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The female reproductive tract (FRT) microbiome plays an important role in maintaining vaginal health. Viruses play a key role in regulating other microbial ecosystems, but little is known about how the FRT viruses (virome), particularly bacteriophages, impacts FRT health and dysbiosis. We hypothesize that bacterial vaginosis is associated with alterations in the FRT virome, and these changes correlate with bacteriome shifts. We conducted a retrospective, longitudinal analysis of vaginal swabs collected from 54 bacterial vaginosis (BV)-positive and 46 BV-negative South African women. Bacteriome analysis revealed samples clustered into five distinct bacterial community groups (CG). Bacterial alpha diversity was significantly associated with BV. Virome analysis on a subset of baseline samples showed FRT bacteriophages clustering into novel viral state types (VSTs), a viral community clustering system based on virome composition and abundance. Distinct BV bacteriophage signatures included increased alpha diversity along with Bacillus, Burkholderia and Escherichia bacteriophages. Discriminate bacteriophage-bacteria transkingdom associations were also identified between Bacillus and Burkholderia viruses and BV-associated bacteria, providing key insight for future studies elucidating transkingdom interactions driving BV-associated microbiome perturbations. In this cohort, bacteriophage-bacterial associations suggest complex interactions which may play a role in the establishment and maintenance of BV.

Untreated tooth decays affect nearly one third of the world and is the most prevalent disease burden among children. The disease progression of tooth decay is multifactorial and involves a prolonged decrease in pH, resulting in the demineralization of tooth surfaces. Bacterial species that are capable of fermenting carbohydrates contribute to the demineralization process by the production of organic acids. The combined use of machine learning and 16s rRNA sequencing offers the potential to predict tooth decay by identifying the bacterial community that is present in an individual’s oral cavity. A few recent studies have demonstrated machine learning predictive modeling using 16s rRNA sequencing of oral samples, but they lack consideration of the multifactorial nature of tooth decay, as well as the role of fungal species within their models. Here, the oral microbiome of mother–child dyads (both healthy and caries-active) was used in combination with demographic–environmental factors and relevant fungal information to create a multifactorial machine learning model based on the LASSO-penalized logistic regression. For the children, not only were several bacterial species found to be caries-associated (Prevotella histicola, Streptococcus mutans, and Rothia muciloginosa) but also Candida detection and lower toothbrushing frequency were also caries-associated. Mothers enrolled in this study had a higher detection of S. mutans and Candida and a higher plaque index. This proof-of-concept study demonstrates the significant impact machine learning could have in prevention and diagnostic advancements for tooth decay, as well as the importance of considering fungal and demographic–environmental factors.

Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infections and hospital visits during infancy and childhood. Although risk factors for RSV infection have been identified, the role of microbial species in the respiratory tract is only partially known. We aimed to understand the impact of interactions between the nasal microbiome and host transcriptome on the severity and clinical outcomes of RSV infection. We used 16 S rRNA sequencing to characterize the nasal microbiome of infants with RSV infection. We used RNA sequencing to interrogate the transcriptome of CD4+ T cells obtained from the same set of infants. After dimension reduction through principal component (PC) analysis, we performed an integrative analysis to identify significant co-variation between microbial clade and gene expression PCs. We then employed LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples) to estimate the clade-gene association patterns for each infant. Our network-based integrative analysis identified several clade-gene associations significantly related to the severity of RSV infection. The microbial taxa with the highest loadings in the implicated clade PCs included Moraxella, Corynebacterium, Streptococcus, Haemophilus influenzae, and Staphylococcus. Interestingly, many of the genes with the highest loadings in the implicated gene PCs are encoded in mitochondrial DNA, while others are involved in the host immune response. This study on microbiome-transcriptome interactions provides insights into how the host immune system mounts a response against RSV and specific infectious agents in nasal microbiota.

Dietary fibres can exert beneficial anti-inflammatory effects through microbially fermented short-chain fatty acid metaboliteslt;supgt;1,2lt;/supgt;, although the immunoregulatory roles of most fibre diets and their microbiota-derived metabolites remain poorly defined. Here, using microbial sequencing and untargeted metabolomics, we show that a diet of inulin fibre alters the composition of the mouse microbiota and the levels of microbiota-derived metabolites, notably bile acids. This metabolomic shift is associated with type 2 inflammation in the intestine and lungs, characterized by IL-33 production, activation of group 2 innate lymphoid cells and eosinophilia. Delivery of cholic acid mimics inulin-induced type 2 inflammation, whereas deletion of the bile acid receptor farnesoid X receptor diminishes the effects of inulin. The effects of inulin are microbiota dependent and were reproduced in mice colonized with human-derived microbiota. Furthermore, genetic deletion of a bile-acid-metabolizing enzyme in one bacterial species abolishes the ability of inulin to trigger type 2 inflammation. Finally, we demonstrate that inulin enhances allergen- and helminth-induced type 2 inflammation. Taken together, these data reveal that dietary inulin fibre triggers microbiota-derived cholic acid and type 2 inflammation at barrier surfaces with implications for understanding the pathophysiology of allergic inflammation, tissue protection and host defence.

