Literature DB >> 31350318

Contamination Is Not Linked to the Gestational Microbiome.

Michelle D Rodriguez1, Kevin K Yu2, Zubin S Paul2, Maureen Keller-Wood3, Charles E Wood2, Eric W Triplett4.   

Abstract

Differentiating between contamination and the genuine presence of 16S rRNA genes in gestational tissue samples is the gold standard for supporting the in utero colonization hypothesis. During gestation, the fetus undergoes significant physiological changes that may be directly affected by maternal colonization of key bacterial genera. In this study, lab benches, necropsy tables, and air ducts were swabbed at the same time as clinical sampling. The relative and absolute abundance of bacteria present in sheep samples was determined by culture-independent and culture-dependent means. Of 14 healthy pregnant ewes, there was no evidence of any bacteria in the fetal liver, spleen, or brain cortex using culture-independent techniques despite evidence of the presence of bacteria in various locations of the necropsy room used for 11 of these 14 sheep. Of the 336 bacterial genera found in the room swabs, only 12 (5%) were also found in the saliva and vaginal swabs among the three ewes for which bacteria were detected. These 12 taxa represent 1.32% of the relative abundance and approximately 393 16S rRNA copies/swab in these three ewes. Using careful necropsy protocols, bacterial contamination of sheep tissues was avoided. Contamination of saliva and vaginal samples was limited to less than 2% of the bacterial population.IMPORTANCE Recent evidence for a gestational microbiome suggests that active transfer between mother and fetus in utero is possible, and, therefore, actions must be taken to clarify the presence versus absence of these organisms in their respected sources. The value of this study is the differentiation between bacterial DNA identified in the necropsy rooms of animals and bacterial DNA whose origin is purely clinical in nature. We do not know the extent to which microorganisms traverse maternal tissues and infiltrate fetal circulation, so measures taken to control for contamination during sample processing are vital for addressing these concerns.
Copyright © 2019 American Society for Microbiology.

Entities:  

Keywords:  community-level analysis; contamination; environment; gestation; microbiome

Year:  2019        PMID: 31350318      PMCID: PMC6752004          DOI: 10.1128/AEM.01127-19

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  18 in total

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Authors:  Mangala A Nadkarni; F Elizabeth Martin; Nicholas A Jacques; Neil Hunter
Journal:  Microbiology       Date:  2002-01       Impact factor: 2.777

2.  Vaginal microbiome of reproductive-age women.

Authors:  Jacques Ravel; Pawel Gajer; Zaid Abdo; G Maria Schneider; Sara S K Koenig; Stacey L McCulle; Shara Karlebach; Reshma Gorle; Jennifer Russell; Carol O Tacket; Rebecca M Brotman; Catherine C Davis; Kevin Ault; Ligia Peralta; Larry J Forney
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-03       Impact factor: 11.205

3.  The placenta harbors a unique microbiome.

Authors:  Kjersti Aagaard; Jun Ma; Kathleen M Antony; Radhika Ganu; Joseph Petrosino; James Versalovic
Journal:  Sci Transl Med       Date:  2014-05-21       Impact factor: 17.956

4.  The maternal microbiota drives early postnatal innate immune development.

Authors:  Mercedes Gomez de Agüero; Stephanie C Ganal-Vonarburg; Tobias Fuhrer; Sandra Rupp; Yasuhiro Uchimura; Hai Li; Anna Steinert; Mathias Heikenwalder; Siegfried Hapfelmeier; Uwe Sauer; Kathy D McCoy; Andrew J Macpherson
Journal:  Science       Date:  2016-03-18       Impact factor: 47.728

5.  Bifidobacterium and Lactobacillus DNA in the human placenta.

Authors:  R Satokari; T Grönroos; K Laitinen; S Salminen; E Isolauri
Journal:  Lett Appl Microbiol       Date:  2008-10-17       Impact factor: 2.858

6.  DADA2: High-resolution sample inference from Illumina amplicon data.

Authors:  Benjamin J Callahan; Paul J McMurdie; Michael J Rosen; Andrew W Han; Amy Jo A Johnson; Susan P Holmes
Journal:  Nat Methods       Date:  2016-05-23       Impact factor: 28.547

7.  PANDAseq: paired-end assembler for illumina sequences.

Authors:  Andre P Masella; Andrea K Bartram; Jakub M Truszkowski; Daniel G Brown; Josh D Neufeld
Journal:  BMC Bioinformatics       Date:  2012-02-14       Impact factor: 3.169

8.  Meconium microbiome analysis identifies bacteria correlated with premature birth.

Authors:  Alexandria N Ardissone; Diomel M de la Cruz; Austin G Davis-Richardson; Kevin T Rechcigl; Nan Li; Jennifer C Drew; Roberto Murgas-Torrazza; Renu Sharma; Mark L Hudak; Eric W Triplett; Josef Neu
Journal:  PLoS One       Date:  2014-03-10       Impact factor: 3.240

9.  Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

Authors:  Susannah J Salter; Michael J Cox; Elena M Turek; Szymon T Calus; William O Cookson; Miriam F Moffatt; Paul Turner; Julian Parkhill; Nicholas J Loman; Alan W Walker
Journal:  BMC Biol       Date:  2014-11-12       Impact factor: 7.431

10.  Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples.

Authors:  Angela Glassing; Scot E Dowd; Susan Galandiuk; Brian Davis; Rodrick J Chiodini
Journal:  Gut Pathog       Date:  2016-05-26       Impact factor: 4.181

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