Diversity of human salivary heparan sulfate.

The human oral cavity and upper airway serves as an early barrier and reservoir in the transmission of SARS-CoV-2. Saliva in this microenvironment may serve as a key host factor that can modulate susceptibility to infection and eventual infection of the lower respiratory tract. We sought to analyze the content and composition of heparan sulfate, a glycosaminoglycan identified as an important co-receptor for viral entry, and whether there is any correlation with SARS-CoV-2 infection. We enlisted 98 participants stratified by age, gender, race, and COVID-19 history. Notably, the concentration of heparan sulfate in saliva increased with age, and its composition showed a wide range of variability within each age group independently of age. Heparan sulfate concentration and composition did not differ significantly with gender, ethnicity or race. Compared to patients with no COVID-19 history, patients with previous infection had a similar salivary heparan sulfate concentration, but significant increases in overall sulfation were noted. Moreover, in a subset of participants, for which data was available pre- and post- infection, significant elevation in N-sulfoglucosamine in heparan sulfate was observed post- COVID-19. Examination of salivary bacterial 16S rRNA, showed a significant reduction in species predicted to possess heparan sulfate-modifying capacity among participants >60 years old, which correlates with the increase in heparan sulfate content in older individuals. These findings demonstrate a surprisingly wide variation in heparan sulfate content and composition in saliva across the sampled population and confirm other findings showing variation in content and composition of glycosaminoglycans in blood and urine.

Integrated Multi-Cohort Analysis of the Parkinson's Disease Gut Metagenome.

BACKGROUND: The gut microbiome is altered in several neurologic disorders, including Parkinson's disease (PD). OBJECTIVES: The aim is to profile the fecal gut metagenome in PD for alterations in microbial composition, taxon abundance, metabolic pathways, and microbial gene products, and their relationship with disease progression. METHODS: Shotgun metagenomic sequencing was conducted on 244 stool donors from two independent cohorts in the United States, including individuals with PD (n = 48, n = 47, respectively), environmental household controls (HC, n = 29, n = 30), and community population controls (PC, n = 41, n = 49). Microbial features consistently altered in PD compared to HC and PC subjects were identified. Data were cross-referenced to public metagenomic data sets from two previous studies in Germany and China to determine generalizable microbiome features. RESULTS: We find several significantly altered taxa between PD and controls within the two cohorts sequenced in this study. Analysis across global cohorts returns consistent changes only in Intestinimonas butyriciproducens. Pathway enrichment analysis reveals disruptions in microbial carbohydrate and lipid metabolism and increased amino acid and nucleotide metabolism in PD. Global gene-level signatures indicate an increased response to oxidative stress, decreased cellular growth and microbial motility, and disrupted intercommunity signaling. CONCLUSIONS: A metagenomic meta-analysis of PD shows consistent and novel alterations in functional metabolic potential and microbial gene abundance across four independent studies from three continents. These data reveal that stereotypic changes in the functional potential of the gut microbiome are a consistent feature of PD, highlighting potential diagnostic and therapeutic avenues for future research. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Bacterial and Chemical Evidence of Coastal Water Pollution from the Tijuana River in Sea Spray Aerosol.

Roughly half of the human population lives near the coast, and coastal water pollution (CWP) is widespread. Coastal waters along Tijuana, Mexico, and Imperial Beach (IB), USA, are frequently polluted by millions of gallons of untreated sewage and stormwater runoff. Entering coastal waters causes over 100 million global annual illnesses, but CWP has the potential to reach many more people on land via transfer in sea spray aerosol (SSA). Using 16S rRNA gene amplicon sequencing, we found sewage-associated bacteria in the polluted Tijuana River flowing into coastal waters and returning to land in marine aerosol. Tentative chemical identification from non-targeted tandem mass spectrometry identified anthropogenic compounds as chemical indicators of aerosolized CWP, but they were ubiquitous and present at highest concentrations in continental aerosol. Bacteria were better tracers of airborne CWP, and 40 tracer bacteria comprised up to 76% of the bacteria community in IB air. These findings confirm that CWP transfers in SSA and exposes many people along the coast. Climate change may exacerbate CWP with more extreme storms, and our findings call for minimizing CWP and investigating the health effects of airborne exposure.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Qiita: rapid, web-enabled microbiome meta-analysis.

