Amplicon Sequencing Data Research Articles

Complementary Field and Laboratory Batch Studies to Quantify Generation Rates of Perfluoroalkyl Acids in a Contaminated Agricultural Topsoil with Unknown Precursors

AbstractSoil microbiome changes and generation rates of per‐ and polyfluoroalkyl substances (PFAS) precursors were studied in a contaminated agricultural field using a combination of field and laboratory batch microcosm studies. 16S rRNA gene amplicon sequencing was used to track how microbial community composition changed over time, while perfluoroalkyl acids (PFAA) generation rates were quantified using a combination of field and batch incubations combined with the direct total oxidizable precursor (dTOP) assay. The study site in Brilon‐Scharfenberg, North Rhine‐Westphalia, Germany, has PFAS contamination in the topsoil (0 to 30 cm) originating from compost. Generation rate constants of these short‐chain PFAA estimated from batch incubations (0.12 to 0.75 1/year) were higher but similar to rate constants from the fields (0.05 to 0.22 1/year). Long‐term field mass discharge data (2009 to 2023) suggest that at least 60 years are needed to remove 99.99% of short‐chain PFAA and their precursors. 16S rRNA gene amplicon sequencing data revealed a major impact of PFAA on the biodiversity of soil microorganisms, with batch‐incubated contaminated soils showing higher richness and diversity indexes than field control soils. However, most of these impacts occurred at lower taxonomical ranks and did not seem to have a prominent impact on the overall structure of the autochtonous microbial communities of the soils where PFAA were produced and accumulated. Overall, our findings demonstrate that well‐controlled aerobic batch test combined with the results of dTOP assay are a suitable approach for estimating short‐chain PFAA generation rates. Additionally, our research suggests that the complete removal of PFAA precursors from topsoil will take decades.

VAMPirus: A versatile amplicon processing and analysis program for studying viruses.

Amplicon sequencing is an effective and increasingly applied method for studying viral communities in the environment. Here, we present vAMPirus, a user-friendly, comprehensive, and versatile DNA and RNA virus amplicon sequence analysis program, designed to support investigators in exploring virus amplicon sequencing data and running informed, reproducible analyses. vAMPirus intakes raw virus amplicon libraries and, by default, performs nucleotide- and amino acid-based analyses to produce results such as sequence abundance information, taxonomic classifications, phylogenies and community diversity metrics. The vAMPirus analytical framework leverages 16 different opensource tools and provides optional approaches that can increase the ratio of biological signal-to-noise and thereby reveal patterns that would have otherwise been masked. Here, we validate the vAMPirus analytical framework and illustrate its implementation as a general virus amplicon sequencing workflow by recapitulating findings from two previously published double-stranded DNA virus datasets. As a case study, we also apply the program to explore the diversity and distribution of a coral reef-associated RNA virus. vAMPirus is streamlined within Nextflow, offering straightforward scalability, standardization and communication of virus lineage-specific analyses. The vAMPirus framework is designed to be adaptable; community-driven analytical standards will continue to be incorporated as the field advances. vAMPirus supports researchers in revealing patterns of virus diversity and population dynamics in nature, while promoting study reproducibility and comparability.

Development of MetaXplore: An Interactive Tool for Targeted Metagenomic Analysis.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

Revisiting the bicontinental allopolyploid origin of Australasian Lepidium species with amplicon sequencing of 15 nuclear genes

