The Past and Future Biology of the Human Microbiome in an Age of Extinctions.

The evolutionary fate of humans is intimately linked with that of our microbiome. Medical and technological advances have caused large-scale changes in the composition and maturation of human-associated microbial communities, increasing our susceptibility to infectious and developmental diseases. Restoration of the human microbiome must become a priority for biomedicine.

Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences.

Acquisition of the intestinal microbiota begins at birth, and a stable microbial community develops from a succession of key organisms. Disruption of the microbiota during maturation by low-dose antibiotic exposure can alter host metabolism and adiposity. We now show that low-dose penicillin (LDP), delivered from birth, induces metabolic alterations and affects ileal expression of genes involved in immunity. LDP that is limited to early life transiently perturbs the microbiota, which is sufficient to induce sustained effects on body composition, indicating that microbiota interactions in infancy may be critical determinants of long-term host metabolic effects. In addition, LDP enhances the effect of high-fat diet induced obesity. The growth promotion phenotype is transferrable to germ-free hosts by LDP-selected microbiota, showing that the altered microbiota, not antibiotics per se, play a causal role. These studies characterize important variables in early-life microbe-host metabolic interaction and identify several taxa consistently linked with metabolic alterations. PAPERCLIP:

The potential importance of the built-environment microbiome and its impact on human health.

There is increasing evidence that interactions between microbes and their hosts not only play a role in determining health and disease but also in emotions, thought, and behavior. Built environments greatly influence microbiome exposures because of their built-in highly specific microbiomes coproduced with myriad metaorganisms including humans, pets, plants, rodents, and insects. Seemingly static built structures host complex ecologies of microorganisms that are only starting to be mapped. These microbial ecologies of built environments are directly and interdependently affected by social, spatial, and technological norms. Advances in technology have made these organisms visible and forced the scientific community and architects to rethink gene-environment and microbe interactions respectively. Thus, built environment design must consider the microbiome, and research involving host-microbiome interaction must consider the built-environment. This paradigm shift becomes increasingly important as evidence grows that contemporary built environments are steadily reducing the microbial diversity essential for human health, well-being, and resilience while accelerating the symptoms of human chronic diseases including environmental allergies, and other more life-altering diseases. New models of design are required to balance maximizing exposure to microbial diversity while minimizing exposure to human-associated diseases. Sustained trans-disciplinary research across time (evolutionary, historical, and generational) and space (cultural and geographical) is needed to develop experimental design protocols that address multigenerational multispecies health and health equity in built environments.

Alzheimer's Disease Has Its Origins in Early Life via a Perturbed Microbiome.

Alzheimer's disease (AD) is a neurodegenerative disorder with limited therapeutic options. Accordingly, new approaches for prevention and treatment are needed. One focus is the human microbiome, the consortium of microorganisms that live in and on us, which contributes to human immune, metabolic, and cognitive development and that may have mechanistic roles in neurodegeneration. AD and Alzheimer's disease-related dementias (ADRD) are recognized as spectrum disorders with complex pathobiology. AD/ADRD onset begins before overt clinical signs, but initiation triggers remain undefined. We posit that disruption of the normal gut microbiome in early life leads to a pathological cascade within septohippocampal and cortical brain circuits. We propose investigation to understand how early-life microbiota changes may lead to hallmark AD pathology in established AD/ADRD models. Specifically, we hypothesize that antibiotic exposure in early life leads to exacerbated AD-like disease endophenotypes that may be amenable to specific microbiological interventions. We propose suitable models for testing these hypotheses.

Quantifying bacterial evolution in the wild: A birthday problem for Campylobacter lineages.

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the 'birthday problem'. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time frame-analogous to a shared birthday-and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species.

The hygiene hypothesis, the COVID pandemic, and consequences for the human microbiome.

