Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach.

BACKGROUND: The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. OBJECTIVE: Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. METHODS AND RESULTS: Using a subset of milk samples obtained as part of our broad studies examining the effects on milk of SARS-CoV-2 infection and COVID-19 vaccination, an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. CONCLUSIONS: Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Media matters! Alterations in the loading and release of Histoplasma capsulatum extracellular vesicles in response to different nutritional milieus.

Histoplasma capsulatum is a dimorphic fungus that most frequently causes pneumonia, but can also disseminate and proliferate in diverse tissues. Histoplasma capsulatum has a complex secretion system that mediates the release of macromolecule-degrading enzymes and virulence factors. The formation and release of extracellular vesicles (EVs) are an important mechanism for non-conventional secretion in both ascomycetes and basidiomycetes. Histoplasma capsulatum EVs contain diverse proteins associated with virulence and are immunologically active. Despite the growing knowledge of EVs from H. capsulatum and other pathogenic fungi, the extent that changes in the environment impact the sorting of organic molecules in EVs has not been investigated. In this study, we cultivated H. capsulatum with distinct culture media to investigate the potential plasticity in EV loading in response to differences in nutrition. Our findings reveal that nutrition plays an important role in EV loading and formation, which may translate into differences in biological activities of these fungi in various fluids and tissues.

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells.

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

Metabolomic and transcriptomic remodeling of bone marrow myeloid cells in response to maternal obesity.

Maternal obesity puts the offspring at high risk of developing obesity and cardio-metabolic diseases in adulthood. Here, using a mouse model of maternal high-fat diet (HFD)-induced obesity, we show that whole body fat content of the offspring of HFD-fed mothers (Off-HFD) increases significantly from very early age when compared to the offspring regular diet-fed mothers (Off-RD). We have previously shown significant metabolic and immune perturbations in the bone marrow of newly-weaned offspring of obese mothers. Therefore, we hypothesized that lipid metabolism is altered in the bone marrow Off-HFD in newly-weaned offspring of obese mothers when compared to the Off-RD. To test this hypothesis, we investigated the lipidomic profile of bone marrow cells collected from three-week-old offspring of regular and high fat diet-fed mothers. Diacylgycerols (DAGs), triacylglycerols (TAGs), sphingolipids and phospholipids, including plasmalogen, and lysophospholipids were remarkably different between the groups, independent of fetal sex. Levels of cholesteryl esters were significantly decreased in offspring of obese mothers, suggesting reduced delivery of cholesterol to bone marrow cells. This was accompanied by age-dependent progression of mitochondrial dysfunction in bone marrow cells. We subsequently isolated CD11b+ myeloid cells from three-week-old mice and conducted metabolomics, lipidomics, and transcriptomics analyses. The lipidomic profiles of these bone marrow myeloid cells were largely similar to that seen in bone marrow cells and included increases in DAGs and phospholipids alongside decreased TAGs, except for long-chain TAGs, which were significantly increased. Our data also revealed significant sex-dependent changes in amino acids and metabolites related to energy metabolism. Transcriptomic analysis revealed altered expression of genes related to major immune pathways including macrophage alternative activation, B-cell receptor signaling, TGFß signaling, and communication between the innate and adaptive immune systems. All told, this study revealed lipidomic, metabolomic, and gene expression abnormalities in bone marrow cells broadly, and in bone marrow myeloid cells particularly, in the newly-weaned offspring of obese mothers, which might at least partially explain the progression of metabolic and cardiovascular diseases in their adulthood.

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data.

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, we describe and illustrate PeakQC's functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry.

IMPORTANCE: Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions.

Graphene oxide exposure alters gut microbial community composition and metabolism in an in vitro human model.

