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Objective: Obesity continues to be a major problem, despite known treatment strategies such as lifestyle modifications, pharmaceuticals, and surgical options, necessitating the development of novel weight loss approaches. The naturally occurring fatty acid, 10,12 conjugated linoleic acid (10,12 CLA), promotes weight loss by increasing fat oxidation and browning of white adipose tissue, leading to increased energy expenditure in obese mice. Coincident with weight loss, 10,12 CLA also alters the murine gut microbiota by enriching for microbes that produce short chain fatty acids (SCFAs), with concurrent elevations in fecal butyrate and plasma acetate. Methods: To determine if the observed microbiota changes are required for 10,12 CLA-mediated weight loss, adult male mice with diet-induced obesity were given broad-spectrum antibiotics (ABX) to perturb the microbiota prior to and during 10,12 CLA-mediated weight loss. Conversely, to determine whether gut microbes were sufficient to induce weight loss, conventionally-raised and germ-free mice were transplanted with cecal contents from mice that had undergone weight loss by 10,12 CLA supplementation. Results: While body weight was minimally modulated by ABX-mediated perturbation of gut bacterial populations, adult male mice given ABX were more resistant to the increased energy expenditure and fat loss that are induced by 10,12 CLA supplementation. Transplanting cecal contents from donor mice losing weight due to oral 10,12 CLA consumption into conventional or germ-free mice led to improved glucose metabolism with increased butyrate production. Conclusions: These data suggest a critical role for the microbiota in diet-modulated changes in energy balance and glucose metabolism, and distinguish the metabolic effects of orally delivered 10,12 CLA from cecal transplantation of the resulting microbiota.

Abstract Introduction: The New Jersey Kids Study (NJKS) is a transdisciplinary statewide initiative to understand influences on child health, development, and disease. We conducted a mixed-methods study of project planning teams to investigate team effectiveness and relationships between team dynamics and quality of deliverables. Methods: Ten theme-based working groups (WGs) (e.g., Neurodevelopment, Nutrition) informed protocol development and submitted final reports. WG members (n = 79, 75%) completed questionnaires including de-identified demographic and professional information and a modified TeamSTEPPS Team Assessment Questionnaire (TAQ). Reviewers independently evaluated final reports using a standardized tool. We analyzed questionnaire results and final report assessments using linear regression and performed constant comparative qualitative analysis to identify central themes. Results: WG-level factors associated with greater team effectiveness included proportion of full professors (β = 31.24, 95% CI 27.65–34.82), team size (β = 0.81, 95% CI 0.70–0.92), and percent dedicated research effort (β = 0.11, 95% CI 0.09–0.13); age distribution (β = −2.67, 95% CI –3.00 to –2.38) and diversity of school affiliations (β = –33.32, 95% CI –36.84 to –29.80) were inversely associated with team effectiveness. No factors were associated with final report assessments. Perceptions of overall initiative leadership were associated with expressed enthusiasm for future NJKS participation. Qualitative analyses of final reports yielded four themes related to team science practices: organization and process, collaboration, task delegation, and decision-making patterns. Conclusions: We identified several correlates of team effectiveness in a team science initiative's early planning phase. Extra effort may be needed to bridge differences in team members' backgrounds to enhance the effectiveness of diverse teams. This work also highlights leadership as an important component in future investigator engagement.

Abstract The human vaginal and fecal microbiota change during pregnancy. Because of the proximity of these perineal sites and the evolutionarily conserved maternal-to-neonatal transmission of the microbiota, we hypothesized that the microbiota of these two sites (rectal and vaginal) converge during the last gestational trimester as part of the preparation for parturition. To test this hypothesis, we analyzed 16S rRNA sequences from vaginal introitus and rectal samples in 41 women at gestational ages 6 and 8 months, and at 2 months post-partum. The results show that the human vaginal and rectal bacterial microbiota converged during the last gestational trimester and into the 2nd month after birth, with a significant decrease in Lactobacillus species in both sites, as alpha diversity progressively increased in the vagina and decreased in the rectum. The microbiota convergence of the maternal vaginal-anal sites perinatally might hold significance for the inter-generational transmission of the maternal microbiota.

ABSTRACT Predicting which patients are at greatest risk of severe disease from COVID-19 has the potential to improve patient outcomes and improve resource allocation. We developed machine learning models for predicting COVID-19 prognosis from a retrospective chart review of 969 hospitalized COVID-19 patients at Robert Wood Johnson University Hospital during the first pandemic wave in the United States, focusing on 77 variables from patients’ first day of hospital admission. Our best 77-variable model was better able to predict mortality (receiver operating characteristic area under the curve [ROC AUC] = 0.808) than CURB-65, a commonly used clinical prediction rule for pneumonia severity (ROC AUC = 0.722). After identifying highly predictive variables in our full models using Shapley additive explanations values, we generated two models, platelet count, lactate, age, blood urea nitrogen, aspartate aminotransferase, and C-reactive protein (PLABAC) and platelet count, red blood cell distribution width, age, blood urea nitrogen, lactate, and eosinophil count (PRABLE), that use age and five common laboratory tests to predict mortality (PLABAC: ROC AUC = 0.796, PRABLE: ROC AUC = 0.793), which also outperformed CURB-65. We externally validated PLABAC using data from the National COVID Cohort Collaborative Data Enclave from 7901 hospitalized COVID-19 patients from the pre-vaccination period and 1547 from the vaccination period, yielding ROC AUCs of 0.755 and 0.766, respectively. This study demonstrates that our models can accurately predict COVID-19 outcomes from a small number of variables obtained early in a patient’s hospital stay in patients from institutions around the United States after the initial pandemic wave. These models can serve as a clinical prediction aid and accurately capture a patient’s prognosis using a small number of routinely obtained laboratory values. IMPORTANCE COVID-19 remains the fourth leading cause of death in the United States. Predicting COVID-19 patient prognosis is essential to help efficiently allocate resources, including ventilators and intensive care unit beds, particularly when hospital systems are strained. Our PLABAC and PRABLE models are unique because they accurately assess a COVID-19 patient’s risk of death from only age and five commonly ordered laboratory tests. This simple design is important because it allows these models to be used by clinicians to rapidly assess a patient’s risk of decompensation and serve as a real-time aid when discussing difficult, life-altering decisions for patients. Our models have also shown generalizability to external populations across the United States. In short, these models are practical, efficient tools to assess and communicate COVID-19 prognosis.

