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Background: Parkinson’s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. Objective: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson’s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. Methods: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). Results: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson’s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA + fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. Conclusion: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analysis identified unique proinflammatory microbial signature in the IgA + fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches.

Background: Human noroviruses are a leading cause of acute and sporadic gastroenteritis worldwide. The evolution of human noroviruses in immunocompromised persons has been evaluated in many studies. Much less is known about the evolutionary dynamics of human norovirus in healthy adults. Methods: We used sequential samples collected from a controlled human infection study with GI.1/Norwalk/US/68 virus to evaluate intra- and inter-host evolution of a human norovirus in healthy adults. Up to 12 samples from day 1 to day 56 post-challenge were sequenced using a norovirus-specific capture probe method. Results: Complete genomes were assembled, even in samples that were below the limit of detection of standard RT-qPCR assays, up to 28 days post-challenge. Analysis of 123 complete genomes showed changes in the GI.1 genome in all persons, but there were no conserved changes across all persons. Single nucleotide variants resulting in non-synonymous amino acid changes were observed in all proteins, with the capsid VP1 and nonstructural protein NS3 having the largest numbers of changes. Conclusions: These data highlight the potential of a new capture-based sequencing approach to assemble human norovirus genomes with high sensitivity and demonstrate limited conserved immune pressure-driven evolution of GI.1 virus in healthy adults.

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation ‘hotspots’; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

Wastewater is a discarded human by-product but analyzing it may help us understand the health of communities. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. We conducted a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Over 450 distinct pathogenic viruses were detected. Sequencing reads of established pathogens and emerging viruses correlated to clinical data sets. Viral communities were tightly organized by space and time. Finally, the most abundant human viruses yielded sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.One-Sentence SummaryWastewater contains a trickle of circulating human viruses, and now we can sequence them to better track community transmission.

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Given the increasing evidence that the oral microbiome is involved in obesity, diabetes, and cancer risk, we investigated baseline oral microbiota profiles in relation to all-cancer incidence among nonsmoking women enrolled in a Texas cohort of first- and second-generation immigrants of Mexican origin. We characterized the 16Sv4 rDNA microbiome in oral mouthwash samples collected at baseline from a representative subset of 305 nonsmoking women, ages 20–75 years. We evaluated within- (alpha) and between-sample (beta) diversity by incident cancer status and applied linear discriminant analysis (LDA) effect size analysis to assess differentially abundant taxa. Diversity and candidate taxa in relation to all-cancer incidence were evaluated in multivariable-adjusted Cox regression models. Over 8.8 median years of follow-up, 31 incident cancer cases were identified and verified. Advanced age, greater acculturation, and cardiometabolic risk factors were associated with all-cancer incidence. Higher alpha diversity (age-adjusted Pdifference < 0.01) and distinct biological communities (Pdifference = 0.002) were observed by incident cancer status. Each unit increase in the Shannon diversity index yielded >8-fold increase in all-cancer and obesity-related cancer risk [multivariable-adjusted HR (95% confidence interval), 8.11 (3.14–20.94) and 10.72 (3.30–34.84), respectively] with similar findings for the inverse Simpson index. Streptococcus was enriched among women who did not develop cancer, while Fusobacterium, Prevotella, Mogibacterium, Campylobacter, Lachnoanaerobaculum, Dialister, and Atopobium were higher among women who developed cancer (LDA score ≥ 3; q-value < 0.01). This initial study of oral microbiota and overall cancer risk in nonsmoking Mexican American women suggests the readily accessible oral microbiota as a promising biomarker.Prevention Relevance:Mexican American women suffer a disproportionate burden of chronic health conditions that increase cancer risk. Few investigations of the microbiome, a key determinant of host health, have been conducted among this group. Oral microbiota profiles may provide early and accessible cancer biomarker data on invasive bacteria or community disruptions.

Chronic pancreatitis (CP) is a chronic fibroinflammatory condition of the pancreas difficult to diagnose in early stages. Novel biomarkers useful to facilitate early diagnosis or treatment responses may be found in biofluids. Although saliva can be easily and noninvasively collected from patients, useful salivary biomarkers from CP patients have not yet been identified.Here, we analyzed the proteome by quantitative proteomics, cytokine/chemokine levels by Luminex analysis, prostaglandin E2 (PGE2) levels by a mass spectrometry-based assay, and bacterial species diversity by 16S ribosomal ribonucleic acid sequencing in saliva samples from confirmed CP patients and healthy controls.Our results indicate the presence of various differentially expressed proteins, cytokines/chemokines, and a loss of oral bacterial diversity in the saliva of CP patients. The PGE2 levels trend toward elevation in CP patients. Area under the receiver operating characteristic curve models for proteomic, cytokine, and PGE2 assays ranged from 0.59 to 0.90.Collectively, our studies identify a range of putative CP biomarkers and alterations in human saliva requiring further validation. The biomarker discovery approaches we used might lead to identification of biomarkers useful for CP diagnosis and monitoring.

