FEMS Microbes

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

Microbial communities in indoor environments are shaped by resource availability and disturbances, yet their growth dynamics and compositional changes remain unclear. Here we combined quantitative colony growth analysis with 16S rRNA gene sequencing to investigate bacterial communities on public restroom surfaces before and after routine cleaning under varied nutrient conditions. Cultivation revealed that nutrient availability strongly influenced bacterial growth and selectively enriched distinct taxa, while cleaning caused limited shifts in overall community structure and diversity. Correlations between growth parameters and diversity indices were weak, indicating that taxon-specific responses to nutrients primarily drive growth outcomes. These findings suggest that resource composition, rather than cleaning disturbance, governs bacterial growth and community assembly in built environments. Integrating culture-based phenotyping with sequencing provides a comprehensive framework to understand microbial dynamics following environmental perturbations.

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.

Montane fens are rare and microbiologically poorly characterised wetland ecosystems in south-eastern Australia, and their microbial communities remain virtually unexplored. Here, we profile the microbiomes of Victorian montane fens using 16S rRNA metabarcoding of 12 soil cores collected along a 12-m transect and sampled across four depth horizons. Surface soils exhibited slightly higher alpha diversity than deeper layers, but the most pronounced differences occurred in community composition, with surface microbiomes significantly distinct from all subsurface depths. To contextualise these communities within global environmental diversity, we compared them with 9662 Earth Microbiome Project samples spanning 24 environmental materials processed using comparable methods. Montane fen microbiomes were one of the most diverse environmental materials analysed and compositionally distinct from all comparator biomes. Overrepresentation analysis identified signature microbial taxa, including archaeal lineages from the Crenarchaeota and Methanomicrobia and bacterial phyla such as Acidobacteria, highlighting taxa involved in ecological processes associated with acidic, saturated, and organic-rich soils. Notably, the majority of sOTUs detected in montane fens were unique to this environment - the highest proportion of source-specific taxa among all biomes analysed. Together, these findings demonstrate that southeastern Australian montane fens harbour a highly distinctive and largely uncharacterised microbial community, underscoring their ecological uniqueness and the importance of conserving these rare alpine wetlands. Data SummarySequencing data is available in SRA BioProject PRJNA1398590; accessions SRR36684598 through SRR36684645. Metadata and accessions for collected montane fen samples are included in Table S1 and metadata for Earth Microbiome Project samples included in this study are listed in Table S4. Impact StatementWetland ecosystems are increasingly recognised as important reservoirs of microbial diversity, yet many remain poorly characterised in global microbiome surveys. In this study, we provide the first characterisation of microbial communities inhabiting montane fens in southeastern Australia and place them in a global context using publicly available environmental microbiome data. We show that these fens harbour exceptionally diverse microbial communities that are compositionally distinct from other environmental sources processed using comparable methods, with a high proportion of taxa that are not present in any other sample in an existing reference dataset. By extending global comparisons to an under-sampled wetland type, this work adds to the growing body of evidence that significant microbial diversity remains undocumented in geographically and ecologically restricted environments. The findings are relevant to researchers working in microbial ecology, environmental genomics, and biogeography, as well as those interested in wetland function and conservation. While largely descriptive, this study represents an important step in expanding environmental genome catalogues and provides a baseline framework for future genomic, functional, and mechanistic investigations of montane wetland microbiomes.

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.

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.

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.

Microbial-mediated plastic degradation has the potential to address the persistent global problems of plastic waste and pollution. Previous work has shown that soils can harbour microbes capable of plastic degradation, but we expect there is a broader diversity of soil microbes capable of metabolizing plastics than identified to date using more traditional cultivation-based screening methods. Here we demonstrate a novel approach to identify putative plastic degrading microbes in soil. We paired in situ, real-time measurements of microbial plastic degradation on conductive sensors with subsequent microbial community profiling of the sensor-associated biofilms exhibiting appreciable degradation. To illustrate the utility of our approach, we focus on microbial degradation of the bioplastic polymer PHBV, poly(3-hydroxybutuyrate-co-3-hydroxyvalerate). We screened a range of soils with the in situ sensors to identify a subset of five soils with high PHBV degradation rates, and confirmed that PHBV degradation was due to microbial activity. We then extracted DNA directly from sensors placed in soils with high measured rates of PHBV degradation and used marker gene sequencing to identify the bacterial and fungal taxa associated with the observed PHBV degradation. We confirmed via in vitro culturing that microbes isolated from the sensors have a demonstrated capacity for PHBV metabolism. Together, these results highlight the benefit and feasibility of using low-cost, in-soil sensors to simultaneously collect real-time data on plastic degradation rates in soil and identify previously unrecognized microbial taxa capable of degrading and metabolizing plastic polymers in situ.