Abstract People with acute COVID-19 due to SARS-CoV-2 infection experience a range of symptoms, but major factors contributing to severe clinical outcomes remain to be understood. Emerging evidence suggests associations between the gut microbiome and the severity and progression of COVID-19. To better understand the host-microbiota interactions in acute COVID-19, we characterized the intestinal microbiome of patients with active SARS-CoV-2 infection in comparison to recovered patients and uninfected healthy controls. We performed 16S rRNA sequencing of stool samples collected between May 2020 and January 2021 from 20 COVID-19-positive patients, 20 COVID-19-recovered subjects and 20 healthy controls. COVID-19-positive patients had altered microbiome community characteristics compared to the recovered and control subjects, as assessed by both α- and β-diversity differences. In COVID-19-positive patients, we observed depletion of Bacteroidaceae, Ruminococcaceae, and Lachnospiraceae, as well as decreased relative abundances of the genera Faecalibacterium, Adlercreutzia, and the Eubacterium brachy group. The enrichment of Prevotellaceae with COVID-19 infection continued after viral clearance; antibiotic use induced further gut microbiota perturbations in COVID-19-positive patients. In conclusion, we present evidence that acute COVID-19 induces gut microbiota dysbiosis with depletion of particular populations of commensal bacteria, a phenomenon heightened by antibiotic exposure, but the general effects do not persist post-recovery.

Summary: Background: The clinical outcomes of SARS-CoV-2 infection vary in severity, potentially influenced by the resident human microbiota. There is limited consensus on conserved microbiome changes in response to SARS-CoV-2 infection, with many studies focusing on severely ill individuals. This study aimed to assess the variation in the upper respiratory tract microbiome using saliva specimens in a cohort of individuals with primarily mild to moderate disease. Methods: In early 2020, a cohort of 831 adults without known SARS-CoV-2 infection was followed over a six-month period to assess the occurrence and natural history of SARS-CoV-2 infection. From this cohort, 81 participants with a SARS-CoV-2 infection, along with 57 unexposed counterparts were selected with a total of 748 serial saliva samples were collected for analysis. Total bacterial abundance, composition, population structure, and gene function of the salivary microbiome were measured using 16S rRNA gene and shotgun metagenomic sequencing. Findings: The salivary microbiome remained stable in unexposed individuals over the six-month study period, as evidenced by all measured metrics. Similarly, participants with mild to moderate SARS-CoV-2 infection showed microbiome stability throughout and after their infection. However, there were significant reductions in microbiome diversity among SARS-CoV-2-positive participants with severe symptoms early after infection. Over time, the microbiome diversity in these participants showed signs of recovery. Interpretation: These findings demonstrate the resilience of the salivary microbiome in relation to SARS-CoV-2 infection. Mild to moderate infections did not significantly disrupt the stability of the salivary microbiome, suggesting its ability to maintain its composition and function. However, severe SARS-CoV-2 infection was associated with temporary reductions in microbiome diversity, indicating the limits of microbiome resilience in the face of severe infection. Funding: This project was supported in part by Danone North America and grants from the National Institutes of Health, United States.

ABSTRACT Children delivered by elective, prelabor Cesarean section (C-section) are not exposed to the birth canal microbiota and, in relation to vaginally delivered children, show altered microbiota development. Perturbed microbial colonization during critical early-life windows of development alters metabolic and immune programming and is associated with an increased risk of immune and metabolic diseases. In nonrandomized studies, vaginal seeding of C-section-born neonates partially restores their microbiota colonization to that of their vaginally delivered counterparts, but without randomization, confounding factors cannot be excluded. In a double-blind, randomized, placebo-controlled trial, we determined the effect of vaginal seeding versus placebo seeding (control arm) on the skin and stool microbiota of elective, prelabor C-section-born neonates (n = 20) at 1 day and 1 month after birth. We also examined whether there were between-arm differences in engraftment of maternal microbes in the neonatal microbiota. In relation to the control arm, vaginal seeding increased mother-to-neonate microbiota transmission and caused compositional changes and a reduction in alpha diversity (Shannon Index) of the skin and stool microbiota. The neonatal skin and stool microbiota alpha diversity when maternal vaginal microbiota is provided is intriguing and highlights the need of larger randomized studies to determine the ecological mechanisms and effects of vaginal seeding on clinical outcomes. IMPORTANCE Children delivered by elective C-section are not exposed to the birth canal and show altered microbiota development. Impairing microbial colonization during early life alters metabolic and immune programming and is associated with an increased risk of immune and metabolic diseases. In a double-blind, randomized, placebo-controlled trial, we determined the effect of vaginal seeding on the skin and stool microbiota of elective C-section born neonates and found that vaginal seeding increased mother-to-neonate microbiota transmission and caused compositional changes and a reduction in the skin and stool microbiota diversity. The reduction of neonatal skin and stool microbiota diversity when maternal vaginal microbiota is provided is intriguing and highlights the need of larger randomized studies to determine the ecological mechanisms and effects of vaginal seeding on clinical outcomes.

Serum amyloid A (SAA) subtypes 1–3 are well-described acute phase reactants that are elevated in acute inflammatory conditions such as infection, tissue injury, and trauma, while SAA4 is constitutively expressed. SAA subtypes also have been implicated as playing roles in chronic metabolic diseases including obesity, diabetes, and cardiovascular disease, and possibly in autoimmune diseases such as systemic lupus erythematosis, rheumatoid arthritis, and inflammatory bowel disease. Distinctions between the expression kinetics of SAA in acute inflammatory responses and chronic disease states suggest the potential for differentiating SAA functions. Although circulating SAA levels can rise up to 1,000-fold during an acute inflammatory event, elevations are more modest (∼5-fold) in chronic metabolic conditions. The majority of acute-phase SAA derives from the liver, while in chronic inflammatory conditions SAA also derives from adipose tissue, the intestine, and elsewhere. In this review, roles for SAA subtypes in chronic metabolic disease states are contrasted to current knowledge about acute phase SAA. Investigations show distinct differences between SAA expression and function in human and animal models of metabolic disease, as well as sexual dimorphism of SAA subtype responses.

