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Tang ID, Mallia D, Yan Q, Pe'er I, Raja A, Salleb-Aouissi A, Wapner R. A Scoping Review of Preterm Birth Risk Factors. Am J Perinatol 2024; 41:e2804-e2817. [PMID: 37748506 DOI: 10.1055/s-0043-1775564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
Preterm birth is a major cause of neonatal morbidity and mortality, but its etiology and risk factors are poorly understood. We undertook a scoping review to illustrate the breadth of risk factors for preterm birth that have been reported in the literature. We conducted a search in the PubMed database for articles published in the previous 5 years. We determined eligibility for this scoping review by screening titles and abstracts, followed by full-text review. We extracted odds ratios and other measures of association for each identified risk factor in the articles. A total of 2,509 unique articles were identified from the search, of which 314 were eligible for inclusion in our final analyses. We summarized risk factors and their relative impacts in the following categories: Activity, Psychological, Medical History, Toxicology, Genetics, and Vaginal Microbiome. Many risk factors for preterm birth have been reported. It is challenging to synthesize findings given the multitude of isolated risk factors that have been studied, inconsistent definitions of risk factors and outcomes, and use of different covariates in analyses. Novel methods of analyzing large datasets may promote a more comprehensive understanding of the etiology of preterm birth and ability to predict the outcome. KEY POINTS: · Preterm birth is difficult to predict.. · Preterm birth has many diverse risk factors.. · Holistic approaches may yield new insights..
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Affiliation(s)
- Irene D Tang
- Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Daniel Mallia
- Department of Computer Science, Hunter College, New York, New York
| | - Qi Yan
- Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, New York
| | - Itsik Pe'er
- Department of Computer Science, Columbia University, New York, New York
| | - Anita Raja
- Department of Computer Science, Hunter College, New York, New York
| | | | - Ronald Wapner
- Department of Obstetrics and Gynecology, Columbia University Medical Center, New York, New York
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2
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Wei X, Tsai MS, Liang L, Jiang L, Hung CJ, Jelliffe-Pawlowski L, Rand L, Snyder M, Jiang C. Vaginal microbiomes show ethnic evolutionary dynamics and positive selection of Lactobacillus adhesins driven by a long-term niche-specific process. Cell Rep 2024; 43:114078. [PMID: 38598334 DOI: 10.1016/j.celrep.2024.114078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 03/01/2024] [Accepted: 03/22/2024] [Indexed: 04/12/2024] Open
Abstract
The vaginal microbiome's composition varies among ethnicities. However, the evolutionary landscape of the vaginal microbiome in the multi-ethnic context remains understudied. We perform a systematic evolutionary analysis of 351 vaginal microbiome samples from 35 multi-ethnic pregnant women, in addition to two validation cohorts, totaling 462 samples from 90 women. Microbiome alpha diversity and community state dynamics show strong ethnic signatures. Lactobacillaceae have a higher ratio of non-synonymous to synonymous polymorphism and lower nucleotide diversity than non-Lactobacillaceae in all ethnicities, with a large repertoire of positively selected genes, including the mucin-binding and cell wall anchor genes. These evolutionary dynamics are driven by the long-term evolutionary process unique to the human vaginal niche. Finally, we propose an evolutionary model reflecting the environmental niches of microbes. Our study reveals the extensive ethnic signatures in vaginal microbial ecology and evolution, highlighting the importance of studying the host-microbiome ecosystem from an evolutionary perspective.
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Affiliation(s)
- Xin Wei
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Ming-Shian Tsai
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Liang Liang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Liuyiqi Jiang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China
| | - Chia-Jui Hung
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Informatics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Laura Jelliffe-Pawlowski
- Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Larry Rand
- Department of Obstetrics, Gynecology & Reproductive Sciences, School of Medicine, University of California, San Francisco, San Francisco, CA 94158, USA.
| | - Michael Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
| | - Chao Jiang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310030, China; State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
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3
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Zhou Q, Yu Y, Zhou J, Liu J, Gao J. Relationship of Lactobacillus Vaginal Microbiota Changes and the Risk of Preterm Birth: A Systematic Review and Meta-Analysis. J Womens Health (Larchmt) 2024; 33:228-238. [PMID: 38064523 DOI: 10.1089/jwh.2023.0393] [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: 02/18/2024] Open
Abstract
Objective: With a global incidence of more than 10%, preterm birth (PTB) remains a significant concern. The vaginal microbiome strongly influences the well-being of the female reproductive tract. This study examines the correlation between changes in Lactobacillus vaginal microbiota and the PTB risk. Materials and Methods: A thorough search of PubMed, Web of Science, Cochrane Library, and EMBASE was conducted to locate studies that examined the association between changes in Lactobacillus vaginal microbiota and the risk of PTB from January 1, 2010, to January 30, 2023. The risk of PTB was determined by calculating odds ratios (ORs) with 95% confidence intervals (CIs). Results: In our analysis, there were 11 studies with 1577 pregnant women. The findings revealed a significant negative correlation between higher Lactobacillus abundance and the PTB risk (OR = 0.49, 95% CI: 0.29-0.84, p = 0.009 < 0.05). Similarly, the four individual dominant species, Lactobacillus crispatus (OR = 0.3, 95% CI: 0.14-0.67, p = 0.003 < 0.05), Lactobacillus gasseri (OR = 0.34, 95% CI: 0.17-0.69, p = 0.003 < 0.05), Lactobacillus iners (OR = 0.68, 95% CI: 0.49-0.93, p = 0.016 < 0.05), and Lactobacillus jensenii (OR = 0.43, 95% CI: 0.21-0.89, p = 0.024 < 0.05), were also negatively associated with the PTB risk. The risk of Lactobacillus for PTB was significant in both America (OR = 0.67; 95% CI: 0.50-0.92) and Asia (OR = 0.20; 95% CI: 0.09-0.47), whereas no significant risk was found in Europe (OR = 0.49; 95% CI: 0.11-2.15). Conclusions: Our study demonstrated that the abundance of Lactobacillus and the four dominant individual species (L. crispatus, L. jensenii, L. iners, and L. gasseri) were significantly and negatively associated with the PTB risk.
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Affiliation(s)
- Qian Zhou
- Department of Obstetrics & Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Yi Yu
- Department of Obstetrics & Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Jingwen Zhou
- Department of Obstetrics & Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Juntao Liu
- Department of Obstetrics & Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
| | - Jinsong Gao
- Department of Obstetrics & Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Obstetric & Gynecologic Diseases, Beijing, China
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4
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Golob JL, Oskotsky TT, Tang AS, Roldan A, Chung V, Ha CWY, Wong RJ, Flynn KJ, Parraga-Leo A, Wibrand C, Minot SS, Oskotsky B, Andreoletti G, Kosti I, Bletz J, Nelson A, Gao J, Wei Z, Chen G, Tang ZZ, Novielli P, Romano D, Pantaleo E, Amoroso N, Monaco A, Vacca M, De Angelis M, Bellotti R, Tangaro S, Kuntzleman A, Bigcraft I, Techtmann S, Bae D, Kim E, Jeon J, Joe S, Theis KR, Ng S, Lee YS, Diaz-Gimeno P, Bennett PR, MacIntyre DA, Stolovitzky G, Lynch SV, Albrecht J, Gomez-Lopez N, Romero R, Stevenson DK, Aghaeepour N, Tarca AL, Costello JC, Sirota M. Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research. Cell Rep Med 2024; 5:101350. [PMID: 38134931 PMCID: PMC10829755 DOI: 10.1016/j.xcrm.2023.101350] [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: 03/28/2023] [Revised: 09/15/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023]
Abstract
Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.
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Affiliation(s)
- Jonathan L Golob
- Division of Infectious Disease, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA.
| | - Tomiko T Oskotsky
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
| | - Alice S Tang
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Alennie Roldan
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | | | - Connie W Y Ha
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Ronald J Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA; March of Dimes Prematurity Research Center at Stanford University, Stanford, CA, USA
| | | | - Antonio Parraga-Leo
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, Obstetrics and Gynaecology, Universidad de Valencia, Valencia, Spain; IVIRMA Global Research Alliance, IVI Foundation, Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain
| | - Camilla Wibrand
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Samuel S Minot
- Data Core, Shared Resources, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Boris Oskotsky
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Gaia Andreoletti
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Idit Kosti
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | | | | | - Jifan Gao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Zhoujingpeng Wei
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Guanhua Chen
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Zheng-Zheng Tang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Pierfrancesco Novielli
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Donato Romano
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Ester Pantaleo
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento Interateneo di Fisica "M, Merlin", Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento di Farmacia - Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Alfonso Monaco
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento Interateneo di Fisica "M, Merlin", Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Mirco Vacca
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Maria De Angelis
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Roberto Bellotti
- Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy; Dipartimento Interateneo di Fisica "M, Merlin", Università degli Studi di Bari Aldo Moro, Bari, Italy
| | - Sabina Tangaro
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy
| | - Abigail Kuntzleman
- Department of Biological Sciences, Michigan Technological University, Houghton, MI, USA
| | - Isaac Bigcraft
- Department of Biological Sciences, Michigan Technological University, Houghton, MI, USA
| | - Stephen Techtmann
- Department of Biological Sciences, Michigan Technological University, Houghton, MI, USA
| | - Daehun Bae
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Eunyoung Kim
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Jongbum Jeon
- Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
| | - Soobok Joe
- Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
| | - Kevin R Theis
- Department of Biochemistry, Microbiology and Immunology, Wayne State University, Detroit, MI, USA
| | - Sherrianne Ng
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK
| | - Yun S Lee
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK
| | - Patricia Diaz-Gimeno
- IVIRMA Global Research Alliance, IVI Foundation, Instituto de Investigación Sanitaria La Fe (IIS La Fe), Valencia, Spain
| | - Phillip R Bennett
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK
| | - David A MacIntyre
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK
| | - Gustavo Stolovitzky
- Center for Computational Biology and Bioinformatics, Columbia University, New York, NY, USA; Thomas J. Watson Research Center, IBM, Yorktown Heights, NY, USA; Sema4, Stamford, CT, USA
| | - Susan V Lynch
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA; Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Nardhy Gomez-Lopez
- Department of Biochemistry, Microbiology and Immunology, Wayne State University, Detroit, MI, USA; Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Detroit, MI, USA
| | - Roberto Romero
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Detroit, MI, USA; Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA; Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA; Detroit Medical Center, Detroit, MI, USA; Department of Obstetrics and Gynecology, Florida International University, Miami, FL, USA
| | - David K Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA; Center for Academic Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA; Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA; Department of Biomedical Data Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Adi L Tarca
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, Detroit, MI, USA; Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA; Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA; Department of Computer Science, Wayne State University College of Engineering, Detroit, MI, USA
| | - James C Costello
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Marina Sirota
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
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5
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Nori SRC, McGuire TK, Lawton EM, McAuliffe FM, Sinderen DV, Walsh CJ, Cotter PD, Feehily C. Profiling of vaginal Lactobacillus jensenii isolated from preterm and full-term pregnancies reveals strain-specific factors relating to host interaction. Microb Genom 2023; 9. [PMID: 38010361 DOI: 10.1099/mgen.0.001137] [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: 11/29/2023] Open
Abstract
Each year, 15 million infants are born preterm (<37 weeks gestation), representing the leading cause of mortality for children under the age of five. Whilst there is no single cause, factors such as maternal genetics, environmental interactions, and the vaginal microbiome have been associated with an increased risk of preterm birth. Previous studies show that a vaginal microbiota dominated by Lactobacillus is, in contrast to communities containing a mixture of genera, associated with full-term birth. However, this binary principle does not fully consider more nuanced interactions between bacterial strains and the host. Here, through a combination of analyses involving genome-sequenced isolates and strain-resolved metagenomics, we identify that L. jensenii strains from preterm pregnancies are phylogenetically distinct from strains from full-term pregnancies. Detailed analysis reveals several genetic signatures that distinguish preterm birth strains, including genes predicted to be involved in cell wall synthesis, and lactate and acetate metabolism. Notably, we identify a distinct gene cluster involved in cell surface protein synthesis in our preterm strains, and profiling the prevalence of this gene cluster in publicly available genomes revealed it to be predominantly present in the preterm-associated clade. This study contributes to the ongoing search for molecular biomarkers linked to preterm birth and opens up new avenues for exploring strain-level variations and mechanisms that may contribute to preterm birth.