As the most common chronic disease in preschool children in the United States, early childhood caries (ECC) has a profound impact on a child’s quality of life, represents a tremendous human and economic burden to society, and disproportionately affects those living in poverty. Caries risk assessment (CRA) is a critical component of ECC management, yet the accuracy, consistency, reproducibility, and longitudinal validation of the available risk assessment techniques are lacking. Molecular and microbial biomarkers represent a potential source for accurate and reliable dental caries risk and onset. Next-generation nucleotide-sequencing technology has made it feasible to profile the composition of the oral microbiota. In the present study, 16S ribosomal RNA (rRNA) gene sequencing was applied to saliva samples that were collected at 6-mo intervals for 24 mo from a subset of 56 initially caries-free children from an ongoing cohort of 189 children, aged 1 to 3 y, over the 2-y study period; 36 children developed ECC and 20 remained caries free. Analyses from machine learning models of microbiota composition, across the study period, distinguished between affected and nonaffected groups at the time of their initial study visits with an area under the receiver operating characteristic curve (AUC) of 0.71 and discriminated ECC-converted from healthy controls at the visit immediately preceding ECC diagnosis with an AUC of 0.89, as assessed by nested cross-validation. Rothia mucilaginosa, Streptococcus sp., and Veillonella parvula were selected as important discriminatory features in all models and represent biomarkers of risk for ECC onset. These findings indicate that oral microbiota as profiled by high-throughput 16S rRNA gene sequencing is predictive of ECC onset.

Background Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. The causes and correlates of severe illness in the majority of infants are poorly defined. Methods We recruited a cohort of RSV-infected infants and simultaneously assayed the molecular status of their airways and the presence of airway microbiota. We used rigorous statistical approaches to identify gene expression patterns associated with disease severity and microbiota composition, separately and in combination. Results We measured comprehensive airway gene expression patterns in 106 infants with primary RSV infection. We identified an airway gene expression signature of severe illness dominated by excessive chemokine expression. We also found an association between Haemophilus influenzae, disease severity, and airway lymphocyte accumulation. Exploring the time of onset of clinical symptoms revealed acute activation of interferon signaling following RSV infection in infants with mild or moderate illness, which was absent in subjects with severe illness. Conclusions Our data reveal that airway gene expression patterns distinguish mild/moderate from severe illness. Furthermore, our data identify biomarkers that may be therapeutic targets or useful for measuring efficacy of intervention responses.

RationaleRespiratory Syncytial Virus (RSV) infection is a leading cause of infant respiratory disease and hospitalization. Infant airway microbiota occupying the nasopharynx have been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease severity and infection susceptibility, are not well understood.ObjectivesTo characterize associations between the nasal microbiota and RSV infection before, during, and after infants’ first respiratory illness.MethodsNasal 16S rRNA microbial community profiling of two cohorts of infants in the first year of life: 1) a cross-sectional cohort of 89 RSV infected infants sampled during illness and 102 population matched healthy controls, and 2) an individually matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled at time points before, during, and after infection.Measurements and Main ResultsWe identified 12 taxa significantly associated with RSV infection. All 12 were differentially abundant during infection, with seven differentially abundant prior to infection, and eight differentially abundant after infection. Eight of these taxa were associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs. infected than of disease severity.ConclusionsOur findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with first-time RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and the impact of RSV infection on microbiota composition. Identified taxa represent appealing targets for additional translationally-oriented research.

Non-invasive diagnostics for Staphylococcus aureus musculoskeletal infections (MSKI) remain challenging. Antibodies from newly activated, pathogen-specific plasmablasts in human blood, which emerge during an ongoing infection, can be utilized for diagnosing and tracking treatment response in diabetic foot infections. Utilizing multianalyte immunoassays on medium enriched for newly synthesized antibodies (MENSA) from antibody secreting cells (ASCs), we assessed anti-S. aureus IgG responses in 101 MSKI patients (63 culture-confirmed S. aureus, 38 S. aureus negative), and 52 healthy controls. MENSA IgG levels were assessed for their ability to identify the presence and type of S. aureus MSKI utilizing machine learning and multivariate receiver operating characteristics (ROC). Eleven S. aureus infected patients presented with prosthetic joint infections (PJI), 15 with fracture-related infections (FRI), 5 with native joint septic arthritis (SEP), 15 with diabetic foot infections (DFI) and 17 with suspected orthopaedic infections in the soft tissue (SSTIs). Anti-S. aureus MENSA IgG levels in patients with non-S. aureus infections and healthy controls were 4-fold (***p=0.0002) and 8-fold (****p