Summary: During postnatal development, both the maturing microbiome and the host immune system are susceptible to environmental perturbations such as antibiotic use. The impact of timing in which antibiotic exposure occurs was investigated by treating mice from days 5–9 with amoxicillin or azithromycin, two of the most commonly prescribed medications in children. Both early-life antibiotic regimens disrupted Peyer’s patch development and immune cell abundance, with a sustained decrease in germinal center formation and diminished intestinal immunoglobulin A (IgA) production. These effects were less pronounced in adult mice. Through comparative analysis of microbial taxa, Bifidobacterium longum abundance was found to be associated with germinal center frequency. When re-introduced to antibiotic-exposed mice, B. longum partially rescued the immunological deficits. These findings suggest that early-life antibiotic use affects the development of intestinal IgA-producing B cell functions and that probiotic strains could be used to restore normal development after antibiotic exposure.

Elevated C-reactive protein (CRP) levels have been associated with poorer COVID-19 outcomes. While baseline CRP levels are higher in women, obese individuals, and older adults, the relationship between CRP, sex, body mass index (BMI), age, and COVID-19 outcomes remains unknown. To investigate, we performed a retrospective analysis on 824 adult patients with COVID-19 admitted during the first pandemic wave, of whom 183 (22.2%) died. The maximum CRP value over the first five hospitalization days better predicted hospitalization outcome than the CRP level at admission, as a maximum CRP > 10 mg/dL independently quadrupled the risk of death (p < 0.001). Males (p < 0.001) and patients with a higher BMI (p = 0.001) had higher maximum CRP values, yet CRP levels did not impact their hospitalization outcome. While CRP levels did not statistically mediate any relation between sex, age, or BMI with clinical outcomes, age impacted the association between BMI and the risk of death. For patients 60 or over, a BMI < 25 kg/m2 increased the risk of death (p = 0.017), whereas the reverse was true for patients p = 0.030). Further impact of age on the association between BMI, CRP, and the risk of death could not be assessed due to a lack of statistical power but should be further investigated.

Abstract The oral microbiome has been connected with lung health and may be of significance in the progression of SARS-CoV-2 infection. Saliva-based SARS-CoV-2 tests provide the opportunity to leverage stored samples for assessing the oral microbiome. However, these collection kits have not been tested for their accuracy in measuring the oral microbiome. Saliva is highly enriched with human DNA and reducing it prior to shotgun sequencing may increase the depth of bacterial reads. We examined both the effect of saliva collection method and sequence processing on measurement of microbiome depth and diversity by 16 S rRNA gene amplicon and shotgun metagenomics. We collected 56 samples from 22 subjects. Each subject provided saliva samples with and without preservative, and a subset provided a second set of samples the following day. 16 S rRNA gene (V4) sequencing was performed on all samples, and shotgun metagenomics was performed on a subset of samples collected with preservative with and without human DNA depletion before sequencing. We observed that the beta diversity distances within subjects over time was smaller than between unrelated subjects, and distances within subjects were smaller in samples collected with preservative. Samples collected with preservative had higher alpha diversity measuring both richness and evenness. Human DNA depletion before extraction and shotgun sequencing yielded higher total and relative reads mapping to bacterial sequences. We conclude that collecting saliva with preservative may provide more consistent measures of the oral microbiome and depleting human DNA increases yield of bacterial sequences.

Abstract Background The human microbiome is inherently dynamic and its dynamic nature plays a critical role in maintaining health and driving disease. With an increasing number of longitudinal microbiome studies, scientists are eager to learn the comprehensive characterization of microbial dynamics and their implications to the health and disease-related phenotypes. However, due to the challenging structure of longitudinal microbiome data, few analytic methods are available to characterize the microbial dynamics over time. Results We propose a microbial trend analysis (MTA) framework for the high-dimensional and phylogenetically-based longitudinal microbiome data. In particular, MTA can perform three tasks: 1) capture the common microbial dynamic trends for a group of subjects at the community level and identify the dominant taxa; 2) examine whether or not the microbial overall dynamic trends are significantly different between groups; 3) classify an individual subject based on its longitudinal microbial profiling. Our extensive simulations demonstrate that the proposed MTA framework is robust and powerful in hypothesis testing, taxon identification, and subject classification. Our real data analyses further illustrate the utility of MTA through a longitudinal study in mice. Conclusions The proposed MTA framework is an attractive and effective tool in investigating dynamic microbial pattern from longitudinal microbiome studies.

Abstract Since alterations in the intestinal microbiota may induce systemic inflammation and polarization of macrophages to the M1 state, the microbiome role in atherosclerosis, an M1-driven disease, requires evaluation. We aimed to determine if antibiotic (Abx) induced alterations to the intestinal microbiota interferes with atherosclerotic plaque inflammation resolution after lipid-lowering in mice. Hyperlipidemic Apoe −/− mice were fed a western diet to develop aortic atherosclerosis with aortas then transplanted into normolipidemic wild-type (WT) mice to model clinically aggressive lipid management and promote atherosclerosis inflammation resolution. Gut microbial composition pre and post-transplant was altered via an enteral antibiotic or not. Post aortic transplant, after Abx treatment, while plaque size did not differ, compared to Apoe −/− mice, Abx– WT recipient mice had a 32% reduction in CD68-expressing cells (p = 0.02) vs. a non-significant 12% reduction in Abx+ WT mice. A trend toward an M1 plaque CD68-expresing cell phenotype was noted in Abx+ mice. By 16S rRNA sequence analysis, the Abx+ mice had reduced alpha diversity and increased Firmicutes/Bacteroidetes relative abundance ratio with a correlation between gut Firmicutes abundance and plaque CD68-expressing cell content (p

Abstract For more than a century, the prenatal environment was considered sterile. Over the last few years, findings obtained with next-generation sequencing approaches from samples of the placenta, the amniotic fluid, meconium, and even fetal tissues have challenged the dogma of a sterile womb, and additional reports have emerged that used culture, microscopy, and quantitative PCR to support the presence of a low-biomass microbial community at prenatal sites. Given the substantial implications of prenatal exposure to microbes for the development and health of the host, the findings have gathered substantial interest from academics, high impact journals, the public press, and funding agencies. However, an increasing number of studies have challenged the prenatal microbiome identifying contamination as a major issue, and scientists that remained skeptical have pointed to inconsistencies with in utero colonization, the impact of c-sections on early microbiome assembly, and the ability to generate germ-free mammals. A lively academic controversy has emerged on the existence of the wider importance of prenatal microbial communities. Microbiome has asked experts to discuss these issues and provide their thoughts on the implications. To allow for a broader perspective of this discussion, we have specifically selected scientists, who have a long-standing expertise in microbiome sciences but who have not directly been involved in the debate so far.