Limited data exist on the spatial distribution of the colonic bacteria in humans. We collected the colonic biopsies from five segments of 27 polyp-free adults and collected feces from 13 of them. We sequenced the V4 region of the bacterial 16S rRNA gene using the MiSeq platform. The sequencing data were assigned to the amplicon sequence variant (ASV) using SILVA. Biodiversity and the relative abundance of the ASV were compared across the colonic segments and between the rectal and fecal samples. Bacterial functional capacity was assessed using Tax4fun. Each individual had a unique bacterial community composition (Weighted Bray–Curtis P value = 0.001). There were no significant differences in richness, evenness, community composition, and the taxonomic structure across the colon segments in all the samples. Firmicutes (47%), Bacteroidetes (39%), and Proteobacteria (6%) were the major phyla in all segments, followed by Verrucomicrobia, Fusobacteria, Desulfobacterota, and Actinobacteria. There were 15 genera with relative abundance > 1%, including Bacteroides, Faecalibacterium, Escherichia/Shigella, Sutterella, Akkermansia, Parabacteroides, Prevotella, Lachnoclostridium, Alistipes, Fusobacterium, Erysipelatoclostridium, and four Lachnospiraceae family members. Intra-individually, the community compositional dissimilarity was the greatest between the cecum and the rectum. There were significant differences in biodiversity and the taxonomic structure between the rectal and fecal bacteria. The bacterial community composition and structure were homogeneous across the large intestine in adults. The inter-individual variability of the bacteria was greater than inter-segment variability. The rectal and fecal bacteria differed in the community composition and structure.

Mounting evidence supports synergistic roles for the gut microbiome in cancer progression. Yet, the interplay between the gut microbiome and immune responses in cancer is still poorly understood. We recently showed that gut microbiome changes are closely associated with development of Kras-mutant lung adenocarcinoma (KM-LUAD) in a human-relevant, tobacco-associated mouse model (Gprc5a-/-; G). Knockout of the antimicrobial protein Lcn2 in these mice (Gprc5a-/-/Lcn2-/-; GL) further reduced microbial diversity while enhancing inflammation and tumor development. We thus hypothesized that microbial dysbiosis in the gut, such as that incurred by loss of Lcn2, may exacerbate LUAD development. Here, we investigated the effects of gut microbiome modulation on LUAD pathogenesis using fecal microbiota transfer (FMT) in both syngeneic and tobacco carcinogenesis models. Syngeneic G mice (transplant of G LUAD cells) that received FMT from GL donors (G < GL) exhibited significantly increased tumor growth relative to littermates with FMT from G mice (G < G). These effects were recapitulated in an independent syngeneic model (KrasG12D LKR13 cells in wild type mice). Tobacco carcinogen-exposed G < GL mice also exhibited increased lung tumor development compared with similarly exposed G < G littermates. 16S rDNA-Seq analysis of fecal pellets revealed significant differences in gut beta diversity between syngeneic G < G and G < GL mice. G < GL mice additionally displayed elevated relative abundance of tumor-promoting Alistipes, while Ruminoccocus and Akkermansia, taxa associated with favorable response to immunotherapy, were reduced. We next performed single-cell RNA-sequencing to comprehensively probe the tumor immune microenvironment (TIME) and the immune milieu near the gut of tumors and mesenteric lymph nodes (MLNs), respectively. The TIME in G < GL mice displayed an overall enhanced immunosuppressive phenotype evidenced by prominently increased fractions of T regulatory and Cd4+ Izumo1r+ exhausted T cells and, conversely, reduced levels of activated Isg15+ Cd8a+ T cells. MLNs from G < GL mice showed markedly increased fractions of memory B cells expressing the immunosuppressor Bank1 and reduced levels of follicular B cells and Cd8a+ Clec9a+ class 1 dendritic cells (cDC1). Flow cytometry further showed enhanced immunosuppression in G < GL relative to G < G mice, including increased fractions of myeloid-derived suppressor cells in the TIME of the former group. Our findings show that gut microbiome dysbiosis fosters lung cancer development by promoting immunosuppression, perhaps via a local and systemic gut microbiota-immune system crosstalk. Modulating the gut microbiome may be a promising strategy for interception or early treatment of lung cancer. Citation Format: Zahraa Rahal, Fuduan Peng, Yuejiang Liu, Matthew C. Ross, Ansam Sinjab, Ke Liang, Jiping Feng, Chidera O. Chukwuocha, Manvi Sharma, Elizabeth Tang, Camille Abaya, Joseph Petrosino, Junya Fujimoto, Seyed Javad Moghaddam, Linghua Wang, Kristi L. Hoffman, Humam Kadara. Gut microbiome dysbiosis promotes immune suppression and lung cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2883.

