Whole-metagenome Shotgun Sequencing Research Articles

Characterizations of gut bacteriome, mycobiome, and virome of healthy individuals living in sea-level and high-altitude areas.

The contribution of gut microbiota to human high-altitude adaptation remains inadequatelyunderstood. Here a comparative analysis of gut microbiota was conducted between healthy individuals living at sealevel and high altitude using deep whole-metagenome shotgun sequencing, to investigate the adaptivemechanisms of gut microbiota in plateau inhabitants. The results showed the gut bacteriomes in high-altitude individuals exhibited greater within-samplediversity and significant alterations in both bacterial compositional and functional profiles when compared to thoseof sea-level individuals, indicating the potential selection of unique bacteria associated with high-altitudeenvironments. The strain-level investigation revealed enrichment of Collinsella aerofaciens and Akkermansiamuciniphila in high-altitude populations. The characteristics of gut virome and gut mycobiome were alsoinvestigated. Compared to sea-level subjects, high-altitude subjects exhibited a greater diversity in their gut virome,with an increased number of viral operational taxonomic units (vOTUs) and unique annotated genes. Finally,correlation analyses revealed 819 significant correlations between 42 bacterial species and 375 vOTUs, while nosignificant correlations were observed between bacteria and fungi or between fungi and viruses. The findings have significantly contributed to an enhanced comprehension of the mechanismsunderlying the high-altitude geographic adaptation of the human gut microbiota.

Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis

Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential pathobionts, and host metabolome in individuals with AP remains elusive. Hence, we employed fecal whole-metagenome shotgun sequencing in 82 AP patients and 115 matched healthy controls, complemented by untargeted serum metabolome and lipidome profiling in a subset of participants. Analyses of the gut microbiome in AP patients revealed reduced diversity, disrupted microbial functions, and altered abundance of 77 species, influenced by both etiology and severity. AP-enriched species, mostly potential pathobionts, correlated positively with host liver function and serum lipid indicators. Conversely, many AP-depleted species were short-chain fatty acid producers. Gut microflora changes were accompanied by shifts in the serum metabolome and lipidome. Specifically, certain gut species, like enriched Bilophila wadsworthia and depleted Bifidobacterium spp., appeared to contribute to elevated triglyceride levels in biliary or hyperlipidemic AP patients. Through culturing and whole-genome sequencing of bacterial isolates, we identified virulence factors and clinically relevant antibiotic resistance in patient-derived strains, suggesting a predisposition to opportunistic infections. Finally, our study demonstrated that gavage of specific pathobionts could exacerbate pancreatitis in a caerulein-treated mouse model. In conclusion, our comprehensive analysis sheds light on the gut microbiome and serum metabolome in AP, elucidating the role of pathobionts in disease progression. These insights offer valuable perspectives for etiologic diagnosis, prevention, and intervention in AP and related conditions.

Comparative analysis of the vaginal bacteriome and virome in healthy women living in high-altitude and sea-level areas

The vaginal microbiota plays an important role in the health of the female reproductive tract and is closely associated with various pregnancy outcomes and sexually transmitted diseases. Plenty of internal and external factors have strong influence on the changes in a woman's vaginal microbiome. However, the effect of a high-altitude on female vaginal microbiota has not been described. In this study, we characterized the vaginal bacteriome and virome of 13 and 34 healthy women living in high-altitude and sea-level areas, using whole-metagenome shotgun sequencing of their vaginal mucus samples. The results revealed that the vaginal bacteriomes of high-altitude individuals are featured by a significant increase of species diversity, depletion of Lactobacillus crispatus, and more abundant of some anaerobic bacteria, such as Chlamydia trachomatis, Mageeibacillus indolicus, Dialister micraerophilus, and Sneathia amnii). In addition, the vagina samples of sea-level subjects harbor more Lactobacillus strains, whereas the anaerobic bacteroidetes strains mostly appeared in high-altitude subjects. Identified and assembled 191 virus operational taxonomic units (vOTUs), there were significant differences in the abundance of 107 vOTUs between the two groups. Together, the results of this study raised the understanding of bacteriome and virome in the vagina of women at different elevations, and demonstrated that the vaginal microbiome is related to the high-altitude geographic adaptation.