Candida albicans is an opportunistic fungal organism frequently detected in the oral cavity of children with severe early childhood caries (S-ECC). Previous studies suggested the cariogenic potential of C. albicans, in vitro and in vivo, and further demonstrated its synergistic interactions with Streptococcus mutans. In combination, the 2 organisms are associated with higher caries severity in a rodent model. However, it remains unknown whether C. albicans influences the composition and diversity of the entire oral bacterial community to promote S-ECC onset. With 16s rRNA amplicon sequencing, this study analyzed the microbiota of saliva and supragingival plaque from 39 children (21 S-ECC and 18 caries-free [CF]) and 33 mothers (17 S-ECC and 16 CF). The results revealed that the presence of oral C. albicans is associated with a highly acidogenic and acid-tolerant bacterial community in S-ECC, with an increased abundance of plaque Streptococcus (particularly S. mutans) and certain Lactobacillus/Scardovia species and salivary/plaque Veillonella and Prevotella, as well as decreased levels of salivary/plaque Actinomyces. Concurrent with this microbial community assembly, the activity of glucosyltransferases (cariogenic virulence factors secreted by S. mutans) in plaque was significantly elevated when C. albicans was present. Moreover, the oral microbial community composition and diversity differed significantly by disease group (CF vs. S-ECC) and sample source (saliva vs. plaque). Children and mothers within the CF and S-ECC groups shared microbiota composition and diversity, suggesting a strong maternal influence on children’s oral microbiota. Altogether, this study underscores the importance of C. albicans in association with the oral bacteriome in the context of S-ECC etiopathogenesis. Further longitudinal studies are warranted to examine how fungal-bacterial interactions modulate the onset and severity of S-ECC, potentially leading to novel anticaries treatments that address fungal contributions.

Respiratory syncytial virus (RSV) infection results in millions of hospitalizations and thousands of deaths each year. Variations in the adaptive and innate immune response appear to be associated with RSV severity. To investigate the host response to RSV infection in infants, we performed a systems-level study of RSV pathophysiology, incorporating high-throughput measurements of the peripheral innate and adaptive immune systems and the airway epithelium and microbiota. We implemented a novel multi-omic data integration method based on multilayered principal component analysis, penalized regression, and feature weight back-propagation, which enabled us to identify cellular pathways associated with RSV severity. In both airway and immune cells, we found an association between RSV severity and activation of pathways controlling Th17 and acute phase response signaling, as well as inhibition of B cell receptor signaling. Dysregulation of both the humoral and mucosal response to RSV may play a critical role in determining illness severity., Author summary This paper presents a novel approach to understanding the localized molecular responses to respiratory syncytial virus (RSV) and the system-level correlates of clinical outcomes. To do this, we developed a novel statistical method able to integrate high dimensional molecular data characterizing the host airway microbota and immune and nasal gene expression. We show that this integrative approach facilitates superior performance in estimating clinical outcome as opposed to any single data type. Using this approach, we identified both cell type-specific and shared biomarkers and regulatory pathways associated with RSV severity. Specifically, we identified an association between RSV severity, activation of pathways controlling Th17, and inhibition of B cell receptor signaling, which were present in both the site of infection airway and in peripheral immune cells. These results can guide future efforts to identify biomarkers for identifying or predicting illness severity following infant RSV infection. They may also be useful as biomarkers to inform the efficacy of future interventions (e.g., therapies) or preventative measures to suppress the rate of severe disease (e.g., vaccines).

Neonatal immune-microbiota co-development is poorly understood, yet appropriate recognition of – and response to – pathogens and commensal microbiota is critical to health. In this longitudinal study of 148 pre- and 119 full-term infants from birth through one year of age we found that postmenstrual age, or weeks from conception, not post-natal age, is the dominant factor influencing T cell and mucosal microbiota development. Numerous features of the T cell and microbiota functional development remain unexplained, however, by either age metric and are instead shaped by discrete peri- and post-natal events. Most strikingly, we establish that prenatal antibiotics or infection disrupt the normal T cell population developmental trajectory, influencing subsequent respiratory microbial colonization and predicting respiratory morbidity. In this way, early exposures imprint the postnatal immune-microbiota axis and place an infant at significant risk for respiratory morbidity in early childhood.One Sentence SummaryT cells and microbiota follow predictable, coordinated trajectories in newborns, and their coordination is an important determinant of illness in the first year.Graphical AbstractNasal and rectal microbiome was assessed weekly in the NICU, monthly post-discharge, and when respiratory illness symptoms occurred. T cells were characterized at birth (cord blood), 36-42 weeks postmenstrual age, and at 12 months. Quarterly respiratory morbidity surveys determined the 12-month outcome of persistent respiratory disease. More frequent illnesses and chronic disease outcomes occurred by one year of age if development of these systems was discordant or disrupted.

