Longitudinal microbiome changes in children exposed to proton pump inhibitors.

INTRODUCTION: Proton pump inhibitor (PPI) use has been associated with an increased risk of gastrointestinal and upper respiratory infections in children. There are limited longitudinal data on the effect of PPI in children. The goal of this prospective observational study was to compare the stool and oropharyngeal microbiome of children before and after starting PPIs. METHODS: We prospectively recruited participants from a gastroenterology clinic. Consented pariticpants provided stool samples and oropharyngeal swabs at baseline and after eight weeks of PPI therapy. Microbiome changes were measured by analyzing 16S sequencing from both body sites at both timepoints. RESULTS: Thirty-four participants completed the study and provided samples both at baseline and after eight weeks on PPI therapy. Of those, 24 participants had sufficient sequencing from both stool and oropharyngeal samples at both time points. There were no differences between the pre- vs post-PPI samples using beta-diversity metrics in either the oropharynx or stool. There were, however, significant changes in specific taxa. There was an enrichment of Streptococcus in the stool in after PPI-use and a reduction in the relative abundance of Bifidobacterium, Peptostreptococcus and Turicibacter (p-values < 0.01). Furthermore, there was an increase in the relative abundance of oropharyngeal bacteria in the stool after PPI therapy. This enrichment of oropharyngeal bacteria in the stool was most prominent in younger participants. DISCUSSION: Further investigation is needed to determine the clinical and microbial factors that predispose or protect against microbiome changes due to PPI-use, and why young children are more susceptible to this PPI effect.

Fast and accurate variant identification tool for sequencing-based studies.

BACKGROUND: Accurate identification of genetic variants, such as point mutations and insertions/deletions (indels), is crucial for various genetic studies into epidemic tracking, population genetics, and disease diagnosis. Genetic studies into microbiomes often require processing numerous sequencing datasets, necessitating variant identifiers with high speed, accuracy, and robustness. RESULTS: We present QuickVariants, a bioinformatics tool that effectively summarizes variant information from read alignments and identifies variants. When tested on diverse bacterial sequencing data, QuickVariants demonstrates a ninefold higher median speed than bcftools, a widely used variant identifier, with higher accuracy in identifying both point mutations and indels. This accuracy extends to variant identification in virus samples, including SARS-CoV-2, particularly with significantly fewer false negative indels than bcftools. The high accuracy of QuickVariants is further demonstrated by its detection of a greater number of Omicron-specific indels (5 versus 0) and point mutations (61 versus 48-54) than bcftools in sewage metagenomes predominated by Omicron variants. Much of the reduced accuracy of bcftools was attributable to its misinterpretation of indels, often producing false negative indels and false positive point mutations at the same locations. CONCLUSIONS: We introduce QuickVariants, a fast, accurate, and robust bioinformatics tool designed for identifying genetic variants for microbial studies. QuickVariants is available at https://github.com/caozhichongchong/QuickVariants .

An immune-competent human gut microphysiological system enables inflammation-modulation by Faecalibacterium prausnitzii.

Crosstalk of microbes with human gut epithelia and immune cells is crucial for gut health. However, there is no existing system for a long-term co-culture of human innate immune cells with epithelium and oxygen-intolerant commensal microbes, hindering the understanding of microbe-immune interactions in a controlled manner. Here, we established a gut epithelium-microbe-immune (GuMI) microphysiological system to maintain the long-term continuous co-culture of Faecalibacterium prausnitzii/Faecalibacterium duncaniae with colonic epithelium, antigen-presenting cells (APCs, herein dendritic cells and macrophages), and CD4+ naive T cells circulating underneath the colonic epithelium. In GuMI-APC condition, multiplex cytokine assays suggested that APCs contribute to the elevated level of cytokines and chemokines secreted into both apical and basolateral compartments compared to GuMI condition that lacks APC. In GuMI-APC with F. prausnitzii (GuMI-APC-FP), F. prausnitzii increased the transcription of pro-inflammatory genes such as toll-like receptor 1 (TLR1) and interferon alpha 1 (IFNA1) in the colonic epithelium, without a significant effect on cytokine secretion, compared to the GuMI-APC without bacteria (GuMI-APC-NB). In contrast, in the presence of CD4+ naive T cells (GuMI-APCT-FP), TLR1, IFNA1, and IDO1 transcription levels decreased with a simultaneous increase in F. prausnitzii-induced secretion of pro-inflammatory cytokines (e.g., IL8) compared to GuMI-APC-FP that lacks T cells. These results highlight the contribution of individual innate immune cells in regulating the immune response triggered by the gut commensal F. prausnitzii. The integration of defined populations of immune cells in the gut microphysiological system demonstrated the usefulness of GuMI physiomimetic platform to study microbe-epithelial-immune interactions in healthy and disease conditions.

