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.

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.

Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery

Non-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded by biosynthetic gene clusters (BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.

ReDU: a framework to find and reanalyze public mass spectrometry data

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

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.

MetaMiner: A Scalable Peptidogenomics Approach for Discovery of Ribosomal Peptide Natural Products with Blind Modifications from Microbial Communities

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that contain antibiotics and a variety of other bioactive compounds. The existing methods for discovery of RiPPs by combining genome mining and computational mass spectrometry are limited to discovering specific classes of RiPPs from small datasets, and these methods fail to handle unknown post-translational modifications. Here, we present MetaMiner, a software tool for addressing these challenges that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just eight genomic and metagenomic datasets, MetaMiner discovered 31 known and seven unknown RiPPs from diverse microbial communities, including human microbiome and lichen microbiome, and microorganisms isolated from the International Space Station.

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in raw and processed foods and beverages

In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.

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.

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

One of the goals of forensic science is to identify individuals and their lifestyle by analyzing the trace signatures left behind in built environments. Here, microbiome and metabolomic methods were used to see how its occupants used an office and to also gain insights into the lifestyle characteristics such as diet, medications, and personal care products of the occupants. 3D molecular cartography, a molecular visualization technology, was used in combination with mass spectrometry and microbial inventories to highlight human-environmental interactions. Molecular signatures were correlated with the individuals as well as their interactions with this indoor environment. There are person-specific chemical and microbial signatures associated with this environment that directly relate who had touched objects such as computers, computer mice, cell phones, desk phone, table or desks. By combining molecular and microbial investigation forensic strategies, this study offers novel insights to investigators who value the reconstructing of human lifestyle and characterization of human environmental interaction.

Antimicrobials from human skin commensal bacteria protect against Staphylococcus aureus and are deficient in atopic dermatitis

The microbiome can promote or disrupt human health by influencing both adaptive and innate immune functions. We tested whether bacteria that normally reside on human skin participate in host defense by killing Staphylococcus aureus, a pathogen commonly found in patients with atopic dermatitis (AD) and an important factor that exacerbates this disease. High-throughput screening for antimicrobial activity against S. aureus was performed on isolates of coagulase-negative Staphylococcus (CoNS) collected from the skin of healthy and AD subjects. CoNS strains with antimicrobial activity were common on the normal population but rare on AD subjects. A low frequency of strains with antimicrobial activity correlated with colonization by S. aureus The antimicrobial activity was identified as previously unknown antimicrobial peptides (AMPs) produced by CoNS species including Staphylococcus epidermidis and Staphylococcus hominis These AMPs were strain-specific, highly potent, selectively killed S. aureus, and synergized with the human AMP LL-37. Application of these CoNS strains to mice confirmed their defense function in vivo relative to application of nonactive strains. Strikingly, reintroduction of antimicrobial CoNS strains to human subjects with AD decreased colonization by S. aureus These findings show how commensal skin bacteria protect against pathogens and demonstrate how dysbiosis of the skin microbiome can lead to disease.

Three-Dimensional Microbiome and Metabolome Cartography of a Diseased Human Lung

Our understanding of the spatial variation in the chemical and microbial makeup of an entire human organ remains limited, in part due to the size and heterogeneity of human organs and the complexity of the associated metabolome and microbiome. To address this challenge, we developed a workflow to enable the cartography of metabolomic and microbiome data onto a three-dimensional (3D) organ reconstruction built off radiological images. This enabled the direct visualization of the microbial and chemical makeup of a human lung from a cystic fibrosis patient. We detected host-derived molecules, microbial metabolites, medications, and region-specific metabolism of medications and placed it in the context of microbial distributions in the lung. Our tool further created browsable maps of a 3D microbiome/metabolome reconstruction map on a radiological image of a human lung and forms an interactive resource for the scientific community.

Coupling Targeted and Untargeted Mass Spectrometry for Metabolome-Microbiome-Wide Association Studies of Human Fecal Samples

Increasing appreciation of the gut microbiome's role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Microbiome Tools for Forensic Science

Microbes are present at every crime scene and have been used as physical evidence for over a century. Advances in DNA sequencing and computational approaches have led to recent breakthroughs in the use of microbiome approaches for forensic science, particularly in the areas of estimating postmortem intervals (PMIs), locating clandestine graves, and obtaining soil and skin trace evidence. Low-cost, high-throughput technologies allow us to accumulate molecular data quickly and to apply sophisticated machine-learning algorithms, building generalizable predictive models that will be useful in the criminal justice system. In particular, integrating microbiome and metabolomic data has excellent potential to advance microbial forensics.

Mass Spectrometry-Based Visualization of Molecules Associated with Human Habitats

The cars we drive, the homes we live in, the restaurants we visit, and the laboratories and offices we work in are all a part of the modern human habitat. Remarkably, little is known about the diversity of chemicals present in these environments and to what degree molecules from our bodies influence the built environment that surrounds us and vice versa. We therefore set out to visualize the chemical diversity of five built human habitats together with their occupants, to provide a snapshot of the various molecules to which humans are exposed on a daily basis. The molecular inventory was obtained through untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of samples from each human habitat and from the people that occupy those habitats. Mapping MS-derived data onto 3D models of the environments showed that frequently touched surfaces, such as handles (e.g., door, bicycle), resemble the molecular fingerprint of the human skin more closely than other surfaces that are less frequently in direct contact with humans (e.g., wall, bicycle frame). Approximately 50% of the MS/MS spectra detected were shared between people and the environment. Personal care products, plasticizers, cleaning supplies, food, food additives, and even medications that were found to be a part of the human habitat. The annotations indicate that significant transfer of chemicals takes place between us and our built environment. The workflows applied here will lay the foundation for future studies of molecular distributions in medical, forensic, architectural, space exploration, and environmental applications.

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Mass spectrometry of natural products: current, emerging and future technologies

Although mass spectrometry is a century old technology, we are entering into an exciting time for the analysis of molecular information directly from complex biological systems. In this Highlight, we feature emerging mass spectrometric methods and tools used by the natural product community and give a perspective of future directions where the mass spectrometry field is migrating towards over the next decade.

Complementarity of MALDI and LA ICP mass spectrometry for platinum anticancer imaging in human tumor

The follow-up of the Heated Intraoperative Chemotherapy (HIPEC) of peritoneal carcinomatosis would benefit from the monitoring of the penetration, distribution and metabolism of the drug within the tumor.

Matrix-assisted laser desorption/ionization imaging mass spectrometry of oxaliplatin derivatives in heated intraoperative chemotherapy (HIPEC)-like treated rat kidney

Oxaliplatin [1,2-diaminocyclohexane (dach)-Pt complex] is a platinum anticancer drug which is mainly used in the treatment of advanced colorectal cancer, particularly in Heated Intraoperative Chemotherapy (HIPEC) for the treatment of colorectal peritoneal carcinomatosis. In order to better understand the penetration of oxaliplatin in treated tissues we performed a direct imaging of tissue sections from HIPEC-like treated rat kidney using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. This procedure allowed the detection and localization of oxaliplatin and its metabolites, the monocysteine and monomethionine complexes, in kidney sections. Specifically, oxaliplatin and its metabolites were localized exclusively in the kidney cortex, suggesting that it did not penetrate deeply into the organ. Based on these results, an imaging analysis of human tumors collected after HIPEC is currently in progress to assess the distribution of oxaliplatin and/or metabolites with the aim of defining clinical conditions to improve drug penetration.