Lifestyle chemistries from phones for individual profiling

Exploring gunshot residue detection in fingerprints by functionalized particle-coupled matrix-assisted laser desorption/ionization mass spectrometry

In firearm forensic investigations, detecting gunshot residue (GSR) is crucial for linking firearms to suspects and determining firing distance for forensic reconstruction. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF-MS) is emerging as a versatile and promising technological platform for fingerprint analysis. The capability of functionalized particles as an advanced dusting powder for visualizing latent fingerprints is widely recognized. This study aims to investigate the feasibility of employing functionalized magnetic fingerprint dusting powders for distinguishing regular and GSR fingerprints using MALDI-ToF-MS, thereby enhancing forensic evidentiary support. In this study, silica and carbon coated magnetic iron oxide particles were surface functionalized with phenyltriethoxy orthosilicate (PTEOS) or 3-aminopropyl triethoxysilane (APTES) to create hydrophobic and hydrophilic particles, respectively. Donor shooters' fingerprints, both GSR-containing and regular, were analyzed using these functionalized particles coupled with MALDI-ToF-MS. The results demonstrated effective fingerprint visualization and conclusive discrimination between GSR-containing and regular fingerprints through orthogonal partial least squares discriminant analysis. This technique provides enhanced sensitivity, speed, and adaptability compared to conventional methods, making it a promising choice for initial detection of GSR in latent fingerprints. Moreover, when subjected to thorough analysis using advanced instruments, it has the potential to significantly strengthen the probative value of fingerprint evidence in forensic investigations.

Noninvasive skin swab analysis detects environmental drug exposure of pharmacy staff

The skin is complex with multiple layers serving protective, regulatory, and detective functions. The skin hosts chemicals originating from consumption, synthesis, and the environment. Skin chemicals can provide insight into one's daily routine or their level of safety in a work environment. The goal of this study was to investigate the utility of noninvasive skin swabs to detect drugs in a pharmacy setting and to determine whether drugs are transferred to the skin of pharmacy staff. To answer this question, skin swabs were collected from healthy pharmacy staff workers and healthy non-pharmacy individuals and analyzed via untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS). Drugs were annotated through library matching against the GNPS community spectral library. We then used questionnaire data to exclude medications that participants took orally or applied topically and focused on the drugs participants were exposed to in the work setting. Overall, pharmacy staff had a higher number and variety of medications on their skin as compared with healthy individuals who did not work in a pharmacy. In addition, we identified some chemicals such as N,N-Diethyl-metatoluamide on a large number of subjects in both experimental and control groups, indicating environmental exposure to this compound may be ubiquitous and long-lasting.

Smartphone swabs as an emerging tool for toxicology testing: a proof-of-concept study in a nightclub

OBJECTIVES

Smartphones have become everyday objects on which the accumulation of fingerprints is significant. In addition, a large proportion of the population regularly uses a smartphone, especially younger people. The objective of this study was to evaluate smartphones as a new matrix for toxico-epidemiology.

METHODS

This study was conducted during two separate events (techno and trance) at an electronic music nightclub in Grenoble, France. Data on reported drug use and whether drugs were snorted directly from the surface of the smartphone were collected using an anonymous questionnaire completed voluntarily by drug users. Then, a dry swab was rubbed for 20 s on all sides of the smartphone. The extract was analyzed by liquid chromatography coupled to tandem mass spectrometry on a Xevo TQ-XS system (Waters).

RESULTS

In total, 122 swabs from 122 drug users were collected. The three main drugs identified were MDMA (n=83), cocaine (n=59), and THC (n=51). Based on declarative data, sensitivity ranged from 73 to 97.2 % and specificity from 71.8 to 88.1 % for MDMA, cocaine, and THC. Other substances were identified such as cocaine adulterants, ketamine, amphetamine, LSD, methamphetamine, CBD, DMT, heroin, mescaline, and several NPS. Numerous medications were also identified, such as antidepressants, anxiolytics, hypnotics, and painkillers. Different use patterns were identified between the two events.

CONCLUSIONS

This proof-of-concept study on 122 subjects shows that smartphone swab analysis could provide a useful and complementary tool for drug testing, especially for harm-reduction programs and toxico-epidemiolgy studies, with acceptable test performance, despite declarative data.

