Affinity-based protein profiling (AfBPP) allows us to identify target proteins that bind drugs or other small molecules of interest in complex samples. As an enrichment technique, label-free AfBPP often generates data with high missingness, particularly in negative control samples. We developed an R package, chemoprotR, which enables both quantitative and qualitative statistical analyses of chemoproteomic data, and applied it to the identification of specific benzodiazepine drug targets in the brain. Benzodiazepines comprise a class of drugs that affect GABAA receptors through positive allosteric modulation, but benzodiazepine interactions with other proteins are not fully understood. To this end, we synthesized benzodiazepine affinity-based probes (AfBPs) and applied them to rat brain synaptosomes. Our benzodiazepine AfBPs identified GABAA receptor subunits and other proteins with ion channel functions. Across the three probes, there was minimal overlap in protein targets identified by competitive labeling with flurazepam, and FR-DA, the probe based on flurazepam, yielded more significant protein targets than the probes based on flunitrazepam. These results demonstrate the ability of benzodiazepine AfBPs to identify protein targets when used with an authentic benzodiazepine to compete for binding sites and highlight the utility of combined statistical analyses for the interpretation of presence-absence data in AfBPP data sets.

[This corrects the article DOI: 10.1371/journal.pone.0250586.].

Infections with Mycobacterium tuberculosis (Mtb) cause tuberculosis (TB), which requires at least 6 months of treatment with multiple antibiotics. There is emergent interest in using β-lactam antibiotics to improve treatment outcomes for patients. These drugs target cell wall biosynthesis, but a comprehensive list of enzymes inhibited by β-lactams in Mtb is lacking. In the current study, we sought to identify and characterize Mtb enzymes inhibited by β-lactam antibiotics using physiological conditions representative of both acute and chronic TB disease. We used new activity-based probes based on the β-lactam antibiotic meropenem due to its approval by the World Health Organization for TB treatment. Activity-based probes label enzymes based on both substrate specificity and catalytic mechanism, enabling precise identification of drug targets. We identified previously undiscovered targets of meropenem in addition to known cell wall biosynthetic enzymes. We validated β-lactam binding and hydrolysis for six newly identified targets: Rv1723, Rv2257c, Rv0309, DapE (Rv1202), MurI (Rv1338), and LipD (Rv1923). Our results demonstrate that there are at least 30 enzymes in Mtb vulnerable to inhibition by meropenem. This is many more β-lactam targets than historically described, suggesting that efficacy in Mtb is a direct result of polypharmacology.

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 fentanyl's 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 fentanyl's 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. ### Competing Interest Statement The authors have declared no competing interest.

Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses chemical probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across various biological systems and treatments, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern, a wide range of concentrations may be needed, particularly for chemicals that may lack toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity differentiation across a wide range of concentrations for the model organophosphate (OP), paraoxon. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving discrete samples at various paraoxon concentrations with pooling of samples across that same concentration range. The results show that small vs. large differences in integral intensities for the competitive sample can be used to distinguish low vs. high sensitivity proteins, respectively, without increasing the overall number of samples. We envision the integral ABPP method will provides a means to screen diverse chemicals more rapidly to identify both highly sensitive and less sensitive protein targets.

Glutathione transferases (GSTs) represent a large and diverse enzyme family involved in the detoxification of small molecules by glutathione conjugation in crops, weeds and model plants. In this study, we introduce an easy and quick assay for photoaffinity labeling of GSTs to study GSTs globally in various plant species. The small-molecule probe contains glutathione, a photoreactive group and a minitag for coupling to reporter tags via click chemistry. Under UV irradiation, this probe quickly and robustly labels GSTs in crude protein extracts of different plant species. Purification and mass spectrometry (MS) analysis of labeled proteins from Arabidopsis identified 10 enriched GSTs from the Phi(F) and Tau(U) classes. Photoaffinity labeling of GSTs demonstrated GST induction in wheat seedlings upon treatment with safeners and in Arabidopsis leaves upon infection with avirulent bacteria. Treatment of Arabidopsis with salicylic acid (SA) analog benzothiadiazole (BTH) induces GST labeling independent of NPR1, the master regulator of SA. Six Phi- and Tau-class GSTs that are induced upon BTH treatment were identified, and their labeling was confirmed upon transient overexpression. These data demonstrate that GST photoaffinity labeling is a useful approach to studying GST induction in crude extracts of different plant species upon different types of stress.

