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Sun H, Wang Y, Xiao Z, Huang X, Wang H, He T, Jiang X. multiMiAT: an optimal microbiome-based association test for multicategory phenotypes. Brief Bioinform 2023; 24:7005163. [PMID: 36702753 DOI: 10.1093/bib/bbad012] [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: 09/05/2022] [Revised: 12/31/2022] [Accepted: 01/03/2023] [Indexed: 01/28/2023] Open
Abstract
Microbes can affect the metabolism and immunity of human body incessantly, and the dysbiosis of human microbiome drives not only the occurrence but also the progression of disease (i.e. multiple statuses of disease). Recently, microbiome-based association tests have been widely developed to detect the association between the microbiome and host phenotype. However, the existing methods have not achieved satisfactory performance in testing the association between the microbiome and ordinal/nominal multicategory phenotypes (e.g. disease severity and tumor subtype). In this paper, we propose an optimal microbiome-based association test for multicategory phenotypes, namely, multiMiAT. Specifically, under the multinomial logit model framework, we first introduce a microbiome regression-based kernel association test for multicategory phenotypes (multiMiRKAT). As a data-driven optimal test, multiMiAT then integrates multiMiRKAT, score test and MiRKAT-MC to maintain excellent performance in diverse association patterns. Massive simulation experiments prove the success of our method. Furthermore, multiMiAT is also applied to real microbiome data experiments to detect the association between the gut microbiome and clinical statuses of colorectal cancer as well as for diverse statuses of Clostridium difficile infections.
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Affiliation(s)
- Han Sun
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China
| | - Yue Wang
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
| | - Zhen Xiao
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
- School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China
| | - Xiaoyun Huang
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
- Collaborative & Innovative Center for Educational Technology, Central China Normal University, Wuhan 430079, China
| | - Haodong Wang
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
| | - Tingting He
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
- National Language Resources Monitoring & Research Center for Network Media, Central China Normal University, Wuhan 430079, China
| | - Xingpeng Jiang
- Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China
- School of Computer Science, Central China Normal University, Wuhan 430079, China
- National Language Resources Monitoring & Research Center for Network Media, Central China Normal University, Wuhan 430079, China
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152
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Wang AJ, Song D, Hong YM, Liu NN. Multi-omics insights into the interplay between gut microbiota and colorectal cancer in the "microworld" age. Mol Omics 2023; 19:283-296. [PMID: 36916422 DOI: 10.1039/d2mo00288d] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Colorectal cancer (CRC) is a multifactorial heterogeneous disease largely due to both genetic predisposition and environmental factors including the gut microbiota, a dynamic microbial ecosystem inhabiting the gastrointestinal tract. Elucidation of the molecular mechanisms by which the gut microbiota interacts with the host may contribute to the pathogenesis, diagnosis, and promotion of CRC. However, deciphering the influence of genetic variants and interactions with the gut microbial ecosystem is rather challenging. Despite recent advancements in single omics analysis, the application of multi-omics approaches to integrate multiple layers of information in the microbiome and host to introduce effective prevention, diagnosis, and treatment strategies is still in its infancy. Here, we integrate host- and microbe-based multi-omics studies, respectively, to provide a strategy to explore potential causal relationships between gut microbiota and colorectal cancer. Specifically, we summarize the recent multi-omics studies such as metagenomics combined with metabolomics and metagenomics combined with genomics. Meanwhile, the sample size and sample types commonly used in multi-omics research, as well as the methods of data analysis, were also generalized. We highlight multiple layers of information from multi-omics that need to be verified by different types of models. Together, this review provides new insights into the clinical diagnosis and treatment of colorectal cancer patients.
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Affiliation(s)
- An-Jun Wang
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China.
| | - Dingka Song
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China.
| | - Yue-Mei Hong
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China.
| | - Ning-Ning Liu
- State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, 200025 Shanghai, China.
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153
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Dai R, Wu H, Liu G, Shen L, Geng Y, Zhang S, Zhou H, Jiang C, Gong J, Fan X, Ji C. Investigation of bacterial and fungal population structure on environmental surfaces of three medical institutions during the COVID-19 pandemic. Front Microbiol 2023; 14:1089474. [PMID: 36970696 PMCID: PMC10033641 DOI: 10.3389/fmicb.2023.1089474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 02/15/2023] [Indexed: 03/11/2023] Open
Abstract
ObjectivesTo evaluate the population structure of environmental bacteria and fungi in three different types of medical institutions and the potential risks due to antibiotic resistance during the coronavirus disease 2019 (COVID-19) pandemic.MethodsOne hundred twenty-six environmental surface samples were collected from three medical institutions during the COVID-19 pandemic. A total of 6,093 and 13,514 representative sequences of 16S and ITS ribosomal RNA (rRNA) were obtained by amplicon sequencing analysis. The functional prediction was performed using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States tool based on the Greengenes database and the FAPROTAX database.ResultsOn environmental surfaces in three medical institutions during the COVID-19 pandemic, Firmicutes (51.6%) and Bacteroidetes (25%) were the dominant bacteria, while Ascomycota (39.4%) and Basidiomycota (14.2%) were the dominant fungi. A number of potential bacterial and fungal pathogens were successfully identified by the metagenomic approach. Furthermore, compared with the bacterial results, the fungi showed a generally closer Bray Curtis distance between samples. The overall ratio of Gram-negative bacteria to Gram-positive bacteria was about 3:7. The proportion of stress-tolerant bacteria in medical institutions A, B and C reached 88.9, 93.0 and 93.8%, respectively. Anaerobic bacteria accounted for 39.6% in outdoor environments, 77.7% in public areas, 87.9% in inpatient areas and 79.6% in restricted areas. Finally, the β-Lactam resistance pathway and polymyxin resistance pathway were revealed through functional prediction.ConclusionWe described the microbial population structure changes in three different types of medical institutions using the metagenomic approach during the COVID-19 pandemic. We found that the disinfection measures performed by three healthcare facilities may be effective on the “ESKAPE” pathogens, but less effective on fungal pathogens. Moreover, emphasis should be given to the prevention and control of β-lactam and polymyxin antibiotics resistance bacteria during the COVID-19 pandemic.
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Affiliation(s)
- Rongchen Dai
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Hanting Wu
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Guiming Liu
- Beijing Agro-Biotechnology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Linlai Shen
- China Academy of Chinese Medical Sciences, Beijing, China
| | - Yuanyuan Geng
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Infectious Diseases and Clinical Microbiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Shu Zhang
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Infectious Diseases and Clinical Microbiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Haijian Zhou
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Canran Jiang
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Infectious Diseases and Clinical Microbiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Jie Gong
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Infectious Diseases and Clinical Microbiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Xin Fan
- Department of Infectious Diseases and Clinical Microbiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
- *Correspondence: Xin Fan, ; Conghua Ji,
| | - Conghua Ji
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- *Correspondence: Xin Fan, ; Conghua Ji,
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154
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Athanasopoulou K, Adamopoulos PG, Scorilas A. Unveiling the Human Gastrointestinal Tract Microbiome: The Past, Present, and Future of Metagenomics. Biomedicines 2023; 11:biomedicines11030827. [PMID: 36979806 PMCID: PMC10045138 DOI: 10.3390/biomedicines11030827] [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: 01/31/2023] [Revised: 02/26/2023] [Accepted: 03/08/2023] [Indexed: 03/30/2023] Open
Abstract
Over 1014 symbiotic microorganisms are present in a healthy human body and are responsible for the synthesis of vital vitamins and amino acids, mediating cellular pathways and supporting immunity. However, the deregulation of microbial dynamics can provoke diverse human diseases such as diabetes, human cancers, cardiovascular diseases, and neurological disorders. The human gastrointestinal tract constitutes a hospitable environment in which a plethora of microbes, including diverse species of archaea, bacteria, fungi, and microeukaryotes as well as viruses, inhabit. In particular, the gut microbiome is the largest microbiome community in the human body and has drawn for decades the attention of scientists for its significance in medical microbiology. Revolutions in sequencing techniques, including 16S rRNA and ITS amplicon sequencing and whole genome sequencing, facilitate the detection of microbiomes and have opened new vistas in the study of human microbiota. Especially, the flourishing fields of metagenomics and metatranscriptomics aim to detect all genomes and transcriptomes that are retrieved from environmental and human samples. The present review highlights the complexity of the gastrointestinal tract microbiome and deciphers its implication not only in cellular homeostasis but also in human diseases. Finally, a thorough description of the widely used microbiome detection methods is discussed.
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Affiliation(s)
- Konstantina Athanasopoulou
- Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, 15701 Athens, Greece
| | - Panagiotis G Adamopoulos
- Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, 15701 Athens, Greece
| | - Andreas Scorilas
- Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, 15701 Athens, Greece
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155
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CNN_FunBar: Advanced Learning Technique for Fungi ITS Region Classification. Genes (Basel) 2023; 14:genes14030634. [PMID: 36980906 PMCID: PMC10048311 DOI: 10.3390/genes14030634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 12/28/2022] [Accepted: 01/09/2023] [Indexed: 03/06/2023] Open
Abstract
Fungal species identification from metagenomic data is a highly challenging task. Internal Transcribed Spacer (ITS) region is a potential DNA marker for fungi taxonomy prediction. Computational approaches, especially deep learning algorithms, are highly efficient for better pattern recognition and classification of large datasets compared to in silico techniques such as BLAST and machine learning methods. Here in this study, we present CNN_FunBar, a convolutional neural network-based approach for the classification of fungi ITS sequences from UNITE+INSDC reference datasets. Effects of convolution kernel size, filter numbers, k-mer size, degree of diversity and category-wise frequency of ITS sequences on classification performances of CNN models have been assessed at all taxonomic levels (species, genus, family, order, class and phylum). It is observed that CNN models can produce >93% average accuracy for classifying ITS sequences from balanced datasets with 500 sequences per category and 6-mer frequency features at all levels. The comparative study has revealed that CNN_FunBar can outperform machine learning-based algorithms (SVM, KNN, Naïve-Bayes and Random Forest) as well as existing fungal taxonomy prediction software (funbarRF, Mothur, RDP Classifier and SINTAX). The present study will be helpful for fungal taxonomy classification using large metagenomic datasets.
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156
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The soil bacterial community regulates germination of Plasmodiophora brassicae resting spores rather than root exudates. PLoS Pathog 2023; 19:e1011175. [PMID: 36862655 PMCID: PMC9980788 DOI: 10.1371/journal.ppat.1011175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 02/03/2023] [Indexed: 03/03/2023] Open
Abstract
Clubroot, caused by Plasmodiophora brassicae, is a severe soil-borne disease that restricts the production of cruciferous crops worldwide. A better understanding of biotic and abiotic factors regulating germination of P. brassicae resting spores in the soil is significant for developing novel control methods. Previous studies reported that root exudates can trigger P. brassicae resting spore germination, thus enabling a targeted attack of P. brassicae on host plant roots. However, we found that native root exudates collected under sterile conditions from host or non-host plants cannot stimulate the germination of sterile spores, indicating that root exudates may not be direct stimulation factors. Instead, our studies demonstrate that soil bacteria are essential for triggering germination. Through 16s rRNA amplicon sequencing analysis, we found that certain carbon sources and nitrate can reshape the initial microbial community to an inducing community leading to the germination of P. brassicae resting spores. The stimulating communities significantly differed in composition and abundance of bacterial taxa compared to the non-stimulating ones. Several enriched bacterial taxa in stimulating community were significantly correlated with spore germination rates and may be involved as stimulation factors. Based on our findings, a multi-factorial 'pathobiome' model comprising abiotic and biotic factors is proposed to represent the putative plant-microbiome-pathogen interactions associated with breaking spore dormancy of P. brassicae in soil. This study presents novel views on P. brassicae pathogenicity and lays the foundation for novel sustainable control strategies of clubroot.
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157
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Bai H, Liu T, Wang S, Shen L, Wang Z. Variations in gut microbiome and metabolites of dogs with acute diarrhea in poodles and Labrador retrievers. Arch Microbiol 2023; 205:97. [PMID: 36823480 DOI: 10.1007/s00203-023-03439-6] [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: 01/19/2023] [Revised: 02/09/2023] [Accepted: 02/11/2023] [Indexed: 02/25/2023]
Abstract
For different breeds of dogs with acute diarrhea, the gut microbiota and metabolome profiles are unclear. This prospective observational study analyzed the gut microbiomes of poodles with acute diarrhea and Labrador retrievers with acute diarrhea based on 16S amplicon sequencing, with respective healthy dogs as controls. Fecal non-target metabolomics and metagenomics were performed on poodles with acute diarrhea. This study found that the diversity and structure of the microbial community differed significantly between the two breeds in cohorts of healthy dogs. Two breeds of dogs with acute diarrhea demonstrated different changes in microbial communities and metabolic functions. The metabolism of starch and sucrose was significantly decreased in dogs with acute diarrhea, which may be attributed to the reduced activity of dextran dextrinase. Non-targeted metabolomics identified 21 abnormal metabolic pathways exhibited by dogs with acute diarrhea, including starch, amino acid, bile acid metabolism, etc., and were closely related to specific intestinal flora. This study provided new insights into breed specificity and the development of dietary treatment strategy in canine gastrointestinal disease.