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Affiliation(s)
- Sai Ravi Chandra Nori
- Teagasc Food Research Centre, Fermoy, Co. Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
- School of Microbiology, University College Cork, Cork, Ireland
- SFI Centre for Research Training in Genomics Data Science, School of Mathematics, Statistics & Applied Mathematics, University of Galway, Galway, Ireland
| | | | | | - Fionnuala M McAuliffe
- UCD Perinatal Research Centre, School of Medicine, University College Dublin, National Maternity Hospital, Dublin, Ireland
| | - Douwe Van Sinderen
- APC Microbiome Ireland, University College Cork, Cork, Ireland
- School of Microbiology, University College Cork, Cork, Ireland
| | - Calum J Walsh
- Department of Microbiology & Immunology, Peter Doherty Institute for Infection & Immunity, University of Melbourne, Melbourne, Australia
| | - Paul D Cotter
- Teagasc Food Research Centre, Fermoy, Co. Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
- School of Microbiology, University College Cork, Cork, Ireland
| | - Conor Feehily
- Teagasc Food Research Centre, Fermoy, Co. Cork, Ireland
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
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6
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Huang C, Gin C, Fettweis J, Foxman B, Gelaye B, MacIntyre DA, Subramaniam A, Fraser W, Tabatabaei N, Callahan B. Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth. BMC Biol 2023; 21:199. [PMID: 37743497 PMCID: PMC10518966 DOI: 10.1186/s12915-023-01702-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 09/12/2023] [Indexed: 09/26/2023] Open
Abstract
BACKGROUND High-throughput sequencing measurements of the vaginal microbiome have yielded intriguing potential relationships between the vaginal microbiome and preterm birth (PTB; live birth prior to 37 weeks of gestation). However, results across studies have been inconsistent. RESULTS Here, we perform an integrated analysis of previously published datasets from 12 cohorts of pregnant women whose vaginal microbiomes were measured by 16S rRNA gene sequencing. Of 2039 women included in our analysis, 586 went on to deliver prematurely. Substantial variation between these datasets existed in their definition of preterm birth, characteristics of the study populations, and sequencing methodology. Nevertheless, a small group of taxa comprised a vast majority of the measured microbiome in all cohorts. We trained machine learning (ML) models to predict PTB from the composition of the vaginal microbiome, finding low to modest predictive accuracy (0.28-0.79). Predictive accuracy was typically lower when ML models trained in one dataset predicted PTB in another dataset. Earlier preterm birth (< 32 weeks, < 34 weeks) was more predictable from the vaginal microbiome than late preterm birth (34-37 weeks), both within and across datasets. Integrated differential abundance analysis revealed a highly significant negative association between L. crispatus and PTB that was consistent across almost all studies. The presence of the majority (18 out of 25) of genera was associated with a higher risk of PTB, with L. iners, Prevotella, and Gardnerella showing particularly consistent and significant associations. Some example discrepancies between studies could be attributed to specific methodological differences but not most study-to-study variations in the relationship between the vaginal microbiome and preterm birth. CONCLUSIONS We believe future studies of the vaginal microbiome and PTB will benefit from a focus on earlier preterm births and improved reporting of specific patient metadata shown to influence the vaginal microbiome and/or birth outcomes.
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Affiliation(s)
- Caizhi Huang
- Bioinformatics Research Center, North Carolina State University, Raleigh, 27606, USA
| | - Craig Gin
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, 27607, USA
| | - Jennifer Fettweis
- Department of Obstetrics and Gynecology, Virginia Commonwealth University, Richmond, 23284, USA
| | - Betsy Foxman
- Thomas Francis School of Public Health, University of Michigan, Raleigh, 27606, USA
| | - Bizu Gelaye
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, 02115, USA
| | - David A MacIntyre
- March of Dimes Prematurity Research Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, USA
| | - Akila Subramaniam
- Obstetrics & Gynecology and Maternal-Fetal Medicine, University of Alabama at Birmingham, Birmingham, 35294, USA
| | - William Fraser
- Departments of Obstetrics and Gynecology, University of Sherbrooke, Sherbrooke, J1K 2R1, USA
| | - Negar Tabatabaei
- Departments of Obstetrics and Gynecology, University of Sherbrooke, Sherbrooke, J1K 2R1, USA
- Department of Pharmacology and Regenerative Medicine, University of Illinois College of Medicine, Chicago, 60612, USA
| | - Benjamin Callahan
- Bioinformatics Research Center, North Carolina State University, Raleigh, 27606, USA.
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, 27607, USA.
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7
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Liao J, Shenhav L, Urban JA, Serrano M, Zhu B, Buck GA, Korem T. Microdiversity of the vaginal microbiome is associated with preterm birth. Nat Commun 2023; 14:4997. [PMID: 37591872 PMCID: PMC10435516 DOI: 10.1038/s41467-023-40719-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/07/2023] [Indexed: 08/19/2023] Open
Abstract
Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield insights into these associations. Here, we analyze metagenomic data from 705 vaginal samples collected during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative. We find that the vaginal microbiome of pregnancies that ended preterm exhibited unique genetic profiles. It was more genetically diverse at the species level, a result which we validate in an additional cohort, and harbored a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species drove this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. underwent more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our population genetics analyses reveal associations between the vaginal microbiome and PTB and suggest that evolutionary processes acting on vaginal microbes may play a role in adverse pregnancy outcomes such as PTB.
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Affiliation(s)
- Jingqiu Liao
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA.
| | - Liat Shenhav
- Center for Studies in Physics and Biology, Rockefeller University, New York, NY, USA
| | - Julia A Urban
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Myrna Serrano
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Bin Zhu
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Gregory A Buck
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
- Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Tal Korem
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA.
- CIFAR Azrieli Global Scholars program, CIFAR, Toronto, ON, Canada.
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8
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Liao J, Shenhav L, Urban JA, Serrano M, Zhu B, Buck GA, Korem T. Microdiversity of the Vaginal Microbiome is Associated with Preterm Birth. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.13.523991. [PMID: 36711990 PMCID: PMC9882146 DOI: 10.1101/2023.01.13.523991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield new insights into these associations. To this end, we analyzed metagenomic data from 705 vaginal samples collected longitudinally during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative (MOMS-PI). We find that the vaginal microbiome of pregnancies that ended preterm exhibits unique genetic profiles. It is more genetically diverse at the species level, a result which we validate in an additional cohort, and harbors a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species, a group of central vaginal pathobionts, are driving this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. undergoes more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our results reveal novel associations between the vaginal microbiome and PTB using population genetics analyses, and suggest that evolutionary processes acting on the vaginal microbiome may play a vital role in adverse pregnancy outcomes such as preterm birth.
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Affiliation(s)
- Jingqiu Liao
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Liat Shenhav
- Center for Studies in Physics and Biology, Rockefeller University, New York, NY, USA
| | - Julia A. Urban
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Myrna Serrano
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Bin Zhu
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Gregory A. Buck
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
- Department of Computer Science, School of Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Tal Korem
- Program for Mathematical Genomics, Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA
- CIFAR Azrieli Global Scholars program, CIFAR, Toronto, Canada
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9
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Golob JL, Oskotsky TT, Tang AS, Roldan A, Chung V, Ha CWY, Wong RJ, Flynn KJ, Parraga-Leo A, Wibrand C, Minot SS, Andreoletti G, Kosti I, Bletz J, Nelson A, Gao J, Wei Z, Chen G, Tang ZZ, Novielli P, Romano D, Pantaleo E, Amoroso N, Monaco A, Vacca M, De Angelis M, Bellotti R, Tangaro S, Kuntzleman A, Bigcraft I, Techtmann S, Bae D, Kim E, Jeon J, Joe S, Theis KR, Ng S, Lee Li YS, Diaz-Gimeno P, Bennett PR, MacIntyre DA, Stolovitzky G, Lynch SV, Albrecht J, Gomez-Lopez N, Romero R, Stevenson DK, Aghaeepour N, Tarca AL, Costello JC, Sirota M. Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.07.23286920. [PMID: 36945505 PMCID: PMC10029035 DOI: 10.1101/2023.03.07.23286920] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.
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Affiliation(s)
- Jonathan L Golob
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
| | - Tomiko T Oskotsky
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Alice S Tang
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Alennie Roldan
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | | | - Connie W Y Ha
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
| | - Ronald J Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
| | | | - Antonio Parraga-Leo
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Camilla Wibrand
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Samuel S Minot
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
| | - Gaia Andreoletti
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Idit Kosti
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | | | | | - Jifan Gao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Zhoujingpeng Wei
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Guanhua Chen
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Zheng-Zheng Tang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Pierfrancesco Novielli
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Donato Romano
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Ester Pantaleo
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
| | - Nicola Amoroso
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
| | - Alfonso Monaco
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Mirco Vacca
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Maria De Angelis
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Roberto Bellotti
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Sabina Tangaro
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Abigail Kuntzleman
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
| | - Isaac Bigcraft
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Stephen Techtmann
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Daehun Bae
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
| | - Eunyoung Kim
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | | | - Soobok Joe
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Kevin R Theis
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
| | - Sherrianne Ng
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
| | - Yun S Lee Li
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Patricia Diaz-Gimeno
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Phillip R Bennett
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - David A MacIntyre
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Gustavo Stolovitzky
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Susan V Lynch
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
| | | | - Nardhy Gomez-Lopez
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Roberto Romero
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - David K Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
| | - Nima Aghaeepour
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
| | - Adi L Tarca
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - James C Costello
- Division of Infectious Disease. Department of Internal Medicine. University of Michigan. Ann Arbor, MI. USA
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
- Sage Bionetworks, Seattle, WA. USA
- Benioff Center for Microbiome Medicine, Department of Medicine, University of California, San Francisco, CA. USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA. USA
- March of Dimes Prematurity Research Center at Stanford University, Stanford, CA USA
- Data Core, Shared Resources, Fred Hutchinson Cancer Center. Seattle, WA. USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI. USA
| | - Marina Sirota
- March of Dimes Prematurity Research Center at the University of California San Francisco, San Francisco, CA USA
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA. USA
- Department of Pediatrics. University of California San Francisco, San Francisco, CA. USA
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10
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Ling Z, Cheng Y, Gao J, Lei W, Yan X, Hu X, Shao L, Liu X, Kang R. Alterations of the fecal and vaginal microbiomes in patients with systemic lupus erythematosus and their associations with immunological profiles. Front Immunol 2023; 14:1135861. [PMID: 36969178 PMCID: PMC10036376 DOI: 10.3389/fimmu.2023.1135861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 02/27/2023] [Indexed: 03/12/2023] Open
Abstract
BackgroundExploring the human microbiome in multiple body niches is beneficial for clinicians to determine which microbial dysbiosis should be targeted first. We aimed to study whether both the fecal and vaginal microbiomes are disrupted in SLE patients and whether they are correlated, as well as their associations with immunological features.MethodsA group of 30 SLE patients and 30 BMI-age-matched healthy controls were recruited. Fecal and vaginal samples were collected, the 16S rRNA gene was sequenced to profile microbiomes, and immunological features were examined.ResultsDistinct fecal and vaginal bacterial communities and decreased microbial diversity in feces compared with the vagina were found in SLE patients and controls. Altered bacterial communities were found in the feces and vaginas of patients. Compared with the controls, the SLE group had slightly lower gut bacterial diversity, which was accompanied by significantly higher bacterial diversity in their vaginas. The most predominant bacteria differed between feces and the vagina in all groups. Eleven genera differed in patients’ feces; for example, Gardnerella and Lactobacillus increased, whereas Faecalibacterium decreased. Almost all the 13 genera differed in SLE patients’ vaginas, showing higher abundances except for Lactobacillus. Three genera in feces and 11 genera in the vagina were biomarkers for SLE patients. The distinct immunological features were only associated with patients’ vaginal microbiomes; for example, Escherichia−Shigella was negatively associated with serum C4.ConclusionsAlthough SLE patients had fecal and vaginal dysbiosis, dysbiosis in the vagina was more obvious than that in feces. Additionally, only the vaginal microbiome interacted with patients’ immunological features.
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Affiliation(s)
- Zongxin Ling
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong, China
- *Correspondence: Zongxin Ling, ; Runfang Kang,
| | - Yiwen Cheng
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jie Gao
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenhui Lei
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong, China
- Department of Laboratory Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Xiumei Yan
- Department of Geriatrics, Lishui Second People’s Hospital, Lishui, Zhejiang, China
| | - Xiaogang Hu
- Department of Geriatrics, Lishui Second People’s Hospital, Lishui, Zhejiang, China
| | - Li Shao
- School of Clinical Medicine, Institute of Hepatology and Metabolic Diseases, Hangzhou Normal University, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Xia Liu
- Department of Intensive Care Unit, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Runfang Kang
- Department of Dermatology, Lishui Second People’s Hospital, Lishui, Zhejiang, China
- *Correspondence: Zongxin Ling, ; Runfang Kang,
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11
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Najmanová L, Vídeňská P, Cahová M. Healthy microbiome – a mere idea or a sound concept? Physiol Res 2022. [DOI: 10.33549/physiolres.934967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Hundreds of studies in last decades have aimed to compare the microbiome of patients suffering from diverse diseases with that of healthy controls. The microbiome-related component was additionally identified in pathophysiology of many diseases formerly considered to depend only on the host physiology. This, however, opens important questions like: “What is the healthy microbiome?” or “Is it possible to define it unequivocally?”. In this review, we describe the main hindrances complicating the definition of “healthy microbiome” in terms of microbiota composition. We discuss the human microbiome from the perspective of classical ecology and we advocate for the shift from the stress on microbiota composition to the functions that microbiome ensures for the host. Finally, we propose to leave the concept of ideal healthy microbiome and replace it by focus on microbiome advantageous for the host, which always depends on the specific context like the age, genetics, dietary habits, body site or physiological state.