Temporal dynamics of gut microbiomes in non-industrialized urban Amazonia.

Increasing levels of industrialization have been associated with changes in gut microbiome structure and loss of features thought to be crucial for maintaining gut ecological balance. The stability of gut microbial communities over time within individuals seems to be largely affected by these changes but has been overlooked among transitioning populations from low- to middle-income countries. Here, we used metagenomic sequencing to characterize the temporal dynamics in gut microbiomes of 24 individuals living an urban non-industrialized lifestyle in the Brazilian Amazon. We further contextualized our data with 165 matching longitudinal samples from an urban industrialized and a rural non-industrialized population. We show that gut microbiome composition and diversity have greater variability over time among non-industrialized individuals when compared to industrialized counterparts and that taxa may present diverse temporal dynamics across human populations. Enterotype classifications show that community types are generally stable over time despite shifts in microbiome structure. Furthermore, by tracking genomes over time, we show that levels of bacterial population replacements are more frequent among Amazonian individuals and that non-synonymous variants accumulate in genes associated with degradation of host dietary polysaccharides. Taken together, our results suggest that the stability of gut microbiomes is influenced by levels of industrialization and that tracking microbial population dynamics is important to understand how the microbiome will adapt to these transitions.IMPORTANCEThe transition from a rural or non-industrialized lifestyle to urbanization and industrialization has been linked to changes in the structure and function of the human gut microbiome. Understanding how the gut microbiomes changes over time is crucial to define healthy states and to grasp how the gut microbiome interacts with the host environment. Here, we investigate the temporal dynamics of gut microbiomes from an urban and non-industrialized population in the Amazon, as well as metagenomic data sets from urban United States and rural Tanzania. We showed that healthy non-industrialized microbiomes experience greater compositional shifts over time compared to industrialized individuals. Furthermore, bacterial strain populations are more frequently replaced in non-industrialized microbiomes, and most non-synonymous mutations accumulate in genes associated with the degradation of host dietary components. This indicates that microbiome stability is affected by transitions to industrialization, and that strain tracking can elucidate the ecological dynamics behind such transitions.

Low-level resource partitioning supports coexistence among functionally redundant bacteria during successional dynamics.

Members of microbial communities can substantially overlap in substrate use. However, what enables functionally redundant microorganisms to coassemble or even stably coexist remains poorly understood. Here, we show that during unstable successional dynamics on complex, natural organic matter, functionally redundant bacteria can coexist by partitioning low-concentration substrates even though they compete for one simple, dominant substrate. We allowed ocean microbial communities to self-assemble on leachates of the brown seaweed Fucus vesiculosus and then analyzed the competition among 10 taxonomically diverse isolates representing two distinct stages of the succession. All, but two isolates, exhibited an average of 90% ± 6% pairwise overlap in resource use, and functional redundancy of isolates from the same assembly stage was higher than that from between assembly stages, leading us to construct a simpler four-isolate community with two isolates from each of the early and late stages. We found that, although the short-term dynamics of the four-isolate communities in F. vesiculosus leachate was dependent on initial isolate ratios, in the long term, the four isolates stably coexist in F. vesiculosus leachate, albeit with some strains at low abundance. We therefore explored the potential for nonredundant substrate use by genomic content analysis and RNA expression patterns. This analysis revealed that the four isolates mainly differed in peripheral metabolic pathways, such as the ability to degrade pyrimidine, leucine, and tyrosine, as well as aromatic substrates. These results highlight the importance of fine-scale differences in metabolic strategies for supporting the frequently observed coexistence of large numbers of rare organisms in natural microbiomes.

Structured community transitions explain the switching capacity of microbial systems.

Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.

Environmental stress mediates groundwater microbial community assembly.

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and 'drift' related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. Our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

An immune-competent human gut microphysiological system enables inflammation-modulation of Faecalibacterium prausnitzii.