Dating across religious lines is becoming more common in the United States, especially among young adults, suggesting greater acceptance of interfaith relationships. Although college is a place whe...

ObjectiveNecrotising enterocolitis (NEC) is a devastating intestinal disease primarily affecting preterm infants. The underlying mechanisms are poorly understood: mother’s own breast milk (MOM) is protective, possibly relating to human milk oligosaccharide (HMO) and infant gut microbiome interplay. We investigated the interaction between HMO profiles and infant gut microbiome development and its association with NEC.DesignWe performed HMO profiling of MOM in a large cohort of infants with NEC (n=33) with matched controls (n=37). In a subset of 48 infants (14 with NEC), we also performed longitudinal metagenomic sequencing of infant stool (n=644).ResultsConcentration of a single HMO, disialyllacto-N-tetraose (DSLNT), was significantly lower in MOM received by infants with NEC compared with controls. A MOM threshold level of 241 nmol/mL had a sensitivity and specificity of 0.9 for NEC. Metagenomic sequencing before NEC onset showed significantly lower relative abundance of Bifidobacterium longum and higher relative abundance of Enterobacter cloacae in infants with NEC. Longitudinal development of the microbiome was also impacted by low MOM DSLNT associated with reduced transition into preterm gut community types dominated by Bifidobacterium spp and typically observed in older infants. Random forest analysis combining HMO and metagenome data before disease accurately classified 87.5% of infants as healthy or having NEC.ConclusionThese results demonstrate the importance of HMOs and gut microbiome in preterm infant health and disease. The findings offer potential targets for biomarker development, disease risk stratification and novel avenues for supplements that may prevent life-threatening disease.

Methamphetamine is a highly abused psychostimulant drug and its use remains a major public health concern worldwide with limited effective treatment options. Accumulative evidence reveals the influence of gut microbiota on the brain, behavior, and health as a part of the gut-brain axis but its involvement in modulating this substance use disorder remains poorly understood. We sought to determine whether methamphetamine exposure and cessation or withdrawal alter the intestinal gut microbiota as well as characterize cessation-induced behavioral changes. Male, Sprague-Dawley rats were administered methamphetamine (2 mg/kg; s.c.) or vehicle (n = 8 per group) twice per day for 14 consecutive days. On various days before, during, and after administration, fecal samples were collected and tests of anxiety- and depressive-like behaviors were conducted. Methamphetamine administration and cessation did not alter the relative abundance of bacteria but significantly changed the composition of gut bacteria through 16S rRNA sequencing. These changes were normalized after 7 days of methamphetamine cessation. Moreover, acute methamphetamine cessation induced depressive-like behavior, with an increase in immobility in the forced swim test but did not alter anxiety-like behaviors in tests of open field test or elevated plus maze. These findings provide direct evidence that methamphetamine and its cessation cause gut dysbiosis and that the latter associates with depressive-like behavior in rodents. Our observation will contribute to a better understanding of the function of gut microbiota in the process of substance use disorders and guide the choice of target therapeutics.