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Affiliation(s)
- Huasong Bai
- Nourse Centre for Pet Nutrition, Wuhu, 241200, China
| | - Tong Liu
- Nourse Centre for Pet Nutrition, Wuhu, 241200, China
| | - Songjun Wang
- Nourse Centre for Pet Nutrition, Wuhu, 241200, China
| | - Liya Shen
- Nourse Centre for Pet Nutrition, Wuhu, 241200, China
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158
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Zhang XL, Zhou YR, Xu SS, Xu S, Xiong YJ, Xu K, Xu CJ, Che JJ, Huang L, Liu ZG, Wang BY, Mu YL, Xiao SB, Li K. Characterization of Gut Microbiota Compositions along the Intestinal Tract in CD163/pAPN Double Knockout Piglets and Their Potential Roles in Iron Absorption. Microbiol Spectr 2023; 11:e0190622. [PMID: 36625575 PMCID: PMC9927099 DOI: 10.1128/spectrum.01906-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Accepted: 12/13/2022] [Indexed: 01/11/2023] Open
Abstract
The gut microbiota is known to play a role in regulating host metabolism, yet the mechanisms underlying this regulation are not well elucidated. Our study aimed to characterize the differences in gut microbiota compositions and their roles in iron absorption between wild-type (WT) and CD163/pAPN double-gene-knockout (DKO) weaned piglets. A total of 58 samples along the entire digestive tract were analyzed for microbial community using 16S rRNA gene sequencing. The colonic microbiota and their metabolites were determined by metagenomic sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS), respectively. Our results showed that no alterations in microbial community structure and composition were observed between DKO and WT weaned piglets, with the exception of colonic microbiota. Interestingly, the DKO piglets had selectively increased the relative abundance of the Leeia genus belonging to the Neisseriaceae family and decreased the Ruminococcaceae_UCG_014 genus abundance. Functional capacity analysis showed that organic acid metabolism was enriched in the colon in DKO piglets. In addition, the DKO piglets showed increased iron levels in important tissues compared with WT piglets without any pathological changes. Pearson's correlation coefficient indicated that the specific bacteria such as Leeia and Ruminococcaceae_UCG_014 genus played a key role in host iron absorption. Moreover, the iron levels had significantly (P < 0.05) positive correlation with microbial metabolites, particularly carboxylic acids and their derivatives, which might increase iron absorption by preventing iron precipitation. Overall, this study reveals an interaction between colonic microbiota and host metabolism and has potential significance for alleviating piglet iron deficiency. IMPORTANCE Iron deficiency is a major risk factor for iron deficiency anemia, which is among the most common nutritional disorders in piglets. However, it remains unclear how the gut microbiota interacts with host iron absorption. The current report provides the first insight into iron absorption-microbiome connection in CD163/pAPN double knockout piglets. The present results showed that carboxylic acids and their derivatives contributed to the absorption of nonheme iron by preventing ferric iron precipitation.
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Affiliation(s)
- Xiu-Ling Zhang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, People’s Republic of China
| | - Yan-Rong Zhou
- State Key Laboratory of Agricultural Microbiology and Key Laboratory of Preventive Veterinary Medicine in Hubei Province, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, People’s Republic of China
| | - Song-Song Xu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, People’s Republic of China
| | - Si Xu
- State Key Laboratory of Agricultural Microbiology and Key Laboratory of Preventive Veterinary Medicine in Hubei Province, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, People’s Republic of China
| | - Yu-Jian Xiong
- State Key Laboratory of Agricultural Microbiology and Key Laboratory of Preventive Veterinary Medicine in Hubei Province, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, People’s Republic of China
| | - Kui Xu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Chang-Jiang Xu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Jing-Jing Che
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Lei Huang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, People’s Republic of China
| | - Zhi-Guo Liu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Bing-Yuan Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Yu-Lian Mu
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
| | - Shao-Bo Xiao
- State Key Laboratory of Agricultural Microbiology and Key Laboratory of Preventive Veterinary Medicine in Hubei Province, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, People’s Republic of China
| | - Kui Li
- State Key Laboratory of Animal Nutrition, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, People’s Republic of China
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, People’s Republic of China
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159
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Xu M, Lan R, Qiao L, Lin X, Hu D, Zhang S, Yang J, Zhou J, Ren Z, Li X, Liu G, Liu L, Xu J. Bacteroides vulgatus Ameliorates Lipid Metabolic Disorders and Modulates Gut Microbial Composition in Hyperlipidemic Rats. Microbiol Spectr 2023; 11:e0251722. [PMID: 36625637 PMCID: PMC9927244 DOI: 10.1128/spectrum.02517-22] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Hyperlipidemia is a risk factor and key indicator for cardiovascular diseases, and the gut microbiota is highly associated with hyperlipidemia. Bacteroides vulgatus is a prevalent mutualist across human populations and confers multiple health benefits such as immunoregulation, antiobesity, and coronary artery disease intervention. However, its role in antihyperlipidemia has not been systematically characterized. This study sought to identify the effect of B. vulgatus Bv46 on hyperlipidemia. Hyperlipidemic rats were modeled by feeding them a high-fat diet for 6 weeks. The effect of B. vulgatus Bv46 supplementation was evaluated by measuring anthropometric parameters, lipid and inflammation markers, and the liver pathology. Multi-omics was used to explore the underlying mechanisms. The ability of B. vulgatus Bv46 to produce bile salt hydrolase was confirmed by gene annotation and in vitro experiments. Oral administration of B. vulgatus Bv46 in hyperlipidemic rats significantly reduced the body weight gain, food efficiency, and liver index, improved the serum lipid profile, lowered the levels of serum inflammatory cytokines, promoted the loss of fecal bile acids (BAs), and extended the fecal pool of short-chain fatty acids (SCFAs), especially propionate and butyrate. B. vulgatus Bv46 induced compositional shifts of the gut microbial community of hyperlipidemic rats, characterized by a lower ratio of Firmicutes to Bacteroidetes with an increase of genera Bacteroides and Parabacteroides. After intervention, serum metabolite profiling exhibited an adaptation in amino acids and glycerophospholipid metabolism. Transcriptomics further detected altered biological processes, including primary bile acid biosynthesis and fatty acid metabolic process. Taken together, the findings suggest that B. vulgatus Bv46 could be a promising candidate for interventions against hyperlipidemia. IMPORTANCE As a core microbe of the human gut ecosystem, Bacteroides vulgatus has been linked to multiple aspects of metabolic disorders in a collection of associative studies, which, while indicative, warrants more direct experimental evidence to verify. In this study, we experimentally demonstrated that oral administration of B. vulgatus Bv46 ameliorated the serum lipid profile and systemic inflammation of high-fat diet-induced hyperlipidemic rats in a microbiome-regulated manner, which appears to be associated with changes of bile acid metabolism, short-chain fatty acid biosynthesis, and serum metabolomic profile. This finding supports the causal contribution of B. vulgatus in host metabolism and helps to form the basis of novel therapies for the treatment of hyperlipidemia.
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Affiliation(s)
- Mingchao Xu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ruiting Lan
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Lei Qiao
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaoying Lin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dalong Hu
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Suping Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jing Yang
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Units of Discovery of Unknown Bacteria and Function, Chinese Academy of Medical Sciences, Beijing, China
| | - Juan Zhou
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhihong Ren
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xianping Li
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Guoxing Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liyun Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Units of Discovery of Unknown Bacteria and Function, Chinese Academy of Medical Sciences, Beijing, China
| | - Jianguo Xu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Units of Discovery of Unknown Bacteria and Function, Chinese Academy of Medical Sciences, Beijing, China
- Institute of Public Health, Nankai University, Tianjin, China
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160
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Yuan M, Huang Z, Malakar PK, Pan Y, Zhao Y, Zhang Z. Antimicrobial resistomes in food chain microbiomes. Crit Rev Food Sci Nutr 2023; 64:6953-6974. [PMID: 36785889 DOI: 10.1080/10408398.2023.2177607] [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] [Indexed: 02/15/2023]
Abstract
The safety and integrity of the global food system is in a constant state of flux with persistent chemical and microbial risks. While chemical risks are being managed systematically, microbial risks pose extra challenges. Antimicrobial resistant microorganism and persistence of related antibiotic resistance genes (ARGs) in the food chain adds an extra dimension to the management of microbial risks. Because the food chain microbiome is a key interface in the global health system, these microbes can affect health in many ways. In this review, we systematically summarize the distribution of ARGs in foods, describe the potential transmission pathway and transfer mechanism of ARGs from farm to fork, and discuss potential food safety problems and challenges. Modulating antimicrobial resistomes in the food chain facilitates a sustainable global food production system.
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Affiliation(s)
- Mengqi Yuan
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Zhenhua Huang
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Pradeep K Malakar
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Yingjie Pan
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
- Laboratory of Quality & Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture and Rural Affairs, Shanghai, China
- Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai Ocean University, Shanghai, China
| | - Yong Zhao
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
- Laboratory of Quality & Safety Risk Assessment for Aquatic Products on Storage and Preservation (Shanghai), Ministry of Agriculture and Rural Affairs, Shanghai, China
- Shanghai Engineering Research Center of Aquatic-Product Processing & Preservation, Shanghai Ocean University, Shanghai, China
| | - Zhaohuan Zhang
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
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161
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Liu Y, Chen L, Ma T, Li X, Zheng M, Zhou X, Chen L, Qian X, Xi J, Lu H, Cao H, Ma X, Bian B, Zhang P, Wu J, Gan R, Jia B, Sun L, Ju Z, Gao Y, Wen T, Chen T. EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research. IMETA 2023; 2:e83. [PMID: 38868346 PMCID: PMC10989771 DOI: 10.1002/imt2.83] [Citation(s) in RCA: 44] [Impact Index Per Article: 44.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/01/2023] [Accepted: 01/10/2023] [Indexed: 06/14/2024]
Abstract
It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).
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Affiliation(s)
- Yong‐Xin Liu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenGuangdongChina
| | - Lei Chen
- Department of Vascular Surgery, Fu Xing HospitalCapital Medical UniversityBeijingChina
| | - Tengfei Ma
- State Key Laboratory of Grassland Agro‐ecosystems, Centre for Grassland Microbiome, College of Pastoral Agricultural Science and TechnologyLanzhou UniversityLanzhouGansuChina
| | - Xiaofang Li
- Centre for Agricultural Resources Research, Institute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuangChina
| | - Maosheng Zheng
- College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijingChina
| | - Xin Zhou
- Institute of MicrobiologyChinese Academy of SciencesBeijingChina
| | - Liang Chen
- Institute of MicrobiologyChinese Academy of SciencesBeijingChina
| | - Xubo Qian
- Department of Pediatrics, Affiliated Jinhua HospitalZhejiang University School of MedicineJinhuaZhejiangChina
| | - Jiao Xi
- College of Natural Resources and EnvironmentNorthwest A&F UniversityYanglingShaanxiChina
| | - Hongye Lu
- Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Clinical Research Center for Oral Diseases of Zhejiang Province, School of Stomatology, Zhejiang University School of MedicineStomatology HospitalHangzhouZhejiangChina
| | - Huiluo Cao
- Department of MicrobiologyUniversity of Hong KongHong KongChina
| | - Xiaoya Ma
- Center of Excellence in Fungal ResearchMae Fah Luang UniversityChiang RaiThailand
| | - Bian Bian
- Graduate School of Frontier SciencesUniversity of TokyoChibaJapan
| | - Pengfan Zhang
- Department of Plant‐Microbe InteractionsMax Planck Institute for Plant Breeding ResearchCologneGermany
| | - Jiqiu Wu
- APC Microbiome InstituteUniversity College CorkCorkIreland
- Department of Genetics, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands
| | - Ren‐You Gan
- Singapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for ScienceTechnology and Research (A*STAR)SingaporeSingapore
| | - Baolei Jia
- Department of Life ScienceChung‐Ang UniversitySeoulRepublic of Korea
| | - Linyang Sun
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenGuangdongChina
| | - Zhicheng Ju
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenGuangdongChina
| | - Yunyun Gao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenGuangdongChina
| | - Tao Wen
- The Key Laboratory of Plant Immunity Jiangsu Provincial Key Lab for Organic Solid Waste Utilization Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic‐Based FertilizersNanjing Agricultural UniversityNanjingChina
| | - Tong Chen
- National Resource Center for Chinese Materia MedicaChina Academy of Chinese Medical SciencesBeijingChina
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162
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Lyu F, Han F, Ge C, Mao W, Chen L, Hu H, Chen G, Lang Q, Fang C. OmicStudio: A composable bioinformatics cloud platform with real-time feedback that can generate high-quality graphs for publication. IMETA 2023; 2:e85. [PMID: 38868333 PMCID: PMC10989813 DOI: 10.1002/imt2.85] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 01/06/2023] [Accepted: 01/12/2023] [Indexed: 06/14/2024]
Abstract
OmicStudio focuses on speed, quality together with flexibility. Generally, OmicStudio can not only meet the users' demand of ordinary bioinformatics data analysis, statistics, and visualization, but also provides them freedom of data mining beyond developer's framework. Additionally, unlimited to developer's aesthetics, users can get more elegant graphs through customizing. Available online https://www.omicstudio.cn.
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Affiliation(s)
- Fengye Lyu
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Feiran Han
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Changli Ge
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Weikang Mao
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Li Chen
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Huipeng Hu
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Guoguo Chen
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Qiulei Lang
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
| | - Chao Fang
- Operation DepartmentLC‐Bio Technology Co., Ltd.HangzhouChina
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163
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Li H, Zhang H, Chang F, Liu Q, Zhang Y, Liu F, Zhang X. Sedimentary DNA for tracking the long-term changes in biodiversity. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:17039-17050. [PMID: 36622608 DOI: 10.1007/s11356-023-25130-5] [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: 05/25/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
Understanding long-term dynamics is vitally important for explaining current biodiversity patterns and setting conservation goals in a changing world. However, the changes in biodiversity in time and space, particularly the dynamics at the centuries or even longer time scales, are poorly documented because of a lack of continuous monitoring data. The sedimentary DNA (sedDNA) has a great potential for paleo-community reconstruction, and it has recently been used as a powerful tool to characterize past dynamics in terms of biodiversity over geological timescales. In particular, it is useful for prokaryotes and eukaryotes that do not fossilize; hence, it is revolutionizing the scope of paleoecological research. Here, a "Research Weaving" method was performed with systematic maps and bibliometric webs based on the Web of Science for Science Citation Index Expanded, presenting a comprehensive landscape of the sedDNA that traces biological dynamics. We identified that most sedDNA-based studies have focused on microbial dynamics and on using samples from multitypes of sediments. This review summarized the advantages and common applications of sedDNA, focused on the biodiversity in microbial communities, and provided an outlook for the future of sedDNA research.