Associations of central obesity and habitual food consumption with saliva microbiota and its enzymatic profiles - a pilot study in Finnish children.

Variation in diversity and composition of saliva microbiota has been linked to weight status, but findings have been inconsistent. Focusing on clinically relevant conditions such as central obesity and using advanced sequencing techniques might fill in the gaps of knowledge. We investigated saliva microbiota with shallow metagenome sequencing in children with (n = 14) and without (n = 36) central obesity. Additionally, we examined the role of habitual food consumption on microbial enzymatic repertoire. Data comprised 50 children (50% male) with a mean age of 14.2 (SD 0.3) years, selected from the Finnish Health in Teens (Fin-HIT) cohort. Dietary scores for consumption frequency of sweet treats (STI), dairy products (DCI) and plants (PCI) were derived based on a self-administered food frequency questionnaire. Central obesity was defined based on waist-height ratio using the cut-off 0.5. Saliva samples were subjected to whole-metagenome shotgun sequencing, and taxonomic and functional profiling was achieved with METAnnotatorX2 bioinformatics platform. Groups had an average 20 (95% CI 14-27) cm difference in waist circumference. We identified the lack of Pseudomonas guguagenesis and Prevotella scopos, oulorum and oris as putative biomarkers associated with central obesity and observed a total of 16 enzymatic reactions differing between the groups. DCI was associated with the highest number of enzyme profiles (122), followed by STI (60) and DCI (25) (Pearson correlation p < 0.05). Intriguingly, STI showed a high positive/negative correlation ratio (5.09), while DCI and PCI showed low ratios (0.54 and 0.33, respectively). Thus, the main driver of enzymatic reactions was STI, and the related pathways involved nitrate metabolism induced by Haemophilus parainfluenzae and Veilonella dispar among others. Clinically relevant differences in central obesity were only modestly reflected in the composition of saliva microbiota. Habitual consumption of sweet treats was a strong determinant of enzymatic reactions of saliva microbiota in children with and without central obesity. The clinical relevance of these findings warrants further studies.

Characterizations of the multi-kingdom gut microbiota in Chinese patients with gouty arthritis

ObjectiveThe gut microbial composition has been linked to metabolic and autoimmune diseases, including arthritis. However, there is a dearth of knowledge on the gut bacteriome, mycobiome, and virome in patients with gouty arthritis (GA).MethodsWe conducted a comprehensive analysis of the multi-kingdom gut microbiome of 26 GA patients and 28 healthy controls, using whole-metagenome shotgun sequencing of their stool samples.ResultsProfound alterations were observed in the gut bacteriome, mycobiome, and virome of GA patients. We identified 1,117 differentially abundant bacterial species, 23 fungal species, and 4,115 viral operational taxonomic units (vOTUs). GA-enriched bacteria included Escherichia coli_D GENOME144544, Bifidobacterium infantis GENOME095938, Blautia_A wexlerae GENOME096067, and Klebsiella pneumoniae GENOME147598, while control-enriched bacteria comprised Faecalibacterium prausnitzii_G GENOME147678, Agathobacter rectalis GENOME143712, and Bacteroides_A plebeius_A GENOME239725. GA-enriched fungi included opportunistic pathogens like Cryptococcus neoformans GCA_011057565, Candida parapsilosis GCA_000182765, and Malassezia spp., while control-enriched fungi featured several Hortaea werneckii subclades and Aspergillus fumigatus GCA_000002655. GA-enriched vOTUs mainly attributed to Siphoviridae, Myoviridae, Podoviridae, and Microviridae, whereas control-enriched vOTUs spanned 13 families, including Siphoviridae, Myoviridae, Podoviridae, Quimbyviridae, Phycodnaviridae, and crAss-like. A co-abundance network revealed intricate interactions among these multi-kingdom signatures, signifying their collective influence on the disease. Furthermore, these microbial signatures demonstrated the potential to effectively discriminate between patients and controls, highlighting their diagnostic utility.ConclusionsThis study yields crucial insights into the characteristics of the GA microbiota that may inform future mechanistic and therapeutic investigations.

