Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

A serum-induced gene signature in hepatocytes is associated with pediatric nonalcoholic fatty liver disease.

OBJECTIVE: Pediatric nonalcoholic fatty liver disease (NAFLD) is a growing problem, but its underlying mechanisms are poorly understood. We used transcriptomic reporter cell assays to investigate differences in transcriptional signatures induced in hepatocyte reporter cells by the sera of children with and without NAFLD. METHODS: We studied serum samples from 45 children with NAFLD and 28 children without NAFLD. The sera were used to induce gene expression in cultured HepaRG cells and RNA-sequencing was used to determine gene expression. Computational techniques were used to compare gene expression patterns. RESULTS: Sera from children with NAFLD induced the expression of 195 genes that were significantly differentially expressed in hepatocytes compared to controls with obesity. NAFLD was associated with increased expression of genes promoting inflammation, collagen synthesis, and extracellular matrix remodeling. Additionally, there was lower expression of genes involved in endobiotic and xenobiotic metabolism, and downregulation of peroxisome function, oxidative phosphorylation, and xenobiotic, bile acid, and fatty acid metabolism. A 13-gene signature, including upregulation of TREM1 and MMP1 and downregulation of CYP2C9, was consistently associated with all diagnostic categories of pediatric NAFLD. CONCLUSION: The extracellular milieu of sera from children with NAFLD induced specific gene profiles distinguishable by a hepatocyte reporter system. Circulating factors may contribute to inflammation and extracellular matrix remodeling and impair xenobiotic and endobiotic metabolism in pediatric NAFLD.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study Highlights: The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Exploratory studies of oral and fecal microbiome in healthy human aging.

Growing evidence has linked an altered host fecal microbiome composition with health status, common chronic diseases, and institutionalization in vulnerable older adults. However, fewer studies have described microbiome changes in healthy older adults without major confounding diseases or conditions, and the impact of aging on the microbiome across different body sites remains unknown. Using 16S ribosomal RNA gene sequencing, we reconstructed the composition of oral and fecal microbiomes in young (23-32; mean = 25 years old) and older (69-94; mean = 77 years old) healthy community-dwelling research subjects. In both body sites, we identified changes in minor bacterial operational taxonomic units (OTUs) between young and older subjects. However, the composition of the predominant bacterial species of the healthy older group in both microbiomes was not significantly different from that of the young cohort, which suggests that dominant bacterial species are relatively stable with healthy aging. In addition, the relative abundance of potentially pathogenic genera, such as Rothia and Mycoplasma, was enriched in the oral microbiome of the healthy older group relative to the young cohort. We also identified several OTUs with a prevalence above 40% and some were more common in young and others in healthy older adults. Differences with aging varied for oral and fecal samples, which suggests that members of the microbiome may be differentially affected by aging in a tissue-specific fashion. This is the first study to investigate both oral and fecal microbiomes in the context of human aging, and provides new insights into interactions between aging and the microbiome within two different clinically relevant sites.

Skin Microbiome Variation with Cancer Progression in Human Cutaneous Squamous Cell Carcinoma.

The skin microbiome plays a critical role in skin homeostasis and disorders. UVR is the major cause of nonmelanoma skin cancer, but other risk factors, including immune suppression, chronic inflammation, and antibiotic usage, suggest the microbiome as an additional, unexplored risk factor and potential disease biomarker. The overarching goal was to study the skin microbiome in squamous cell carcinoma (SCC) and premalignant actinic keratosis compared with that in healthy skin to identify skin cancer‒associated changes in the skin microbiome. We performed a high-resolution analysis of shotgun metagenomes of actinic keratosis and SCC in healthy skin, revealing the microbial community shifts specific to actinic keratosis and SCC. Most prominently, the relative abundance of pathobiont Staphylococcus aureus was increased at the expense of commensal Cutibacterium acnes in SCC compared with that in healthy skin, and enrichment of functional pathways in SCC reflected this shift. Notably, C. acnes associated with lesional versus healthy skin differed at the strain level, suggesting the specific functional changes associated with its depletion in SCC. Our study revealed a transitional microbial dysbiosis from healthy skin to actinic keratosis to SCC, supporting further investigation of the skin microbiome for use as a biomarker and providing hypotheses for studies investigating how these microbes might influence skin cancer progression.

