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Tian Q, Zhang P, Zhai Y, Wang Y, Zou Q. Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data. Genome Biol Evol 2024; 16:evae102. [PMID: 38748485 PMCID: PMC11135637 DOI: 10.1093/gbe/evae102] [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] [Accepted: 05/12/2024] [Indexed: 05/30/2024] Open
Abstract
The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and analyzing the deluge of sequencing data for precise taxonomic classification remains a formidable challenge. Existing classification approaches primarily fall into two categories, database-based methods and machine learning methods, each presenting its own set of challenges and advantages. On this basis, the aim of our study was to conduct a comparative analysis between these two methods while also investigating the merits of integrating multiple database-based methods. Through an in-depth comparative study, we evaluated the performance of both methodological categories in taxonomic classification by utilizing simulated data sets. Our analysis revealed that database-based methods excel in classification accuracy when backed by a rich and comprehensive reference database. Conversely, while machine learning methods show superior performance in scenarios where reference sequences are sparse or lacking, they generally show inferior performance compared with database methods under most conditions. Moreover, our study confirms that integrating multiple database-based methods does, in fact, enhance classification accuracy. These findings shed new light on the taxonomic classification of high-throughput sequencing data and bear substantial implications for the future development of computational biology. For those interested in further exploring our methods, the source code of this study is publicly available on https://github.com/LoadStar822/Genome-Classifier-Performance-Evaluator. Additionally, a dedicated webpage showcasing our collected database, data sets, and various classification software can be found at http://lab.malab.cn/~tqz/project/taxonomic/.
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Affiliation(s)
- Qinzhong Tian
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003 China
| | - Pinglu Zhang
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003 China
| | - Yixiao Zhai
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003 China
| | - Yansu Wang
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003 China
| | - Quan Zou
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324003 China
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Lin WZ, Chen BY, Qiu P, Zhou LJ, Li YL, Du LJ, Liu Y, Wang YL, Zhu H, Wu XY, Liu X, Duan SZ, Zhu YQ. Altered salivary microbiota profile in patients with abdominal aortic aneurysm. Heliyon 2023; 9:e23040. [PMID: 38144289 PMCID: PMC10746442 DOI: 10.1016/j.heliyon.2023.e23040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 11/19/2023] [Accepted: 11/24/2023] [Indexed: 12/26/2023] Open
Abstract
Evidence suggests that the DNA of oral pathogens is detectable in the dilated aortic tissue of abdominal aortic aneurysm (AAA), one of the most fatal cardiovascular diseases. However, the association between oral microbial homeostasis and aneurysm formation remains largely unknown. In this study, a cohort of individuals, including 53 AAA patients and 30 control participants (CTL), was recruited for salivary microbiota investigation by 16S rRNA gene sequencing and bioinformatics analysis. Salivary microbial diversity was decreased in AAA compared with CTL, and the microbial structures were significantly separated between the two groups. Additionally, significant taxonomic and functional changes in the salivary microbiota of AAA participants were observed. The genera Streptococcus and Gemella were remarkably enriched, while Selenomonas, Leptotrichia, Lautropia and Corynebacterium were significantly depleted in AAA. Co-occurrence network analysis showed decreased potential interactions among the differentially abundant microbial genera in AAA. A machine-learning model predicted AAA using the combination of 5 genera and 14 differentially enriched functional pathways, which could distinguish AAA from CTL with an area under the receiver-operating curve of 90.3 %. Finally, 16 genera were found to be significantly positively correlated with the morphological parameters of AAA. Our study is the first to show that AAA patients exhibit oral microbial dysbiosis, which has high predictive power for AAA, and the over-representation of specific salivary bacteria may be associated with AAA disease progression. Further studies are needed to better understand the function of putative oral bacteria in the etiopathogenesis of AAA. Importance Host microbial dysbiosis has recently been linked to AAA as a possible etiology. To our knowledge, studies of the oral microbiota and aneurysms remain scarce, although previous studies have indicated that the DNA of some oral pathogens is detectable in aneurysms by PCR method. We take this field one step further by investigating the oral microbiota composition of AAA patients against control participants via high-throughput sequencing technologies and unveiling the potential microbial biomarker associated with AAA formation. Our study will provide new insights into AAA etiology, treatment and prevention from a microecological perspective and highlight the effects of oral microbiota on vascular health.