The COVID-19 pandemic has the potential to affect the human microbiome in infected and uninfected individuals, having a substantial impact on human health over the long term. This pandemic intersects with a decades-long decline in microbial diversity and ancestral microbes due to hygiene, antibiotics, and urban living (the hygiene hypothesis). High-risk groups succumbing to COVID-19 include those with preexisting conditions, such as diabetes and obesity, which are also associated with microbiome abnormalities. Current pandemic control measures and practices will have broad, uneven, and potentially long-term effects for the human microbiome across the planet, given the implementation of physical separation, extensive hygiene, travel barriers, and other measures that influence overall microbial loss and inability for reinoculation. Although much remains uncertain or unknown about the virus and its consequences, implementing pandemic control practices could significantly affect the microbiome. In this Perspective, we explore many facets of COVID-19-induced societal changes and their possible effects on the microbiome, and discuss current and future challenges regarding the interplay between this pandemic and the microbiome. Recent recognition of the microbiome's influence on human health makes it critical to consider both how the microbiome, shaped by biosocial processes, affects susceptibility to the coronavirus and, conversely, how COVID-19 disease and prevention measures may affect the microbiome. This knowledge may prove key in prevention and treatment, and long-term biological and social outcomes of this pandemic.

The Microbiome and Infectious Diseases.

Our perception of microbes has considerably changed since the recognition of their pathogenic potential in the 19th century. The discovery of antibiotics and their subsequent widespread adoption have substantially altered the landscape of medicine, providing us with treatment options for many infectious diseases and enabling the deployment of previously risky interventions (eg, surgical procedures and chemotherapy), while also leading to the rise of AMR. The latter is commonly viewed as the predominant downside of antibiotic use. However, with the increasing recognition that all metazoan organisms rely on a community of microbes (the microbiota) for normal development and for most physiologic processes, the negative impacts of antibiotic use now extend well beyond AMR. Using the iceberg as a metaphor, we argue that the effects of antibiotics on AMR represent the tip of the iceberg, with much greater repercussions stemming from their role in the rise of so-called noncommunicable diseases (including obesity, diabetes, allergic and autoimmune diseases, neurodevelopmental disorders, and certain cancers). We highlight some of the emerging science around the intersection of the microbiome, antibiotic use, and health (including biological costs and future therapeutic avenues), and we advocate a more nuanced approach in evaluating the impacts of proposed antibiotic use, especially in the setting of preexposure and postexposure prophylaxis.

Intranasal administration of Acinetobacter lwoffii in a murine model of asthma induces IL-6-mediated protection associated with cecal microbiota changes.

BACKGROUND: Early-life exposure to certain environmental bacteria including Acinetobacter lwoffii (AL) has been implicated in protection from chronic inflammatory diseases including asthma later in life. However, the underlying mechanisms at the immune-microbe interface remain largely unknown. METHODS: The effects of repeated intranasal AL exposure on local and systemic innate immune responses were investigated in wild-type and Il6-/- , Il10-/- , and Il17-/- mice exposed to ovalbumin-induced allergic airway inflammation. Those investigations were expanded by microbiome analyses. To assess for AL-associated changes in gene expression, the picture arising from animal data was supplemented by in vitro experiments of macrophage and T-cell responses, yielding expression and epigenetic data. RESULTS: The asthma preventive effect of AL was confirmed in the lung. Repeated intranasal AL administration triggered a proinflammatory immune response particularly characterized by elevated levels of IL-6, and consequently, IL-6 induced IL-10 production in CD4+ T-cells. Both IL-6 and IL-10, but not IL-17, were required for asthma protection. AL had a profound impact on the gene regulatory landscape of CD4+ T-cells which could be largely recapitulated by recombinant IL-6. AL administration also induced marked changes in the gastrointestinal microbiome but not in the lung microbiome. By comparing the effects on the microbiota according to mouse genotype and AL-treatment status, we have identified microbial taxa that were associated with either disease protection or activity. CONCLUSION: These experiments provide a novel mechanism of Acinetobacter lwoffii-induced asthma protection operating through IL-6-mediated epigenetic activation of IL-10 production and with associated effects on the intestinal microbiome.

Toward a Universal Unit for Quantification of Antibiotic Resistance Genes in Environmental Samples.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the "One-Health" framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.

Accounting for variation in and overuse of antibiotics among humans.