Background: The majority of infants hospitalized with primary respiratory syncytial virus (RSV) infection have no obvious risk factors for severe disease. Objective: The aim of this study (Assessing Predictors of Infant RSV Effects and Severity, AsPIRES) was to identify factors associated with severe disease in full-term healthy infants younger than 10 months with primary RSV infection. Methods: RSV infected infants were enrolled from 3 cohorts during consecutive winters from August 2012 to April 2016 in Rochester, New York. A birth cohort was prospectively enrolled and followed through their first winter for development of RSV infection. An outpatient supplemental cohort was enrolled in the emergency department or pediatric offices, and a hospital cohort was enrolled on admission with RSV infection. RSV was diagnosed by reverse transcriptase-polymerase chain reaction. Demographic and clinical data were recorded and samples collected for assays: buccal swab (cytomegalovirus polymerase chain reaction, PCR), nasal swab (RSV qualitative PCR, complete viral gene sequence, 16S ribosomal ribonucleic acid [RNA] amplicon microbiota analysis), nasal wash (chemokine and cytokine assays), nasal brush (nasal respiratory epithelial cell gene expression using RNA sequencing [RNAseq]), and 2 to 3 ml of heparinized blood (flow cytometry, RNAseq analysis of purified cluster of differentiation [CD]4+, CD8+, B cells and natural killer cells, and RSV-specific antibody). Cord blood (RSV-specific antibody) was also collected for the birth cohort. Univariate and multivariate logistic regression will be used for analysis of data using a continuous Global Respiratory Severity Score (GRSS) as the outcome variable. Novel statistical methods will be developed for integration of the large complex datasets. Results: A total of 453 infants were enrolled into the 3 cohorts; 226 in the birth cohort, 60 in the supplemental cohort, and 78 in the hospital cohort. A total of 126 birth cohort infants remained in the study and were evaluated for 150 respiratory illnesses. Of the 60 RSV positive infants in the supplemental cohort, 42 completed the study, whereas all 78 of the RSV positive hospital cohort infants completed the study. A GRSS was calculated for each RSV-infected infant and is being used to analyze each of the complex datasets by correlation with disease severity in univariate and multivariate methods. Conclusions: The AsPIRES study will provide insights into the complex pathogenesis of RSV infection in healthy full-term infants with primary RSV infection. The analysis will allow assessment of multiple factors potentially influencing the severity of RSV infection including the level of RSV specific antibodies, the innate immune response of nasal epithelial cells, the adaptive response by various lymphocyte subsets, the resident airway microbiota, and viral factors. Results of this study will inform disease interventions such as vaccines and antiviral therapies.

Respiratory syncytial virus (RSV) is the leading cause of severe respiratory disease in infants. Other than age at the time of infection, the causes and correlates of severe illness in infants lacking known risk factors are poorly defined. We recruited a cohort of confirmed RSV-infected infants and simultaneously assayed the presence of resident airway microbiota and the molecular status of their airways using a novel method. Rigorous statistical analyses identified a molecular airway gene expression signature of severe illness dominated by excessive chemokine expression. Global 16S rRNA sequencing confirmed an association between H. influenzae and clinical severity. Interestingly, adjusting for H. influenzae in our gene expression analysis revealed an association between severity and airway lymphocyte accumulation. Exploring the relationship between airway gene expression and the time of onset of clinical symptoms revealed a robust, acute activation of interferon (IFN) signaling, which was absent in subjects with severe illness. Finally, we explored the relationship between IFN activity, airway gene expression and productive RSV infection using a novel in vitro model of bona fide pediatric human airway epithelial cells. Interestingly, blocking IFN signaling, but not IFN ligand production, in these cells leads to increased viral infection. Our data reveal that acute airway interferon responses are physiologically relevant in the context of infant RSV infection and may be a target for therapeutic intervention. Additionally, the airway gene expression signature we define may be useful as a biomarker for efficacy of intervention responses.

