Creating a 3D microbial and chemical snapshot of a human habitat

Biocontrol in built environments to reduce pathogen exposure and infection risk

The microbiome of the built environment comprises bacterial, archaeal, fungal, and viral communities associated with human-made structures. Even though most of these microbes are benign, antibiotic-resistant pathogens can colonize and emerge indoors, creating infection risk through surface transmission or inhalation. Several studies have catalogued the microbial composition and ecology in different built environment types. These have informed in vitro studies that seek to replicate the physicochemical features that promote pathogenic survival and transmission, ultimately facilitating the development and validation of intervention techniques used to reduce pathogen accumulation. Such interventions include using Bacillus-based cleaning products on surfaces or integrating bacilli into printable materials. Though this work is in its infancy, early research suggests the potential to use microbial biocontrol to reduce hospital- and home-acquired multidrug-resistant infections. Although these techniques hold promise, there is an urgent need to better understand the microbial ecology of built environments and to determine how these biocontrol solutions alter species interactions. This review covers our current understanding of microbial ecology of the built environment and proposes strategies to translate that knowledge into effective biocontrol of antibiotic-resistant pathogens.

Recent advances in single-cell engineered live biotherapeutic products research for skin repair and disease treatment

The human microbiome has emerged as a key player in maintaining skin health, and dysbiosis has been linked to various skin disorders. Amidst growing concerns regarding the side effects of antibiotic treatments, the potential of live biotherapeutic products (LBPs) in restoring a healthy microbiome has garnered significant attention. This review aims to evaluate the current state of the art of the genetically or metabolically engineered LBPs, termed single-cell engineered LBPs (eLBPs), for skin repair and disease treatment. While some studies demonstrate promising outcomes, the translation of eLBPs into clinical applications remains a significant hurdle. Substantial concerns arise regarding the practical implementation and scalability of eLBPs, despite the evident potential they hold in targeting specific cells and delivering therapeutic agents. This review underscores the need for further research, robust clinical trials, and the exploration of current advances in eLBP-based bioengineered bacterial chassis and new outlooks to substantiate the viability and effectiveness of eLBPs as a transformative approach in skin repair and disease intervention.

Ecosystem-specific microbiota and microbiome databases in the era of big data

The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB's), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB's, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB's.

Determining Informative Microbial Single Nucleotide Polymorphisms for Human Identification

The skin microbiome is a highly abundant and relatively stable source of DNA that may be utilized for human identification (HID). In this study, a set of single nucleotide polymorphisms (SNPs) with a high mean estimated Wright's fixation index (F_ST) (>0.1) and widespread abundance (found in ≥75% of samples compared) were selected from a diverse set of markers in the hidSkinPlex panel. The least absolute shrinkage and selection operator (LASSO) was used in a novel machine learning framework to generate a SNP panel and predict the human host from skin microbiome samples collected from the hand, manubrium, and foot. The framework was devised to emulate a new unknown person introduced to the algorithm and to match samples from that person against a population database. Unknown samples were classified with 96% accuracy (Matthews correlation coefficient [MCC], 0.954) in the test (n = 225 samples) data set. A final panel of informative SNPs was determined for HID (hidSkinPlex+) using all 51 individuals sampled at three body sites in triplicate. The hidSkinPlex+ panel comprises 365 SNPs and yielded prediction accuracy for the correct host of 95% (MCC = 0.949). The accuracy of the hidSkinPlex+ panel may be somewhat overestimated due to using 26 individuals from the training data set for the selection of the final panel. However, this accuracy still provides an indication of performance when tested on new samples. IMPORTANCE One of the fundamental goals in forensic genetics is to identify the source of biological evidence. Methods for detecting human DNA have advanced and can be quite sensitive, but not all DNA samples are amenable to current methods. However, the human skin microbiome is a source of DNA with high copy numbers, and it has the potential for high discriminatory power. The hidSkinPlex panel has been used for HID; however, some aspects of it could be improved. Missing information is ambiguous, as it is unclear if marker drop-out is a by-product of a low-template sample or if the reasons for not observing a marker are biological. Such ambiguity may confound methods for HID, and as such, an improved marker set (hidSkinPlex+) was designed that is considerably smaller and more robust to drop-out (365 SNPs contained in 135 markers) yet still can be used to accurately predict the human host.

