Seasonal airway microbiome and transcriptome interactions promote childhood asthma exacerbations.

BACKGROUND: Seasonal variation in respiratory illnesses and exacerbations in pediatric populations with asthma is well described, though whether upper airway microbes play season-specific roles in these events is unknown. OBJECTIVE: We hypothesized that nasal microbiota composition is seasonally dynamic and that discrete microbe-host interactions modify risk of asthma exacerbation in a season-specific manner. METHODS: Repeated nasal samples from children with exacerbation-prone asthma collected during periods of respiratory health (baseline; n = 181 samples) or first captured respiratory illness (n = 97) across all seasons, underwent bacterial (16S ribosomal RNA gene) and fungal (internal transcribed spacer region 2) biomarker sequencing. Virus detection was performed by multiplex PCR. Paired nasal transcriptome data were examined for seasonal dynamics and integrative analyses. RESULTS: Upper airway bacterial and fungal microbiota and rhinovirus detection exhibited significant seasonal dynamics. In seasonally adjusted analysis, variation in both baseline and respiratory illness microbiota related to subsequent exacerbation. Specifically, in the fall, when respiratory illness and exacerbation events were most frequent, several Moraxella and Haemophilus members were enriched both in virus-positive respiratory illnesses and those that progressed to exacerbations. The abundance of 2 discrete bacterial networks, characteristically comprising either Streptococcus or Staphylococcus, exhibited opposing interactions with an exacerbation-associated SMAD3 nasal epithelial transcriptional module to significantly increase the odds of subsequent exacerbation (odds ratio = 14.7, 95% confidence interval = 1.50-144, P = .02; odds ratio = 39.17, 95% confidence interval = 2.44-626, P = .008, respectively). CONCLUSIONS: Upper airway microbiomes covary with season and with seasonal trends in respiratory illnesses and asthma exacerbations. Seasonally adjusted analyses reveal specific bacteria-host interactions that significantly increase risk of asthma exacerbation in these children.

Inducible expression quantitative trait locus analysis of the MUC5AC gene in asthma in urban populations of children.

BACKGROUND: Mucus plugging can worsen asthma control, lead to reduced lung function and fatal exacerbations. MUC5AC is the secretory mucin implicated in mucus plugging, and MUC5AC gene expression has been associated with development of airway obstruction and asthma exacerbations in urban children with asthma. However, the genetic determinants of MUC5AC expression are not established. OBJECTIVES: This study sought to assess single-nucleotide polymorphisms (SNPs) that influence MUC5AC expression and relate to pulmonary functions in childhood asthma. METHODS: This study used RNA-sequencing data from upper airway samples and performed cis-expression quantitative trait loci (eQTL) and allele-specific expression analyses in 2 cohorts of predominantly Black and Hispanic urban children, a high asthma-risk birth cohort, and an exacerbation-prone asthma cohort. Inducible MUC5AC eQTLs were further investigated during incipient asthma exacerbations. Significant eQTLs SNPs were tested for associations with lung function measurements and their functional consequences were investigated in DNA regulatory databases. RESULTS: Two independent groups of SNPs in the MUC5AC gene that were significantly associated with MUC5AC expression were identified. Moreover, these SNPs showed stronger eQTL associations with MUC5AC expression during asthma exacerbations, which is consistent with inducible expression. SNPs in 1 group also showed significant association with decreased pulmonary functions. These SNPs included multiple EGR1 transcription factor binding sites, suggesting a mechanism of effect. CONCLUSIONS: These findings demonstrate the applicability of organ-specific RNA-sequencing data to determine genetic factors contributing to a key disease pathway. Specifically, they suggest important genetic variations that may underlie propensity to mucus plugging in asthma and could be important in targeted asthma phenotyping and disease management strategies.

csrT Represents a New Class of csrA-Like Regulatory Genes Associated with Integrative Conjugative Elements of Legionella pneumophila.