New Zealand is home to 16 endemic species of Lepidium (Brassicaceae), including two species considered to have become extinct since European colonisation and an additional species shared with Australia. Previous meiotic chromosome counts suggest at least some are high polyploids. A hybrid origin has been proposed for several of them, with African and American species implicated as parents. We generated amplicon sequence data for 15 genes derived from targeted enrichment data from a selection of species endemic to New Zealand, and of African, American, and Australian origin naturalised in New Zealand. These were analysed, along with publicly available genomic data from other Lepidium species. Our results are consistent with earlier work in supporting two main groups of endemic New Zealand Lepidium, corresponding to different dominant nrDNA sequences. Our data suggest that these two groups differ in ploidy (one octoploid, the ploidy of the other uncertain). The octoploid species combine four distinguishable subgenomes and the other species may be the products of allopolyploidisation between octoploid species and a diploid species closely related to, if not, L. africanum. Previously proposed links to American Lepidium are also supported, with at least two Australasian Lepidium subgenomes related to subgenomes present in American polyploid species. The affinities of two further subgenomes present in Australasian Lepidium remain to be determined, but they may also be of American origin. One New Zealand endemic species, L. naufragorum, displays sequences broadly consistent with it being the octodecaploid product of hybridisation between octoploid and decaploid New Zealand groups.

16S rRNA gene amplicon sequencing data from an Australian wastewater treatment plant.

Amplicon sequencing data of the 16S rRNA (V1-V3) gene from 56 effluent and sediment samples from an Australian wastewater treatment plant are reported. Proteobacteria (3.50%-90.09%), Actinobacteria (0.02%-45.71%), and Cyanobacteria (0.05%-63.73%) were dominant in the effluent. The sediment samples were dominated by Proteobacteria (13.14%-84.83%), Chloroflexi (0.84%-42.52%), and Firmicutes (1.54%-17.21%).

Impact of root canal disinfection on the bacteriome present in primary endodontic infection: A next generation sequencing study.

To investigate the bacteriome present in teeth with primary endodontic infection (PEI) and apical periodontitis (AP) and to determine quantitatively and qualitatively the impact of chemomechanical preparation (CMP) using 2.5% sodium hypochlorite NAOCl on the bacteriome found in PEI with AP using the Illumina MiSeq platform. Thirty-six paired samples from 18 patients were successfully sequenced and analysed. Samples were collected at two sampling times: before (s1) and after (s2) CMP using 2.5% NaOCl. The DNA was extracted from s1 and s2 samples and quantified using quantitative PCR (qPCR). All 36 samples were sequenced using the Illumina MiSeq platform. Raw V3-V4 amplicon sequencing data were processed with the DADA2 pipeline to generate amplicon sequence variants (ASVs). Alpha diversity metrics representing abundance (Chao1) and diversity and evenness (Shannon, Simpson) were computed. The paired-sample Wilcoxon's test was used to compare alpha diversity metrics and qPCR counts between s1 and s2. The PERMANOVA method (with 999 permutations) was applied to compare community composition between sample types (s1 versus s2) and between patient IDs. ALDEx2 (ANOVA-like differential expression tool for high-throughput sequencing data) to investigate differentially abundant taxa between s1 and s2. A paired-sample Wilcoxon's test was used to compare alpha diversity metrics and qPCR counts between s1 and s2. The qPCR counts were significantly higher in s1 compared to s2 (p = .0007). The Chao1 index indicated no difference in alpha diversity (p < .7019); whereas Shannon (p = .0056) and Simpson (p = .02685) indexes showed higher values in s2. The PERMANOVA test using Adonis2 showed a significant effect of sample time on community composition (R2 = .0630, p = .012). Patient ID also showed a significant effect on community composition (R2 = .6961, p = .001). At the genus level, Dialister, Mogibacterium, Prevotella, and Olsenella were differentially enriched at s1, while Actinomyces, Stenotrophomonas_unclassified, Enterococcus_unclassified, and Actinomyces_unclassified were differentially enriched in s2. The bacteriome present in teeth with PEI with AP is complex and diverse. CMP using 2.5% NaOCl showed a high quantitatively and qualitatively disinfectant impact on the bacteriome present in PEI with AP.