Metagenomics: a path to understanding the gut microbiome.

The gut microbiome is a major determinant of host health, yet it is only in the last 2 decades that the advent of next-generation sequencing has enabled it to be studied at a genomic level. Shotgun sequencing is beginning to provide insight into the prokaryotic as well as eukaryotic and viral components of the gut community, revealing not just their taxonomy, but also the functions encoded by their collective metagenome. This revolution in understanding is being driven by continued development of sequencing technologies and in consequence necessitates reciprocal development of computational approaches that can adapt to the evolving nature of sequence datasets. In this review, we provide an overview of current bioinformatic strategies for handling metagenomic sequence data and discuss their strengths and limitations. We then go on to discuss key technological developments that have the potential to once again revolutionise the way we are able to view and hence understand the microbiome.

Longitudinal Analysis of Serum Cytokine Levels and Gut Microbial Abundance Links IL-17/IL-22 With Clostridia and Insulin Sensitivity in Humans.

Recent studies using mouse models suggest that interaction between the gut microbiome and IL-17/IL-22-producing cells plays a role in the development of metabolic diseases. We investigated this relationship in humans using data from the prediabetes study of the Integrated Human Microbiome Project (iHMP). Specifically, we addressed the hypothesis that early in the onset of metabolic diseases there is a decline in serum levels of IL-17/IL-22, with concomitant changes in the gut microbiome. Clustering iHMP study participants on the basis of longitudinal IL-17/IL-22 profiles identified discrete groups. Individuals distinguished by low levels of IL-17/IL-22 were linked to established markers of metabolic disease, including insulin sensitivity. These individuals also displayed gut microbiome dysbiosis, characterized by decreased diversity, and IL-17/IL-22-related declines in the phylum Firmicutes, class Clostridia, and order Clostridiales This ancillary analysis of the iHMP data therefore supports a link between the gut microbiome, IL-17/IL-22, and the onset of metabolic diseases. This raises the possibility for novel, microbiome-related therapeutic targets that may effectively alleviate metabolic diseases in humans as they do in animal models.

Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis.

The 16S rRNA gene has been a mainstay of sequence-based bacterial analysis for decades. However, high-throughput sequencing of the full gene has only recently become a realistic prospect. Here, we use in silico and sequence-based experiments to critically re-evaluate the potential of the 16S gene to provide taxonomic resolution at species and strain level. We demonstrate that targeting of 16S variable regions with short-read sequencing platforms cannot achieve the taxonomic resolution afforded by sequencing the entire (~1500 bp) gene. We further demonstrate that full-length sequencing platforms are sufficiently accurate to resolve subtle nucleotide substitutions (but not insertions/deletions) that exist between intragenomic copies of the 16S gene. In consequence, we argue that modern analysis approaches must necessarily account for intragenomic variation between 16S gene copies. In particular, we demonstrate that appropriate treatment of full-length 16S intragenomic copy variants has the potential to provide taxonomic resolution of bacterial communities at species and strain level.

Microbiome Signatures Associated With Steatohepatitis and Moderate to Severe Fibrosis in Children With Nonalcoholic Fatty Liver Disease.