Diagnosis of Crohn’s disease and ulcerative colitis using the microbiome

BackgroundInflammatory bowel disease (IBD) is a multifactorial chronic inflammatory disease resulting from dysregulation of the mucosal immune response and gut microbiota. Crohn's disease (CD) and ulcerative colitis (UC) are difficult to distinguish, and differential diagnosis is essential for establishing a long-term treatment plan for patients. Furthermore, the abundance of mucosal bacteria is associated with the severity of the disease. This study aimed to differentiate and diagnose these two diseases using the microbiome and identify specific biomarkers associated with disease activity.ResultsDifferences in the abundance and composition of the microbiome between IBD patients and healthy controls (HC) were observed. Compared to HC, the diversity of the gut microbiome in patients with IBD decreased; the diversity of the gut microbiome in patients with CD was significantly lower. Sixty-eight microbiota members (28 for CD and 40 for UC) associated with these diseases were identified. Additionally, as the disease progressed through different stages, the diversity of the bacteria decreased. The abundances of Alistipes shahii and Pseudodesulfovibrio aespoeensis were negatively correlated with the severity of CD, whereas the abundance of Polynucleobacter wianus was positively correlated. The severity of UC was negatively correlated with the abundance of A. shahii, Porphyromonas asaccharolytica and Akkermansia muciniphilla, while it was positively correlated with the abundance of Pantoea candidatus pantoea carbekii. A regularized logistic regression model was used for the differential diagnosis of the two diseases. The area under the curve (AUC) was used to examine the performance of the model. The model discriminated UC and CD at an AUC of 0.873 (train set), 0.778 (test set), and 0.633 (validation set) and an area under the precision-recall curve (PRAUC) of 0.888 (train set), 0.806 (test set), and 0.474 (validation set).ConclusionsBased on fecal whole-metagenome shotgun (WMS) sequencing, CD and UC were diagnosed using a machine-learning predictive model. Microbiome biomarkers associated with disease activity (UC and CD) are also proposed.

The Human Ocular Surface Microbiome and Its Associations with the Tear Proteome in Dry Eye Disease.

Although dry eye disease (DED) is one of the most common ocular surface diseases worldwide, its pathogenesis is incompletely understood, and treatment options are limited. There is growing evidence that complex interactions between the ocular surface microbiome (OSM) and tear fluid constituents, potentially leading to inflammatory processes, are associated with ocular surface diseases such as DED. In this study, we aimed to find unique compositional and functional features of the OSM associated with human and microbial tear proteins in patients with DED. Applying whole-metagenome shotgun sequencing of forty lid and conjunctival swabs, we identified 229 taxa, with Actinobacteria and Proteobacteria being the most abundant phyla and Propionibacterium acnes the dominating species in the cohort. When DED patients were compared to controls, the species Corynebacterium tuberculostearicum was more abundant in conjunctival samples, whereas the family Propionibacteriaceae was more abundant in lid samples. Functional analysis showed that genes of L-lysine biosynthesis, tetrapyrrole biosynthesis, 5-aminoimidazole ribonucleotide biosynthesis, and the super pathway of L-threonine biosynthesis were enriched in conjunctival samples of controls. The relative abundances of Acinetobacter johnsonii correlated with seven human tear proteins, including mucin-16. The three most abundant microbial tear proteins were the chaperone protein DnaK, the arsenical resistance protein ArsH, and helicase. Compositional and functional features of the OSM and the tear proteome are altered in patients with DED. Ultimately, this may help to design novel interventional therapeutics to target DED.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome.