Worldwide, antibiotic use is increasing, but many infections against which antibiotics are applied are not even caused by bacteria. Over-the-counter and internet sales preclude physician oversight. Regional differences, between and within countries highlight many potential factors influencing antibiotic use. Taking a systems perspective that considers pharmaceutical commodity chains, we examine antibiotic overuse from the vantage point of both sides of the therapeutic relationship. We examine patterns and expectations of practitioners and patients, institutional policies and pressures, the business strategies of pharmaceutical companies and distributors, and cultural drivers of variation. Solutions to improve antibiotic stewardship include practitioners taking greater responsibility for their antibiotic prescribing, increasing the role of caregivers as diagnosticians rather than medicine providers, improving their communication to patients about antibiotic treatment consequences, lessening the economic influences on prescribing, and identifying antibiotic alternatives.

Oral and gastric microbiome in relation to gastric intestinal metaplasia.

Evidence suggests that Helicobacter pylori plays a role in gastric cancer (GC) initiation. However, epidemiologic studies on the specific role of other bacteria in the development of GC are lacking. We conducted a case-control study of 89 cases with gastric intestinal metaplasia (IM) and 89 matched controls who underwent upper gastrointestinal endoscopy at three sites affiliated with NYU Langone Health. We performed shotgun metagenomic sequencing using oral wash samples from 89 case-control pairs and antral mucosal brushing samples from 55 case-control pairs. We examined the associations of relative abundances of bacterial taxa and functional pathways with IM using conditional logistic regression with and without elastic-net penalty. Compared with controls, oral species Peptostreptococcus stomatis, Johnsonella ignava, Neisseria elongata and Neisseria flavescens were enriched in cases (odds ratios [ORs] = 1.29-1.50, P = .004-.01) while Lactobacillus gasseri, Streptococcus mutans, S parasanguinis and S sanguinis were under-represented (ORs = 0.66-0.76, P = .006-.042) in cases. Species J ignava and Filifactor alocis in the gastric microbiota were enriched (ORs = 3.27 and 1.43, P = .005 and .035, respectively), while S mutans, S parasanguinis and S sanguinis were under-represented (ORs = 0.61-0.75, P = .024-.046), in cases compared with controls. The lipopolysaccharide and ubiquinol biosynthesis pathways were more abundant in IM, while the sugar degradation pathways were under-represented in IM. The findings suggest potential roles of certain oral and gastric microbiota, which are correlated with regulation of pathways associated with inflammation, in the development of gastric precancerous lesions.

Community- Versus Health Care Organization-Based Approaches to Expanding At-Home COVID-19 Testing in Black and Latino Communities, New Jersey, 2021.

At-home COVID-19 testing offers convenience and safety advantages. We evaluated at-home testing in Black and Latino communities through an intervention comparing community-based organization (CBO) and health care organization (HCO) outreach. From May through December 2021, 1100 participants were recruited, 94% through CBOs. The odds of COVID-19 test requests and completions were significantly higher in the HCO arm. The results showed disparities in test requests and completions related to age, race, language, insurance, comorbidities, and pandemic-related challenges. Despite the popularity of at-home testing, barriers exist in underresourced communities. (Am J Public Health. 2022;112(S9):S918-S922. https://doi.org/10.2105/AJPH.2022.306989).

Joint modeling of zero-inflated longitudinal proportions and time-to-event data with application to a gut microbiome study.

Recent studies have suggested that the temporal dynamics of the human microbiome may have associations with human health and disease. An increasing number of longitudinal microbiome studies, which record time to disease onset, aim to identify candidate microbes as biomarkers for prognosis. Owing to the ultra-skewness and sparsity of microbiome proportion (relative abundance) data, directly applying traditional statistical methods may result in substantial power loss or spurious inferences. We propose a novel joint modeling framework [JointMM], which is comprised of two sub-models: a longitudinal sub-model called zero-inflated scaled-beta generalized linear mixed-effects regression to depict the temporal structure of microbial proportions among subjects; and a survival sub-model to characterize the occurrence of an event and its relationship with the longitudinal microbiome proportions. JointMM is specifically designed to handle the zero-inflated and highly skewed longitudinal microbial proportion data and examine whether the temporal pattern of microbial presence and/or the nonzero microbial proportions are associated with differences in the time to an event. The longitudinal sub-model of JointMM also provides the capacity to investigate how the (time-varying) covariates are related to the temporal microbial presence/absence patterns and/or the changing trend in nonzero proportions. Comprehensive simulations and real data analyses are used to assess the statistical efficiency and interpretability of JointMM.