Enabling Quantitative Analysis of Surface Small Molecules for Exposomics and Behavioral Studies

Workplace chemical exposures are a major source of occupational injury. Although over half of these are skin exposures, exposomics research often focuses on chemical levels in the air or in worker biofluids such as blood and urine. Until now, one limitation has been the lack of methods to quantitatively measure surface chemical transfer. Outside the realm of harmful chemicals, the small molecules we leave behind on surfaces can also reveal important aspects of human behavior. In this study, we developed a swab-based quantitative approach to determine small molecule concentrations across common surfaces. We demonstrate its utility using one drug, cyclobenzaprine, on metal surfaces, and two human-derived metabolites, carnitine and phenylacetylglutamine, on four common surfaces: linoleum flooring, plastified laboratory workbench, metal, and Plexiglas. We observed peak areas proportional to surface analyte concentrations at 45 min and 1 week after deposition, enabling quantification of molecule abundance on workplace built environment surfaces. In contrast, this method was unsuitable for analysis of oleanolic acid, for which we did not observe a strong linear proportional relationship following swab-based recovery from surfaces. Overall, this method paves the way for future quantitative exposomics studies in analyte-specific and surface-specific frameworks.

Chemical Cartography Approaches to Study Trypanosomatid Infection

Pathogen tropism and disease tropism refer to the tissue locations selectively colonized or damaged by pathogens, leading to localized disease symptoms. Human-infective trypanosomatid parasites include Trypanosoma cruzi, the causative agent of Chagas disease; Trypanosoma brucei, the causative agent of sleeping sickness; and Leishmania species, causative agents of leishmaniasis. Jointly, they affect 20 million people across the globe. These parasites show specific tropism: heart, esophagus, colon for T. cruzi, adipose tissue, pancreas, skin, circulatory system and central nervous system for T. brucei, skin for dermotropic Leishmania strains, and liver, spleen, and bone marrow for viscerotropic Leishmania strains. A spatial perspective is therefore essential to understand trypanosomatid disease pathogenesis. Chemical cartography generates 3D visualizations of small molecule abundance generated via liquid chromatography-mass spectrometry, in comparison to microbiological and immunological parameters. This protocol demonstrates how chemical cartography can be applied to study pathogenic processes during trypanosomatid infection, beginning from systematic tissue sampling and metabolite extraction, followed by liquid chromatography-tandem mass spectrometry data acquisition, and concluding with the generation of 3D maps of metabolite distribution. This method can be used for multiple research questions, such as nutrient requirements for tissue colonization by T. cruzi, T. brucei, or Leishmania, immunometabolism at sites of infection, and the relationship between local tissue metabolic perturbation and clinical disease symptoms, leading to comprehensive insight into trypanosomatid disease pathogenesis.

Advances in Microbiome-Derived Solutions and Methodologies Are Founding a New Era in Skin Health and Care

The microbiome, as a community of microorganisms and their structural elements, genomes, metabolites/signal molecules, has been shown to play an important role in human health, with significant beneficial applications for gut health. Skin microbiome has emerged as a new field with high potential to develop disruptive solutions to manage skin health and disease. Despite an incomplete toolbox for skin microbiome analyses, much progress has been made towards functional dissection of microbiomes and host-microbiome interactions. A standardized and robust investigation of the skin microbiome is necessary to provide accurate microbial information and set the base for a successful translation of innovations in the dermo-cosmetic field. This review provides an overview of how the landscape of skin microbiome research has evolved from method development (multi-omics/data-based analytical approaches) to the discovery and development of novel microbiome-derived ingredients. Moreover, it provides a summary of the latest findings on interactions between the microbiomes (gut and skin) and skin health/disease. Solutions derived from these two paths are used to develop novel microbiome-based ingredients or solutions acting on skin homeostasis are proposed. The most promising skin and gut-derived microbiome interventional strategies are presented, along with regulatory, safety, industrial, and technical challenges related to a successful translation of these microbiome-based concepts/technologies in the dermo-cosmetic industry.