BACKGROUND The majority of infants hospitalized with primary respiratory syncytial virus (RSV) infection have no obvious risk factors for severe disease. OBJECTIVE The aim of this study (Assessing Predictors of Infant RSV Effects and Severity, AsPIRES) was to identify factors associated with severe disease in full-term healthy infants younger than 10 months with primary RSV infection. METHODS RSV infected infants were enrolled from 3 cohorts during consecutive winters from August 2012 to April 2016 in Rochester, New York. A birth cohort was prospectively enrolled and followed through their first winter for development of RSV infection. An outpatient supplemental cohort was enrolled in the emergency department or pediatric offices, and a hospital cohort was enrolled on admission with RSV infection. RSV was diagnosed by reverse transcriptase-polymerase chain reaction. Demographic and clinical data were recorded and samples collected for assays: buccal swab (cytomegalovirus polymerase chain reaction, PCR), nasal swab (RSV qualitative PCR, complete viral gene sequence, 16S ribosomal ribonucleic acid [RNA] amplicon microbiota analysis), nasal wash (chemokine and cytokine assays), nasal brush (nasal respiratory epithelial cell gene expression using RNA sequencing [RNAseq]), and 2 to 3 ml of heparinized blood (flow cytometry, RNAseq analysis of purified cluster of differentiation [CD]4+, CD8+, B cells and natural killer cells, and RSV-specific antibody). Cord blood (RSV-specific antibody) was also collected for the birth cohort. Univariate and multivariate logistic regression will be used for analysis of data using a continuous Global Respiratory Severity Score (GRSS) as the outcome variable. Novel statistical methods will be developed for integration of the large complex datasets. RESULTS A total of 453 infants were enrolled into the 3 cohorts; 226 in the birth cohort, 60 in the supplemental cohort, and 78 in the hospital cohort. A total of 126 birth cohort infants remained in the study and were evaluated for 150 respiratory illnesses. Of the 60 RSV positive infants in the supplemental cohort, 42 completed the study, whereas all 78 of the RSV positive hospital cohort infants completed the study. A GRSS was calculated for each RSV-infected infant and is being used to analyze each of the complex datasets by correlation with disease severity in univariate and multivariate methods. CONCLUSIONS The AsPIRES study will provide insights into the complex pathogenesis of RSV infection in healthy full-term infants with primary RSV infection. The analysis will allow assessment of multiple factors potentially influencing the severity of RSV infection including the level of RSV specific antibodies, the innate immune response of nasal epithelial cells, the adaptive response by various lymphocyte subsets, the resident airway microbiota, and viral factors. Results of this study will inform disease interventions such as vaccines and antiviral therapies.

Obesity is a risk factor for osteoarthritis (OA), the greatest cause of disability in the US. The impact of obesity on OA is driven by systemic inflammation, and increased systemic inflammation is now understood to be caused by gut microbiome dysbiosis. Oligofructose, a nondigestible prebiotic fiber, can restore a lean gut microbial community profile in the context of obesity, suggesting a potentially novel approach to treat the OA of obesity. Here, we report that - compared with the lean murine gut - obesity is associated with loss of beneficial Bifidobacteria, while key proinflammatory species gain in abundance. A downstream systemic inflammatory signature culminates with macrophage migration to the synovium and accelerated knee OA. Oligofructose supplementation restores the lean gut microbiome in obese mice, in part, by supporting key commensal microflora, particularly Bifidobacterium pseudolongum. This is associated with reduced inflammation in the colon, circulation, and knee and protection from OA. This observation of a gut microbiome-OA connection sets the stage for discovery of potentially new OA therapeutics involving strategic manipulation of specific microbial species inhabiting the intestinal space.

Background:Postnatal development of the microbiota in early life influences immunity, metabolism, neurodevelopment and long-term infant health. Microbiome development occurs at multiple body sites, each with distinct community compositions and functions. Associations between microbiota at multiple sites represent an unexplored influence on the infant microbiome. Here, we examined co-occurrence patterns of gut and respiratory microbiota in pre- and full-term infants over the first year of life, a period critical to neonatal development and risk of respiratory diseases.Results:Gut and respiratory microbiota collected as longitudinal rectal, throat and nasal samples from 38 pre-term and 44 full-term infants were first clustered into community state types (CSTs) on the basis of their composition. Multiple methods were used to relate the occurrence of CSTs to several measures of infant maturity, including gestational age (GA) at birth, week of life (WOL), and post menstrual age (PMA: equal to GA plus WOL). Manifestation of CSTs followed one of three patterns with respect to infant maturity. First,chronological: independent of infant maturity (GA) at birth, and strongly associated with post-natal age (WOL). Second,idiosyncratic: primarily dependent on maturity (GA) at birth, with persistent differences in CST occurrence between pre- and full-term infants through the first year of life. Third,convergent: CSTs appear earlier in infants with greater maturity (GA) at birth, but after a sufficient post-natal interval their occurrence in pre-term infants reaches parity with full-term infants. The composition of CSTs was highly dissimilar between different body sites, but the CST of any one body site was highly predictive of the CSTs at other body sites. There were significant associations between the abundance of individual taxa at each body site and the CSTs of the other body sites, which persisted after stringent control for the non-linear effects of infant maturity. Significant canonical correlations exist between the microbiota composition at each pair of body sites, with the strongest correlations between more proximal locations.Conclusion:Cross-body site associations of developing infant microbiota suggest the importance of research and clinical practices that focus on dynamic interactions between multiple microbial communities to elucidate and promote systemic microbiota development.