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

The impact of skin care products on skin chemistry and microbiome dynamics.

BACKGROUND: Use of skin personal care products on a regular basis is nearly ubiquitous, but their effects on molecular and microbial diversity of the skin are unknown. We evaluated the impact of four beauty products (a facial lotion, a moisturizer, a foot powder, and a deodorant) on 11 volunteers over 9 weeks. RESULTS: Mass spectrometry and 16S rRNA inventories of the skin revealed decreases in chemical as well as in bacterial and archaeal diversity on halting deodorant use. Specific compounds from beauty products used before the study remain detectable with half-lives of 0.5-1.9 weeks. The deodorant and foot powder increased molecular, bacterial, and archaeal diversity, while arm and face lotions had little effect on bacterial and archaeal but increased chemical diversity. Personal care product effects last for weeks and produce highly individualized responses, including alterations in steroid and pheromone levels and in bacterial and archaeal ecosystem structure and dynamics. CONCLUSIONS: These findings may lead to next-generation precision beauty products and therapies for skin disorders.

Suppression of the gut microbiome ameliorates age-related arterial dysfunction and oxidative stress in mice.

KEY POINTS: Age-related arterial dysfunction, characterized by oxidative stress- and inflammation-mediated endothelial dysfunction and arterial stiffening, is the primary risk factor for cardiovascular diseases. To investigate whether age-related changes in the gut microbiome may mediate arterial dysfunction, we suppressed gut microbiota in young and old mice with a cocktail of broad-spectrum, poorly-absorbed antibiotics in drinking water for 3-4 weeks. In old mice, antibiotic treatment reversed endothelial dysfunction and arterial stiffening and attenuated vascular oxidative stress and inflammation. To provide insight into age-related changes in gut microbiota that may underlie these observations, we show that ageing altered the abundance of microbial taxa associated with gut dysbiosis and increased plasma levels of the adverse gut-derived metabolite trimethylamine N-oxide. The results of the present study provide the first proof-of-concept evidence that the gut microbiome is an important mediator of age-related arterial dysfunction and therefore may be a promising therapeutic target for preserving arterial function with ageing, thereby reducing the risk of cardiovascular diseases. ABSTRACT: Oxidative stress-mediated arterial dysfunction (e.g. endothelial dysfunction and large elastic artery stiffening) is the primary mechanism driving age-related cardiovascular diseases. Accumulating evidence suggests the gut microbiome modulates host physiology because dysregulation ('gut dysbiosis') has systemic consequences, including promotion of oxidative stress. The present study aimed to determine whether the gut microbiome modulates arterial function with ageing. We measured arterial function in young and older mice after 3-4 weeks of treatment with broad-spectrum, poorly-absorbed antibiotics to suppress the gut microbiome. To identify potential mechanistic links between the gut microbiome and age-related arterial dysfunction, we sequenced microbiota from young and older mice and measured plasma levels of the adverse gut-derived metabolite trimethylamine N-oxide (TMAO). In old mice, antibiotics reversed endothelial dysfunction [area-under-the-curve carotid artery dilatation to acetylcholine in young: 345 ± 16 AU vs. old control (OC): 220 ± 34 AU, P < 0.01; vs. old antibiotic-treated (OA): 334 ± 15 AU; P < 0.01 vs. OC] and arterial stiffening (aortic pulse wave velocity in young: 3.62 ± 0.15 m  s-1  vs. OC: 4.43 ± 0.38 m  s-1 ; vs. OA: 3.52 ± 0.35 m  s-1 ; P = 0.03). These improvements were accompanied by lower oxidative stress and greater antioxidant enzyme expression. Ageing altered the abundance of gut microbial taxa associated with gut dysbiosis. Lastly, plasma TMAO was higher with ageing (young: 2.6 ± 0.4 µmol  L-1   vs. OC: 7.2 ± 2.0 µmol  L-1 ; P < 0.0001) and suppressed by antibiotic treatment (OA: 1.2 ± 0.2 µmol  L-1 ; P < 0.0001 vs. OC). The results of the present study provide the first evidence for the gut microbiome being an important mediator of age-related arterial dysfunction and oxidative stress and suggest that therapeutic strategies targeting gut microbiome health may hold promise for preserving arterial function and reducing cardiovascular risk with ageing in humans.