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Affiliation(s)
| | | | - M Cahová
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
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12
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NAJMANOVÁ L, VÍDEŇSKÁ P, CAHOVÁ M. Healthy microbiome - a mere idea or a sound concept? Physiol Res 2022; 71:719-738. [PMID: 36426891 PMCID: PMC9814986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Hundreds of studies in last decades have aimed to compare the microbiome of patients suffering from diverse diseases with that of healthy controls. The microbiome-related component was additionally identified in pathophysiology of many diseases formerly considered to depend only on the host physiology. This, however, opens important questions like: "What is the healthy microbiome?" or "Is it possible to define it unequivocally?". In this review, we describe the main hindrances complicating the definition of "healthy microbiome" in terms of microbiota composition. We discuss the human microbiome from the perspective of classical ecology and we advocate for the shift from the stress on microbiota composition to the functions that microbiome ensures for the host. Finally, we propose to leave the concept of ideal healthy microbiome and replace it by focus on microbiome advantageous for the host, which always depends on the specific context like the age, genetics, dietary habits, body site or physiological state.
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Affiliation(s)
- Lucie NAJMANOVÁ
- Institute of Microbiology of the CAS, Prague, Czech Republic
| | - Petra VÍDEŇSKÁ
- RECETOX, Faculty of Science Masaryk University, Brno, Czech Republic
| | - Monika CAHOVÁ
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
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13
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Chopra C, Bhushan I, Mehta M, Koushal T, Gupta A, Sharma S, Kumar M, Khodor SA, Sharma S. Vaginal microbiome: considerations for reproductive health. Future Microbiol 2022; 17:1501-1513. [DOI: 10.2217/fmb-2022-0112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The microbial communities are an indispensable part of the human defense system and coexist with humans as symbionts, contributing to the metabolic functions and immune defense against pathogens. An ecologically stable vaginal microbiota is dominated by Lactobacillus species, which plays an important role in the prevention of genital infections by controlling the vaginal pH, reducing glycogen to lactic acid, and stimulating bacteriocins and hydrogen peroxide. In contrast, an abnormal vaginal microbial composition is associated with an increased risk of bacterial vaginosis, trichomoniasis, sexually transmitted diseases, preterm labor and other birth defects. This microbial diversity is affected by race, ethnicity, pregnancy, hormonal changes, sexual activities, hygiene practices and other conditions. In the present review, we discuss the changes in the microbial community of the vaginal region at different stages of a female's life cycle and its influence on her reproductive health and pathological conditions.
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Affiliation(s)
- Chitrakshi Chopra
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, Jammu & Kashmir, 182320, India
| | - Indu Bhushan
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, Jammu & Kashmir, 182320, India
| | - Malvika Mehta
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, Jammu & Kashmir, 182320, India
| | - Tanvi Koushal
- School of Biotechnology, Shri Mata Vaishno Devi University, Katra, Jammu & Kashmir, 182320, India
| | - Amita Gupta
- Department of Gynecology, Government Medical College, Jammu, (J&K), 180001, India
| | - Sarika Sharma
- Department of Sponsored Research, Division of Research & Development, Lovely Professional University, Phagwara, 144411, India
| | - Manoj Kumar
- Research Department, Sidra Medicine, Doha, 26999, Qatar
| | | | - Sandeep Sharma
- Department of Medical Laboratory Sciences, Lovely Professional University, Phagwara, Punjab, 144411, India
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14
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Sensing Host Health: Insights from Sensory Protein Signature of the Metagenome. Appl Environ Microbiol 2022; 88:e0059622. [PMID: 35862686 PMCID: PMC9361814 DOI: 10.1128/aem.00596-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
The human microbiota, which comprises an ensemble of taxonomically and functionally diverse but often mutually cooperating microorganisms, benefits its host by shaping the host immunity, energy harvesting, and digestion of complex carbohydrates as well as production of essential nutrients. Dysbiosis in the human microbiota, especially the gut microbiota, has been reported to be linked to several diseases and metabolic disorders. Recent studies have further indicated that tracking these dysbiotic variations could potentially be exploited as biomarkers of disease states. However, the human microbiota is not geography agnostic, and hence a taxonomy-based (microbiome) biomarker for disease diagnostics has certain limitations. In comparison, (microbiome) function-based biomarkers are expected to have a wider applicability. Given that (i) the host physiology undergoes certain changes in the course of a disease and (ii) host-associated microbial communities need to adapt to this changing microenvironment of their host, we hypothesized that signatures emanating from the abundance of bacterial proteins associated with the signal transduction system (herein referred to as sensory proteins [SPs]) might be able to distinguish between healthy and diseased states. To test this hypothesis, publicly available metagenomic data sets corresponding to three diverse health conditions, namely, colorectal cancer, type 2 diabetes mellitus, and schizophrenia, were analyzed. Results demonstrated that SP signatures (derived from host-associated metagenomic samples) indeed differentiated among healthy individual and patients suffering from diseases of various severities. Our finding was suggestive of the prospect of using SP signatures as early biomarkers for diagnosing the onset and progression of multiple diseases and metabolic disorders. IMPORTANCE The composition of the human microbiota, a collection of host-associated microbes, has been shown to differ among healthy and diseased individuals. Recent studies have investigated whether tracking these variations could be exploited for disease diagnostics. It has been noted that compared to microbial taxonomies, the ensemble of functional proteins encoded by microbial genes are less likely to be affected by changes in ethnicity and dietary preferences. These functions are expected to help the microbe adapt to changing environmental conditions. Thus, healthy individuals might harbor a different set of genes than diseased individuals. To test this hypothesis, we analyzed metagenomes from healthy and diseased individuals for signatures of a particular group of proteins called sensory proteins (SP), which enable the bacteria to sense and react to changes in their microenvironment. Results demonstrated that SP signatures indeed differentiate among healthy individuals and those suffering from diseases of various severities.
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15
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Microbiota of the Pregnant Mouse: Characterization of the Bacterial Communities in the Oral Cavity, Lung, Intestine, and Vagina through Culture and DNA Sequencing. Microbiol Spectr 2022; 10:e0128622. [PMID: 35916526 PMCID: PMC9430855 DOI: 10.1128/spectrum.01286-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Mice are frequently used as animal models for mechanistic studies of infection and obstetrical disease, yet characterization of the murine microbiota during pregnancy is lacking. The objective of this study was to characterize the microbiotas of distinct body sites of the pregnant mouse—vagina, oral cavity, intestine, and lung—that harbor microorganisms that could potentially invade the murine amniotic cavity, thus leading to adverse pregnancy outcomes. The microbiotas of these body sites were characterized through anoxic, hypoxic, and oxic culture as well as through 16S rRNA gene sequencing. With the exception of the vagina, the cultured microbiotas of each body site varied by atmosphere, with the greatest diversity in the cultured microbiota appearing under anoxic conditions. Only cultures of the vagina were comprehensively representative of the microbiota observed through direct DNA sequencing of body site samples, primarily due to the predominance of two Rodentibacter strains. Identified as Rodentibacter pneumotropicus and Rodentibacter heylii, these isolates exhibited predominance patterns similar to those of Lactobacillus crispatus and Lactobacillus iners in the human vagina. Whole-genome sequencing of these Rodentibacter strains revealed shared genomic features, including the ability to degrade glycogen, an abundant polysaccharide in the vagina. In summary, we report body site-specific microbiotas in the pregnant mouse with potential ecological parallels to those of humans. Importantly, our findings indicate that the vaginal microbiotas of pregnant mice can be readily cultured, suggesting that mock vaginal microbiotas can be tractably generated and maintained for experimental manipulation in future mechanistic studies of host vaginal-microbiome interactions. IMPORTANCE Mice are widely utilized as animal models of obstetrical complications; however, the characterization of the murine microbiota during pregnancy has been neglected. Microorganisms from the vagina, oral cavity, intestine, and lung have been found in the intra-amniotic space, where their presence threatens the progression of gestation. Here, we characterized the microbiotas of pregnant mice and established the appropriateness of culture in capturing the microbiota at each site. The high relative abundance of Rodentibacter observed in the vagina is similar to that of Lactobacillus in humans, suggesting potential ecological parallels. Importantly, we report that the vaginal microbiota of the pregnant mouse can be readily cultured under hypoxic conditions, demonstrating that mock microbial communities can be utilized to test the potential ecological parallels between microbiotas in human and murine pregnancy and to evaluate the relevance of the structure of these microbiotas for adverse pregnancy outcomes, especially intra-amniotic infection and preterm birth.
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16
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Wright ML, Dunlop AL, Dunn AB, Mitchell RM, Wissel EF, Corwin EJ. Factors Associated with Vaginal Lactobacillus Predominance Among African American Women Early in Pregnancy. J Womens Health (Larchmt) 2022; 31:682-689. [PMID: 34448602 PMCID: PMC9133973 DOI: 10.1089/jwh.2021.0148] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Background: Vaginal Lactobacillus is considered protective of some adverse reproductive health outcomes, including preterm birth. However, factors that increase or decrease the likelihood of harboring Lactobacillus in the vaginal microbiome remain largely unknown. In this study, we sought to identify risk and protective factors associated with vaginal Lactobacillus predominance within a cohort of pregnant African American women. Materials and Methods: Vaginal microbiome samples were self-collected by African American women (N = 436) during their 8-14th week of pregnancy. Sociodemographic information and measures of health behaviors, including substance use, antibiotic exposure, sexual practices, frequency of vaginal intercourse, and the use of vaginal products, were collected through participant self-report. The V3-V4 region of the 16S rRNA gene was targeted for amplification and sequencing using Illumina HiSeq, with bacterial taxonomy assigned using the PECAN classifier. Univariate and a series of multivariate logistic regression models identified factors predictive of diverse vaginal microbiota or Lactobacillus predominance. Results: Participants who used marijuana in the past 30 days (aOR 1.80, 95% CI 1.08-2.98) were more likely to have diverse non-Lactobacillus-predominant vaginal microbiota, as were women not living with their partners (aOR 1.90, 95% CI 1.20-3.01). Cohabitating or marijuana usage were not associated with type of Lactobacillus (non-iners Lactobacillus vs. Lactobacillus iners) predominance (aOR 1.11, 95% CI 0.52-2.38 and aOR 0.56, 95% CI 0.21-1.47, respectively). Conclusions: Living with a partner is conducive to vaginal Lactobacillus predominance. As such, cohabitation may be in important covariate to consider in vaginal microbiome studies.
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Affiliation(s)
- Michelle L. Wright
- School of Nursing, The University of Texas at Austin, Austin, Texas, USA
- Department of Women's Health, Dell Medical School, The University of Texas at Austin, Austin, Texas, USA
| | - Anne L. Dunlop
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA
| | - Alexis B. Dunn
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA
| | - Rebecca M. Mitchell
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA
- Department of Computer Science, College of Arts and Sciences, Emory University, Atlanta, Georgia, USA
| | - Emily F. Wissel
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA
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17
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Lledo B, Fuentes A, Lozano FM, Cascales A, Morales R, Hortal M, Sellers F, Palacios-Marques A, Bermejo R, Quereda F, Martínez-Escoriza JC, Bernabeu R, Bernabeu A. Identification of vaginal microbiome associated with IVF pregnancy. Sci Rep 2022; 12:6807. [PMID: 35474343 PMCID: PMC9042930 DOI: 10.1038/s41598-022-10933-2] [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: 11/28/2021] [Accepted: 04/15/2022] [Indexed: 12/14/2022] Open
Abstract
The factors that cause a preterm birth (PTB) are not completely understood up to date. Moreover, PTB is more common in pregnancies achieved by in-vitro fertilization (IVF) than in spontaneous pregnancies. Our aim was to compare the composition of vaginal microbiome at 12 weeks of gestation between women who conceived naturally or through IVF in order to study whether IVF PTB-risk could be related to vaginal microbiome composition. We performed an observational, prospective and multicentre study among two public hospitals and a fertility private clinic in Spain. Vaginal swabs from 64 pregnant women at 12 weeks of gestation were collected to analyse the microbiome composition by sequencing the V3-V4 region of the 16S rRNA. Our results showed that the vaginal microbiome signature at 12 weeks of pregnancy was different from women who conceived naturally or through IVF. The beta diversity and the genus composition were different between both cohorts. Gardnerella, Neisseria, Prevotella, and Staphylococcus genus were enriched genus in the vaginal microbiome from the IVF group, allowing us to create a balance model to predict both cohorts. Moreover, at species level the L. iners abundance was higher and L. gasseri was lower in the IVF group. As a conclusion, our findings were consistent with a proposed framework in which IVF pregnancy are related to risk for preterm birth (PTB) suggesting vaginal microbiome could be the reason to the relation between IVF pregnancy and risk for PTB.