Optimization of Amplicon-Based Sequencing for Large-Scale Diagnostics of Known Pome Viruses and Viroids

The implementation of reliable methods for the simultaneous detection of multiple viruses is challenging in plant viral diagnosis. In the present study, we report the development and effectiveness of an optimized version of a robust multiplexed PCR (HiPlex) followed by simultaneous targeted amplicon sequencing to detect 14 viruses and 5 viroids of pome fruit trees. We used amplicon sequencing data from 1,400 pome fruit tree samples previously diagnosed with the HiPlex v.1.0, which included 290 primer pairs for pome viruses. The analysis enabled the identification of highly efficient and specific primer pairs to be assembled in a new HiPlex (dubbed HiPlex v.2.0). Additionally, newly designed primers were implemented for 30% of targeted viruses and viroids. Overall, 116 primer pairs were assembled into the HiPlex v.2.0, resulting in a reduction of the number of primers and multiplex PCR reactions needed by 60 and 50%, respectively. The new HiPlex also includes two nepoviruses, tomato ringspot virus and tobacco ringspot virus, showing flexibility at augmenting and expanding the number of targeted diagnosed viruses using this approach. This optimized set of primers increased the cost-effectiveness and sensitivity while reducing background amplification. Comparable results for virus and viroid detection were obtained using the HiPlex v.2.0 and individual RT-qPCRs, even at a 10,000-fold dilution, demonstrating similar sensitivity to standard PCR-based diagnostics. This new HiPlex-based amplicon sequencing represents a powerful, sensitive, and low-cost tool for large-scale screening of pome fruit trees for all reported viruses and viroids infecting these crops. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease

BackgroundThe human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case–control results has made the identification of consistent and generalizable URT-disease associations difficult.ResultsIn order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case–control URT studies, with approximately 2–3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states.ConclusionsWe found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.

Multiple approaches in the study of ancient human microbiome

Abstract Research related to the analysis of microbial communities in ancient human samples began two decades ago. Since then, new technologies as well as new bioinformatic tools have been developed for the manipulation of massive data. All this together, with the theoretical knowledge generated from microbial ecology has expanded our understanding of the human microbiome. Despite the challenge of studying ancient samples and their microbiome, some approaches applied to the contemporary human microbiome have been successfully applied to ancient samples. Most studies in ancient samples have focused on taxonomic profiling at the community level with metagenomic or high-throughput 16S rRNA gene amplicon sequencing data. However, other approaches have emerged in order to get deeper understanding of the ancient human microbiome. Therefore, the aim of this review is to discuss all the approaches and methodologies successfully applied to ancient samples and ancient microbiome as well as the information that can be generated using them, in order to understand the evolution of human microbiome interactions throughout history.

Upstream land use with microbial downstream consequences: Iron and humic substances link to Legionella spp.

Intensified land use can disturb water quality, potentially increasing the abundance of bacterial pathogens, threatening public access to clean water. This threat involves both direct contamination of faecal bacteria as well as indirect factors, such as disturbed water chemistry and microbiota, which can lead to contamination. While direct contamination has been well described, the impact of indirect factors is less explored, despite the potential of severe downstream consequences on water supply. To assess direct and indirect downstream effects of buildings, farms, pastures and fields on potential water sources, we studied five Swedish lakes and their inflows. We analysed a total of 160 samples in a gradient of anthropogenic activity spanning four time points, including faecal and water-quality indicators. Through species distribution modelling, Random Forest and network analysis using 16S rRNA amplicon sequencing data, our findings highlight that land use indirectly impacts lakes via inflows. Land use impacted approximately one third of inflow microbiota taxa, in turn impacting ∼20–50 % of lake taxa. Indirect effects via inflows were also suggested by causal links between e.g. water colour and lake bacterial taxa, where this influenced the abundance of several freshwater bacteria, such as Polynucleobacter and Limnohabitans. However, it was not possible to identify direct effects on the lakes based on analysis of physiochemical- or microbial parameters. To avoid potential downstream consequences on water supply, it is thus important to consider possible indirect effects from upstream land use and inflows, even when no direct effects can be observed on lakes. Legionella (a genus containing bacterial pathogens) illustrated potential consequences, since the genus was particularly abundant in inflows and was shown to increase by the presence of pastures, fields, and farms. The approach presented here could be used to assess the suitability of lakes as alternative raw water sources or help to mitigate contaminations in important water catchments. Continued broad investigations of stressors on the microbial network can identify indirect effects, avoid enrichment of pathogens, and help secure water accessibility.

