Affective Symptoms in Pregnancy are Associated with the Vaginal Microbiome.

Composition of the vaginal microbiome in pregnancy is associated with adverse maternal, obstetric, and child health outcomes. Identifying the sources of individual differences in the vaginal microbiome is therefore of considerable clinical and public health interest. The current study tested the hypothesis that vaginal microbiome composition during pregnancy is associated with an individual's experience of affective symptoms and stress exposure. Data were based on a prospective longitudinal study of a diverse and medically healthy community sample of 275 mother-infant pairs. Affective symptoms and stress exposure and select measures of associated biomarkers (diurnal salivary cortisol, serum measures of sex hormones) were collected at each trimester; self-report, clinical, and medical records were used to collect detailed data on socio-demographic factors and health behavior, including diet and sleep. Vaginal microbiome samples were collected in the third trimester (34-40 weeks) and characterized by 16S rRNA sequencing. Identified taxa were clustered into three community state types (CST1-3) based on dissimilarity of vaginal microbiota composition. Results indicate that depressive symptoms during pregnancy were reliably associated with individual taxa and CST3 in the third trimester. Prediction of functional potential from 16S taxonomy revealed a differential abundance of metabolic pathways in CST1-3 and individual taxa, including biosynthetic pathways for the neuroactive metabolites, serotonin and dopamine. With the exception of bioavailable testosterone, no significant associations were found between symptoms- and stress-related biomarkers and CSTs. Our results provide further evidence of how prenatal psychological distress during pregnancy alters the maternal-fetal microbiome ecosystem that may be important for understanding maternal and child health outcomes.

Longitudinal intravital imaging of the bone marrow for analysis of the race for the surface in a murine osteomyelitis model.

Critical knowledge gaps of orthopedic infections pertain to bacterial colonization. The established dogma termed the Race for the Surface posits that contaminating bacteria compete with host cells for the implant post-op, which remains unproven without real-time in vivo evidence. Thus, we modified the murine longitudinal intravital imaging of the bone marrow (LIMB) system to allow real-time quantification of green fluorescent protein (GFP+) host cells and enhanced cyan fluorescent protein (ECFP+) or red fluorescent protein (RFP+) methicillin-resistant Staphylococcus aureus (MRSA) proximal to a transfemoral implant. Following inoculation with ~105 CFU, an L-shaped metal implant was press-fit through the lateral cortex at a 90° angle ~0.150 mm below a gradient refractive index (GRIN) lens. We empirically derived a volume of interest (VOI) = 0.0161 ± 0.000675 mm3 during each imaging session by aggregating the Z-stacks between the first (superior) and last (inferior) in-focus LIMB slice. LIMB postimplantation revealed very limited bacteria detection at 1 h, but by 3 h, 56.8% of the implant surface was covered by ECFP+ bacteria, and the rest were covered by GFP+ host cells. 3D volumetric rendering of the GFP+ and ECFP+ or RFP+ voxels demonstrated exponential MRSA growth between 3 and 6 h in the Z-plane, which was validated with cross-sectional ex vivo bacterial burden analyses demonstrating significant growth by ~2 × 104 CFU/h on the implant from 2 to 12 h post-op (p < 0.05; r2 > 0.98). Collectively, these results show the competition at the surface is completed by 3 h in this model and demonstrate the potential of LIMB to elucidate mechanisms of bacterial colonization, the host immune response, and the efficacy of antimicrobials.

Rapid reduction in Staphylococcus aureus in atopic dermatitis subjects following dupilumab treatment.

BACKGROUND: Atopic dermatitis (AD) is an inflammatory disorder characterized by dominant type 2 inflammation leading to chronic pruritic skin lesions, allergic comorbidities, and Staphylococcus aureus skin colonization and infections. S aureus is thought to play a role in AD severity. OBJECTIVES: This study characterized the changes in the host-microbial interface in subjects with AD following type 2 blockade with dupilumab. METHODS: Participants (n = 71) with moderate-severe AD were enrolled in a randomized (dupilumab vs placebo; 2:1), double-blind study at Atopic Dermatitis Research Network centers. Bioassays were performed at multiple time points: S aureus and virulence factor quantification, 16s ribosomal RNA microbiome, serum biomarkers, skin transcriptomic analyses, and peripheral blood T-cell phenotyping. RESULTS: At baseline, 100% of participants were S aureus colonized on the skin surface. Dupilumab treatment resulted in significant reductions in S aureus after only 3 days (compared to placebo), which was 11 days before clinical improvement. Participants with the greatest S aureus reductions had the best clinical outcomes, and these reductions correlated with reductions in serum CCL17 and disease severity. Reductions (10-fold) in S aureus cytotoxins (day 7), perturbations in TH17-cell subsets (day 14), and increased expression of genes relevant for IL-17, neutrophil, and complement pathways (day 7) were also observed. CONCLUSIONS: Blockade of IL-4 and IL-13 signaling, very rapidly (day 3) reduces S aureus abundance in subjects with AD, and this reduction correlates with reductions in the type 2 biomarker, CCL17, and measures of AD severity (excluding itch). Immunoprofiling and/or transcriptomics suggest a role for TH17 cells, neutrophils, and complement activation as potential mechanisms to explain these findings.