BACKGROUND: Systemic diseases have been associated with oral health and gut microbiota. We examined the association between oral health and the community composition and structure of the adherent colonic gut microbiota. METHODS: We obtained 197 snap-frozen colonic biopsies from 62 colonoscopy-confirmed polyp-free individuals. Microbial DNA was sequenced for the 16S rRNA V4 region using the Illumina MiSeq, and the sequences were assigned to the operational taxonomic unit based on SILVA. We used a questionnaire to ascertain tooth loss, gum disease, and lifestyle factors. We compared biodiversity and relative abundance of bacterial taxa based on the amount of tooth loss and the presence of gum disease. The multivariable negative binomial regression model for panel data was used to estimate the association between the bacterial count and oral health. False discovery rate-adjusted P value (q value) < .05 indicated statistical significance. RESULTS: More tooth loss and gum disease were associated with lower bacterial alpha diversity. The relative abundance of Faecalibacterium was lower (q values < .05) with more tooth loss. The association was significant after adjusting for age, ethnicity, obesity, smoking, alcohol use, hypertension, diabetes, and the colon segment. The relative abundance of Bacteroides was higher in those with gum disease. CONCLUSIONS: Oral health was associated with alteration in the community composition and structure of the adherent gut bacteria in the colon. The reduced anti-inflammatory Faecalibacterium in participants with more tooth loss may indicate systemic inflammation. Future studies are warranted to confirm our findings and investigate the systemic role of Faecalibacterium.

Aim To investigate the role of the gut microbiome in regulating key insulin homeostasis traits (insulin sensitivity, insulin secretion and insulin clearance) whose dysfunction leads to type 2 diabetes (T2D). Materials and methods The Microbiome and Insulin Longitudinal Evaluation Study (MILES) focuses on African American and non-Hispanic white participants aged 40-80 years without diabetes. Three study visits are planned (at baseline, 15 and 30 months). Baseline measurements include assessment of the stool microbiome and administration of an oral glucose tolerance test, which will yield indexes of insulin sensitivity, insulin secretion and insulin clearance. The gut microbiome profile (composition and function) will be determined using whole metagenome shotgun sequencing along with analyses of plasma short chain fatty acids. Additional data collected include dietary history, sociodemographic factors, health habits, anthropometry, medical history, medications and family history. Most assessments are repeated 15 and 30 months following baseline. Results After screening 875 individuals, 129 African American and 224 non-Hispanic white participants were enrolled. At baseline, African American participants have higher blood pressure, weight, body mass index, waist and hip circumferences but similar waist-hip ratio compared with the non-Hispanic white participants. On average, African American participants are less insulin-sensitive and have higher acute insulin secretion and lower insulin clearance. Conclusions The longitudinal design and robust characterization of potential mediators will allow for the assessment of glucose and insulin homeostasis and gut microbiota as they change over time, improving our ability to discern causal relationships between the microbiome and the insulin homeostasis traits whose deterioration determines T2D, setting the stage for future microbiome-directed therapies to prevent and treat T2D.

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 between 36 butyrate-producing taxa (7 genera, 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, body mass index, and race. 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 0.91, 95% confidence interval (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. While 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.

Another benefit of dietary fiber The gut microbiome can modulate the immune system and influence the therapeutic response of cancer patients, yet the mechanisms underlying the effects of microbiota are presently unclear. Spencer et al . add to our understanding of how dietary habits affect microbiota and clinical outcomes to immunotherapy. In an observational study, the researchers found that melanoma patients reporting high fiber (prebiotic) consumption had a better response to checkpoint inhibitor immunotherapy compared with those patients reporting a low-fiber diet. The most marked benefit was observed for those patients reporting a combination of high fiber consumption and no use of over-the-counter probiotic supplements. These findings provide early insights as to how diet-related factors may influence the immune response. —PNK

To characterize the spatial variation of the mucosa-associated adherent mycobiota along the large intestine in individuals with a normal-colon, we performed eukaryotic rRNA operon’s internal transcribed spacer-2 sequencing to profile fungal community composition and structure in 70 mucosal biopsies taken from the cecum, ascending, transverse, descending colon, and rectum of 14 polyp-free individuals. The bacteriome of these samples was previously characterized by sequencing the V4 region of the 16S rRNA gene. We identified 64 amplicon sequence variants (ASVs) with the relative abundance no less than 0.05% from these colonic mucosa samples. Each individual has a unique community composition of the gut mycobiome (P = 0.001 for beta diversity). Alpha-diversity and beta-diversity did not differ significantly across the colon segments. The most common phyla (relative abundance) were Ascomycota (45.4%) and Basidiomycota (45.3%). The most common genera were Malassezia (28.2%) and Candida (13.4%). Malassezia was found in 13 of 14 individuals. Other fungi genera were sporadically found in the large intestine. The most common species were Malassezia restricta (22.7%), Candida albicans (11.9%), Malasseziales sp. (8.80%), unclassified fungi (7.80%), and Penicillium paneum (5.70%). Malasseziaceae was co-abundant with Enterobacteriaceae and co-exclusive with Barnesiellaceae, Rikenellaceae, and Acidaminococcaceae. Malassezia was widely colonized whereas other fungal genera were sporadically colonized in the large intestine. The physiologic and pathogenic functions of fungi in human gastrointestinal tract including Malasseziaceae that may interact with several bacterial families remain to be fully elucidated.