Skin Surface Sebum Analysis by ESI-MS

The skin surface is an important sample source that the metabolomics community has only just begun to explore. Alterations in sebum, the lipid-rich mixture coating the skin surface, correlate with age, sex, ethnicity, diet, exercise, and disease state, making the skin surface an ideal sample source for future noninvasive biomarker exploration, disease diagnosis, and forensic investigation. The potential of sebum sampling has been realized primarily via electrospray ionization mass spectrometry (ESI-MS), an ideal approach to assess the skin surface lipidome. However, a better understanding of sebum collection and subsequent ESI-MS analysis is required before skin surface sampling can be implemented in routine analyses. Challenges include ambiguity in definitive lipid identification, inherent biological variability in sebum production, and methodological, technical variability in analyses. To overcome these obstacles, avoid common pitfalls, and achieve reproducible, robust outcomes, every portion of the workflow-from sample collection to data analysis-should be carefully considered with the specific application in mind. This review details current practices in sebum sampling, sample preparation, ESI-MS data acquisition, and data analysis, and it provides important considerations in acquiring meaningful lipidomic datasets from the skin surface. Forensic researchers investigating sebum as a means for suspect elimination in lieu of adequate fingerprint ridge detail or database matches, as well as clinical researchers interested in noninvasive biomarker exploration, disease diagnosis, and treatment monitoring, can use this review as a guide for developing methods of best-practice.

Medium-chain dicarboxylic acids: chemistry, pharmacological properties, and applications in modern pharmaceutical and cosmetics industries

Succinic (SUA), glutaric (GLA), pimelic (PA), suberic (SUBA), adipic (ADA), azelaic (AZA), and sebacic acids (SA) make up the majority of medium-chain dicarboxylic acids (MCDAs) with chain lengths of C4-C10, and are widely utilised in the chemical, food, textile, pesticide, pharmaceutical, and liquid crystal sectors. The MCDAs' two carboxyl groups provide them with an incredibly broad variety of applications. The focus of significant scientific research now is on the increasingly varied pharmacological effects of MCDAs. However, only a few studies have compared the biological characteristics of MCDAs in the contemporary pharmaceutical and cosmetic sectors and thoroughly examined the most recent research and marketing initiatives for MCDAs. This review's objective is to offer a thorough analysis of academic works on MCDAs, to assess the usefulness of these substances' chemical-pharmacological properties for use in the contemporary pharmaceutical and cosmetic industries, and to investigate the direction of their possible applications in these two disciplines. In addition, this review investigates how these compounds are metabolised in the human body.

Untargeted metabolomics for lifestyle biomarker discovery in human hair

There is a risk of crimes remaining unsolved when no matching DNA profiles or fingermarks are found. If this is the case, forensic investigations are faced with a significant shortage of evidence and information regarding the unknown perpetrator and/or victim as well as any missing persons. However, a rather commonly found biological trace encountered at crime scenes is human hair. As hair acts as a biochemical reservoir, it may contain valuable information regarding one's characteristics and habits. This study aimed to build an analytical method capable of determining a marker set of relevant metabolites in hair, eventually building up a profile of its donor. To find potential markers, an untargeted metabolomics approach was developed to select and identify statistically significant features. For that purpose, a total of 68 hair samples were collected at several hairdresser shops in varying neighbourhoods. Compound extraction was achieved via methanolic incubation overnight and analysis performed using a high-resolution mass spectrometry (HRMS) Orbitrap Q Exactive Focus. The acquired data was uploaded and statistically evaluated using two free online software/libraries, where a total of eight compounds have given a match on both tools. Their presumptive identity was confirmed using reference standards and consequently added to a dynamic target donor profiling list. These results show the potential of using untargeted metabolomics for the search for lifestyle biomarkers capable of differentiating individuals. Such tools are of paramount importance in a forensic setting with little or no evidence available and no clear tactical leads.

Alterations in microbiome of COVID-19 patients and its impact on forensic investigations

