
- BGI Research, Shenzhen, 518083, China
| | - Tao Zhang
- BGI Research, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Human commensal microorganisms and Health Research, Shenzhen, China
- BGI Research, Wuhan, 430074, China
| | - Shida Zhu
- BGI Genomics, Shenzhen, 518083, China
| | - Xin Jin
- BGI Research, Shenzhen, 518083, China
| | - Jian Wang
- BGI Research, Shenzhen, 518083, China
| | | | - Xun Xu
- BGI Research, Shenzhen, 518083, China
| | - Huanzi Zhong
- BGI Research, Shenzhen, 518083, China
- BGI Genomics, Shenzhen, 518083, China
| | - Liang Xiao
- BGI Research, Shenzhen, 518083, China
- Shenzhen Engineering Laboratory of Detection and Intervention of Human Intestinal Microbiome, Shenzhen, China
| | - Pei-Rong Ding
- Department of Colorectal Surgery, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, 510060, China.
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43
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Dicks LMT. Gut Bacteria Provide Genetic and Molecular Reporter Systems to Identify Specific Diseases. Int J Mol Sci 2024; 25:4431. [PMID: 38674014 PMCID: PMC11050607 DOI: 10.3390/ijms25084431] [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: 03/22/2024] [Revised: 04/15/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
With genetic information gained from next-generation sequencing (NGS) and genome-wide association studies (GWAS), it is now possible to select for genes that encode reporter molecules that may be used to detect abnormalities such as alcohol-related liver disease (ARLD), cancer, cognitive impairment, multiple sclerosis (MS), diabesity, and ischemic stroke (IS). This, however, requires a thorough understanding of the gut-brain axis (GBA), the effect diets have on the selection of gut microbiota, conditions that influence the expression of microbial genes, and human physiology. Bacterial metabolites such as short-chain fatty acids (SCFAs) play a major role in gut homeostasis, maintain intestinal epithelial cells (IECs), and regulate the immune system, neurological, and endocrine functions. Changes in butyrate levels may serve as an early warning of colon cancer. Other cancer-reporting molecules are colibactin, a genotoxin produced by polyketide synthetase-positive Escherichia coli strains, and spermine oxidase (SMO). Increased butyrate levels are also associated with inflammation and impaired cognition. Dysbiosis may lead to increased production of oxidized low-density lipoproteins (OX-LDLs), known to restrict blood vessels and cause hypertension. Sudden changes in SCFA levels may also serve as a warning of IS. Early signs of ARLD may be detected by an increase in regenerating islet-derived 3 gamma (REG3G), which is associated with changes in the secretion of mucin-2 (Muc2). Pro-inflammatory molecules such as cytokines, interferons, and TNF may serve as early reporters of MS. Other examples of microbial enzymes and metabolites that may be used as reporters in the early detection of life-threatening diseases are reviewed.
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Affiliation(s)
- Leon M T Dicks
- Department of Microbiology, Stellenbosch University, Stellenbosch 7600, South Africa
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44
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Yahaya N, Mohamed Rehan M, Hamdan NH, Nasaruddin SM. Metagenomic data of microbiota in mangrove soil from Lukut River, Malaysia. Data Brief 2024; 53:110155. [PMID: 38379885 PMCID: PMC10877682 DOI: 10.1016/j.dib.2024.110155] [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: 07/05/2023] [Revised: 01/24/2024] [Accepted: 01/30/2024] [Indexed: 02/22/2024] Open
Abstract
The mangrove ecosystem contains sediment microorganisms that play a crucial part in the decomposition of organic matter and the cycling of water and nutrients in the mangrove. Here we present the metagenomics whole genome shotgun (mWGS) sequence data analysis from three soil samples that were collected at the freshwater riverine mangrove at Lukut River, Negeri Sembilan, Malaysia. Data analysis shows different distributions of bacteria of the genera Bradyrhizobium, Methyloceanibacter and Desulfobacteaceae were detected in soil samples collected at freshwater riverine mangrove. In the data analysis, we report the existence of a large number of Carbohydrate-Active genes in metagenomes collected from mangrove soil. An in-depth exploration of functional annotation analysis based on the KEGG database also showed that the most abundant genes found in these three soils are those that function in carbon fixation pathways, followed by methane, nitrogen, sulfur metabolisms, atrazine and dioxin degradations.