Hurricane Harvey caused record-breaking, catastrophic flooding across the city of Houston. After floodwaters receded, several health concerns arose, including the potential adverse impact of exposure to mold in flooded homes. We rapidly launched the Houston Hurricane Harvey Health Study to evaluate if microbiome sampling in the wake of a disaster could inform flood-associated environmental exposures and adverse health outcomes. We enrolled a total of 347 subjects at 1-month and 12-months post-Harvey, collecting human (stool, nasal, saliva) and environmental (house swab) samples to profile the bacterial and fungal microbiota. Here we show reported exposure to mold was associated with increased risk of allergic symptoms for up to one year post-disaster, and that butyrate-producing bacteria in the gut were linked to protection from allergic symptoms in mold-exposed individuals. Together, these data provide new insights into how microbiome:environment interactions may influence health in the setting of a flood-related disaster.

Background Cryptosporidium parvum is an apicomplexan parasite commonly found across many host species with a global infection prevalence in human populations of 7.6%. Understanding its diversity and genomic makeup can help in fighting established infections and prohibiting further transmission. The basis of every genomic study is a high-quality reference genome that has continuity and completeness, thus enabling comprehensive comparative studies. Findings Here, we provide a highly accurate and complete reference genome of Cryptosporidium parvum. The assembly is based on Oxford Nanopore reads and was improved using Illumina reads for error correction. We also outline how to evaluate and choose from different assembly methods based on 2 main approaches that can be applied to other Cryptosporidium species. The assembly encompasses 8 chromosomes and includes 13 telomeres that were resolved. Overall, the assembly shows a high completion rate with 98.4% single-copy BUSCO genes. Conclusions This high-quality reference genome of a zoonotic IIaA17G2R1 C. parvum subtype isolate provides the basis for subsequent comparative genomic studies across the Cryptosporidium clade. This will enable improved understanding of diversity, functional, and association studies.

Secretory IgA (SIgA) is released into mucosal surfaces where its function extends beyond that of host defense to include the shaping of resident microbial communities by mediating exclusion/inclusion of respective microbes and regulating bacterial gene expression. In this capacity, SIgA acts as the fulcrum on which host immunity and the health of the microbiota are balanced. We recently completed an analysis of the gut and salivary IgA-Biomes (16S rDNA sequencing of SIgA-coated/uncoated bacteria) in Mexican-American adults that identified IgA-Biome differences across the glycemic spectrum. As Th17:Treg ratio imbalances are associated with gut microbiome dysbiosis and chronic inflammatory conditions such as type 2 diabetes, the present study extends our prior work by examining the impact of Th17:Treg ratios (pro-inflammatory:anti-inflammatory T-cell ratios) and the SIgA response (Th17:Treg-SIgA axis) in shaping microbial communities. Examining the impact of Th17:Treg ratios (determined by epigenetic qPCR lymphocyte subset quantification) on the IgA-Biome across diabetes phenotypes identified a proportional relationship between Th17:Treg ratios and alpha diversity in the stool IgA-Biome of those with dysglycemia, significant changes in community composition of the stool and salivary microbiomes across glycemic profiles, and genera preferentially abundant by T-cell inflammatory phenotype. This is the first study to associate epigenetically quantified Th17:Treg ratios with both the larger and SIgA-fractionated microbiome, assess these associations in the context of a chronic inflammatory disease, and offers a novel frame through which to evaluate mucosal microbiomes in the context of host responses and inflammation.