Molecular cartography of the human skin surface in 3D.

The human skin is an organ with a surface area of 1.5-2 m(2) that provides our interface with the environment. The molecular composition of this organ is derived from host cells, microbiota, and external molecules. The chemical makeup of the skin surface is largely undefined. Here we advance the technologies needed to explore the topographical distribution of skin molecules, using 3D mapping of mass spectrometry data and microbial 16S rRNA amplicon sequences. Our 3D maps reveal that the molecular composition of skin has diverse distributions and that the composition is defined not only by skin cells and microbes but also by our daily routines, including the application of hygiene products. The technological development of these maps lays a foundation for studying the spatial relationships of human skin with hygiene, the microbiota, and environment, with potential for developing predictive models of skin phenotypes tailored to individual health.

Meta-analyses of studies of the human microbiota.

Our body habitat-associated microbial communities are of intense research interest because of their influence on human health. Because many studies of the microbiota are based on the same bacterial 16S ribosomal RNA (rRNA) gene target, they can, in principle, be compared to determine the relative importance of different disease/physiologic/developmental states. However, differences in experimental protocols used may produce variation that outweighs biological differences. By comparing 16S rRNA gene sequences generated from diverse studies of the human microbiota using the QIIME database, we found that variation in composition of the microbiota across different body sites was consistently larger than technical variability across studies. However, samples from different studies of the Western adult fecal microbiota generally clustered by study, and the 16S rRNA target region, DNA extraction technique, and sequencing platform produced systematic biases in observed diversity that could obscure biologically meaningful compositional differences. In contrast, systematic compositional differences in the fecal microbiota that occurred with age and between Western and more agrarian cultures were great enough to outweigh technical variation. Furthermore, individuals with ileal Crohn's disease and in their third trimester of pregnancy often resembled infants from different studies more than controls from the same study, indicating parallel compositional attributes of these distinct developmental/physiological/disease states. Together, these results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.

Vertebrate decomposition is accelerated by soil microbes.

Carrion decomposition is an ecologically important natural phenomenon influenced by a complex set of factors, including temperature, moisture, and the activity of microorganisms, invertebrates, and scavengers. The role of soil microbes as decomposers in this process is essential but not well understood and represents a knowledge gap in carrion ecology. To better define the role and sources of microbes in carrion decomposition, lab-reared mice were decomposed on either (i) soil with an intact microbial community or (ii) soil that was sterilized. We characterized the microbial community (16S rRNA gene for bacteria and archaea, and the 18S rRNA gene for fungi and microbial eukaryotes) for three body sites along with the underlying soil (i.e., gravesoils) at time intervals coinciding with visible changes in carrion morphology. Our results indicate that mice placed on soil with intact microbial communities reach advanced stages of decomposition 2 to 3 times faster than those placed on sterile soil. Microbial communities associated with skin and gravesoils of carrion in stages of active and advanced decay were significantly different between soil types (sterile versus untreated), suggesting that substrates on which carrion decompose may partially determine the microbial decomposer community. However, the source of the decomposer community (soil- versus carcass-associated microbes) was not clear in our data set, suggesting that greater sequencing depth needs to be employed to identify the origin of the decomposer communities in carrion decomposition. Overall, our data show that soil microbial communities have a significant impact on the rate at which carrion decomposes and have important implications for understanding carrion ecology.