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Affiliation(s)
- B Lledo
- Molecular Biology, Instituto Bernabeu of Fertility and Gynecology, Avda. Albufereta, 31, 03016, Alicante, Spain.
| | - A Fuentes
- Reproductive Medicine, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain
| | - F M Lozano
- Molecular Biology, Instituto Bernabeu of Fertility and Gynecology, Avda. Albufereta, 31, 03016, Alicante, Spain
| | - A Cascales
- Molecular Biology, Instituto Bernabeu of Fertility and Gynecology, Avda. Albufereta, 31, 03016, Alicante, Spain
| | - R Morales
- Molecular Biology, Instituto Bernabeu of Fertility and Gynecology, Avda. Albufereta, 31, 03016, Alicante, Spain
| | - M Hortal
- Molecular Biology, Instituto Bernabeu of Fertility and Gynecology, Avda. Albufereta, 31, 03016, Alicante, Spain
| | - F Sellers
- Reproductive Medicine, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain.,Obstetrics, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain
| | - A Palacios-Marques
- Obstetrics, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain.,Obstetrics and Gynecology, Hospital General Universitario de Alicante, 03010, Alicante, Spain.,ISABIAL (Instituto de Investigación Sanitaria y Biomédica de Alicante), Alicante, Spain
| | - R Bermejo
- Division of Gynecology, Hospital Universitario San Juan de Alicante, 03550, Alicante, Spain.,Division of Gynecology, School of Medicine, Miguel Hernández University, Alicante, Spain
| | - F Quereda
- Division of Gynecology, Hospital Universitario San Juan de Alicante, 03550, Alicante, Spain.,Division of Gynecology, School of Medicine, Miguel Hernández University, Alicante, Spain
| | - J C Martínez-Escoriza
- Obstetrics and Gynecology, Hospital General Universitario de Alicante, 03010, Alicante, Spain.,ISABIAL (Instituto de Investigación Sanitaria y Biomédica de Alicante), Alicante, Spain
| | - R Bernabeu
- Reproductive Medicine, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain
| | - A Bernabeu
- Reproductive Medicine, Instituto Bernabeu of Fertility and Gynecology, 03016, Alicante, Spain
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18
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Emerging tools for understanding the human microbiome. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2022; 191:29-51. [DOI: 10.1016/bs.pmbts.2022.06.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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19
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Ronde E, Frerichs NM, Brantenaar S, El Manouni El Hassani S, Wicaksono AN, Covington JA, De Boer NKH, De Meij TG, Hankemeier T, Reiss IKM, Schoenmakers S. Detection of spontaneous preterm birth by maternal urinary volatile organic compound analysis: A prospective cohort study. Front Pediatr 2022; 10:1063248. [PMID: 36578660 PMCID: PMC9791099 DOI: 10.3389/fped.2022.1063248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022] Open
Abstract
Accurate prediction of preterm birth is currently challenging, resulting in unnecessary maternal hospital admittance and fetal overexposure to antenatal corticosteroids. Novel biomarkers like volatile organic compounds (VOCs) hold potential for predictive, bed-side clinical applicability. In a proof of principle study, we aimed to assess the predictive potential of urinary volatile organic compounds in the identification of pregnant women at risk for preterm birth. Urine samples of women with a high risk for preterm birth (≧24 + 0 until 36 + 6 weeks) were collected prospectively and analyzed for VOCs using gas chromatography coupled with an ion mobility spectrometer (GS-IMS). Urinary VOCs of women delivering preterm were compared with urine samples of women with suspicion of preterm birth collected at the same gestation period but delivering at term. Additionally, the results were also interpreted in combination with patient characteristics, such as physical examination at admission, microbial cultures, and placental pathology. In our cohort, we found that urinary VOCs of women admitted for imminent preterm birth were not significantly different in the overall group of women delivering preterm vs. term. However, urinary VOCs of women admitted for imminent preterm birth and delivering between 28 + 0 until 36 + 6 weeks compared to women with a high risk for preterm birth during the same gestation period and eventually delivering at term (>37 + 0 weeks) differed significantly (area under the curve: 0.70). In addition, based on the same urinary VOCs, we could identify women with a confirmed chorioamnionitis (area under the curve: 0.72) and urinary tract infection (area under the curve: 0.97). In conclusion, urinary VOCs hold potential for non-invasive, bedside prediction of preterm birth and on the spot identification of intra-uterine infection and urinary tract infections. We suggest these observations are further explored in larger populations.
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Affiliation(s)
- Emma Ronde
- Division of Obstetrics and Prenatal Diagnosis, Erasmus University Medical Centre, Rotterdam, Netherlands
| | - Nina M Frerichs
- Department of Pediatric Gastroenterology, Amsterdam University Medical Centre, Amsterdam, Netherlands
| | - Shauni Brantenaar
- Division of Obstetrics and Prenatal Diagnosis, Erasmus University Medical Centre, Rotterdam, Netherlands
| | | | | | - James A Covington
- School of Engineering, University of Warwick, Coventry, United Kingdom
| | - Nanne K H De Boer
- Department of Pediatric Gastroenterology, Amsterdam University Medical Centre, Amsterdam, Netherlands
| | - Tim G De Meij
- Department of Pediatric Gastroenterology, Amsterdam University Medical Centre, Amsterdam, Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Irwin K M Reiss
- Department of Pediatrics, Division of Neonatology, Erasmus University Medical Centre, Rotterdam, Netherlands
| | - Sam Schoenmakers
- Division of Obstetrics and Prenatal Diagnosis, Erasmus University Medical Centre, Rotterdam, Netherlands
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20
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Ruan XF, Zhang YX, Chen S, Liu XR, Zhu FF, Huang YX, Liu XJ, Luo SP, Deng GP, Gao J. Non- Lactobacillus-Dominated Vaginal Microbiota Is Associated With a Tubal Pregnancy in Symptomatic Chinese Women in the Early Stage of Pregnancy: A Nested Case-Control Study. Front Cell Infect Microbiol 2021; 11:659505. [PMID: 34307190 PMCID: PMC8294389 DOI: 10.3389/fcimb.2021.659505] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 05/04/2021] [Indexed: 12/02/2022] Open
Abstract
The features of the vaginal microbiota (VM) community can reflect health status, and they could become new biomarkers for disease diagnosis. During pregnancy, domination of bacteria of the genus Lactobacillus in the VM community is regarded as a keystone because they stabilize the VM by producing antimicrobial compounds and competing adhesion. An altered VM composition provides a marker for adverse pregnancy outcomes. This nested case–control study aimed to characterize the VM in women with a tubal pregnancy (TP) presenting with pain and/or uterine bleeding in early pregnancy. Chinese women with a symptomatic early pregnancy of unknown location were the study cohort. 16S rDNA gene-sequencing of V3–V4 variable regions was done to assess the diversity, structures, taxonomic biomarkers, and classification of the VM community. The primary outcome was the location of the early pregnancy. The VM community in women with a TP showed higher diversity (PD-whole-tree, median: 8.26 vs. 7.08, P = 0.047; Shannon Diversity Index, median: 1.43 vs 0.99, P = 0.03) and showed different structures to those in women with an intrauterine pregnancy (IUP) (R = 0.23, P < 0.01). Bacteria of the genus Lactobacillus were significantly enriched in the IUP group, whereas bacteria of the genera Gardnerella and Prevotella were significantly enriched in the TP group. Lactobacillus abundance could be used to classify the pregnancy location (AUC = 0.81). Non-Lactobacillus-dominated microbiota (≤ 0.85% Lactobacillus) was significantly associated with a TP (adjusted odds ratio: 4.42, 95% confidence interval: 1.33 to 14.71, P = 0.02). In conclusion, among women with a symptomatic early pregnancy, a higher diversity and lower abundance of Lactobacillus in the VM is associated with a TP.
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Affiliation(s)
- Xiao-Feng Ruan
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.,Department of Gynecology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ying-Xuan Zhang
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Si Chen
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiao-Rong Liu
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Fang-Fang Zhu
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yan-Xi Huang
- Department of Gynecology, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiao-Jing Liu
- Department of Gynecology, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Song-Ping Luo
- Department of Gynecology, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Gao-Pi Deng
- Department of Gynecology, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jie Gao
- Department of Gynecology, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
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21
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Emulsion-Based Multicompartment Vaginal Drug Carriers: From Nanoemulsions to Nanoemulgels. Int J Mol Sci 2021; 22:ijms22126455. [PMID: 34208652 PMCID: PMC8233730 DOI: 10.3390/ijms22126455] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 01/05/2023] Open
Abstract
In order to overcome the limitations associated with vaginal administration of drugs, e.g., the short contact time of the drug form with the mucosa or continuous carrier wash-out, the development of new carriers for gynecological use is necessary. Furthermore, high individual anatomical and physiological variability resulting in unsatisfactory therapeutic efficacy of lipophilic active substances requires application of multicompartment drug delivery systems. This manuscript provides an up-to-date comprehensive review of the literature on emulsion-based vaginal dosage forms (EVDF) including macroemulsions, microemulsions, nanoemulsions, multiple emulsions and self-emulsifying drug delivery systems. The first part of the paper discusses (i) the influence of anatomical-physiological conditions on therapeutic efficacy of drug forms after local and systemic administration, (ii) characterization of EVDF components and the manufacturing techniques of these dosage forms and (iii) methods used to evaluate the physicochemical and pharmaceutical properties of emulsion-based vaginal dosage forms. The second part of the paper presents (iv) the results of biological and in vivo studies as well as (v) clinical evaluation of EVDF safety and therapeutic efficacy across different indications.
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22
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Liu F, Zhou Y, Zhu L, Wang Z, Ma L, He Y, Fu P. Comparative metagenomic analysis of the vaginal microbiome in healthy women. Synth Syst Biotechnol 2021; 6:77-84. [PMID: 33997357 PMCID: PMC8085786 DOI: 10.1016/j.synbio.2021.04.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 04/03/2021] [Accepted: 04/06/2021] [Indexed: 01/22/2023] Open
Abstract
The composition of these vaginal microbiome has a significant impact on women's health. However, few studies have characterized the vaginal microbiome of healthy Chinese women using metagenomic sequencing. Here, we carried out a comparative metagenomic analysis to survey taxonomic, functional levels, and microbial communities' genome content in healthy women's vaginal microbiome. Overall, we observed a total of 111 species, including all dominant vaginal Lactobacillus species, such as L. iners, L. crispatus, L. gasseri, and L. jensenii. Unlike microbial taxa, several pathways were ubiquitous and prevalent across individuals, including adenosine ribonucleotides de novo biosynthesis and pyruvate fermentation to acetate and lactate II. Notably, our diversity analysis confirmed a significant difference in healthy women from different ethnic groups. Moreover, we binned vaginal assemblies into 62 high-quality genomes, including 9 L. iners, 7 A. vaginae, 5 L. jensenii, and 5 L. crispatus. We identified the pan and core genomes of L. iners and A. vaginae and revealed the genetic diversity. Primary differences between strains were the hypothetical genes and mobile element-like genes. Our results provide a framework for understanding the implications of the female reproductive tract's composition and functional potential and highlight the importance of genome-resolved metagenomic analysis to further understand the human vaginal microbiome.