Dysbiosis of the maternal gut microbiome during pregnancy is associated with adverse neurodevelopmental outcomes. We previously showed that maternal high-fat diet (MHFD) in mice induces gut dysbiosis, social dysfunction, and underlying synaptic plasticity deficits in male offspring (F(1)). Here, we reason that, if HFD-mediated changes in maternal gut microbiota drive offspring social deficits, then MHFD-induced dysbiosis in F(1) female MHFD offspring would likewise impair F(2) social behavior. Metataxonomic sequencing reveals reduced microbial richness among female F(1) MHFD offspring. Despite recovery of microbial richness among MHFD-descendant F(2) mice, they display social dysfunction. Post-weaning Limosilactobacillus reuteri treatment increases the abundance of short-chain fatty acid-producing taxa and rescues MHFD-descendant F(2) social deficits. L. reuteri exerts a sexually dimorphic impact on gut microbiota configuration, increasing discriminant taxa between female cohorts. Collectively, these results show multigenerational impacts of HFD-induced dysbiosis in the maternal lineage and highlight the potential of maternal microbiome-targeted interventions for neurodevelopmental disorders.

The neonatal cutaneous mycobiome has not been characterized in preterm infants. Invasive fungal infections in preterm neonates are associated with high mortality. The immaturity of the preterm skin predisposes neonates to invasive infection by skin colonizers. We report the clinical and host determinants that influence the skin mycobiome. Skin swabs from the antecubital fossa, forehead, and gluteal region of 15 preterm and 15 term neonates were obtained during the first 5 weeks of life. The mycobiome was sequenced using the conserved pan-fungal ITS2 region. Blood samples were used to genotype immune modulating genes. Clinical metadata was collected to determine the clinical predictors of the abundance and diversity of the skin mycobiome. The neonatal mycobiome is characterized by few taxa. Alpha diversity of the mycobiome is influenced by antibiotic exposure, the forehead body site, and the neonatal intensive care unit (NICU) environment. Beta diversity varies with mode of delivery, diet, and body site. The host determinants of the cutaneous microbiome include single-nucleotide polymorphisms in TLR4, NLRP3,CARD8, and NOD2. The neonatal cutaneous mycobiome is composed of few genera and is influenced by clinical factors and host genetics, the understanding of which will inform preventive strategies against invasive fungal infections.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here we report a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with four strains of RSV representing both major subgroups as well as historic and more contemporaneous genotypes -- [RSV/A/Tracy (GA1), RSV/A/Ontario (ON), RSV/B/18537 (GB1), RSV/B/Buenos Aires (BA)] -- via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response including transcriptional changes and levels of secreted cytokines and growth factors. Our findings strongly suggest 1) the existence of a conserved difference in gene expression between RSV subgroups A and B; 2) the A549 cell line is a more stringent and natural host of replicating RSV than the HEp-2 cell line; and 3) consistent with previous studies, determining the full effects of viral genetic variation in RSV pathogenesis requires model systems as tractable as transformed cell lines but better representative of the human host.IMPORTANCEInfection with respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. In vitro data from two historic RSV/A strains and two cell lines, HEp-2 and A549, constitute most of our knowledge; but RSV contains ample variation from two evolving subgroups (A and B) showing recent convergent evolution. Here we measure viral action and host response in HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporaneous strains. We discover a subgroup-dependent difference in viral gene expression and find A549 cells are more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings reveal important differences between RSV subgroups and two widely used cell lines and provide baseline data for experiments with model systems better representative of natural RSV infection.

Microbiome composition and function have been implicated as contributing factors in the pathogenesis of autoimmune diseases (ADs), including systemic lupus erythematosus (SLE), rheumatoid arthritis and autoimmune hepatitis (AIH). Furthermore, dysbiosis of gut microbiome is associated with impaired barrier function and mucosal immune dysregulation. However, mechanisms by which gut microbiome contributes to the ADs and whether antioxidant treatment can restore gut homeostasis and ameliorate the disease outcome are not known. This study was, therefore, focused on examining the involvement of gut microbiome and host responses in the pathogenesis of SLE using unique female mouse models (C57BL/6, MRL+/+ and MRL/lpr) of 6 and 18 weeks with varying degrees of disease progression. Fecal microbiome diversity and composition, gut oxidative stress (OS), barrier function and inflammation, as well as systemic autoimmunity were determined. Interestingly, each mouse strain had distinct bacterial community as revealed by β-diversity. A lower Firmicutes/Bacteroidetes ratio in 6-week-old MRL/lpr mice was observed, evidenced by decrease in Peptostreptococcaceae under Firmicutes phylum along with enrichment of Rikenellaceae under Bacteroidetes phylum. Additionally, we observed increases in colonic OS [4-hydroxynonenal (HNE)-adducts and HNE-specific immune complexes], permeability changes (lower tight junction protein ZO-2; increased fecal albumin and IgA levels) and inflammatory responses (increased phos-NF-κB, IL-6 and IgG levels) in 18-week-old MRL/lpr mice. These changes were associated with markedly elevated AD markers (antinuclear and anti-smooth muscle antibodies) along with hepatic portal inflammation and severe glomerulonephritis. Notably, antioxidant N-acetylcysteine treatment influenced the microbial composition (decreased Rikenellaceae; increased Akkeransiaceae, Erysipelotrichaceae and Muribaculaceae) and attenuated the systemic autoimmunity in MRL/lpr mice. Our data thus show that gut microbiome dysbiosis is associated with increased colonic OS, barrier dysfunction, inflammatory responses and systemic autoimmunity markers. These findings apart from delineating a role for gut microbiome dysbiosis, also support the contribution of gut OS, permeability changes and inflammatory responses in the pathogenesis of ADs.