Seasonal Gene Profiling in Tuz Lake with Regard to Biogeochemical Cycling

Tuz Lake, a thalassohaline lake with a salt rate of 32%, is a unique habitat for a halophilic microbiome. Culture-dependent and independent methods have been applied to identify prokaryotic microbial diversity in Tuz Lake. However, the key processes and genes involved in biogeochemical cycles in Tuz Lake have not been investigated seasonally. The aim of the study is to investigate seasonal gene profiling in Tuz Lake associated with biogeochemical cycling and thereby reveal more about the ecosystem dynamics of this extreme environment. Therefore, the PICRUSt2 tool was applied to analyze the metabolic function of archaeal and bacterial diversity in Tuz Lake. As a result of metabolic functions based on 16S rDNA amplicon sequencing data, it was observed that methane production by H2 and CO2 by anaerobic archaea in Tuz Lake was the predominant methanogenesis pathway. It was determined that sulfur oxidation was the dominant sulfur metabolism, while the reductive citric acid cycle was the dominant carbon fixation pathway.

Abstract A023: Assessing the reproducibility crisis in vaginal microbiome studies for clinical applications in endometrial cancer

Abstract Recent associations between vaginal microbiota and gynecological cancer have led to high-throughput sequencing datasets identifying diagnostic biomarkers for Endometrial Cancer (EC). However, lack of bioinformatics standards results in inconsistent independent studies with poor reproducibility, making them clinically inapplicable. This study leverages publicly available amplicon sequence data to address the reproducibility of EC microbiome studies. We implemented bioinformatics pipelines from five studies to reproduce and measure the replicability of published results across cohorts using metrics such as alpha diversity, beta diversity and differentially expressed taxa. We further evaluated separability between benign and cancer patients at different taxonomic levels (phylum, class, order, family, and genus) within and across datasets using boosted tree classifiers and Area Under the Curve (AUC) as the performance metric. While we reproduced the general trend of observing higher microbial diversity in EC compared to healthy controls, we found irregularities in two cohorts. Using beta diversity distance metrics, we identified that histology alone explains less than 3% of the variance in all cohorts. Three microbiome differential abundance methods were used in the five studies. While they all agree on a decrease in the Lactobacillus genus in EC patients, there is no consensus on other taxa associated with EC. We also found that separability between benign and cancerous conditions is highest at the class level, having an AUC score of 0.86. In subsequent steps, we will perform an integrative analysis to identify an EC vaginal microbiome predictive signature that is preserved across all five cohorts, benefiting screening programs. Citation Format: Dollina D. Dodani, Aline Talhouk. Assessing the reproducibility crisis in vaginal microbiome studies for clinical applications in endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A023.

Annual recurrence of prokaryotic climax communities in shallow waters of the North Mediterranean.

In temperate coastal environments, wide fluctuations of biotic and abiotic factors drive microbiome dynamics. To link recurrent ecological patterns with planktonic microbial communities, we analysed a monthly-sampled 3-year time series of 16S rRNA amplicon sequencing data, alongside environmental variables, collected at two stations in the northern Adriatic Sea. Time series multivariate analyses allowed us to identify three stable, mature communities (climaxes), whose recurrence was mainly driven by changes in photoperiod and temperature. Mixotrophs (e.g., Ca. Nitrosopumilus, SUP05 clade, and Marine Group II) thrived under oligotrophic, low-light conditions, whereas copiotrophs (e.g., NS4 and NS5 clades) bloomed at higher temperatures and substrate availability. The early spring climax was characterised by a more diverse set of amplicon sequence variants, including copiotrophs associated with phytoplankton-derived organic matter degradation, and photo-auto/heterotrophic organisms (e.g., Synechococcus sp., Roseobacter clade), whose rhythmicity was linked to photoperiod lengthening. Through the identification of recurrent climax assemblages, we begin to delineate a typology of ecosystem based on microbiome composition and functionality, allowing for the intercomparison of microbial assemblages among different biomes, a still underachieved goal in the omics era.

