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ABSTRACT Shotgun metagenomic sequencing has the potential to provide bacterial strain-level resolution which is of key importance to tackle a host of clinical questions. While bioinformatic tools that achieve strain-level resolution are available, thorough benchmarking is needed to validate their use for less investigated and low biomass microbiomes like those from the upper respiratory tract. We analyzed a previously published data set of longitudinally collected nasopharyngeal samples from Bangladeshi infants (Microbiota and Health study) and a novel data set of oropharyngeal samples from Swiss children with cystic fibrosis. Data from bacterial cultures were used for benchmarking the parameters of StrainPhlAn 3, a bioinformatic tool designed for strain-level resolution. In addition, StrainPhlAn 3 results were compared with metagenomic assemblies derived from StrainGE and newly derived whole-genome sequencing data. After optimizing the analytical parameters, we compared StrainPhlAn 3 results to culture gold standard methods and achieved sensitivity values of 87% (Streptococcus pneumoniae), 80% (Moraxella catarrhalis), 75% (Haemophilus influenzae), and 57% (Staphylococcus aureus) for 420 nasopharyngeal and 75% (H. influenzae) and 46% (S. aureus) for 260 oropharyngeal samples. Comparing the phylogenetic tree of the core genome of 50 S. aureus isolates with a corresponding marker gene tree generated by StrainPhlAn 3 revealed a striking similarity in tree topology for all but three samples indicating adequate strain resolution. In conclusion, a comparison of StrainPhlAn 3 results to data from bacterial cultures revealed that strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA when parameters are carefully optimized to fit low biomass microbiomes.IMPORTANCEThe usage of 16S rRNA gene sequencing has become the state-of-the-art method for the characterization of the microbiota in health and respiratory disease. The method is reliable for low biomass samples due to prior amplification of the 16S rRNA gene but has limitations as species and certainly strain identification is not possible. However, the usage of metagenomic tools for the analyses of microbiome data from low biomass samples is not straight forward, and careful optimization is needed. In this work, we show that by validating StrainPhlAn 3 results with the data from bacterial cultures, the strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA being present when parameters are carefully optimized to fit low biomass microbiomes. This work further proposes that strain retention analyses are feasible, at least for more abundant species. This will help to better understand the longitudinal dynamics of the upper respiratory microbiome during health and disease.

Cow’s milk protein allergy (CMPA) is a prevalent food allergy among infants and young children. We conducted a randomized, multicenter intervention study involving 194 non-breastfed infants with CMPA until 12 months of age (clinical trial registration: NCT03085134). One exploratory objective was to assess the effects of a whey-based extensively hydrolyzed formula (EHF) supplemented with 2′-fucosyllactose (2′-FL) and lacto-N-neotetraose (LNnT) on the fecal microbiome and metabolome in this population. Thus, fecal samples were collected at baseline, 1 and 3 months from enrollment, as well as at 12 months of age. Human milk oligosaccharides (HMO) supplementation led to the enrichment of bifidobacteria in the gut microbiome and delayed the shift of the microbiome composition toward an adult-like pattern. We identified specific HMO-mediated changes in fecal amino acid degradation and bile acid conjugation, particularly in infants commencing the HMO-supplemented formula before the age of three months. Thus, HMO supplementation partially corrected the dysbiosis commonly observed in infants with CMPA. Further investigation is necessary to determine the clinical significance of these findings in terms of a reduced incidence of respiratory infections and other potential health benefits.

Faecalibacterium prausnitzii (F. prausnitzii) is a bacterial taxon in the human gut with anti-inflammatory properties, and this may contribute to the beneficial effects of healthy eating habits. However, little is known about the nutrients that enhance the growth of F. prausnitzii other than simple sugars and fibers. Here, we combined dietary and microbiome data from the American Gut Project (AGP) to identify nutrients that may be linked to the relative abundance of F. prausnitzii. Using a machine learning approach in combination with univariate analyses, we identified that sugar alcohols, carbocyclic sugar, and vitamins may contribute to F. prausnitzii growth. We next explored the effects of these nutrients on the growth of two F. prausnitzii strains in vitro and observed robust and strain-dependent growth patterns on sorbitol and inositol, respectively. In the context of a complex community using in vitro fermentation, neither inositol alone nor in combinations with vitamin B exerted a significant growth-promoting effect on F. prausnitzii, partly due to high variability among the fecal microbiota community from four healthy donors. However, the fecal communities that showed an increase in F. prausnitzii on inulin also responded with at least 60% more F. prausnitzii on any of inositol containing media than control. Future nutritional studies aiming to increase the relative abundance of F. prausnitzii should explore a personalized approach accounting for strain-level genetic variations and community-level microbiome composition.

