Biology subjects

Strobel, M.

Publications and source records attributed to Strobel, M..

13 recordsLinked to original sources

bioRxiv2026

The Evolving Bileome: A Pan-Repository Landscape of Expanded Bile Acid and Related Steroidal Signatures

Bile acids and related steroidal metabolites are among the most studied biomolecules, yet recent work has revealed far greater structural diversity than previously recognized, much of it shaped by the microbiome. We previously introduced a repository-scale bile acid MS/MS library built from queries targeting C24 bile acid fragmentation, limited to Orbitrap Q Exactive datasets within GNPS/MassIVE. Here we announce a major expansion of this library: a bile acid and steroidal MS/MS spectral library assembled across three major metabolomics repositories, now capturing C23, C24 (including alkamine), C26 (C-C bonded aceto derivatives), and C27 bile acids, as well as C28 bile alcohols. The expanded libraries comprise 640,141 unique MS/MS spectra, of which 120,293 (18.8%) match 2,529 reference spectra, leaving most of this steroidal chemical space structurally unassigned. Linked to harmonized pan-repository metadata, the library provides a starting point for classifying MS/MS spectra as likely bile acids or related steroids, with two example analyses illustrated here. This resource allows researchers to flag candidate bile acid and steroidal signatures in their own data for further characterization.

bioinformatics↗

bioRxiv2026

mzQC: a versatile way to communicate quality information for biological mass spectrometry

Reliable quality control (QC) is essential for reproducible biological mass spectrometry, yet QC information is still typically stored in tool-specific, poorly interoperable formats that hinder comparison, reuse, and transparent reporting. We present mzQC, a community-developed standard from the HUPO Proteomics Standards Initiative for the compact, machine-readable representation of QC metrics and their associated metadata across mass spectrometry workflows. mzQC is implemented in JSON, organized to support both individual mass spectrometry acquisitions and collections thereof, with formal QC metrics definitions supported by controlled vocabularies to ensure unambiguous metric interpretation and semantic consistency. The format is supported by validation tools and reference libraries in Python, R, and Java, facilitating integration into existing software ecosystems. We demonstrate the utility of mzQC across diverse analytical modalities and QC settings, spanning longitudinal instrument monitoring, acquisition-method evaluation, study-level quality assessment, repository-scale data characterization, and spatially resolved mass spectrometry imaging. Together, these use cases show that mzQC provides not merely a file format, but a shared foundation for interoperable QC reporting, large-scale data assessment, and more rigorous, reproducible, and reusable mass spectrometry-based research.

bioinformatics↗

bioRxiv2026

Widespread detection of Polyethylene glycol reveals chronic human exposure through pharmaceutical drugs

Polyethylene glycol (PEG) is a synthetic polymer ubiquitous in pharmaceuticals, personal care products, food additives, and industrial manufacturing. Despite its widespread use and potential importance as an exposure chemical, the prevalence of PEG exposure and its excretion in human populations remain largely uncharacterized. Moreover, PEG detected in human biofluids is frequently assumed to arise from analytical contamination during sample preparation, potentially obscuring its contribution to the human exposome and confounding metabolic phenotyping studies. Here, we show that PEG is as component of the human xenobiotic exposome and is further metabolized into PEG hydoxy acid and diacid metabolites in humans. We further find that PEG exposure is associated with alterations in microbiome composition and short-chain fatty acid metabolism, suggesting its biological impact of its exposure. We identify PEG exposure in approximately 2.3% of publicly available metabolomics data files and provide a reusable 85,484 candidate PEG and PEGylated MS/MS spectral library for future use for the metabolomic community. Together, these findings establish PEG signal in human biofluids can reflect genuine exposure, and that PEG exposure is neither metabolically inert nor biologically silent.

biochemistry↗

bioRxiv2026

The Everything Bagel Feature Finder: Ultra-fast automated feature finding for untargeted metabolomics

