FEMS Microbes

Characterizing the household bacterial microbiome allows for a stronger understanding of the various microbes that a person is exposed to everyday in their home. Exploring household microbiomes in different countries around the world increases - our understanding of the impact cultural differences might have on niche microbial communities in the house. The goal of this study was to use shotgun metagenomics to characterize the microbiome for ten locations around the home in ten different houses from three different countries (Mysuru, India; Dubai, United Arab Emirates (UAE); and Tucson, United States of America (USA)). There was a significant difference in alpha diversity between the three countries (ANOVA, p<0.05) with homes in Mysuru, India showing significantly higher bacterial diversity compared to Dubai, UAE and Tucson, AZ, USA. Beta diversity analysis of the homes found that bacterial communities significantly differed between cities (PERMANOVA, p<0.01) and within cities by household locations (PERMANOVA, p<0.001). Locations such as underneath the toilet rim, bathroom and kitchen sinks had the highest levels of bacterial diversity across the three cities compared to other sampling areas. A core microbiome of Actinomycetes and Gammaproteobacteria was found in all homes in all three cities. Within each city, a core microbiome was identified at the species level within specific household locations in each city. Over 90% of bacterial taxa found in the homes were a part of the human-associated phyla Actinomycetes (eg. genera Brevibacterium, Corynebacterium, and Microbacterium), Pseudomonadota (eg. genera Acinetobacter, Moraxella, Pantoea, Paracoccus, and Psuedomonas), and Bacillota (genus Streptococcus), which was comparable to previous studies. The household microbiome is variable in different locations in the house and on a global scale. Factors such as human activity, cultural practices, climate, and surface type and use may drive this diversity. Characterizing the household microbiome on a global scale allows for a better understanding of what drives microbial diversity, increasing our understanding of how microbial communities are shaped by the environment and how humans influence their dynamics, as well as any risks to human health that the built microbiome may potentially pose. Impact StatementThis research contributes to the understanding of the built microbiome, specifically how it varies within the house, within cities, and across the globe. This can aid in our understanding of microbial dynamics in environments with heavy human influence and help develop and improve hygiene habits and products which are mindful of the existing microbiome. Data SummaryDNA sequence data from this research is publicly available on the NCBIs Sequence Read Archive under BioProject PRJNA1416920. Data was analyzed using python and R code. Analysis protocols and information on software versions, packages, and more can be found within the text and in the following github repository: https://github.com/carolinescranton01/Global_Household_Microbiome. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

The Imperial Palace in Tokyo serves as a significant reservoir of biodiversity within the urban landscape; however, its soil microbial communities remain uncharacterized despite decades of macro-biological surveys. This study presents the first dataset profiling the soil microbiome of the Imperial Palace Outer Gardens, utilizing both 16S rRNA amplicon and shotgun metagenomic sequencing to fill this knowledge gap. We collected bulk soil samples from four distinct sites, including pond sediments and soils beneath ginkgo and pine trees, to capture a range of environmental conditions within this conserved greenspace. Both 16S rRNA amplicon sequencing and shotgun metagenomic sequencing revealed that Pseudomonadota and Actinomycetota were the predominant phyla across all samples. Notably, sites with monoculture vegetation, such as those beneath pine trees, exhibited lower microbial diversity than other locations. Functional annotation identified core metabolic pathways and detected specific antimicrobial resistance and virulence factor genes in selected samples. These datasets provide a critical baseline for future research into urban ecosystem dynamics, soil health, and the intersection of environmental conservation and public health.