Immunization against poly-N-acetylglucosamine reduces neutrophil activation and GVHD while sparing microbial diversity.

Microbial invasion into the intestinal mucosa after allogeneic hematopoietic cell transplantation (allo-HCT) triggers neutrophil activation and requires antibiotic interventions to prevent sepsis. However, antibiotics lead to a loss of microbiota diversity, which is connected to a higher incidence of acute graft-versus-host disease (aGVHD). Antimicrobial therapies that eliminate invading bacteria and reduce neutrophil-mediated damage without reducing the diversity of the microbiota are therefore highly desirable. A potential solution would be the use of antimicrobial antibodies that target invading pathogens, ultimately leading to their elimination by innate immune cells. In a mouse model of aGVHD, we investigated the potency of active and passive immunization against the conserved microbial surface polysaccharide poly-N-acetylglucosamine (PNAG) that is expressed on numerous pathogens. Treatment with monoclonal or polyclonal antibodies to PNAG (anti-PNAG) or vaccination against PNAG reduced aGVHD-related mortality. Anti-PNAG treatment did not change the intestinal microbial diversity as determined by 16S ribosomal DNA sequencing. Anti-PNAG treatment reduced myeloperoxidase activation and proliferation of neutrophil granulocytes (neutrophils) in the ileum of mice developing GVHD. In vitro, anti-PNAG treatment showed high antimicrobial activity. The functional role of neutrophils was confirmed by using neutrophil-deficient LysMcreMcl1fl/fl mice that had no survival advantage under anti-PNAG treatment. In summary, the control of invading bacteria by anti-PNAG treatment could be a novel approach to reduce the uncontrolled neutrophil activation that promotes early GVHD and opens a new avenue to interfere with aGVHD without affecting commensal intestinal microbial diversity.

Determinants and Dynamics of SARS-CoV-2 Infection in a Diverse Population: 6-Month Evaluation of a Prospective Cohort Study.

BACKGROUND: We studied risk factors, antibodies, and symptoms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a diverse, ambulatory population. METHODS: A prospective cohort (n = 831) previously undiagnosed with SARS-CoV-2 infection underwent serial testing (SARS-CoV-2 polymerase chain reaction, immunoglobulin G [IgG]) for 6 months. RESULTS: Ninety-three participants (11.2%) tested SARS-CoV-2-positive: 14 (15.1%) asymptomatic, 24 (25.8%) severely symptomatic. Healthcare workers (n = 548) were more likely to become infected (14.2% vs 5.3%; adjusted odds ratio, 2.1; 95% confidence interval, 1.4-3.3) and severely symptomatic (29.5% vs 6.7%). IgG antibodies were detected after 79% of asymptomatic infections, 89% with mild-moderate symptoms, and 96% with severe symptoms. IgG trajectories after asymptomatic infections (slow increases) differed from symptomatic infections (early peaks within 2 months). Most participants (92%) had persistent IgG responses (median 171 days). In multivariable models, IgG titers were positively associated with symptom severity, certain comorbidities, and hospital work. Dyspnea and neurologic changes (including altered smell/taste) lasted ≥ 120 days in ≥ 10% of affected participants. Prolonged symptoms (frequently more severe) corresponded to higher antibody levels. CONCLUSIONS: In a prospective, ethnically diverse cohort, symptom severity correlated with the magnitude and trajectory of IgG production. Symptoms frequently persisted for many months after infection.Clinical Trials Registration. NCT04336215.

Microbial trend analysis for common dynamic trend, group comparison, and classification in longitudinal microbiome study.

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.

Estimating and testing the microbial causal mediation effect with high-dimensional and compositional microbiome data.