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Affiliation(s)
- Nazariyah Yahaya
- Programme of Food Biotechnology, Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
- Institut Fatwa dan Halal (IFFAH), Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
| | - Maryam Mohamed Rehan
- Programme of Food Biotechnology, Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
| | - Nabila Huda Hamdan
- Programme of Food Biotechnology, Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
| | - Siti Munirah Nasaruddin
- Programme of Food Biotechnology, Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan, Malaysia
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45
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Asnicar F, Thomas AM, Passerini A, Waldron L, Segata N. Machine learning for microbiologists. Nat Rev Microbiol 2024; 22:191-205. [PMID: 37968359 DOI: 10.1038/s41579-023-00984-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2023] [Indexed: 11/17/2023]
Abstract
Machine learning is increasingly important in microbiology where it is used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex host diseases. The applications in microbiology are quickly expanding and the machine learning tools frequently used in basic and clinical research range from classification and regression to clustering and dimensionality reduction. In this Review, we examine the main machine learning concepts, tasks and applications that are relevant for experimental and clinical microbiologists. We provide the minimal toolbox for a microbiologist to be able to understand, interpret and use machine learning in their experimental and translational activities.
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Affiliation(s)
- Francesco Asnicar
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Andrew Maltez Thomas
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
| | - Andrea Passerini
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
| | - Levi Waldron
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.
- Department of Epidemiology and Biostatistics, City University of New York, New York, NY, USA.
| | - Nicola Segata
- Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy.
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46
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Lima HS, Oliveira GFVD, Ferreira RDS, Castro AGD, Silva LCF, Ferreira LDS, Oliveira DADS, Silva LFD, Kasuya MCM, de Paula SO, Silva CCD. Machine learning-based soil quality assessment for enhancing environmental monitoring in iron ore mining-impacted ecosystems. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 356:120559. [PMID: 38471324 DOI: 10.1016/j.jenvman.2024.120559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 02/22/2024] [Accepted: 03/05/2024] [Indexed: 03/14/2024]
Abstract
In November 2015, a catastrophic rupture of the Fundão dam in Mariana (Brazil), resulted in extensive socio-economic and environmental repercussions that persist to this day. In response, several reforestation programs were initiated to remediate the impacted regions. However, accurately assessing soil health in these areas is a complex endeavor. This study employs machine learning techniques to predict soil quality indicators that effectively differentiate between the stages of recovery in these areas. For this, a comprehensive set of soil parameters, encompassing 3 biological, 16 chemical, and 3 physical parameters, were evaluated for samples exposed to mining tailings and those unaffected, totaling 81 and 6 samples, respectively, which were evaluated over 2 years. The most robust model was the decision tree with a restriction of fewer levels to simplify the tree structure. In this model, Cation Exchange Capacity (CEC), Microbial Biomass Carbon (MBC), Base Saturation (BS), and Effective Cation Exchange Capacity (eCEC) emerged as the most pivotal factors influencing model fitting. This model achieved an accuracy score of 92% during training and 93% during testing for determining stages of recovery. The model developed in this study has the potential to revolutionize the monitoring efforts conducted by regulatory agencies in these regions. By reducing the number of parameters that necessitate evaluation, this enhanced efficiency promises to expedite recovery monitoring, simultaneously enhancing cost-effectiveness while upholding the analytical rigor of assessments.