Abstract Background Healthcare workers (HCW) are presumed to be at increased risk of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection due to occupational exposure to infected patients. However, there has been little epidemiological research to assess these risks. Methods We conducted a prospective cohort study of HCW (n = 546) and non-healthcare workers (NHCW; n = 283) with no known prior SARS-CoV-2 infection who were recruited from a large U.S. university and two affiliated university hospitals. In this cross-sectional analysis of data collected at baseline, we examined SARS-CoV-2 infection status (as determined by presence of SARS-CoV-2 RNA in oropharyngeal swabs) by healthcare worker status and role. Results At baseline, 41 (5.0%) of the participants tested positive for SARS-CoV-2 infection, of whom 14 (34.2%) reported symptoms. The prevalence of SARS-CoV-2 infection was higher among HCW (7.3%) than in NHCW (0.4%), representing a 7.0% greater absolute risk (95% confidence interval for risk difference 4.7, 9.3%). The majority of infected HCW (62.5%) were nurses. Positive tests increased across the two weeks of cohort recruitment in line with rising confirmed cases in the hospitals and surrounding counties. Conclusions Overall, our results demonstrate that HCW had a higher prevalence of SARS-CoV-2 infection than NHCW. Continued follow-up of this cohort will enable us to monitor infection rates and examine risk factors for transmission.

Abstract Background There is increasing evidence that the intestinal microbiota plays a crucial role in the maturation of the immune system and the prevention of diseases during childhood. Early-life short-course antibiotic use may affect the progression of subsequent disease conditions by changing both host microbiota and immunologic development. Epidemiologic studies provide evidence that early-life antibiotic exposures predispose to inflammatory bowel disease (IBD). Methods By using a murine model of dextran sodium sulfate (DSS)-induced colitis, we evaluated the effect on disease outcomes of early-life pulsed antibiotic treatment (PAT) using tylosin, a macrolide and amoxicillin, a beta-lactam. We evaluated microbiota effects at the 16S rRNA gene level, and intestinal T cells by flow cytometry. Antibiotic-perturbed or control microbiota were transferred to pups that then were challenged with DSS. Results A single PAT course early-in-life exacerbated later DSS-induced colitis by both perturbing the microbial community and altering mucosal immune cell composition. By conventionalizing germ-free mice with either antibiotic-perturbed or control microbiota obtained 40 days after the challenge ended, we showed the transferrable and direct effect of the still-perturbed microbiota on colitis severity in the DSS model. Conclusions The findings in this experimental model provide evidence that early-life microbiota perturbation may increase risk of colitis later in life.

Dynamic changes of microbiome communities may play important roles in human health and diseases. The recent rise in longitudinal microbiome studies calls for statistical methods that can model the temporal dynamic patterns and simultaneously quantify the microbial interactions and community stability. Here, we propose a novel autoregressive zero-inflated mixed-effects model (ARZIMM) to capture the sparse microbial interactions and estimate the community stability. ARZIMM employs a zero-inflated Poisson autoregressive model to model the excessive zero abundances and the non-zero abundances separately, a random effect to investigate the underlining dynamic pattern shared within the group, and a Lasso-type penalty to capture and estimate the sparse microbial interactions. Based on the estimated microbial interaction matrix, we further derive the estimate of community stability, and identify the core dynamic patterns through network inference. Through extensive simulation studies and real data analyses we evaluate ARZIMM in comparison with the other methods.

Summary: We have established experimental systems to assess the effects of early-life exposures to antibiotics on the intestinal microbiota and gene expression in the brain. This model system is highly relevant to human exposure and may be developed into a preclinical model of neurodevelopmental disorders in which the gut–brain axis is perturbed, leading to organizational effects that permanently alter the structure and function of the brain. Exposing newborn mice to low-dose penicillin led to substantial changes in intestinal microbiota population structure and composition. Transcriptomic alterations implicate pathways perturbed in neurodevelopmental and neuropsychiatric disorders. There also were substantial effects on frontal cortex and amygdala gene expression by bioinformatic interrogation, affecting multiple pathways underlying neurodevelopment. Informatic analyses established linkages between specific intestinal microbial populations and the early-life expression of particular affected genes. These studies provide translational models to explore intestinal microbiome roles in the normal and abnormal maturation of the vulnerable central nervous system.

The assembly of microbial communities that populate all mucosal surfaces of the human body begins right after birth. This process is prone to disruption as newborns and young infants are increasingly exposed to antibiotics, both deliberately for therapeutic purposes, and as a consequence of transmaternal exposure.

Background: Atopic dermatitis (AD) is a common cutaneous disease, associated with imbalances in the skin microbiota.Objective: To explore the characteristics of the cutaneous microbiota and its dynamic changes during clinical treatment.Methods: Cutaneous swab samples were collected from 51 AD patients before treatment, and 40 AD patients remained after a 2-week treatment with mometasone and mupirocin.Results: AD patients exhibited significant enrichments of Prevotella and Desulfovibrio as well as obvious reductions of Corynebacterium, Streptococcus and Parabacteroides. Based on the proportion of Staphylococcus aureus, the AD patients were further classified into S. aureus-predominant group (AD.S) and S. aureus-non-dominant (AD.ND) group. The AD.S group exhibited lower skin microbial diversity and higher atopic dermatitis (SCORAD) index. In the AD.S group, the cutaneous microbial diversity significantly increased from 2.9 ± 0.8 to 3.7 ± 1.0, while the relative abundance of S. aureus decreased from 42.5 ± 20.7 to 10.3 ± 28.4 after treatment. In contrast, no significant skin microbiota changes were detected in the AD.ND group.Conclusions: AD patients with predominant S. aureus had higher disease severity and lower microbiota diversity compared to patients in the AD.ND group. Mometasone and mupirocin therapy had significant effects on skin microbiota in AD.S patients, but had a paradoxical response in the AD.ND patients.