Background Current treatment of acute exacerbations of chronic rhinosinusitis (CRS) is driven by identification of predominant bacteria using culture-based methods and determination of antibiotic sensitivities. The objective of this study was to evaluate the response of the sinonasal microbiome to antibiotic therapy in the setting of an acute exacerbation of CRS. Methods Aspirate and swab samples for culture and DNA analysis were collected bilaterally from 8 CRS patients presenting with acute exacerbations. Patients were started on a 2-week course of a culture-directed antibiotic after sensitivities were determined. Repeat samples were taken immediately on the completion of treatment. DNA was extracted from each sample, amplified using bacterial 16S primers and sequenced. Bacterial abundance was determined by quantitative polymerase chain reaction (qPCR). Diversity metrics of the microbiota between pretreatment and posttreatment samples were calculated. Results There was significantly more bacterial DNA present in the pretreatment group than in the posttreatment group. An increase in α-diversity was found in the posttreatment group relative to the pretreatment group (p < 0.05 in each comparison) with swab sampling, but not by aspirate sampling. The predominant organism identified by 16S sequencing correlated with the culture-identified bacteria genus in each patient. Conclusion Significant differences exist in the diversity of bacteria populations during acute exacerbations of CRS and after antimicrobial treatment. After therapy, the increase in diversity is accompanied by a decrease in the total of abundance of the bacterial population.

Background Identification of factors that influence the neonatal gut microbiome is urgently needed to guide clinical practices that support growth of healthy preterm infants. Here, we examined the influence of nutrition and common practices on the gut microbiota and growth in a cohort of preterm infants. Results With weekly gut microbiota samples spanning postmenstrual age (PMA) 24 to 46 weeks, we developed two models to test associations between the microbiota, nutrition and growth: a categorical model with three successive microbiota phases (P1, P2, and P3) and a model with two periods (early and late PMA) defined by microbiota composition and PMA, respectively. The more significant associations with phase led us to use a phase-based framework for the majority of our analyses. Phase transitions were characterized by rapid shifts in the microbiota, with transition out of P1 occurring nearly simultaneously with the change from meconium to normal stool. The rate of phase progression was positively associated with gestational age at birth, and delayed transition to a P3 microbiota was associated with growth failure. We found distinct bacterial metabolic functions in P1–3 and significant associations between nutrition, microbiota phase, and infant growth. Conclusion The phase-dependent impact of nutrition on infant growth along with phase-specific metabolic functions suggests a pioneering potential for improving growth outcomes by tailoring nutrient intake to microbiota phase. Electronic supplementary material The online version of this article (10.1186/s40168-017-0377-0) contains supplementary material, which is available to authorized users.

Evaluating the potential for methylmercury (MeHg) toxicity relies on accurately predicting the mercury (Hg) body burden that results from eating fish. Hg body burden is directly determined by the slow elimination kinetics of MeHg in the human body (kel = 0.014 days-1 or t1/2 =50 days). Existing studies on MeHg half-life in humans demonstrate a wide range values (t1/2 = 30 to >150 days) and has lead to uncertainty in the derivation of a regulatory standard for acceptable daily oral intake. The causes of variation in MeHg toxicokinetics in humans remain little explored. Here we characterize variation in human MeHg metabolism and elimination rate (kel) in 37 adult volunteers who consumed 3 fish meals. We determined MeHg elimination rates via longitudinal Hg analysis in single hairs using laser ablation inductively coupled plasma mass spectrometry. We also measured MeHg metabolism (biotransformation) via speciation of fecal Hg. We find an average kel = 0.0157 days-1 (t1/2 = 44 days) amongst a more than 2-fold variation in kel across the cohort (0.0248-0.0112 days-1; t1/2 = 28-62 days). Although MeHg biotransformation varied widely between individuals, it showed a positive association with elimination rates across the cohort. A more than 2-fold change in kel over a period of 2 years was seen in some individuals. In 2 individuals, who received antibiotic for unrelated health issues, elimination rate was seen to slow significantly. Associations of kel with age, body mass index, gender, and fish eating habits were not observed. We establish that a measure of methylmercury metabolism and eliminaiton status (MerMES) can reduce uncertainty in determining an individual's MeHg toxicokinetics subsequent to eating fish.