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. There is growing interest in the use of GO and extensive in vitro and in vivo studies have been conducted to assess its nanotoxicity. Although it is known that GO can alter the composition of the gut microbiota in mice and zebrafish, studies on the potential impacts of GO on the human gut microbiome are largely lacking. This study addresses an important knowledge gap by investigating the impact of GO exposure- at low (25 mg/L) and high (250 mg/L) doses under both fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial communitys' structure and function, using an in vitro model. This model includes simulated oral, gastric, small intestinal phase digestion of GO followed by incubation in a colon bioreactor. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 mg/L GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 mg/L GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 mg/L GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 mg/L GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism at both low and high GO concentrations.

Fungal organic acid uptake of mineral-derived K is dependent on distance from carbon hotspot.

IMPORTANCE: Fungal species are foundational members of soil ecosystems with vital contributions that support interspecies resource translocation. The minute details of these biogeochemical processes are poorly investigated. Here, we addressed this knowledge gap by probing fungal growth in a novel mineral-doped soil micromodel platform using spatially-resolved imaging methodologies. We found that fungi uptake K from K-rich minerals using organic acids exuded in a distance-dependent manner from a carbon-rich hotspot. While identification of specific mechanisms within soil remains challenging, our findings demonstrate the significance of reduced complexity platforms such as the mineral-doped micromodel in probing biogeochemical processes. These findings provide visualization into hyphal uptake and transport of mineral-derived nutrients in a resource-limited environment.

Interrogating the role of the milk microbiome in mastitis in the multi-omics era.

There is growing interest in a functional understanding of milk-associated microbiota as there is ample evidence that host-associated microbial communities play an active role in host health and phenotype. Mastitis, characterized by painful inflammation of the mammary gland, is prevalent among lactating humans and agricultural animals and is associated with significant clinical and economic consequences. The etiology of mastitis is complex and polymicrobial and correlative studies have indicated alterations in milk microbial community composition. Recent evidence is beginning to suggest that a causal relationship may exist between the milk microbiota and host phenotype in mastitis. Multi-omic approaches can be leveraged to gain a mechanistic, molecular level understanding of how the milk microbiome might modulate host physiology, thereby informing strategies to prevent and ameliorate mastitis. In this paper, we review existing studies that have utilized omics approaches to investigate the role of the milk microbiome in mastitis. We also summarize the strengths and challenges associated with the different omics techniques including metagenomics, metatranscriptomics, metaproteomics, metabolomics and lipidomics and provide perspective on the integration of multiple omics technologies for a better functional understanding of the milk microbiome.

Rapid remodeling of the soil lipidome in response to a drying-rewetting event.

BACKGROUND: Microbiomes contribute to multiple ecosystem services by transforming organic matter in the soil. Extreme shifts in the environment, such as drying-rewetting cycles during drought, can impact the microbial metabolism of organic matter by altering microbial physiology and function. These physiological responses are mediated in part by lipids that are responsible for regulating interactions between cells and the environment. Despite this critical role in regulating the microbial response to stress, little is known about microbial lipids and metabolites in the soil or how they influence phenotypes that are expressed under drying-rewetting cycles. To address this knowledge gap, we conducted a soil incubation experiment to simulate soil drying during a summer drought of an arid grassland, then measured the response of the soil lipidome and metabolome during the first 3 h after wet-up. RESULTS: Reduced nutrient access during soil drying incurred a replacement of membrane phospholipids, resulting in a diminished abundance of multiple phosphorus-rich membrane lipids. The hot and dry conditions increased the prevalence of sphingolipids and lipids containing long-chain polyunsaturated fatty acids, both of which are associated with heat and osmotic stress-mitigating properties in fungi. This novel finding suggests that lipids commonly present in eukaryotes such as fungi may play a significant role in supporting community resilience displayed by arid land soil microbiomes during drought. As early as 10 min after rewetting dry soil, distinct changes were observed in several lipids that had bacterial signatures including a rapid increase in the abundance of glycerophospholipids with saturated and short fatty acid chains, prototypical of bacterial membrane lipids. Polar metabolites including disaccharides, nucleic acids, organic acids, inositols, and amino acids also increased in abundance upon rewetting. This rapid metabolic reactivation and growth after rewetting coincided with an increase in the relative abundance of firmicutes, suggesting that members of this phylum were positively impacted by rewetting. CONCLUSIONS: Our study revealed specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. The drought-induced nutrient limitation was reflected in the lipidome and polar metabolome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long-chain polyunsaturated fatty acids in dry soil suggest that lipids likely play an important role in the drought tolerance of microbial taxa capable of synthesizing these lipids. An increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest a metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions. Video Abstract.