ABSTRACT Alterations in diet can have significant impact on the host, with high-fat diet (HFD) leading to obesity, diabetes, and inflammation of the gut. Although membership and abundances in gut bacterial communities are strongly influenced by diet, substantially less is known about how viral communities respond to dietary changes. Examining fecal contents of mice as the mice were transitioned from normal chow to HFD, we found significant changes in the relative abundances and the diversity in the gut of bacteria and their viruses. Alpha diversity of the bacterial community was significantly diminished in response to the diet change but did not change significantly in the viral community. However, the diet shift significantly impacted the beta diversity in both the bacterial and viral communities. There was a significant shift away from the relatively abundant Siphoviridae accompanied by increases in bacteriophages from the Microviridae family. The proportion of identified bacteriophage structural genes significantly decreased after the transition to HFD, with a conserved loss of integrase genes in all four experimental groups. In total, this study provides evidence for substantial changes in the intestinal virome disproportionate to bacterial changes, and with alterations in putative viral lifestyles related to chromosomal integration as a result of shift to HFD. IMPORTANCE Prior studies have shown that high-fat diet (HFD) can have profound effects on the gastrointestinal (GI) tract microbiome and also demonstrate that bacteria in the GI tract can affect metabolism and lean/obese phenotypes. We investigated whether the composition of viral communities that also inhabit the GI tract are affected by shifts from normal to HFD. We found significant and reproducible shifts in the content of GI tract viromes after the transition to HFD. The differences observed in virome community membership and their associated gene content suggest that these altered viral communities are populated by viruses that are more virulent toward their host bacteria. Because HFD also are associated with significant shifts in GI tract bacterial communities, we believe that the shifts in the viral community may serve to drive the changes that occur in associated bacterial communities.

Abstract Background Microbiota and bile acids in the gastrointestinal tract profoundly alter systemic metabolic processes. In obese subjects, gradual weight loss ameliorates adipose tissue inflammation and related systemic changes. We assessed how rapid weight loss due to a very low calorie diet (VLCD) affects the fecal microbiome and fecal bile acid composition, and their interactions with the plasma metabolome and subcutaneous adipose tissue inflammation in obesity. Methods We performed a prospective cohort study of VLCD-induced weight loss of 10% in ten grades 2–3 obese postmenopausal women in a metabolic unit. Baseline and post weight loss evaluation included fasting plasma analyzed by mass spectrometry, adipose tissue transcription by RNA sequencing, stool 16S rRNA sequencing for fecal microbiota, fecal bile acids by mass spectrometry, and urinary metabolic phenotyping by 1H-NMR spectroscopy. Outcome measures included mixed model correlations between changes in fecal microbiota and bile acid composition with changes in plasma metabolite and adipose tissue gene expression pathways. Results Alterations in the urinary metabolic phenotype following VLCD-induced weight loss were consistent with starvation ketosis, protein sparing, and disruptions to the functional status of the gut microbiota. We show that the core microbiome was preserved during VLCD-induced weight loss, but with changes in several groups of bacterial taxa with functional implications. UniFrac analysis showed overall parallel shifts in community structure, corresponding to reduced abundance of the genus Roseburia and increased Christensenellaceae;g__ (unknown genus). Imputed microbial functions showed changes in fat and carbohydrate metabolism. A significant fall in fecal total bile acid concentration and reduced deconjugation and 7-α-dihydroxylation were accompanied by significant changes in several bacterial taxa. Individual bile acids in feces correlated with amino acid, purine, and lipid metabolic pathways in plasma. Furthermore, several fecal bile acids and bacterial species correlated with altered gene expression pathways in adipose tissue. Conclusions VLCD dietary intervention in obese women changed the composition of several fecal microbial populations while preserving the core fecal microbiome. Changes in individual microbial taxa and their functions correlated with variations in the plasma metabolome, fecal bile acid composition, and adipose tissue transcriptome. Trial Registration ClinicalTrials.gov NCT01699906, 4-Oct-2012, Retrospectively registered. URL-https://clinicaltrials.gov/ct2/show/NCT01699906

Abstract Background In microbiome studies, it is important to detect taxa which are associated with pathological outcomes at the lowest definable taxonomic rank, such as genus or species. Traditionally, taxa at the target rank are tested for individual association, followed by the Benjamini-Hochberg (BH) procedure to control for false discovery rate (FDR). However, this approach neglects the dependence structure among taxa and may lead to conservative results. The taxonomic tree of microbiome data represents alignment from phylum to species rank and characterizes evolutionary relationships across microbial taxa. Taxa that are closer on the tree usually have similar responses to the exposure (environment). The statistical power in microbial association tests can be enhanced by efficiently employing the prior evolutionary information via the taxonomic tree. Methods We propose a two-stage microbial association mapping framework (massMap) which uses grouping information from the taxonomic tree to strengthen statistical power in association tests at the target rank. massMap first screens the association of taxonomic groups at a pre-selected higher taxonomic rank using a powerful microbial group test OMiAT. The method then proceeds to test the association for each candidate taxon at the target rank within the significant taxonomic groups identified in the first stage. Hierarchical BH (HBH) and selected subset testing (SST) procedures are evaluated to control the FDR for the two-stage structured tests. Results Our simulations show that massMap incorporating OMiAT and the advanced FDR controlling methodologies largely alleviates the multiplicity issue. It is statistically more powerful than the traditional association mapping directly at the target rank while controlling the FDR at desired levels under most scenarios. In our real data analyses, massMap detects more or the same amount of associated species with smaller adjusted p values compared to the traditional method, which further illustrates the efficiency of the proposed framework. The R package of massMap is publicly available at https://sites.google.com/site/huilinli09/software and https://github.com/JiyuanHu/. Conclusions massMap is a novel microbial association mapping framework and achieves additional efficiency by utilizing the intrinsic taxonomic structure of microbiome data.