Crosstalk of microbes with human gut epithelia and immune cells is crucial for gut health. However, there is no existing system for a long-term co-culture of human innate immune cells with epithelium and oxygen-intolerant commensal microbes, hindering the understanding of microbe-immune interactions in a controlled manner. Here, we establish a gut epithelium-microbe-immune microphysiological system to maintain the long-term continuous co-culture of Faecalibacterium prausnitzii/Faecalibacterium duncaniae with colonic epithelium, antigen-presenting cells (APCs, herein dendritic cells and macrophages), with CD4+ naïve T cells circulating underneath the colonic epithelium. Multiplex cytokine assays suggested that APCs contribute to the elevated level of cytokines and chemokines being secreted into both apical and basolateral compartments. In contrast, the absence of APCs does not allow reliable detection of these cytokines. In the presence of APCs, F. prausnitzii increased the transcription of pro-inflammatory genes such as toll-like receptor 1 (TLR1) and interferon alpha 1 (IFNA1) in the colonic epithelium, but no significant change on the secreted cytokines. In contrast, integration of CD4+ naïve T cells reverses this effect by decreasing the transcription of TLR1, IFNA1, and indoleamine 2,3-dioxygenase, and increasing the F. prausnitzii-induced secretion of pro-inflammatory cytokines such as IL-8, MCP-1/CCL2, and IL1A. These results highlight the contribution of individual innate immune cells in the regulation of the immune response triggered by the gut commensal F. prausnitzii. The successful integration of defined populations of immune cells in this gut microphysiological system demonstrated the usefulness of the GuMI physiomimetic platform to study microbe-epithelial-immune interactions in health and disease.

Lectin-Seq: A method to profile lectin-microbe interactions in native communities.

Soluble human lectins are critical components of innate immunity. Genetic models suggest that lectins influence host-resident microbiota, but their specificity for commensal and mutualist species is understudied. Elucidating lectins' roles in regulating microbiota requires an understanding of which microbial species they bind within native communities. To profile human lectin recognition, we developed Lectin-Seq. We apply Lectin-Seq to human fecal microbiota using the soluble mannose-binding lectin (MBL) and intelectin-1 (hItln1). Although each lectin binds a substantial percentage of the samples (10 to 20%), the microbial interactomes of MBL and hItln1 differ markedly in composition and diversity. MBL binding is highly selective for a small subset of species commonly associated with humans. In contrast, hItln1's interaction profile encompasses a broad range of lower-abundance species. Our data uncover stark differences in the commensal recognition properties of human lectins.

Co-incidence of BA.1 and BA.2 at the start of Singapore's Omicron wave revealed by Community and University Campus wastewater surveillance.

Wastewater surveillance (WWS) has been globally recognised to be a useful tool in quantifying SARS-CoV-2 RNA at the community and residential levels without biases associated with case-reporting. The emergence of variants of concern (VOCs) have given rise to an unprecedented number of infections even though populations are increasingly vaccinated. This is because VOCs have been reported to possess higher transmissibility and can evade host immune responses. The B.1.1.529 lineage (Omicron) has severely disrupted global plans to return to normalcy. In this study, we developed an allele-specific (AS) RT-qPCR assay which simultaneously targets the stretch of deletions and mutations in the spike protein from position 24-27 for quantitative detection of Omicron BA.2. Together with previous assays that detect mutations associated with Omicron BA.1 (deletion at position 69 and 70) and all Omicron (mutation at position 493 and 498), we report the validation and time series of these assays from September 2021 to May 2022 using influent samples from two wastewater treatment plants and across four University campus sites in Singapore. Viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases, AS RT-qPCR assays revealed co-incidence of Omicron BA.1 and BA.2 on 12 January 2022, almost two months after initial BA.1 detection in South Africa and Botswana. BA.2 became the dominant variant by the end of January 2022 and completely displaced BA.1 by mid-March 2022. University campus sites were similarly positive for BA.1 and/or BA.2 in the same week as first detection at the treatment plants, where BA.2 became rapidly established as the dominant lineage within three weeks. These results corroborate clinical incidence of the Omicron lineages in Singapore and indicate minimal silent circulation prior to January 2022. The subsequent simultaneous spread of both variant lineages followed strategic relaxation of safe management measures upon meeting nationwide vaccination goals.

Higher alpha diversity and Lactobacillus blooms are associated with better engraftment after Fecal Microbiota Transplant in Inflammatory Bowel Disease.