Category: Basic Sciences/Biologics, Diabetes Introduction/Purpose: Currently, there is no sensitive and specific diagnostic tool for identifying the active pathogen in a polymicrobial environment such as diabetic foot infection (DFI). In addition, monitoring the success of antibiotic treatment is limited to clinical signs and nonspecific inflammatory markers. Consequently, surgeons are often forced to make interventional decisions without adequate prognostic information. While DFI are generally polymicrobial, about 50% prominently include Staphylococcus aureus (SA). We investigated applicability of utilizing a novel diagnostic immunoassay that measures the patient’s current production of anti-SA antibodies (IgG) to accurately diagnose SA and monitor its pathogenic activity. We hypothesize that 1) compared to standard culture, the immunoassay has a higher sensitivity to detect SA and 2) able monitor changes in pathogenic activity of SA in DFI. Methods: From July 2015 to August 2016, we enrolled 20 diabetic patients with DFU who displayed clinical symptoms and signs of infection which necessitated hospitalization and undertook initial foot salvage therapy (FST): irrigation and debridement followed by wet-to-dry dressings and 6 weeks of intravenous antibiotic treatment. At weeks 0, 4, 8 and 12, the infected DFUs samples were obtained for standard culture and 16 S rRNA microbiome analysis. Whole blood and serum samples were collected to measure the abundance of anti-SA IgG in the serum and in the in vitro secretions of antibody-secreting cells harvested from whole blood in “medium enriched for newly synthesized antibody”. Sensitivity and specificity for detection of SA were compared against the standard culture and microbiome analysis. Preliminary analyses compare the ability of the SA immunoassay to track therapy and its concordance with changes in the microbiome. Results: Of the 20 enrolled patients, 18 were available for at least partial follow-up and only four completed the entire sampling protocol. At the enrollment, 12 patients (60%) were identified positive for SA infection by at least one diagnostic method, while only 8 were diagnosed by standard culture. Six out of 10 SA-positive patients showed polymicrobial growth. The concordance rate for the presence or absence of SA was 85% between the immunoassay and microbiome, 70% between immunoassay and standard culture and 75% between microbiome and standard culture. Comparison of serial samples from the 7 subjects who were SA-positive by both the immunoassay and microbiome analysis demonstrated trends that the two novel assays provide complementary measures of therapeutic success. (Figure 1) Conclusion: Measurement of anti-SA antibodies showed higher sensitivity than standard culture and was able to monitor changes in pathogenic activity of SA in DFI undertaking salvage treatment. This novel immnoassay may serve as an important diagnostic and prognostic tools for monitoring SA infection in polymicrobial DFI. It provides important information for counseling patients of treatment response, prognosis, and determining to pursuit further foot salvage versus amputation. Future study will include expanding immunoassay measure other commonly found organisms in DFI.

The microbiome can promote or disrupt human health by influencing both adaptive and innate immune functions. We tested whether bacteria that normally reside on human skin participate in host defense by killing Staphylococcus aureus, a pathogen commonly found in patients with atopic dermatitis (AD) and an important factor that exacerbates this disease. High-throughput screening for antimicrobial activity against S. aureus was performed on isolates of coagulase-negative Staphylococcus (CoNS) collected from the skin of healthy and AD subjects. CoNS strains with antimicrobial activity were common on the normal population but rare on AD subjects. A low frequency of strains with antimicrobial activity correlated with colonization by S. aureus The antimicrobial activity was identified as previously unknown antimicrobial peptides (AMPs) produced by CoNS species including Staphylococcus epidermidis and Staphylococcus hominis These AMPs were strain-specific, highly potent, selectively killed S. aureus, and synergized with the human AMP LL-37. Application of these CoNS strains to mice confirmed their defense function in vivo relative to application of nonactive strains. Strikingly, reintroduction of antimicrobial CoNS strains to human subjects with AD decreased colonization by S. aureus These findings show how commensal skin bacteria protect against pathogens and demonstrate how dysbiosis of the skin microbiome can lead to disease.

Responses by resident cells are likely to play a key role in determining the severity of respiratory disease. However, sampling of the airways poses a significant challenge, particularly in infants and children. Here, we report a reliable method for obtaining nasal epithelial cell RNA from infants for genome-wide transcriptomic analysis and describe baseline expression characteristics in an asymptomatic cohort. Nasal epithelial cells were collected by brushing of the inferior turbinates and gene expression was interrogated by RNA-seq analysis. Reliable recovery of RNA occurred in the absence of adverse events. We observed high expression of epithelial cell markers and similarity to the transcriptome for intrapulmonary airway epithelial cells. We identified genes displaying low and high expression variability, both inherently and in response to environmental exposures. The greatest gene expression differences in this asymptomatic cohort were associated with the presence of known pathogenic viruses and/or bacteria. Robust bacteria-associated gene expression patterns were significantly associated with the presence of Moraxella. In summary, we have developed a reliable method for interrogating the infant airway transcriptome by sampling the nasal epithelium. Our data demonstrates both the fidelity and feasibility of our methodology and describes normal gene expression and variation within a healthy infant cohort.

