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Abstract The consumption of alcohol and caffeine affects the lives of billions of individuals worldwide. Although recent evidence indicates that caffeine impairs the reinforcing properties of alcohol, a characterization of its effects on alcohol-stimulated mesolimbic dopamine (DA) function was lacking. Acting as the pro-drug of salsolinol, alcohol excites DA neurons in the posterior ventral tegmental area (pVTA) and increases DA release in the nucleus accumbens shell (AcbSh). Here we show that caffeine, via antagonistic activity on A2A adenosine receptors (A2AR), prevents alcohol-dependent activation of mesolimbic DA function as assessed, in-vivo, by brain microdialysis of AcbSh DA and, in-vitro, by electrophysiological recordings of pVTA DA neuronal firing. Accordingly, while the A1R antagonist DPCPX fails to prevent the effects of alcohol on DA function, both caffeine and the A2AR antagonist SCH 58261 prevent alcohol-dependent pVTA generation of salsolinol and increase in AcbSh DA in-vivo, as well as alcohol-dependent excitation of pVTA DA neurons in-vitro. However, caffeine also prevents direct salsolinol- and morphine-stimulated DA function, suggesting that it can exert these inhibitory effects also independently from affecting alcohol-induced salsolinol formation or bioavailability. Finally, untargeted metabolomics of the pVTA showcases that caffeine antagonizes alcohol-mediated effects on molecules (e.g. phosphatidylcholines, fatty amides, carnitines) involved in lipid signaling and energy metabolism, which could represent an additional salsolinol-independent mechanism of caffeine in impairing alcohol-mediated stimulation of mesolimbic DA transmission. In conclusion, the outcomes of this study strengthen the potential of caffeine, as well as of A2AR antagonists, for future development of preventive/therapeutic strategies for alcohol use disorder.

Abstract Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-infected trees. We demonstrate how spatial information from molecular maps of branches and single leaves yields insight into the biology not accessible otherwise. In particular, we found evidence that flavonoid biosynthesis is disrupted in HLB-infected trees, and an increase in the polyamine, feruloylputrescine, is highly correlated with an increase in disease severity. Based on mechanistic details revealed by these molecular maps, followed by metabolic modeling, we formulated and tested the hypothesis that CLas infection either directly or indirectly converts the precursor compound, ferulic acid, to feruloylputrescine to suppress the antimicrobial effects of ferulic acid and biosynthetically downstream flavonoids. Using in vitro bioassays, we demonstrated that ferulic acid and bioflavonoids are indeed highly bactericidal to CLas, with the activity on par with a reference antibiotic, oxytetracycline, recently approved for HLB management. We propose these compounds should be evaluated as therapeutics alternatives to the antibiotics for HLB treatment. Overall, the utilized 3D metabolic mapping approach provides a promising methodological framework to identify pathogen-specific inhibitory compounds in planta for potential prophylactic or therapeutic applications.

Abstract 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.

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

ABSTRACT Gastrointestinal diseases are the most frequently reported clinical problems in captive common marmosets (Callithrix jacchus), often affecting the health and welfare of the animal and ultimately their use as a research subject. The microbiome has been shown to be intimately connected to diet and gastrointestinal health. Here, we use shotgun metagenomics and untargeted metabolomics in fecal samples of common marmosets collected before, during, and after a dietary transition from a biscuit to a gel diet. The overall health of marmosets, measured as weight recovery and reproductive outcome, improved after the diet transition. Moreover, each marmoset pair had significant shifts in the microbiome and metabolome after the diet transition. In general, we saw a decrease in Escherichia coli and Prevotella species and an increase in Bifidobacterium species. Untargeted metabolic profiles indicated that polyamine levels, specifically cadaverine and putrescine, were high after diet transition, suggesting either an increase in excretion or a decrease in intestinal reabsorption at the intestinal level. In conclusion, our data suggest that Bifidobacterium species could potentially be useful as probiotic supplements to the laboratory marmoset diet. Future studies with a larger sample size will be beneficial to show that this is consistent with the diet change.IMPORTANCEAppropriate diet and health of the common marmoset in captivity are essential both for the welfare of the animal and to improve experimental outcomes. Our study shows that a gel diet compared to a biscuit diet improves the health of a marmoset colony, is linked to increases in Bifidobacterium species, and increases the removal of molecules associated with disease. The diet transition had an influence on the molecular changes at both the pair and time point group levels, but only at the pair level for the microbial changes. It appears to be more important which genes and functions present changed rather than specific microbes. Further studies are needed to identify specific components that should be considered when choosing an appropriate diet and additional supplementary foods, as well as to validate the benefits of providing probiotics. Probiotics containing Bifidobacterium species appear to be useful as probiotic supplements to the laboratory marmoset diet, but additional work is needed to validate these findings.