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

Mucosal surfaces like those present in the lung, gut, and mouth interface with distinct external environments. These mucosal gateways are not only portals of entry for potential pathogens but also homes to microbial communities that impact host health. Secretory immunoglobulin A (SIgA) is the single most abundant acquired immune component secreted onto mucosal surfaces and, via the process of immune exclusion, shapes the architecture of these microbiomes. Not all microorganisms at mucosal surfaces are targeted by SIgA; therefore, a better understanding of the SIgA-coated fraction may identify the microbial constituents that stimulate host immune responses in the context of health and disease. Chronic diseases like type 2 diabetes are associated with altered microbial communities (dysbiosis) that in turn affect immune-mediated homeostasis. 16S rRNA gene sequencing of SIgA-coated/uncoated bacteria (IgA-Biome) was conducted on stool and saliva samples of normoglycemic participants and individuals with prediabetes or diabetes (n = 8/group). These analyses demonstrated shifts in relative abundance in the IgA-Biome profiles between normoglycemic, prediabetic, or diabetic samples distinct from that of the overall microbiome. Differences in IgA-Biome alpha diversity were apparent for both stool and saliva, while overarching bacterial community differences (beta diversity) were also observed in saliva. These data suggest that IgA-Biome analyses can be used to identify novel microbial signatures associated with diabetes and support the need for further studies exploring these communities. Ultimately, an understanding of the IgA-Biome may promote the development of novel strategies to restructure the microbiome as a means of preventing or treating diseases associated with dysbiosis at mucosal surfaces.

One of the major research questions regarding human microbiome studies is the feasibility of designing interventions that modulate the composition of the microbiome to promote health and cure disease. This requires extensive understanding of the modulating factors of the microbiome, such as dietary intake, as well as the relation between microbial composition and phenotypic outcomes, such as body mass index (BMI). Previous efforts have modeled these data separately, employing two-step approaches that can produce biased interpretations of the results. Here, we propose a Bayesian joint model that simultaneously identifies clinical covariates associated with microbial composition data and predicts a phenotypic response using information contained in the compositional data. Using spike-and-slab priors, our approach can handle high-dimensional compositional as well as clinical data. Additionally, we accommodate the compositional structure of the data via balances and overdispersion typically found in microbial samples. We apply our model to understand the relations between dietary intake, microbial samples, and BMI. In this analysis, we find numerous associations between microbial taxa and dietary factors that may lead to a microbiome that is generally more hospitable to the development of chronic diseases, such as obesity. Additionally, we demonstrate on simulated data how our method outperforms two-step approaches and also present a sensitivity analysis., 32 pages, 5 figures