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.

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.

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.

Nucleic acid extraction is the first step in molecular biology studies of soil bacterial communities. The most common used soil DNA extraction method is the direct, hard extraction Mobio method, which uses bead beating to lyse bacteria. In this study we compared the Mobio method with a soft, enzymatic lysis extraction method. Next generation sequencing (Illumina and Pyrosequencing) of amplicons generated from four 16S primer pairs and DNA from 12 soils and 3 composts was used to compare the two extraction methods. Four bacterial orders, the delta proteobacterial Desulfuromonadales and gamma proteobacterial Pseudomonadales, Enterobacteriales, and Alteromonadales were more common in amplicons from soft extracted DNA, sometimes by two orders of magnitude. These groups can be a significant fraction of the bacterial population. For example the Pseudomonadales made up to 16 % and Enterobacteriales 10% of amplicons from Soft extracted DNA. The JG30-KF-CM45 order was under extracted by the enzymatic lysis extraction method. Results differed more by primer choice than extraction method and the phylogenetic resolution of differences between extraction methods changed with primer choice. Given how often Mobio extraction is used, these proteobacterial orders are probably under-represented in the studies of soil bacteria that use nucleic acid methods. Further improvements in soil DNA extraction are needed. Amplicons sequencing studies should use a range of different primers to confirm the phylogenetic resolution of their results. ImportanceSeveral large scale studies of soil bacteria that compare thousands of soil samples across continents have used the Mobio method for DNA extraction. Large scale studies like these are increasing with the recent establishment of the Global Soil Biodiversity Observation Network (Soil BON), which also uses the Mobio method. The results of this work will be used to make policy decisions about how to manage the soil and may be a guide for bioprospectors. As the Mobio method is so widely used, it is important to know its limitations. Studies that use the Mobio method underestimate the fraction of several proteobacterial groups. Most notably the Enterobacteria and Pseudomonas can be under extracted by 10-100 fold. The degree of under extraction varies with different soils.

Illegal wildlife trade and habitat degradation displace thousands of animals annually in Southeast Asia, with many confiscated primates housed in rehabilitation centers that increasingly function as long-term holding environments. In slow lorises, dental clipping associated with the pet trade may generate persistent disruption along the oral-gut axis, potentially undermining physiological readiness for release in ways not captured by conventional screening. Here, we evaluated whether microbiome structure provides an integrative marker of release readiness in rehabilitating Javan slow lorises (Nycticebus javanicus). From June to October 2024, we collected fecal (n = 26) and saliva (n = 18) samples from 19 adults housed at YIARI, including 10 release candidates and 9 non-candidates classified primarily based on tooth loss, medical history, and possibility of release. Bacterial communities were characterized using 16S rRNA (V3-V4) amplicon sequencing, with alpha and beta diversity, taxonomic enrichment (LEfSe), and predicted functional profiles (PICRUSt2) assessed. Microbiome composition was strongly compartmentalized by body site, with higher alpha diversity in the gut. Release candidacy was associated with modest gut compositional differences, whereas oral microbiomes showed pronounced divergence between candidates and non-candidates. Non-candidates were enriched in dysbiosis-associated taxa and degradation-oriented functional pathways, while candidates showed enrichment of biosynthetic and central energy metabolism pathways. Gut microbiome structure was stable across pre-release and soft-release phases. These findings indicate that oral and gut microbiomes represent distinct physiological niches and that persistent oral microbiome alteration is a sensitive marker of long-term dental perturbation. Integrating microbiome-informed metrics may improve multidimensional assessment of release readiness.