Abstract Coral bleaching is a well-documented and increasingly widespread phenomenon in reefs across the globe, yet there has been relatively little research on the implications for reef water column microbiology and biogeochemistry. A mesocosm heating experiment and bottle incubation compared how unbleached and bleached corals alter dissolved organic matter (DOM) exudation in response to thermal stress and subsequent effects on microbial growth and community structure in the water column. Thermal stress of healthy corals tripled DOM flux relative to ambient corals. DOM exudates from stressed corals (heated and/or previously bleached) were compositionally distinct from healthy corals and significantly increased growth of bacterioplankton, enriching copiotrophs and putative pathogens. Together these results demonstrate how the impacts of both short-term thermal stress and long-term bleaching may extend into the water column, with altered coral DOM exudation driving microbial feedbacks that influence how coral reefs respond to and recover from mass bleaching events.

Abstract Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Summary: The gastrointestinal (GI) tract is innervated by intrinsic neurons of the enteric nervous system (ENS) and extrinsic neurons of the central nervous system and peripheral ganglia. The GI tract also harbors a diverse microbiome, but interactions between the ENS and the microbiome remain poorly understood. Here, we activate choline acetyltransferase (ChAT)-expressing or tyrosine hydroxylase (TH)-expressing gut-associated neurons in mice to determine effects on intestinal microbial communities and their metabolites as well as on host physiology. The resulting multi-omics datasets support broad roles for discrete peripheral neuronal subtypes in shaping microbiome structure, including modulating bile acid profiles and fungal colonization. Physiologically, activation of either ChAT+ or TH+ neurons increases fecal output, while only ChAT+ activation results in increased colonic contractility and diarrhea-like fluid secretion. These findings suggest that specific subsets of peripherally activated neurons differentially regulate the gut microbiome and GI physiology in mice without involvement of signals from the brain.

ABSTRACTSkin microbiome can be altered in patients with atopic dermatitis (AD). An understanding of the changes from healthy to atopic skin can help develop new targets for treatment by identifying microbial and molecular biomarkers. This study investigates the skin microbiome and metabolome of healthy adult subjects and lesion (ADL) and non-lesion (ADNL) of AD patients by 16S rRNA gene sequencing and mass spectrometry, respectively. Samples from AD patients showed alterations in the diversity and composition of the skin microbiome, with ADL skin having the greatest divergence. Staphylococcus species, especially S. aureus, were significantly increased in AD patients. Metabolomic profiles were also different between the groups. Dipeptide derivatives are more abundant in ADL, which may be related to skin inflammation. Co-occurrence network analysis of the microbiome and metabolomics data revealed higher co-occurrence of metabolites and bacteria in healthy ADNL compared to ADL. S. aureus co-occurred with dipeptide derivatives in ADL, while phytosphingosine-derived compounds showed co-occurrences with commensal bacteria, for example, Paracoccus sp., Pseudomonas sp., Prevotella bivia, Lactobacillus iners, Anaerococcus sp., Micrococcus sp., Corynebacterium ureicelerivorans, Corynebacterium massiliense, Streptococcus thermophilus, and Roseomonas mucosa, in healthy and ADNL groups. Therefore, these findings provide valuable insights into how AD affects the human skin metabolome and microbiome.IMPORTANCEThis study provides valuable insight into changes in the skin microbiome and associated metabolomic profiles in an adult population with mild to moderate atopic dermatitis. It also identifies new therapeutic targets that may be useful for developing personalized treatments for individuals with atopic dermatitis based on their unique skin microbiome and metabolic profiles.

Abstract White teeth can give confidence and tend to be associated with a healthier lifestyle in modern society. Therefore, tooth-bleaching strategies have been developed, including the use of hydrogen peroxide. Recently, peroxymonosulfate has been introduced as an alternative bleaching method to hydrogen peroxide. Although both chemicals are oxidizing agents, their effects on the molecular composition of the stained teeth are yet unknown. In this study, the molecular profiles of teeth bleached with hydrogen peroxide and peroxymonosulfate were compared using Liquid Chromatography-Tandem Mass Spectrometry. Statistical analyses were used to assess the samples. In addition, reference spectral libraries and in silico tools were used to perform metabolite annotation. Overall, principal component analysis showed a strong separation between control and hydrogen peroxide and peroxymonosulfate samples (p