UNLABELLED: Bacterial evolution is accelerated by mobile genetic elements. To spread horizontally and to benefit the recipient bacteria, genes encoded on these elements must be properly regulated. Among the legionellae are multiple integrative conjugative elements (ICEs) that each encode a paralog of the broadly conserved regulator csrA. Using bioinformatic analyses, we deduced that specific csrA paralogs are coinherited with particular lineages of the type IV secretion system that mediates horizontal spread of its ICE, suggesting a conserved regulatory interaction. As a first step to investigate the contribution of csrA regulators to this class of mobile genetic elements, we analyzed here the activity of the csrA paralog encoded on Legionella pneumophila ICE-ßox. Deletion of this gene, which we name csrT, had no observed effect under laboratory conditions. However, ectopic expression of csrT abrogated the protection to hydrogen peroxide and macrophage degradation that ICE-ßox confers to L. pneumophila. When ectopically expressed, csrT also repressed L. pneumophila flagellin production and motility, a function similar to the core genome's canonical csrA. Moreover, csrT restored the repression of motility to csrA mutants of Bacillus subtilis, a finding consistent with the predicted function of CsrT as an mRNA binding protein. Since all known ICEs of legionellae encode coinherited csrA-type IV secretion system pairs, we postulate that CsrA superfamily proteins regulate ICE activity to increase their horizontal spread, thereby expanding L. pneumophila versatility. IMPORTANCE: ICEs are mobile DNA elements whose type IV secretion machineries mediate spread among bacterial populations. All surveyed ICEs within the Legionella genus also carry paralogs of the essential life cycle regulator csrA. It is striking that the csrA loci could be classified into distinct families based on either their sequence or the subtype of the adjacent type IV secretion system locus. To investigate whether ICE-encoded csrA paralogs are bona fide regulators, we analyzed ICE-ßox as a model system. When expressed ectopically, its csrA paralog inhibited multiple ICE-ßox phenotypes, as well as the motility of not only Legionella but also Bacillus subtilis. Accordingly, we predict that CsrA regulators equip legionellae ICEs to promote their spread via dedicated type IV secretion systems.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

The Gut Bacterial Community Potentiates Clostridioides difficile Infection Severity.

The severity of Clostridioides difficile infections (CDI) has increased over the last few decades. Patient age, white blood cell count, and creatinine levels as well as C. difficile ribotype and toxin genes have been associated with disease severity. However, it is unclear whether specific members of the gut microbiota are associated with variations in disease severity. The gut microbiota is known to interact with C. difficile during infection. Perturbations to the gut microbiota are necessary for C. difficile to colonize the gut. The gut microbiota can inhibit C. difficile colonization through bile acid metabolism, nutrient consumption, and bacteriocin production. Here, we sought to demonstrate that members of the gut bacterial communities can also contribute to disease severity. We derived diverse gut communities by colonizing germfree mice with different human fecal communities. The mice were then infected with a single C. difficile ribotype 027 clinical isolate, which resulted in moribundity and histopathologic differences. The variation in severity was associated with the human fecal community that the mice received. Generally, bacterial populations with pathogenic potential, such as Enterococcus, Helicobacter, and Klebsiella, were associated with more-severe outcomes. Bacterial groups associated with fiber degradation and bile acid metabolism, such as Anaerotignum, Blautia, Lactonifactor, and Monoglobus, were associated with less-severe outcomes. These data indicate that, in addition to the host and C. difficile subtype, populations of gut bacteria can influence CDI disease severity. IMPORTANCE Clostridioides difficile colonization can be asymptomatic or develop into an infection ranging in severity from mild diarrhea to toxic megacolon, sepsis, and death. Models that predict severity and guide treatment decisions are based on clinical factors and C. difficile characteristics. Although the gut microbiome plays a role in protecting against CDI, its effect on CDI disease severity is unclear and has not been incorporated into disease severity models. We demonstrated that variation in the microbiome of mice colonized with human feces yielded a range of disease outcomes. These results revealed groups of bacteria associated with both severe and mild C. difficile infection outcomes. Gut bacterial community data from patients with CDI could improve our ability to identify patients at risk of developing more severe disease and improve interventions that target C. difficile and the gut bacteria to reduce host damage.

Deep immune phenotyping reveals similarities between aging, Down syndrome, and autoimmunity.