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Affiliation(s)
- Fei Liu
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yingshun Zhou
- Department of Pathogenic Biology, Pathogenic Biology platform, School of Basic Medical Sciences, Southwest Medical University, Luzhou, 646000, Sichuan Province, China
| | - Lisi Zhu
- Laboratory of Clinical Genetics, Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Zhiyi Wang
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - LiangKun Ma
- Peking Union Medical College Hospital (Dongdan Campus), No. 1 Shuai Fu Yuan, Beijing, 100730, China
| | - Yuan He
- National Human Genetic Resources Center, National Research Institute for Health and Family Planning, Beijing, China
| | - Pengcheng Fu
- Mybiome (Beijing) Medical Consulting Co. LTD, China
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Singer M, Koedooder R, Bos MP, Poort L, Schoenmakers S, Savelkoul PHM, Laven JSE, de Jonge JD, Morré SA, Budding AE. The profiling of microbiota in vaginal swab samples using 16S rRNA gene sequencing and IS-pro analysis. BMC Microbiol 2021; 21:100. [PMID: 33789573 PMCID: PMC8015044 DOI: 10.1186/s12866-021-02149-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 01/29/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND 16S rRNA gene sequencing is currently the most common way of determining the composition of microbiota. This technique has enabled many new discoveries to be made regarding the relevance of microbiota to the health and disease of the host. However, compared to other diagnostic techniques, 16S rRNA gene sequencing is fairly costly and labor intensive, leaving room for other techniques to improve on these aspects. RESULTS The current study aimed to compare the output of 16S rRNA gene sequencing to the output of the quick IS-pro analysis, using vaginal swab samples from 297 women of reproductive age. 16S rRNA gene sequencing and IS-pro analyses yielded very similar vaginal microbiome profiles, with a median Pearson's R2 of 0.97, indicating a high level of similarity between both techniques. CONCLUSIONS We conclude that the results of 16S rRNA gene sequencing and IS-pro are highly comparable and that both can be used to accurately determine the vaginal microbiota composition, with the IS-pro analysis having the benefit of rapidity.
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Affiliation(s)
- M Singer
- Laboratory of Immunogenetics, Department of Medical Microbiology and Infection Control, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands.,Tubascan, Spin-off at the Department of Medical Microbiology and Infection Control, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - R Koedooder
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Erasmus University Medical Center, Wytemaweg 12, Rotterdam, 3015 CN, The Netherlands.
| | - M P Bos
- InBiome B.V, Amsterdam, The Netherlands
| | - L Poort
- InBiome B.V, Amsterdam, The Netherlands
| | - S Schoenmakers
- Division Obstetrics, Department of Obstetrics and Gynecology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - P H M Savelkoul
- Department of Medical Microbiology, Maastricht University Medical Center, Maastricht, the Netherlands.,Department of Medical Microbiology and Infection Control, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands
| | - J S E Laven
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Erasmus University Medical Center, Wytemaweg 12, Rotterdam, 3015 CN, The Netherlands
| | - J D de Jonge
- ARTPred B.V, Seringenstraat 15, 's Hertogenbosch, 5213 GS, The Netherlands
| | - S A Morré
- Laboratory of Immunogenetics, Department of Medical Microbiology and Infection Control, Amsterdam UMC, location VUmc, Amsterdam, the Netherlands.,Institute of Public Health Genomics, Department of Genetics and Cell Biology, Research Institute GROW, Faculty of Health, Medicine & Life Sciences, University of Maastricht, Maastricht, The Netherlands
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Coscia A, Bardanzellu F, Caboni E, Fanos V, Peroni DG. When a Neonate Is Born, So Is a Microbiota. Life (Basel) 2021; 11:life11020148. [PMID: 33669262 PMCID: PMC7920069 DOI: 10.3390/life11020148] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 02/09/2021] [Accepted: 02/11/2021] [Indexed: 02/06/2023] Open
Abstract
In recent years, the role of human microbiota as a short- and long-term health promoter and modulator has been affirmed and progressively strengthened. In the course of one’s life, each subject is colonized by a great number of bacteria, which constitute its specific and individual microbiota. Human bacterial colonization starts during fetal life, in opposition to the previous paradigm of the “sterile womb”. Placenta, amniotic fluid, cord blood and fetal tissues each have their own specific microbiota, influenced by maternal health and habits and having a decisive influence on pregnancy outcome and offspring outcome. The maternal microbiota, especially that colonizing the genital system, starts to influence the outcome of pregnancy already before conception, modulating fertility and the success rate of fertilization, even in the case of assisted reproduction techniques. During the perinatal period, neonatal microbiota seems influenced by delivery mode, drug administration and many other conditions. Special attention must be reserved for early neonatal nutrition, because breastfeeding allows the transmission of a specific and unique lactobiome able to modulate and positively affect the neonatal gut microbiota. Our narrative review aims to investigate the currently identified pre- and peri-natal factors influencing neonatal microbiota, before conception, during pregnancy, pre- and post-delivery, since the early microbiota influences the whole life of each subject.
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Affiliation(s)
- Alessandra Coscia
- Neonatology Unit, Department of Public Health and Pediatrics, Università degli Studi di Torino, 10124 Turin, Italy;
| | - Flaminia Bardanzellu
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, SS 554 km 4,500, 09042 Monserrato, Italy; (E.C.); (V.F.)
- Correspondence:
| | - Elisa Caboni
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, SS 554 km 4,500, 09042 Monserrato, Italy; (E.C.); (V.F.)
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, SS 554 km 4,500, 09042 Monserrato, Italy; (E.C.); (V.F.)
| | - Diego Giampietro Peroni
- Clinical and Experimental Medicine Department, Section of Pediatrics, University of Pisa, Via Roma, 55, 56126 Pisa PI, Italy;
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25
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Payne MS, Newnham JP, Doherty DA, Furfaro LL, Pendal NL, Loh DE, Keelan JA. A specific bacterial DNA signature in the vagina of Australian women in midpregnancy predicts high risk of spontaneous preterm birth (the Predict1000 study). Am J Obstet Gynecol 2021; 224:206.e1-206.e23. [PMID: 32861687 DOI: 10.1016/j.ajog.2020.08.034] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 07/23/2020] [Accepted: 08/12/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Intrauterine infection accounts for a quarter of the cases of spontaneous preterm birth; however, at present, it is not possible to efficiently identify pregnant women at risk to deliver preventative treatments. OBJECTIVE This study aimed to establish a vaginal microbial DNA test for Australian women in midpregnancy that will identify those at increased risk of spontaneous preterm birth. STUDY DESIGN A total of 1000 women with singleton pregnancies were recruited in Perth, Australia. Midvaginal swabs were collected between 12 and 23 weeks' gestation. DNA was extracted for the detection of 23 risk-related microbial DNA targets by quantitative polymerase chain reaction. Obstetrical history, pregnancy outcome, and demographics were recorded. RESULTS After excluding 64 women owing to losses to follow-up and insufficient sample for microbial analyses, the final cohort consisted of 936 women of predominantly white race (74.3%). The overall preterm birth rate was 12.6% (118 births); the spontaneous preterm birth rate at <37 weeks' gestation was 6.2% (2.9% at ≤34 weeks' gestation), whereas the preterm premature rupture of the membranes rate was 4.2%. No single individual microbial target predicted increased spontaneous preterm birth risk. Conversely, women who subsequently delivered at term had higher amounts of Lactobacillus crispatus, Lactobacillus gasseri, or Lactobacillus jensenii DNA in their vaginal swabs (13.8% spontaneous preterm birth vs 31.2% term; P=.005). In the remaining women, a specific microbial DNA signature was identified that was strongly predictive of spontaneous preterm birth risk, consisting of DNA from Gardnerella vaginalis (clade 4), Lactobacillus iners, and Ureaplasma parvum (serovars 3 and 6). Risk prediction was improved if Fusobacterium nucleatum detection was included in the test algorithm. The final algorithm, which we called the Gardnerella Lactobacillus Ureaplasma (GLU) test, was able to detect women at risk of spontaneous preterm birth at <37 and ≤34 weeks' gestation, with sensitivities of 37.9% and 44.4%, respectively, and likelihood ratios (plus or minus) of 2.22 per 0.75 and 2.52 per 0.67, respectively. Preterm premature rupture of the membranes was more than twice as common in GLU-positive women. Adjusting for maternal demographics, ethnicity, and clinical history did not improve prediction. Only a history of spontaneous preterm birth was more effective at predicting spontaneous preterm birth than a GLU-positive result (odds ratio, 3.6). CONCLUSION We have identified a vaginal bacterial DNA signature that identifies women with a singleton pregnancy who are at increased risk of spontaneous preterm birth and may benefit from targeted antimicrobial therapy.
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Affiliation(s)
- Matthew S Payne
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia; Women and Infants Research Foundation, Subiaco, Australia.
| | - John P Newnham
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia; Women and Infants Research Foundation, Subiaco, Australia
| | - Dorota A Doherty
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia; Women and Infants Research Foundation, Subiaco, Australia
| | - Lucy L Furfaro
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia
| | - Narisha L Pendal
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia
| | - Diane E Loh
- Women and Infants Research Foundation, Subiaco, Australia
| | - Jeffrey A Keelan
- Division of Obstetrics and Gynaecology, The University of Western Australia, Subiaco, Australia; Women and Infants Research Foundation, Subiaco, Australia
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26
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Ali A, Christophersen CT, Keelan JA. Vaginal microbial profiling in a preterm birth high-risk cohort using shallow shotgun metagenomics. MICROBIOLOGY AUSTRALIA 2021. [DOI: 10.1071/ma21023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Preterm birth (PTB) is a significant health problem globally, with an estimate of 15 million cases annually. Approximately 10% of neonates born early will die prematurely, while a subset will develop severe life-long morbidities. Unfortunately, preterm birth’s syndromic nature has evaded prevention strategies, and it continues to impose a high burden on healthcare systems and families. The role of vaginal bacteria in triggering biomolecular causes of PTB has been recognised for years. However, translating this knowledge to practical diagnostic and therapeutic strategies has remained elusive. New techniques in high-throughput sequencing have improved our understanding of the nature and role of the vaginal microbiome during pregnancy. Several multi-ethnic and multi-geographical studies into the vaginal microbiome have identified five distinct bacterial profiles termed community state types (CSTs), one of which is positively associated with dysbiosis and increased risk of PTB. In a small pilot study of first-trimester vaginal microbial DNA obtained from pregnant women at high-risk of PTB, we compared the CST profiles generated using standard 16S amplicon sequencing with shallow shotgun metagenomics (SSM). Both methods identified the presence of the five CSTs as has been reported previously, although the metagenomic data showed greater taxonomic resolution and more accurate CST assignation. These findings suggest that SSM is a cost-effective and potentially superior alternative to 16S sequencing for vaginal microbiome analysis.
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27
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Sroka-Oleksiak A, Gosiewski T, Pabian W, Gurgul A, Kapusta P, Ludwig-Słomczyńska AH, Wołkow PP, Brzychczy-Włoch M. Next-Generation Sequencing as a Tool to Detect Vaginal Microbiota Disturbances during Pregnancy. Microorganisms 2020; 8:microorganisms8111813. [PMID: 33217908 PMCID: PMC7698737 DOI: 10.3390/microorganisms8111813] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 11/13/2020] [Accepted: 11/16/2020] [Indexed: 12/29/2022] Open
Abstract
The physiological microbiota of the vagina is responsible for providing a protective barrier, but Some factors can disturb the balance in its composition. At that time, the amounts of the genus Lactobacillus decrease, which may lead to the development of infection and severe complications during pregnancy. The aim of the study was the analysis of the bacterial composition of the vagina in 32 Caucasian women at each trimester of pregnancy using the next-generation sequencing method and primers targeting V3-V4 regions. In the studied group, the dominant species were Lactobacillus iners, Lactobacillus gasseri, and Lactobacillusplantarum. Statistically significant differences in the quantitative composition between trimesters were observed in relation to Lactobacillus jensenii,Streptococcus agalactiae, Lactobacillus iners, Gardnerella spp. Out of the 32 patients, 20 demonstrated fluctuations within the genus Lactobacillus, and 9 of them, at different stages of pregnancy, exhibited the presence of potentially pathogenic microbiota, among others: Streptococcus agalactiae, Gardnerella spp., Atopobium vaginae, and Enterococcus faecalis. The composition of the vaginal microbiota during pregnancy was subject to partial changes over trimesters. Although in one-third of the studied patients, both the qualitative and quantitative composition of microbiota was relatively constant, in the remaining patients, physiological and potentially pathogenic fluctuations were distinguished.
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Affiliation(s)
- Agnieszka Sroka-Oleksiak
- Department of Molecular Medical Microbiology, Chair of Microbiology, Faculty of Medicine, Jagiellonian University Medical College, 31-121 Krakow, Poland; (A.S.-O.); (T.G.)
| | - Tomasz Gosiewski
- Department of Molecular Medical Microbiology, Chair of Microbiology, Faculty of Medicine, Jagiellonian University Medical College, 31-121 Krakow, Poland; (A.S.-O.); (T.G.)
| | - Wojciech Pabian
- Clinical Department of Gynecological Endocrinology and Gynecology, Jagiellonian University Medical College, Kopernika 23, 31-501 Krakow, Poland;
| | - Artur Gurgul
- Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland;
| | - Przemysław Kapusta
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kopernika 7c, 31-034 Krakow, Poland; (P.K.); (A.H.L.-S.); (P.P.W.)
| | - Agnieszka H. Ludwig-Słomczyńska
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kopernika 7c, 31-034 Krakow, Poland; (P.K.); (A.H.L.-S.); (P.P.W.)
| | - Paweł P. Wołkow
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kopernika 7c, 31-034 Krakow, Poland; (P.K.); (A.H.L.-S.); (P.P.W.)
| | - Monika Brzychczy-Włoch
- Department of Molecular Medical Microbiology, Chair of Microbiology, Faculty of Medicine, Jagiellonian University Medical College, 31-121 Krakow, Poland; (A.S.-O.); (T.G.)