Aberrant newborn T cell and microbiota developmental trajectories predict respiratory compromise during infancy.

Neonatal immune-microbiota co-development is poorly understood, yet age-appropriate recognition of - and response to - pathogens and commensal microbiota is critical to health. In this longitudinal study of 148 preterm and 119 full-term infants from birth through one year of age, we found that postmenstrual age or weeks from conception is a central 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 perinatal and postnatal 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 predict the postnatal immune-microbiota axis trajectory, placing infants at later risk for respiratory morbidity in early childhood.

Machine Learning Approach Identified Multi-Platform Factors for Caries Prediction in Child-Mother Dyads.

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.

Microbiomics of irrigation with xylitol or Lactococcus lactis in chronic rhinosinusitis.

OBJECTIVE: Topical sinonasal rinse therapies may alter the local microbiome and improve disease control in chronic rhinosinusitis (CRS). The objective of this study was to examine microbiome changes in post-surgical CRS patients when rinsing with commercially available products containing xylitol or Lactococcus lactis. METHODS: A crossover-type protocol with a washout period was designed. Swab samples from anterior ethmoid cavities of CRS patients were collected prospectively at baseline. Subjects were provided packets containing either L. lactis W136 or xylitol in non-blinded fashion and instructed to add it to their rinse bottles daily for 28 days, after which another swab was taken. A saline wash-out period was completed and a third swab taken. A final 28-day regimen of the opposite product was followed by a final swab. DNA extraction and sequencing of the 16S rRNA gene allowed for global microbiome analysis. RESULTS: We enrolled 25 subjects with CRS and 10 controls resulting in 70 adequate samples. Increased detection of Lactococcus was observed after use of L. lactis. No significant trends in alpha or beta diversity as a result of treatment were observed. SNOT-22 score did not change significantly following treatment with xylitol, L. lactis, or saline. CONCLUSION: We did not detect any major clinical or microbiome-level effect due to treatment with two topical rinse products. Further research is needed to elucidate their clinical utility and possible probiotic effect. LEVEL OF EVIDENCE: 3.

Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection.

BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of infant respiratory disease. Infant airway microbiota has 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 susceptibility and severity, are unknown. METHODS: We carried out 16S rRNA microbiota profiling of infants in the first year of life from (1) a cross-sectional cohort of 89 RSV-infected infants sampled during illness and 102 matched healthy controls, and (2) a matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled before, during, and after infection. RESULTS: We identified 12 taxa significantly associated with RSV infection. All 12 taxa were differentially abundant during infection, with 8 associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs infected than of disease severity. CONCLUSIONS: Our findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and impact of RSV infection on microbiota composition.

Neonatal gut and respiratory microbiota: coordinated development through time and space.

BACKGROUND: Postnatal development of early life microbiota influences immunity, metabolism, neurodevelopment, and infant health. Microbiome development occurs at multiple body sites, 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. 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 compositional profiles. Multiple methods were used to relate the occurrence of CSTs to temporal microbiota development and measures of infant maturity, including gestational age (GA) at birth, week of life (WOL), and post-menstrual age (PMA). Manifestation of CSTs followed one of three patterns with respect to infant maturity: (1) chronological, with CST occurrence frequency solely a function of post-natal age (WOL), (2) idiosyncratic to maturity at birth, with the interval of CST occurrence dependent on infant post-natal age but the frequency of occurrence dependent on GA at birth, and (3) convergent, in which CSTs appear first in infants of greater maturity at birth, with occurrence frequency in pre-terms converging after a post-natal interval proportional to pre-maturity. 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. Canonical correlations exist between the microbiota composition at each pair of body sites, with the strongest correlations between proximal locations. CONCLUSION: These findings suggest that early microbiota is shaped by neonatal innate and adaptive developmental responses. Temporal progression of CST occurrence is influenced by infant maturity at birth and post-natal age. Significant associations of microbiota across body sites reveal distal connections and coordinated development of the infant microbial ecosystem.

