The intestinal microbiota has been implicated in insulin resistance, although evidence regarding causality in humans is scarce. We therefore studied the effect of lean donor (allogenic) versus own (autologous) fecal microbiota transplantation (FMT) to male recipients with the metabolic syndrome. Whereas we did not observe metabolic changes at 18 weeks after FMT, insulin sensitivity at 6 weeks after allogenic FMT was significantly improved, accompanied by altered microbiota composition. We also observed changes in plasma metabolites such as γ-aminobutyric acid and show that metabolic response upon allogenic FMT (defined as improved insulin sensitivity 6 weeks after FMT) is dependent on decreased fecal microbial diversity at baseline. In conclusion, the beneficial effects of lean donor FMT on glucose metabolism are associated with changes in intestinal microbiota and plasma metabolites and can be predicted based on baseline fecal microbiota composition.
Trillions of microorganisms inhabit the human gut and are regarded as potential key factors for health. Characteristics such as diet, lifestyle, or genetics can shape the composition of the gut microbiota and are usually shared by individuals from comparable ethnic origin. So far, most studies assessing how ethnicity relates to the intestinal microbiota compared small groups living at separate geographical locations. Using fecal 16S ribosomal RNA gene sequencing in 2,084 participants of the Healthy Life in an Urban Setting (HELIUS) study, we show that individuals living in the same city tend to share similar gut microbiota characteristics with others of their ethnic background. Ethnicity contributed to explain the interindividual dissimilarities in gut microbiota composition, with three main poles primarily characterized by operational taxonomic units (OTUs) classified as Prevotella (Moroccans, Turks, Ghanaians), Bacteroides (African Surinamese, South-Asian Surinamese), and Clostridiales (Dutch). The Dutch exhibited the greatest gut microbiota α-diversity and the South-Asian Surinamese the smallest, with corresponding enrichment or depletion in numerous OTUs. Ethnic differences in α-diversity and interindividual dissimilarities were independent of metabolic health and only partly explained by ethnic-related characteristics including sociodemographic, lifestyle, or diet factors. Hence, the ethnic origin of individuals may be an important factor to consider in microbiome research and its potential future applications in ethnic-diverse societies.
Microbial amplicon sequencing studies are an important tool in biological and biomedical research. Widespread 16S rRNA gene microbial surveys have shed light on the structure of many ecosystems inhabited by bacteria, including the human body. However, specialized software and algorithms are needed to convert raw sequencing data into biologically meaningful information (i.e. tables of bacterial counts). While different bioinformatic pipelines are available in a rapidly changing and improving field, users are often unaware of limitations and biases associated with individual pipelines and there is a lack of agreement regarding best practices. Here, we compared six bioinformatic pipelines for the analysis of amplicon sequence data: three OTU-level flows (QIIME-uclust, MOTHUR, and USEARCH-UPARSE) and three ASV-level (DADA2, Qiime2-Deblur, and USEARCH-UNOISE3). We tested workflows with different quality control options, clustering algorithms, and cutoff parameters on a mock community as well as on a large (N = 2170) recently published fecal sample dataset from the multi-ethnic HELIUS study. We assessed the sensitivity, specificity, and degree of consensus of the different outputs. DADA2 offered the best sensitivity, at the expense of decreased specificity compared to USEARCH-UNOISE3 and Qiime2-Deblur. USEARCH-UNOISE3 showed the best balance between resolution and specificity. OTU-level USEARCH-UPARSE and MOTHUR performed well, but with lower specificity than ASVlevel pipelines. QIIME-uclust produced large number of spurious OTUs as well as inflated alpha-diversity measures and should be avoided in future studies. This study provides guidance for researchers using amplicon sequencing to gain biological insights. OPEN ACCESSCitation: Prodan A, Tremaroli V, Brolin H, Zwinderman AH, Nieuwdorp M, Levin E (2020) Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing. PLoS ONE 15(1): e0227434. https://doi.org/10.
Birth by Caesarian section is associated with short- and long-term respiratory morbidity. We hypothesized that mode of delivery affects the development of the respiratory microbiota, thereby altering its capacity to provide colonization resistance and consecutive pathobiont overgrowth and infections. Therefore, we longitudinally studied the impact of mode of delivery on the nasopharyngeal microbiota development from birth until six months of age in a healthy, unselected birth cohort of 102 children (n = 761 samples). Here, we show that the respiratory microbiota develops within one day from a variable mixed bacterial community towards a Streptococcus viridans-predominated profile, regardless of mode of delivery. Within the first week, rapid niche differentiation had occurred; initially with in most infants Staphylococcus aureus predominance, followed by differentiation towards Corynebacterium pseudodiphteriticum/propinquum, Dolosigranulum pigrum, Moraxella catarrhalis/nonliquefaciens, Streptococcus pneumoniae, and/or Haemophilus influenzae dominated communities. Infants born by Caesarian section showed a delay in overall development of respiratory microbiota profiles with specifically reduced colonization with health-associated commensals like Corynebacterium and Dolosigranulum, thereby possibly influencing respiratory health later in life.
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