- Correspondence: ; Tel.: +48-1263-325-67
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28
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Mehta O, Ghosh TS, Kothidar A, Gowtham MR, Mitra R, Kshetrapal P, Wadhwa N, Thiruvengadam R, Nair GB, Bhatnagar S, Das B. Vaginal Microbiome of Pregnant Indian Women: Insights into the Genome of Dominant Lactobacillus Species. MICROBIAL ECOLOGY 2020; 80:487-499. [PMID: 32206831 DOI: 10.1007/s00248-020-01501-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 03/04/2020] [Indexed: 06/10/2023]
Abstract
The trillions of microorganisms residing in the human body display varying degrees of compositional and functional diversities within and between individuals and contribute significantly to host physiology and susceptibility to disease. Microbial species present in the vaginal milieu of reproductive age women showed a large personal component and varies widely in different ethnic groups at the taxonomic, genomic, and functional levels. Lactobacillus iners, L. crispatus, L. gasseri, L. jensenii, and L. johnsonii are most frequently detected bacterial species in the vaginal milieu of reproductive age women. However, we currently lack (i) an understanding of the baseline vaginal microbiota of reproductive age Indian women, (ii) the extent of taxonomic and functional variations of vaginal microbiota between individuals and (iii) the genomic repertoires of the dominant vaginal microbiota associated with the Indian subjects. In our study, we analyzed the metagenome of high vaginal swab (HVS) samples collected from 40 pregnant Indian women enrolled in the GARBH-Ini cohort. Composition and abundance of bacterial species was characterized by pyrosequencing 16S rRNA gene. We identified 3067 OTUs with ≥ 10 reads from four different bacterial phyla. Several species of lactobacilli were clustered into three community state types (CSTs). L. iners, L. crispatus, L. gasseri, and L. jensenii are the most frequently detected Lactobacillus species in the vaginal environment of Indian women. Other than Lactobacillus, several species of Halomonas were also identified in the vaginal environment of most of the women sampled. To gain genomic and functional insights, we isolated several Lactobacillus species from the HVS samples and explored their whole genome sequences by shotgun sequencing. We analyzed the genome of dominant Lactobacillus species, L. iners, L. crispatus, L. gasseri, and L. paragesseri to represent the CSTs and identify functions that may influence the composition of complex vaginal microbial ecology. This study reports for the first time the vaginal microbial ecology of Indian women and genomic insights into L. iners, L. crispatus, L. gasseri, and L. paragesseri commonly found in the genital tract of reproductive age women.
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Affiliation(s)
- Ojasvi Mehta
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
| | - Tarini Shankar Ghosh
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Akansha Kothidar
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
| | - M Rama Gowtham
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
| | - Ridhima Mitra
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
| | - Pallavi Kshetrapal
- Pediatric Biology Center, Translational Health Science and Technology institute, NCR Biotech Science Cluster, Faridabad, India
| | - Nitya Wadhwa
- Pediatric Biology Center, Translational Health Science and Technology institute, NCR Biotech Science Cluster, Faridabad, India
| | - Ramachandran Thiruvengadam
- Pediatric Biology Center, Translational Health Science and Technology institute, NCR Biotech Science Cluster, Faridabad, India
| | - G Balakrish Nair
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India
| | - Shinjini Bhatnagar
- Pediatric Biology Center, Translational Health Science and Technology institute, NCR Biotech Science Cluster, Faridabad, India
| | - Bhabatosh Das
- Molecular Genetics Laboratory, Translational Health Science and Technology Institute|, NCR Biotech Science Cluster, 3rd Milestone, Faridabad - Gurgaon Expressway, PO box #04, Faridabad, Haryana, 121001, India.
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29
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Lacey L, Daulton E, Wicaksono A, Covington JA, Quenby S. Volatile organic compound analysis, a new tool in the quest for preterm birth prediction-an observational cohort study. Sci Rep 2020; 10:12153. [PMID: 32699319 PMCID: PMC7376243 DOI: 10.1038/s41598-020-69142-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 07/01/2020] [Indexed: 01/26/2023] Open
Abstract
Preterm birth is the leading cause of death worldwide in children under five years. Due to its complex multifactorial nature, prediction is a challenge. Current research is aiming to develop accurate predictive models using patient history, ultrasound and biochemical markers. Volatile organic compound (VOC) analysis is an approach, which has good diagnostic potential to predict many disease states. Analysis of VOCs can reflect both the microbiome and host response to a condition. We aimed to ascertain if VOC analysis of vaginal swabs, taken throughout pregnancy, could predict which women go on to deliver preterm. Our prospective observational cohort study demonstrates that VOC analysis of vaginal swabs, taken in the midtrimester, is a fair test (AUC 0.79) for preterm prediction, with a sensitivity of 0.66 (95%CI 0.56–0.75) and specificity 0.89 (95%CI 0.82–0.94). Using vaginal swabs taken closest to delivery, VOC analysis is a good test (AUC 0.84) for the prediction of preterm birth with a sensitivity of 0.73 (95%CI 0.64–0.81) and specificity of 0.90 (95%CI 0.82–0.95). Consequently, VOC analysis of vaginal swabs has potential to be used as a predictive tool. With further work it could be considered as an additional component in models for predicting preterm birth.
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Affiliation(s)
- Lauren Lacey
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK. .,Department of Obstetrics and Gynaecology, University Hospitals Coventry and Warwickshire, Coventry, CV2 2DX, UK.
| | - Emma Daulton
- School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
| | - Alfian Wicaksono
- School of Engineering, University of Warwick, Coventry, CV4 7AL, UK
| | | | - Siobhan Quenby
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.,Department of Obstetrics and Gynaecology, University Hospitals Coventry and Warwickshire, Coventry, CV2 2DX, UK
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30
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García-Velasco JA, Budding D, Campe H, Malfertheiner SF, Hamamah S, Santjohanser C, Schuppe-Koistinen I, Nielsen HS, Vieira-Silva S, Laven J. The reproductive microbiome - clinical practice recommendations for fertility specialists. Reprod Biomed Online 2020; 41:443-453. [PMID: 32753361 DOI: 10.1016/j.rbmo.2020.06.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 06/12/2020] [Accepted: 06/19/2020] [Indexed: 02/08/2023]
Abstract
The interest in and understanding of the human microbiome has grown remarkably over recent years. Advances in molecular techniques have allowed researchers to identify and study the microbiota and also use this information to develop therapeutic solutions for a spectrum of conditions. Alongside the growing interest in the microbiome, societal changes have resulted in many couples looking to start families later in life, therefore increasing the demand for assisted reproductive technologies. Combining these trends, it makes sense that clinicians are eager to understand and exploit the microbiome of their patients, i.e. the reproductive microbiome, in order to help them achieve their goal of becoming parents. This paper aims to provide an overview of the current and future research into the reproductive microbiome in relation to fertility and also share clinical practice recommendations for physicians who are new to this field or unsure about how they can utilise what is known to help their patients.
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Affiliation(s)
- Juan A García-Velasco
- Department of Reproductive Endocrinology and Infertility, IVI Madrid, Rey Juan Carlos University, Madrid 28023, Spain.
| | | | | | | | - Samir Hamamah
- Centre Hospitalier Universitaire de Montpellier, Service Biologie de la Reproduction, 34295 Montpellier, Inserm U1203, France
| | | | - Ina Schuppe-Koistinen
- Karolinska Institutet, Department of Microbiology, Tumor and Cell Biology, Centre for Translational Microbiome Research (CTMR), Stockholm 171 77, Sweden
| | - Henriette Svarre Nielsen
- Department of Obstetrics and Gynecology, Hvidovre Hospital, Copenhagen University Hospital, Hvidovre 2650, Denmark
| | - Sara Vieira-Silva
- Laboratory of Molecular Bacteriology, Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven 3000, Belgium; Center for Microbiology, VIB, Leuven, Belgium
| | - Joop Laven
- Erasmus MC, University Medical Center Rotterdam, Division of Reproductive Medicine, Rotterdam 3015 GD, the Netherlands
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Kosti I, Lyalina S, Pollard KS, Butte AJ, Sirota M. Meta-Analysis of Vaginal Microbiome Data Provides New Insights Into Preterm Birth. Front Microbiol 2020; 11:476. [PMID: 32322240 PMCID: PMC7156768 DOI: 10.3389/fmicb.2020.00476] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 03/04/2020] [Indexed: 11/13/2022] Open
Abstract
Preterm birth (PTB) is defined as the birth of an infant before 37 weeks of gestational age. It is the leading cause of perinatal morbidity and mortality worldwide. In this study, we present a comprehensive meta-analysis of vaginal microbiome in PTB. We integrated raw longitudinal 16S rRNA vaginal microbiome data from five independent studies across 3,201 samples and were able to gain new insights into the vaginal microbiome state in women who deliver preterm in comparison to those who deliver at term. We found that women who deliver prematurely show higher within-sample variance in vaginal microbiome abundance, with the most significant difference observed during the first trimester. Modeling the data longitudinally revealed a number of microbial genera as associated with PTB, including several that were previously known and two newly identified by this meta-analysis: Olsenella and Clostridium sensu stricto. New hypotheses emerging from this integrative analysis can lead to novel diagnostics to identify women who are at higher risk for PTB and potentially inform new therapeutic interventions.
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Affiliation(s)
- Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
| | - Svetlana Lyalina
- Integrative Program in Quantitative Biology, Gladstone Institutes, University of California, San Francisco, San Francisco, CA, United States
| | - Katherine S. Pollard
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Epidemiology & Biostatistics, Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Chan Zuckerberg Biohub, San Francisco, CA, United States
| | - Atul J. Butte
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
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Kaur H, Merchant M, Haque MM, Mande SS. Crosstalk Between Female Gonadal Hormones and Vaginal Microbiota Across Various Phases of Women's Gynecological Lifecycle. Front Microbiol 2020; 11:551. [PMID: 32296412 PMCID: PMC7136476 DOI: 10.3389/fmicb.2020.00551] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 03/13/2020] [Indexed: 01/02/2023] Open
Abstract
Functional equilibrium between vaginal microbiota and the host is important for maintaining gynecological and reproductive health. Apart from host genetics, infections, changes in diet, life-style and hygiene status are known to affect this delicate state of equilibrium. More importantly, the gonadal hormones strongly influence the overall structure and function of vaginal microbiota. Several studies have attempted to understand (a) the composition of vaginal microbiota in specific stages of women's reproductive cycle as well as in menopause (b) their association with gonadal hormones, and their potential role in manifestation of specific health conditions (from the perspective of cause/consequence). However, a single study that places, in context, the structural variations of the vaginal microbiome across the entire life-span of women's reproductive cycle and during various stages of menopause is currently lacking. With the objective to obtain a holistic overview of the community dynamics of vaginal micro-environment 'across' various stages of women's reproductive and post-reproductive life-cycle, we have performed a meta-analysis of approximately 1,000 vaginal microbiome samples representing various stages of the reproductive cycle and menopausal states. Objectives of this analysis included (a) understanding temporal changes in vaginal community taxonomic structure and composition as women pass through various reproductive and menopausal stages (b) exploring correlations between the levels of female sex hormones with vaginal microbiome diversity (c) analyzing changes in the pattern of community diversity in cases of dysbiotic conditions such as bacterial vaginosis, and viewing the analyzed changes in the context of a healthy state. Results reveal interesting temporal trends with respect to vaginal microbial community diversity and its pattern of correlation with host physiology. Results indicate significant differences in alpha-diversity and overall vaginal microbial community members in various reproductive and post-reproductive phases. In addition to reinforcing the known influence/role of gonadal hormones in maintaining gynecological health, results indicate how hormonal level perturbations cause/contribute to imbalances in vaginal microbiota. The nature of resulting dysbiotic state and its influence on vaginal health is also analyzed and discussed. Results also suggest that elevated vaginal microbial diversity in pregnancy does not necessarily indicate a state of bacterial infection. The study puts forward a hormone-level driven microbiome diversity hypothesis for explaining temporal patterns in vaginal microbial diversity during various stages of women's reproductive cycle and at menopause.