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Affiliation(s)
- Haoyu Li
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
| | - Hucai Zhang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China.
| | - Fengqin Chang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
| | - Qi Liu
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
| | - Yang Zhang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
| | - Fengwen Liu
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
| | - Xiaonan Zhang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming, 650500, China
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164
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Yang L, Fan W, Xu Y. Chameleon-like microbes promote microecological differentiation of Daqu. Food Microbiol 2023; 109:104144. [DOI: 10.1016/j.fm.2022.104144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/31/2022] [Accepted: 09/12/2022] [Indexed: 11/28/2022]
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165
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Guo X, Yan M, Huang D, Chen S, Zhang D, Li Z, Yang X, Wu W. A large scale 16S ribosomal RNA gene amplicon dataset of hand, foot and mouth patients and healthy individuals. Sci Data 2023; 10:48. [PMID: 36681671 PMCID: PMC9867725 DOI: 10.1038/s41597-023-01953-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/10/2023] [Indexed: 01/22/2023] Open
Abstract
There is evidence linking hand, foot and mouth disease (HFMD) to gut microbiota dysbiosis, and this relationship was corroborated in a large HFMD patient population in our previous study. Here, we present a bacterial 16S rRNA gene dataset from faecal samples of 713 individuals (254 HFMD patients, 459 healthy controls) aged 2 to 7 years residing in Heyuan and Jiangmen counties, Guangdong Province, southern China. Microbiome analysis indicated a significant increase in genus Prevotella, Cetobacterium, and Megamonas was observed in patients with HFMD, whereas a large increase in genus Bacteroides, Ruminococcus, and Faecalibacterium were seen in the control group. We also share the bioinformatic analytical pipeline for this analysis, from data preprocessing to data filtering and amplicon sequence variant (ASV) table generation. We expect that the dataset will be reprocessed, evaluated and fully analysed with various analysis methods to further elucidate the role of the gut microbiota in HFMD development.
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Affiliation(s)
- Xiaoying Guo
- School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Min Yan
- School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Dongyi Huang
- School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Siyi Chen
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Dantao Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Zhifeng Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xingfen Yang
- School of Public Health, Southern Medical University, Guangzhou, China.
| | - Wei Wu
- School of Public Health, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
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166
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Jin L, Dang H, Wu J, Yuan L, Chen X, Yao J. Supplementation of Weizmannia coagulans BC2000 and Ellagic Acid Inhibits High-Fat-Induced Hypercholesterolemia by Promoting Liver Primary Bile Acid Biosynthesis and Intestinal Cholesterol Excretion in Mice. Microorganisms 2023; 11:microorganisms11020264. [PMID: 36838229 PMCID: PMC9964488 DOI: 10.3390/microorganisms11020264] [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: 01/06/2023] [Revised: 01/13/2023] [Accepted: 01/17/2023] [Indexed: 01/20/2023] Open
Abstract
The probiotic Weizmannia coagulans (W. coagulans) BC2000 can increase the abundance of intestinal transforming ellagic acid (EA) bacteria and inhibit metabolic disorders caused by hyperlipidemia by activating liver autophagy. This study aimed to investigate the inhibitory effects of W. coagulans BC2000 and EA on hyperlipidemia-induced cholesterol metabolism disorders. C57BL/6J mice (n = 10 in each group) were fed a low-fat diet, high-fat diet (HFD), HFD supplemented with EA, HFD supplemented with EA and W. coagulans BC77, HFD supplemented with EA, and W. coagulans BC2000. EA and W. coagulans BC2000 supplementation prevented HFD-induced hypercholesterolemia and promoted fecal cholesterol excretion. Transcriptome analysis showed that primary bile acid biosynthesis in the liver was significantly activated by EA and W. coagulans BC2000 treatments. EA and W. coagulans BC2000 treatment also significantly increased the intestinal Eggerthellaceae abundance and the liver EA metabolites, iso-urolithin A, Urolithin A, and Urolithin B. Therefore, W. coagulans BC2000 supplementation promoted the intestinal transformation of EA, which led to the upregulation of liver bile synthesis, thus preventing hypercholesterolemia.
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Affiliation(s)
- Long Jin
- Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- Science Island Branch, Graduate School of University of Science and Technology of China, Hefei 230026, China
- Probiotics Institute, Hefei 230031, China
| | - Hongyang Dang
- College Life Science & Technology, Xinjiang University, Urumqi 830046, China
- Institute of Nutrition and Health, Qingdao University, Qingdao 266021, China
| | - Jinyong Wu
- Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Lixia Yuan
- Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Xiangsong Chen
- Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- Correspondence: (X.C.); (J.Y.)
| | - Jianming Yao
- Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- Science Island Branch, Graduate School of University of Science and Technology of China, Hefei 230026, China
- Correspondence: (X.C.); (J.Y.)
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167
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Isenring J, Bircher L, Geirnaert A, Lacroix C. In vitro human gut microbiota fermentation models: opportunities, challenges, and pitfalls. MICROBIOME RESEARCH REPORTS 2023; 2:2. [PMID: 38045607 PMCID: PMC10688811 DOI: 10.20517/mrr.2022.15] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 12/05/2023]
Abstract
The human gut microbiota (HGM) plays a pivotal role in health and disease. Consequently, nutritional and medical research focusing on HGM modulation strategies as a means of improving host health is steadily increasing. In vitro HGM fermentation models offer a valid complement to human and animal studies when it comes to the mechanistic exploration of novel modulation approaches and their direct effects on HGM composition and activity, while excluding interfering host effects. However, in vitro cultivation of HGM can be challenging due to its high oxygen sensitivity and the difficulties of accurately modeling the physio-chemical complexity of the gut environment. Despite the increased use of in vitro HGM models, there is no consensus about appropriate model selection and operation, sometimes leading to major deficiencies in study design and result interpretation. In this review paper, we aim to analyze crucial aspects of the application, setup and operation, data validation and result interpretation of in vitro HGM models. When carefully designed and implemented, in vitro HGM modeling is a powerful strategy for isolating and investigating biotic and abiotic factors in the HGM, as well as evaluating their effects in a controlled environment akin to the gut. Furthermore, complementary approaches combining different in vitro and in vivo models can strengthen the design and interpretation of human studies.
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Affiliation(s)
| | | | | | - Christophe Lacroix
- Department of Health Sciences and Technology, ETH Zurich, Zürich 8092, Switzerland
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168
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Xue C, Chu Q, Zheng Q, Yuan X, Su Y, Bao Z, Lu J, Li L. Current understanding of the intratumoral microbiome in various tumors. Cell Rep Med 2023; 4:100884. [PMID: 36652905 PMCID: PMC9873978 DOI: 10.1016/j.xcrm.2022.100884] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Revised: 09/18/2022] [Accepted: 12/13/2022] [Indexed: 01/19/2023]
Abstract
It is estimated that in the future, the number of new cancer cases worldwide will exceed the 19.3 million recorded in 2020, and the number of deaths will exceed 10 million. Cancer remains the leading cause of human mortality and lagging socioeconomic development. Intratumoral microbes have been revealed to exist in many cancer types, including pancreatic, colorectal, liver, esophageal, breast, and lung cancers. Intratumoral microorganisms affect not only the host immune system, but also the effectiveness of tumor chemotherapy. This review concentrates on the characteristics and roles of intratumoral microbes in various tumors. In addition, the potential of therapies targeting intratumoral microbes, as well as the main challenges currently delaying these therapies, are explored. Furthermore, we briefly summarize existing technical methods used to characterize intratumoral microbes. We hope to provide ideas for exploring intratumoral microbes as potential biomarkers and targets for tumor diagnosis, treatment, and prognostication.
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Affiliation(s)
- Chen Xue
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Qingfei Chu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Qiuxian Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Xin Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Yuanshuai Su
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Zhengyi Bao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Juan Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
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169
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Zhao N, Zhang Q, Guo Y, Cui S, Tian Y, Zhang Y, Zhou Y, Wang X. Oral microbiome contributes to the failure of orthodontic temporary anchorage devices (TADs). BMC Oral Health 2023; 23:22. [PMID: 36650527 PMCID: PMC9844000 DOI: 10.1186/s12903-023-02715-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 01/04/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND The stability of temporary anchorage devices (TADs) is critical in orthodontic clinics. The failure of TADs is multifactorial, and the role of the oral microbiome has not been clearly defined. Herein, we attempted to analyze the contribution of the oral microbiome to the failure of TADs. METHODS Next-generation sequencing was adopted for analyzing the microbiome on the TADs from orthodontic patients. 29 TADs (15 failed TADs and 14 successful TADs) were used for 16S rRNA gene sequencing. A total of 135 TADs (62 failed TADs and 73 successful TADs) were collected to conduct metagenomic sequencing. Additionally, 34 verified samples (18 failed TADs and 16 successful TADs) were collected for quantitative real-time polymerase chain reaction analysis (qRT-PCR). RESULTS Successful and failed TADs demonstrated discrepancies in microbiome structure, composition, and function. Clear separations were found in β-diversity in 16S rRNA gene sequencing as well as metagenomic sequencing (p < 0.05). Metagenomic sequencing showed that Prevotella intermedia, Eikenella corrodens, Parvimonas spp., Neisseria elongata, and Catonella morbi were enriched in the failed groups. qRT-PCR also demonstrated that the absolute bacteria load of Prevotella intermedia was higher in failed TADs (p < 0.05). Considering functional aspects, the failed group showed enriched genes involved in flagellar assembly, bacterial chemotaxis, and oxidative phosphorylation. CONCLUSIONS This study illustrated the compositional and functional differences of microorganisms found on successful and failed TADs, indicating that controlling bacterial adhesion on the surface of TADs is essential for their success rate.
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Affiliation(s)
- Ningrui Zhao
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Qian Zhang
- grid.11135.370000 0001 2256 9319Central Laboratory, Peking University School and Hospital of Stomatology, 22# Zhongguancun South Avenue, Haidian District, Beijing, 100081 China
| | - Yanning Guo
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Shengjie Cui
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Yajing Tian
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Yidan Zhang
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Yanheng Zhou
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
| | - Xuedong Wang
- grid.11135.370000 0001 2256 9319Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No. 22 Zhongguancun South Avenue, Beijing, 100081 China
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Wang P, Liu J, Han S, Wang Y, Duan Y, Liu T, Hou L, Zhang Z, Li L, Lin Y. Polyethylene mulching film degrading bacteria within the plastisphere: Co-culture of plastic degrading strains screened by bacterial community succession. JOURNAL OF HAZARDOUS MATERIALS 2023; 442:130045. [PMID: 36162306 DOI: 10.1016/j.jhazmat.2022.130045] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/15/2022] [Accepted: 09/20/2022] [Indexed: 06/16/2023]
Abstract
As an ecological niche close to the polymer, microorganisms in the plastisphere possess the advantage of degrading plastics. This study aims to investigate the bacterial community succession and obtain degrading bacteria in the plastisphere, as well as identify the most efficient degradation combination by co-culture of multiple strains. The findings demonstrate the alpha-diversity indices of the plastisphere bacterial community are significantly lower, and the community structure is regularly and significantly altered. With the time of culture, the plastisphere community composition alters regularly, and the hydrocarbon-degrading genera become the core members. Functional prediction of community reveals the potential for Xenobiotics Biodegradation and Metabolism of plastisphere, and the apparent variations detections of polyethylene mulching film (PMF) indicating the PMF degrading ability of plastisphere. Besides, three PMF-degrading bacterial strains, Rhodopseudomonas sp. P1 (P), Rhodanobacter sp. Rs (R) and Microbacterium sp. M1 (M), are screened for co-culture with PMF degrading strain Bacillus aryabhattai 5-3 (B). By considering bacterial growth, biofilm adhesion, and apparent degradation of different samples, RB (R. sp. Rs + B. aryabhattai 5-3) is ultimately selected as the best PMF degradation combination. This study provides a new possibility for plastisphere-related research from the perspective of mitigating plastic pollution on agricultural land.
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Affiliation(s)
- Peiyuan Wang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Jiaxi Liu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Siqi Han
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Yufan Wang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Yifan Duan
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Tingting Liu
- College of Science, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Lijun Hou
- Department of Natural Resource Sciences, McGill University, Ste-Anne-de-Bellevue, Quebec H9X 3V9, Canada
| | - Zengqiang Zhang
- College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, PR China
| | - Li Li
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, PR China
| | - Yanbing Lin
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, 712100, PR China; State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, PR China.