Background: Fecal Microbiota Transplant (FMT) has proven effective in treating recurrent Clostridioides difficile infection (rCDI) and has shown some success in treating inflammatory bowel diseases (IBD). There is emerging evidence that host engraftment of donor taxa is a tenet of successful FMT. However, there is little known regarding predictors of engraftment. We undertook a double-blind, randomized, placebo-controlled pilot study to characterize the response to FMT in children and young adults with mild to moderate active Crohn's disease (CD) and ulcerative colitis (UC). Results: Subjects with CD or UC were randomized to receive antibiotics and weekly FMT or placebo in addition to baseline medications. The treatment arm received seven days of antibiotics followed by FMT enema and then capsules weekly for seven weeks. We enrolled four subjects with CD and 11 with UC, ages 14-29 years. Due to weekly stool sampling, we were able to create a time series of alpha diversity, beta diversity and engraftment as they related to clinical response. Subjects exhibited a wide range of microbial diversity and donor engraftment as FMT progressed. Specifically, engraftment ranged from 26% to 90% at week 2 and 3% to 92% at two months. Consistent with the current literature, increases over time of both alpha diversity (p< 0.05) and donor engraftment (p< 0.05) correlated with improved clinical response. Additionally, our weekly time series enabled an investigation into the clinical and microbial correlates of engraftment at various time points. We discovered that the post-antibiotic but pre-FMT time point, often overlooked in FMT trials, was rich in microbial correlates of eventual engraftment. Greater residual alpha diversity after antibiotic treatment was positively correlated with engraftment and subsequent clinical response. Interestingly, a transient rise in the relative abundance of Lactobacillus was also positively correlated with engraftment, a finding that we recapitulated with our analysis of another FMT trial with publicly available weekly sequencing data. Conclusions: We found that higher residual alpha diversity and Lactobacillus blooms after antibiotic treatment correlated with improved engraftment and clinical response to FMT. Future studies should closely examine the host microbial communities pre-FMT and the impact of antibiotic preconditioning on engraftment and response.

Contextualizing Wastewater-Based surveillance in the COVID-19 vaccination era.

SARS-CoV-2 wastewater-based surveillance (WBS) offers a tool for cost-effective oversight of a population's infections. In the past two years, WBS has proven to be crucial for managing the pandemic across different geographical regions. However, the changing context of the pandemic due to high levels of COVID-19 vaccination warrants a closer examination of its implication towards SARS-CoV-2 WBS. Two main questions were raised: 1) Does vaccination cause shedding of viral signatures without infection? 2) Does vaccination affect the relationship between wastewater and clinical data? To answer, we review historical reports of shedding from viral vaccines in use prior to the COVID-19 pandemic including for polio, rotavirus, influenza and measles infection and provide a perspective on the implications of different COVID-19 vaccination strategies with regard to the potential shedding of viral signatures into the sewershed. Additionally, we reviewed studies that looked into the relationship between wastewater and clinical data and how vaccination campaigns could have affected the relationship. Finally, analyzing wastewater and clinical data from the Netherlands, we observed changes in the relationship concomitant with increasing vaccination coverage and switches in dominant variants of concern. First, that no vaccine-derived shedding is expected from the current commercial pipeline of COVID-19 vaccines that may confound interpretation of WBS data. Secondly, that breakthrough infections from vaccinated individuals contribute significantly to wastewater signals and must be interpreted in light of the changing dynamics of shedding from new variants of concern.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities.

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) will have greater value as an important diagnostic tool. An in-depth analysis and understanding of the metrics derived from WWS is required to interpret and utilize WWS-acquired data effectively (McClary-Gutierrez et al., 2021; O'Keeffe, 2021). In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven cities in Canada over periods ranging from 8 to 21 months. This work demonstrates that significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing (resulting in a reduction to testing access and a reduction in the number of daily tests) in these communities, despite increases in the wastewater signal. Furthermore, the WC ratio decreased significantly in 6 of the 7 studied locations, serving as a potential signal of the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community (40-60 % allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community (40-60 % allelic proportion). Finally, a significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant's greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when community immunity was high. The WC ratio, used as an additional monitoring metric, could complement clinical case counts and wastewater signals as individual metrics in its potential ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.

A conserved Bacteroidetes antigen induces anti-inflammatory intestinal T lymphocytes.