Urbanization is a leading cause of global biodiversity loss, but its impact on soil microorganisms and biogeochemistry remains uncertain. To address this gap, we investigate urban soil microbiome composition using metagenomic sequences from the Global Urban Soil Environment Ecology Network (GLUSEEN). We seek to reveal (1) changes in taxonomic composition and functional potential and (2) ubiquitous (core) taxa and metabolisms across the urban soil microbiome. We hypothesize that soil taxonomic and functional diversity are correlated due to the unique selective pressures of the urban ecosystem, and that the potential for carbon, nutrient, and pollutant cycling is a key feature of the urban soil microbiome. We find that Baltimore soil microbiomes are distinct from all other cities, displaying the highest taxonomic and lowest functional diversity. Only 66.3% of taxonomic and functional composition is correlated across all cities, highlighting differing functional potential within similar soil microbial taxa. Metabolic processes involving carbon and nitrogen cycling are abundant, as well as xenobiotic degradation. Core urban microbiota include many common soil bacteria and methane- and nitrogen-cycling archaea. Understanding the predominant characteristics of microbial taxonomy and functional potential in urban soils will aid in understanding feedback between growing metropolitan areas and processes driving climate change. Sentence summaryTaxonomic and functional potential of global urban soil microbiomes are partially decoupled and reveal ubiquitous potential for contaminant cycling. Feature image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/592449v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@133e122org.highwire.dtl.DTLVardef@1019556org.highwire.dtl.DTLVardef@f36fc7org.highwire.dtl.DTLVardef@2f952e_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundBuilt environment microbiome studies have identified numerous factors that shape indoor microbiomes, yet the reproducibility of these findings across buildings, timepoints, and research groups remains unclear. Differences in sequencing protocols, sampling design, and environments pose major challenges for cross-study comparisons, particularly in low-biomass environments where technical variation can obscure biological signal. To address this gap, we constructed a simple ontology which groups samples into one of three categories: hand, hand-associated surfaces, and floor then applied it to four publicly available 16S rRNA gene datasets: a hospital, university dormitory, Air Force dormitory, and private residential houses. ResultsWe identified strong and reproducible separation between floors and surfaces with frequent human contact. We found that floors consistently harbored soil-associated taxa, including KD4-96, 67-14, Skermanella, and Sphingobacterium, whereas hands and hand-associated surfaces were enriched with skin-associated genera, such as Lawsonella and Cutibacterium. Within studies, these results were generally consistent across timepoints. Across studies, mixed-model PERMANOVA analysis revealed significant clustering by sample type, with modest effects of study, suggesting that biological signal outweighed differences in laboratory or sequencing methods. Leave-one-study-out random forest models achieved high AUCs for hand vs. floor comparisons (0.865 to 0.921), moderate AUCs for hand-associated vs. floor comparisons, and weaker performance for hand vs. hand-associated comparisons. Application of the batch-correction method DEBIAS-M did not improve effect sizes or classification performance, indicating that reproducible structure was already discernible without batch adjustment. ConclusionsDespite substantial temporal and environmental heterogeneity among studies, we found that the built environment microbiome has a reproducible bacterial signal. There was consistent enrichment of soil-derived taxa on floors and human-associated taxa on hands and hand-associated surfaces suggesting a stable microbiome despite differences in building type, occupancy, and methodology. These findings establish an important foundation for future studies, suggesting cross-study comparability, the accuracy of ecological inference, and the ability to support the development of predictive applications in indoor microbiome research.