Individuals with Down syndrome show cellular and clinical features of dysregulated aging of the immune system, including a shift from naïve to memory T cells and increased incidence of autoimmunity. However, a quantitative understanding of how various immune compartments change with age in Down syndrome remains lacking. Here, we performed deep immunophenotyping of a cohort of individuals with Down syndrome across the life span, selecting for autoimmunity-free individuals. We simultaneously interrogated age- and sex-matched healthy controls and people with type 1 diabetes as a representative autoimmune disease. We built an analytical software, IMPACD (Iterative Machine-assisted Permutational Analysis of Cytometry Data), that enabled us to rapidly identify many features of immune dysregulation in Down syndrome shared with other autoimmune diseases. We found quantitative and qualitative dysregulation of naïve CD4+ and CD8+ T cells in individuals with Down syndrome and identified interleukin-6 as a candidate driver of some of these changes, thus extending the consideration of immunopathologic cytokines in Down syndrome beyond interferons. We used immune cellular composition to generate three linear models of aging (immune clocks) trained on control participants. All three immune clocks demonstrated advanced immune aging in individuals with Down syndrome. One of these clocks, informed by Down syndrome­relevant biology, also showed advanced immune aging in individuals with type 1 diabetes. Orthologous RNA sequencing­derived immune clocks also demonstrated advanced immune aging in individuals with Down syndrome. Together, our findings demonstrate an approach to studying immune aging in Down syndrome that may have implications in other autoimmune diseases.

The Cyclin-Dependent Kinase 8 (CDK8) Inhibitor DCA Promotes a Tolerogenic Chemical Immunophenotype in CD4+ T Cells via a Novel CDK8-GATA3-FOXP3 Pathway.

Immune health requires innate and adaptive immune cells to engage precisely balanced pro- and anti-inflammatory forces. We employ the concept of chemical immunophenotypes to classify small molecules functionally or mechanistically according to their patterns of effects on primary innate and adaptive immune cells. The high-specificity, low-toxicity cyclin-dependent kinase 8 (CDK8) inhibitor 16-didehydro-cortistatin A (DCA) exerts a distinct tolerogenic profile in both innate and adaptive immune cells. DCA promotes regulatory T cells (Treg) and Th2 differentiation while inhibiting Th1 and Th17 differentiation in both murine and human cells. This unique chemical immunophenotype led to mechanistic studies showing that DCA promotes Treg differentiation in part by regulating a previously undescribed CDK8-GATA3-FOXP3 pathway that regulates early pathways of Foxp3 expression. These results highlight previously unappreciated links between Treg and Th2 differentiation and extend our understanding of the transcription factors that regulate Treg differentiation and their temporal sequencing. These findings have significant implications for future mechanistic and translational studies of CDK8 and CDK8 inhibitors.

Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes.

Human islet antigen reactive CD4+ memory T cells (IAR T cells) play a key role in the pathogenesis of autoimmune type 1 diabetes (T1D). Using single-cell RNA sequencing (scRNA-Seq) to identify T cell receptors (TCRs) in IAR T cells, we have identified a class of TCRs that share TCRα chains between individuals ("public" chains). We isolated IAR T cells from blood of healthy, new-onset T1D and established T1D donors using multiplexed CD154 enrichment and identified paired TCRαß sequences from 2767 individual cells. More than a quarter of cells shared TCR junctions between 2 or more cells ("expanded"), and 29/47 (~62%) of expanded TCRs tested showed specificity for islet antigen epitopes. Public TCRs sharing TCRα junctions were most prominent in new-onset T1D. Public TCR sequences were more germline like than expanded unique, or "private," TCRs, and had shorter junction sequences, suggestive of fewer random nucleotide insertions. Public TCRα junctions were often paired with mismatched TCRß junctions in TCRs; remarkably, a subset of these TCRs exhibited cross-reactivity toward distinct islet antigen peptides. Our findings demonstrate a prevalent population of IAR T cells with diverse specificities determined by TCRs with restricted TCRα junctions and germline-constrained antigen recognition properties. Since these "innate-like" TCRs differ from previously described immunodominant TCRß chains in autoimmunity, they have implications for fundamental studies of disease mechanisms. Self-reactive restricted TCRα chains and their associated epitopes should be considered in fundamental and translational investigations of TCRs in T1D.

Spatial Variation of the Native Colon Microbiota in Healthy Adults.