The human microbiome is vital for maintaining human health and has garnered substantial attention in recent years, particularly in the context of the coronavirus disease 2019 (COVID-19) outbreak. Studies have underscored significant alterations in the microbiome of COVID-19 patients across various body niches, including the gut, respiratory tract, oral cavity, skin, and vagina. These changes manifest as shifts in microbiota composition, characterized by an increase in opportunistic pathogens and a decrease in beneficial commensal bacteria. Such microbiome transformations may play a pivotal role in influencing the course and severity of COVID-19, potentially contributing to the inflammatory response. This ongoing relationship between COVID-19 and the human microbiome serves as a compelling subject of research, underscoring the necessity for further investigations into the underlying mechanisms and their implications for patient health. Additionally, these alterations in the microbiome may have significant ramifications for forensic investigations, given the microbiome's potential in establishing individual characteristics. Consequently, changes in the microbiome could introduce a level of complexity into forensic determinations. As research progresses, a more profound understanding of the human microbiome within the context of COVID-19 may offer valuable insights into disease prevention, treatment strategies, and its potential applications in forensic science. Consequently, this paper aims to provide an overarching review of microbiome alterations due to COVID-19 and the associated impact on forensic applications, bridging the gap between the altered microbiome of COVID-19 patients and the challenges forensic investigations may encounter when analyzing this microbiome as a forensic biomarker.

Raman imaging to capture microplastics and nanoplastics carried by smartphones

The sources of microplastics and nanoplastics can be found almost everywhere, including being released from the activities of our daily lives. Unfortunately, the process for determining the sources of microplastics and nanoplastics is hampered by the limited techniques available for characterisation. Herewith, we advance Raman imaging by combining it with logic-based, algebra-based, PCA-based algorithms and their hybrid, which can significantly increase the signal-noise ratio and the imaging certainty, to enable the characterisation of microplastics. Consequently, we can capture and identify the microplastics carried by our smartphones. That is because, due to the friction and fragmentation etc., our clothes and the decoration trinkets that might be made of plastic fibres can release microplastics. The released microplastics stick on the phone surface, or are trapped in the charging port, speaker ports etc., towards accumulation. We estimate hundreds or thousands of microplastics can be captured and carried by a smartphone, depending on the clothing materials, pocketing styles, user habits etc. Due to the complexity of the samples (which shields the weak signals emitted from nanoplastics), further methodological improvements are required, such as optimisation of sample preparation (for better isolation of nano-sized plastics), refinement of data processing algorithms and combined use of Raman microscopy and scanning electron microscopy (SEM).

Differentiating individuals through the chemical composition of their fingermarks

Fingermark patterns are one of the oldest means of biometric identification. During this last decade, the molecules that constitute the fingermark residue have gained interest among the forensic research community to gain additional intelligence regarding its donor profile including its gender, age, lifestyle or even its pathological state. In this work, the molecular composition of fingermarks have been studied to monitor the variability between donors and to explore its capacity to differentiate individuals using supervised multi-class classification models. Over one year, fingermarks from thirteen donors have been analysed by Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry Imaging (n = 716) and mined by different machine learning approaches. We demonstrate the potential of the fingermark chemical composition to help differentiating individuals with an accuracy between 80% and 96% depending on the period of sample collection for each donor and size of the pool of donors. It would be premature at this stage to transpose the results of this research to real cases, however the conclusions of this study can provide a better understanding of the variations of the chemical composition of the fingermark residue in between individuals over long periods and help clarifying the notion of donorship.

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.

Non-invasive skin sampling detects systemically administered drugs in humans

Clinical testing typically relies on invasive blood draws and biopsies. Alternative methods of sample collection are continually being developed to improve patient experience; swabbing the skin is one of the least invasive sampling methods possible. To show that skin swabs in combination with untargeted mass spectrometry (metabolomics) can be used for non-invasive monitoring of an oral drug, we report the kinetics and metabolism of diphenhydramine in healthy volunteers (n = 10) over the course of 24 hours in blood and three regions of the skin. Diphenhydramine and its metabolites were observed on the skin after peak plasma levels, varying by compound and skin location, and is an illustrative example of how systemically administered molecules can be detected on the skin surface. The observation of diphenhydramine directly from the skin supports the hypothesis that both parent drug and metabolites can be qualitatively measured from a simple non-invasive swab of the skin surface. The mechanism of the drug and metabolites pathway to the skin’s surface remains unknown.

The study of distribution of ingested terbinafine on skin with ambient ionization tandem mass spectrometry

We aim to develop an efficient and non-invasive strategy for monitoring of drugs and their metabolites via human skin. Probe sampling was combined with thermal desorption-electrospray ionization tandem mass spectrometry (TD-ESI/MS/MS) to characterize trace terbinafine, which was secreted on patient's skin after ingesting terbinafine tablets. The terbinafine ion signals were directly detected in the samples collected from different skin regions and the signals were monitored for 8 weeks. The detection and location of terbinafine via the skin suggest that the methods are useful in rapidly and noninvasively collecting the molecular information of the ingested drug on skin for pharmacokinetic studies.