Abstract Background Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. Results We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. Conclusions WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Abstract Background There has been increasing interest in discovering microbial taxa that are associated with human health or disease, gathering momentum through the advances in next-generation sequencing technologies. Investigators have also increasingly employed prospective study designs to survey survival (i.e., time-to-event) outcomes, but current item-by-item statistical methods have limitations due to the unknown true association pattern. Here, we propose a new adaptive microbiome-based association test for survival outcomes, namely, optimal microbiome-based survival analysis (OMiSA). OMiSA approximates to the most powerful association test in two domains: 1) microbiome-based survival analysis using linear and non-linear bases of OTUs (MiSALN) which weighs rare, mid-abundant, and abundant OTUs, respectively, and 2) microbiome regression-based kernel association test for survival traits (MiRKAT-S) which incorporates different distance metrics (e.g., unique fraction (UniFrac) distance and Bray-Curtis dissimilarity), respectively. Results We illustrate that OMiSA powerfully discovers microbial taxa whether their underlying associated lineages are rare or abundant and phylogenetically related or not. OMiSA is a semi-parametric method based on a variance-component score test and a re-sampling method; hence, it is free from any distributional assumption on the effect of microbial composition and advantageous to robustly control type I error rates. Our extensive simulations demonstrate the highly robust performance of OMiSA. We also present the use of OMiSA with real data applications. Conclusions OMiSA is attractive in practice as the true association pattern is unpredictable in advance and, for survival outcomes, no adaptive microbiome-based association test is currently available.

Colonization of commensal bacteria is thought to impact immune development, especially in the earliest years of life. Here, the authors show, by analyzing the development of the gut microbiome of 690 children, that microbial composition at the age of 1 year is associated with asthma diagnosed in the first 5 years of life.

High or multiple doses of macrolide antibiotics, when given early in life, can perturb the metabolic and immunological development of lab mice. Here, Ruiz et al. show that even a single macrolide course, given early in life, leads to long-lasting changes in the gut microbiota and immune system of mice.

Abstract Background Increasing evidence shows the importance of the commensal microbe Oxalobacter formigenes in regulating host oxalate homeostasis, with effects against calcium oxalate kidney stone formation, and other oxalate-associated pathological conditions. However, limited understanding of O. formigenes in humans poses difficulties for designing targeted experiments to assess its definitive effects and sustainable interventions in clinical settings. We exploited the large-scale dataset from the American Gut Project (AGP) to study O. formigenes colonization in the human gastrointestinal (GI) tract and to explore O. formigenes-associated ecology and the underlying host–microbe relationships. Results In >8000 AGP samples, we detected two dominant, co-colonizing O. formigenes operational taxonomic units (OTUs) in fecal specimens. Multivariate analysis suggested that O. formigenes abundance was associated with particular host demographic and clinical features, including age, sex, race, geographical location, BMI, and antibiotic history. Furthermore, we found that O. formigenes presence was an indicator of altered host gut microbiota structure, including higher community diversity, global network connectivity, and stronger resilience to simulated disturbances. Conclusions Through this study, we identified O. formigenes colonizing patterns in the human GI tract, potential underlying host–microbe relationships, and associated microbial community structures. These insights suggest hypotheses to be tested in future experiments. Additionally, we proposed a systematic framework to study any bacterial taxa of interest to computational biologists, using large-scale public data to yield novel biological insights.

Abstract Background The role of the microbiota in human health and disease has been increasingly studied, gathering momentum through the use of high-throughput technologies. Further identification of the roles of specific microbes is necessary to better understand the mechanisms involved in diseases related to microbiome perturbations. Methods Here, we introduce a new microbiome-based group association testing method, optimal microbiome-based association test (OMiAT). OMiAT is a data-driven testing method which takes an optimal test throughout different tests from the sum of powered score tests (SPU) and microbiome regression-based kernel association test (MiRKAT). We illustrate that OMiAT efficiently discovers significant association signals arising from varying microbial abundances and different relative contributions from microbial abundance and phylogenetic information. We also propose a way to apply it to fine-mapping of diverse upper-level taxa at different taxonomic ranks (e.g., phylum, class, order, family, and genus), as well as the entire microbial community, within a newly introduced microbial taxa discovery framework, microbiome comprehensive association mapping (MiCAM). Results Our extensive simulations demonstrate that OMiAT is highly robust and powerful compared with other existing methods, while correctly controlling type I error rates. Our real data analyses also confirm that MiCAM is especially efficient for the assessment of upper-level taxa by integrating OMiAT as a group analytic method. Conclusions OMiAT is attractive in practice due to the high complexity of microbiome data and the unknown true nature of the state. MiCAM also provides a hierarchical association map for numerous microbial taxa and can also be used as a guideline for further investigation on the roles of discovered taxa in human health and disease.

ABSTRACT Early-life antibiotic exposure may provoke long-lasting microbiota perturbation. Since a healthy gut microbiota confers resistance to enteric pathogens, we hypothesized that early-life antibiotic exposure would worsen the effects of a bacterial infection encountered as an adult. To test this hypothesis, C57BL/6 mice received a 5-day course of tylosin (macrolide), amoxicillin (β-lactam), or neither (control) early in life and were challenged with Citrobacter rodentium up to 80 days thereafter. The early-life antibiotic course led to persistent alterations in the intestinal microbiota and even with pathogen challenge 80 days later worsened the subsequent colitis. Compared to exposure to amoxicillin, exposure to tylosin led to greater disease severity and microbiota perturbation. Transferring the antibiotic-perturbed microbiota to germfree animals led to worsened colitis, indicating that the perturbed microbiota was sufficient for the increased disease susceptibility. These experiments highlight the long-term effects of early-life antibiotic exposure on susceptibility to acquired pathogens. IMPORTANCE The gastrointestinal microbiota protects hosts from enteric infections; while antibiotics, by altering the microbiota, may diminish this protection. We show that after early-life exposure to antibiotics host susceptibility to enhanced Citrobacter rodentium-induced colitis is persistent and that this enhanced disease susceptibility is transferable by the antibiotic-altered microbiota. These results strongly suggest that early-life antibiotics have long-term consequences on the gut microbiota and enteropathogen infection susceptibility.