Current treatment of acute exacerbations of chronic rhinosinusitis (CRS) is driven by identification of predominant bacteria using culture-based methods and determination of antibiotic sensitivities. The objective of this study was to evaluate the response of the sinonasal microbiome to antibiotic therapy in the setting of an acute exacerbation of CRS.Aspirate and swab samples for culture and DNA analysis were collected bilaterally from 8 CRS patients presenting with acute exacerbations. Patients were started on a 2-week course of a culture-directed antibiotic after sensitivities were determined. Repeat samples were taken immediately on the completion of treatment. DNA was extracted from each sample, amplified using bacterial 16S primers and sequenced. Bacterial abundance was determined by quantitative polymerase chain reaction (qPCR). Diversity metrics of the microbiota between pretreatment and posttreatment samples were calculated.There was significantly more bacterial DNA present in the pretreatment group than in the posttreatment group. An increase in α-diversity was found in the posttreatment group relative to the pretreatment group (p0.05 in each comparison) with swab sampling, but not by aspirate sampling. The predominant organism identified by 16S sequencing correlated with the culture-identified bacteria genus in each patient.Significant differences exist in the diversity of bacteria populations during acute exacerbations of CRS and after antimicrobial treatment. After therapy, the increase in diversity is accompanied by a decrease in the total of abundance of the bacterial population.

Development of the intestinal microbiome in preterm infants has significant impact on infant health. Our objective was to determine if duration of antibiotics within the first 10 and 30 d after birth affects the intestinal microbiome. Subjects were 24 0/7–31 6/7 wk of gestational age who received ≥50% breast milk and a total of ≥100 ml/kg of feeds by 10 d. Rectal (fecal) swabs were collected at 10 and 30 d and analyzed by 16S rRNA pyrosequencing. At both time points, we examined the rectal microbiome from infants who received only 2 d of antibiotics and those who received at least 7 d of antibiotics. In the 29 infants enrolled in our study, we found a decrease in diversity index from 10 d samples in those who received more antibiotics. Such difference in diversity and richness was not as pronounced in 30 d samples. Firmicutes and Bacteroidetes were most abundant in the 10 d samples. While these two phyla remained dominant in 30 d samples, there was an increase in Proteobacteria and Actinobacteria. Despite antibiotic therapy, neonates continued to acquire bacteria in the gastrointestinal tract. The process of bacterial acquisition is perturbed with the use of antibiotics.

The goal of this project is to improve and extend best practices in the algorithmic and biochemical identification of the function of proteins, and to make these resources available to the life science education and research communities. In the earlier phases of this project we developed the ProMOL plugin for PyMOL, a tool used to explore the catalytic site structural homologies between proteins of known function and those for which functions are not yet known, and we have applied it to examine more than 3000 structures in the Protein Data Bank for which functions are not yet known. Although catalytic site structural homology alone is not sufficient to define the function of a protein, it provides one mechanism which, when combined with other structural and sequence motifs, can suggest candidates for experimental verification. In addition, similar, non-catalytic structural motifs can be indicative of non-catalytic functions. The motif library is being extended to include NMR structures, metal ions, and non-catalytic motifs. A database of results has been established. The combination of in-silico characterization and wet-lab characterization has proven to be a suitable task for undergraduate biochemistry students and partnerships to embed this work in undergraduate curricula are being established.

Background The accumulation of protein structural data occurs more rapidly than it can be characterized by traditional laboratory means. This has motivated widespread efforts to predict enzyme function computationally. The most useful/accurate strategies employed to date are based on the detection of motifs in novel structures that correspond to a specific function. Functional residues are critical components of predictively useful motifs. We have implemented a novel method, to complement current approaches, which detects motifs solely on the basis of distance restraints between catalytic residues. Results ProMOL is a plugin for the PyMOL molecular graphics environment that can be used to create active site motifs for enzymes. A library of 181 active site motifs has been created with ProMOL, based on definitions published in the Catalytic Site Atlas (CSA). Searches with ProMOL produce better than 50% useful Enzyme Commission (EC) class suggestions for level 1 searches in EC classes 1, 4 and 5, and produce some useful results for other classes. 261 additional motifs automatically translated from Jonathan Barker’s JESS motif set [Bioinformatics 19:1644–1649, 2003] and a set of NMR motifs is under development. Alignments are evaluated by visual superposition, Levenshtein distance and root-mean-square deviation (RMSD) and are reasonably consistent with related search methods. Conclusion The ProMOL plugin for PyMOL provides ready access to template-based local alignments. Recent improvements to ProMOL, including the expanded motif library, RMSD calculations and output selection formatting, have greatly increased the program’s usability and speed, and have improved the way that the results are presented.