Clearing the plate: a strategic approach to mitigate well-to-well contamination in large-scale microbiome studies.

Large-scale studies are essential to answer questions about complex microbial communities that can be extremely dynamic across hosts, environments, and time points. However, managing acquisition, processing, and analysis of large numbers of samples poses many challenges, with cross-contamination being the biggest obstacle. Contamination complicates analysis and results in sample loss, leading to higher costs and constraints on mixed sample type study designs. While many researchers opt for 96-well plates for their workflows, these plates present a significant issue: the shared seal and weak separation between wells leads to well-to-well contamination. To address this concern, we propose an innovative high-throughput approach, termed as the Matrix method, which employs barcoded Matrix Tubes for sample acquisition. This method is complemented by a paired nucleic acid and metabolite extraction, utilizing 95% (vol/vol) ethanol to stabilize microbial communities and as a solvent for extracting metabolites. Comparative analysis between conventional 96-well plate extractions and the Matrix method, measuring 16S rRNA gene levels via quantitative polymerase chain reaction, demonstrates a notable decrease in well-to-well contamination with the Matrix method. Metagenomics, 16S rRNA gene amplicon sequencing (16S), and untargeted metabolomics analysis via liquid chromatography-tandem mass spectrometry (LC-MS/MS) confirmed that the Matrix method recovers reproducible microbial and metabolite compositions that can distinguish between subjects. This advancement is critical for large-scale study design as it minimizes well-to-well contamination and technical variation, shortens processing times, and integrates with automated infrastructure for enhancing sample randomization and metadata generation. IMPORTANCE: Understanding dynamic microbial communities typically requires large-scale studies. However, handling large numbers of samples introduces many challenges, with cross-contamination being a major issue. It not only complicates analysis but also leads to sample loss and increased costs and restricts diverse study designs. The prevalent use of 96-well plates for nucleic acid and metabolite extractions exacerbates this problem due to their wells having little separation and being connected by a single plate seal. To address this, we propose a new strategy using barcoded Matrix Tubes, showing a significant reduction in cross-contamination compared to conventional plate-based approaches. Additionally, this method facilitates the extraction of both nucleic acids and metabolites from a single tubed sample, eliminating the need to collect separate aliquots for each extraction. This innovation improves large-scale study design by shortening processing times, simplifying analysis, facilitating metadata curation, and producing more reliable results.

Medication Use is Associated with Distinct Microbial Features in Anxiety and Depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by DSM-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing and shallow shotgun sequencing were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and NeuroMAP CoBRE cohorts. The results highlight the significant influence of medication use; antidepressant use is associated with significant differences in gut microbiota beta diversity and has a larger effect size than NPD diagnosis. Next, specific microbes were associated with ANXD and MDD, highlighting their potential for non-pharmacological intervention. Finally, the study demonstrated the capability of Random Forest classifiers to predict diagnoses of NPD and medication use from microbial profiles, suggesting a promising direction for the use of gut microbiota as biomarkers for NPD. The findings suggest that future research on the gut microbiota's role in NPD and its interactions with pharmacological treatments are needed.

A conserved interdomain microbial network underpins cadaver decomposition despite environmental variables.

Microbial breakdown of organic matter is one of the most important processes on Earth, yet the controls of decomposition are poorly understood. Here we track 36 terrestrial human cadavers in three locations and show that a phylogenetically distinct, interdomain microbial network assembles during decomposition despite selection effects of location, climate and season. We generated a metagenome-assembled genome library from cadaver-associated soils and integrated it with metabolomics data to identify links between taxonomy and function. This universal network of microbial decomposers is characterized by cross-feeding to metabolize labile decomposition products. The key bacterial and fungal decomposers are rare across non-decomposition environments and appear unique to the breakdown of terrestrial decaying flesh, including humans, swine, mice and cattle, with insects as likely important vectors for dispersal. The observed lockstep of microbial interactions further underlies a robust microbial forensic tool with the potential to aid predictions of the time since death.

