Uncovering Bifidobacteria via Targeted Sequencing of the Mammalian Gut Microbiota

Utilization of diverse oligosaccharides for growth by Bifidobacterium and Lactobacillus species and their in vitro co-cultivation characteristics

Various approaches have been used to study the relationship between prebiotics and probiotics. The utilization of different carbohydrates by probiotics depends on the biochemical properties of the enzymes and substrates required by the microbial strain. However, few studies have systematically analyzed the ability of probiotics to utilize different prebiotics. Here, we investigated the effects of prebiotics from different manufacturers on the proliferation of 13 strains of the Lactobacillus group and the genus Bifidobacterium co-cultured in vitro. Inulin, fructose-oligosaccharide (FOS), and galactose-oligosaccharide (GOS) had broad growth-promoting effects. FOS significantly promoted the proliferation of B. longum. When strains from Lactobacillus group and Bifidobacterium were co-cultured, FOS caused each strain to proliferate cooperatively. GOS was effectively used by L. rhamnosus and L. reuteri for energy and growth promotion. L. casei and L. paracasei fully metabolized inulin; these strains performed better than other strains from Lactobacillus group and Bifidobacterium. Media containing a mixture of oligosaccharides had stronger effects on the growth of B. animalis subsp. lactis, L. acidophilus, and L. rhamnosus than media containing single oligosaccharides. Thus, different oligosaccharides had different effects on the growth of probiotics, providing a scientific basis for the use of synbiotics in health and related fields.

Faecal Microbiota Characterisation of Potamochoerus porcus Living in a Controlled Environment

Intestinal bacteria establish a specific relationship with the host animal, which causes the acquisition of gut microbiota with a unique composition classified as the enterotype. As the name suggests, the Red River Hog is a wild member of the pig family living in Africa, in particular through the West and Central African rainforest. To date, very few studies have analysed the gut microbiota of Red River Hogs (RRHs) both housed under controlled conditions and in wild habitats. This study analysed the intestinal microbiota and the distribution of Bifidobacterium species in five Red River Hog (RRH) individuals (four adults and one juvenile), hosted in two different modern zoological gardens (Parco Natura Viva, Verona, and Bioparco, Rome) with the aim of disentangling the possible effects of captive different lifestyle and host genetics. Faecal samples were collected and studied both for bifidobacterial counts and isolation by means of culture-dependent method and for total microbiota analysis through the high-quality sequences of the V3-V4 region of bacterial 16S rRNA. Results showed a host-specific bifidobacterial species distribution. Indeed, B. boum and B. thermoacidophilum were found only in Verona RRHs, whereas B. porcinum species were isolated only in Rome RRHs. These bifidobacterial species are also typical of pigs. Bifidobacterial counts were about 10⁶ CFU/g in faecal samples of all the individuals, with the only exception for the juvenile subject, showing 10⁷ CFU/g. As in human beings, in RRHs a higher count of bifidobacteria was also found in the young subject compared with adults. Furthermore, the microbiota of RRHs showed qualitative differences. Indeed, Firmicutes was found to be the dominant phylum in Verona RRHs whereas Bacteroidetes was the most represented in Roma RRHs. At order level, Oscillospirales and Spirochaetales were the most represented in Verona RRHs compared with Rome RRHs, where Bacteroidales dominated over the other taxa. Finally, at the family level, RRHs from the two sites showed the presence of the same families, but with different levels of abundance. Our results highlight that the intestinal microbiota seems to reflect the lifestyle (i.e., the diet), whereas age and host genetics are the driving factors for the bifidobacterial population.

Assessment of short-read shotgun sequencing and microbiome analysis of faecal samples to discriminate between equol producers and non-producers

Among the isoflavones and isoflavone-derived metabolites, equol, which in the human gut is synthesised from daidzein by minority bacterial populations, shows the strongest estrogenic and antioxidant activity. The beneficial effects on human health of isoflavone consumption might be partially or indeed totally attributable to this equol. Although some of the bacterial strains involved in its formation have been identified, the interplay between the composition and functionality of the gut microbiota and equol producer phenotype has hardly been studied. In this study, after shotgun metagenomic sequencing, different pipelines for the taxonomic and functional annotation of sequencing data were used in the search for similarities and differences in the faecal metagenome of equol-producing (n=3) and non-producing (n=2) women, with special focus on equol-producing taxa and their equol-associated genes. The taxonomic profiles of the samples differed significantly depending on the analytical method followed, although the microbial diversity detected by each tool was very similar at the phylum, genus and species levels. Equol-producing taxa were detected in both equol producers and non-producers, but no correlation between the abundance of equol-producing taxa and the equol producing/non-producing phenotype was found. Indeed, functional metagenomic analysis was unable to identify the genes involved in equol production, even in samples from equol producers. By aligning equol operons with the collected metagenomics data, a small number of reads mapping to equol-associated sequences were recognised in samples from both equol producers and equol non-producers, but only two reads mapping onto equol reductase-encoding genes in a sample from an equol producer. In conclusion, the taxonomic analysis of metagenomic data might not be suitable for detecting and quantifying equol-producing microbes in human faeces. Functional analysis of the data might provide an alternative. However, to detect the genetic makeup of the minority gut populations, more extensive sequencing than that achieved in the present study might be required.