Indigenous Australians experience disproportionately high rates of dental caries, yet the biological pathways linking socioeconomic disadvantage to oral health remain unclear. This study examined how individual- and neighbourhood-level socioeconomic status (SES) shape the oral microbiome and mediate dental caries risk in Indigenous adults. A cross-sectional study of 100 Indigenous Australians ([&ge;]18 years) collected demographic, SES, and oral health behaviour data, followed by dental examinations for dental caries assessment, followed by collection of saliva and plaque samples. The microbiome was profiled using 16S rRNA sequencing, with analyses of microbial diversity, composition, differential abundance, and mediation of SES-caries associations. Saliva exhibited greater observed and Shannon diversity than plaque (both p < 0.01), with significant compositional differences (adonis p < 0.001). In saliva, alpha diversity was reduced with age, secondary education, low income, ownership of a healthcare card, and caries presence (all p < 0.05). SES explained greater variation in saliva than plaque composition, with associations for income (R{superscript 2}=3.8%, p<0.01), education (R{superscript 2}=2.0%, p<0.01), and caries (R{superscript 2}=2.2%, p<0.01). Differentially abundant taxa in low-income and caries groups included Rikenellaceae RC9 gut group, F0058, Filifactor, and Treponema. Mediation analyses showed 75.6% of the income effect on caries was mediated by microbiome shifts (ME=0.28, SE=0.32), compared with 21% for education (ME=0.03, SE=0.02). Socioeconomic disadvantage has a significant impact on the oral microbiome, influencing caries risk through income-related microbial dysbiosis. Saliva emerges as a sensitive biomarker of SES gradients. Addressing oral health inequities requires both structural policies targeting income inequality and microbiome-informed interventions. IMPORTANCEThis research provides novel biological insights into how socioeconomic disadvantage contributes to the higher burden of dental caries among Indigenous Australians. Although social determinants of health are well recognised, the pathways connecting these determinants to oral disease remain unclear. By demonstrating that low income and education affect oral microbiome diversity and composition, and that a significant part of income-related caries risk is mediated through microbiome changes, this study highlights an important mechanism behind oral health inequalities. Identifying saliva as particularly responsive to socioeconomic differences makes it a useful, non-invasive biomarker for tracking risk in vulnerable populations. These findings emphasise the need for two approaches: structural interventions to reduce social and income gaps, and microbiome-based strategies to address microbial imbalance and disease risk. Together, they strengthen the evidence for more effective, culturally sensitive efforts to promote oral health equity.

PurposeThe Population-based Microbiome Research Core (PMRC) is an expandable and longitudinal research core infrastructure to support the study of the human microbiome within the context of environmental, sociodemographic, and health factors. Broadly, the purpose of this infrastructure is to provide new insights into how human-environment interactions affect health through its influence on the composition and function of the microbiome. The PMRC was established as an ancillary study of the Survey of Health of Wisconsin (SHOW) and serves as a platform for ancillary studies, ongoing follow-up of the cohort, and expansion of the microbiome biorepository. ParticipantsThe study recruited adult participants who had previously participated in SHOWs Wisconsin Microbiome Study (WMS). Over 59% of the eligible WMS participants agreed to provide a repeat stool sample and household samples including dust, high touch surface swabs and outside soil. Findings to datePMRC includes 323 individuals; the majority (96%) were over the age of eighteen, white (84%), urban (75%), and lived in their homes for over one year (92%). Overall, 97% of participants completed the questionnaire and household high-touch surface swab collection, and 93% and 94% completed dust and stool collection, respectively. Soil samples were collected for 86% of all participant homes. Future plansSample protocols developed for the PMRC offer a unique framework for future household-based microbiome research. This infrastructure can support the generation of new knowledge on the role of the home environment in relation to the human microbiome and identify new opportunities for intervention research.

Volcanic soils provide a unique environment for studying microbial colonization and succession due to their extreme conditions and distinct geochemical profiles. This study focused on carbon monoxide (CO)-oxidizing microbial communities in volcanic soils of varying ages at Piton De La Fournaise (Reunion island). Soil samples from three sites were analyzed to assess microbial community structure using 16S rRNA gene sequencing and metagenomic analysis to identify functional genes involved in CO oxidation. The activity of CO oxidizing microbes in soils was measured. Phylum-level analysis showed increasing Acidobacteriota and Chloroflexota, decreasing Actinomycetota and Bacteroidota, and stable Pseudomonadota, while class-level patterns included rising Alphaproteobacteria and Acidobacteriia, with Ktenobacteria emerging in the oldest soils. CO dehydrogenase-related genes were found in 17 metagenome-assembled genomes across all sites. CO-oxidizing microbes were present across soil ages, with detectable activity in the younger soils and greatest activity in the oldest, suggesting that these microbes actively use CO as an energy source even in soils with primary vegetation, contrary to general understanding. The findings highlight the intricate dynamics of microbial succession in volcanic soils and challenge conventional expectations about community complexity over time. Understanding pioneer communities elucidates soil restoration processes, which will become critical when countering anthropogenic soil degradation.