The Molecular Effect of Wearing Silver-Threaded Clothing on the Human Skin.

With growing awareness that what we put in and on our bodies affects our health and wellbeing, little is still known about the impact of textiles on the human skin. Athletic wear often uses silver threading to improve hygiene, but little is known about its effect on the body's largest organ. In this study, we investigated the impact of such clothing on the skin's chemistry and microbiome. Samples were collected from different body sites of a dozen volunteers over the course of 12 weeks. The changes induced by the antibacterial clothing were specific for individuals, but more so defined by gender and body site. Unexpectedly, the microbial biomass on skin increased in the majority of the volunteers when wearing silver-threaded T-shirts. Although the most abundant taxa remained unaffected, silver caused an increase in diversity and richness of low-abundant bacteria and a decrease in chemical diversity. Both effects were mainly observed for women. The hallmark of the induced changes was an increase in the abundance of various monounsaturated fatty acids (MUFAs), especially in the upper back. Several microbe-metabolite associations were uncovered, including Cutibacterium, detected in the upper back area, which was correlated with the distribution of MUFAs, and Anaerococcus spp. found in the underarms, which were associated with a series of different bile acids. Overall, these findings point to a notable impact of the silver-threaded material on the skin microbiome and chemistry. We observed that relatively subtle changes in the microbiome result in pronounced shifts in molecular composition. IMPORTANCE The impact of silver-threaded material on human skin chemistry and microbiome is largely unknown. Although the most abundant taxa remained unaffected, silver caused an increase in diversity and richness of low-abundant bacteria and a decrease in chemical diversity. The major change was an increase in the abundance of various monounsaturated fatty acids that were also correlated with Cutibacterium. Additionally, Anaerococcus spp., found in the underarms, were associated with different bile acids in the armpit samples. Overall, the impact of the silver-threaded clothing was gender and body site specific.

Stability of the Fecal and Oral Microbiome over 2 Years at -80°C for Multiple Collection Methods.

BACKGROUND: In prospective cohorts, biological samples are generally stored over long periods before an adequate number of cases have accrued. We investigated the impact of sample storage at -80°C for 2 years on the stability of the V4 region of the 16S rRNA gene across seven different collection methods (i.e., no additive, 95% ethanol, RNAlater stabilization solution, fecal occult blood test cards, and fecal immunochemical test tubes for feces; OMNIgene ORAL tubes and Scope mouthwash for saliva) among 51 healthy volunteers. METHODS: Intraclass correlation coefficients (ICC) were calculated for the relative abundance of the top three phyla, the 20 most abundant genera, three alpha-diversity metrics, and the first principal coordinates of three beta-diversity matrices. RESULTS: The subject variability was much higher than the variability introduced by the sample collection type, and storage time. For fecal samples, microbial stability over 2 years was high across collection methods (range, ICCs = 0.70-0.99), except for the samples collected with no additive (range, ICCs = 0.23-0.83). For oral samples, most microbiome diversity measures were stable over time with ICCs above 0.74; however, ICCs for the samples collected with Scope mouthwash were lower for two alpha-diversity measures, Faith's phylogenetic diversity (0.23) and the observed number of operational taxonomic units (0.23). CONCLUSIONS: Fecal and oral samples in most used collection methods are stable for microbiome analyses after 2 years at -80°C, except for fecal samples with no additive. IMPACT: This study provides evidence that samples stored for an extended period from prospective studies are useful for microbiome analyses.

Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts.

IMPORTANCE: There are challenges in merging microbiome data from diverse research groups due to the intricate and multifaceted nature of such data. To address this, we utilized a combination of machine-learning (ML) models to analyze 16S sequencing data from a substantial set of gut microbiome samples, sourced from 12 distinct infant cohorts that were gathered prospectively. Our initial focus was on the mode of delivery due to its prior association with changes in infant gut microbiomes. Through ML analysis, we demonstrated the effective merging and comparison of various gut microbiome data sets, facilitating the identification of robust microbiome biomarkers applicable across varied study populations.