Comparative metabolomic analysis reveals shared and unique chemical interactions in sponge holobionts.

BACKGROUND: Sponges are ancient sessile metazoans, which form with their associated microbial symbionts a complex functional unit called a holobiont. Sponges are a rich source of chemical diversity; however, there is limited knowledge of which holobiont members produce certain metabolites and how they may contribute to chemical interactions. To address this issue, we applied non-targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) and gas chromatography mass spectrometry (GC-MS) to either whole sponge tissue or fractionated microbial cells from six different, co-occurring sponge species. RESULTS: Several metabolites were commonly found or enriched in whole sponge tissue, supporting the notion that sponge cells produce them. These include 2-methylbutyryl-carnitine, hexanoyl-carnitine and various carbohydrates, which may be potential food sources for microorganisms, as well as the antagonistic compounds hymenialdisine and eicosatrienoic acid methyl ester. Metabolites that were mostly observed or enriched in microbial cells include the antioxidant didodecyl 3,3'-thiodipropionate, the antagonistic compounds docosatetraenoic acid, and immune-suppressor phenylethylamide. This suggests that these compounds are mainly produced by the microbial members in the sponge holobiont, and are potentially either involved in inter-microbial competitions or in defenses against intruding organisms. CONCLUSIONS: This study shows how different chemical functionality is compartmentalized between sponge hosts and their microbial symbionts and provides new insights into how chemical interactions underpin the function of sponge holobionts. Video abstract.

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

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

Fate, cytotoxicity and cellular metabolomic impact of ingested nanoscale carbon dots using simulated digestion and a triculture small intestinal epithelial model.

Carbon dots (CDs) are a promising material currently being explored in many industrial applications in the biomedical and agri-food areas; however, studies supporting the environmental health risk assessment of CDs are needed. This study focuses on various CD forms including iron (FeCD) and copper (CuCD) doped CDs synthesized using hydrothermal method, their fate in gastrointestinal tract, and their cytotoxicity and potential changes to cellular metabolome in a triculture small intestinal epithelial model. Physicochemical characterization revealed that 75% of Fe in FeCD and 95% of Cu in CuCD were dissolved during digestion. No significant toxic effects were observed for pristine CDs and FeCDs. However, CuCD induced significant dose-dependent toxic effects including decreases in TEER and cell viability, increases in cytotoxicity and ROS production, and alterations in important metabolites, including D-glucose, L-cysteine, uridine, citric acid and multiple fatty acids. These results support the current understanding that pristine CDs are relatively non-toxic and the cytotoxicity is dependent on the doping molecules.

Comparative Molecular and Immunoregulatory Analysis of Extracellular Vesicles from Candida albicans and Candida auris.