Metabolomics studies are increasingly being applied with hundreds to thousands, even tens of thousands of samples that demand rapid, automated data processing while maintaining analytical sensitivity or quantitative accuracy. A major computational bottleneck is feature finding, which is the transformation of LC-MS and LC-MS/MS data into a set of analyte signals aligned and quantified across samples. Feature finding can be computationally intensive and often requires manual iterative parameter optimization. To accelerate this process, we present the Everything Bagel (EB) feature finder, an ultra-fast automated feature finding tool that integrates feature detection, retention-time alignment, and gap filling designed for run-time and memory efficiency. We benchmarked EB against two automated feature finding methods on eight benchmarking datasets. Specifically, we evaluated these three feature finding methods by measuring spike-in standard detection coverage, dilution series quantification accuracy, and yeast 12C/13C credentialed features. In this evaluation, the EB feature finder achieved performance comparable to, and often exceeding, existing methods while requiring up to 150-fold lower CPU hours and up to 113-fold lower wall time. We further demonstrated the bioanalytical validity of EB by reanalyzing published datasets used for biomarker discovery and reproduced biologically significant features that matched the published findings using manually tuned feature finding settings. Taken along with the speed improvements, we anticipate EB will enhance the ability to automatically analyze datasets with thousands to tens of thousands of samples for the community.

bioinformatics↗

bioRxiv2026

M-CSF stimulated alveolar macrophages safeguard from invasive aspergillosis

Invasive pulmonary aspergillosis (IPA) is a life-threatening complication in immunocompromised individuals, including recipients of allogeneic hematopoietic cell transplantation (allo-HCT). While systemic neutropenia is traditionally considered the primary risk factor for IPA, we demonstrate that tissue-resident alveolar macrophages (AMs), rather than recruited neutrophils, dictate survival during the critical early window after transplantation. Utilizing an ultra-low dose Aspergillus fumigatus infection model that mimics physiological exposure, we identify alveolar macrophages (AMs) as key players in pulmonary antifungal defense. In immunocompromised mice, AMs conferred protection against lethal invasive aspergillosis by day 6, but not day 4 post-allo-HCT. To enhance AM function at the earlier time point, we tested cytokine-based interventions and show that M-CSF, but not IL-34, which both bind to the CSF-1 receptor, promotes migratory activity, phagolysosomal function and fungal killing in both mouse and human primary tissue-resident AMs. In allo-HCT recipient mice, M-CSF treatment preserved lung tissue integrity, suppressed pro-inflammatory cytokines, and protected mice from lethal invasive aspergillosis. The M-CSF-driven protective effect was abrogated upon AM depletion. Our findings demonstrate a critical role of tissue-resident AMs in pulmonary antifungal immunity and suggest that therapeutic modulation of AM activity via M-CSF may offer a promising strategy to combat severe fungal infections in immunocompromised patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/736478v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@49ba37org.highwire.dtl.DTLVardef@607c4forg.highwire.dtl.DTLVardef@814894org.highwire.dtl.DTLVardef@1c413c9_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

MALDI Tandem Mass Spectrometry for Colony-Based Dereplication of Natural Products

Microbial libraries remain an important resource for natural product discovery; however, constructing taxonomically and chemically diverse collections remains a challenge. Advances in dereplication strategies, including molecular networking, have reduced the rediscovery of known bioactive molecules and facilitated the identification of novel chemical scaffolds, but these approaches are typically applied after library construction or to existing repositories. Furthermore, many dereplication workflows require scaled fermentation and extraction, increasing the time needed to assess a microbes metabolite profile. Here, we integrate matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) into the bioinformatics platform IDBac, enabling streamlined characterization of microbial taxonomic identity, metabolite production potential, and preliminary metabolite annotation through GNPS2 molecular networking. This miniaturized high-content workflow facilitates strain prioritization by providing metabolite annotations directly from single microbial colonies prior to scale-up and extraction. Application of this approach to marine actinomycetes enabled the annotation of lavanducyanin and multiple napyradiomycin analogs. Subsequent investigation led to the discovery of napyradiomycin B8 from marine Streptomyces sp. CNZ-289, which was confirmed by 1D and 2D NMR spectroscopy and MALDI-MS/MS. Expanding this workflow to an untargeted analysis of 25 commensal marine vertebrate-derived bacterial isolates resulted in the annotation of several known bioactive natural products, including surugamides, antimycins, desferrioxamine siderophores, and the isolation and elucidation of harmane derivatives using NMR. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/733640v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@c92cfforg.highwire.dtl.DTLVardef@1a9522borg.highwire.dtl.DTLVardef@151b309org.highwire.dtl.DTLVardef@c1531f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Predicting Discrete Structural Transformations in Small Molecules from Tandem Mass Spectrometry