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Affiliation(s)
| | | | | | - Sharmila S. Mande
- Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services, Pune, India
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Chang DH, Shin J, Rhee MS, Park KR, Cho BK, Lee, SK, Kim BC. Vaginal Microbiota Profiles of Native Korean Women and Associations with High-Risk Pregnancy. J Microbiol Biotechnol 2020; 30:248-258. [PMID: 31838792 PMCID: PMC9728229 DOI: 10.4014/jmb.1908.08016] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The vaginal microbiota may be important for pregnancy prognosis because vaginal dysbiosis during pregnancy appears to be related to preterm birth (PTB) or pregnancy loss. Previous reports have indicated that a Lactobacillus-poor microbial flora in the vagina and intrauterine infection by diverse anaerobes ascending from the vagina are associated with undesirable delivery outcomes. However, no research has involved the use of pyrosequencing analysis to examine vaginal microbiota profiles or their potential associations with high-risk pregnancy in Korean women. Vaginal swabs were collected from 500 Korean women for the identification of community state types (CSTs). Of these, 137 samples were further analyzed using a Roche/454 GS Junior pyrosequencer. Three distinct CSTs were identified based on the dominant vaginal microbes: CST I (Lactobacillus crispatus dominated), CST III (Lactobacillus iners dominated), and CST IV (with diverse species of anaerobes). Twelve of the 67 pregnant women had undesirable pregnancy outcomes (four miscarriages and eight PTBs). The dominant microbe in the vaginal microbiota of women who gave birth at full-term was L. crispatus. In contrast, L. iners was the dominant vaginal microbe in women who miscarried. Most (n = 6/8) vaginal microbiota profiles of women who experienced PTB could be classified as CST IV, with diverse bacteria, including anaerobic vaginal species. The present study provides valuable information regarding the characteristics of the vaginal microbiota of Korean women related to high-risk pregnancy. Investigation of the vaginal microbiotic structure in pregnant Korean women is necessary to enable better prediction of adverse pregnancy outcomes.
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Affiliation(s)
- Dong-Ho Chang
- Metabolic Regulation Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 344, Republic of Korea,Department of Biological Science and Biotechnology, Hannam University, Daejeon 34054, Republic of Korea
| | - Jongoh Shin
- Department of Biological Sciences and KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 4141, Republic of Korea
| | - Moon-Soo Rhee
- Biological Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 311, Republic of Korea
| | - Kyung-Ryang Park
- Department of Biological Science and Biotechnology, Hannam University, Daejeon 34054, Republic of Korea
| | - Byung-Kwan Cho
- Department of Biological Sciences and KI for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 4141, Republic of Korea
| | - Sung-Ki Lee,
- Department of Obstetrics and Gynecology, College of Medicine, Myunggok Medical Research Center, Konyang University, Daejeon 336, Republic of Korea,Corresponding authors S.K.L. Phone: +82-42-600-9204 Fax: +82-42-600-9204 E-mail:
| | - Byoung-Chan Kim
- Metabolic Regulation Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 344, Republic of Korea,Department of Bioprocess Engineering, KRIBB School of Biotechnology, Korea University of Science and Technology (UST), Daejeon 34113, Republic of Korea,Corresponding authors S.K.L. Phone: +82-42-600-9204 Fax: +82-42-600-9204 E-mail:
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The Evolving Microbiome from Pregnancy to Early Infancy: A Comprehensive Review. Nutrients 2020; 12:nu12010133. [PMID: 31906588 PMCID: PMC7019214 DOI: 10.3390/nu12010133] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 12/20/2019] [Accepted: 12/20/2019] [Indexed: 12/12/2022] Open
Abstract
Pregnancy induces a number of immunological, hormonal, and metabolic changes that are necessary for the mother to adapt her body to this new physiological situation. The microbiome of the mother, the placenta and the fetus influence the fetus growth and undoubtedly plays a major role in the adequate development of the newborn infant. Hence, the microbiome modulates the inflammatory mechanisms related to physiological and pathological processes that are involved in the perinatal progress through different mechanisms. The present review summarizes the actual knowledge related to physiological changes in the microbiota occurring in the mother, the fetus, and the child, both during neonatal period and beyond. In addition, we approach some specific pathological situations during the perinatal periods, as well as the influence of the type of delivery and feeding.
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Romero R, Gomez-Lopez N, Winters AD, Jung E, Shaman M, Bieda J, Panaitescu B, Pacora P, Erez O, Greenberg JM, Ahmad MM, Hsu CD, Theis KR. Evidence that intra-amniotic infections are often the result of an ascending invasion - a molecular microbiological study. J Perinat Med 2019; 47:915-931. [PMID: 31693497 PMCID: PMC7147941 DOI: 10.1515/jpm-2019-0297] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 08/18/2019] [Indexed: 12/15/2022]
Abstract
Background Microbial invasion of the amniotic cavity resulting in intra-amniotic infection is associated with obstetrical complications such as preterm labor with intact or ruptured membranes, cervical insufficiency, as well as clinical and histological chorioamnionitis. The most widely accepted pathway for intra-amniotic infection is the ascension of microorganisms from the lower genital tract. However, hematogenous dissemination of microorganisms from the oral cavity or intestine, retrograde seeding from the peritoneal cavity through the fallopian tubes, and introduction through invasive medical procedures have also been suggested as potential pathways for intra-amniotic infection. The primary reason that an ascending pathway is viewed as most common is that the microorganisms most often detected in the amniotic fluid are those that are typical inhabitants of the vagina. However, thus far, no studies have shown that microorganisms in the amniotic cavity are simultaneously present in the vagina of the woman from which they were isolated. The objective of the study was to determine the frequency with which microorganisms isolated from women with intra-amniotic infection are also present in the lower genital tract. Methods This was a cross-sectional study of women with intra-amniotic infection with intact membranes. Intra-amniotic infection was defined as a positive culture and elevated concentrations of interleukin-6 (IL-6) (>2.6 ng/mL) in amniotic fluid and/or acute histologic chorioamnionitis and funisitis. Microorganisms isolated from bacterial cultures of amniotic fluid were taxonomically identified through matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF) and 16S ribosomal RNA (rRNA) gene sequencing. Vaginal swabs were obtained at the time of amniocentesis for the identification of microorganisms in the lower genital tract. The overall bacterial profiles of amniotic fluids and vaginal swabs were characterized through 16S rRNA gene sequencing. The bacterial profiles of vaginal swabs were interrogated for the presence of bacteria cultured from amniotic fluid and for the presence of prominent (>1% average relative abundance) operational taxonomic units (OTUs) within the overall 16S rRNA gene bacterial profiles of amniotic fluid. Results (1) A total of 75% (6/8) of women had bacteria cultured from their amniotic fluid that are typical residents of the vaginal ecosystem. (2) A total of 62.5% (5/8) of women with bacteria cultured from their amniotic fluid also had these bacteria present in their vagina. (3) The microorganisms cultured from amniotic fluid and also detected in the vagina were Ureaplasma urealyticum, Escherichia coli, and Streptococcus agalactiae. (4) 16S rRNA gene sequencing revealed that the amniotic fluid of women with intra-amniotic infection had bacterial profiles dominated by Sneathia, Ureaplasma, Prevotella, Lactobacillus, Escherichia, Gardnerella, Peptostreptococcus, Peptoniphilus, and Streptococcus, many of which had not been cultured from the amniotic fluid samples. (5) Seventy percent (7/10) of the prominent (>1% average relative abundance) OTUs found in amniotic fluid were also prominent in the vagina. Conclusion The majority of women with intra-amniotic infection had bacteria cultured from their amniotic fluid that were typical vaginal commensals, and these bacteria were detected within the vagina at the time of amniocentesis. Molecular microbiological interrogation of amniotic fluid from women with intra-amniotic infection revealed that the bacterial profiles of amniotic fluid were largely consistent with those of the vagina. These findings indicate that ascension from the lower genital tract is the primary pathway for intra-amniotic infection.
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Affiliation(s)
- Roberto Romero
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA
- Detroit Medical Center, Detroit, MI, USA
- Department of Obstetrics and Gynecology, Florida International University, Miami, FL, USA
| | - Nardhy Gomez-Lopez
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
- Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, MI, USA
- Perinatal Research Initiative in Maternal, Perinatal and Child Health, Wayne State University School of Medicine, Detroit, MI, USA
| | - Andrew D. Winters
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Eunjung Jung
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Majid Shaman
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Janine Bieda
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Bogdan Panaitescu
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Percy Pacora
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Offer Erez
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
- Maternity Department “D,” Division of Obstetrics and Gynecology, Soroka University Medical Center School of Medicine, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer-Sheva, Israel
| | - Jonathan M. Greenberg
- Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Madison M. Ahmad
- Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Chaur-Dong Hsu
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA
- Perinatal Research Initiative in Maternal, Perinatal and Child Health, Wayne State University School of Medicine, Detroit, MI, USA
- Department of Physiology, Wayne State University School of Medicine, Detroit, MI, USA
| | - Kevin R. Theis
- Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA
- Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, MI, USA
- Perinatal Research Initiative in Maternal, Perinatal and Child Health, Wayne State University School of Medicine, Detroit, MI, USA
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Haque MM, Mande SS. Decoding the microbiome for the development of translational applications: Overview, challenges and pitfalls. J Biosci 2019; 44:118. [PMID: 31719227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Recent studies have highlighted the potential of 'translational' microbiome research in addressing real-world challenges pertaining to human health, nutrition and disease. Additionally, outcomes of microbiome research have also positively impacted various aspects pertaining to agricultural productivity, fuel or energy requirements, and stability/preservation of various ecological habitats. Microbiome data is multi-dimensional with various types of data comprising nucleic and protein sequences, metabolites as well as various metadata related to host and or environment. This poses a major challenge for computational analysis and interpretation of data to reach meaningful, reproducible (and replicable) biological conclusions. In this review, we first describe various aspects of microbiomes that make them an attractive tool/target for developing various translational applications. The challenge of deciphering signatures from an information-rich resource like the microbiome is also discussed. Subsequently, we present three case-studies that exemplify the potential of microbiome- based solutions in solving real-world problems. The final part of the review attempts to familiarize readers with the importance of a robust study design and the diligence required during every stage of analysis for achieving solutions with potential translational value.
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Affiliation(s)
- Mohammed Monzoorul Haque
- Bio-Sciences R and D Division, TCS Research, Tata Consultancy Services Limited, Pune 411 013, India
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37
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Haque MM, Mande SS. Decoding the microbiome for the development of translational applications: Overview, challenges and pitfalls. J Biosci 2019. [DOI: 10.1007/s12038-019-9932-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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38
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Das Purkayastha S, Bhattacharya MK, Prasad HK, Upadhyaya H, Lala SD, Pal K, Das M, Sharma GD, Bhattacharjee MJ. Contrasting diversity of vaginal lactobacilli among the females of Northeast India. BMC Microbiol 2019; 19:198. [PMID: 31455211 PMCID: PMC6712660 DOI: 10.1186/s12866-019-1568-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 08/11/2019] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Lactobacilli are gatekeepers of vaginal ecosystem impeding growth of pathogenic microbes and their diversity varies across populations worldwide. The present study investigated diversity of human vaginal microbiota among females of Northeast India, who are distinct in dietary habits, lifestyle, and genomic composition from rest of India. RESULTS Altogether, 154 bacterial isolates were obtained from vaginal swab samples of 40 pregnant and 29 non-pregnant females. The samples were sequenced for 16 s rRNA gene and analysed for identification using a dual approach of homology search and maximum likelihood based clustering. Molecular identification based on 16S rRNA gene sequence confirmed the isolates belonging to 31 species. Lactobacilli constituted 37.7% of the bacterial isolates with 10 species and other Lactic Acid Bacteria (39.61%) represented another 10 species, some of which are opportunistic pathogens. The remaining of the communities are mostly dominated by species of Staphylococcus (14.28%) and rarely by Propionibacterium avidum (3.90%), Bacillus subtilis, Escherchia coli, Janthinobacterium lividum, and Kocuria kristinae (each 0.64%). Interestingly Lactobacillus mucosae and Enterococcus faecalis, which are globally uncommon vaginal microbes is found dominant among women of Northeast India. This tentatively reflects adaptability of particular Lactobacillus species, in distinct population, to better compete for receptors and nutrients in vaginal epithelium than other species. Further, intrageneric 16S rRNA gene exchange was observed among Enterococcus, Staphylococcus, and two species of Lactobacillus, and deep intraspecies divergence among L. mucosae, which pinpointed possibility of emergence of new strains with evolved functionality. Lactobacilli percentage decreased from young pregnant to aged non-pregnant women with maximum colonization in trimester II. CONCLUSION The study highlighted importance of assessment of vaginal microbiota, Lactobacillus in particular, across different population to gain more insight on female health.