Legionnaires disease has increased sixfold since 2000 in the United States, yet environmental reservoirs such as soils remain understudied sources of infection. It remains unclear how the diversity and abundance of environmental pathogens, such as Legionella, will shift as the climate continues to change. Here, we utilize 4,287 publicly available global soil 16S rRNA gene amplicon datasets to analyze how the distribution of the genus Legionella, including pathogenic lineages, varies across continental-scale biogeographic regions and along climatic and geochemical gradients. Legionella relative abundance increased across the joint precipitation-air temperature gradient, and mixed-effects modeling indicated that the chance of detecting Legionella in soils increased substantially when annual precipitation reached [~]500 mm. Legionella diversity was characterized by high spatial turnover, with the majority of abundant ASVs restricted to individual regions despite broad phylogenetic representation across the genus. Further, fewer than 2% of our 16S-derived Legionella sequences matched ASVs corresponding to characterized species, and the clinically dominant species L. pneumophila was rarely detected. In contrast, ASVs matching several other known pathogens (L. longbeachae, L. anisa, L. bozemanae, L. cincinnatiensis) were orders of magnitude more common than L. pneumophila in soils. Moreover, pathogenic Legionella ASVs were detected significantly more frequently at warmer and wetter conditions. Collectively, our findings suggest that Legionella relative abundance and diversity in soils, especially pathogenic lineages, are shaped by both dispersal and climatic filtering. As temperature and precipitation regimes shift in the future, our results imply that soils should be an important pathogen source to monitor and that Legionella species beyond L. pneumophila warrant increased ecological and public health attention.

Airborne microbial pathogens in built environments (BEs) may pose potential health threats, yet the ecological mechanisms governing their assembly and persistence across interconnected architectural spaces are less studied. Here, we conducted a year-long, multi-spatial investigation across a university campus complex, sampling the exhaust outlets of three indoor environments and the adjacent outdoor inlets. By integrating the 16S rRNA gene and ITS sequencing from 437 paired bacterial-fungal samples, we characterized the spatiotemporal dynamics of airborne opportunistic pathogen-containing genera. Our study showed that spatial filtering emerged as the dominant determinant of pathogen community structure, with confined elevator environments serving as reservoirs of pathogens with limited but continuous microbial influx from surrounding spaces. Superimposed on this spatial baseline, bacterial and fungal pathogens displayed distinct seasonal dynamics. Opportunistic fungal pathogens such as Fusarium peaked during autumn and winter, possibly driven by enhanced aerosol persistence and dispersal under cooler, drier conditions. In contrast, bacterial pathogens exhibited greater temporal resilience, with key taxa such as Listeria transcribed actively during winter, predisposing them to increased relative abundance during spring. Cross-domain ecological networks further revealed the dynamic interactions among pathogens, centered on the skeletal structure mediated by the keystone fungal pathogen Aspergillus, suggesting that coordinated microbial interactions reinforced pathogen persistence across seasons. Together, our findings support a unified ecological framework in which pathogen dynamics within BEs arise from the coupled effects of spatial filtering, climatic modulation, and biotic interactions. These results provide a foundation for transitioning from static environmental control toward predictive pathogen management in BEs. ImportanceBEs are the primary settings of human microbial exposure, yet the ecological principles governing the persistence of airborne pathogens across interconnected indoor spaces remain poorly resolved. Most previous indoor studies have focused on isolated environments or single microbial groups, limiting our understanding of how pathogens are maintained and redistributed within complex architectural systems. By integrating bacterial and fungal community dynamics across spatial environments over four seasons, this year-long study demonstrates that the ecology of airborne pathogens is not static, but is instead dictated by a complex interplay of spatial, climatic, and biological forces. Our findings identify enclosed, high-transit elevator spaces as critical hotspots for pathogen accumulation and highlight the role of seasonal ecological reorganization in driving airborne health risks. More broadly, this work establishes a systems-level ecological framework for understanding airborne pathogen dynamics in BEs and provides a conceptual basis for developing more adaptive strategies for indoor microbial risk management.