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes. Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2. The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied. The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

Microbiome of Ceca from Broiler Chicken Vaccinated or Not against Coccidiosis and Fed Berry Pomaces.

American cranberry (Vaccinium macrocarpon) and lowbush/wild blueberry (V. angustifolium) pomace are polyphenol-rich products having potentially beneficial effects in broiler chickens. This study investigated the cecal microbiome of broiler-vaccinated or non-vaccinated birds against coccidiosis. Birds in each of the two groups (vaccinated or non-vaccinated) were fed a basal non-supplemented diet (NC), a basal diet supplemented with bacitracin (BAC), American cranberry (CP), and lowbush blueberry (BP) pomace alone or in combination (CP + BP). At 21 days of age, cecal DNA samples were extracted and analyzed using both whole-metagenome shotgun sequencing and targeted-resistome sequencing approaches. Ceca from vaccinated birds showed a lower abundance of Lactobacillus and a higher abundance of Escherichia coli than non-vaccinated birds (p < 0.05). The highest and lowest abundance of L. crispatus and E. coli, respectively, were observed in birds fed CP, BP, and CP + BP compared to those from NC or BAC treatments (p < 0.05). Coccidiosis vaccination affected the abundance of virulence genes (VGs) related to adherence, flagella, iron utilization, and secretion system. Toxin-related genes were observed in vaccinated birds (p < 0.05) in general, with less prevalence in birds fed CP, BP, and CP + BP than NC and BAC (p < 0.05). More than 75 antimicrobial resistance genes (ARGs) detected by the shotgun metagenomics sequencing were impacted by vaccination. Ceca from birds fed CP, BP, and CP + BP showed the lowest (p < 0.05) abundances of ARGs related to multi-drug efflux pumps, modifying/hydrolyzing enzyme and target-mediated mutation, when compared to ceca from birds fed BAC. Targeted metagenomics showed that resistome from BP treatment was distant to other groups for antimicrobials, such as aminoglycosides (p < 0.05). Significant differences in the richness were observed between the vaccinated and non-vaccinated groups for aminoglycosides, β-lactams, lincosamides, and trimethoprim resistance genes (p < 0.05). Overall, this study demonstrated that dietary berry pomaces and coccidiosis vaccination significantly impacted cecal microbiota, virulome, resistome, and metabolic pathways in broiler chickens.

The root canal microbiome diversity and function. A whole-metagenome shotgun analysis.

To evaluate the root canal microbiome composition and bacterial functional capability in cases of primary and secondary apical periodontitis utilizing whole-metagenome shotgun sequencing. Twenty-two samples from patients with primary root canal infections, and 18 samples obtained from previously treated teeth currently diagnosed with apical periodontitis were analysed with whole-metagenome shotgun sequencing at a depth of 20 M reads. Taxonomic and functional gene annotations were made using MetaPhlAn3 and HUMAnN3 software. The Shannon and Chao1 indices were utilized to measure alpha diversity. Differences in community composition were evaluated utilizing analysis of similarity (ANOSIM) using Bray-Curtis dissimilarities. The Wilcoxon rank sum test was used to compare differences in taxa and functional genes. Microbial community variations within a community were significantly lower in secondary relative to primary infections (alpha diversity p = .001). Community composition was significantly different in primary versus secondary infection (R = .11, p = .005). The predominant taxa observed among samples (>2.5%) were Pseudopropionibacterium propionicum, Prevotella oris, Eubacterium infirmum, Tannerella forsythia, Atopobium rimae, Peptostreptococcus stomatis, Bacteroidetes bacterium oral taxon 272, Parvimonas micra, Olsenella profusa, Streptococcus anginosus, Lactobacillus rhamnosus, Porphyromonas endodontalis, Pseudoramibacter alactolyticus, Fusobacterium nucleatum, Eubacterium brachy and Solobacterium moorei. The Wilcoxon rank test revealed no significant differences in relative abundances of functional genes in both groups. Genes with greater relative abundances (top 25) were associated with genetic, signalling and cellular processes including the iron and peptide/nickel transport system. Numerous genes encoding toxins were identified: exfoliative toxin, haemolysins, thiol-activated cytolysin, phospholipase C, cAMP factor, sialidase, and hyaluronic glucosaminidase. Despite taxonomic differences between primary and secondary apical periodontitis, the functional capability of the microbiomes was similar.

Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods

BackgroundWith the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample’s metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods.ResultA targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition.ConclusionsFor metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.

In Vitro Modelling of Oral Microbial Invasion in the Human Colon.

Recent advances in the human microbiome characterization have revealed significant oral microbial detection in stools of dysbiotic patients. However, little is known about the potential interactions of these invasive oral microorganisms with commensal intestinal microbiota and the host. In this proof-of-concept study, we proposed a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Oral invasion of the intestinal microbiota was simulated by injection of enriched saliva in the in vitro colon model inoculated with a fecal sample from the same healthy adult donor. The mucosal compartment of M-ARCOL was able to retain the highest species richness levels over time, while species richness levels decreased in the luminal compartment. This study also showed that oral microorganisms preferably colonized the mucosal microenvironment, suggesting potential oral-to-intestinal mucosal competitions. This new model of oral-to-gut invasion can provide useful mechanistic insights into the role of oral microbiome in various disease processes. IMPORTANCE Here, we propose a new model of oral-to-gut invasion by the combined use of an in vitro model simulating both the physicochemical and microbial (lumen- and mucus-associated microbes) parameters of the human colon (M-ARCOL), a salivary enrichment protocol, and whole-metagenome shotgun sequencing. Our study revealed the importance of integrating the mucus compartment, which retained higher microbial richness during fermentation, showed the preference of oral microbial invaders for the mucosal resources, and indicated potential oral-to-intestinal mucosal competitions. It also underlined promising opportunities to further understand mechanisms of oral invasion into the human gut microbiome, define microbe-microbe and mucus-microbe interactions in a compartmentalized fashion, and help to better characterize the potential of oral microbial invasion and their persistence in the gut.

BADASS: BActeriocin-Diversity ASsessment Software

BackgroundBacteriocins are defined as thermolabile peptides produced by bacteria with biological activity against taxonomically related species. These antimicrobial peptides have a wide application including disease treatment, food conservation, and probiotics. However, even with a large industrial and biotechnological application potential, these peptides are still poorly studied and explored. BADASS is software with a user-friendly graphical interface applied to the search and analysis of bacteriocin diversity in whole-metagenome shotgun sequencing data.ResultsThe search for bacteriocin sequences is performed with tools such as BLAST or DIAMOND using the BAGEL4 database as a reference. The putative bacteriocin sequences identified are used to determine the abundance and richness of the three classes of bacteriocins. Abundance is calculated by comparing the reads identified as bacteriocins to the reads identified as 16S rRNA gene using SILVA database as a reference. BADASS has a complete pipeline that starts with the quality assessment of the raw data. At the end of the analysis, BADASS generates several plots of richness and abundance automatically as well as tabular files containing information about the main bacteriocins detected. The user is able to change the main parameters of the analysis in the graphical interface. To demonstrate how the software works, we used four datasets from WMS studies using default parameters. Lantibiotics were the most abundant bacteriocins in the four datasets. This class of bacteriocin is commonly produced by Streptomyces sp.ConclusionsWith a user-friendly graphical interface and a complete pipeline, BADASS proved to be a powerful tool for prospecting bacteriocin sequences in Whole-Metagenome Shotgun Sequencing (WMS) data. This tool is publicly available at https://sourceforge.net/projects/badass/.

The role of the gut microbiome in eye diseases.