Unlocking the potential of forensic traces: Analytical approaches to generate investigative leads

Forensic investigation involves gathering the information necessary to understand the criminal events as well as linking objects or individuals to an item, location or other individual(s) for investigative purposes. For years techniques such as presumptive chemical tests, DNA profiling or fingermark analysis have been of great value to this process. However, these techniques have their limitations, whether it is a lack of confidence in the results obtained due to cross-reactivity, subjectivity and low sensitivity; or because they are dependent on holding reference samples in a pre-existing database. There is currently a need to devise new ways to gather as much information as possible from a single trace, particularly from biological traces commonly encountered in forensic casework. This review outlines the most recent advancements in the forensic analysis of biological fluids, fingermarks and hair. Special emphasis is placed on analytical methods that can expand the information obtained from the trace beyond what is achieved in the usual practices. Special attention is paid to those methods that accurately determine the nature of the sample, as well as how long it has been at the crime scene, along with individualising information regarding the donor source of the trace.

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.

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.

Analysis of Microbial Communities: An Emerging Tool in Forensic Sciences

The objective of forensic sciences is to find clues in a crime scene in order to reconstruct the scenario. Classical samples include DNA or fingerprints, but both have inherent limitations and can be uninformative. Another type of sample has emerged recently in the form of the microbiome. Supported by the Human Microbiome Project, the characteristics of the microbial communities provide real potential in forensics. They are highly specific and can be used to differentiate and classify the originating body site of a human biological trace. Skin microbiota is also highly specific and different between individuals, leading to its possibility as an identification tool. By extension, the possibilities of the microbial communities to be deposited on everyday objects has also been explored. Other uses include the determination of the post-mortem interval or the analysis of soil communities. One challenge is that the microbiome changes over time and can be influenced by many environmental and lifestyle factors. This review offers an overview of the main methods and applications to demonstrate the benefit of the microbiome to provide forensically relevant information.

Physicochemical properties determining drug detection in skin

Chemicals, including some systemically administered xenobiotics and their biotransformations, can be detected noninvasively using skin swabs and untargeted metabolomics analysis. We sought to understand the principal drivers that determine whether a drug taken orally or systemically is likely to be observed on the epidermis by using a random forest classifier to predict which drugs would be detected on the skin. A variety of molecular descriptors describing calculated properties of drugs, such as measures of volume, electronegativity, bond energy, and electrotopology, were used to train the classifier. The mean area under the receiver operating characteristic curve was 0.71 for predicting drug detection on the epidermis, and the SHapley Additive exPlanations (SHAP) model interpretation technique was used to determine the most relevant molecular descriptors. Based on the analysis of 2561 US Food and Drug Administration (FDA)‐approved drugs, we predict that therapeutic drug classes, such as nervous system drugs, are more likely to be detected on the skin. Detecting drugs and other chemicals noninvasively on the skin using untargeted metabolomics could be a useful clinical advancement in therapeutic drug monitoring, adherence, and health status.

Feature-based molecular networking for identification of organic micropollutants including metabolites by non-target analysis applied to riverbank filtration

Due to growing concern about organic micropollutants and their transformation products (TP) in surface and drinking water, reliable identification of unknowns is required. Here, we demonstrate how non-target liquid chromatography (LC)-high-resolution tandem mass spectrometry (MS/MS) and the feature-based molecular networking (FBMN) workflow provide insight into water samples from four riverbank filtration sites with different redox conditions. First, FBMN prioritized and connected drinking water relevant and seasonally dependent compounds based on a modification-aware MS/MS cosine similarity. Within the resulting molecular networks, forty-three compounds were annotated. Here, carbamazepine, sartans, and their respective TP were investigated exemplarily. With chromatographic information and spectral similarity, four additional TP (dealkylated valsartan, dealkylated irbesartan, two oxygenated irbesartan isomers) and olmesartan were identified and partly verified with an authentic standard. In this study, sartans and TP were investigated and grouped regarding their removal behavior under different redox conditions and seasons for the first time. Antihypertensives were grouped into compounds being well removed during riverbank filtration, those primarily removed under anoxic conditions, and rather persistent compounds. Observed seasonal variations were mainly limited to varying river water concentrations. FBMN is a powerful tool for identifying previously unknown or unexpected compounds and their TP in water samples by non-target analysis.