ObjectivesThe fall of the Roman Empire (476 CE) profoundly affected the lives of its peoples due to the political, administrative, and territorial changes that occurred. The majority of written records of the time focus on the social elite, leaving larger parts of the population understudied. Here, we employ a bioarchaeological approach to understand how differences in lifestyle may be reflected in the oral microbiome of people from different social classes living before and after the fall. Material and MethodsWe analysed shotgun sequencing data from dental calculus, the preserved oral microbiome, of 67 individuals belonging to different social classes from two Classical cemeteries dated to I-III century CE (Lucus Feroniae and Isola Sacra) and one post-Classical cemetery dated to IV-VIII century CE (Selvicciola), all located in proximity to the city of Rome, Italy. ResultsWe detect significant differences in the oral microbiome taxonomic and functional composition across time periods and social classes, with the rural town of Lucus Feroniae standing out compared to its two counterparts. Reliable identification of dietary items was not possible. DiscussionThe distinct oral microbiome of Lucus Feroniae could reflect differences in general health and subsistence practices. The rural position of this community may have mitigated the cyclical food crises that, instead, affected the contemporary Isola Sacra and the later community of Selvicciola, thereby buffering against the nutritional stress observed in these two locations.

Early-life wheezing in children has been associated with microbial alterations along the gut-airway axis, yet studies simultaneously investigating bacterial communities in both compartments remain scarce. The aim of this cross-sectional exploratory pilot study (n=25) was to characterize and compare nasal and stool bacterial communities in preschool children aged 1-4 years with recurrent wheezing and healthy controls using 16S rRNA gene metabarcoding. Across participants, nasal and stool bacteriomes were highly individualized and taxonomically diverse. Overall richness, evenness, and community composition did not differ significantly between healthy children and wheezers in either compartment. However, wheezers displayed markedly higher within-group variability, particularly in nasal communities. Stratification based on microbiome similarity to healthy samples revealed increased Moraxella and reduced commensal genera including Prevotella spp. and Veillonella, along with lower richness and evenness (all p<0.001) in nasal samples with divergent bacterial communities. Stool alterations were more subtle but included trends toward reduced Bacteroides, Faecalibacterium, and Alistipes in wheezers more divergent from healthy controls. Community assembly in both compartments was largely governed by stochastic processes but accompanied by less complex and more fragmented bacterial interaction networks in wheezing children. Cross-compartment correlations were also altered, most prominently involving stool Lactococcus showing stronger and more numerous correlations with nasal taxa in wheezers than in healthy controls. Divergent wheezers exhibited distinct modular network structure and cross-compartment profiles, consistent with a differentiated microbial organization. Together, these findings suggest compartment-specific differences in microbial interaction patterns across the gut-airway axis in early-life wheezing, despite limited differences in overall community diversity. Take home messagePreschool wheezers showed fragmented gut-airway microbial networks and Moraxella-associated airway community stratification despite limited differences in overall diversity.

The oral microbiome is a complex community of bacteria, fungi, and viruses that inhabit the oral cavity. Microbes of the oral microbiome are implicated in health and disease. We collected 220 unstimulated saliva samples from patients with periodontal disease and varying degrees of dental caries, as well as from subjects with no signs of oral disease. Metagenomic analysis of saliva revealed significantly higher abundance of periodontal pathogens in people with gum disease, and significantly higher abundance of cariogenic species in people with dental caries. We also found that salivary microbiome diversity was significantly higher in people with periodontal disease, but not in those with only caries. Furthermore, oral microbiome diversity is affected by oral hygiene habits such as flossing frequency, but not brushing frequency. Clustering and differential analysis allowed us to identify specific commensal species, such as Prevotella pallens and Veillonella atypica, which are significantly higher in patients without oral disease. Clustering further suggested that oral microbiome diversity may contribute to disease risk. These results suggest that oral hygiene behaviors influence the oral microbiome, and modulation of the oral microbiome could prevent or reduce the incidence and severity of oral disease.