Infections caused by multidrug-resistant organisms (MDRO) lead to considerable morbidity and mortality. The elderly population residing in nursing homes are a major reservoir of MDRO. Our objective was to characterize the fecal microbiome of 82 elderly subjects from 23 nursing homes and compare their resistome to that of healthy young persons. Comparisons of microbiome composition and the resistome between subjects who acquired MDRO or not were analyzed to characterize specific microbiome disruption indices (MDI) associated with MDRO acquisition. An approach based on both 16S rRNA amplicon and whole metagenome shotgun (WMS) sequencing data was used. The microbiome of the study cohort was substantially perturbed, with Bacteroides, Firmicutes, and Proteobacteria predominating. Compared to healthy persons, the cohort of elderly persons had an increased number, abundance, and diversity of antimicrobial resistance genes. High proportions of study subjects harbored genes for multidrug-efflux pumps (96%) and linezolid resistance (52%). Among the 302 antimicrobial resistance gene families identified in any subject, 60% were exclusively detected within the study cohort, including Class D beta-lactamase genes. Subjects who acquired MDRO or not had significant differences in bacterial taxa; Odoribacter laneus, and Akkermansia muciniphila were significantly greater among subjects who did not acquire MDRO whereas Blautia hydrogenotrophica predominated among subjects who acquired MDRO. These findings suggest that specific MDI may identify persons at high risk of acquiring MDRO.

ABSTRACT Bacterial resistance to antibiotics is a pressing health issue around the world, not only in health care settings but also in the community and environment, particularly in crowded urban populations. The aim of our work was to characterize the microbial populations in sewage and the spread of antibiotic resistance within New York City (NYC). Here, we investigated the structure of the microbiome and the prevalence of antibiotic resistance genes in raw sewage samples collected from the fourteen NYC Department of Environmental Protection wastewater treatment plants, distributed across the five NYC boroughs. Sewage, a direct output of anthropogenic activity and a reservoir of microbes, provides an ecological niche to examine the spread of antibiotic resistance. Taxonomic diversity analysis revealed a largely similar and stable bacterial population structure across all the samples, which was found to be similar over three time points in an annual cycle, as well as in the five NYC boroughs. All samples were positive for the presence of the seven antibiotic resistance genes tested, based on real-time quantitative PCR assays, with higher levels observed for tetracycline resistance genes at all time points. For five of the seven genes, abundances were significantly higher in May than in February and August. This study provides characteristics of the NYC sewage resistome in the context of the overall bacterial populations. IMPORTANCE Urban sewage or wastewater is a diverse source of bacterial growth, as well as a hot spot for the development of environmental antibiotic resistance, which can in turn influence the health of the residents of the city. As part of a larger study to characterize the urban New York City microbial metagenome, we collected raw sewage samples representing three seasonal time points spanning the five boroughs of NYC and went on to characterize the microbiome and the presence of a range of antibiotic resistance genes. Through this study, we have established a baseline microbial population and antibiotic resistance abundance in NYC sewage which can prove to be very useful in studying the load of antibiotic usage, as well as for developing effective measures in antibiotic stewardship.

Infection with SARS-CoV-2 leading to COVID-19 induces hyperinflammatory and hypercoagulable states, resulting in arterial and venous thromboembolic events. Deep vein thrombosis (DVT) has been well reported in COVID-19 patients. While most DVTs occur in a lower extremity, involvement of the upper extremity is uncommon. In this report, we describe the first reported patient with an upper extremity DVT recurrence secondary to COVID-19 infection.

Helicobacter pylori is a late-in-life human pathogen with potential early-life benefits. Although H. pylori is disappearing from the human population, little is known about the influence of H. pylori on the host’s microbiota and immunity. Studying the interactions of H. pylori with murine hosts over 6 months, we found stable colonization accompanied by gastric histologic and antibody responses. Analysis of gastric and pulmonary tissues revealed increased expression of multiple immune response genes, conserved across mice and over time in the stomach and more transiently in the lungs. Moreover, H. pylori infection led to significantly different population structures in both the gastric and intestinal microbiota. These studies indicate that H. pylori influences the microbiota and host immune responses not only locally in the stomach, but distantly as well, affecting important target organs.

Coronavirus 2019 (COVID-19) has been reported to trigger Guillain–Barré syndrome (GBS). While uncommon, recurrent GBS (rGBS) episodes, triggered by antecedent viral infections, have been reported in a small proportion of GBS patients, here we describe a patient with a recurrent case of GBS, occurring secondary to COVID-19 infection. Before this patient’s episode, he had two prior GBS flares, each precipitated by a viral infection followed by complete recovery besides intermittent paresthesias. We also consider the nosology of this illness in the spectrum of rGBS and Chronic Inflammatory Demyelinating Polyneuropathy (CIDP), with their differing natural histories, prognosis, and therapeutic approaches. For patients who have a history of inflammatory demyelinating polyradiculopathies who develop COVID-19, we recommend close observation for neurologic symptoms over the next days and weeks.

The human cervicovaginal microbiota resides at an interface between the host and the environment and may affect susceptibility to disease. Puerto Rican women have high human papillomavirus (HPV) infection and cervical cancer rates. We hypothesized that the population structure of the cervicovaginal bacterial and fungal biota changed with cervical squamous intraepithelial lesions and HPV infections. DNA was extracted from cervix, introitus, and anal sites of 62 patients attending high-risk San Juan clinics. The 16S rRNA V4 region and ITS-2 fungal regions were amplified and sequenced using Illumina technology. HPV genotyping was determined by reverse hybridization with the HPV SPF10-LiPA25 kit. HPV prevalence was 84% of which ∼44% subjects were infected with high-risk HPV, ∼35% were co-infected with as many as 9 HPV types and ∼5% were infected with exclusively low-risk HPV types. HPV diversity did not change with cervical dysplasia. Cervical bacteria were more diverse in patients with CIN3 pre-cancerous lesions. We found enrichment of Atopobium vaginae and Gardnerella vaginalis in patients with CIN3 lesions. We found no significant bacterial biomarkers associated with HPV infections. Fungal diversity was significantly higher in cervical samples with high-risk HPV and introitus samples of patients with Atypical Squamous Cells of Undetermined Significance (ASCUS). Fungal biomarker signatures for vagina and cervix include Sporidiobolaceae and Sacharomyces for ASCUS, and Malassezia for high-risk HPV infections. Our combined data suggests that specific cervicovaginal bacterial and fungal populations are related to the host epithelial microenvironment, and could play roles in cervical dysplasia.