Exploring the biodiversity of Bifidobacterium asteroides among honey bee microbiomes

Bifidobacterium asteroides is considered the ancestor of the genus Bifidobacterium, which has evolved in close touch with the hindgut of social insects. However, recent studies revealed high intraspecies biodiversity within this taxon, uncovering the putative existence of multiple bifidobacterial species, thus, suggesting its reclassification. Here, a genomic investigation of 98 B. asteroides-related genomes retrieved from public repositories and reconstructed from metagenomes of the hindgut of Apis mellifera and Apis cerana was performed to shed light on the genetic variability of this taxon. Phylogenetic and genomic analyses revealed the existence of eight clusters, of which five have been recently characterized with a representative type strain of the genus and three were represented by putative novel bifidobacterial species inhabiting the honeybee gut. Then, the dissection of 366 shotgun metagenomes of honeybee guts revealed a pattern of seven B. asteroides-related taxa within A. mellifera that co-exist with the host, while A. cerana microbiome was characterized by the predominance of one of the novel species erroneously classified as B. asteroides. A further glycobiome analysis unveiled a conserved repertoire of glycosyl hydrolases (GHs) reflecting degradative abilities towards a broad range of simple carbohydrates together with genes encoding specific GHs of each B. asteroides-related taxa.

Designation of optimal reference strains representing the infant gut bifidobacterial species through a comprehensive multi-omics approach

The genomic era has resulted in the generation of a massive amount of genetic data concerning the genomic diversity of bacterial taxa. As a result, the microbiological community is increasingly looking for ways to define reference bacterial strains to perform experiments that are representative of the entire bacterial species. Despite this, there is currently no established approach allowing a reliable identification of reference strains based on a comprehensive genomic, ecological, and functional context. In the current study, we developed a comprehensive multi-omics approach that will allow the identification of the optimal reference strains using the Bifidobacterium genus as test case. Strain tracking analysis based on 1664 shotgun metagenomics datasets of healthy infant faecal samples were employed to identify bifidobacterial strains suitable for in silico and in vitro analyses. Subsequently, an ad hoc bioinformatic tool was developed to screen local strain collections for the most suitable species-representative strain alternative. The here presented approach was validated using in vitro trials followed by metagenomics and metatranscriptomics analyses. Altogether, these results demonstrated the validity of the proposed model for reference strain selection, thus allowing improved in silico and in vitro investigations both in terms of cross-laboratory reproducibility and relevance of research findings.

Metagenomic features of bioburden serve as outcome indicators in combat extremity wounds

Battlefield injury management requires specialized care, and wound infection is a frequent complication. Challenges related to characterizing relevant pathogens further complicates treatment. Applying metagenomics to wounds offers a comprehensive path toward assessing microbial genomic fingerprints and could indicate prognostic variables for future decision support tools. Wound specimens from combat-injured U.S. service members, obtained during surgical debridements before delayed wound closure, were subjected to whole metagenome analysis and targeted enrichment of antimicrobial resistance genes. Results did not indicate a singular, common microbial metagenomic profile for wound failure, instead reflecting a complex microenvironment with varying bioburden diversity across outcomes. Genus-level Pseudomonas detection was associated with wound failure at all surgeries. A logistic regression model was fit to the presence and absence of antimicrobial resistance classes to assess associations with nosocomial pathogens. A. baumannii detection was associated with detection of genomic signatures for resistance to trimethoprim, aminoglycosides, bacitracin, and polymyxin. Machine learning classifiers were applied to identify wound and microbial variables associated with outcome. Feature importance rankings averaged across models indicated the variables with the largest effects on predicting wound outcome, including an increase in P. putida sequence reads. These results describe the microbial genomic determinants in combat wound bioburden and demonstrate metagenomic investigation as a comprehensive tool for providing information toward aiding treatment of combat-related injuries.

Genetic insights into the dark matter of the mammalian gut microbiota through targeted genome reconstruction

Whole metagenomic shotgun (WMS) sequencing has dramatically enhanced our ability to study microbial genomics. The possibility to unveil the genetic makeup of bacteria that cannot be easily isolated has significantly expanded our microbiological horizon. Here, we report an approach aimed at uncovering novel bacterial species by the use of targeted WMS sequencing. Employing in silico data retrieved from metabolic modelling to formulate a chemically defined medium (CDM), we were able to isolate and subsequently sequence the genomes of six putative novel species of bacteria from the gut of non‐human primates.

Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment

Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.

Longitudinal Investigation of the Gut Microbiota in Goat Kids from Birth to Postweaning

Early microbial colonization in the gut impacts animal performance and lifelong health. However, research on gut microbial colonization and development in young ruminants, especially after weaning, is currently limited. In this study, next-generation sequencing technology was performed to investigate the temporal dynamic changes of the microbial community in the jejunum and colon of goats at 1, 7, 14, 28, 42, 56, 70, and 84 days (d) of age. As age increased, significant increases in microbial diversity, including the number of Observed OTUs and the Shannon Index, were observed in both the jejunum and colon. Regarding beta diversity, significant shifts in community membership and structure from d1 to d84 were observed based on both Bray–Curtis and Jaccard distances. With increasing age, dominant genera in the jejunum shifted from Lactobacillus to unclassified Ruminococcaceae, unclassified Lachnospiraceae and unclassified Clostridiales through starter supplementation, whereas colonic dominant genera changed from Lactobacillus and Butyricicoccus, within d1–d28, to unclassified Ruminococcaceae, unclassified Clostridiales and Campylobacter after solid diet supplementation. The linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed bacterial features that are stage-specific in the jejunum and colon, respectively. In the jejunum and colon, a significantly distinct structure and membership of the microbiota was observed across all ages. The growth stage-associated microbiota in each gut compartment was also identified as a marker for biogeography. Our data indicate the temporal and spatial differences of the gut microbiota in goats are important for their performance and health. Early microbial colonization can influence microbial composition in later life (e.g., post-weaning phase). This study provides insights that the temporal dynamics of gut microbiota development from newborn to post-weaning can aid in developing feeding strategies to improve goat health and production.