The gut microbiome is a complex ecosystem of microorganisms and their genetic entities colonizing the gastrointestinal tract. When in balanced composition, the gut microbiome is in symbiotic interaction with its host and maintains intestinal homeostasis. It is involved in essential functions such as nutrient metabolism, inhibition of pathogens and regulation of immune function. Through translocation of microbes and their metabolites along the epithelial barrier, microbial dysbiosis induces systemic inflammation that may lead to tissue destruction and promote the onset of various diseases. Using whole-metagenome shotgun sequencing, several studies have shown that the composition and associated functional capacities of the gut microbiome are associated with age-related macular degeneration, retinal artery occlusion, central serous chorioretinopathy and uveitis. In this review, we provide an overview of the current knowledge about the gut microbiome in eye diseases, with a focus on interactions between the microbiome, specific microbial-derived metabolites and the immune system. We explain how these interactions may be involved in the pathogenesis of age-related macular degeneration, retinal artery occlusion, central serous chorioretinopathy and uveitis and guide the development of new therapeutic approaches by microbiome-altering interventions for these diseases.

Analyzing Predominant Bacterial Species and Potential Short-Chain Fatty Acid-Associated Metabolic Routes in Human Gut Microbiome Using Integrative Metagenomics.

Gut microbiome plays an essential role in host health, and there is interest in utilizing diet to modulate the composition and function of microbial communities. Copra meal hydrolysate (CMH) is commonly used as a natural additive to enhance health. However, the gut microbiome is largely unknown at species level and is associated with metabolic routes involving short-chain fatty acids (SCFAs). In this study, we aimed to analyze, using integrative metagenomics, the predominant species and metabolic routes involved in SCFAs production in the human gut microbiome after treatment with CMH. The effect of CMH treatment on the Thai gut microbiome was demonstrated using 16S rRNA genes with whole-metagenome shotgun (WMGS) sequencing technology. Accordingly, these results revealed that CMH has potentially beneficial effects on the gut microbiome. Twelve predominant bacterial species, as well as their potential metabolic routes, were involved in cooperative microbiome networks under sugar utilization (e.g., glucose, mannose, or xylose) and energy supply (e.g., NADH and ATP) in relation to SCFAs biosynthesis. These findings suggest that CMH may be used as a potential prebiotic diet for modulating and maintaining the gut microbiome. To our knowledge, this is the first study to reveal the predominant bacterial species and metabolic routes in the Thai gut microbiome after treatment with potential prebiotics.

Meta-analysis of sputum microbiome studies identifies airway disease-specific taxonomic and functional signatures.

Introduction. Studying taxonomic and functional signatures of respiratory microbiomes provide a better understanding of airway diseases.Gap Statement. Several human airway metagenomics studies have identified taxonomic and functional features restricted to a single disease condition and the findings are not comparable across airway diseases due to use of different samples, NGS platforms, and bioinformatics databases and tools.Aim. To study the microbial taxonomic and functional components of sputum microbiome across airway diseases and healthy smokers.Methodology. Here, 57 whole metagenome shotgun sequencing (WMSS) runs coming from the sputum of five airway diseases: asthma, bronchiectasis, chronic obstructive pulmonary diseases (COPD), cystic fibrosis (CF), tuberculosis (TB), and healthy smokers as the control were reanalysed using a common WMSS analysis pipeline.Results. Shannon's index (alpha diversity) of the healthy smoker group was the highest among all. The beta diversity showed that the sputum microbiome is distinct in major airway diseases such as asthma, COPD and cystic fibrosis. The microbial composition based on differential analysis showed that there are specific markers for each airway disease like Acinetobacter bereziniae as a marker for COPD and Achromobacter xylosoxidans as a marker of cystic fibrosis. Pathways and metabolites identified from the sputum microbiome of these five diseases and healthy smokers also show specific markers. 'ppGpp biosynthesis' and 'purine ribonucleosides degradation' pathways were identified as differential markers for bronchiectasis and COPD. In this meta-analysis, besides bacteria kingdom, Aspergillus fumigatus was detected in asthma and COPD, and Roseolovirus human betaherpesvirus 7 was detected in COPD. Our analysis showed that the majority of the gene families specific to the drug-resistant associated genes were detected from opportunistic pathogens across all the groups.Conclusion. In summary, the specific species in the sputum of airway diseases along with the microbial features like specific gene families, pathways, and metabolites were identified which can be explored for better diagnosis and therapy.