Urbanization-driven environmental change has significant implications for human health and well-being. However, studies have found differing patterns in microbial diversity along urbanization gradients; and it remains unknown whether this reflects methodological limitations or genuine ecological complexities. Resolving these inconsistencies requires innovative, reproducible methods that accurately reflect human contact with environmental microbiota. In this study, we have validated a new method for assessing environmental microbial exposure by measuring microbiota from particulate matter collected from shoe soles and studied the influence of vegetation at different proximities. Through repeated walks on routes along an urbanization gradient in Finland, we show that left and right shoe sole dust from the same walk and same route represent more similar microbial communities compared to different walks and routes. We found that bacterial biomass and diversity were best predicted by Normalized Difference Vegetation Index (NDVI, as a measure of greenness) immediately surrounding the walking path, whereas fungal communities responded to broader landscape-scale greenness (100m-1km), suggesting that bacteria and fungi are governed by different dispersal processes. Importantly, NDVI explained these differences in diversity more effectively than simple classifications of the path based on its substrate and whether it was in a rural or urban setting. Shoe sole dust sampling offers a simple, effective, and reliable approach for evaluating microbial exposures, capturing scale-dependent microbial responses to vegetation, and enabling more robust epidemiological studies on the health effects of greenness and environmental biodiversity.

BackgroundSecondhand tobacco smoke exposure (TSE) increases susceptibility to respiratory diseases, but the mechanisms of action are poorly understood. ObjectiveTo study the effect of TSE in the nasal microbiome of children, and to evaluate whether such effect is dose-dependent with measured levels of cotinine in saliva and urine. MethodsThe study was performed at the Mount Sinai Kravis Childrens Hospital (New York, NY) and the Johns Hopkins Hospital (Baltimore, MD). We enrolled 236 children between 6 months and 10 years of age, both inpatients and outpatients. We collected swabs to characterize the diversity and composition of the nasal microbiome using 16S rRNA gene sequencing and measured cotinine levels in salivary and urinary samples to quantify TSE. We then determined the relationship between these measures and participant respiratory conditions, demographics and lifestyle factors. ResultsInfants with high cotinine levels had lower nasal microbiome alpha diversity and an enrichment in Moraxella, Dolosigranulum and Corynebacterium, which formed a distinct cluster in network analysis. A Dirichlet Multinomial Mixture model identified the existence of two distinct microbial rhinotypes, the first one characterized by significantly higher cotinine levels, lower alpha diversity, and enrichment of these taxa. ConclusionChildren with higher cotinine levels had reduced alpha diversity and a distinct nasal rhinotype. Our results suggest TSE is associated with alterations of the nasal microbiome and identify a rhinotype as a potential biomarker for TSE.

Across microbiome studies, fecal and oral samples are stored and processed in different ways, which could affect the observed microbiome composition. Here, we compared treatment methods, which included both storage conditions and processing methods, applied to samples prior to DNA extraction to determine how each affects microbial community diversity as assessed by 16S rRNA gene sequencing. We collected dental swab, saliva, and fecal samples from 10 individuals, with three technical replicates per treatment method. We assessed four methods of processing fecal samples prior to DNA extraction. We also compared different fractions of frozen saliva and dental samples to fresh samples. We found that lyophilized fecal samples, fresh whole saliva samples, and the supernatant fraction of thawed dental samples retained the highest levels of alpha diversity in samples. The supernatant fraction of thawed saliva samples had the second highest alpha diversity compared to fresh. Then we investigated the differences in microbes between different treatments at the domain and phylum levels as well as identified the amplicon sequence variants (ASVs) that were significantly different between the methods producing the highest alpha diversity and the other treatment methods. Lyophilized fecal samples had a greater prevalence of Archaea as well as a greater ratio of Firmicutes to Bacteroidetes compared to the other treatment methods. Our results provide practical considerations, not only for selection of processing method, but also for comparing results across studies that use these methods. Our findings also indicate differences in treatment method could be a confounding factor influencing the presence, absence, or differential abundance of microbes reported in conflicting studies.