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Affiliation(s)
- Wen-Zhen Lin
- Department of General Dentistry, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Bo-Yan Chen
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Peng Qiu
- Department of Vascular Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lu-Jun Zhou
- Department of General Dentistry, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Yu-Lin Li
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Lin-Juan Du
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Yuan Liu
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Yong-Li Wang
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Hong Zhu
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Xiao-Yu Wu
- Department of Vascular Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaobing Liu
- Department of Vascular Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sheng-Zhong Duan
- Laboratory of Oral Microbiota and Systemic Diseases, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
| | - Ya-Qin Zhu
- Department of General Dentistry, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- College of Stomatology, Shanghai Jiao Tong University, Shanghai, China
- National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology; Shanghai Research Institute of Stomatology; Research Unit of Oral and Maxillofacial Regenerative Medicine, Chinese Academy of Medical Sciences, Shanghai, China
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Aminu S, Ascandari A, Laamarti M, Safdi NEH, El Allali A, Daoud R. Exploring microbial worlds: a review of whole genome sequencing and its application in characterizing the microbial communities. Crit Rev Microbiol 2023:1-25. [PMID: 38006569 DOI: 10.1080/1040841x.2023.2282447] [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: 05/22/2023] [Accepted: 11/06/2023] [Indexed: 11/27/2023]
Abstract
The classical microbiology techniques have inherent limitations in unraveling the complexity of microbial communities, necessitating the pivotal role of sequencing in studying the diversity of microbial communities. Whole genome sequencing (WGS) enables researchers to uncover the metabolic capabilities of the microbial community, providing valuable insights into the microbiome. Herein, we present an overview of the rapid advancements achieved thus far in the use of WGS in microbiome research. There was an upsurge in publications, particularly in 2021 and 2022 with the United States, China, and India leading the metagenomics research landscape. The Illumina platform has emerged as the widely adopted sequencing technology, whereas a significant focus of metagenomics has been on understanding the relationship between the gut microbiome and human health where distinct bacterial species have been linked to various diseases. Additionally, studies have explored the impact of human activities on microbial communities, including the potential spread of pathogenic bacteria and antimicrobial resistance genes in different ecosystems. Furthermore, WGS is used in investigating the microbiome of various animal species and plant tissues such as the rhizosphere microbiome. Overall, this review reflects the importance of WGS in metagenomics studies and underscores its remarkable power in illuminating the variety and intricacy of the microbiome in different environments.
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Affiliation(s)
- Suleiman Aminu
- Chemical and Biochemical Sciences-Green Process Engineering, University Mohammed VI Polytechnic, Ben Guerir, Morocco
- Department of Biochemistry, Ahmadu Bello University, Zaria, Nigeria
| | - AbdulAziz Ascandari
- Chemical and Biochemical Sciences-Green Process Engineering, University Mohammed VI Polytechnic, Ben Guerir, Morocco
| | - Meriem Laamarti
- Faculty of Medical Sciences, University Mohammed VI Polytechnic, Ben Guerir, Morocco
| | - Nour El Houda Safdi
- AgroBioSciences Program, College for Sustainable Agriculture and Environmental Science, University Mohammed VI Polytechnic, Ben Guerir, Morocco
| | - Achraf El Allali
- Bioinformatics Laboratory, College of Computing, University Mohammed VI Polytechnic, Ben Guerir, Morocco
| | - Rachid Daoud
- Chemical and Biochemical Sciences-Green Process Engineering, University Mohammed VI Polytechnic, Ben Guerir, Morocco
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Leiva C, Pérez-Portela R, Lemer S. Genomic signatures suggesting adaptation to ocean acidification in a coral holobiont from volcanic CO 2 seeps. Commun Biol 2023; 6:769. [PMID: 37481685 PMCID: PMC10363134 DOI: 10.1038/s42003-023-05103-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 07/06/2023] [Indexed: 07/24/2023] Open
Abstract
Ocean acidification, caused by anthropogenic CO2 emissions, is predicted to have major consequences for reef-building corals, jeopardizing the scaffolding of the most biodiverse marine habitats. However, whether corals can adapt to ocean acidification and how remains unclear. We addressed these questions by re-examining transcriptome and genome data of Acropora millepora coral holobionts from volcanic CO2 seeps with end-of-century pH levels. We show that adaptation to ocean acidification is a wholistic process involving the three main compartments of the coral holobiont. We identified 441 coral host candidate adaptive genes involved in calcification, response to acidification, and symbiosis; population genetic differentiation in dinoflagellate photosymbionts; and consistent transcriptional microbiome activity despite microbial community shifts. Coral holobionts from natural analogues to future ocean conditions harbor beneficial genetic variants with far-reaching rapid adaptation potential. In the face of climate change, these populations require immediate conservation strategies as they could become key to coral reef survival.