The microbiome has been implicated in the development of colorectal cancer and inflammatory bowel diseases. The specific traits of these diseases vary along the axis of the digestive tract. Further, variation in the structure of the gut microbiota has been associated with both diseases. We profiled the microbiota of the healthy proximal and distal mucosa and lumen to better understand how bacterial populations vary along the colon. We used a two-colonoscope approach to sample proximal and distal mucosal and luminal contents from the colons of 20 healthy subjects that had not undergone any bowel preparation procedure. The biopsies and home-collected stool were subjected to 16S rRNA gene sequencing, and random forest classification models were built using taxa abundance and location to identify microbiota specific to each site. The right mucosa and lumen had the most similar community structures of the five sites we considered from each subject. The distal mucosa had higher relative abundance of Finegoldia, Murdochiella, Peptoniphilus, Porphyromonas, and Anaerococcus The proximal mucosa had more of the genera Enterobacteriaceae, Bacteroides, and Pseudomonas The classification model performed well when classifying mucosal samples into proximal or distal sides (AUC = 0.808). Separating proximal and distal luminal samples proved more challenging (AUC = 0.599), and specific microbiota that differentiated the two were hard to identify. By sampling the unprepped colon, we identified distinct bacterial populations native to the proximal and distal sides. Further investigation of these bacteria may elucidate if and how these groups contribute to different disease processes on their respective sides of the colon. Cancer Prev Res; 11(7); 393-402. ©2018 AACR.

Metabolic and Community Synergy of Oral Bacteria in Colorectal Cancer.

The oral periodontopathic bacterium Fusobacterium nucleatum has been repeatedly associated with colorectal tumors. Molecular analysis has identified specific virulence factors that promote tumorigenesis in the colon. However, other oral community members, such as members of the Porphyromonas spp., are also found with F. nucleatum on colonic tumors, and thus, narrow studies of individual pathogens do not take community-wide virulence properties into account. A broader view of oral bacterial physiology and pathogenesis identifies two factors that could promote colonization and persistence of oral bacterial communities in the colon. The polymicrobial nature of oral biofilms and the asaccharolytic metabolism of many of these species make them well suited to life in the microenvironment of colonic lesions. Consideration of these two factors offers a novel perspective on the role of oral microbiota in the initiation, development, and treatment of colorectal cancer.

On the intrinsic sterility of 3D printing.

3D printers that build objects using extruded thermoplastic are quickly becoming commonplace tools in laboratories. We demonstrate that with appropriate handling, these devices are capable of producing sterile components from a non-sterile feedstock of thermoplastic without any treatment after fabrication. The fabrication process itself results in sterilization of the material. The resulting 3D printed components are suitable for a wide variety of applications, including experiments with bacteria and cell culture.

Integrative conjugative element ICE-ßox confers oxidative stress resistance to Legionella pneumophila in vitro and in macrophages.

ABSTRACT Integrative conjugative elements (ICEs) are mobile blocks of DNA that can contribute to bacterial evolution by self-directed transmission of advantageous traits. Here, we analyze the activity of a putative 65-kb ICE harbored by Legionella pneumophila using molecular genetics, conjugation assays, a phenotype microarray screen, and macrophage infections. The element transferred to a naive L. pneumophila strain, integrated site-specifically, and conferred increased resistance to oxacillin, penicillin, hydrogen peroxide, and bleach. Furthermore, the element increased survival of L. pneumophila within restrictive mouse macrophages. In particular, this ICE protects L. pneumophila from phagocyte oxidase activity, since mutation of the macrophage NADPH oxidase eliminated the fitness difference between strains that carried and those that lacked the mobile element. Renamed ICE-ßox (for ß-lactam antibiotics and oxidative stress), this transposable element is predicted to contribute to the emergence of L. pneumophila strains that are more fit in natural and engineered water systems and in macrophages. IMPORTANCE Bacteria evolve rapidly by acquiring new traits via horizontal gene transfer. Integrative conjugative elements (ICEs) are mobile blocks of DNA that encode the machinery necessary to spread among bacterial populations. ICEs transfer antibiotic resistance and other bacterial survival factors as cargo genes carried within the element. Here, we show that Legionella pneumophila, the causative agent of Legionnaires' disease, carries ICE-ßox, which enhances the resistance of this opportunistic pathogen to bleach and ß-lactam antibiotics. Moreover, L. pneumophila strains encoding ICE-ßox are more resistant to macrophages that carry phagocyte oxidase. Accordingly, ICE-ßox is predicted to increase the fitness of L. pneumophila in natural and engineered waters and in humans. To our knowledge, this is the first description of an ICE that confers oxidative stress resistance to a nosocomial pathogen.