ABSTRACT Acute respiratory infections (ARIs) are one of the most common causes of morbidity and mortality in young children. The aim of our study was to examine whether variation in maternal FUT2 (α1,2-fucosyltransferase 2) and FUT3 (α1,3/4-fucosyltransferase 3) genes, which shape fucosylated human milk oligosaccharides (HMOs) in breast milk, are associated with the occurrence of ARIs in breastfed infants as well as the influence of the nasopharyngeal microbiome on ARI risk. Occurrences of ARIs were prospectively recorded in a cohort of 240 breastfed Bangladeshi infants from birth to 2 years. Secretor and Lewis status was established by sequencing of FUT2/3 genes. The nasopharyngeal microbiome was characterized by shotgun metagenomics, complemented by specific detection of respiratory pathogens; 88.6% of mothers and 91% of infants were identified as secretors. Maternal secretor status was associated with reduced ARI incidence among these infants in the period from birth to 6 months (incidence rate ratio [IRR], 0.66; 95% confidence interval [CI], 0.47 to 0.94; P = 0.020), but not at later time periods. The nasopharyngeal microbiome, despite precise characterization to the species level, was not predictive of subsequent ARIs. The observed risk reduction of ARIs among infants of secretor mothers during the predominant breastfeeding period is consistent with the hypothesis that fucosylated oligosaccharides in human milk contribute to protection against respiratory infections. However, we found no evidence that modulation of the nasopharyngeal microbiome influenced ARI risk. IMPORTANCE The observed risk reduction of acute respiratory infections (ARIs) among infants of secretor mothers during the predominant breastfeeding period is consistent with the hypothesis that fucosylated oligosaccharides in human milk contribute to protection against respiratory infections. Respiratory pathogens were only weak modulators of risk, and the nasopharyngeal microbiome did not influence ARI risk, suggesting that the associated protective effects of human milk oligosaccharides (HMOs) are not conveyed via changes in the nasopharyngeal microbiome. Our observations add to the evidence for a role of fucosylated HMOs in protection against respiratory infections in exclusively or predominantly breastfed infants in low-resource settings. There is no indication that the nasopharyngeal microbiome substantially modulates the risk of subsequent mild ARIs. Larger studies are needed to provide mechanistic insights on links between secretor status, HMOs, and risk of respiratory infections.

ABSTRACT Human milk oligosaccharides (HMOs) may provide health benefits to infants partly by shaping the development of the early-life intestinal microbiota. In a randomized double-blinded controlled multicentric clinical trial, healthy term infants received either infant formula (control) or the same formula with two HMOs (2′-fucosyllactose and lacto-N-neotetraose; test) from enrollment (0 to 14 days) to 6 months. Then, all infants received the same follow-up formula without HMOs until 12 months of age. Breastfed infants (BF) served as a reference group. Stool microbiota at 3 and 12 months, analyzed by 16S rRNA gene sequencing, clustered into seven fecal community types (FCTs) with marked differences in total microbial abundances. Three of the four 12-month FCTs were likely precursors of the adult enterotypes. At 3 months, microbiota composition in the test group (n = 58) appeared closer to that of BF (n = 35) than control (n = 63) by microbiota alpha (within group) and beta (between groups) diversity analyses and distribution of FCTs. While bifidobacteriaceae dominated two FCTs, its abundance was significantly higher in one (FCT BiH for Bifidobacteriaceae at high abundance) than in the other (FCT Bi for Bifidobacteriaceae). HMO supplementation increased the number of infants with FCT BiH (predominant in BF) at the expense of FCT Bi (predominant in control). We explored the association of the FCTs with reported morbidities and medication use up to 12 months. Formula-fed infants with FCT BiH at 3 months were significantly less likely to require antibiotics during the first year than those with FCT Bi. Previously reported lower rates of infection-related medication use with HMOs may therefore be linked to gut microbiota community types. (This study has been registered at ClinicalTrials.gov under registration number NCT01715246.) IMPORTANCE Human milk is the sole and recommended nutrition for the newborn infant and contains one of the largest constituents of diverse oligosaccharides, dubbed human milk oligosaccharides (HMOs). Preclinical and clinical association studies indicate that HMOs have multiple physiological functions largely mediated through the establishment of the gut microbiome. Until recently, HMOs were not available to investigate their role in randomized controlled intervention trials. To our knowledge, this is the first report on the effects of 2 HMOs on establishing microbiota in newborn infants. We provide a detailed description of the microbiota changes observed upon feeding a formula with 2 HMOs in comparison to breastfed reference infants' microbiota. Then, we associate the microbiota to long-term health as assessed by prescribed antibiotic use.