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171
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Yang Y, Deng S, Wang C, Wang Y, Shi Y, Lin J, Wang N, Su L, Yang F, Wang H, Zhu S. Association of Dental Caries with Muscle Mass, Muscle Strength, and Sarcopenia: A Community-Based Study. J Nutr Health Aging 2023; 27:10-20. [PMID: 36651482 DOI: 10.1007/s12603-022-1875-8] [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] [Indexed: 12/24/2022]
Abstract
OBJECTIVES Changes in the oral cavity can reflect other changes throughout the body. This study aimed to investigate the association of dental caries with muscle mass, muscle strength, and sarcopenia, and also to describe the microbial diversity, composition, and community structure of severe dental caries and sarcopenia. DESIGN Cross-sectional study based on a Chinese population aged from 50 to 85 years. SETTING Communities from Lanxi City, Zhejiang Province, China. PARTICIPANTS A total of 1,442 participants aged from 50 to 85 years from a general community (62.8% women; median age 61.0 [interquartile range: 55.0, 68.0]). MEASUREMENTS Dental caries was assessed by the decayed, missing, and filled teeth (DMFT) index. Sarcopenia was defined as the presence of both low muscle mass (assessed by dual-energy X-ray absorptiometry scanning) and low muscle strength (assessed by handgrip strength). Multivariate logistic regression models were used to analyze the association of dental caries with muscle mass, muscle strength, and sarcopenia. Fecal samples underwent 16S rRNA profiling to evaluate the diversity and composition of the gut microbiota in patients with severe dental caries and/or sarcopenia. RESULTS In the fully adjusted logistic models, dental caries was positively associated with low muscle strength (DMFT ≥ 7: OR, 1.61; 95% CI, 1.25-2.06), and sarcopenia (DMFT ≥ 7: OR, 1.51; 95% CI, 1.01-2.26), but not low muscle mass. Severe dental caries was positively associated with higher alpha-diversity indices (richness, chao1, and ACE, all p < 0.05) and associated with beta-diversity based on Bray-Curtis distance (p = 0.006). The severe dental caries group and the sarcopenia group overlapped with 11 depleted and 13 enriched genera. CONCLUSION Dental caries was positively associated with low muscle strength and sarcopenia but not muscle mass, and this association was more pronounced in male individuals. Significant differences were observed in gut microbiota composition both in severe dental caries and sarcopenia, and there was an overlap of the genera features. Future longitudinal studies are needed to clarify causal relationships.
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Affiliation(s)
- Y Yang
- Dr. Huiming Wang, Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, North Qiutao Road No.166, Hangzhou, Zhejiang, China, ; Tel: 13858092696; Fax: 0571-87217433; Dr. Shankuan Zhu, Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China; ; Tel : +86-571-8820-8520; Fax: +86-571-8820-8520
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172
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Avila-Ponce de León U, Vazquez-Jimenez A, Cervera A, Resendis-González G, Neri-Rosario D, Resendis-Antonio O. Machine Learning and COVID-19: Lessons from SARS-CoV-2. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1412:311-335. [PMID: 37378775 DOI: 10.1007/978-3-031-28012-2_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Currently, methods in machine learning have opened a significant number of applications to construct classifiers with capacities to recognize, identify, and interpret patterns hidden in massive amounts of data. This technology has been used to solve a variety of social and health issues against coronavirus disease 2019 (COVID-19). In this chapter, we present some supervised and unsupervised machine learning techniques that have contributed in three aspects to supplying information to health authorities and diminishing the deadly effects of the current worldwide outbreak on the population. First is the identification and construction of powerful classifiers capable of predicting severe, moderate, or asymptomatic responses in COVID-19 patients starting from clinical or high-throughput technologies. Second is the identification of groups of patients with similar physiological responses to improve the triage classification and inform treatments. The final aspect is the combination of machine learning methods and schemes from systems biology to link associative studies with mechanistic frameworks. This chapter aims to discuss some practical applications in the use of machine learning techniques to handle data coming from social behavior and high-throughput technologies, associated with COVID-19 evolution.
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Affiliation(s)
- Ugo Avila-Ponce de León
- Programa de Doctorado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Human Systems Biology Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico
| | - Aarón Vazquez-Jimenez
- Human Systems Biology Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico
| | - Alejandra Cervera
- Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico
| | - Galilea Resendis-González
- Human Systems Biology Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico
| | - Daniel Neri-Rosario
- Human Systems Biology Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico
| | - Osbaldo Resendis-Antonio
- Human Systems Biology Laboratory, Instituto Nacional de Medicina Genómica (INMEGEN), Ciudad de México, Mexico.
- Coordinación de la Investigación Científica - Red de Apoyo a la Investigación - Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, Mexico.
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173
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Sun R, Chen H, Yao S, Yu Z, Lai C, Huang J. Ecological and dynamic analysis of gut microbiota in the early stage of azomethane-dextran sodium sulfate model in mice. Front Cell Infect Microbiol 2023; 13:1178714. [PMID: 37153156 PMCID: PMC10157258 DOI: 10.3389/fcimb.2023.1178714] [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: 03/03/2023] [Accepted: 04/05/2023] [Indexed: 05/09/2023] Open
Abstract
The success rate of azomethane-dextran sodium sulfate (AOM-DSS) model in mice has been a long-standing problem. Treatment of AOM and the first round DSS induces acute colitis and is of great significance for the success of AOM-DSS model. In this study, we focused on the role of gut microbiota in the early stage of AOM-DSS model. Few mice with obvious weight loss and high disease-activity score survived from double strike of AOM and the first round DSS. Different ecological dynamics of gut microbiota were observed in AOM-DSS treated mice. Pseudescherichia, Turicibacter, and Clostridium_XVIII were of significance in the model, uncontrolled proliferation of which accompanied with rapid deterioration and death of mice. Akkermansia and Ruthenibacterium were significantly enriched in the alive AOM-DSS treated mice. Decrease of Ligilactobacillus, Lactobacillus, and Limosilactobacillus were observed in AOM-DSS model, but significant drop of these genera could be lethal. Millionella was the only hub genus of gut microbiota network in dead mice, which indicated dysbiosis of the intestinal flora and fragility of microbial network. Our results will provide a better understanding for the role of gut microbiota in the early stage of AOM-DSS model and help improve the success rate of model construction.
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Affiliation(s)
- Ruizheng Sun
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Parasitology, School of Basic Medical Science, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Precise Diagnosis and Treatment of Gastrointestinal Tumor, Xiangya Hospital Central South University, Changsha, Hunan, China
- International Joint Research Center of Minimally Invasive Endoscopic Technology Equipment & Standardization, Changsha, Hunan, China
| | - Hao Chen
- Department of Parasitology, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Siqi Yao
- Department of Parasitology, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Zheng Yu
- Department of Parasitology, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Chen Lai
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Precise Diagnosis and Treatment of Gastrointestinal Tumor, Xiangya Hospital Central South University, Changsha, Hunan, China
- International Joint Research Center of Minimally Invasive Endoscopic Technology Equipment & Standardization, Changsha, Hunan, China
- *Correspondence: Chen Lai, ; Jing Huang,
| | - Jing Huang
- Department of Parasitology, School of Basic Medical Science, Central South University, Changsha, Hunan, China
- *Correspondence: Chen Lai, ; Jing Huang,
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174
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Qi C, Tu H, Zhao Y, Zhou J, Chen J, Hu H, Yu R, Sun J. Breast Milk-Derived Limosilactobacillus reuteri Prevents Atopic Dermatitis in Mice via Activating Retinol Absorption and Metabolism in Peyer's Patches. Mol Nutr Food Res 2023; 67:e2200444. [PMID: 36480309 DOI: 10.1002/mnfr.202200444] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/24/2022] [Indexed: 12/13/2022]
Abstract
SCOPE Supplementing Limosilactobacillus reuteri Fn041, a breast milk-derived probiotic from agricultural and pastoral areas, to maternal mice during late pregnancy and lactation prevents atopic dermatitis (AD) in offspring. This study aims to elucidate the molecular mechanism of Fn041-mediated immune regulation. METHODS AND RESULTS Fn041 is administered prenatal and postnatal to maternal mice, and to offspring after weaning. The ears are administered with calcipotriol to induce AD. Fn041 treatment significantly alleviates ear inflammation, and reduces mast cell infiltration. Fn041 treatment upregulates and downregulates intestinal ZO-1 and Claudin-2 mRNA expression, respectively. Transcriptome analysis of Peyer's patches reveals that pathways related to DNA damage repair are activated in AD mice, which is inhibited by Fn041 treatment. Fn041 activates pathways related to retinol absorption and metabolism. Untargeted metabolomic analysis reveals that Fn041 treatment increases plasma retinol and kynurenine. Fn041 treatment does not significantly alter the overall cecal microbiota profile, only increases the relative abundances of Ligilactobacillus apodemi, Ligilactobacillus murinus, Akkermansia muciniphila, and Bacteroides thetaiotaomicron. CONCLUSIONS Fn041 induces anti-AD immune responses directly by promoting the absorption and metabolism of retinol in Peyer's patches, and plays an indirect role by strengthening the mucosal barrier and increasing the abundance of specific anti-AD bacteria in the cecum.
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Affiliation(s)
- Ce Qi
- Institute of Nutrition and Health, Qingdao University, Qingdao, 266071, China
| | - Huayu Tu
- Institute of Nutrition and Health, Qingdao University, Qingdao, 266071, China
| | - Yuning Zhao
- Institute of Nutrition and Health, Qingdao University, Qingdao, 266071, China
| | - Jingbo Zhou
- Institute of Nutrition and Health, Qingdao University, Qingdao, 266071, China
| | - Jie Chen
- Department of Pediatric Cardiology Nephrology and Rheumatism, The Affiliated Hospital of Qingdao University Medical College, Qingdao, 266003, China
| | - Haiting Hu
- Department of Neonatology, The Affiliated Changzhou Maternity and Child Health Care Hospital of Nanjing Medical University, Changzhou, 213004, China
| | - Renqiang Yu
- Department of Neonatology, Wuxi Maternity and Child Health Care Hospital, Wuxi School of Medicine, Jiangnan University, Wuxi, 214022, China
| | - Jin Sun
- Institute of Nutrition and Health, Qingdao University, Qingdao, 266071, China
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175
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Li M, Liu J, Zhu J, Wang H, Sun C, Gao NL, Zhao XM, Chen WH. Performance of Gut Microbiome as an Independent Diagnostic Tool for 20 Diseases: Cross-Cohort Validation of Machine-Learning Classifiers. Gut Microbes 2023; 15:2205386. [PMID: 37140125 PMCID: PMC10161951 DOI: 10.1080/19490976.2023.2205386] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/05/2023] Open
Abstract
Cross-cohort validation is essential for gut-microbiome-based disease stratification but was only performed for limited diseases. Here, we systematically evaluated the cross-cohort performance of gut microbiome-based machine-learning classifiers for 20 diseases. Using single-cohort classifiers, we obtained high predictive accuracies in intra-cohort validation (~0.77 AUC), but low accuracies in cross-cohort validation, except the intestinal diseases (~0.73 AUC). We then built combined-cohort classifiers trained on samples combined from multiple cohorts to improve the validation of non-intestinal diseases, and estimated the required sample size to achieve validation accuracies of >0.7. In addition, we observed higher validation performance for classifiers using metagenomic data than 16S amplicon data in intestinal diseases. We further quantified the cross-cohort marker consistency using a Marker Similarity Index and observed similar trends. Together, our results supported the gut microbiome as an independent diagnostic tool for intestinal diseases and revealed strategies to improve cross-cohort performance based on identified determinants of consistent cross-cohort gut microbiome alterations.
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Affiliation(s)
- Min Li
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Jinxin Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jiaying Zhu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Huarui Wang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Chuqing Sun
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Na L Gao
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Xing-Ming Zhao
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- International Human Phenome Institutes (Shanghai), Shanghai, China
| | - Wei-Hua Chen
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
- College of Life Science, Henan Normal University, Xinxiang, China
- Institution of Medical Artificial Intelligence, Binzhou Medical University, Yantai, China
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176
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Baltoumas FA, Karatzas E, Paez-Espino D, Venetsianou NK, Aplakidou E, Oulas A, Finn RD, Ovchinnikov S, Pafilis E, Kyrpides NC, Pavlopoulos GA. Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters. FRONTIERS IN BIOINFORMATICS 2023; 3:1157956. [PMID: 36959975 PMCID: PMC10029925 DOI: 10.3389/fbinf.2023.1157956] [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: 02/07/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.
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Affiliation(s)
- Fotis A. Baltoumas
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
| | - Evangelos Karatzas
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - David Paez-Espino
- Lawrence Berkeley National Laboratory, DOE Joint Genome Institute, Berkeley, CA, United States
| | - Nefeli K. Venetsianou
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - Eleni Aplakidou
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
| | - Anastasis Oulas
- The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Robert D. Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, United Kingdom
| | - Sergey Ovchinnikov
- John Harvard Distinguished Science Fellowship Program, Harvard University, Cambridge, MA, United States
| | - Evangelos Pafilis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece
| | - Nikos C. Kyrpides
- Lawrence Berkeley National Laboratory, DOE Joint Genome Institute, Berkeley, CA, United States
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
| | - Georgios A. Pavlopoulos
- Institute for Fundamental Biomedical Research, BSRC “Alexander Fleming”, Vari, Greece
- Center of New Biotechnologies and Precision Medicine, Department of Medicine, School of Health Sciences, National and Kapodistrian University of Athens, Athens, Greece
- Hellenic Army Academy, Vari, Greece
- *Correspondence: Fotis A. Baltoumas, ; Nikos C. Kyrpides, ; Georgios A. Pavlopoulos,
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177
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Zafeiropoulos H, Beracochea M, Ninidakis S, Exter K, Potirakis A, De Moro G, Richardson L, Corre E, Machado J, Pafilis E, Kotoulas G, Santi I, Finn RD, Cox CJ, Pavloudi C. metaGOflow: a workflow for the analysis of marine Genomic Observatories shotgun metagenomics data. Gigascience 2022; 12:giad078. [PMID: 37850871 PMCID: PMC10583283 DOI: 10.1093/gigascience/giad078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/30/2023] [Accepted: 09/11/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND Genomic Observatories (GOs) are sites of long-term scientific study that undertake regular assessments of the genomic biodiversity. The European Marine Omics Biodiversity Observation Network (EMO BON) is a network of GOs that conduct regular biological community samplings to generate environmental and metagenomic data of microbial communities from designated marine stations around Europe. The development of an effective workflow is essential for the analysis of the EMO BON metagenomic data in a timely and reproducible manner. FINDINGS Based on the established MGnify resource, we developed metaGOflow. metaGOflow supports the fast inference of taxonomic profiles from GO-derived data based on ribosomal RNA genes and their functional annotation using the raw reads. Thanks to the Research Object Crate packaging, relevant metadata about the sample under study, and the details of the bioinformatics analysis it has been subjected to, are inherited to the data product while its modular implementation allows running the workflow partially. The analysis of 2 EMO BON samples and 1 Tara Oceans sample was performed as a use case. CONCLUSIONS metaGOflow is an efficient and robust workflow that scales to the needs of projects producing big metagenomic data such as EMO BON. It highlights how containerization technologies along with modern workflow languages and metadata package approaches can support the needs of researchers when dealing with ever-increasing volumes of biological data. Despite being initially oriented to address the needs of EMO BON, metaGOflow is a flexible and easy-to-use workflow that can be broadly used for one-sample-at-a-time analysis of shotgun metagenomics data.