Visualizing the Hidden Half: Plant-Microbe Interactions in the Rhizosphere

Plant roots and the associated rhizosphere constitute a dynamic environment that fosters numerous intra- and interkingdom interactions, including metabolite exchange between plants and soil mediated by root exudates and the rhizosphere microbiome. These interactions affect plant fitness and performance, soil health, and the belowground carbon budget. Exploring and understanding the molecular mechanisms governing ecosystem responses via rhizosphere interactions allow the rational and sustainable design of future ecosystems. However, visualizing the plant root system architecture with spatially resolved root exudate and microbiome profiles along the root in its native state remains an ambitious grand challenge in rhizosphere biology. To address this challenge, we developed a three-dimensional (3D) root cartography platform to accurately visualize molecular and microbial constituents and their interactions in the root-rhizosphere zone.

Microbiome for Mars: surveying microbiome connections to healthcare with implications for long-duration human spaceflight, virtual workshop, July 13, 2020

The inaugural "Microbiome for Mars" virtual workshop took place on July 13, 2020. This event assembled leaders in microbiome research and development to discuss their work and how it may relate to long-duration human space travel. The conference focused on surveying current microbiome research, future endeavors, and how this growing field could broadly impact human health and space exploration. This report summarizes each speaker's presentation in the order presented at the workshop.

Catabolic Machinery of the Human Gut Microbes Bestow Resilience Against Vanillin Antimicrobial Nature

Vanillin is a phenolic food additive commonly used for flavor, antimicrobial, and antioxidant properties. Though it is one of the widely used food additives, strategies of the human gut microbes to evade its antimicrobial activity await extensive elucidation. The current study explores the human gut microbiome with a multi-omics approach to elucidate its composition and metabolic machinery to counter vanillin bioactivity. A combination of SSU rRNA gene diversity, metagenomic RNA features diversity, phylogenetic affiliation of metagenome encoded proteins, uniformly (R = 0.99) indicates the abundance of Bacteroidetes followed by Firmicutes and Proteobacteria. Manual curation of metagenomic dataset identified gene clusters specific for the vanillin metabolism (ligV, ligK, and vanK) and intermediary metabolic pathways (pca and cat operon). Metagenomic dataset comparison identified the omnipresence of vanillin catabolic features across diverse populations. The metabolomic analysis brings forth the functionality of the vanillin catabolic pathway through the Protocatechuate branch of the beta-ketoadipate pathway. These results highlight the human gut microbial features and metabolic bioprocess involved in vanillin catabolism to overcome its antimicrobial activity. The current study advances our understanding of the human gut microbiome adaption toward changing dietary habits.

Metabolites from Microbes Isolated from the Skin of the Panamanian Rocket Frog Colostethus panamansis (Anura: Dendrobatidae)

The Panamanian rocket frog Colostethus panamansis (family Dendrobatidae) has been affected by chytridiomycosis, a deadly disease caused by the fungus Batrachochytrium dendrobatidis (Bd). While there are still uninfected frogs, we set out to isolate microbes from anatomically distinct regions in an effort to create a cultivable resource within Panama for potential drug/agricultural/ecological applications that perhaps could also be used as part of a strategy to protect frogs from infections. To understand if there are specific anatomies that should be explored in future applications of this resource, we mapped skin-associated bacteria of C. panamansis and their metabolite production potential by mass spectrometry on a 3D model. Our results indicate that five bacterial families (Enterobacteriaceae, Comamonadaceae, Aeromonadaceae, Staphylococcaceae and Pseudomonadaceae) dominate the cultivable microbes from the skin of C. panamansis. The combination of microbial classification and molecular analysis in relation to the anti-Bd inhibitory databases reveals the resource has future potential for amphibian conservation.