Despite substantial evidence supporting the efficacy of prebiotics for promoting host health and stress resilience, few experiments present evidence documenting the dynamic changes in microbial ecology and fecal microbially modified metabolites over time. Furthermore, the literature reports a lack of reproducible effects of prebiotics on specific bacteria and bacterial-modified metabolites. The current experiments examined whether consumption of diets enriched in prebiotics (galactooligosaccharides (GOS) and polydextrose (PDX)), compared to a control diet, would consistently impact the gut microbiome and microbially modified bile acids over time and between two research sites. Male Sprague Dawley rats were fed control or prebiotic diets for several weeks, and their gut microbiomes and metabolomes were examined using 16S rRNA gene sequencing and untargeted LC–MS/MS analysis. Dietary prebiotics altered the beta diversity, relative abundance of bacterial genera, and microbially modified bile acids over time. PICRUSt2 analyses identified four inferred functional metabolic pathways modified by the prebiotic diet. Correlational network analyses between inferred metabolic pathways and microbially modified bile acids revealed deoxycholic acid as a potential network hub. All these reported effects were consistent between the two research sites, supporting the conclusion that dietary prebiotics robustly changed the gut microbial ecosystem. Consistent with our previous work demonstrating that GOS/PDX reduces the negative impacts of stressor exposure, we propose that ingesting a diet enriched in prebiotics facilitates the development of a health-promoting gut microbial ecosystem.

Abstract Elective transjugular intrahepatic portosystemic shunt (TIPS) placement can worsen cognitive dysfunction in hepatic encephalopathy (HE) patients due to toxins, including possible microbial metabolites, entering the systemic circulation. We conducted untargeted metabolomics on a prospective cohort of 22 patients with cirrhosis undergoing elective TIPS placement and followed them up to one year post TIPS for HE development. Here we suggest that pre-existing intrahepatic shunting predicts HE severity post-TIPS. Bile acid levels decrease in the peripheral vein post-TIPS, and the abundances of three specific conjugated di- and tri-hydroxylated bile acids are inversely correlated with HE grade. Bilirubins and glycerophosphocholines undergo chemical modifications pre- to post-TIPS and based on HE grade. Our results suggest that TIPS-induced metabolome changes can impact HE development, and that pre-existing intrahepatic shunting could be used to predict HE severity post-TIPS.

Abstract The dominant benthic primary producers in coral reef ecosystems are complex holobionts with diverse microbiomes and metabolomes. In this study, we characterize the tissue metabolomes and microbiomes of corals, macroalgae, and crustose coralline algae via an intensive, replicated synoptic survey of a single coral reef system (Waimea Bay, Oʻahu, Hawaii) and use these results to define associations between microbial taxa and metabolites specific to different hosts. Our results quantify and constrain the degree of host specificity of tissue metabolomes and microbiomes at both phylum and genus level. Both microbiome and metabolomes were distinct between calcifiers (corals and CCA) and erect macroalgae. Moreover, our multi-omics investigations highlight common lipid-based immune response pathways across host organisms. In addition, we observed strong covariation among several specific microbial taxa and metabolite classes, suggesting new metabolic roles of symbiosis to further explore.

Abstract The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra. However, the number of reference NMR spectra available is limited and has mostly facilitated annotation of commercially available derivatives. Here, we introduce DeepSAT, a neural network-based structure annotation and scaffold prediction system that directly extracts the chemical features associated with molecular structures from their NMR spectra. Using only the 1H-13C HSQC spectrum, DeepSAT identifies related known compounds and thus efficiently assists in the identification of molecular structures. DeepSAT is expected to accelerate chemical and biomedical research by accelerating the identification of molecular structures.

ABSTRACTAlthough metabolomics data acquisition and analysis technologies have become increasingly sophisticated over the past 5–10 years, deciphering a metabolite’s function from a description of its structure and its abundance in a given experimental setting is still a major scientific and intellectual challenge. To point out ways to address this “data to knowledge” challenge, we developed a functional metabolomics strategy that combines state-of-the-art data analysis tools and applied it to a human scalp metabolomics data set: skin swabs from healthy volunteers with normal or oily scalp (Sebumeter score 60–120, n = 33; Sebumeter score > 120, n = 41) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), yielding four metabolomics data sets for reversed phase chromatography (C18) or hydrophilic interaction chromatography (HILIC) separation in electrospray ionization (ESI) + or − ionization mode. Following our data analysis strategy, we were able to obtain increasingly comprehensive structural and functional annotations, by applying the Global Natural Product Social Networking (M. Wang, J. J. Carver, V. V. Phelan, L. M. Sanchez, et al., Nat Biotechnol 34:828–837, 2016, https://doi.org/10.1038/nbt.3597), SIRIUS (K. Dührkop, M. Fleischauer, M. Ludwig, A. A. Aksenov, et al., Nat Methods 16:299–302, 2019, https://doi.org/10.1038/s41592-019-0344-8), and MicrobeMASST (S. ZuffaS, R. Schmid, A. Bauermeister, P. W, P. Gomes, et al., bioRxiv:rs.3.rs-3189768, 2023, https://doi.org/10.21203/rs.3.rs-3189768/v1) tools. We finally combined the metabolomics data with a corresponding metagenomic sequencing data set using MMvec (J. T. Morton, A. A. Aksenov, L. F. Nothias, J. R. Foulds, et. al., Nat Methods 16:1306–1314, 2019, https://doi.org/10.1038/s41592-019-0616-3), gaining insights into the metabolic niche of one of the most prominent microbes on the human skin, Staphylococcus epidermidis.IMPORTANCESystems biology research on host-associated microbiota focuses on two fundamental questions: which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites’ functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of “omics” data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.