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Affiliation(s)
- Helena Santiago Lima
- Laboratory of Applied Environmental Microbiology, Department of Microbiology, Federal University of Viçosa, Viçosa, MG, Brazil.
| | | | | | - Alex Gazolla de Castro
- Laboratory of Applied Environmental Microbiology, Department of Microbiology, Federal University of Viçosa, Viçosa, MG, Brazil.
| | - Lívia Carneiro Fidélis Silva
- Laboratory of Applied Environmental Microbiology, Department of Microbiology, Federal University of Viçosa, Viçosa, MG, Brazil.
| | - Letícia de Souza Ferreira
- Laboratory of Applied Environmental Microbiology, Department of Microbiology, Federal University of Viçosa, Viçosa, MG, Brazil.
| | | | | | | | | | - Cynthia Canêdo da Silva
- Laboratory of Applied Environmental Microbiology, Department of Microbiology, Federal University of Viçosa, Viçosa, MG, Brazil.
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47
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Ding X, Lan W, Li J, Deng M, Li Y, Katayama Y, Gu JD. Metagenomic insight into the pathogenic-related characteristics and resistome profiles within microbiome residing on the Angkor sandstone monuments in Cambodia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170402. [PMID: 38307295 DOI: 10.1016/j.scitotenv.2024.170402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/06/2024] [Accepted: 01/22/2024] [Indexed: 02/04/2024]
Abstract
To reveal the characteristics of indigenous microbiome including the pathogenic-related ones on Angkor monuments in Cambodia and the distribution pattern of resistome at different locations, several sites, namely Angkor Wat, Bayon of Angkor Thom, and Prasat Preah Vihear with different exposure levels to tourists were selected to conduct the metagenomic analysis in this study. The general characteristics of the microbiome on these monuments were revealed, and the association between the environmental geo-ecological feature and the indigenous microbiome was delineated. The most common microbial groups included 6 phyla, namely Acidobacteria, Actinobacteria, Gemmatimonadetes, Nitrospirae, Proteobacteria and Verrucomicrobia on the monuments, but Firmicutes and Chlamydiae were the most dominant phyla found in bats droppings. The taxonomic family of Chitinophagaceae could serve as a signature microbial group for Preah Vihear, the less visited site. More importantly, the pathogenic-related characteristics of the microbiome residing on Angkor monuments were uncovered. A set of specific antibiotic resistance genes (ARGs) with cross-niches dispersal capacity (between the environmental microbiome and the microbiome within warm blood fauna) was identified to be high by the source tracking analysis based on ARGs profile varies in this study. Among the 10 ARG-types detected in this study, 6 of them are confined to resistance mechanism of antibiotic efflux-pump. The findings of this study provide new a new direction on public health management and implication globally at archaeological sites for tourism.
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Affiliation(s)
- Xinghua Ding
- School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China; School of History and Culture, Hunan Normal University, 36 Lushan Road, Changsha 410000, Hunan, People's Republic of China
| | - Wensheng Lan
- Shenzhen R&D Key Laboratory of Alien Pest Detection Technology, The Shenzhen Academy of Inspection and Quarantine, Food Inspection and Quarantine Center of Shenzhen Custom, 1011 Fuqiang Road, Shenzhen 518045, People's Republic of China
| | - Jing Li
- School of Food and Biotechnology, Guangdong Industry Polytechnic, Guangzhou 510300, People's Republic of China
| | - Maocheng Deng
- School of Food and Biotechnology, Guangdong Industry Polytechnic, Guangzhou 510300, People's Republic of China
| | - Yiliang Li
- Department of Earth Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, China
| | - Yoko Katayama
- Tokyo National Research Institute for Cultural Properties, 13-43 Ueno Park, Taito-ku, Tokyo 110-8713, Japan
| | - Ji-Dong Gu
- Environmental Science and Engineering Research Group, Guangdong Technion - Israel Institute of Technology, 241 Daxue Road, Shantou, Guangdong 515063, People's Republic of China; Guangdong Provincial Key Laboratory of Materials and Technologies for Energy Conversion, Guangdong Technion - Israel Institute of Technology, 241 Daxue Road, Shantou, Guangdong 515063, People's Republic of China.