BACKGROUND & AIMS: The intestinal microbiome might affect the development and severity of nonalcoholic fatty liver disease (NAFLD). We analyzed microbiomes of children with and without NAFLD. METHODS: We performed a prospective, observational, cross-sectional study of 87 children (age range, 8-17 years) with biopsy-proven NAFLD and 37 children with obesity without NAFLD (controls). Fecal samples were collected and microbiome composition and functions were assessed using 16S ribosomal RNA amplicon sequencing and metagenomic shotgun sequencing. Microbial taxa were identified using zero-inflated negative binomial modeling. Genes contributing to bacterial pathways were identified using gene set enrichment analysis. RESULTS: Fecal microbiomes of children with NAFLD had lower α-diversity than those of control children (3.32 vs 3.52, P = .016). Fecal microbiomes from children with nonalcoholic steatohepatitis (NASH) had the lowest α-diversity (control, 3.52; NAFLD, 3.36; borderline NASH, 3.37; NASH, 2.97; P = .001). High abundance of Prevotella copri was associated with more severe fibrosis (P = .036). Genes for lipopolysaccharide biosynthesis were enriched in microbiomes from children with NASH (P < .001). Classification and regression tree model with level of alanine aminotransferase and relative abundance of the lipopolysaccharide pathway gene encoding 3-deoxy-d-manno-octulosonate 8-phosphate-phosphatase identified patients with NASH with an area under the receiver operating characteristic curve value of 0.92. Genes involved in flagellar assembly were enriched in the fecal microbiomes of patients with moderate to severe fibrosis (P < .001). Classification and regression tree models based on level of alanine aminotransferase and abundance of genes encoding flagellar biosynthesis protein had good accuracy for identifying case children with moderate to severe fibrosis (area under the receiver operating characteristic curve, 0.87). CONCLUSIONS: In an analysis of fecal microbiomes of children with NAFLD, we associated NAFLD and NASH with intestinal dysbiosis. NAFLD and its severity were associated with greater abundance of genes encoding inflammatory bacterial products. Alterations to the intestinal microbiome might contribute to the pathogenesis of NAFLD and be used as markers of disease or severity.

11ß-hydroxysteroid dehydrogenase-1 deficiency alters the gut microbiome response to Western diet.

The enzyme 11ß-hydroxysteroid dehydrogenase (11ß-HSD) interconverts active glucocorticoids and their intrinsically inert 11-keto forms. The type 1 isozyme, 11ß-HSD1, predominantly reactivates glucocorticoids in vivo and can also metabolise bile acids. 11ß-HSD1-deficient mice show altered inflammatory responses and are protected against the adverse metabolic effects of a high-fat diet. However, the impact of 11ß-HSD1 on the composition of the gut microbiome has not previously been investigated. We used high-throughput 16S rDNA amplicon sequencing to characterise the gut microbiome of 11ß-HSD1-deficient and C57Bl/6 control mice, fed either a standard chow diet or a cholesterol- and fat-enriched 'Western' diet. 11ß-HSD1 deficiency significantly altered the composition of the gut microbiome, and did so in a diet-specific manner. On a Western diet, 11ß-HSD1 deficiency increased the relative abundance of the family Bacteroidaceae, and on a chow diet, it altered relative abundance of the family Prevotellaceae Our results demonstrate that (i) genetic effects on host-microbiome interactions can depend upon diet and (ii) that alterations in the composition of the gut microbiome may contribute to the aspects of the metabolic and/or inflammatory phenotype observed with 11ß-HSD1 deficiency.

Long noncoding RNAs in B-cell development and activation.

Long noncoding RNAs (lncRNAs) are potentially important regulators of cell differentiation and development, but little is known about their roles in B lymphocytes. Using RNA-seq and de novo transcript assembly, we identified 4516 lncRNAs expressed in 11 stages of B-cell development and activation. Most of these lncRNAs have not been previously detected, even in the closely related T-cell lineage. Comparison with lncRNAs previously described in human B cells identified 185 mouse lncRNAs that have human orthologs. Using chromatin immunoprecipitation-seq, we classified 20% of the lncRNAs as either enhancer-associated (eRNA) or promoter-associated RNAs. We identified 126 eRNAs whose expression closely correlated with the nearest coding gene, thereby indicating the likely location of numerous enhancers active in the B-cell lineage. Furthermore, using this catalog of newly discovered lncRNAs, we show that PAX5, a transcription factor required to specify the B-cell lineage, bound to and regulated the expression of 109 lncRNAs in pro-B and mature B cells and 184 lncRNAs in acute lymphoblastic leukemia.

CGAT: computational genomics analysis toolkit.

Computational genomics seeks to draw biological inferences from genomic datasets, often by integrating and contextualizing next-generation sequencing data. CGAT provides an extensive suite of tools designed to assist in the analysis of genome scale data from a range of standard file formats. The toolkit enables filtering, comparison, conversion, summarization and annotation of genomic intervals, gene sets and sequences. The tools can both be run from the Unix command line and installed into visual workflow builders, such as Galaxy.