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Affiliation(s)
- Haris Zafeiropoulos
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Molecular Bacteriology, 3000 Leuven, Belgium
| | - Martin Beracochea
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Stelios Ninidakis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
| | - Katrina Exter
- Flanders Marine Institute (VLIZ), 8400 Oostende, Belgium
| | - Antonis Potirakis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
| | - Gianluca De Moro
- Centro de Ciências do Mar (CCMAR), Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
| | - Lorna Richardson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Erwan Corre
- CNRS, FR 2424, ABiMS Platform, Station Biologique de Roscoff (SBR), 29680 Roscoff, France
| | - João Machado
- Centro de Ciências do Mar (CCMAR), Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
| | - Evangelos Pafilis
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
| | - Georgios Kotoulas
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
| | - Ioulia Santi
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
- European Marine Biological Resource Centre (EMBRC-ERIC), 75005 Paris, France
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Cymon J Cox
- Centro de Ciências do Mar (CCMAR), Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
| | - Christina Pavloudi
- Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Former U.S. Base of Gournes, 71003 Heraklion, Crete, Greece
- Department of Biological Sciences, The George Washington University, 20052 Washington, DC, USA
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178
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Sun K, Cao Y, Chen Y, Peng Q, Xie Y, Luo Y, Tian H, Li X, Zeng M, Zhang X, Li X, Su S, He X, Duan C, Sun H. Altered gut microbiomes are associated with the symptomatic status of unruptured intracranial aneurysms. Front Neurosci 2022; 16:1056785. [PMID: 36620449 PMCID: PMC9814123 DOI: 10.3389/fnins.2022.1056785] [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: 09/29/2022] [Accepted: 11/21/2022] [Indexed: 12/24/2022] Open
Abstract
Background Gut microbiome has recently been recognized as an important environmental factor affecting the occurrence and development of unruptured intracranial aneurysms (UIA). This study aimed to investigate the relationship between gut microbiome and symptomatic UIA, which is a predictor of instability and a high propensity to rupture. Methods A total of 132 patients including 86 asymptomatic UIA and 46 symptomatic UIA were recruited in the study. The composition of gut bacterial communities was determined by 16S ribosomal RNA gene sequencing. In addition, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was used to predict the functional composition of the gut microbiome. Results There is no difference in the fecal microbial alpha diversity between symptomatic and asymptomatic UIA, but gut microbiome composition changed significantly. At the order level, the relative abundance of Clostridiales was significantly enriched in the symptomatic compared with asymptomatic UIA (p = 0.043). In addition, similar alterations were observed at the family levels of Ruminococcaceae. The Linear discriminant analysis (LEfSe) revealed Fournierella, Ruthenibacterium, and Anaerotruncus as discriminative features in the symptomatic group. Notably, functional differences in gut microbiome of patients with symptomatic UIA included decreased propionate metabolism pathway and enrichment of peptidoglycan biosynthesis pathways. Conclusion The present study comprehensively characterizes gut microbiome in a large cohort of different risk statuses of UIA patients and demonstrates the potential biological function of gut microbiome involved in the development of UIA. It may provide additional benefits in guiding UIA management and improving patient outcomes.
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Affiliation(s)
- Kaijian Sun
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Ying Cao
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Yiting Chen
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Qing Peng
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Yugu Xie
- Department of Laboratory Medicine, Clinical Biobank Centre, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yunhao Luo
- Department of Laboratory Medicine, Clinical Biobank Centre, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Hao Tian
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Xin Li
- Department of Laboratory Medicine, Clinical Biobank Centre, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Meiqin Zeng
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Xin Zhang
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Xifeng Li
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Shixing Su
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Xuying He
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China
| | - Chuanzhi Duan
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China,*Correspondence: Chuanzhi Duan,
| | - Haitao Sun
- The National Key Clinical Specialty, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Department of Cerebrovascular Surgery, Engineering Technology Research Center of Education Ministry of China on Diagnosis and Treatment of Cerebrovascular Disease, Neurosurgery Center, Zhujiang Hospital, The Neurosurgery Institute of Guangdong Province, Southern Medical University, Guangzhou, Guangdong, China,Department of Laboratory Medicine, Clinical Biobank Centre, Microbiome Medicine Center, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China,Key Laboratory of Mental Health of the Ministry of Education, Guangdong–Hong Kong–Macao Greater Bay Area Centre for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, Guangdong, China,Haitao Sun,
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Wang Z, Yang T, Mei X, Wang N, Li X, Yang Q, Dong C, Jiang G, Lin J, Xu Y, Shen Q, Jousset A, Banerjee S. Bio-Organic Fertilizer Promotes Pear Yield by Shaping the Rhizosphere Microbiome Composition and Functions. Microbiol Spectr 2022; 10:e0357222. [PMID: 36453930 PMCID: PMC9769518 DOI: 10.1128/spectrum.03572-22] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 11/11/2022] [Indexed: 12/03/2022] Open
Abstract
Bio-organic fertilizers (BOF) containing both organic amendments and beneficial microorganisms have been consistently shown to improve soils fertility and yield. However, the exact mechanisms which link amendments and yields remain disputed, and the complexity of bio-organic fertilizers may work in parallel in several ways. BOF may directly improve yield by replenishing soil nutrients or introducing beneficial microbial genes or indirectly by altering the soil microbiome to enrich native beneficial microorganisms. In this work, we aim to disentangle the relative contributions of direct and indirect effects on pear yield. We treated pear trees with either chemical fertilizer or organic fertilizer with/without the plant-beneficial bacterium Bacillus velezensis SQR9. We then assessed, in detail, soil physicochemical and biological properties (metagenome sequencing) as well as pear yield. We then evaluated the relative importance of direct and indirect effects of soil amendments on pear yield. Both organic treatments increased plant yield by up to 20%, with the addition of bacteria tripling the increase driven by organic fertilizer alone. This increase could be linked to alterations in soil physicochemical properties, bacterial community function, and metabolism. Supplementation of organic fertilizer SQR9 increased rhizosphere microbiome richness and functional diversity. Fertilizer-sensitive microbes and functions responded as whole guilds. Pear yield was most positively associated with the Mitsuaria- and Actinoplanes-dominated ecological clusters and with gene clusters involved in ion transport and secondary metabolite biosynthesis. Together, these results suggested that bio-organic fertilizers mainly act indirectly on plant yield by creating soil chemical properties which promote a plant-beneficial microbiome. IMPORTANCE Bio-organic fertilization is a widely used, eco-friendly, sustainable approach to increasing plant productivity in the agriculture and fruit industries. However, it remains unclear whether the promotion of fruit productivity is related to specific changes in microbial inoculants, the resident microbiome, and/or the physicochemical properties of rhizosphere soils. We found that bio-organic fertilizers alter soil chemical properties, thus manipulating specific microbial taxa and functions within the rhizosphere microbiome of pear plants to promote yield. Our work unveils the ecological mechanisms which underlie the beneficial impacts of bio-organic fertilizers on yield promotion in fruit orchards, which may help in the design of more efficient biofertilizers to promote sustainable fruit production.
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Affiliation(s)
- Zhonghua Wang
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences, Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing, China
| | - Tianjie Yang
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Xinlan Mei
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Ningqi Wang
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Xiaogang Li
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences, Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing, China
| | - Qingsong Yang
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences, Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing, China
| | - Caixia Dong
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Gaofei Jiang
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Jing Lin
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences, Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Nanjing, China
| | - Yangchun Xu
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Qirong Shen
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Alexandre Jousset
- Jiangsu Provincial Key Laboratory for Organic Solid Waste Utilization, Key Laboratory of Plant immunity, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, Nanjing, China
| | - Samiran Banerjee
- Department of Microbiological Sciences, North Dakota State University, Fargo, North Dakota, USA
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Gil JC, Hird SM. Multiomics Characterization of the Canada Goose Fecal Microbiome Reveals Selective Efficacy of Simulated Metagenomes. Microbiol Spectr 2022; 10:e0238422. [PMID: 36318011 PMCID: PMC9769641 DOI: 10.1128/spectrum.02384-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/03/2022] [Indexed: 11/07/2022] Open
Abstract
16S rRNA amplicon sequences are predominantly used to identify the taxonomic composition of a microbiome, but they can also be used to generate simulated metagenomes to circumvent costly empirical shotgun sequencing. The effectiveness of using "simulated metagenomes" (shotgun metagenomes simulated from 16S rRNA amplicons using a database of full genomes closely related to the amplicons) in nonmodel systems is poorly known. We sought to determine the accuracy of simulated metagenomes in a nonmodel organism, the Canada goose (Branta canadensis), by comparing metagenomes and metatranscriptomes to simulated metagenomes derived from 16S amplicon sequencing. We found significant differences between the metagenomes, metatranscriptomes, and simulated metagenomes when comparing enzymes, KEGG orthologies (KO), and metabolic pathways. The simulated metagenomes accurately identified the majority (>70%) of the total enzymes, KOs, and pathways. The simulated metagenomes accurately identified the majority of the short-chain fatty acid metabolic pathways crucial to folivores. When narrowed in scope to specific genes of interest, the simulated metagenomes overestimated the number of antimicrobial resistance genes and underestimated the number of genes related to the breakdown of plant matter. Our results suggest that simulated metagenomes should not be used in lieu of empirical sequencing when studying the functional potential of a nonmodel organism's microbiome. Regarding the function of the Canada goose microbiome, we found unexpected amounts of fermentation pathways, and we found that a few taxa are responsible for large portions of the functional potential of the microbiome. IMPORTANCE The taxonomic composition of a microbiome is predominately identified using amplicon sequencing of 16S rRNA genes, but as a single marker, it cannot identify functions (genes). Metagenome and metatranscriptome sequencing can determine microbiome function but can be cost prohibitive. Therefore, computational methods have been developed to generate simulated metagenomes derived from 16S rRNA sequences and databases of full-length genomes. Simulated metagenomes can be an effective alternative to empirical sequencing, but accuracy depends on the genomic database used and whether the database contains organisms closely related to the 16S sequences. These tools are effective in well-studied systems, but the accuracy of these predictions in a nonmodel system is less known. Using a nonmodel bird species, we characterized the function of the microbiome and compared the accuracy of 16S-derived simulated metagenomes to sequenced metagenomes. We found that the simulated metagenomes reflect most but not all functions of empirical metagenome sequencing.
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Affiliation(s)
- Joshua C. Gil
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut, USA
| | - Sarah M. Hird
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, Connecticut, USA
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181
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Wang Z, Liu X, Zhou W, Sinclair F, Shi L, Xu J, Gui H. Land use intensification in a dry-hot valley reduced the constraints of water content on soil microbial diversity and multifunctionality but increased CO 2 production. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 852:158397. [PMID: 36055510 DOI: 10.1016/j.scitotenv.2022.158397] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 08/21/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
Conversion of abandoned land (mainly savanna) into cropland generally occurs in fragile ecosystems such as dry-hot valleys (DHVs) in southwest China, with the intent of increasing land productivity and conducting ecological restoration. However, the effects of conversion on soil microbial communities and carbon turnover of savanna ecosystems remain unclear, since savannas could be a vital but overlooked carbon sink. To illustrate the ecological consequences of land-use change (LUC) for savanna ecosystems, a 1-year field experiment was conducted in DHVs of southwest China. The soil properties, microbial respiration, and metagenomics from two different land-use types (grassland and mango plantation) were examined to reveal the effects of regional LUC on soil C turnover and microbial traits. Conversion from degraded grassland into cropland increased the contribution of soil microclimate to the microbial community composition, reduced the constraints of soil water content (SWC), and further decreased nutrient availability. LUC reshaped the composition and structure of soil bacterial communities. Specifically, soil dominant microbes that belonged to Actinobacteria and Proteobacteria were significantly enriched by conversion, while rare microbes that belonged to a wider range of phyla were generally depleted, leading to an overall decrease in community diversity. In addition, LUC-induced changes in soil characteristics and microbial communities further decreased soil multifunctionality as well as the carbon use efficiency of microbes. Intensified microbial respiration and a significant increase in the soil CO2 efflux were observed following LUC, which could drive changes in soil microbial community composition and functions (such as growth and regeneration). In summary, through simultaneously reducing constraints on SWC and decreasing nutrient availability, conversion from degraded grassland to cropland in a DHV decreased soil microbial diversity and multifunctionality, and increased microbial respiration and soil CO2 efflux. Our study provides new insights for understanding the role and mechanisms of LUC in soil carbon turnover in ecologically fragile areas such as DHVs.