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Affiliation(s)
- Sumi Das Purkayastha
- Karimganj College, Karimganj, Assam, India.,Department of Life Science and Bioinformatics, Assam University, Silchar, Assam, India
| | | | | | | | - Suparna Das Lala
- Department of Gynaecology, Hospital of Red Cross Society, Karimganj, Assam, India
| | - Kunal Pal
- Department of Biotechnology and Medical Engineering, NIT Rourkela, Rourkela, Orissa, India
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39
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Fettweis JM, Serrano MG, Brooks JP, Edwards DJ, Girerd PH, Parikh HI, Huang B, Arodz TJ, Edupuganti L, Glascock AL, Xu J, Jimenez NR, Vivadelli SC, Fong SS, Sheth NU, Jean S, Lee V, Bokhari YA, Lara AM, Mistry SD, Duckworth RA, Bradley SP, Koparde VN, Orenda XV, Milton SH, Rozycki SK, Matveyev AV, Wright ML, Huzurbazar SV, Jackson EM, Smirnova E, Korlach J, Tsai YC, Dickinson MR, Brooks JL, Drake JI, Chaffin DO, Sexton AL, Gravett MG, Rubens CE, Wijesooriya NR, Hendricks-Muñoz KD, Jefferson KK, Strauss JF, Buck GA. The vaginal microbiome and preterm birth. Nat Med 2019; 25:1012-1021. [PMID: 31142849 PMCID: PMC6750801 DOI: 10.1038/s41591-019-0450-2] [Citation(s) in RCA: 496] [Impact Index Per Article: 99.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 04/09/2019] [Indexed: 12/15/2022]
Abstract
The incidence of preterm birth exceeds 10% worldwide. There are significant disparities in the frequency of preterm birth among populations within countries, and women of African ancestry disproportionately bear the burden of risk in the United States. In the present study, we report a community resource that includes ‘omics’ data from approximately 12,000 samples as part of the integrative Human Microbiome Project. Longitudinal analyses of 16S ribosomal RNA, metagenomic, metatranscriptomic and cytokine profiles from 45 preterm and 90 term birth controls identified harbingers of preterm birth in this cohort of women predominantly of African ancestry. Women who delivered preterm exhibited significantly lower vaginal levels of Lactobacillus crispatus and higher levels of BVAB1, Sneathia amnii, TM7-H1, a group of Prevotella species and nine additional taxa. The first representative genomes of BVAB1 and TM7-H1 are described. Preterm-birth-associated taxa were correlated with proinflammatory cytokines in vaginal fluid. These findings highlight new opportunities for assessment of the risk of preterm birth. As part of the second phase of Human Microbiome Project, the Multi-Omic Microbiome Study: Pregnancy Initiative presents a community resource to help better understand how microbiome and host profiles change throughout pregnancy as well as to identify new opportunities for assessment of the risk of preterm birth.
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Affiliation(s)
- Jennifer M Fettweis
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Department of Obstetrics and Gynecology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Myrna G Serrano
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - J Paul Brooks
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Supply Chain Management and Analytics, School of Business, Virginia Commonwealth University, Richmond, VA, USA
| | - David J Edwards
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Department of Statistical Sciences and Operations Research, College of Humanities and Sciences, Virginia Commonwealth University, Richmond, VA, USA
| | - Philippe H Girerd
- Department of Obstetrics and Gynecology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Hardik I Parikh
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Bernice Huang
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Tom J Arodz
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Department of Computer Science, College of Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Laahirie Edupuganti
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Jie Xu
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Division of Neonatal Medicine, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Department of Pediatrics, School of Medicine, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, VA, USA
| | - Nicole R Jimenez
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Stephany C Vivadelli
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Stephen S Fong
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Department of Chemical and Life Science Engineering, College of Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Nihar U Sheth
- Center for the Study of Biological Complexity, VCU Life Sciences, Virginia Commonwealth University, Richmond, VA, USA
| | - Sophonie Jean
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Vladimir Lee
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Yahya A Bokhari
- Department of Computer Science, College of Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - Ana M Lara
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Shreni D Mistry
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Robert A Duckworth
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Steven P Bradley
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Vishal N Koparde
- Center for the Study of Biological Complexity, VCU Life Sciences, Virginia Commonwealth University, Richmond, VA, USA
| | - X Valentine Orenda
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Sarah H Milton
- Department of Obstetrics and Gynecology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Sarah K Rozycki
- School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Andrey V Matveyev
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Michelle L Wright
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.,Department of Women's Health, Dell School of Medicine, University of Texas at Austin, Austin, TX, USA.,School of Nursing, University of Texas at Austin, Austin, TX, USA
| | - Snehalata V Huzurbazar
- Department of Biostatistics, School of Public Health, West Virginia University, Morgantown, WV, USA
| | - Eugenie M Jackson
- Department of Biostatistics, School of Public Health, West Virginia University, Morgantown, WV, USA
| | - Ekaterina Smirnova
- Department of Mathematical Sciences, University of Montana, Missoula, MT, USA.,Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | | | | | - Molly R Dickinson
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Jamie L Brooks
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Jennifer I Drake
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Donald O Chaffin
- Global Alliance to Prevent Prematurity and Stillbirth, Seattle, WA, USA
| | - Amber L Sexton
- Global Alliance to Prevent Prematurity and Stillbirth, Seattle, WA, USA
| | - Michael G Gravett
- Global Alliance to Prevent Prematurity and Stillbirth, Seattle, WA, USA.,Department of Obstetrics & Gynecology, University of Washington, Seattle, WA, USA
| | - Craig E Rubens
- Global Alliance to Prevent Prematurity and Stillbirth, Seattle, WA, USA
| | - N Romesh Wijesooriya
- Department of Pediatrics, School of Medicine, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, VA, USA
| | - Karen D Hendricks-Muñoz
- Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA.,Division of Neonatal Medicine, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Department of Pediatrics, School of Medicine, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, VA, USA
| | - Kimberly K Jefferson
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Jerome F Strauss
- Department of Obstetrics and Gynecology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA.,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA
| | - Gregory A Buck
- Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA. .,Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, VA, USA. .,Department of Computer Science, College of Engineering, Virginia Commonwealth University, Richmond, VA, USA.
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40
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Brown RG, Al-Memar M, Marchesi JR, Lee YS, Smith A, Chan D, Lewis H, Kindinger L, Terzidou V, Bourne T, Bennett PR, MacIntyre DA. Establishment of vaginal microbiota composition in early pregnancy and its association with subsequent preterm prelabor rupture of the fetal membranes. Transl Res 2019; 207:30-43. [PMID: 30633889 PMCID: PMC6489901 DOI: 10.1016/j.trsl.2018.12.005] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 12/19/2018] [Accepted: 12/21/2018] [Indexed: 10/31/2022]
Abstract
Vaginal bacterial community composition influences pregnancy outcome. Preterm prelabor rupture of the fetal membranes (PPROM), which precedes 30% of all spontaneous preterm births, is associated with high vaginal bacterial diversity prior to rupture. The point at which vaginal bacterial diversity is established before PPROM is unknown. In this study, we use metataxonomics to longitudinally characterize the vaginal bacterial composition from as early as 6 weeks of gestation in women at high (n = 38) and low (n = 22) risk of preterm birth who subsequently experience PPROM and in women delivering at term without complications (n = 36). Reduced Lactobacillus spp. abundance and high diversity was observed prior to PPROM in 20% and 26% of women at low and high risk of preterm births respectively, but in only 3% of women who delivered at term. PPROM was associated with instability of bacterial community structure during pregnancy and a shift toward higher diversity predominately occurring during the second trimester. This was characterized by increased relative abundance of potentially pathogenic species including Prevotella, Peptoniphilus, Streptococcus, and Dialister. This study identifies reduced Lactobacillus spp. abundance and increasing vaginal bacterial diversity as an early risk factor for PPROM and highlights the need for interventional studies designed to assess the impact of modifying vaginal bacterial composition for the prevention of preterm birth.
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Key Words
- bmi, body mass index
- dna, deoxyribonucleic acid
- ena, european nucleotide archive
- ga, gestational age
- hca, hierarchical cluster analysis
- lda, latent discriminatory analysis
- mr, membrane rupture
- nhs, national health service
- nice, national institute for health and care excellence
- pcr, polymerase chain reaction
- pprom, preterm prelabor rupture of the fetal membranes
- ptb, preterm birth
- rdp, ribosomal database project
- sra, sequence read archive
- stamp, statistical analysis of metagenomic profiles
- sop, standard operating procedure
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Affiliation(s)
- Richard G Brown
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Maya Al-Memar
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Julian R Marchesi
- March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK; Centre for Digestive and Gut Health, Imperial College London, London, UK; School of Biosciences, Cardiff University, Cardiff, UK
| | - Yun S Lee
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK
| | - Ann Smith
- School of Medicine, Cardiff University, Cardiff, UK
| | - Denise Chan
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Holly Lewis
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Lindsay Kindinger
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Vasso Terzidou
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK; Chelsea & Westminster Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Tom Bourne
- March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK
| | - Phillip R Bennett
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; Queen Charlotte's Hospital, Imperial College Healthcare NHS Trust, London, UK; March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK
| | - David A MacIntyre
- Imperial College Parturition Research Group, Division of the Institute of Reproductive and Developmental Biology, Imperial College London, London, UK; March of Dimes European Preterm Birth Research Centre, Imperial College London, London, UK.
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41
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Shaping Microbiota During the First 1000 Days of Life. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1125:3-24. [PMID: 30680645 DOI: 10.1007/5584_2018_312] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The data obtained in prior studies suggest that early microbial exposition begins prior to conception and gestation. Given that the host-microbe interaction is shaped by the immune system response, it is important to understand the key immune system-microbiota relationship during the period from conception to the first years of life. The present work summarizes the available evidence concerning early microbiota exposure within the male and the female reproductive tracts at the point of conception and during gestation, focusing on the potential impact on infant development during the first 1000 days of life. Furthermore, we conclude that some dietary strategies including specific probiotics could become potentially valuable tools to modulate the gut microbiota during this early critical window of opportunity for targeted health outcomes throughout the entire lifespan.
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Côté N, Pasquier JC. [Spontaneous preterm birth and the maternal microbiome]. Med Sci (Paris) 2018; 34:799-805. [PMID: 30451673 DOI: 10.1051/medsci/2018205] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Preterm birth is the leading cause of perinatal mortality and morbidity. Despite the efforts spent over the past 40 years to solve the physiopathological processes involved in the triggering of prematurity, efficient therapeutics are still lacking. Recently, growing body of evidence suggests that the maternal microbiome is a major player for a normal pregnancy and that dysbiosis is associated with preterm birth. The vaginal microbiome and its commensal Lactobacillus species may protect the uterus of ascending dissemination of pathogens. The uterus can also be contaminated with oral bacteria by the blood stream. Thus, the maternal microbiome can play both a protective role or a causal role in the triggering of preterm birth.
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Affiliation(s)
- Nathalie Côté
- Département d'obstétrique-gynécologie et département de microbiologie et infectiologie, université de Sherbrooke, 3001 12e avenue Nord, Sherbrooke, Québec (J1H 5H3), Canada - Département d'obstétrique-gynécologie, université de Sherbrooke, 3001 12e avenue Nord, Sherbrooke, Québec (J1H 5H3), Canada
| | - Jean-Charles Pasquier
- Département d'obstétrique-gynécologie et département de microbiologie et infectiologie, université de Sherbrooke, 3001 12e avenue Nord, Sherbrooke, Québec (J1H 5H3), Canada - Département d'obstétrique-gynécologie, université de Sherbrooke, 3001 12e avenue Nord, Sherbrooke, Québec (J1H 5H3), Canada
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43
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Gut Microbiota and Mucosal Immunity in the Neonate. Med Sci (Basel) 2018; 6:medsci6030056. [PMID: 30018263 PMCID: PMC6163169 DOI: 10.3390/medsci6030056] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 07/04/2018] [Accepted: 07/12/2018] [Indexed: 12/17/2022] Open
Abstract
Gut microbiota colonization is a complex, dynamic, and step-wise process that is in constant development during the first years of life. This microbial settlement occurs in parallel with the maturation of the immune system, and alterations during this period, due to environmental and host factors, are considered to be potential determinants of health-outcomes later in life. Given that host–microbe interactions are mediated by the immune system response, it is important to understand the close relationship between immunity and the microbiota during birth, lactation, and early infancy. This work summarizes the evidence to date on early gut microbiota colonization, and how it influences the maturation of the infant immune system and health during the first 1000 days of life. This review will also address the influence of perinatal antibiotic intake and the importance of delivery mode and breastfeeding for an appropriate development of gut immunity.
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44
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Intrauterine inflammatory activation, functional progesterone withdrawal, and the timing of term and preterm birth. J Reprod Immunol 2018; 125:89-99. [DOI: 10.1016/j.jri.2017.12.004] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 12/17/2017] [Accepted: 12/21/2017] [Indexed: 01/19/2023]
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