Fungal Spore Richness and Abundance of Allergenic Taxa: Comparing a Portable Impactor and Passive Trap Indoors and Outdoors in an Urban Setting

Fungal spores are common airborne allergens, and fungal richness has been implicated in allergic disease. Amplicon sequencing of environmental DNA from air samples is a promising method to estimate fungal spore richness with semi-quantification of hundreds of taxa and can be combined with quantitative PCR to derive abundance estimates. However, it remains unclear how the choice of air sampling method influences these estimates. This study compared active sampling with a portable impactor and passive sampling with a passive trap over different durations to estimate fungal spore richness and the abundance of allergenic taxa. Air sampling was conducted indoors and outdoors at 12 residences, including repeated measurements with a portable impactor and passive traps with 1-day and 7-day durations. ITS2 amplicon sequence data were transformed to spore equivalents estimated by quantitative PCR, repeated active samples were combined, and abundance-based rarefaction was performed to standardize sample coverage for estimation of genus-level richness and spore abundance. Rarefied fungal richness was similar between methods indoors but higher for passive traps with a 7-day duration outdoors. Rarefied abundance of allergenic genera was similar between methods but some genera had lower abundance for passive traps with a 1-day duration, which differed indoors and outdoors indicating stochasticity in the collection of spores on collocated samplers. This study found that similar estimates of fungal spore richness and abundance of allergenic taxa can be obtained using a portable impactor or a passive trap within one day and that increased passive sample duration provides limited additional information.

Rubisco in high Arctic tidewater glacier‐marine systems: A new window into phytoplankton dynamics

AbstractThe hundreds of tidewater glaciers found in the Canadian Arctic Archipelago have the potential to enhance delivery of nutrients and other material to the surface ocean. Despite this, their influence on marine ecosystems, specifically phytoplankton, is poorly characterized. Here we developed and applied a quantitative mass spectrometry‐based approach to measure phytoplankton ribulose‐1,5‐bisphosphate carboxylase/oxygenase (Rubisco) concentrations to examine differences in productivity in glacierized and non‐glacierized marine systems in Jones Sound, Nunavut, within Inuit Nunangat. Comparisons to chloroplast 16S rRNA gene amplicon sequencing data suggested that these measurements detect the majority of Rubisco produced in Jones Sound. Because Rubisco catalyzes carbon fixation, we used these measurements to estimate total and group‐specific primary production potential, which were within the range of historical primary production measurements made using classical methods in this region. Our measurements also revealed that up to 2% of total protein in the water column is Rubisco, and that Rubisco concentrations are correlated with chlorophyll fluorescence, with maxima near the nitracline. Rubisco produced by diatom genera Chaetoceros and Thalassiosira were higher in marine regions influenced by glaciers, while Rubisco from Micromonas (Chlorophyta) was greater in non‐glacierized regions. This suggests that future climate scenarios may favor smaller phytoplankton groups, like Micromonas, with consequences for food webs and carbon cycling. This study broadens our understanding of how tidewater glaciers will impact phytoplankton communities, now and in a warmer future, and lays the foundation for using this mass spectrometry‐based approach to quantify phytoplankton group‐specific carbon fixation potential in other marine regions.

A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions.

Metagenomics, Metabolomics, and Metaproteomics have significantly advanced our knowledge of microbial communities by providing culture-independent insights into their composition and functional potential. However, a critical challenge in this field is the lack of standard and comprehensive metadata associated with raw data, hindering the ability to perform robust data stratifications and consider confounding factors. In this comprehensive review, we categorize publicly available microbiome data into five types: shotgun sequencing, amplicon sequencing, metatranscriptomic, metabolomic, and metaproteomic data. We explore the importance of metadata for data reuse and address the challenges in collecting standardized metadata. We also, assess the limitations in metadata collection of existing public repositories collecting metagenomic data. This review emphasizes the vital role of metadata in interpreting and comparing datasets and highlights the need for standardized metadata protocols to fully leverage metagenomic data's potential. Furthermore, we explore future directions of implementation of Machine Learning (ML) in metadata retrieval, offering promising avenues for a deeper understanding of microbial communities and their ecological roles. Leveraging these tools will enhance our insights into microbial functional capabilities and ecological dynamics in diverse ecosystems. Finally, we emphasize the crucial metadata role in ML models development.