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.

Visualizing shed skin cells in fingerprint residue using dark-field microscopy

This proof-of-concept study shows that dark-field microscopy provides sufficient contrast for cell visualization in fingerprints with high sebum content. Although the application is limited to smooth surfaces that do not scatter light, such as polyethylene terephthalate (PET), it was able to measure the number of cells deposited within a fingerprint residue and the reduction in cell transfer with repeated skin contact. On a PET surface, at roughly 5 N of contact force, a typical finger transfers several hundred cells onto the surface. Over subsequent finger contacts onto a clean PET surface, this number decreased exponentially until a steady state was reached, which is characterized by the transfer of (78 ± 36) cells or (0.46 ± 0.21) cells/mm² when normalized for fingerprint area. High uncertainty in cell transfer was due to: the highly variable nature of a human finger (where the number of loose cells varies from person to person and from day to day depending on what they touch) and difficulties in controlling the contact force and finger movement such as twisting during deposition (where twisting of the finger can expose a new patch of skin to the substrate, increasing the number of cell transfer). Plasma etching was also explored as an effective way to validate dark-field microscopy for cell counting. Although limited to inorganic substrates due to etching effects, exposing the fingerprint for less than 10 min can remove a majority of the sebum while keeping the cells intact for a before-and-after comparison using light microscopy.

Disentangling of the ecotoxicological signal using "omics" analyses, a lesson from the survey of the impact of cyanobacterial proliferations on fishes

Omics technologies offer unprecedented perspectives for the rational investigation of complex biological systems. Indeed, omics present the ability of offering an extensive perception of the biochemistry and physiology of the cell and of any perturbing consequences of contaminants through the joint investigation of thousands of molecular responses simultaneously; then it has recently conducted to a fervent attention by research ecotoxicologists. Beyond the presentation of latest advances, exemplified here by omics investigation of cyanobacterial deleterious effects on various fishes (at various experimental and biological scales and with various analytical tools and pipeline), the present review paper re-explores the promising perspectives and also the pitfalls of such holistic investigations of the ecotoxicological response of organisms for environmental assessment.

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.

Interpol review of fingermarks and other body impressions 2016-2019

This review paper covers the forensic-relevant literature in fingerprint and bodily impression sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20 Review%20 Papers%202019. pdf.

Local Phenomena Shape Backyard Soil Metabolite Composition

Soil covers most of Earth's continental surface and is fundamental to life-sustaining processes such as agriculture. Given its rich biodiversity, soil is also a major source for natural product drug discovery from soil microorganisms. However, the study of the soil small molecule profile has been challenging due to the complexity and heterogeneity of this matrix. In this study, we implemented high-resolution liquid chromatography-tandem mass spectrometry and large-scale data analysis tools such as molecular networking to characterize the relative contributions of city, state and regional processes on backyard soil metabolite composition, in 188 soil samples collected from 14 USA States, representing five USA climate regions. We observed that region, state and city of collection all influence the overall soil metabolite profile. However, many metabolites were only detected in unique sites, indicating that uniquely local phenomena also influence the backyard soil environment, with both human-derived and naturally-produced (plant-derived, microbially-derived) metabolites identified. Overall, these findings are helping to define the processes that shape the backyard soil metabolite composition, while also highlighting the need for expanded metabolomic studies of this complex environment.

Cutibacterium acnes (Propionibacterium acnes) 16S rRNA Genotyping of Microbial Samples from Possessions Contributes to Owner Identification

Cutibacterium acnes is the most common and abundant bacterial species on human skin, and the gene that encodes its 16S rRNA has multiple single-nucleotide polymorphisms. In this study, we developed a method to efficiently determine the C. acnes 16S rRNA genotype composition from microbial samples taken from the hands of participants and from their possessions. Using the C. acnes 16S rRNA genotype composition, we could predict the owner of a possession with around 90% accuracy when the 16S rRNA gene-based microbiome profile was included. We also showed that the C. acnes 16S rRNA genotype composition was more stable over time than the skin microbiome profile and thus is more suitable for owner identification.