The originally published version of this Article contained an incorrect version of Figure 3 that was introduced following peer review and inadvertently not corrected during the production process. Both versions contain the same set of abundance data, but the incorrect version has the children’s asthma status erroneously disconnected from the abundance data, thereby producing the non-representative p values and graphic presentations. These errors have now been rectified, with the correct version of Figure 3 replaced in both the PDF and HTML versions of the Article.

ABSTRACT Microorganisms have shaped our planet and its inhabitants for over 3.5 billion years. Humankind has had a profound influence on the biosphere, manifested as global climate and land use changes, and extensive urbanization in response to a growing population. The challenges we face to supply food, energy, and clean water while maintaining and improving the health of our population and ecosystems are significant. Given the extensive influence of microorganisms across our biosphere, we propose that a coordinated, cross-disciplinary effort is required to understand, predict, and harness microbiome function. From the parallelization of gene function testing to precision manipulation of genes, communities, and model ecosystems and development of novel analytical and simulation approaches, we outline strategies to move microbiome research into an era of causality. These efforts will improve prediction of ecosystem response and enable the development of new, responsible, microbiome-based solutions to significant challenges of our time.

We examined how a common therapy that includes clarithromycin affects normally colonizing Staphylococcus epidermidis. Samples from the nostrils of 5 patients receiving therapy were collected before, immediately after, 1 year after, and 4 years after treatment. From each patient and sample, S. epidermidis strains were isolated and analyzed for clarithromycin susceptibility and presence of the erm(C) gene. We show that macrolide-resistant strains of S. epidermidis were selected during therapy and that the same resistant strain may persist for 4 years, in the absence of further antimicrobial treatment.

Campylobacter fetus subsp. testudinum subsp. nov. is a newly proposed subspecies of C. fetus with markers of reptile origin. We summarize epidemiologic information for 9 humans infected with this bacterium. All cases were in men, most of whom were of Asian origin. Infection might have been related to exposure to Asian foods or reptiles.

We performed polymerase chain reaction analysis, for Mycobacterium species 16S rRNA, rpoB, and IS6110 sequences, on 25 tissue specimens from patients with sarcoidosis and on 25 control tissue specimens consisting of mediastinal or cervical lymph nodes and lung biopsies. Mycobacterium species 16S rRNA sequences were amplified from 12 (48%) rpoB sequences from 6 (24%) of the sarcoidosis specimens. In total, 16S rRNA or rpoB sequences were amplified from 15 sarcoidosis specimens (60%) but were not detected in any of the control tissues (p=0.00002, Chi square). In three specimens, the sequences resembled Mycobacterium species other than M. tuberculosis. All specimens with sequences consistent with M. tuberculosis were negative for IS6110. We provide evidence that one of a variety of Mycobacterium species, especially organisms resembling M. tuberculosis, is found in most patients with sarcoidosis.

ABSTRACT The age structure of human populations is exceptional among animal species. Unlike with most species, human juvenility is extremely extended, and death is not coincident with the end of the reproductive period. We examine the age structure of early humans with models that reveal an extraordinary balance of human fertility and mortality. We hypothesize that the age structure of early humans was maintained by mechanisms incorporating the programmed death of senescent individuals, including by means of interactions with their indigenous microorganisms. First, before and during reproductive life, there was selection for microbes that preserve host function through regulation of energy homeostasis, promotion of fecundity, and defense against competing high-grade pathogens. Second, we hypothesize that after reproductive life, there was selection for organisms that contribute to host demise. While deleterious to the individual, the presence of such interplay may be salutary for the overall host population in terms of resource utilization, resistance to periodic diminutions in the food supply, and epidemics due to high-grade pathogens. We provide deterministic mathematical models based on age-structured populations that illustrate the dynamics of such relationships and explore the relevant parameter values within which population viability is maintained. We argue that the age structure of early humans was robust in its balance of the juvenile, reproductive-age, and senescent classes. These concepts are relevant to issues in modern human longevity, including inflammation-induced neoplasia and degenerative diseases of the elderly, which are a legacy of human evolution. IMPORTANCE The extended longevity of modern humans is a very recent societal artifact, although it is inherent in human evolution. The age structure of early humans was balanced by fertility and mortality, with an exceptionally prolonged juvenility. We examined the role of indigenous microbes in early humans as fundamental contributors to this age structure. We hypothesize that the human microbiome evolved mechanisms specific to the mortality of senescent individuals among early humans because their mortality contributed to the stability of the general population. The hypothesis that we present provides new bases for modern medical problems, such as inflammation-induced neoplasia and degenerative diseases of the elderly. We postulate that these mechanisms evolved because they contributed to the stability of early human populations, but their legacy is now a burden on human longevity in the changed modern world.

Guillain-Barré syndrome (GBS), an acute demyelinating peripheral neuropathy, may be triggered by an acute infectious illness; infection with Campylobacter jejuni is the most frequently reported antecedent event. In Japan, O:19 is the most common serotype among GBS-associated C. jejuni strains. To determine whether serotype O:19 occurs among GBS-associated strains in the United States and Europe, we serotyped seven such strains and found that two (29%) of seven GBS-associated strains from patients in the United States and Germany were serotype O:19. To determine whether GBS-associated strains may be resistant to killing by normal human serum (NHS), we studied the serum susceptibility of 17 GBS- and 27 enteritis-associated strains (including many O:19 and non-O:19 strains) using C. jejuni antibody positive (pool 1) or negative (pool 2) human serum. Using pool 1 serum we found that one (6%) of 18 serotype O:19 strains compared with 11 (42%) of 26 non-O:19 strains were killed; results using pool 2 serum were nearly identical. Finally, 8 O:19 and 8 non-O:19 strains were not significantly different in their ability to bind complement component C3. Serotype O:19 C. jejuni strains were overrepresented among GBS-associated strains in the United States and Germany and were significantly more serum-resistant than non-O:19 strains. The mechanism of this resistance appears unrelated to C3 binding.