Targeted Screening of Fiber Degrading Bacteria with Probiotic Function in Herbivore Feces.

Cellulolytic bacteria with probiotic functions play a crucial role in promoting the intestinal health in herbivores. In this study, we aimed to correlate the 16S rRNA gene amplicon sequencing and fiber-degrading enzyme activity data from six different herbivore feces samples. By utilizing the separation and screening steps of probiotics, we targeted and screened high-efficiency fiber-degrading bacteria with probiotic functions. The animals included Maiwa Yak (MY), Holstein cow (CC), Tibetan sheep (TS), Southern Sichuan black goat (SG), Sichuan white rex rabbit (CR), and New Zealand white rabbit (ZR). The results showed that the enzymes associated with fiber degradation were higher in goat and sheep feces compared to cattle and rabbit's feces. Correlation analysis revealed that Bacillus and Fibrobacter were positively correlated with five types of fiber-degrading related enzymes. Notably, the relative abundance of Bacillus in the feces of Tibetan sheep was significantly higher than that of other five herbivores. A strain TS5 with good cellulose decomposition ability from the feces of Tibetan sheep by Congored staining, filter paper decomposition test, and enzyme activity determination was isolated. The strain was identified as Bacillus velezensis by biological characteristics, biochemical analysis, and 16S rRNA gene sequencing. To test the probiotic properties of Bacillus velezensis TS5, we evaluated its tolerance to acid and bile salt, production of digestive enzymes, antioxidants, antibacterial activity, and adhesion ability. The results showed that the strain had good tolerance to pH 2.0 and 0.3% bile salts, as well as good potential to produce cellulase, protease, amylase, and lipase. This strain also had good antioxidant capacity and the ability to antagonistic Staphylococcus aureus BJ216, Salmonella SC06, Enterotoxigenic Escherichia coli CVCC196, and Escherichia coli ATCC25922. More importantly, the strain had good self-aggregation and Caco-2 cell adhesion rate. In addition, we tested the safety of Bacillus velezensis TS5 by hemolysis test, antimicrobial susceptibility test, and acute toxicity test in mice. The results showed that the strain had no hemolytic phenotype, did not develop resistance to 19 commonly used antibiotics, had no cytotoxicity to Caco-2, and did not have acute toxic harm to mice. In summary, this study targeted isolated and screened a strain of Bacillus velezensis TS5 with high fiber-degrading ability and probiotic potency. This strain can be used as a potential probiotic for feeding microbial preparations for ruminants.

The gut microbiomes of Channel Island foxes and island spotted skunks exhibit fine-scale differentiation across host species and island populations.

California's Channel Islands are home to two endemic mammalian carnivores: island foxes (Urocyon littoralis) and island spotted skunks (Spilogale gracilis amphiala). Although it is rare for two insular terrestrial carnivores to coexist, these known competitors persist on both Santa Cruz Island and Santa Rosa Island. We hypothesized that examination of their gut microbial communities would provide insight into the factors that enable this coexistence, as microbial symbionts often reflect host evolutionary history and contemporary ecology. Using rectal swabs collected from island foxes and island spotted skunks sampled across both islands, we generated 16S rRNA amplicon sequencing data to characterize their gut microbiomes. While island foxes and island spotted skunks both harbored the core mammalian microbiome, host species explained the largest proportion of variation in the dataset. We further identified intraspecific variation between island populations, with greater differentiation observed between more specialist island spotted skunk populations compared to more generalist island fox populations. This pattern may reflect differences in resource utilization following fine-scale niche differentiation. It may further reflect evolutionary differences regarding the timing of intraspecific separation. Considered together, this study contributes to the growing catalog of wildlife microbiome studies, with important implications for understanding how eco-evolutionary processes enable the coexistence of terrestrial carnivores-and their microbiomes-in island environments.