BackgroundThe COVID-19 pandemic changed societys habits and customs due to the social restrictions and health measures imposed during the first half of 2020. This study analyzes the composition of the oral microbiota in relation to age, household cohabitation, SARS-CoV-2 infection, and COVID-19 severity among children and adults under home confinement in Barcelona, Spain. MethodsA prospective study conducted involving children and adults confined during the COVID-19 pandemic in the Barcelona Metropolitan Area between April and June 2020 included multiple cases of several participants living within the same family household. Saliva samples were collected from all participants, and microbiota composition was characterized through 16S rRNA gene sequencing. ResultsA total of 142 adults and 265 children living in 121 family households were included in the study. All 142 adults had a prior confirmed SARS-CoV-2 infection, and 20 (14.08%) of them had a history of severe COVID-19. SARS-CoV2 infection was detected in 58/265 (21.89%) of children; all of them were asymptomatic. Oral microbiota composition and diversity did not differ by SARS-CoV-2 infection status in children. In contrast, adults with severe COVID-19 exhibited lower microbiota diversity and distinct microbiota composition compared to those with mild disease symptoms. Age-related differences in oral microbiota composition were marked in the younger children groups. Additionally, cohabiting individuals shared more Amplicon Sequence Variants (ASVs) than non-cohabitants. ConclusionsAge and cohabitation strongly influenced oral microbial composition. Our study demonstrates that oral microbiota composition in adults varies according to COVID-19 severity, whereas such microbial shifts are not observed in asymptomatic pediatric populations, regardless of infection status.

Scalable soil microbiome monitoring requires sampling methods that are reproducible across operators, field sites, and logistical constraints. Here, we evaluated three key methodological choices that commonly limit comparability in agricultural rhizosphere studies: how the rhizosphere sampling unit is operationally defined, sample pooling strategies, and preservation methods. We introduce the RhizoCore, a standardized root-zone soil core defined by core diameter, depth, position relative to the plant, and subsample volume, as a practical proxy for traditional rhizosphere sampling. The RhizoCore method captured more than 92% of the sequencing depth found in traditional rhizosphere samples, with differences limited predominantly to low-abundance taxa. Preservation methods significantly affected bacterial communities, while sample pooling showed greater impact on fungal diversity and substantially reduced within-group variability across all treatments. Despite these effects, differential abundance analysis revealed minimal compositional changes, with only a small fraction of microbial taxa significantly affected by either pooling or preservation method. Our findings demonstrate that the RhizoCore method provides a reproducible, and scalable approach for rhizosphere sampling that balances scientific rigor with practical field implementation, offering a framework for large-scale soil microbiome monitoring programs and for improving comparability among agricultural microbiome studies across diverse environmental conditions.

Urbanization can result in shifts in abiotic and biotic factors, including temperature, pollution, habitat type, pathogens, and diet, among others. These shifts can, in turn, shape the ecological and evolutionary trajectory of urban wildlife. The gut microbiota has the potential to mediate host-environment interactions, especially in the context of diet and disease, and thus may be a useful lens for understanding the impacts of urbanization. House mice (Mus musculus domesticus) are a cosmopolitan human commensal with a wealth of genomic and metagenomic resources. Here, we investigate patterns of variation in diet and gut microbial diversity, community composition, and function using a paired urban-rural sampling design in house mice from three metro regions in the eastern United States. First, using stable isotope analysis, we found that habitat--urban versus rural--was a major driver of variation in {delta}15N, suggesting a diet richer in animal proteins in cities. Next, using short-read sequencing of the 16S rRNA gene, we found that urban mice have lower gut microbial taxonomic diversity than their rural counterparts. We also found that community composition varied among urban and rural habitats, with differences largely reflecting shifts among closely related taxa. In particular, Prevotellaceae, a family known to be responsive to dietary quality, was differentially abundant, with lower abundance in urban habitats. Finally, we found differentiation in a few predicted microbial functions across habitat, primarily related to metabolism. Together, data across three independent sampling regions provide strong evidence that urbanization has the potential to shape the diet and the microbiome of house mice.