The human skin surface harbors huge numbers of microbes. The skin microbiota interacts with its host and forms a skin microbiome profile that is specific for each individual. It has been reported that the skin microbiota that is left on an individual’s possessions can act as a sort of “fingerprint” and be used for owner identification. However, this approach needs to be improved to take into account any long-term instability of skin microbiota and contamination from nonspecific bacteria. Here, we took advantage of single-nucleotide polymorphisms (SNPs) in the 16S-encoding rRNA gene of Cutibacterium acnes, the most common and abundant bacterium on human skin, to perform owner identification. We first developed a high-throughput genotyping method based on next-generation sequencing to characterize the SNPs of the C. acnes 16S rRNA gene and found that the genotype composition of C. acnes 16S rRNA is individual specific. Owner identification accuracy of around 90% based on random forest machine learning was achieved by using a combination of C. acnes 16S rRNA genotype and skin microbiome profile data. Furthermore, our study showed that the C. acnes 16S rRNA genotype remained more stable over time than the skin microbiome profile. This characteristic of C. acnes was further confirmed by the analysis of publicly available human skin metagenome data. Our approach, with its high precision, good reproducibility, and low costs, thus provides new possibilities in the field of microbiome-based owner identification and forensics in general.

IMPORTANCECutibacterium acnes is the most common and abundant bacterial species on human skin, and the gene that encodes its 16S rRNA has multiple single-nucleotide polymorphisms. In this study, we developed a method to efficiently determine the C. acnes 16S rRNA genotype composition from microbial samples taken from the hands of participants and from their possessions. Using the C. acnes 16S rRNA genotype composition, we could predict the owner of a possession with around 90% accuracy when the 16S rRNA gene-based microbiome profile was included. We also showed that the C. acnes 16S rRNA genotype composition was more stable over time than the skin microbiome profile and thus is more suitable for owner identification.

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.

Ethical priority of the most actionable system of biomolecules: the metabolome

The metabolome is a system of small biomolecules (metabolites) and a direct result of human bioculture. Consequently, metabolomics is well poised to impact anthropological and biomedical research for the foreseeable future. Overall, we provide a perspective on the ethical, legal, and social implications (ELSI) of metabolomics, which we argue are often more alarming than those of genomics. Given the current mechanisms to fund research, ELSI beyond human DNA is stifled and in need of considerable attention.

Mass Spectral Similarity Networking and Gas-Phase Fragmentation Reactions in the Structural Analysis of Flavonoid Glycoconjugates

Flavonoids represent an important class of natural products with a central role in plant physiology and human health. Their accurate annotation using untargeted mass spectrometry analysis still relies on differentiating similar chemical scaffolds through spectral matching to reference library spectra. In this work, we combined molecular network analysis with rules for fragment reactions and chemotaxonomy to enhance the annotation of similar flavonoid glyconjugates. Molecular network topology progressively propagated the flavonoid chemical functionalization according to collision-induced dissociation (CID) reactions, as the following chemical attributes: aglycone nature, saccharide type and number, and presence of methoxy substituents. This structure-based distribution across the spectral networks revealed the chemical composition of flavonoids across intra- and interspecies and guided the putatively assignment of 64 isomers and isobars in the Chrysobalanaceae plant species, most of which are not accurately annotated by automated untargeted MS² matching. These proof of concept results demonstrate how molecular networking progressively grouped structurally related molecules according to their product ion scans, abundances, and ratios. The approach can be extrapolated to other classes of metabolites sharing similar structures and diagnostic fragments from tandem mass spectrometry.

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.

Are cell phones an indicator of personal exposure to organophosphate flame retardants and plasticizers?

BACKGROUND

Exposure to organophosphate ester (OPE) flame retardants and plasticizers is widespread and is of concern due to their toxicity.

OBJECTIVES

To investigate relationships between and within OPE concentrations in air, dust, hands, electronic product wipes and urinary metabolites with the goal of identifying product sources and exposure pathways.

METHODS

Women in Toronto and Ottawa, Canada, provided a urine sample, two sets of hand wipes, access to their homes for air and dust sampling, and completed a questionnaire. OPE concentrations were obtained for air and floor dust in the bedroom (n = 51) and most used room (n = 26), hand wipes (n = 204), and surface wipes of handheld (n = 74) and non-handheld electronic devices (n = 125). All air, dust and wipe samples were analyzed for 23 OPE compounds; urine samples (n = 44) were analyzed for 8 OPE metabolites.