Microbial and chemical dynamics of a toxic dinoflagellate bloom

Harmful Algal Blooms (HABs) exert considerable ecological and economic damage and are becoming increasingly frequent worldwide. However, the biological factors underlying HABs remain uncertain. Relationships between algae and bacteria may contribute to bloom formation, strength, and duration. We investigated the microbial communities and metabolomes associated with a HAB of the toxic dinoflagellate Karenia brevis off the west coast of Florida in June 2018. Microbial communities and intracellular metabolite pools differed based on both bacterial lifestyle and bloom level, suggesting a complex role for blooms in reshaping microbial processes. Network analysis identified K. brevis as an ecological hub in the planktonic ecosystem, with significant connections to diverse microbial taxa. These included four flavobacteria and one sequence variant unidentified past the domain level, suggesting uncharacterized diversity in phytoplankton-associated microbial communities. Additionally, intracellular metabolomic analyses associated high K. brevis levels with higher levels of aromatic compounds and lipids. These findings reveal water column microbial and chemical characteristics with potentially important implications for understanding HAB onset and duration.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

Updates in Rhea: SPARQLing biochemical reaction data

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of over 11 000 expert-curated biochemical reactions that uses chemical entities from the ChEBI ontology to represent reaction participants. Originally designed as an annotation vocabulary for the UniProt Knowledgebase (UniProtKB), Rhea also provides reaction data for a range of other core knowledgebases and data repositories including ChEBI and MetaboLights. Here we describe recent developments in Rhea, focusing on a new resource description framework representation of Rhea reaction data and an SPARQL endpoint (https://sparql.rhea-db.org/sparql) that provides access to it. We demonstrate how federated queries that combine the Rhea SPARQL endpoint and other SPARQL endpoints such as that of UniProt can provide improved metabolite annotation and support integrative analyses that link the metabolome through the proteome to the transcriptome and genome. These developments will significantly boost the utility of Rhea as a means to link chemistry and biology for a more holistic understanding of biological systems and their function in health and disease.

Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Background

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

Methods

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

Results

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.

Home chemical and microbial transitions across urbanization

Urbanization represents a profound shift in human behavior, with significant cultural and health-associated consequences^2,3. Here we investigate chemical and microbial characteristics of houses and their human occupants across an urbanization gradient in the Amazon rainforest, from a remote Peruvian Amerindian village to the Brazilian city of Manaus. Urbanization was associated with reduced microbial outdoor exposure, increased contact with housing materials, antimicrobials, and cleaning products, and increased exposure to chemical diversity. Urbanization degree correlated with changes in house bacterial and micro-eukaryotic community composition, increased house and skin fungal diversity, and increased relative abundance of human skin-associated fungi and bacteria in houses. Overall, our results indicate large-scale effects of urbanization on chemical and microbial exposures and on the human microbiota.

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.

Individualized metabolomics: opportunities and challenges

The goal of advancing science in health care is to provide high quality treatment and therapeutic opportunities to patients in need. This is especially true in precision medicine, wherein the ultimate goal is to link disease phenotypes to targeted treatments and novel therapeutics at the scale of an individual. With the advent of -omics technologies, such as genomics, proteomics, microbiome, among others, the metabolome is of wider and immediate interest for its important role in metabolic regulation. The metabolome, of course, comes with its own questions regarding technological challenges. In this opinion article, I attempt to interrogate some of the main challenges associated with individualized metabolomics, and available opportunities in the context of its clinical application. Some questions this article addresses and attempts to find answers for are: Can a personal metabolome (n = 1) be inexpensive, affordable and informative enough (i.e. provide predictive yet validated biomarkers) to represent the entirety of a population? How can a personal metabolome complement advances in other -omics areas and the use of monitoring devices, which occupy our personal space?