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Affiliation(s)
- Carlos Leiva
- University of Guam Marine Laboratory, 303 University Drive, 96923, Mangilao, Guam, USA.
| | - Rocío Pérez-Portela
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona, Av. Diagonal 643, 08028, Barcelona, Spain
- Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | - Sarah Lemer
- University of Guam Marine Laboratory, 303 University Drive, 96923, Mangilao, Guam, USA
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Ritchie G, Strodl E, Parham S, Bambling M, Cramb S, Vitetta L. An exploratory study of the gut microbiota in major depression with anxious distress. J Affect Disord 2023; 320:595-604. [PMID: 36209779 DOI: 10.1016/j.jad.2022.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 09/29/2022] [Accepted: 10/02/2022] [Indexed: 11/13/2022]
Abstract
OBJECTIVES To explore differences in the diversity and composition of the gut microbiome between major depressive disorder (MDD) with and without anxious distress. METHODS The study comprised 117 participants (79 female, 36 male, 2 other, mean age 38.2 ± 13.4 years) with a current major depressive episode (MDE) with (n = 63) and without (n = 54) the anxious distress specifier. A clinical psychologist administered the structured clinical interview for the DSM-5-RV to confirm a diagnosis of depression. Participants provided stool samples which were immediately frozen and stored at -80 °C. These samples were analysed using the Illumina 16S Metagenomics sequencing protocol in which the sequencing primers target the V3 and V4 regions of the 16S rRNA gene. Participants also completed mental health questionnaires to assess severity of depression (BDI-II), generalized anxiety (GAD-7), and stress (PSS). RESULTS There were no significant group differences in α-diversity (Shannon's diversity Index; Simpson Index), richness (ACE; Chao1), (Pielou's) evenness, or beta diversity (Bray-Curtis dissimilarity index and weighted UniFrac distance) of gut bacteria. Significant group differences in the relative abundance of gut microbiota however were observed at each taxonomical level, including across 15 genera and 18 species. LIMITATIONS This was an exploratory study that needs to be replicated across larger samples and compared with a healthy control group. CONCLUSIONS The research contributes to knowledge of the depressive gut microbial profile unique to the anxious distress subtype of MDD.
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Affiliation(s)
- Gabrielle Ritchie
- Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia.
| | - Esben Strodl
- Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
| | - Sophie Parham
- Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
| | - Matthew Bambling
- Faculty of Medicine, University of Queensland, Herston, Queensland, Australia
| | - Susanna Cramb
- Australian Centre for Health Services Innovation & Centre for Healthcare Transformation, Queensland University of Technology, Brisbane, Australia
| | - Luis Vitetta
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.; Medlab Clinical, Sydney, New South Wales, Australia
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Haiminen N, Utro F, Seabolt E, Parida L. Functional profiling of COVID-19 respiratory tract microbiomes. Sci Rep 2021; 11:6433. [PMID: 33742096 PMCID: PMC7979704 DOI: 10.1038/s41598-021-85750-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 03/03/2021] [Indexed: 12/13/2022] Open
Abstract
In response to the ongoing global pandemic, characterizing the molecular-level host interactions of the new coronavirus SARS-CoV-2 responsible for COVID-19 has been at the center of unprecedented scientific focus. However, when the virus enters the body it also interacts with the micro-organisms already inhabiting the host. Understanding the virus-host-microbiome interactions can yield additional insights into the biological processes perturbed by viral invasion. Alterations in the gut microbiome species and metabolites have been noted during respiratory viral infections, possibly impacting the lungs via gut-lung microbiome crosstalk. To better characterize microbial functions in the lower respiratory tract during COVID-19 infection, we carry out a functional analysis of previously published metatranscriptome sequencing data of bronchoalveolar lavage fluid from eight COVID-19 cases, twenty-five community-acquired pneumonia patients, and twenty healthy controls. The functional profiles resulting from comparing the sequences against annotated microbial protein domains clearly separate the cohorts. By examining the associated metabolic pathways, distinguishing functional signatures in COVID-19 respiratory tract microbiomes are identified, including decreased potential for lipid metabolism and glycan biosynthesis and metabolism pathways, and increased potential for carbohydrate metabolism pathways. The results include overlap between previous studies on COVID-19 microbiomes, including decrease in the glycosaminoglycan degradation pathway and increase in carbohydrate metabolism. The results also suggest novel connections to consider, possibly specific to the lower respiratory tract microbiome, calling for further research on microbial functions and host-microbiome interactions during SARS-CoV-2 infection.
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Affiliation(s)
- Niina Haiminen
- IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
| | - Filippo Utro
- IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
| | - Ed Seabolt
- IBM Almaden Research Center, San Jose, CA, USA
| | - Laxmi Parida
- IBM T. J. Watson Research Center, Yorktown Heights, NY, USA.
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