Srinath, Xie et al. analyze plasma metabolites present in patients with cerebral cavernous angiomas. Cholic acid and hypoxanthine are found in those with Cavernous Angioma disease whilst arachidonic and linoleic acids are found in Cavernous Angioma patients with symptomatic hemorrhage.

Abstract Human milk is the optimal infant nutrition. However, although human‐derived metabolites (such as lipids and oligosaccharides) in human milk are regularly reported, the presence of exogenous chemicals (such as drugs, food, and synthetic compounds) are often not addressed. To understand the types of exogenous compounds that might be present, human milk (n = 996) was analyzed by untargeted metabolomics. This analysis revealed that lifestyle molecules, such as medications and their metabolites, and industrial sources, such as plasticizers, cosmetics, and other personal care products, are found in human milk. We provide further evidence that some of these lifestyle molecules are also detectable in the newborn's stool. Thus, this study gives important insight into the types of exposures infants receiving human milk might ingest due to the lifestyle choices, exposure, or medical status of the lactating parent.

Summary: Colorectal cancer (CRC) is driven by genomic alterations in concert with dietary influences, with the gut microbiome implicated as an effector in disease development and progression. While meta-analyses have provided mechanistic insight into patients with CRC, study heterogeneity has limited causal associations. Using multi-omics studies on genetically controlled cohorts of mice, we identify diet as the major driver of microbial and metabolomic differences, with reductions in α diversity and widespread changes in cecal metabolites seen in high-fat diet (HFD)-fed mice. In addition, non-classic amino acid conjugation of the bile acid cholic acid (AA-CA) increased with HFD. We show that AA-CAs impact intestinal stem cell growth and demonstrate that Ileibacterium valens and Ruminococcus gnavus are able to synthesize these AA-CAs. This multi-omics dataset implicates diet-induced shifts in the microbiome and the metabolome in disease progression and has potential utility in future diagnostic and therapeutic developments.

Bioactivity-guided isolation of specialized metabolites is an iterative process. Here, the authors demonstrate a native metabolomics approach that allows for fast screening of complex metabolite extracts against a protein of interest and simultaneous structure annotation.

Abstract Background Gut microorganisms aid in the digestion of food by providing exogenous metabolic pathways to break down organic compounds. An integration of longitudinal microbial and chemical data is necessary to illuminate how gut microorganisms supplement the energetic and nutritional requirements of animals. Although mammalian gut systems are well-studied in this capacity, the role of microbes in the breakdown and utilization of recalcitrant marine macroalgae in herbivorous fish is relatively understudied and an emerging priority for bioproduct extraction. Here we use a comprehensive survey of the marine herbivorous fish gut microbial ecosystem via parallel 16S rRNA gene amplicon profiling (microbiota) and untargeted tandem mass spectrometry (metabolomes) to demonstrate consistent transitions among 8 gut subsections across five fish of the genus of Kyphosus. Results Integration of microbial phylogenetic and chemical diversity data reveals that microbial communities and metabolomes covaried and differentiated continuously from stomach to hindgut, with the midgut containing multiple distinct and previously uncharacterized microenvironments and a distinct hindgut community dominated by obligate anaerobes. This differentiation was driven primarily by anaerobic gut endosymbionts of the classes Bacteroidia and Clostridia changing in concert with bile acids, small peptides, and phospholipids: bile acid deconjugation associated with early midgut microbiota, small peptide production associated with midgut microbiota, and phospholipid production associated with hindgut microbiota. Conclusions The combination of microbial and untargeted metabolomic data at high spatial resolution provides a new view of the diverse fish gut microenvironment and serves as a foundation to understand functional partitioning of microbial activities that contribute to the digestion of complex macroalgae in herbivorous marine fish.

Interrelating metabolites by their fragmentation spectra is central to metabolomics. Here the authors align fragmentation spectra with both statistical significance and allowance for multiple chemical differences using Significant Interrelation of MS/MS Ions via Laplacian Embedding (SIMILE).