Characterizations of the Gut Bacteriome, Mycobiome, and Virome in Patients with Osteoarthritis.

The gut microbiota plays an essential role in the regulation of the immune system and the etiology of human autoimmune diseases. However, a holistic understanding of the gut bacteriome, mycobiome, and virome in patients with osteoarthritis (OA) remains lacking. Here, we explored the gut microbiotas of 44 OA patients and 46 healthy volunteers via deep whole-metagenome shotgun sequencing of their fecal samples. The gut bacteriome and mycobiome were analyzed using a reference-based strategy. Gut viruses were identified from the metagenomic assembled contigs, and the gut virome was profiled based on 6,567 nonredundant viral operational taxonomic units (vOTUs). We revealed that the gut microbiome (including bacteriome, mycobiome, and virome) of OA patients is fundamentally altered, characterized by a panel of 279 differentially abundant bacterial species, 10 fungal species, and 627 vOTUs. The representative OA-enriched bacteria included Anaerostipes hadrus (GENOME147149), Prevotella sp900313215 (GENOME08259), Eubacterium_E hallii (GENOME000299), and Blautia A (GENOME001004), while Bacteroides plebeius A (GENOME239725), Roseburia inulinivorans (GENOME 001770), Dialister sp900343095 (GENOME075103), Phascolarctobacterium faecium (GENOME233517), and several members of Faecalibacterium and Prevotella were depleted in OA patients. Fungi such as Debaryomyces fabryi (GenBank accession no. GCA_003708665), Candida parapsilosis (GCA_000182765), and Apophysomyces trapeziformis (GCA_000696975) were enriched in the OA gut microbiota, and Malassezia restricta (GCA_003290485), Aspergillus fumigatus (GCA_003069565), and Mucor circinelloides (GCA_010203745) were depleted. The OA-depleted viruses spanned Siphoviridae (95 vOTUs), Myoviridae (70 vOTUs), and Microviridae (5 vOTUs), while 30 Siphoviridae vOTUs were enriched in OA patients. Functional analysis of the gut bacteriome and virome also uncovered their functional signatures in relation to OA. Moreover, we demonstrated that the OA-associated gut bacterial and viral signatures are tightly interconnected, suggesting that they may impact disease together. Finally, we showed that the multikingdom signatures are effective in discriminating the OA patients from healthy controls, suggesting the potential of gut microbiota for the prediction of OA and related diseases. Our results delineated the fecal bacteriome, mycobiome, and virome landscapes of the OA microbiota and provided biomarkers that will aid in future mechanistic and clinical intervention studies. IMPORTANCE The gut microbiome of OA patients was completely altered compared to that in healthy individuals, including 279 differentially abundant bacterial species, 10 fungal species and 627 viral operational taxonomic units (vOTUs). Functional analysis of the gut bacteriome and virome also revealed their functional signatures in relation to OA. We found that OA-associated gut bacterial and viral signatures were tightly interconnected, indicating that they may affect the disease together. The OA patients can be discriminated effectively from healthy controls using the multikingdom signatures, suggesting the potential of gut microbiota for the prediction of OA and related diseases.

Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes

Coronavirus disease 2019 (COVID-19), primarily a respiratory disease caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is often accompanied by gastrointestinal symptoms. However, little is known about the relation between the human microbiome and COVID-19, largely due to the fact that most previous studies fail to provide high taxonomic resolution to identify microbes that likely interact with SARS-CoV-2 infection. Here we used whole-metagenome shotgun sequencing data together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from 514 COVID-19 related nasopharyngeal and fecal samples in six independent cohorts. We reconstructed a total of 11,584 medium-and high-quality microbial MAGs and obtained 5403 non-redundant MAGs (nrMAGs) with strain-level resolution. We found that there is a significant reduction of strain richness for many species in the gut microbiome of COVID-19 patients. The gut microbiome signatures can accurately distinguish COVID-19 cases from healthy controls and predict the progression of COVID-19. Moreover, we identified a set of nrMAGs with a putative causal role in the clinical manifestations of COVID-19 and revealed their functional pathways that potentially interact with SARS-CoV-2 infection. Finally, we demonstrated that the main findings of our study can be largely validated in three independent cohorts. The presented results highlight the importance of incorporating the human gut microbiome in our understanding of SARS-CoV-2 infection and disease progression.

Butyrate-Producing Bacteria and Insulin Homeostasis: The Microbiome and Insulin Longitudinal Evaluation Study (MILES).

Gut microbiome studies have documented depletion of butyrate-producing taxa in type 2 diabetes. We analyzed associations between butyrate-producing taxa and detailed measures of insulin homeostasis, whose dysfunction underlies diabetes in 224 non-Hispanic Whites and 129 African Americans, all of whom completed an oral glucose tolerance test. Stool microbiome was assessed by whole-metagenome shotgun sequencing with taxonomic profiling. We examined associations among 36 butyrate-producing taxa (n = 7 genera and 29 species) and insulin sensitivity, insulin secretion, disposition index, insulin clearance, and prevalence of dysglycemia (prediabetes plus diabetes, 46% of cohort), adjusting for age, sex, BMI, and race. The genus Coprococcus was associated with higher insulin sensitivity (β = 0.14; P = 0.002) and disposition index (β = 0.12; P = 0.012) and a lower rate of dysglycemia (odds ratio [OR] 0.91; 95% CI 0.85-0.97; P = 0.0025). In contrast, Flavonifractor was associated with lower insulin sensitivity (β = -0.13; P = 0.004) and disposition index (β = -0.11; P = 0.04) and higher prevalence of dysglycemia (OR 1.22; 95% CI 1.08-1.38; P = 0.0013). Species-level analyses found 10 bacteria associated with beneficial directions of effects and two bacteria with adverse associations on insulin homeostasis and dysglycemia. Although most butyrate producers analyzed appear to be metabolically beneficial, this is not the case for all such bacteria, suggesting that microbiome-directed therapeutic measures to prevent or treat diabetes should be targeted to specific butyrate-producing taxa rather than all butyrate producers.

Strategies for the Identification and Assessment of Bacterial Strains with Specific Probiotic Traits.

Early in the 1900s, it was proposed that health could be improved and senility delayed by manipulating gut microbiota with the host-friendly bacteria found in yogurt. Later, in 1990, the medical community reconsidered this idea and today probiotics represent a developed area of research with a billion-dollar global industry. As a result, in recent decades, increased attention has been paid to the isolation and characterization of novel probiotic bacteria from fermented foods and dairy products. Most of the identified probiotic strains belong to the lactic acid bacteria group and the genus Bifidobacterium. However, current molecular-based knowledge has allowed the identification and culture of obligatory anaerobic commensal bacteria from the human gut, such as Akkermansia spp. and Faecalibacterium spp., among other human symbionts. We are aware that the identification of new strains of these species does not guarantee their probiotic effects and that each effect must be proved through in vitro and in vivo preclinical studies before clinical trials (before even considering it as a probiotic strain). In most cases, the identification and characterization of new probiotic strain candidates may lack the appropriate set of in vitro experiments allowing the next assessment steps. Here, we address some innovative strategies reported in the literature as alternatives to classical characterization: (i) identification of alternatives using whole-metagenome shotgun sequencing, metabolomics, and multi-omics analysis; and (ii) probiotic characterization based on molecular effectors and/or traits to target specific diseases (i.e., inflammatory bowel diseases, colorectal cancer, allergies, among others).