Tandem mass spectrometry (MS/MS) fragments molecules into smaller pieces, generating spectra composed of m/z values and intensities that encode structural information for molecular annotation. With increasing mass spectrometry data acquisition speeds, manual annotation from MS/MS lags far behind data generation and remains a bottleneck in metabolite annotation. Current computational methods, such as molecular networking, address this challenge by organizing similar structures into families of related compounds. However, they generally provide only similarity scores, offering weak actionable insights for structural annotation. To address this limitation, we present the Molecular Transformation Graph Edit Measure (MT-GEM), a distance metric that quantifies discrete structural transformations between molecules through graph edge removals that approximate structural modifications. Building on this metric, we developed an ensemble machine learning architecture, the Spectrum Transformation Edit Predictor (STEP), that builds upon TransExION and DREAMS to predict MT-GEM distances from MS/MS spectra. STEP achieves an average precision of 48.4% for identifying single structural transformations between MS/MS pairs, representing more than a tenfold improvement over state-of-the-art similarity metrics, including spectral entropy similarity (3.8%) and modified cosine (2.5%). On experimental human gut microbial community data, STEP identifies 3 times more single-transformation metabolite pairs than feature-based molecular networking at equivalent precision. In a discovery application, STEP highlights one drug metabolite and two new natural product analogs missed by modified cosine in feature-based molecular networking. By providing discrete transformation predictions rather than continuous similarity scores, MT-GEM and STEP enable hypothesis-driven metabolite annotation with testable structural modifications, which we envision will accelerate discovery of new molecules from MS/MS metabolomics datasets.

bioinformatics↗

bioRxiv2025

IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry.

The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, current platforms lack meaningful ways to compare multiple properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

microbiology↗

bioRxiv2024

ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization

Untargeted tandem mass spectrometry (MS/MS) has become a high-throughput method to measure small molecules in complex samples. One key goal is the transformation of these MS/MS spectra into chemical structures. Computational techniques such as MS/MS library search have enabled the re-identification of known compounds. Analog library search and molecular networking extend this identification to unknown compounds. While there have been advancements in metrics for the similarity of MS/MS spectra of structurally similar compounds, there is still a lack of automated methods to provide site specific information about structural modifications. Here we introduce ModiFinder that leverages the alignment of peaks in MS/MS spectra between structurally related known and unknown small molecules. Specifically, ModiFinder focuses on shifted MS/MS fragment peaks in the MS/MS alignment. These shifted peaks putatively represent substructures of the known molecule that contain the site of the modification. ModiFinder synthesizes these information together and scores the likelihood for each atom in the known molecule to be the modification site. We demonstrate in this manuscript how ModiFinder can effectively localize modifications which extends the capabilities of MS/MS analog searching and molecular networking to accelerate the discovery of novel compounds.

bioinformatics↗

bioRxiv2023

Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention

Identifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery but remains a difficult task where most campaigns rely on a priori knowledge of binding sites from experiments. Here we present a binding site prediction method called Graph Attention Site Prediction (GrASP) and re-evaluate assumptions in nearly every step in the site prediction workflow from dataset preparation to model evaluation. GrASP is able to achieve state-of-the-art performance at recovering binding sites in PDB structures while maintaining a high degree of precision which will minimize wasted computation in downstream tasks such as docking and free energy perturbation.

biophysics↗

bioRxiv2019

Acid-Sensing Ion Channels Mediate Type III Adenylyl Cyclase-Independent Acid-Sensing of Mouse Olfactory Sensory Neurons

Acids can disturb the ecosystem of wild animals through altering their olfaction and olfaction-related survival behaviors. It is known that the main olfactory epithelia (MOE) of mammals rely on odorant receptors and type III adenylyl cyclase (AC3) to detect general odorants. However, it is unknown how the olfactory system sense protons or acidic odorants. Here we show that the mouse MOE responded to acidic volatile stimuli in the presence and the absence of AC3. Acetic acid-induced electro-olfactogram (EOG) responses in wild type (WT) MOE can be dissected into two components: one dependent on the AC3-mediated cAMP pathway and the other not. MOE of AC3 knockout (KO) mice retained an acid-evoked EOG response but failed to respond to an odor mix. The acid-evoked responses of the AC3 KO could be blocked by diminazene, an inhibitor of acid-sensing ion channels (ASICs), but not by forskolin/IBMX, which desensitize the cAMP pathway. AC3 KO mice lost their sensitivity to detect pungent odorants but maintained sniffing behavior to acetic acid. Immunofluorescence staining demonstrated that ASIC1 proteins were highly expressed in olfactory sensory neurons (OSNs), mostly enriched in the knobs, dendrites, and somata, but not in olfactory cilia. Moreover, mice exhibited reduced preference to attractive objects when placed in an environment with acidic volatiles. Together, we conclude that the mouse olfactory system has a non-conventional, ASICs-mediated mechanism for acid-sensing. Acid stimulation of ASICs may unselectively depolarize different OSNs and interfere with the anatomical logic for odor perception.