The microbiome contributes to the development and maturation of the immune system. In response to commensal bacteria, intestinal CD4+ T lymphocytes differentiate into functional subtypes with regulatory or effector functions. The development of small intestine intraepithelial lymphocytes that coexpress CD4 and CD8αα homodimers (CD4IELs) depends on the microbiota. However, the identity of the microbial antigens recognized by CD4+ T cells that can differentiate into CD4IELs remains unknown. We identified ß-hexosaminidase, a conserved enzyme across commensals of the Bacteroidetes phylum, as a driver of CD4IEL differentiation. In a mouse model of colitis, ß-hexosaminidase-specific lymphocytes protected against intestinal inflammation. Thus, T cells of a single specificity can recognize a variety of abundant commensals and elicit a regulatory immune response at the intestinal mucosa.

Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities.

Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.

Maternal Microbiota Modulate a Fragile X-like Syndrome in Offspring Mice.

Maternal microbial dysbiosis has been implicated in adverse postnatal health conditions in offspring, such as obesity, cancer, and neurological disorders. We observed that the progeny of mice fed a Westernized diet (WD) with low fiber and extra fat exhibited higher frequencies of stereotypy, hyperactivity, cranial features and lower FMRP protein expression, similar to what is typically observed in Fragile X Syndrome (FXS) in humans. We hypothesized that gut dysbiosis and inflammation during pregnancy influenced the prenatal uterine environment, leading to abnormal phenotypes in offspring. We found that oral in utero supplementation with a beneficial anti-inflammatory probiotic microbe, Lactobacillus reuteri, was sufficient to inhibit FXS-like phenotypes in offspring mice. Cytokine profiles in the pregnant WD females showed that their circulating levels of pro-inflammatory cytokine interleukin (Il)-17 were increased relative to matched gravid mice and to those given supplementary L. reuteri probiotic. To test our hypothesis of prenatal contributions to this neurodevelopmental phenotype, we performed Caesarian (C-section) births using dissimilar foster mothers to eliminate effects of maternal microbiota transferred during vaginal delivery or nursing after birth. We found that foster-reared offspring still displayed a high frequency of these FXS-like features, indicating significant in utero contributions. In contrast, matched foster-reared progeny of L. reuteri-treated mothers did not exhibit the FXS-like typical features, supporting a key role for microbiota during pregnancy. Our findings suggest that diet-induced dysbiosis in the prenatal uterine environment is strongly associated with the incidence of this neurological phenotype in progeny but can be alleviated by addressing gut dysbiosis through probiotic supplementation.

Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater.

On November 26, 2021, the B.1.1.529 COVID-19 variant was classified as the Omicron variant of concern (VOC). Reports of higher transmissibility and potential immune evasion triggered flight bans and heightened health control measures across the world to stem its distribution. Wastewater-based surveillance has demonstrated to be a useful complement for clinical community-based tracking of SARS-CoV-2 variants. Using design principles of our previous assays that detect SARS-CoV-2 variants (Alpha and Delta), we developed an allele-specific RT-qPCR assay which simultaneously targets the stretch of mutations from Q493R to Q498R for quantitative detection of the Omicron variant in wastewater. We report their validation against 10-month longitudinal samples from the influent of a wastewater treatment plant in Italy. SARS-CoV-2 RNA concentrations and variant frequencies in wastewater determined using these variant assays agree with clinical cases, revealing rapid displacement of the Delta variant by the Omicron variant within three weeks. These variant trends, when mapped against vaccination rates, support clinical studies that found the rapid emergence of SARS-CoV-2 Omicron variant being associated with an infection advantage over Delta in vaccinated persons. These data reinforce the versatility, utility and accuracy of these open-sourced methods using allele-specific RT-qPCR for tracking the dynamics of variant displacement in communities through wastewater for informed public health responses.

High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome.

Characterizing complex microbial communities with single-cell resolution has been a long-standing goal of microbiology. We present Microbe-seq, a high-throughput method that yields the genomes of individual microbes from complex microbial communities. We encapsulate individual microbes in droplets with microfluidics and liberate their DNA, which we then amplify, tag with droplet-specific barcodes, and sequence. We explore the human gut microbiome, sequencing more than 20,000 microbial single-amplified genomes (SAGs) from a single human donor and coassembling genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe microbial interactions, reconstructing the horizontal gene transfer (HGT) network and observing HGT between 92 species pairs; we also identify a significant in vivo host-phage association between crAssphage and one strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.