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Affiliation(s)
- Zhenghong Wang
- Department of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Centre for Mountain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Institute of Plant and Food Science, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiang Liu
- State Key Laboratory of Grassland Agro-Ecosystems, Institute of Innovation Ecology, Lanzhou University, Lanzhou 730000, China
| | - Wenjun Zhou
- University of Chinese Academy of Sciences, Beijing 100049, China; CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan 666303, China
| | - Fergus Sinclair
- World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri, P.O. Box 30677-00100, Nairobi, Kenya
| | - Lingling Shi
- Department of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Centre for Mountain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Jianchu Xu
- Department of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Centre for Mountain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Heng Gui
- Department of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Centre for Mountain Futures (CMF), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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182
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Martínez-Yáñez MG, Silva-Ortega CO, Hernández-Aranda VA, Vallejo-Pérez MR, Alcalá-Briseño R, Vega-Manriquez DX, Aguilar-Benítez G, Jarquin-Gálvez R, Lara-Ávila JP. Analysis of Bacterial Microbiota of Aerated Compost Teas and Effect on Tomato Growth. MICROBIAL ECOLOGY 2022:10.1007/s00248-022-02156-9. [PMID: 36520176 DOI: 10.1007/s00248-022-02156-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/06/2022] [Indexed: 06/17/2023]
Abstract
Mature composts and their water-based extracts, known as aerated compost teas (ACTs), are biofertilizers that share bioactive effects like soil restoration and plant health promotion, widely used for sustainable agriculture. Bioactive effects of compost and ACTs could be associated with their physicochemical and biological characteristics, like carbon/nitrogen (C/N) ratio and microbiota structure respectively. In our study, we elaborated ACTs using mature homemade compost, wheat bran, and grass clippings, following the C/N ratio criteria. Irrigation of tomato plantlets with ACT whose C/N ratio was close to the expected C/N ratio for mature compost evidenced plant growth promotion. Exploring the bacterial microbiota of elaborated ACTs and origin compost revealed significant structural differences, including phyla involved in N mineralization and free-living N-fixing bacteria. Therefore, ACTs harbor diverse bacterial microbiota involved in the N cycle, which would enrich plant and soil bacterial communities at the taxonomic and functional levels. Furthermore, ACTs are considered a part of agroecological and circular economy approaches.
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Affiliation(s)
| | | | | | - Moisés Roberto Vallejo-Pérez
- CONACYT, Universidad Autónoma de San Luis Potosí. Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACYT), San Luis Potosí, SLP, México
| | | | - Delia Xochil Vega-Manriquez
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Soledad de Graciano Sánchez, SLP, México
| | - Gisela Aguilar-Benítez
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Soledad de Graciano Sánchez, SLP, México
| | - Ramón Jarquin-Gálvez
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Soledad de Graciano Sánchez, SLP, México
| | - José Pablo Lara-Ávila
- Facultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Soledad de Graciano Sánchez, SLP, México.
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183
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Reshuffling of the Coral Microbiome during Dormancy. Appl Environ Microbiol 2022; 88:e0139122. [PMID: 36383004 PMCID: PMC9746315 DOI: 10.1128/aem.01391-22] [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] [Indexed: 11/17/2022] Open
Abstract
Quiescence, or dormancy, is a response to stressful conditions in which an organism slows or halts physiological functioning. Although most species that undergo dormancy maintain complex microbiomes, there is little known about how dormancy influences and is influenced by the host's microbiome, including in the temperate coral Astrangia poculata. Northern populations of A. poculata undergo winter quiescence. Here, we characterized wild A. poculata microbiomes in a high-resolution sampling time series before, during, and after quiescence using 16S rRNA gene sequencing on active (RNA) and present (DNA) microbiomes. We observed a restructuring of the coral microbiome during quiescence that persisted after reemergence. Upon entering quiescence, corals shed copiotrophic microbes, including putative pathogens, suggesting a removal of these taxa as corals cease normal functioning. During and after quiescence, bacteria and archaea associated with nitrification were enriched, suggesting that the quiescent microbiome may replace essential functions through supplying nitrate to corals and/or microbes. Overall, this study demonstrates that key microbial groups related to quiescence in A. poculata may play a role in the onset or emergence from dormancy and long-term regulation of the microbiome composition. The predictability of dormancy in A. poculata provides an ideal natural manipulation system to further identify factors that regulate host-microbial associations. IMPORTANCE Using a high-resolution sampling time series, this study is the first to demonstrate a persistent microbial community shift with quiescence (dormancy) in a marine organism, the temperate coral Astrangia poculata. Furthermore, during this period of community turnover, there is a shedding of putative pathogens and copiotrophs and an enhancement of the ammonia-oxidizing bacteria (Nitrosococcales) and archaea ("Candidatus Nitrosopumilus"). Our results suggest that quiescence represents an important period during which the coral microbiome can reset, shedding opportunistic microbes and enriching for the reestablishment of beneficial associates, including those that may contribute nitrate while the coral animal is not actively feeding. We suggest that this work provides foundational understanding of the interplay of microbes and the host's dormancy response in marine organisms.
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184
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Zhu Y, Zhang M, Jie Z, Tao S. Nucleic acid testing of SARS-CoV-2: A review of current methods, challenges, and prospects. Front Microbiol 2022; 13:1074289. [PMID: 36569096 PMCID: PMC9780671 DOI: 10.3389/fmicb.2022.1074289] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has brought a huge threat to public health and the global economy. Rapid identification and isolation of SARS-CoV-2-infected individuals are regarded as one of the most effective measures to control the pandemic. Because of its high sensitivity and specificity, nucleic acid testing has become the major method of SARS-CoV-2 detection. A deep understanding of different diagnosis methods for COVID-19 could help researchers make an optimal choice in detecting COVID-19 at different symptom stages. In this review, we summarize and evaluate the latest developments in current nucleic acid detection methods for SARS-CoV-2. In particular, we discuss biosensors and CRISPR-based diagnostic systems and their characteristics and challenges. Furthermore, the emerging COVID-19 variants and their impact on SARS-CoV-2 diagnosis are systematically introduced and discussed. Considering the disease dynamics, we also recommend optional diagnostic tests for different symptom stages. From sample preparation to results readout, we conclude by pointing out the pain points and future directions of COVID-19 detection.
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Affiliation(s)
- Yuanshou Zhu
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China,School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Meng Zhang
- Department of Pulmonary and Critical Care Medicine, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China
| | - Zhijun Jie
- Department of Pulmonary and Critical Care Medicine, Shanghai Fifth People’s Hospital, Fudan University, Shanghai, China,Center of Community-Based Health Research, Fudan University, Shanghai, China,*Correspondence: Zhijun Jie,
| | - Shengce Tao
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China,School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China,Shengce Tao,
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185
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Vuong P, Wise MJ, Whiteley AS, Kaur P. Ten simple rules for investigating (meta)genomic data from environmental ecosystems. PLoS Comput Biol 2022; 18:e1010675. [PMID: 36480496 PMCID: PMC9731419 DOI: 10.1371/journal.pcbi.1010675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Paton Vuong
- UWA School of Agriculture & Environment, University of Western Australia, Perth, Australia
| | - Michael J. Wise
- School of Physics, Mathematics and Computing, University of Western Australia, Perth, Australia
- The Marshall Centre of Infectious Diseases, School of Biological Sciences, The University of Western Australia, Perth, Australia
| | - Andrew S. Whiteley
- Centre for Environment & Life Sciences, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Floreat, Australia
| | - Parwinder Kaur
- UWA School of Agriculture & Environment, University of Western Australia, Perth, Australia
- * E-mail:
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186
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Comparison of Metagenomics and Metatranscriptomics Tools: A Guide to Making the Right Choice. Genes (Basel) 2022; 13:genes13122280. [PMID: 36553546 PMCID: PMC9777648 DOI: 10.3390/genes13122280] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/28/2022] [Accepted: 12/01/2022] [Indexed: 12/09/2022] Open
Abstract
The study of microorganisms is a field of great interest due to their environmental (e.g., soil contamination) and biomedical (e.g., parasitic diseases, autism) importance. The advent of revolutionary next-generation sequencing techniques, and their application to the hypervariable regions of the 16S, 18S or 23S ribosomal subunits, have allowed the research of a large variety of organisms more in-depth, including bacteria, archaea, eukaryotes and fungi. Additionally, together with the development of analysis software, the creation of specific databases (e.g., SILVA or RDP) has boosted the enormous growth of these studies. As the cost of sequencing per sample has continuously decreased, new protocols have also emerged, such as shotgun sequencing, which allows the profiling of all taxonomic domains in a sample. The sequencing of hypervariable regions and shotgun sequencing are technologies that enable the taxonomic classification of microorganisms from the DNA present in microbial communities. However, they are not capable of measuring what is actively expressed. Conversely, we advocate that metatranscriptomics is a "new" technology that makes the identification of the mRNAs of a microbial community possible, quantifying gene expression levels and active biological pathways. Furthermore, it can be also used to characterise symbiotic interactions between the host and its microbiome. In this manuscript, we examine the three technologies above, and discuss the implementation of different software and databases, which greatly impact the obtaining of reliable results. Finally, we have developed two easy-to-use pipelines leveraging Nextflow technology. These aim to provide everything required for an average user to perform a metagenomic analysis of marker genes with QIMME2 and a metatranscriptomic study using Kraken2/Bracken.
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187
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Zhan C, Matsumoto H, Liu Y, Wang M. Pathways to engineering the phyllosphere microbiome for sustainable crop production. NATURE FOOD 2022; 3:997-1004. [PMID: 37118297 DOI: 10.1038/s43016-022-00636-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 10/12/2022] [Indexed: 04/30/2023]
Abstract
Current disease resistance breeding, which is largely dependent on the exploitation of resistance genes in host plants, faces the serious challenges of rapidly evolving phytopathogens. The phyllosphere is the largest biological surface on Earth and an untapped reservoir of functional microbiomes. The phyllosphere microbiome has the potential to defend against plant diseases. However, the mechanisms of how the microbiota assemble and function in the phyllosphere remain largely elusive, and this restricts the exploitation of the targeted beneficial microbes in the field. Here we review the endogenous and exogenous cues impacting microbiota assembly in the phyllosphere and how the phyllosphere microbiota in turn facilitate the disease resistance of host plants. We further construct a holistic framework by integrating of holo-omics, genetic manipulation, culture-dependent characterization and emerging artificial intelligence techniques, such as deep learning, to engineer the phyllosphere microbiome for sustainable crop production.
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Affiliation(s)
- Chengfang Zhan
- State Key Laboratory of Rice Biology & Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, Hangzhou, China
- Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Pesticide and Environmental Toxicology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Haruna Matsumoto
- State Key Laboratory of Rice Biology & Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, Hangzhou, China
- Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Pesticide and Environmental Toxicology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Yufei Liu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China
| | - Mengcen Wang
- State Key Laboratory of Rice Biology & Ministry of Agricultural and Rural Affairs Laboratory of Molecular Biology of Crop Pathogens and Insects, Zhejiang University, Hangzhou, China.
- Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Pesticide and Environmental Toxicology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.
- Global Education Program for AgriScience Frontiers, Graduate School of Agriculture, Hokkaido University, Sapporo, Japan.
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Yang P, Lang J, Li H, Lu J, Lin H, Tian G, Bai H, Yang J, Ning K. TCM-Suite: A comprehensive and holistic platform for Traditional Chinese Medicine component identification and network pharmacology analysis. IMETA 2022; 1:e47. [PMID: 38867910 PMCID: PMC10989960 DOI: 10.1002/imt2.47] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/05/2022] [Accepted: 07/20/2022] [Indexed: 06/14/2024]
Abstract
DNA-based biological ingredient identification and downstream pharmacology network analysis are commonly used in research for Traditional Chinese Medicine preparations (TCM formulas). Advancements in bioinformatics tools and the accumulation of related data have become driving forces for progress in this field. However, a lack of a platform integrating biological ingredient identification and downstream pharmacology network analysis hinders the deep understanding of TCM. In this study, we developed the TCM-Suite platform composed of two sub-databases, Holmes-Suite and Watson-Suite, for TCM biological ingredient identification and network pharmacology investigation, respectively, both are among the most complete: In the Holmes-Suite, we collected and processed six types of marker gene sequences, accounting for 1,251,548 marker gene sequences. In the Watson-Suite, we curated and integrated a massive number of entries from more than 10 public databases. Importantly, we developed a comprehensive pipeline to integrate TCM biological ingredient identification and downstream network pharmacology research, allowing users to simultaneously identify components of a TCM formula and analyze its potential pharmacology mechanism. Furthermore, we designed search engines and a user-friendly platform to better search and visualize these rich resources. TCM-Suite is a comprehensive and holistic platform for TCM-based drug discovery and repurposing. TCM-Suite website: http://TCM-Suite.AImicrobiome.cn.