Impact of prematurity and nutrition on the developing gut microbiome and preterm infant growth.

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.

The impact of postnatal antibiotics on the preterm intestinal microbiome.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Despite antibiotic therapy, neonates continued to acquire bacteria in the gastrointestinal tract. The process of bacterial acquisition is perturbed with the use of antibiotics.

Nonclassical MHC class I-dependent invariant T cells are evolutionarily conserved and prominent from early development in amphibians.

Human and murine MHC nonclassical class Ib-restricted invariant T (iT) cell subsets, such as invariant natural killer T cells (iNKT) and mucosal-associated invariant T cells, have specialized functions early in immune responses, especially in modulating subsequent adaptive immune responses. Here, we characterize a prominent iT population in the amphibian Xenopus laevis and show the requirement of the class Ib molecule, Xenopus nonclassical gene 10, in its differentiation and function. Using Xenopus nonclassical gene 10 tetramers and RNAi loss of function by transgenesis, we identified a large class Ib-dependent CD8(-)/CD4(-) iT subset in unmanipulated frogs and tadpoles. This population is critical for antiviral immunity during early larval stages when classical MHC class Ia function is suboptimal. Furthermore, in young tadpoles with low class Ia expression, deep sequencing revealed additional preponderant invariant T cell receptor (TCR)α rearrangements, implying other iT cell subsets and a predominant selection process mediated by other class Ib molecules. The restriction and requirement of class Ib molecules for development and antiviral immunity of a mammalian iNKT or mucosal-associated invariant T cell counterpart in the amphibian Xenopus show the importance of iT cells in the emergence and evolution of the adaptive immune system.

Evolution in fast forward: a potential role for mutators in accelerating Staphylococcus aureus pathoadaptation.

Pathogen evolution and subsequent phenotypic heterogeneity during chronic infection are proposed to enhance Staphylococcus aureus survival during human infection. We tested this theory by genetically and phenotypically characterizing strains with mutations constructed in the mismatch repair (MMR) and oxidized guanine (GO) system, termed mutators, which exhibit increased spontaneous-mutation frequencies. Analysis of these mutators revealed not only strain-dependent increases in the spontaneous-mutation frequency but also shifts in mutational type and hot spots consistent with loss of GO or MMR functions. Although the GO and MMR systems are relied upon in some bacterial species to prevent reactive oxygen species-induced DNA damage, no deficit in hydrogen peroxide sensitivity was found when either of these DNA repair pathways was lost in S. aureus. To gain insight into the contribution of increased mutation supply to S. aureus pathoadaptation, we measured the rate of α-hemolysin and staphyloxanthin inactivation during serial passage. Detection of increased rates of α-hemolysin and staphyloxanthin inactivation in GO and MMR mutants suggests that these strains are capable of modifying virulence phenotypes implicated in mediating infection. Accelerated derivation of altered virulence phenotypes, combined with the absence of increased ROS sensitivity, highlights the potential of mutators to drive pathoadaptation in the host and serve as catalysts for persistent infections.

Development of pooled suppression subtractive hybridization to analyze the pangenome of Staphylococcus aureus.

We describe the development and application of a Pooled Suppression Subtractive Hybridization (PSSH) method to describe differences between the genomic content of a pool of clinical Staphylococcus aureus isolates and a sequenced reference strain. In comparative bacterial genomics, Suppression Subtractive Hybridization (SSH) is normally utilized to compare genomic features or expression profiles of one strain versus another, which limits its ability to analyze communities of isolates. However, a PSSH approach theoretically enables the user to characterize the entirety of gene content unique to a related group of isolates in a single reaction. These unique fragments may then be linked to individual isolates through standard PCR. This method was applied to examine the genomic diversity found in pools of S.aureus isolates associated with complicated bacteremia infections leading to endocarditis and osteomyelitis. Across four pools of 10 isolates each, four hundred and twenty seven fragments not found in or significantly divergent from the S. aureus NCTC 8325 reference genome were detected. These fragments could be linked to individual strains within its pool by PCR. This is the first use of PSSH to examine the S. aureus pangenome. We propose that PSSH is a powerful tool for researchers interested in rapidly comparing the genomic content of multiple unstudied isolates.