Given the increasing evidence that the oral microbiome is involved in obesity, diabetes, and cancer risk, we investigated baseline oral microbiota profiles in relation to all-cancer incidence among nonsmoking women enrolled in a Texas cohort of first- and second-generation immigrants of Mexican origin. We characterized the 16Sv4 rDNA microbiome in oral mouthwash samples collected at baseline from a representative subset of 305 nonsmoking women, ages 20–75 years. We evaluated within- (alpha) and between-sample (beta) diversity by incident cancer status and applied linear discriminant analysis (LDA) effect size analysis to assess differentially abundant taxa. Diversity and candidate taxa in relation to all-cancer incidence were evaluated in multivariable-adjusted Cox regression models. Over 8.8 median years of follow-up, 31 incident cancer cases were identified and verified. Advanced age, greater acculturation, and cardiometabolic risk factors were associated with all-cancer incidence. Higher alpha diversity (age-adjusted Pdifference < 0.01) and distinct biological communities (Pdifference = 0.002) were observed by incident cancer status. Each unit increase in the Shannon diversity index yielded >8-fold increase in all-cancer and obesity-related cancer risk [multivariable-adjusted HR (95% confidence interval), 8.11 (3.14–20.94) and 10.72 (3.30–34.84), respectively] with similar findings for the inverse Simpson index. Streptococcus was enriched among women who did not develop cancer, while Fusobacterium, Prevotella, Mogibacterium, Campylobacter, Lachnoanaerobaculum, Dialister, and Atopobium were higher among women who developed cancer (LDA score ≥ 3; q-value < 0.01). This initial study of oral microbiota and overall cancer risk in nonsmoking Mexican American women suggests the readily accessible oral microbiota as a promising biomarker. Prevention Relevance: Mexican American women suffer a disproportionate burden of chronic health conditions that increase cancer risk. Few investigations of the microbiome, a key determinant of host health, have been conducted among this group. Oral microbiota profiles may provide early and accessible cancer biomarker data on invasive bacteria or community disruptions.

OBJECTIVES: Although the airway microbiota is a highly dynamic ecology, the role of longitudinal changes in airway microbiota during early childhood in asthma development is unclear. We aimed to investigate the association of longitudinal changes in early nasal microbiota with the risk of developing asthma. METHODS: In this prospective, population-based birth cohort study, we followed children from birth to age 7 years. The nasal microbiota was tested by using 16S ribosomal RNA gene sequencing at ages 2, 13, and 24 months. We applied an unsupervised machine learning approach to identify longitudinal nasal microbiota profiles during age 2 to 13 months (the primary exposure) and during age 2 to 24 months (the secondary exposure) and examined the association of these profiles with the risk of physician-diagnosed asthma at age 7 years. RESULTS: Of the analytic cohort of 704 children, 57 (8%) later developed asthma. We identified 4 distinct longitudinal nasal microbiota profiles during age 2 to 13 months. In the multivariable analysis, compared with the persistent Moraxella dominance profile during age 2 to 13 months, the persistent Moraxella sparsity profile was associated with a significantly higher risk of asthma (adjusted odds ratio, 2.74; 95% confidence interval, 1.20–6.27). Similar associations were observed between the longitudinal changes in nasal microbiota during age 2 to 24 months and risk of asthma. CONCLUSIONS: Children with an altered longitudinal pattern in the nasal microbiota during early childhood had a high risk of developing asthma. Our data guide the development of primary prevention strategies (eg, early identification of children at high risk and modification of microbiota) for childhood asthma. These observations present a new avenue for risk modification for asthma (eg, microbiota modification).

BackgroundOral administration of antigen can induce immunological tolerance. Insulin is a key autoantigen in childhood type 1 diabetes with insulin autoimmunity often appearing in the first years of life. Here, oral insulin was given as antigen-specific immunotherapy before the onset of autoimmunity in children from age 6 months to assess its safety and actions on immunity and the gut microbiome.MethodsA phase I/II randomized controlled trial was performed in 44 islet autoantibody-negative children aged 6 months to 2 years with genetic risk for type 1 diabetes. Children were randomized 1:1 to daily oral insulin (7.5 mg with dose escalation to 67.5 mg) or placebo for 12 months. Primary outcome was safety and immune efficacy pre-specified as hypoglycemia and induction of antibody or T cell responses to insulin, respectively.ResultsOral insulin was well tolerated with no changes in metabolic variables. Immune responses to insulin were observed in both children who received insulin (55%) and placebo (67%), and were modified by theINSULINgene. Among children with type 1 diabetes-susceptibleINSULINgenotype, antibody responses to insulin were more frequent in insulin-treated (cumulative response, 75.8%) as compared to placebo-treated children (18.2%;P=0.0085), and T cell responses to insulin were modified by treatment-independent inflammatory episodes. Changes in the microbiome were related toINSULINgenotype.ConclusionThe study demonstrated that oral insulin immunotherapy in young genetically at-risk children was safe and engaged the adaptive immune system in anINSULINgenotype-dependent manner, and linked inflammatory episodes to the activation of insulin-responsive T cells.Trial registrationClinicaltrials.govNCT02547519FundingGerman Center for Diabetes Research (DZD e.V.), Juvenile Diabetes Research Foundation (JDRF, grant 1-SRA-2018-546-S-B), Federal Ministry of Education and Research (BMBF, grant FKZ01KX1818).