Abstract Preterm infants are at a greater risk for the development of asthma and atopic disease, which can lead to lifelong negative health consequences. This may be due, in part, to alterations that occur in the gut microbiome and metabolome during their stay in the Neonatal Intensive Care Unit (NICU). To explore the differential roles of family history (i.e., predisposition due to maternal asthma diagnosis) and hospital-related environmental and clinical factors that alter microbial exposures early in life, we considered a unique cohort of preterm infants born ≤ 34 weeks gestational age from two local level III NICUs, as part of the MAP (Microbiome, Atopic disease, and Prematurity) Study. From MAP participants, we chose a sub-cohort of infants whose mothers had a history of asthma and matched gestational age and sex to infants of mothers without a history of asthma diagnosis (control). We performed a prospective, paired metagenomic and metabolomic analysis of stool and milk feed samples collected at birth, 2 weeks, and 6 weeks postnatal age. Although there were clinical factors associated with shifts in the diversity and composition of stool-associated bacterial communities, maternal asthma diagnosis did not play an observable role in shaping the infant gut microbiome during the study period. There were significant differences, however, in the metabolite profile between the maternal asthma and control groups at 6 weeks postnatal age. The most notable changes occurred in the linoleic acid spectral network, which plays a role in inflammatory and immune pathways, suggesting early metabolomic changes in the gut of preterm infants born to mothers with a history of asthma. Our pilot study suggests that a history of maternal asthma alters a preterm infants’ metabolomic pathways in the gut, as early as the first 6 weeks of life.

Abstract There is a growing interest in unraveling the chemical complexity of our diets. To help the scientific community gain insight into the molecules present in foods and beverages that we ingest, we created foodMASST, a search tool for MS/MS spectra (of both known and unknown molecules) against a growing metabolomics food and beverage reference database. We envision foodMASST will become valuable for nutrition research and to assess the potential uniqueness of dietary biomarkers to represent specific foods or food classes.

Abstract 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.

Abstract Background Depression and obesity are highly prevalent, often co-occurring conditions marked by inflammation. Microbiome perturbations are implicated in obesity-inflammation-depression interrelationships, but how the microbiome mechanistically contributes to pathology remains unclear. Metabolomic investigations into microbial neuroactive metabolites may offer mechanistic insights into host-microbe interactions. Using 16S sequencing and untargeted mass spectrometry of saliva, and blood monocyte inflammation regulation assays, we identified key microbes, metabolites and host inflammation in association with depressive symptomatology, obesity, and depressive symptomatology-obesity comorbidity. Results Gram-negative bacteria with inflammation potential were enriched relative to Gram-positive bacteria in comorbid obesity-depression, supporting the inflammation-oral microbiome link in obesity-depression interrelationships. Oral microbiome was more highly predictive of depressive symptomatology-obesity co-occurrences than of obesity or depressive symptomatology independently, suggesting specific microbial signatures associated with obesity-depression co-occurrences. Mass spectrometry analysis revealed significant changes in levels of signaling molecules of microbiota, microbial or dietary derived signaling peptides and aromatic amino acids among depressive symptomatology, obesity and comorbid obesity-depression. Furthermore, integration of the microbiome and metabolomics data revealed that key oral microbes, many previously shown to have neuroactive potential, co-occurred with potential neuropeptides and biosynthetic precursors of the neurotransmitters dopamine, epinephrine and serotonin. Conclusions Together, our findings offer novel insights into oral microbial-brain connection and potential neuroactive metabolites involved.

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

Zinc is an essential cofactor for bacterial metabolism. Here, the authors show that the probiotic bacterium Escherichia coli Nissle 1917 utilizes the siderophore yersiniabactin as a zincophore, allowing the microbe to grow in zinc-limited media and to thrive in the inflamed gut.

Abstract Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.

Current genome mining methods predict many putative non-ribosomal peptides (NRPs) from their corresponding biosynthetic gene clusters, but it remains unclear which of those exist in nature and how to identify their post-assembly modifications. Here, the authors develop NRPminer, a modification-tolerant tool for the discovery of NRPs from large genomic and mass spectrometry datasets, and use it to find 180 NRPs from different environments.