RESULTS

Five-8 OPEs were detected in >80% of samples depending on the sample type. OPE median concentrations in hand wipes taken 3 weeks apart were not significantly different. Palms had higher concentrations than the back of hands; both were significantly correlated. Concentrations of 9 OPEs were significantly higher in surface wipes of handheld than non-handheld electronic devices. Six OPEs in hand wipes were significantly correlated with cell phone wipes, with two to four OPEs significantly correlated with tablet, laptop and television wipes. Multiple regression models using hand wipes, cell phone wipes and dust explained 8-33% of the variation in creatinine-adjusted urinary metabolites; air concentrations did not have explanatory power. OPEs in cell phone wipes explained the greatest variation in urinary metabolites.

CONCLUSIONS

Handheld electronic devices, notably cell phones, may either be sources or indicators of OPE exposure through hand-to-mouth and/or dermal uptake.

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.

Revealing Individual Lifestyles through Mass Spectrometry Imaging of Chemical Compounds in Fingerprints

Fingerprints, specifically the ridge details within the print, have long been used in forensic investigations for individual identification. Beyond the ridge detail, fingerprints contain useful chemical information. The study of fingerprint chemical information has become of interest, especially with mass spectrometry imaging technologies. Mass spectrometry imaging visualizes the spatial relationship of each compound detected, allowing ridge detail and chemical information in a single analysis. In this work, a range of exogenous fingerprint compounds that may reveal a personal lifestyle were studied using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Studied chemical compounds include various brands of bug sprays and sunscreens, as well as food oils, alcohols, and citrus fruits. Brand differentiation and source determination were possible based on the active ingredients or exclusive compounds left in fingerprints. Tandem mass spectrometry was performed for the key compounds, so that these compounds could be confidently identified in a single multiplex mass spectrometry imaging data acquisition.

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.

Detection of exogenous substances in latent fingermarks by silver-assisted LDI imaging MS: perspectives in forensic sciences

For over one hundred years, the fingerprint has reigned as one of the most trusted pieces of forensic evidence for suspect identification. Today, modern imaging mass spectrometry technology allows to correlate molecular information to the fingerprint giving us valuable insights into a suspect lifestyle and behaviour.

Review of emerging metabolomic tools and resources: 2015-2016

Data processing and analysis are major bottlenecks in high-throughput metabolomic experiments. Recent advancements in data acquisition platforms are driving trends toward increasing data size (e.g., petabyte scale) and complexity (multiple omic platforms). Improvements in data analysis software and in silico methods are similarly required to effectively utilize these advancements and link the acquired data with biological interpretations. Herein, we provide an overview of recently developed and freely available metabolomic tools, algorithms, databases, and data analysis frameworks. This overview of popular tools for MS and NMR-based metabolomics is organized into the following sections: data processing, annotation, analysis, and visualization. The following overview of newly developed tools helps to better inform researchers to support the emergence of metabolomics as an integral tool for the study of biochemistry, systems biology, environmental analysis, health, and personalized medicine.

Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics

In untargeted metabolomics approaches, the inability to structurally annotate relevant features and map them to biochemical pathways is hampering the full exploitation of many metabolomics experiments. Furthermore, variable metabolic content across samples result in sparse feature matrices that are statistically hard to handle. Here, we introduce MS2LDA+ that tackles both above-mentioned problems. Previously, we presented MS2LDA, which extracts biochemically relevant molecular substructures (“Mass2Motifs”) from a collection of fragmentation spectra as sets of co-occurring molecular fragments and neutral losses, thereby recognizing building blocks of metabolomics. Here, we extend MS2LDA to handle multiple metabolomics experiments in one analysis, resulting in MS2LDA+. By linking Mass2Motifs across samples, we expose the variability in prevalence of structurally related metabolite families. We validate the differential prevalence of substructures between two distinct samples groups and apply it to fecal samples. Subsequently, within one sample group of urines, we rank the Mass2Motifs based on their variance to assess whether xenobiotic-derived substructures are among the most-variant Mass2Motifs. Indeed, we could ascribe 22 out of the 30 most-variant Mass2Motifs to xenobiotic-derived substructures including paracetamol/acetaminophen mercapturate and dimethylpyrogallol. In total, we structurally characterized 101 Mass2Motifs with biochemically or chemically relevant substructures. Finally, we combined the discovered metabolite families with full scan feature intensity information to obtain insight into core metabolites present in most samples and rare metabolites present in small subsets now linked through their common substructures. We conclude that by biochemical grouping of metabolites across samples MS2LDA+ aids in structural annotation of metabolites and guides prioritization of analysis by using Mass2Motif prevalence.

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.