Alzheimers Disease (AD) is a neurodegenerative disorder that affects memory, cognition, and behavior. This study reanalyzes a publicly available 16S rRNA sequencing dataset (PRJNA554111) of fecal samples from 43 AD patients and 43 age-and-sex-matched controls to assess differences in microbial composition between the groups. We outlined the relative abundances of major phyla, and identified 137 ASVs across five phyla that were differentially abundant (padj<0.05). We found no distinct pattern of microbial composition distinguishing AD from controls, contrary to the original finding of disease-specific signatures.

BackgroundThe human respiratory tract harbours diverse microbial communities crucial for health, but their dynamics during environmental perturbations like smoking remain poorly understood. While smoking is a major risk factor for various diseases, its compartment-specific effects on the respiratory microbiome and potential recovery following cessation have not been fully elucidated. Here, we present a longitudinal, multi-site study of respiratory microbiome dynamics in smokers undergoing cessation, benchmarked against healthy never-smokers. MethodsUsing standardized sampling of the anterior nares, oropharynx, and bronchoalveolar lavage (BAL), combined with 16S rRNA gene amplicon sequencing and rigorous contamination controls, we characterized community composition, diversity, personalization, and microbial interactions across airway compartments. ResultsSmokers exhibited pronounced microbiome alterations: nasal richness increased, while lung richness and core taxa were reduced. Smoking-induced changes were compartment-specific and most pronounced in nose and lung. The degree of individuum-specific differences in community structure was elevated in smokers and correlated with smoking intensity and duration. Short-term cessation (6 weeks) led to minor shifts in taxa abundance but increased similarity between oropharyngeal and lung communities, whereas long-term cessation (1 year) resulted in partial restoration, particularly in lung and nasal microbiomes. Some taxa, including Haemophilus and Prevotella_7, showed persistent alterations, highlighting lasting smoking effects. Network analyses revealed that smoking disrupted microbial co-occurrence and reduced community connectivity, whereas cessation partially restored interaction networks, with dynamics differing between oropharynx and lung, reflecting different underlying ecological assembly processes. Recovery trajectories were highly individualized, with lung microbiomes influenced by deterministic processes and upper airway microbiomes shaped by stochastic factors, explaining site-specific responses and the persistence of personalized microbial signatures. ConclusionThese results provide the first time-resolved, multi-compartment characterization of respiratory microbiome recovery after smoking cessation, revealing that smoking leaves long-lasting, site-specific imprints on airway microbial communities and interactions. Our findings underscore the need for individual and compartment-specific approaches when designing microbiome-based interventions to support respiratory health.

Soil pH is a predominant factor in structuring microbial communities; however, its role in shaping microbial life-history traits across large spatial scales remains underexplored. Here, we hypothesised that bacterial ubiquity, or niche breadth, across a diverse collection of soils is linked to genomic traits. We leveraged a national-scale survey of UK soils (the Countryside Survey) and 16S rRNA gene sequencing data with trait annotations (estimated genome size, coding density, and rRNA operon copy number) to examine trait-environment-niche breadth relationships. Our analyses revealed that soil pH was the dominant environmental driver of niche classification and bacterial community traits along the niche range. Low pH soils (pH <5.5) hosted ubiquitous taxa with larger genome sizes, lower coding densities and lower rRNA copy numbers, implying slower growing taxa with higher genetic facilities. Mildly acidic soils (pH 5.5 to 7) favour higher rRNA copy numbers, intermediate genome sizes and moderate coding densities. Alkaline soils (pH >7) feature communities with the smallest niche range, smallest genomes and highest coding densities. Here, specialisation occurs through streamlining with simpler, smaller genomes favoured. We found that generalist taxa were widespread across the pH range, becoming dominant under acidic conditions, while taxa adapted to higher pH were comparatively scarce in their distribution. These findings identify soil pH as a key physiological filter that aligns microbial genomic traits and ecological strategies across landscapes. By extending prior site-specific results to a broad-scale context, our study highlights how trait-based metrics can predict microbial responses to soil conditions, with implications for understanding ecosystem carbon cycling and informing land management practices aimed at sustaining soil health in the future.