The Host-Microbiome Response to Hyperbaric Oxygen Therapy in Ulcerative Colitis Patients.

BACKGROUND & AIMS: Hyperbaric oxygen therapy (HBOT) is a promising treatment for moderate-to-severe ulcerative colitis. However, our current understanding of the host and microbial response to HBOT remains unclear. This study examined the molecular mechanisms underpinning HBOT using a multi-omic strategy. METHODS: Pre- and post-intervention mucosal biopsies, tissue, and fecal samples were collected from HBOT phase 2 clinical trials. Biopsies and fecal samples were subjected to shotgun metaproteomics, metabolomics, 16s rRNA sequencing, and metagenomics. Tissue was subjected to bulk RNA sequencing and digital spatial profiling (DSP) for single-cell RNA and protein analysis, and immunohistochemistry was performed. Fecal samples were also used for colonization experiments in IL10-/- germ-free UC mouse models. RESULTS: Proteomics identified negative associations between HBOT response and neutrophil azurophilic granule abundance. DSP identified an HBOT-specific reduction of neutrophil STAT3, which was confirmed by immunohistochemistry. HBOT decreased microbial diversity with a proportional increase in Firmicutes and a secondary bile acid lithocholic acid. A major source of the reduction in diversity was the loss of mucus-adherent taxa, resulting in increased MUC2 levels post-HBOT. Targeted database searching revealed strain-level associations between Akkermansia muciniphila and HBOT response status. Colonization of IL10-/- with stool obtained from HBOT responders resulted in lower colitis activity compared with non-responders, with no differences in STAT3 expression, suggesting complementary but independent host and microbial responses. CONCLUSIONS: HBOT reduces host neutrophil STAT3 and azurophilic granule activity in UC patients and changes in microbial composition and metabolism in ways that improve colitis activity. Intestinal microbiota, especially strain level variations in A muciniphila, may contribute to HBOT non-response.

Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity.

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth's environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

Enhancing untargeted metabolomics using metadata-based source annotation.

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

Evaluation of the Effect of Storage Methods on Fecal, Saliva, and Skin Microbiome Composition.

As the number of human microbiome studies expand, it is increasingly important to identify cost-effective, practical preservatives that allow for room temperature sample storage. Here, we reanalyzed 16S rRNA gene amplicon sequencing data from a large sample storage study published in 2016 and performed shotgun metagenomic sequencing on remnant DNA from this experiment. Both results support the initial findings that 95% ethanol, a nontoxic, cost-effective preservative, is effective at preserving samples at room temperature for weeks. We expanded on this analysis by collecting a new set of fecal, saliva, and skin samples to determine the optimal ratio of 95% ethanol to sample. We identified optimal collection protocols for fecal samples (storing a fecal swab in 95% ethanol) and saliva samples (storing unstimulated saliva in 95% ethanol at a ratio of 1:2). Storing skin swabs in 95% ethanol reduced microbial biomass and disrupted community composition, highlighting the difficulties of low biomass sample preservation. The results from this study identify practical solutions for large-scale analyses of fecal and oral microbial communities.IMPORTANCE Expanding our knowledge of microbial communities across diverse environments includes collecting samples in places far from the laboratory. Identifying cost-effective preservatives that will enable room temperature storage of microbial communities for sequencing analysis is crucial to enabling microbiome analyses across diverse populations. Here, we validate findings that 95% ethanol efficiently preserves microbial composition at room temperature for weeks. We also identified the optimal ratio of 95% ethanol to sample for stool and saliva to preserve both microbial load and composition. These results provide rationale for an accessible, nontoxic, cost-effective solution that will enable crowdsourcing microbiome studies, such as The Microsetta Initiative, and lower the barrier for collecting diverse samples.