Biology subjects

Lin, V. S.

Publications and source records attributed to Lin, V. S..

7 recordsLinked to original sources

bioRxiv2026

Carbon starvation of Mycobacterium abscessus induces a non-replicating state with extensive proteomic remodeling

Mycobacterium abscessus (Mab) is an opportunistic pathogen that can cause chronic, debilitating lung disease. Mab is intrinsically resistant to most antibiotics, making Mab infections challenging to manage and frequently incurable. During infection, Mab adapts to survive various stresses, including hypoxia and nutrient starvation. In vitro, these conditions drive Mab into a drug-tolerant, non-replicating state. Changes in the Mab proteome that result from entering a non-replicating state have been minimally described despite the clinical importance of this physiological state. Using Mab reference strain ATCC 19977, we collected proteomic data comparing replicating to non-replicating states using a carbon starvation (CS) model of persistence. We identified 2251 proteins overall (46% proteome coverage), and 17% of these proteins were found in only one of the two conditions. A third of identified proteins were significantly changed in abundance, indicating an extensive proteomic response to CS. The response regulator DosR and many DosRS responsive proteins were significantly more abundant under CS, suggesting that the DosRS stress response regulator plays a key role in CS-induced Mab persistence. Many aspects of cell wall biosynthesis were changed, including changes in glycolipid abundance under CS. Proteins involved in other key cellular processes such as secretion, oxidative phosphorylation, and nutrient metabolism were altered under CS. The proteomic analysis presented provides new insights and clarity into how the Mab proteome is regulated during non-replicating persistence, a key consideration for understanding Mab pathophysiology.

microbiology↗

bioRxiv2026

Reference-free compound identification using computational prediction of molecular properties and multi-dimensional spectrometric measurements: a fentanyl case study

Mass spectrometry is used to identify chemicals to which humans are exposed, but it cannot directly determine molecular structures. Instead, structures are inferred by matching experimental spectra to libraries of spectra constructed from analyses of pure reference compounds. However, the chemical space of human exposures far exceeds the amount of experimental library spectra. Here, we evaluate a reference-free strategy for confident identification of unknown molecules. Using fentanyl as a case study, we created a suspect library of over 1 billion computationally predicted fentanyl analogs and predicted molecular properties through machine learning, molecular dynamics, and density functional theory. Multi-dimensional spectra from a blinded analysis of a mock fentanyl tablet were matched with the predicted library, yielding an average of three candidate structures per measured analog, with six exact identifications. This work emphasizes the promise of reference-free molecular measurements for assessing human exposure by merging computational predictions with high-dimensional measurements.

scientific communication and education↗

bioRxiv2025

Chemoproteomic elucidation of β-lactam drug targets in Mycobacterium abscessus

The pathogen Mycobacterium abscessus (Mab) can cause severe and difficult to treat chronic lung infections. Despite the rising incidence and clinical concern of Mab infections, treatment options are limited and often ineffective. Treatment is complicated by Mabs ability to persist in a non-replicative, drug-resistant state. Several {beta}-lactam antibiotics are potently bactericidal against Mab but are underutilized because their molecular mechanisms of action against Mab are incompletely understood. In the current study, we used {beta}-lactam-derived activity-based probes and chemoproteomics to report the first comprehensive list of enzymes in Mab targeted by {beta}-lactams. We compared {beta}-lactam targets across two Mab subspecies in actively replicating and non-replicative cultures, using a new carbon starvation model of persistence. We identified 17 targets that were active in every condition tested, seven of which were previously unknown to bind {beta}-lactams. Lastly, we characterized the {beta}-lactamase activity and {beta}-lactam inhibition profiles of nine Mab enzymes, demonstrating that imipenem inhibits these targets more effectively than cefoxitin. These findings provide clarity on the mechanisms of action of clinically relevant {beta}-lactams in Mab, a crucial step toward fully realizing their potential for treating infections caused by this opportunistic pathogen.

microbiology↗

bioRxiv2025

Thermodynamic Modeling of mRNA with the Addition of Precipitants

Nucleic acid therapeutics (NATs) have recently emerged as an exciting therapeutic modality for a range of indications, most notably as vaccines for SARS-CoV-2. In many cases, the thermodynamics of a system containing nucleic acids (such as in the downstream purification of mRNA from solution or within the lipid nanoparticle) can significantly influence the properties and efficacy of that system. Consequently, an accurate thermodynamic description of the system is essential for understanding and optimizing that system. In this work, the SAFT-{gamma} Mie equation of state was used to predictively model mRNA solubility. Experimental measurements of the solubility of two different mRNA sequences in various conditions (namely choice of precipitant(s), precipitant concentration, and temperature) were obtained and used to validate the model. Not only was the thermodynamic model able to quantitatively predict the solubility of mRNA in solution under different conditions, it was also able to yield mechanistic insight into the factor driving precipitation, namely the disruption of water-mRNA hydrogen bonding. The developed model can be extended to other mRNA sequences in a range of conditions beyond the experimental data presented in this work.

biophysics↗

bioRxiv2025

Activity-targeted metaproteomics enhances the ecophysiological characterization of cryptic syntrophic metabolisms