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Affiliation(s)
- Pengshuo Yang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular‐imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems BiologyCollege of Life Science and Technology, Huazhong University of Science and TechnologyWuhanChina
| | - Jidong Lang
- Geneis Beijing Co., Ltd.BeijingChina
- Department of sciencesQingdao Genesis Institute of Big Data Mining and PrecisionQingdaoShandongChina
- Academician WorkstationChangsha Medical UniversityChangshaChina
| | - Hongjun Li
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular‐imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems BiologyCollege of Life Science and Technology, Huazhong University of Science and TechnologyWuhanChina
| | - Jinxiang Lu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular‐imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems BiologyCollege of Life Science and Technology, Huazhong University of Science and TechnologyWuhanChina
| | - Hanyang Lin
- Sequenxe Biological Technology Co., Ltd.XiamenChina
| | - Geng Tian
- Geneis Beijing Co., Ltd.BeijingChina
- Department of sciencesQingdao Genesis Institute of Big Data Mining and PrecisionQingdaoShandongChina
| | - Hong Bai
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular‐imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems BiologyCollege of Life Science and Technology, Huazhong University of Science and TechnologyWuhanChina
| | - Jialiang Yang
- Geneis Beijing Co., Ltd.BeijingChina
- Department of sciencesQingdao Genesis Institute of Big Data Mining and PrecisionQingdaoShandongChina
- Academician WorkstationChangsha Medical UniversityChangshaChina
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular‐imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems BiologyCollege of Life Science and Technology, Huazhong University of Science and TechnologyWuhanChina
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Qi Y, Gu S, Zhang Y, Guo L, Xu M, Cheng X, Wang O, Sun Y, Chen J, Fang X, Liu X, Deng L, Fan G. MetaTrass: A high-quality metagenome assembler of the human gut microbiome by cobarcoding sequencing reads. IMETA 2022; 1:e46. [PMID: 38867906 PMCID: PMC10989976 DOI: 10.1002/imt2.46] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 06/28/2022] [Accepted: 07/20/2022] [Indexed: 06/14/2024]
Abstract
Metagenomic evidence of great genetic diversity within the nonconserved regions of the human gut microbial genomes appeals for new methods to elucidate the species-level variability at high resolution. However, current approaches cannot satisfy this methodologically challenge. In this study, we proposed an efficient binning-first-and-assembly-later strategy, named MetaTrass, to recover high-quality species-resolved genomes based on public reference genomes and the single-tube long fragment read (stLFR) technology, which enables cobarcoding. MetaTrass can generate genomes with longer contiguity, higher completeness, and lower contamination than those produced by conventional assembly-first-and-binning-later strategies. From a simulation study on a mock microbial community, MetaTrass showed the potential to improve the contiguity of assembly from kb to Mb without accuracy loss, as compared to other methods based on the next-generation sequencing technology. From four human fecal samples, MetaTrass successfully retrieved 178 high-quality genomes, whereas only 58 ones were provided by the optimal performance of other conventional strategies. Most importantly, these high-quality genomes confirmed the high level of genetic diversity among different samples and unveiled much more. MetaTrass was designed to work with metagenomic reads sequenced by stLFR technology, but is also applicable to other types of cobarcoding libraries. With the high capability of assembling high-quality genomes of metagenomic data sets, MetaTrass seeks to facilitate the study of spatial characters and dynamics of complex microbial communities at enhanced resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.
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Affiliation(s)
- Yanwei Qi
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenChina
- China National GeneBankBGI‐ShenzhenShenzhenChina
| | - Shengqiang Gu
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- College of Life SciencesUniversity of Chinese Academy of SciencesBeijingChina
| | | | - Lidong Guo
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- College of Life SciencesUniversity of Chinese Academy of SciencesBeijingChina
| | - Mengyang Xu
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenChina
- China National GeneBankBGI‐ShenzhenShenzhenChina
- BGI‐ShenzhenBGI‐ShenzhenShenzhenChina
| | - Xiaofang Cheng
- BGI‐ShenzhenBGI‐ShenzhenShenzhenChina
- MGIBGI‐ShenzhenShenzhenChina
| | - Ou Wang
- BGI‐ShenzhenBGI‐ShenzhenShenzhenChina
- MGIBGI‐ShenzhenShenzhenChina
| | - Ying Sun
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
| | | | - Xiaodong Fang
- BGI‐ShenzhenBGI‐ShenzhenShenzhenChina
- BGI GenomicsBGI‐ShenzhenShenzhenChina
| | - Xin Liu
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenChina
- China National GeneBankBGI‐ShenzhenShenzhenChina
| | - Li Deng
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenChina
- China National GeneBankBGI‐ShenzhenShenzhenChina
| | - Guangyi Fan
- BGI‐QingdaoBGI‐ShenzhenQingdaoChina
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenChina
- China National GeneBankBGI‐ShenzhenShenzhenChina
- BGI‐ShenzhenBGI‐ShenzhenShenzhenChina
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Zhao NR, Guo YN, Cui SJ, Tian YJ, Zhou YH, Wang XD. Microbiological Advances in Orthodontics: An Overview and Detailed Analysis of Temporary Anchorage Devices. Curr Med Sci 2022; 42:1157-1163. [PMID: 36544036 DOI: 10.1007/s11596-022-2653-x] [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: 09/03/2021] [Accepted: 08/08/2022] [Indexed: 12/24/2022]
Abstract
Dental biofilm is the initiating factor of oral diseases, such as periodontitis and caries. Orthodontic treatment could alter the microbiome structure balance, and increase the risk of such diseases. Furthermore, fixed appliances can induce temporary changes in the microbiome community, and the changes that clear aligners bring are smaller by comparison. Temporary anchorage devices (TADs) are skeletal anchorages that are widely used in orthodontic treatment. Microorganisms affect the occurrence and development of inflammation surrounding TADs. At present, existing researches have verified the existence of plaque biofilm on the surface of TADs, but the formation of plaque biofilm and plaque composition under different stable conditions have not been fully understood. The development of high-throughput sequencing, molecular biology experiments, and metabonomics have provided new research ideas to solve this problem. They can become an effective means to explore the microbiome surrounding TADs.
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Affiliation(s)
- Ning-Rui Zhao
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Yan-Ning Guo
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Sheng-Jie Cui
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Ya-Jing Tian
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Yan-Heng Zhou
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China
| | - Xue-Dong Wang
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, 100081, China.
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191
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Vega L, Bohórquez L, Ramírez JD, Muñoz M. Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases. Front Cell Infect Microbiol 2022; 12:918237. [PMID: 36478676 PMCID: PMC9719923 DOI: 10.3389/fcimb.2022.918237] [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: 04/12/2022] [Accepted: 10/31/2022] [Indexed: 11/22/2022] Open
Abstract
Introduction The gut microbiome is involved in multiple processes that influence host physiology, and therefore, disruptions in microbiome homeostasis have been linked to diseases or secondary infections. Given the importance of the microbiome and the communities of microorganisms that compose it (microbiota), the term biomarkers were coined, which are bacteria correlated with disease states, diets, and the lifestyle of the host. However, a large field in the study of intestinal biomarkers remains unexplored because the bacterial communities associated with a given disease state have not been exactly defined yet. Methods Here, we analyzed public data of studies focused on describing the intestinal microbiota of patients with some intestinal inflammatory diseases together with their respective controls. With these analyses, we aimed to identify differentially abundant bacteria between the subjects with the disease and their controls. Results We found that frequently reported bacteria such as Fusobacterium, Streptococcus, and Escherichia/Shigella were differentially abundant between the groups, with a higher abundance mostly in patients with the disease in contrast with their controls. On the other hand, we also identified potentially beneficial bacteria such as Faecalibacterium and Phascolarctobacterium, with a higher abundance in control patients. Discussion Our results of the differentially abundant bacteria contrast with what was already reported in previous studies on certain inflammatory diseases, but we highlight the importance of considering more comprehensive approaches to redefine or expand the definition of biomarkers. For instance, the intra-taxa diversity within a bacterial community must be considered, as well as environmental and genetic factors of the host, and even consider a functional validation of these biomarkers through in vivo and in vitro approaches. With the above, these key bacterial communities in the intestinal microbiota may have potential as next-generation probiotics or may be functional for the design of specific therapies in certain intestinal diseases.
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Affiliation(s)
- Laura Vega
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Laura Bohórquez
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia
| | - Juan David Ramírez
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia,Molecular Microbiology Laboratory, Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Marina Muñoz
- Centro de Investigaciones en Microbiología y Biotecnología-UR (CIMBIUR), Facultad de Ciencias Naturales, Universidad del Rosario, Bogotá, Colombia,*Correspondence: Marina Muñoz,
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192
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Navgire GS, Goel N, Sawhney G, Sharma M, Kaushik P, Mohanta YK, Mohanta TK, Al-Harrasi A. Analysis and Interpretation of metagenomics data: an approach. Biol Proced Online 2022; 24:18. [PMID: 36402995 PMCID: PMC9675974 DOI: 10.1186/s12575-022-00179-7] [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: 07/28/2022] [Accepted: 10/19/2022] [Indexed: 11/20/2022] Open
Abstract
Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8-10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process.
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Affiliation(s)
- Gauri S Navgire
- Department of Microbiology, Savitribai Phule Pune University, Pune, Maharastra, 411007, India
| | - Neha Goel
- Department of Genetics and Tree Improvement, Forest Research Institute, 248006, Dehradun, India
| | - Gifty Sawhney
- Inflammation Pharmacology Division, Academy of Scientific and Innovative Research (AcSIR), CSIR-Indian Institute of Integrative Medicine, Jammu-180001, Jammu Kashmir, India
| | - Mohit Sharma
- Department of Molecular Medicine, Medical University of Warsaw and Malopolska Center of Biotechnology, Karkow, Poland
| | | | | | - Tapan Kumar Mohanta
- Natural and Medical Sciences Research Center, University of Nizwa, Nizwa, 616, Oman.
| | - Ahmed Al-Harrasi
- Natural and Medical Sciences Research Center, University of Nizwa, Nizwa, 616, Oman.
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Zhao N, Ma Z, Jiang Y, Shi Y, Xie Y, Wang Y, Wu S, Liu S, Wang S. Geographical patterns of Fejervarya limnocharis gut microbiota by latitude along mainland China’s coastline. Front Microbiol 2022; 13:1062302. [DOI: 10.3389/fmicb.2022.1062302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/02/2022] [Indexed: 11/18/2022] Open
Abstract
The gut microbiota affects many aspects of host biology and plays key roles in the coevolutionary association with its host. Geographical gradients may play a certain role on gut microbiota variation in the natural environment. However, the distribution pattern of amphibian gut microbiota in the latitudinal gradient remains largely unexplored. Here, we sampled six natural populations of Fejervarya limnocharis along the eastern coastline of mainland China (spanning 20°–30° N = 1,300 km) using 16S rRNA amplicon sequencing to characterize the gut microbiota. First of all, a significant correlation between gut microbial diversity and latitude was observed in our research system. Second, we discovered that latitude influenced the composition of the gut microbiota of F. limnocharis. Finally, we detected that geographical distance could not determine gut microbiota composition in F. limnocharis. These results indicate that latitude can play an important role in shaping the gut microbial diversity of amphibian. Our study offers the first evidence that gut microbial diversity of amphibian presents a latitudinal pattern and highlights the need for increased numbers of individuals to be sampled during microbiome studies in wild populations along environmental gradients.
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194
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The microbial community associated with Parascaris spp. infecting juvenile horses. Parasit Vectors 2022; 15:408. [PMID: 36333754 PMCID: PMC9636743 DOI: 10.1186/s13071-022-05533-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 10/05/2022] [Indexed: 11/06/2022] Open
Abstract
Background Parasitic nematodes, including large roundworms colloquially known as ascarids, affect the health and well-being of livestock animals worldwide. The equine ascarids, Parascaris spp., are important parasites of juvenile horses and the first ascarids to develop widespread anthelmintic resistance. The microbiota has been shown to be an important factor in the fitness of many organisms, including parasitic nematodes, where endosymbiotic Wolbachia have been exploited for treatment of filariasis in humans. Methods This study used short-read 16S rRNA sequences and Illumina sequencing to characterize and compare microbiota of whole worm small intestinal stages and microbiota of male and female intestines and gonads. Diversity metrics including alpha and beta diversity, and the differential abundance analyses DESeq2, ANCOM-BC, corncob, and metagenomeSeq were used for comparisons. Results Alpha and beta diversity of whole worm microbiota did not differ significantly between groups, but Simpson alpha diversity was significantly different between female intestine (FI) and male gonad (MG) (P= 0.0018), and Shannon alpha diversity was significantly different between female and male gonads (P = 0.0130), FI and horse jejunum (HJ) (P = 0.0383), and FI and MG (P= 0.0001). Beta diversity (Fig. 2B) was significantly different between female and male gonads (P = 0.0006), male intestine (MI) and FG (P = 0.0093), and MG and FI (P = 0.0041). When comparing organs, Veillonella was differentially abundant for DESeq2 and ANCOM-BC (p < 0.0001), corncob (P = 0.0008), and metagenomeSeq (P = 0.0118), and Sarcina was differentially abundant across four methods (P < 0.0001). Finally, the microbiota of all individual Parascaris spp. specimens were compared to establish shared microbiota between groups. Conclusions Overall, this study provided important information regarding the Parascaris spp. microbiota and provides a first step towards determining whether the microbiota may be a viable target for future parasite control options. Graphical abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s13071-022-05533-y.