Climate change is altering ecosystems in unprecedented ways and necessitates the development of strategies that model ecosystems and allow for the evaluation of environmental impacts of perturbations: including climate events, novel approaches to agronomy or ecosystem management, and impacts of bio-industry and biotechnology innovations. Mesocosms present a platform to model some of the complexity of an ecosystem, while still being controlled and reproducible enough that they can be used to ask targeted questions and systematically assess the impacts of perturbation events. Herein, we established a methodological pipeline to assess the impact of three perturbation events (hydration, nutrification, contamination) upon plant-associated microbial communities using a terrestrial mesocosm. Mesocosms were assessed over a 30-day time-course following environmental perturbations, including modeling contamination with a foreign microbe via the introduction of Saccharomyces cerevisiae. We developed and applied a suite of diagnostic and bioinformatic analyses, including digital droplet PCR, microscopy, and phylogenomic analyses to assess the impacts of a perturbation event in a system that models a terrestrial ecosystem. The resultant data show that our mesocosms are dynamic yet reproducible, and that the analysis pipeline presented here allowed for a longitudinal assessment of microbial population dynamics and abiotic soil characteristics following perturbations, as well as the fate of yeast in the soil. Notably, our data indicate that a single perturbation event can have long-lasting impact upon soil composition and underlying microbial populations. Thus, this approach can be used to ask targeted questions as well as gain insights on broader ecological trends of soil perturbation events. ImportanceSoils are key to a healthy environment, but the impact of human activities and climate change upon soil microbiomes remains unclear. It is challenging to model the complexity of an ecosystem in a laboratory; however, to gain insight on how ecosystems are impacted by outside perturbations it is valuable to develop approaches that mimic an environmental system. Here, we developed a mesocosm that uses readily accessible components that come together to model a terrestrial ecosystem which is coupled with an analysis pipeline to assess how various perturbations impact the soil. We demonstrate the utility of this approach by tracking the effects of three perturbations (water, nutrition, contamination with yeast) on the soil over the course of 30 days. Our results demonstrate that these treatments can have lasting impacts on the soil. These findings and the methods presented here could be useful to other researchers assessing how ecosystems respond to perturbations. HighlightsO_LIWe developed a pipeline using terrestrial mesocosms that allow for the analysis of how perturbations impact soil systems and demonstrate that it is effective for targeted detection of a microbe of interest as well as global phylogenomic observation of ecological changes due to external perturbation events. C_LIO_LIdigital droplet PCR was adapted to track a low abundance, non-native microbe in soil mesocosms. C_LIO_LITemporal sampling allowed for the longitudinal observation of soil response to a one-time perturbance. C_LIO_LIIntroduction of yeast and its associated growth media conferred an expansion of total biomass and increase in alpha-diversity and shifts in the beta-diversity of the soil microbiome. C_LIO_LITreatment with media or yeast resulted in the expansion in the relative contribution of fungal biomass and an increase in the relative abundances of Saccharomycetes and Trellomycetes, with decreases in Sordariomycetes, Leotiomycetes, and Eurotomycetes C_LIO_LIMedia or yeast introduction also resulted in an expansion of the relative abundances of Gammaproteobacteria, Bacilli, and Bacteroidia, and decreases in Actinomycetia and Acidobacteria. C_LI

AimTo understand the spatiotemporal dynamics of bacterial succession during gingivitis, and to identify taxa with a critical role in gum health with prognostic value. Materials and methodsLongitudinal microbiome data were collected from 15 individuals after completely discontinuing all forms of oral hygiene, and subsequently reintroducing it for three and two weeks, respectively. Sequences from the 16S rRNA V4-V5 gene region from sub- and supra-gingival plaque, saliva, and tongue sites were annotated and mapped to a reference tree of Human Oral Microbiome Database sequences. ResultsSuspending oral hygiene induced gingivitis, which was resolved after its resumption to baseline. Most significant shifts in bacterial abundance were observed in dental plaque, but not in saliva and tongue sites. During gingivitis-induction, baseline microbiota dominated by Streptococcus, was superseded by increased Prevotella, Fusobacterium, Leptotrichia, and Porphyromonas genera. Converse to its decline during disease-induction, gum health restoration was accompanied by a significant increase in streptococci. ConclusionWe present the most comprehensive, spatiotemporal map of bacterial succession during gingivitis onset and resolution. We have identified taxa with potential as probiotic candidates for gum disease (i.e., perio-probiotics), and suggest tooth-associated plaque and not saliva or tongue plaque should be used in future prognostic tests.