THE COLONIC MUCOSAL MICROBIOME IN IBD-ASSOCIATED ARTHRITIS IS MORE VARIABLE THAN IN IBD ALONE

Abstract BACKGROUND Inflammatory bowel disease (IBD)-associated arthritis affects over 25% of those with IBD and is associated with several risk factors including disease location. The intestinal microbiome varies throughout the intestinal tract and is thought to play a role in the development of IBD, although the precise mechanism remains unexplored. To better characterize its relationship with IBD-associated arthritis, we analyzed the intestinal microbiome from a subset of subjects in the LOCATION-IBD cohort. METHODS Microbiome analysis was performed on 16S rRNA V3V4 amplicon sequencing data generated from mucosal biopsies from the terminal ileum (TI), hepatic flexure (HF), and the distal descending colon (DDC) of participants in the LOCATION-IBD cohort. Alpha diversity was assessed using the Shannon index, while beta diversity between samples from the same participant were assessed using Jenson-Shannon Divergence (JSD). ZicoSeq was used to assess differential abundances in composition between those with vs without IBD-associated arthritis. RESULTS In this analysis, we included a subset of samples from participants in the LOCATION-IBD cohort with (n= 68 from 25 participants) and without (n = 86 from 29 participants) joint EIMs and with joint pain of unclear etiology (n= 14 from 5 participants). Overall, samples clustered predominantly based on participant, and similar genera were present across TI, HF, and DDC mucosal samples. Shannon diversity was similar across samples, regardless of the associated arthritis category, though diversity was lower in those with CD compared to those with UC (p-value = 0.0007, Tukey post-hoc p-value = 0.0004) and trended to be higher in sites of inflammation (p-value = 0.0645). JSDs between samples for an individual participant were higher for those with compared to those without IBD-associated arthritis (p-value = 0.038). In those with joint EIMs, Flavonifractor and Fusicatenibacter were significantly lower without accounting for sampling location, whereas other species including Lachnoclostridium (increased) and Fusobacterium (decreased) were noted in the proximal colon. CONCLUSIONS To our knowledge, this represents the first assessment of the mucosal microbiome across several intestinal sites in individuals with and without IBD-associated arthritis. Our finding that similar bacteria are found across the terminal ileum, proximal colon, and distal colon, but that less site-to-site concordance is seen in those with IBD-associated arthritis, aligns with previous findings that the involvement of specific colonic segments is associated with IBD-associated arthritis. Further, our finding that the abundances of specific bacteria are altered, frequently in a site-specific manner, identifies potential opportunities for future studies.

A multi-study analysis enables identification of potential microbial features associated with skin aging signs.

Introduction: During adulthood, the skin microbiota can be relatively stable if environmental conditions are also stable, yet physiological changes of the skin with age may affect the skin microbiome and its function. The microbiome is an important factor to consider in aging since it constitutes most of the genes that are expressed on the human body. However, severity of specific aging signs (one of the parameters used to measure "apparent" age) and skin surface quality (e.g., texture, hydration, pH, sebum, etc.) may not be indicative of chronological age. For example, older individuals can have young looking skin (young apparent age) and young individuals can be of older apparent age. Methods: Here we aim to identify microbial taxa of interest associated to skin quality/aging signs using a multi-study analysis of 13 microbiome datasets consisting of 16S rRNA amplicon sequence data and paired skin clinical data from the face. Results: We show that there is a negative relationship between microbiome diversity and transepidermal water loss, and a positive association between microbiome diversity and age. Aligned with a tight link between age and wrinkles, we report a global positive association between microbiome diversity and Crow's feet wrinkles, but with this relationship varying significantly by sub-study. Finally, we identify taxa potentially associated with wrinkles, TEWL and corneometer measures. Discussion: These findings represent a key step towards understanding the implication of the skin microbiota in skin aging signs.