Comparative genomics of Bacteria commonly identified in the built environment

BACKGROUND

The microbial community of the built environment (BE) can impact the lives of people and has been studied for a variety of indoor, outdoor, underground, and extreme locations. Thus far, these microorganisms have mainly been investigated by culture-based methods or amplicon sequencing. However, both methods have limitations, complicating multi-study comparisons and limiting the knowledge gained regarding in-situ microbial lifestyles. A greater understanding of BE microorganisms can be achieved through basic information derived from the complete genome. Here, we investigate the level of diversity and genomic features (genome size, GC content, replication strand skew, and codon usage bias) from complete genomes of bacteria commonly identified in the BE, providing a first step towards understanding these bacterial lifestyles.

RESULTS

Here, we selected bacterial genera commonly identified in the BE (or "Common BE genomes") and compared them against other prokaryotic genera ("Other genomes"). The "Common BE genomes" were identified in various climates and in indoor, outdoor, underground, or extreme built environments. The diversity level of the 16S rRNA varied greatly between genera. The genome size, GC content and GC skew strength of the "Common BE genomes" were statistically larger than those of the "Other genomes" but were not practically significant. In contrast, the strength of selected codon usage bias (S value) was statistically higher with a large effect size in the "Common BE genomes" compared to the "Other genomes."

CONCLUSION

Of the four genomic features tested, the S value could play a more important role in understanding the lifestyles of bacteria living in the BE. This parameter could be indicative of bacterial growth rates, gene expression, and other factors, potentially affected by BE growth conditions (e.g., temperature, humidity, and nutrients). However, further experimental evidence, species-level BE studies, and classification by BE location is needed to define the relationship between genomic features and the lifestyles of BE bacteria more robustly.

Trace Evidence Potential in Postmortem Skin Microbiomes: From Death Scene to Morgue

Microbes can be used effectively as trace evidence, at least in research settings. However, it is unknown whether skin microbiomes change prior to autopsy and, if so, whether these changes interfere with linking objects to decedents. The current study included microbiomes from 16 scenes of death in the City and County of Honolulu and tested whether objects at the scenes can be linked to individual decedents. Postmortem skin microbiomes were stable during repeated sampling up to 60 h postmortem and were similar to microbiomes of an antemortem population. Objects could be traced to decedents approximately 75% of the time, with smoking pipes and medical devices being especially accurate (100% match), house and car keys being poor (0%), and other objects like phones intermediate (~80%). These results show that microbes from objects at death scenes can be matched to individual decedents, opening up a new method of establishing associations and identifications.

Honor Thy Lodgers? – Structure and Function of the Human Built Environment Microbiome

The microbiome of the built environment (BE) and its interactions with the human occupants represent a new and highly interdisciplinary research field. The BE is characterized by a great microbial diversity as well as very fluctuating environmental conditions and sharp gradients of physicochemical parameters, which significantly shape the resident microbiomes. A great significance of the BE microbiome for human health is obvious, but far from being fully understood. However, there is a growing body of evidence that antimicrobial and probiotic strategies will have to be balanced in a well-considered manner to successfully manage the BE microbiome in a way that finally is most beneficial for human health.

Are microbiome studies ready for hypothesis-driven research?

Hypothesis-driven research has led to many scientific advances, but hypotheses cannot be tested in isolation: rather, they require a framework of aggregated scientific knowledge to allow questions to be posed meaningfully. This framework is largely still lacking in microbiome studies, and the only way to create it is by discovery-driven, tool-driven, and standards-driven research projects. Here we illustrate these issues using several such non-hypothesis-driven projects from our own laboratories, including spatial mapping, the American Gut Project, the Earth Microbiome Project (which is an umbrella project integrating many smaller hypothesis-driven projects), and the knowledgebase-driven tools GNPS and Qiita. We argue that an investment of community resources in infrastructure tasks, and in the controls and standards that underpin them, will greatly enhance the investment in hypothesis-driven research programs.