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Unhealthy lifestyle choices, such as bad eating behaviors and cigarette smoking, have major detrimental impacts on health. However, the inter-relations between obesity and smoking are still not fully understood. We thus developed an experimental model of high-fat diet-fed obese C57BL/6 male mice chronically exposed to cigarette smoke. Our study evaluated for the first time the resulting effects of the combined exposure to unhealthy diet and cigarette smoke on several metabolic, pulmonary, intestinal, and cardiac parameters. We showed that the chronic exposure to cigarette smoke modified the pattern of body fat distribution in favor of the visceral depots in obese mice, impaired the respiratory function, triggered pulmonary inflammation and emphysema, and was associated with gut microbiota dysbiosis, cardiac hypertrophy and myocardial fibrosis.

Targeted metagenomics, also known as metagenetics, is a high-throughput sequencing application focusing on a nucleotide target in a microbiome to describe its taxonomic content. A wide range of bioinformatics pipelines are available to analyze sequencing outputs, and the choice of an appropriate tool is crucial and not trivial. No standard evaluation method exists for estimating the accuracy of a pipeline for targeted metagenomics analyses. This article proposes an evaluation protocol containing real and simulated targeted metagenomics datasets, and adequate metrics allowing us to study the impact of different variables on the biological interpretation of results. This protocol was used to compare six different bioinformatics pipelines in the basic user context: Three common ones (mothur, QIIME and BMP) based on a clustering-first approach and three emerging ones (Kraken, CLARK and One Codex) using an assignment-first approach. This study surprisingly reveals that the effect of sequencing errors has a bigger impact on the results that choosing different amplified regions. Moreover, increasing sequencing throughput increases richness overestimation, even more so for microbiota of high complexity. Finally, the choice of the reference database has a bigger impact on richness estimation for clustering-first pipelines, and on correct taxa identification for assignment-first pipelines. Using emerging assignment-first pipelines is a valid approach for targeted metagenomics analyses, with a quality of results comparable to popular clustering-first pipelines, even with an error-prone sequencing technology like Ion Torrent. However, those pipelines are highly sensitive to the quality of databases and their annotations, which makes clustering-first pipelines still the only reliable approach for studying microbiomes that are not well described.

Targeted metagenomics is the solution of choice to reveal differential microbial profiles (defined by richness, diversity and composition) as part of case-control studies. It is well documented that each data processing step may have the potential to introduce bias in the results. However, selecting a bioinformatics pipeline to analyze high-throughput sequencing data from A to Z remains one of the critical considerations in a case-control microbiota study design. Consequently, the aim of this study was to assess whether the same biological conclusions regarding human gut microbiota composition and diversity could be reached using different bioinformatics pipelines. In this work, we considered four pipelines (mothur, QIIME, kraken and CLARK) with different versions and databases, and examined their impact on the outcome of metagenetic analysis of Ion Torrent 16S sequencing data. We re-analyzed a case-control study evaluating the impact of the colonization of the intestinal protozoa Blastocystis sp. on the human gut microbial profile. Although most pipelines reported the same trends in this case-control study, we demonstrated how the use of different pipelines affects the biological conclusions that can be drawn. Targeted metagenomics must therefore rather be considered as a profiling tool to obtain a broad sense of the variations of the microbiota, rather than an accurate identification tool.