neuroscience↗

bioRxiv2019

3D light sheet fluorescence microscopy of lungs to dissect local host immune - Aspergillus fumigatus interactions

Aspergillus fumigatus is an opportunistic fungal pathogen that can cause life-threatening invasive lung infections in immunodeficient patients. The cellular and molecular processes of infection during onset, establishment and progression are highly complex and depend on both fungal attributes and the immune status of the host. Therefore, preclinical animal models are paramount to investigate and gain better insight into the infection process. Yet, despite their extensive use, commonly employed murine models of invasive pulmonary aspergillosis are not well understood due to analytical limitations. Here we present quantitative light sheet fluorescence microscopy (LSFM) to describe fungal growth and the local immune response in whole lungs at cellular resolution within its anatomical context. We analyzed three very common murine models of pulmonary aspergillosis based on immunosuppression with corticosteroids, chemotherapy-induced leukopenia or myeloablative irradiation. LSFM uncovered distinct architectures of fungal growth and degrees of tissue invasion in each model. Furthermore, LSFM revealed the spatial distribution, interaction and activation of two key immune cell populations in antifungal defense: alveolar macrophages and polymorphonuclear neutrophils. Interestingly, the patterns of fungal growth correlated with the detected effects of the immunosuppressive regimens on the local immune cell populations. Moreover, LSFM demonstrates that the commonly used intranasal route of spore administration did not result in the desired intra-alveolar deposition, as more than 60% of fungal growth occurred outside of the alveolar space. Hence, LSFM allows for more rigorous characterization of murine models of invasive pulmonary aspergillosis and pinpointing their strengths and limitations.\n\nIMPORTANCEThe use of animal models of infection is essential to advance our understanding of complex host-pathogen interactions that take place during Aspergillus fumigatus lung infections. As in the case of humans, mice need to be immunosuppressed to become susceptible to invasive pulmonary aspergillosis, the most serious infection caused by A. fumigatus. There are several immunosuppressive regimens that are routinely used to investigate fungal growth and/or immune responses in murine models of invasive pulmonary aspergillosis (IPA). However, the precise consequences that each immunosuppressive model has on the local immune populations and for fungal growth are not completely understood. Here we employed light sheet fluorescence microscopy (LSFM) to analyze whole lungs at cellular resolution, to pin down the scenario commonly used IPA models. Our results will be valuable to optimize and refine animal models to maximize their use in future research.\n\nVISUAL ABSTRACTQuantitative light sheet fluorescence microscopy to dissect local host-pathogen interactions in the lung after A. fumigatus airway infection.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC=\"FIGDIR/small/661157v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (42K):\norg.highwire.dtl.DTLVardef@4baf31org.highwire.dtl.DTLVardef@dad3c3org.highwire.dtl.DTLVardef@84aab9org.highwire.dtl.DTLVardef@1e45c0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2018

Developmental genetics of corolla tube formation: role of the tasiRNA-ARF pathway

More than 80,000 angiosperm species produce flowers with petals fused into a corolla tube. As an important element of the tremendous diversity of flower morphology, the corolla tube plays a critical role in many specialized interactions between plants and animal pollinators (e.g., beeflies, hawkmoths, hummingbirds, nectar bats), which in turn drives rapid plant speciation. Despite its clear significance in plant reproduction and evolution, the corolla tube remains one of the least understood plant structures from a developmental genetics perspective. Through mutant analyses and transgenic experiments, here we show that the tasiRNA-ARF pathway is required for corolla tube formation in the monkeyflower species Mimulus lewisii. Loss-of-function mutations in the M. lewisii orthologs of ARGONAUTE7 and SUPPRESSOR OF GENE SILENCING 3 cause a dramatic decrease in abundance of TAS3-derived small RNAs and a moderate up-regulation of AUXIN RESPONSE FACTOR 3 (ARF3) and ARF4, which lead to inhibition of lateral expansion of the bases of petal primordia and complete arrest of the upward growth of the inter-primordial regions, resulting in unfused corollas. By using an auxin reporter construct, we discovered that auxin distribution is continuous along the petal primordium base and the inter-primordial region during the critical stage of corolla tube formation in the wild-type, and that this auxin distribution is much weaker and more restricted in the mutant. Together, these results suggest a new conceptual model highlighting the central role of auxin directed synchronized growth of the petal primordium base and the inter-primordial region in corolla tube formation.

plant biology↗