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48
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Wang B, Sun F, Luan Y. Comparison of the effectiveness of different normalization methods for metagenomic cross-study phenotype prediction under heterogeneity. Sci Rep 2024; 14:7024. [PMID: 38528097 DOI: 10.1038/s41598-024-57670-2] [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: 09/28/2023] [Accepted: 03/20/2024] [Indexed: 03/27/2024] Open
Abstract
The human microbiome, comprising microorganisms residing within and on the human body, plays a crucial role in various physiological processes and has been linked to numerous diseases. To analyze microbiome data, it is essential to account for inherent heterogeneity and variability across samples. Normalization methods have been proposed to mitigate these variations and enhance comparability. However, the performance of these methods in predicting binary phenotypes remains understudied. This study systematically evaluates different normalization methods in microbiome data analysis and their impact on disease prediction. Our findings highlight the strengths and limitations of scaling, compositional data analysis, transformation, and batch correction methods. Scaling methods like TMM show consistent performance, while compositional data analysis methods exhibit mixed results. Transformation methods, such as Blom and NPN, demonstrate promise in capturing complex associations. Batch correction methods, including BMC and Limma, consistently outperform other approaches. However, the influence of normalization methods is constrained by population effects, disease effects, and batch effects. These results provide insights for selecting appropriate normalization approaches in microbiome research, improving predictive models, and advancing personalized medicine. Future research should explore larger and more diverse datasets and develop tailored normalization strategies for microbiome data analysis.
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Affiliation(s)
- Beibei Wang
- Frontier Science Center for Nonlinear Expectations, Ministry of Education, Qingdao, 266237, China
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, 266237, China
- School of Mathematics, Shandong University, Jinan, 250100, China
| | - Fengzhu Sun
- Quantitative and Computational Biology Department, University of Southern California, Los Angeles, 90089, USA
| | - Yihui Luan
- Frontier Science Center for Nonlinear Expectations, Ministry of Education, Qingdao, 266237, China.
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, 266237, China.
- School of Mathematics, Shandong University, Jinan, 250100, China.
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49
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Muller E, Shiryan I, Borenstein E. Multi-omic integration of microbiome data for identifying disease-associated modules. Nat Commun 2024; 15:2621. [PMID: 38521774 PMCID: PMC10960825 DOI: 10.1038/s41467-024-46888-3] [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: 01/22/2024] [Accepted: 03/08/2024] [Indexed: 03/25/2024] Open
Abstract
Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.
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Affiliation(s)
- Efrat Muller
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Itamar Shiryan
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Elhanan Borenstein
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
- Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
- Santa Fe Institute, Santa Fe, NM, USA.
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50
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Lei Y, Yu H, Ding S, Liu H, Liu C, Fu R. Molecular mechanism of ATF6 in unfolded protein response and its role in disease. Heliyon 2024; 10:e25937. [PMID: 38434326 PMCID: PMC10907738 DOI: 10.1016/j.heliyon.2024.e25937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/04/2024] [Accepted: 02/05/2024] [Indexed: 03/05/2024] Open
Abstract
Activating transcription factor 6 (ATF6), an important signaling molecule in unfolded protein response (UPR), plays a role in the pathogenesis of several diseases, including diseases such as congenital retinal disease, liver fibrosis and ankylosing spondylitis. After endoplasmic reticulum stress (ERS), ATF6 is activated after separation from binding immunoglobulin protein (GRP78/BiP) in the endoplasmic reticulum (ER) and transported to the Golgi apparatus to be hydrolyzed by site 1 and site 2 proteases into ATF6 fragments, which localize to the nucleus and regulate the transcription and expression of ERS-related genes. In these diseases, ERS leads to the activation of UPR, which ultimately lead to the occurrence and development of diseases by regulating the physiological state of cells through the ATF6 signaling pathway. Here, we discuss the evidence for the pathogenic importance of ATF6 signaling in different diseases and discuss preclinical results.
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Affiliation(s)
| | | | - Shaoxue Ding
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, People's Republic of China
| | - Hui Liu
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, People's Republic of China
| | - Chunyan Liu
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, People's Republic of China
| | - Rong Fu
- Department of Hematology, Tianjin Medical University General Hospital, Tianjin, People's Republic of China
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