Candida auris is a recently described multidrug-resistant pathogenic fungus that is increasingly responsible for health care-associated outbreaks across the world. Bloodstream infections of this fungus cause death in up to 70% of cases. Aggravating this scenario, the disease-promoting mechanisms of C. auris are poorly understood. Fungi release extracellular vesicles (EVs) that carry a broad range of molecules, including proteins, lipids, carbohydrates, pigments, and RNA, many of which are virulence factors. Here, we carried out a comparative molecular characterization of C. auris and Candida albicans EVs and evaluated their capacity to modulate effector mechanisms of host immune defense. Using proteomics, lipidomics, and transcriptomics, we found that C. auris released EVs with payloads that were significantly different from those of EVs released by C. albicans. EVs released by C. auris potentiated the adhesion of this yeast to an epithelial cell monolayer, while EVs from C. albicans had no effect. C. albicans EVs primed macrophages for enhanced intracellular yeast killing, whereas C. auris EVs promoted survival of the fungal cells. Moreover, EVs from both C. auris and C. albicans induced the activation of bone marrow-derived dendritic cells. Together, our findings show distinct profiles and properties of EVs released by C. auris and by C. albicans and highlight the potential contribution of C. auris EVs to the pathogenesis of this emerging pathogen. IMPORTANCE Candida auris is a recently described multidrug-resistant pathogenic fungus that is responsible for outbreaks across the globe, particularly in the context of nosocomial infections. Its virulence factors and pathogenesis are poorly understood. Here, we tested the hypothesis that extracellular vesicles (EVs) released by C. auris are a disease-promoting factor. We describe the production of EVs by C. auris and compare their biological activities against those of the better-characterized EVs from C. albicans. C. auris EVs have immunoregulatory properties, of which some are opposite those of C. albicans EVs. We also explored the cargo and structural components of those vesicles and found that they are remarkably distinct compared to EVs from C. auris's phylogenetic relative Candida albicans.

Omics Approaches for Understanding Biogenesis, Composition and Functions of Fungal Extracellular Vesicles.

Extracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections.

MetFish: a Metabolomics Pipeline for Studying Microbial Communities in Chemically Extreme Environments.

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here, we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exometabolomics analysis in sample matrices containing up to 2 M total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and it can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5 to 6 orders of magnitude) with excellent linearity, and low median interday reproducibility (e.g., 2.6%). MetFish was successfully applied in targeted and untargeted exometabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exometabolome during community succession; in situ in a native prairie soil, whose exometabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exometabolome over time in the well. IMPORTANCE The identification and accurate quantification of metabolites using electrospray ionization-mass spectrometry (ESI-MS) in hypersaline samples is a challenge due to matrix effects. Clean-up and desalting strategies that typically work well for samples with lower salt concentrations are often ineffective in hypersaline samples. To address this gap, we developed and demonstrated a simple yet sensitive and accurate method-MetFish-using chemical derivatization to enable mass spectrometry-based metabolomics in a variety of hypersaline samples from varied ecosystems and containing up to 2 M dissolved salts.

A Histoplasma capsulatum Lipid Metabolic Map Identifies Antifungal Targets.

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here, we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide, and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low-micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development. IMPORTANCE It is estimated that 150 people die per hour due to the insufficient therapeutic treatments to combat fungal infections. A major hurdle to developing antifungal therapies is the scarce knowledge on the fungal metabolic pathways and mechanisms of virulence. In this context, fungal lipid metabolism is an excellent candidate for developing drugs due to its essential roles in cellular scaffolds, energy storage, and signaling transductors. Here, we provide a detailed map of Histoplasma capsulatum lipid metabolism. The map revealed points of this fungus lipid metabolism that can be targeted for developing antifungal drugs.

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

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

Who Is Metabolizing What? Discovering Novel Biomolecules in the Microbiome and the Organisms Who Make Them.

Even as the field of microbiome research has made huge strides in mapping microbial community composition in a variety of environments and organisms, explaining the phenotypic influences on the host by microbial taxa-both known and unknown-and their specific functions still remain major challenges. A pressing need is the ability to assign specific functions in terms of enzymes and small molecules to specific taxa or groups of taxa in the community. This knowledge will be crucial for advancing personalized therapies based on the targeted modulation of microbes or metabolites that have predictable outcomes to benefit the human host. This perspective article advocates for the combined use of standards-free metabolomics and activity-based protein profiling strategies to address this gap in functional knowledge in microbiome research via the identification of novel biomolecules and the attribution of their production to specific microbial taxa.