Abstract Background Infectious bacterial diseases exhibiting increasing resistance to antibiotics are a serious global health issue. Bacteriophage therapy is an anti-microbial alternative to treat patients with serious bacterial infections. However, the impacts to the host microbiome in response to clinical use of phage therapy are not well understood. Results Our paper demonstrates a largely unchanged microbiota profile during 4 weeks of phage therapy when added to systemic antibiotics in a single patient with Staphylococcus aureus device infection. Metabolomic analyses suggest potential indirect cascading ecological impacts to the host (skin) microbiome. We did not detect genomes of the three phages used to treat the patient in metagenomic samples taken from saliva, stool, and skin; however, phages were detected using endpoint-PCR in patient serum. Conclusion Results from our proof-of-principal study supports the use of bacteriophages as a microbiome-sparing approach to treat bacterial infections. Video abstract

Untargeted metabolomics is a powerful tool for profiling the biochemical phenotypes of organisms and discovering new metabolites that drive biological function and might be exploited as pharmaceutical leads. Yet, connecting physiological processes to metabolites detected remains a challenge due to the lack of structural and activity annotations and the underlying complexity of mixed samples (e.g., multiple microorganisms, organelles, etc.). To simplify this biological complexity, we separated coral holobionts into host mitochondria and their algal symbionts prior to LC-MS/MS-based untargeted metabolomic analysis followed by molecular networking. We found distinct metabolomic profiles between tissue fractions. Notably, 14% of metabolites detected were only observed in the mitochondria and algal symbionts, not in the holobiont, and thus were masked when the bulk (holobiont) sample was analyzed. The utility of tissue separation for hypothesis testing was assessed using a simple temperature experiment. We tested the hypothesis that membrane lipids of the coral mitochondria and algal symbionts become more saturated at higher temperatures to maintain membrane rigidity. While the holobiont metabolite profiles showed little change in response to elevated temperature, there was a change in lipid saturation of both fractions through time. The fatty acid saturation of both the coral mitochondria and the algal symbionts shifted upon exposure to higher temperatures (1 h) then returned to ambient saturation levels by 4 h, indicating rapid acclimatization to warmer water. Surprisingly, the fractions deviated in opposite directions: during the first hour of the experiment, the mitochondria showed an increase in saturated lipid concentrations, while the algal symbionts showed an increase in unsaturated lipids. Partitioning the holobiont prior to untargeted metabolomic analysis revealed disparate responses to environmental stress that would have gone undetected if only the holobiont/bulk tissue was analyzed. This work illustrates rapid physiological acclimatization to environmental changes in specific host organelles and symbionts, though via different paths.

Sleep disruption is a challenging and exceedingly common physiological state that contributes to a wide range of biochemical and molecular perturbations and has been linked to numerous adverse health outcomes. Modern society exerts significant pressure on the sleep/wake cycle via myriad factors, including exposure to electric light, psychological stressors, technological interconnection, jet travel, shift work, and widespread use of sleep-affecting compounds. Interestingly, recent research has identified a link between the microbiome and the regulation of sleep, suggesting that interventions targeting the microbiome may offer unique therapeutic approaches to challenges posed by sleep disruption. In this study, we test the hypothesis that administration of a prebiotic diet containing galactooligosaccharides (GOS) and polydextrose (PDX) in adult male rats improves sleep in response to repeated sleep disruption and during recovery sleep. We found that animals fed the GOS/PDX prebiotic diet for 4 weeks exhibit increased non-rapid eye movement (NREM) and rapid eye movement (REM) sleep during 5 days of sleep disruption and increased total sleep time during 24 h of recovery from sleep disruption compared to animals fed a control diet, despite similar baseline sleep characteristics. Further, the GOS/PDX prebiotic diet led to significant changes in the fecal microbiome. Consistent with previous reports, the prebiotic diet increased the relative abundance of the species Parabacteroides distasonis, which positively correlated with sleep parameters during recovery sleep. Taken together, these findings suggest that the GOS/PDX prebiotic diet may offer an approach to improve resilience to the physiologic challenge of sleep disruption, in part through impacts on the microbiome.

Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups.

The toolbox available for microbiologists to study interspecies interactions is rapidly growing, and with continuously more advanced instruments, we are able to expand our knowledge on establishment and function of microbial communities. However, unravelling molecular interspecies interactions in complex biological systems remains a challenge, and interactions are therefore often studied in simplified communities. Here we perform an in-depth characterization of an observed interspecies interaction between two co-isolated bacteria, Xanthomonas retroflexus and Paenibacillus amylolyticus. Using microsensor measurements for mapping the chemical environment, we show how X. retroflexus promoted an alkalization of its local environment through degradation of amino acids and release of ammonia. When the two species were grown in proximity, the modified local environment induced a morphological change and growth of P. amylolyticus followed by sporulation. 2D spatial metabolomics enabled visualization and mapping of the degradation of oligopeptide structures by X. retroflexus and morphological changes of P. amylolyticus through e.g. the release of membrane-associated metabolites. Proteome analysis and microscopy were used to validate the shift from vegetative growth towards sporulation. In summary, we demonstrate how environmental profiling by combined application of microsensor, microscopy, metabolomics and proteomics approaches can reveal growth and sporulation promoting effects resulting from interspecies interactions.