Syntrophic microbial consortia can contribute significantly to the activity and function of anoxic ecosystems, yet are often too rare to study their in situ physiologies using traditional molecular methods. Here, we combined bioorthogonal non-canonical amino acid tagging (BONCAT), stable isotope probing, and metaproteomics to improve the recovery of proteins from active members and track isotope incorporation in an anaerobic digestion community. Both click chemistry-enabled cell-sorting and direct protein pulldown coupled to metaproteomics improved recovery of isotopically labeled proteins during anaerobic acetate oxidation. Resulting labeled protein expression profiles revealed elevated activity of a rare and so-far uncharacterized syntrophic bacterium belonging to the family Natronincolaceae. BONCAT-based capture of newly translated proteins provided direct molecular evidence for the expression of a previously hypothesized oxidative glycine pathway for syntrophic acetate oxidation by this microorganism, showcasing the potential of targeted metaproteomics to characterize rare and active cells central to community metabolism in natural and engineered ecosystems.

microbiology↗

bioRxiv2025

Discovery of non-opioid receptor protein targets of fentanyl across tissues from animal models and humans using photoaffinity probes

Synthetic opioids such as fentanyl and related analogs have been widely used for pain management. However, their negative side effects, including respiratory depression and high potential for addiction, underscore the need for a deeper understanding of fentanyls interactions with proteins throughout the human body. Fentanyl analogs bind and activate opioid receptors in the central and peripheral nervous systems, triggering numerous downstream signaling pathways. Increasingly, fentanyl has been shown to interact with non-opioid receptors, and elucidation of these non-canonical fentanyl-protein interactions may provide insights into the mechanisms contributing to fentanyls adverse effects and illuminate novel countermeasure strategies. To identify proteins in mammalian tissues that may interact with fentanyl, we designed and synthesized three affinity-based probes (AfBPs) that include the fentanyl core and feature a diazirine photoaffinity group and alkyne handle for click chemistry at different positions. Molecular docking simulations predicted that these AfBPs bind the mu opioid receptor similarly to fentanyl. Affinity-based protein profiling using the FA-T1 probe in vitro in tissues from six animal species identified histamine N-methyltransferase (HNMT), endophilin-B1 (SH3GLB1), fructosamine-3-kinase (FN3K), cutA divalent cation tolerance analog (CUTA), and monoamine oxidase B (MAOB) among the top proteins that bind fentanyl in multiple species and tissue types. Molecular docking of fentanyl and remifentanil with these protein structures identified putative binding sites. The interaction of fentanyl with specific proteins was empirically assessed through protein structural analyses. These findings highlight potential fentanyl-protein interactions that may contribute to the acute and long-term impacts of fentanyl exposures.

pharmacology and toxicology↗

bioRxiv2023

Profiling sorghum-microbe interactions with a specialized photoaffinity probe identifies key sorgoleone binders in Acinetobacter pittii

Sorghum (Sorghum bicolor) is a major food and bioenergy grass species cultivated worldwide. To promote more robust and sustainable growth of this important crop, we need a deeper understanding of the plant-microbe interactions between sorghum and soil microbial communities that benefit plant host resiliency and enhance nutrient acquisition. The release of specific metabolites from plant roots, or root exudation, drives these plant-microbe interactions, but the molecular pathways by which root exudates shape the sorghum rhizosphere microbiome require further elucidation. To investigate these complex interkingdom interactions in the sorghum rhizosphere, we developed a photoaffinity probe based on sorgoleone, a hydrophobic secondary metabolite and allelochemical produced in sorghum seedling root exudates. Here, we apply a new synthetic sorgoleone diazirine alkyne photoaffinity probe (SoDA-PAL) to the identification of sorgoleone-binding proteins in Acinetobacter pittii SO1, a potential plant growth promoting microbe derived from Sorghum bicolor rhizosphere soil. Competitive photoaffinity labeling of A. pittii whole cell lysates with SoDA-PAL identified 137 statistically enriched proteins that were complementary to a previously identified gene cluster involved in sorgoleone catabolism. Proteins identified by SoDA-PAL included a select set of putative transporters, transcription regulators, and a subset of proteins with lipid and secondary metabolic activities. We confirm binding of SoDA-PAL to a putative hydrolase in the /{beta} fold family (OH685_09420) through structural bioinformatics and in-vitro recombinant protein analysis. This photoaffinity labeling approach using metabolite-based probes can be extended in the future to proteomic profiling of complex rhizosphere microbiomes to discover genes that can be leveraged to promote beneficial plant-microbe interactions. ImportanceHere we demonstrate a photoaffinity-based chemical probe modeled after sorgoleone, a known secondary metabolite released from the roots of sorghum, can be used to dissect complicated plant-microbe interactions. Applying this probe to the sorghum-associated bacterium Acinetobacter pittii identified diverse proteins that directly interact with sorgoleone. We show that probe labeling is dose-dependent and is sensitive to competition with purified sorgoleone, demonstrating the probe is selective for protein targets that directly interact with sorgoleone. By using the probe to broadly profile proteins that interact with sorgoleone, we identified bacterial catabolic pathways, unintuitive transcriptional regulation pathways, and vital exchange mechanisms involving transporters that may be involved in sorgoleone utilization and cellular response toward this plant metabolite. We envision that this workflow will expand our understanding of the sorghum root exudate interactome and elucidate the molecular mechanisms by which specific metabolites shape the sorghum rhizosphere microbiome.

biochemistry↗