MOTIVATION: Recent microbiome association studies have revealed important associations between microbiome and disease/health status. Such findings encourage scientists to dive deeper to uncover the causal role of microbiome in the underlying biological mechanism, and have led to applying statistical models to quantify causal microbiome effects and to identify the specific microbial agents. However, there are no existing causal mediation methods specifically designed to handle high dimensional and compositional microbiome data. RESULTS: We propose a rigorous Sparse Microbial Causal Mediation Model (SparseMCMM) specifically designed for the high dimensional and compositional microbiome data in a typical three-factor (treatment, microbiome and outcome) causal study design. In particular, linear log-contrast regression model and Dirichlet regression model are proposed to estimate the causal direct effect of treatment and the causal mediation effects of microbiome at both the community and individual taxon levels. Regularization techniques are used to perform the variable selection in the proposed model framework to identify signature causal microbes. Two hypothesis tests on the overall mediation effect are proposed and their statistical significance is estimated by permutation procedures. Extensive simulated scenarios show that SparseMCMM has excellent performance in estimation and hypothesis testing. Finally, we showcase the utility of the proposed SparseMCMM method in a study which the murine microbiome has been manipulated by providing a clear and sensible causal path among antibiotic treatment, microbiome composition and mouse weight. AVAILABILITY AND IMPLEMENTATION: https://sites.google.com/site/huilinli09/software and https://github.com/chanw0/SparseMCMM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evidence for Environmental-Human Microbiota Transfer at a Manufacturing Facility with Novel Work-related Respiratory Disease.

Rationale: Workers' exposure to metalworking fluid (MWF) has been associated with respiratory disease.Objectives: As part of a public health investigation of a manufacturing facility, we performed a cross-sectional study using paired environmental and human sampling to evaluate the cross-pollination of microbes between the environment and the host and possible effects on lung pathology present among workers.Methods: Workplace environmental microbiota were evaluated in air and MWF samples. Human microbiota were evaluated in lung tissue samples from workers with respiratory symptoms found to have lymphocytic bronchiolitis and alveolar ductitis with B-cell follicles and emphysema, in lung tissue samples from control subjects, and in skin, nasal, and oral samples from 302 workers from different areas of the facility. In vitro effects of MWF exposure on murine B cells were assessed.Measurements and Main Results: An increased similarity of microbial composition was found between MWF samples and lung tissue samples of case workers compared with control subjects. Among workers in different locations within the facility, those that worked in the machine shop area had skin, nasal, and oral microbiota more closely related to the microbiota present in the MWF samples. Lung samples from four index cases and skin and nasal samples from workers in the machine shop area were enriched with Pseudomonas, the dominant taxa in MWF. Exposure to used MWF stimulated murine B-cell proliferation in vitro, a hallmark cell subtype found in the pathology of index cases.Conclusions: Evaluation of a manufacturing facility with a cluster of workers with respiratory disease supports cross-pollination of microbes from MWF to humans and suggests the potential for exposure to these microbes to be a health hazard.

Gut microbiota and metabolites in the pathogenesis of endocrine disease.

Type 1 diabetes (T1D) and Hashimoto's thyroiditis (HT) are the two most common autoimmune endocrine diseases that have rising global incidence. These diseases are caused by the immune-mediated destruction of hormone-producing endocrine cells, pancreatic beta cells and thyroid follicular cells, respectively. Both genetic predisposition and environmental factors govern the onset of T1D and HT. Recent evidence strongly suggests that the intestinal microbiota plays a role in accelerating or preventing disease progression depending on the compositional and functional profile of the gut bacterial communities. Accumulating evidence points towards the interplay between the disruption of gut microbial homeostasis (dysbiosis) and the breakdown of host immune tolerance at the onset of both diseases. In this review, we will summarize the major recent findings about the microbiome alterations associated with T1D and HT, and the connection of these changes to disease states. Furthermore, we will discuss the potential mechanisms by which gut microbial dysbiosis modulates the course of the disease, including disruption of intestinal barrier integrity and microbial production of immunomodulatory metabolites. The aim of this review is to provide broad insight into the role of gut microbiome in the pathophysiology of these diseases.