Determining factors that contribute to interindividual and intra‐individual variability in pharmacokinetics (PKs) and drug metabolism is essential for the optimal use of drugs in humans. Intestinal microbes are important contributors to variability; however, such gut microbe‐drug interactions and the clinical significance of these interactions are still being elucidated. Traditional PKs can be complemented by untargeted mass spectrometry coupled with molecular networking to study the intricacies of drug metabolism. To show the utility of molecular networking on metabolism we investigated the impact of a 7‐day course of cefprozil on cytochrome P450 (CYP) activity using a modified Cooperstown cocktail and assessed plasma, urine, and fecal data by targeted and untargeted metabolomics and molecular networking in healthy volunteers. This prospective study revealed that cefprozil decreased the activities of CYP1A2, CYP2C19, and CYP3A, decreased alpha diversity and increased interindividual microbiome variability. We further demonstrate a relationship between the loss of microbiome alpha diversity caused by cefprozil and increased drug and metabolite formation in fecal samples. Untargeted metabolomics/molecular networking revealed several omeprazole metabolites that we hypothesize may be metabolized by both CYP2C19 and bacteria from the gut microbiome. Our observations are consistent with the hypothesis that factors that perturb the gut microbiome, such as antibiotics, alter drug metabolism and ultimately drug efficacy and toxicity but that these effects are most strongly revealed on a per individual basis.

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.

ABSTRACT Alterations to the gut microbiome have been reported between children with autism spectrum disorders (ASDs) and typically developing (TD) children. Characterizing these differences has led to the proposal of new treatments for ASD, such as probiotic interventions and fecal matter transplants. However, no study to date has characterized the gut microbiome or metabolome in Pitt Hopkins syndrome (PTHS), a severe ASD with a high incidence of gastrointestinal (GI) disturbances such as constipation. Here, we surveyed the gut microbiome and metabolome in a cohort of PTHS individuals and their unaffected parents. We focused our analysis on Clostridium bolteae, a microbe previously associated with ASD known to chemically modify bile acids in the gut. PTHS individuals carry a higher load of C. bolteae than their parents as well as both ASD and non-ASD individuals from the American Gut Project cohort. Specific metabolites were associated with PTHS, including bile acids and sphingosines. With a metadata reanalysis tool, we found that PTHS-associated metabolites have previously been identified in inflammatory bowel disease and obesity patients. These results suggest microbial involvement in PTHS, but further research must be performed to clarify the exact mechanisms through which microbes may act. Furthermore, new associations between PTHS-specific metabolites and other conditions may lead to additional therapeutic options for PTHS individuals. IMPORTANCE GI disturbances in ASD such as severe constipation can be medically significant and often require medication. This is especially true for individuals with PTHS, suggesting that the gut microbiome may be involved in PTHS’s pathology. Revealing associations between specific gut microbes and PTHS may allow the development of new therapeutics or the application of existing therapeutics to ease day-to-day challenges encountered by PTHS individuals. In this study, we characterized an association between C. bolteae and PTHS, in addition to metabolites linked to both PTHS and C. bolteae. We also identified other microbiome-involved medical conditions where PTHS-associated metabolites have been isolated. Utilizing common metabolites to identify conditions with similar phenotypes may suggest new therapeutic options for GI-related symptoms.

Recent developments in molecular networking have expanded our ability to characterize the metabolome of diverse samples that contain a significant proportion of ion features with no mass spectral match to known compounds. Manual and tool-assisted natural annotation propagation is readily used to classify molecular networks; however, currently no annotation propagation tools leverage consensus confidence strategies enabled by hierarchical chemical ontologies or enable the use of new in silico tools without significant modification. Herein we present ConCISE (Consensus Classifications of In Silico Elucidations) which is the first tool to fuse molecular networking, spectral library matching and in silico class predictions to establish accurate putative classifications for entire subnetworks. By limiting annotation propagation to only structural classes which are identical for the majority of ion features within a subnetwork, ConCISE maintains a true positive rate greater than 95% across all levels of the ChemOnt hierarchical ontology used by the ClassyFire annotation software (superclass, class, subclass). The ConCISE framework expanded the proportion of reliable and consistent ion feature annotation up to 76%, allowing for improved assessment of the chemo-diversity of dissolved organic matter pools from three complex marine metabolomics datasets comprising dominant reef primary producers, five species of the diatom genus Pseudo-nitzchia, and stromatolite sediment samples.

