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Review
. 2023 Jan;613(7945):639-649.
doi: 10.1038/s41586-022-05546-8. Epub 2023 Jan 25.

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies

Affiliations
Review

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies

Katherine M Kennedy et al. Nature. 2023 Jan.

Abstract

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

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Figures

Fig. 1 |
Fig. 1 |. Relative abundance of bacterial taxa from three recent fetal studies.
Distribution and mean relative abundance (%) of taxa present In fetal samples from three recent studies,, investigating the fetal microbiome, and their corresponding abundance in control samples. Taxa were selected on the basis of the following criteria: genera that were cultured from or detected as enriched in fetal samples as described by Mishra et al. (indicated by ^) or by Rackaityte et al. (indicated by *, including the family Micrococcaceae); all genera detected in fetal samples from Kennedy et al. and the PBS-enriched genus Ralstonia. Taxa were grouped by potential source of contamination in agreement with the likely origin of genera (for skin microorganisms) and previous studies that characterized sources of contamination-. Publicly available unfiltered relative abundance microbiota profiling data associated with each publication were merged into a single phyloseq object (RRID:SCR_01380). Amplicon sequence variants (ASVs) were grouped at the genus or family level (for Micrococcaceae). The mean relative abundance of each taxon was calculated for each sample type within each study and plotted in R (tidyverse, ggplot2; RRID:SCR_014601). Dot size corresponds to the mean relative abundance by sample type and study (mean relative abundances of less than 0.0001% were excluded). Dots are coloured by sample type: reagent controls in grey (Mishra: PBS n = 42, reagent n = 23; Rackaityte: buffer n = 11; Kennedy: reagent n = 2), sampling negatives in aqua (Kennedy: swab n = 1; Rackaityte: air swab n = 19; procedural swab n = 16; moistened swab n = 17) and environmental negatives in sky blue (Mishra: environment n = 47, operator n = 12), internal controls in indigo (Mishra: thymus n = 27, spleen n = 12; Rackaityte: kidney n = 16), fetal lung in pink (Mishra: n = 25), fetal gut in purple (Kennedy: n = 20; Mishra: n = 44; Rackaityte: proximal n = 41, mid n = 45, distal n = 42), and external tissues in red (Mishra: skin n = 35, placenta n = 16).
Fig. 2 |
Fig. 2 |. Reagent contamination in meconium samples from extremely premature infants.
a, Representation of the percentage of reagent contamination (% of total sequence reads) in the first meconium of extremely premature infants collected in a previous study in relation to the day of procurement of said samples (day 1–3 or day 4–6) or in regard to the mode of delivery (C-section or vaginal). Colours indicate the percentage of sequence reads assigned to reagent contamination (legend on top). The day of procurement is significantly correlated with the percentage of reagent contamination reads (P = 0.005 by Mann–Whitney U test or P = 0.01 by Spearman rho test) and the mode of delivery shows a trend (P = 0.07 by Mann–Whitney U test). The number of samples (n) is noted below each category. b, Top, list of reagent contaminants shown together in a. Bottom, list of the most abundant sample-associated-signals and their association (or lack thereof owing to limited size of cohort) with vaginal (V) or C-section (C) delivery.
Fig. 3 |
Fig. 3 |. Relative abundance of bacterial taxa in samples from Rackaityte et al.
Distribution and mean relative abundance (%) of taxa present In fetal and control samples from Rackaityte et al. by batch as defined by Rackaityte et al.. Dominant taxa were selected as described in Fig. 1. Publicly available unfiltered relative abundance microbiota data associated with each publication were merged into a single phyloseq object (RRID:SCR_01380). ASVs were grouped at the genus or family (for Micrococcaceae) level. The mean relative abundance of each taxon was calculated for each sample type within each batch and plotted in R (tidyverse, ggplot2; RRID:SCR_014601). Dot size corresponds to the mean relative abundance by sample type and batch. Dots are coloured by sample type: reagent controls in grey (buffer), sampling negative controls in aqua, internal controls in indigo (kidney) and fetal gut samples in purple.

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