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Wang P, Liu T, Liu J, Duan Y, Han S, Zhang Z, Li L, Lin Y. Effects of different colored polyethylene mulching films on bacterial communities from soil during enrichment incubation. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 246:114160. [PMID: 36215881 DOI: 10.1016/j.ecoenv.2022.114160] [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: 07/07/2022] [Revised: 09/27/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Studies have shown that mulching agricultural fields with plastic residues can influence microbial communities in the environment, but few studies have investigated the differences in the soil microbial communities in distinct areas under mulching with different colored plastic products. Thus, in this study, we explored how different colored polyethylene mulching films (PMFs) might affect soil bacterial communities during enrichment incubation. We found significant differences in the bacterial communities under different colored PMFs after incubation. Treatment with the same colored PMF obtained more similar bacterial community compositions. For instance, at the class level, Gammaproteobacteria and Bacteroidia were most abundant with black PMF, whereas Actinobacteria and Bacteroidia were most abundant with white PMF. The most abundant genera were Acinetobacter and Chryseobacterium with black PMF but Rhodanobacter and Paenarthrobacter with white PMF. Polyethylene- and hydrocarbon-degrading bacteria were the core members detected under both treatments, and the bacterial communities were predicted to have the potential for the biodegradation and metabolism of xenobiotics after enrichment culture according to the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) tool. In addition, the bacterial communities in soil from Xinjiang treated with white PMF and in soil from Yangling treated with black PMF were strongly correlated and stable. Our results suggest that the color of the PMF applied affected the soil bacterial communities, where plastics with the same color may have recruited similar species of microorganisms, although the origins of these microorganisms were not the same.
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Affiliation(s)
- Peiyuan Wang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Tingting Liu
- College of Science, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jiaxi Liu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yifan Duan
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Siqi Han
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zengqiang Zhang
- College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Li Li
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
| | - Yanbing Lin
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China; State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.
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Wei L, Zhu Z, Razavi BS, Xiao M, Dorodnikov M, Fan L, Yuan H, Yurtaev A, Luo Y, Cheng W, Kuzyakov Y, Wu J, Ge T. Visualization and quantification of carbon "rusty sink" by rice root iron plaque: Mechanisms, functions, and global implications. GLOBAL CHANGE BIOLOGY 2022; 28:6711-6727. [PMID: 35986445 DOI: 10.1111/gcb.16372] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/15/2022] [Accepted: 07/25/2022] [Indexed: 06/15/2023]
Abstract
Paddies contain 78% higher organic carbon (C) stocks than adjacent upland soils, and iron (Fe) plaque formation on rice roots is one of the mechanisms that traps C. The process sequence, extent and global relevance of this C stabilization mechanism under oxic/anoxic conditions remains unclear. We quantified and localized the contribution of Fe plaque to organic matter stabilization in a microoxic area (rice rhizosphere) and evaluated roles of this C trap for global C sequestration in paddy soils. Visualization and localization of pH by imaging with planar optodes, enzyme activities by zymography, and root exudation by 14 C imaging, as well as upscale modeling enabled linkage of three groups of rhizosphere processes that are responsible for C stabilization from the micro- (root) to the macro- (ecosystem) levels. The 14 C activity in soil (reflecting stabilization of rhizodeposits) with Fe2+ addition was 1.4-1.5 times higher than that in the control and phosphate addition soils. Perfect co-localization of the hotspots of β-glucosidase activity (by zymography) with root exudation (14 C) showed that labile C and high enzyme activities were localized within Fe plaques. Fe2+ addition to soil and its microbial oxidation to Fe3+ by radial oxygen release from rice roots increased Fe plaque (Fe3+ ) formation by 1.7-2.5 times. The C amounts trapped by Fe plaque increased by 1.1 times after Fe2+ addition. Therefore, Fe plaque formed from amorphous and complex Fe (oxyhydr)oxides on the root surface act as a "rusty sink" for organic matter. Considering the area of coverage of paddy soils globally, upscaling by model revealed the radial oxygen loss from roots and bacterial Fe oxidation may trap up to 130 Mg C in Fe plaques per rice season. This represents an important annual surplus of new and stable C to the existing C pool under long-term rice cropping.
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Affiliation(s)
- Liang Wei
- Key Laboratory of Agro-ecological Processes in Subtropical Region & Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Plant Virology, Ningbo University, Ningbo, China
| | - Zhenke Zhu
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Plant Virology, Ningbo University, Ningbo, China
| | - Bahar S Razavi
- Department of Soil and Plant Microbiome, Institute of Phytopathology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Mouliang Xiao
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Plant Virology, Ningbo University, Ningbo, China
| | - Maxim Dorodnikov
- Department of Soil Science of Temperate Ecosystems, Department of Agricultural Soil Science, University of Goettingen, Goettingen, Germany
- Research Institute of Ecology and Natural Resources Management, Tyumen State University, Tyumen, Russia
| | - Lichao Fan
- Department of Soil Science of Temperate Ecosystems, Department of Agricultural Soil Science, University of Goettingen, Goettingen, Germany
- College of Natural Resources and Environment, Northwest A&F University, Yangling, China
| | - Hongzhao Yuan
- Key Laboratory of Agro-ecological Processes in Subtropical Region & Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China
| | - Andrey Yurtaev
- Research Institute of Ecology and Natural Resources Management, Tyumen State University, Tyumen, Russia
| | - Yu Luo
- Institute of Soil and Water Resources and Environmental Science, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou, China
| | - Weiguo Cheng
- Faculty of Agriculture, Yamagata University, Tsuruoka, Japan
| | - Yakov Kuzyakov
- Key Laboratory of Agro-ecological Processes in Subtropical Region & Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China
- Department of Soil Science of Temperate Ecosystems, Department of Agricultural Soil Science, University of Goettingen, Goettingen, Germany
- Peoples Friendship University of Russia (RUDN University), Moscow, Russia
| | - Jinshui Wu
- Key Laboratory of Agro-ecological Processes in Subtropical Region & Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China
| | - Tida Ge
- Key Laboratory of Agro-ecological Processes in Subtropical Region & Changsha Research Station for Agricultural and Environmental Monitoring, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Plant Virology, Ningbo University, Ningbo, China
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197
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Zhang R, Zhao Y, Liu J, Yang S, Jing L. The response of bacterial community to UVB was significantly different between immature periphyton and mature periphyton, but not for physiological indicators. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 246:114185. [PMID: 36244171 DOI: 10.1016/j.ecoenv.2022.114185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/22/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
Periphyton has important ecological functions. It can even exist in environments with strong ultraviolet radiation. However, knowledge of periphyton under ultraviolet is limited, which limits the understanding and application of periphyton in environments with high ultraviolet radiation. In this study, immature periphyton (IMP) and mature periphyton (MP) under ultraviolet B (UVB) irradiation were investigated and compared in terms of physiological characteristics and bacterial community. Analysis of the physiological characteristics showed that the response patterns of IMP and MP to UVB were similar. IMP and MP could adapt to UVB of 1 W/m2 well. However, high-intensity UVB (2 and 3 W/m2) reduced the periphyton biomass, inhibited photosynthesis and antioxidant enzyme activity and caused severe lipid peroxidation in both IMP and MP. Integrated Biological Response (IBR) analysis and toxicological model fitting showed that the ED50 values of UVB for IMP and MP were 1.25 and 1.50 W/m2, respectively. 16 S rRNA gene analysis showed that in both IMP and MP, bacterial community composition, assembly and function were affected by UVB. In addition, the response of the bacterial community in IMP to UVB was stronger than that in MP. The diversity of the IMP community was inhibited by UVB, but that of the MP community was not. Proteobacteria and Deinococcus-Thermus are key microorganisms responsible for tolerance to UVB stress. Neutral community model fitting showed that both UVB and the development process caused the determinism of bacterial succession. However, UVB may weaken the deterministic process caused by development. Functional prediction showed that many metabolic functions of periphyton were inhibited by UVB in IMP and MP. However, UVB caused different changes (enhancement or inhibition) of some ecological functions in them. This study provides valuable information for understanding periphyton in environments with UVB radiation, which may be used to improve the application of periphyton in these environments.
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Affiliation(s)
- Run Zhang
- Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Key Laboratory of General Chemistry of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Yue Zhao
- Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Key Laboratory of General Chemistry of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Jia Liu
- Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Key Laboratory of General Chemistry of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Shengtao Yang
- Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Key Laboratory of General Chemistry of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China
| | - Liandong Jing
- Key Laboratory of Pollution Control Chemistry and Environmental Functional Materials for Qinghai-Tibet Plateau of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China; Key Laboratory of General Chemistry of the National Ethnic Affairs Commission, School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, China.
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198
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Liu J, Bao Z, Wang C, Wei J, Wei Y, Chen M. Understanding of mercury and methylmercury transformation in sludge composting by metagenomic analysis. WATER RESEARCH 2022; 226:119204. [PMID: 36244140 DOI: 10.1016/j.watres.2022.119204] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/21/2022] [Accepted: 10/03/2022] [Indexed: 06/16/2023]
Abstract
Municipal sewage especially the produced sewage sludge is a significant source releasing mercury (Hg) to the environment. However, the Hg speciation especially methylmercury (MeHg) transformation in sewage sludge treatment process remains poorly understood. This study investigated the transformation of Hg speciation especially MeHg in sludge composting. The distribution of Hg transformation related gene pairs hgcAB and merAB, and their putative microbial hosts were comprehensively analyzed. Both Hg (from 3.16±0.22 mg/kg to 3.20±0.19 mg/kg) and MeHg content (from 4.77±0.64 ng/g to 4.36±0.37 ng/g) were not obviously changed before and after composting, but about 19.69% of Hg and 27.36% of MeHg were lost according to mass balance calculation. The metagenomic analysis further revealed that anaerobes (Desulfobacterota and Euryarchaeota) were the mainly putative Hg methylators especially carrying high abundance of hgcA gene in the initial periods of composting. Among the 151 reconstructed metagenome-assembled genomes (MAGs), only 4 hgcA gene carriers (Myxococcota, Firmicutes, Cyclobacteriaceae, and Methanothermobacter) and 16 merB gene carriers were identified. But almost all of the MAGs carried hgcB gene and merA gene. The merA gene was widely distributed in genomes, which indicated the widespread functionality of microbes for reducing Hg(II) to Hg(0). The hgcA carrying microbes tends to present the similar metabolic pathways including methanogenesis and sulfur metabolism. Besides, both the irregular distribution of hgcA in various species (including Actinobacteria, Archaea, Bacteroidetes, Desulfobacterota, Euryarchaeota, and Nitrospirae, etc.) and opposite evolution trends between hgcA gene abundance and its host genome abundance can be an indication of horizontal gene transfer or gene deletions of hgcA during composting. Our findings thus revealed that sludge composting is not only a hotspot for Hg speciation transformation, but also a potential hotspot for MeHg transformation.
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Affiliation(s)
- Jibao Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Zhen Bao
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Chenlu Wang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jinyi Wei
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuansong Wei
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Meixue Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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199
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Lei B, Xu Y, Lei Y, Li C, Zhou P, Wang L, Yang Q, Li X, Li F, Liu C, Cui C, Chen T, Ni W, Hu S. CRAMdb: a comprehensive database for composition and roles of microbiome in animals. Nucleic Acids Res 2022; 51:D700-D707. [PMID: 36318246 PMCID: PMC9825719 DOI: 10.1093/nar/gkac973] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 10/05/2022] [Accepted: 10/29/2022] [Indexed: 01/09/2023] Open
Abstract
CRAMdb (a database for composition and roles of animal microbiome) is a comprehensive resource of curated and consistently annotated metagenomes for non-human animals. It focuses on the composition and roles of the microbiome in various animal species. The main goal of the CRAMdb is to facilitate the reuse of animal metagenomic data, and enable cross-host and cross-phenotype comparisons. To this end, we consistently annotated microbiomes (including 16S, 18S, ITS and metagenomics sequencing data) of 516 animals from 475 projects spanning 43 phenotype pairs to construct the database that is equipped with 9430 bacteria, 278 archaea, 2216 fungi and 458 viruses. CRAMdb provides two main contents: microbiome composition data, illustrating the landscape of the microbiota (bacteria, archaea, fungi, and viruses) in various animal species, and microbiome association data, revealing the relationships between the microbiota and various phenotypes across different animal species. More importantly, users can quickly compare the composition of the microbiota of interest cross-host or body site and the associated taxa that differ between phenotype pairs cross-host or cross-phenotype. CRAMdb is freely available at (http://www.ehbio.com/CRAMdb).
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Affiliation(s)
| | | | | | - Cunyuan Li
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China,Key Laboratory of Ecological Corps for Oasis City and Mountain Basin System, College of Science, Shihezi University, Shihezi, Xinjiang 832000, China
| | - Ping Zhou
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science, Xinjiang 832003, China
| | - Limin Wang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Science, Xinjiang 832003, China
| | - Qing Yang
- Key Laboratory of Ecological Impacts of Hydraulic-Projects and Restoration of Aquatic Ecosystem of Ministry of Water Resources, Institute of Hydroecology Ministry of Water Resources and Chinese Academy of Sciences, Wuhan 430079, China
| | - Xiaoyue Li
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Fulin Li
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Chuyang Liu
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Chaowen Cui
- College of Life Sciences, Shihezi University, Shihezi, Xinjiang 832003, China
| | - Tong Chen
- Correspondence may also be addressed to Tong Chen.
| | - Wei Ni
- Correspondence may also be addressed to Wei Ni.
| | - Shengwei Hu
- To whom correspondence should be addressed. Tel: +86 993 2058002; Fax: +86 993 2058002;
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200
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The Role of the Cutaneous Mycobiome in Atopic Dermatitis. J Fungi (Basel) 2022; 8:jof8111153. [DOI: 10.3390/jof8111153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
Atopic dermatitis is a chronic inflammatory skin disorder characterized by eczematous lesions, itch, and a significant deterioration in the quality of life. Recently, microbiome dysbiosis has been implicated in the pathogenesis of atopic dermatitis. Changes in the fungal microbiome (also termed mycobiome) appear to be an important factor influencing the clinical picture of this entity. This review summarizes the available insights into the role of the cutaneous mycobiome in atopic dermatitis and the new research possibilities in this field. The prevalence and characteristics of key fungal species, the most important pathogenesis pathways, as well as classic and emerging therapies of fungal dysbiosis and infections complicating atopic dermatitis, are presented.
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