A multidisciplinary approach was used to assess chemical ecological dietary interactions between marine organisms as a tool to isolate novel ecologically relevant compounds with biotechnological potential. First, laboratory-based feeding preference assays of the sea hare Dolabrifera nicaraguana (previously known as D. dolabrifera), an anaspidean mollusc, were conducted by simultaneously offering six food options collected from nearby tidal pools in the Coiba National Park in the Tropical Eastern Pacific of Panama. An evaluation of preferred dietary repertoire revealed D. nicaraguana significantly preferred cf. Lyngbya sp. over the cyanobacterium Symploca sp., green alga Chaetomorpha sp., and red alga Spyridia sp. A no-choice feeding assay using cf. Lyngbya sp. or green alga Cladophora sp. supported this finding. Secondly, we conducted bioactivity-guided fractionation using the preferred food source of D. nicaraguana, the ‘hair-like” cf. Lyngbya sp. from which we also isolated and elucidated two new depsipeptide compounds, veraguamide M (1) and veraguamide N (2). Veraguamides M (1) and N (2) showed in vitro activity toward the malaria-causing parasite Plasmodium falciparum with GI50 values of 4.2 and 4.3 μM, respectively, and therapeutic windows of 7.0–8.0 (based on moderate cytotoxicities to mammalian Vero cells with GI50 values of 29.3 and 34.1 μM, respectively). Veraguamide N (2) was also active against Leishmania donovani, the causative agent of visceral leishmaniasis, with a GI50 value of 6.9 μM. We then evaluated sequestration of these new compounds by D. nicaraguana used in the feeding assays and found trace amounts of the dietary sequestered compounds. Finally, we evaluated sequestration of these new compounds by the sea hare Stylocheilus rickettsi (previously known as S. striatus) that were grazing on the cf. Lyngbya sp. used in the feeding assays and found both to be sequestered. This study is the first example whereby compounds with significant activity against tropical parasites have been found in both the sea hare S. rickettsi and its cyanobacterial food source. These results suggest that chemical ecological studies involving sea hares and cyanobacteria continue to provide a diverse source of bioactive compounds with biotechnological potential.

ABSTRACT Many ant species grow fungus gardens that predigest food as an essential step of the ants’ nutrient uptake. These symbiotic fungus gardens have long been studied and feature a gradient of increasing substrate degradation from top to bottom. To further facilitate the study of fungus gardens and enable the understanding of the predigestion process in more detail than currently known, we applied recent mass spectrometry-based approaches and generated a three-dimensional (3D) molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments to compare with lab-maintained ecosystems. IMPORTANCE The study of complex ecosystems requires an understanding of the chemical processes involving molecules from several sources. Some of the molecules present in fungus-growing ants’ symbiotic system originate from plants. To facilitate the study of fungus gardens from a chemical perspective, we provide a molecular map of an Atta texana fungus garden to reveal chemical modifications as plant substrates pass through it. The metabolomics approach presented in this study can be applied to study similar processes in natural environments.

Summary: Bacterial communities are in a continuous adaptive and evolutionary race for survival. In this work we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis PCL1606 and Bacillus amyloliquefaciens FZB42. We reveal that the bacteriostatic activity of bacillaene produced by Bacillus relies on an interaction with the protein elongation factor FusA of P. chlororaphis and how mutations in this protein lead to tolerance to bacillaene and other protein translation inhibitors. Additionally, we describe how the unspecific tolerance of B. amyloliquefaciens to antimicrobials associated with mutations in the glycerol kinase GlpK is provoked by a decrease of Bacillus cell membrane permeability, among other pleiotropic responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial adaptive dynamics that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.

The rapidly advancing field of metabolomics encompasses a diverse suite of powerful analytical and bioinformatic tools that can help to reveal the diversity and activity of chemical compounds in individual organisms, species interactions, and entire ecosystems. In this perspective we use examples from studies of coral reefs to illustrate ways in which metabolomics has been and can be applied to understand coastal ecosystems. Examples of new insights that can be provided by metabolomics include resolving metabolite exchange between plants, animals and their microbiota, identifying the relevant metabolite exchanges associated with the onset and maintenance of diverse, microbial mutualisms characterizing unknown molecules that act as cues in coral, reproduction, or defining the suites of compounds involved in coral-algal competition and microbialization of algal-dominated ecosystems. Here we outline sampling, analytical and informatic methods that marine biologists and ecologists can apply to understand the role of chemical processes in ecosystems, with a focus on open access data analysis workflows and democratized databases. Finally, we demonstrate how these metabolomics tools and bioinformatics approaches can provide scientists the opportunity to map detailed metabolic inventories and dynamics for a holistic view of the relationships among reef organisms, their symbionts and their surrounding marine environment.

People with obstructive sleep apnea, identified by loud snoring and breathing irregularly while sleeping, are at a higher risk of high blood pressure, type 2 diabetes, cardiac arrhythmias, stroke, and sudden cardiac death. We wanted to understand whether the gut microbiome changes induced by obstructive sleep apnea could potentially explain some of these medical problems.

Abstract As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.

Abstract 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.