A growing body of literature has linked early-life exposures to polycyclic aromatic hydrocarbons (PAH) with adverse neurodevelopmental effects. Once in the body, metabolism serves as a powerful mediator of PAH toxicity by bioactivating and detoxifying PAH metabolites. Since enzyme expression and activity vary considerably throughout human development, we evaluated infant metabolism of PAHs as a potential contributing factor to PAH susceptibility. We measured and compared rates of phenanthrene and retene (two primary PAH constituents of woodsmoke) metabolism in human hepatic microsomes from individuals ≤21 months of age to a pooled sample (n = 200) consisting primarily of adults. We used activity-based protein profiling (ABPP) to characterize cytochrome P450 enzymes (CYPs) in the same hepatic microsome samples. Once incubated in microsomes, phenanthrene demonstrated rapid depletion. Best-fit models for phenanthrene metabolism demonstrated either 1 or 2 phases, depending on the sample, indicating that multiple enzymes could metabolize phenanthrene. We observed no statistically significant differences in phenanthrene metabolism as a function of age, although samples from the youngest individuals had the slowest phenanthrene metabolism rates. We observed slower rates of retene metabolism compared with phenanthrene also in multiple phases. Rates of retene metabolism increased in an age-dependent manner until adult (pooled) metabolism rates were achieved at ∼12 months. ABPP identified 28 unique CYPs among all samples, and we observed lower amounts of active CYPs in individuals ≤21 months of age compared to the pooled sample. Phenanthrene metabolism correlated to CYPs 1A1, 1A2, 2C8, 4A22, 3A4, and 3A43 and retene metabolism correlated to CYPs 1A1, 1A2, and 2C8 measured by ABPP and vendor-supplied substrate marker activities. These results will aid efforts to determine human health risk and susceptibility to PAHs exposure during early life.

Eukaryotes produce a large number of cytochrome P450s that mediate the synthesis and degradation of diverse endogenous and exogenous metabolites. Yet, most of these P450s are uncharacterized and global tools to study these challenging, membrane-resident enzymes remain to be exploited. Here, we applied activity profiling of plant, mouse and fungal P450s with chemical probes that become reactive when oxidized by P450 enzymes. Identification by mass spectrometry revealed labeling of a wide range of active P450s, including six plant P450s, 40 mouse P450s and 13 P450s of the fungal wheat pathogen Zymoseptoria tritici. We next used transient expression of GFP-tagged P450s by agroinfiltration to show ER-targeting and NADPH-dependent, activity-based labeling of plant, mouse and fungal P450s. Both global profiling and transient expression can be used to detect a broad range of active P450s to study e.g. their regulation and discover selective inhibitors.

Chitin is an insoluble and ubiquitous soil biopolymer, estimated to be the second most abundant organic soil biopolymer on Earth. Despite its abundance, role as a source of C and N in soil, and importance to ecosystem function, further research is required to elucidate key controls on chitin breakdown under varying environmental conditions. Previous work highlights the important role rhizosphere microbiomes and root exudates can play in chitin catabolism. To enable mapping of chitinase activity within the highly heterogeneous and spatially organized rhizosphere, we designed and synthesized an enzymatically activated fluorogenic substrate, chitotriose-TokyoGreen (chitotriose-TG), by incorporating a fluorescein derivative (TG) onto the trimeric unit of chitin. This non-fluorescent substrate is selectively hydrolyzed by chitinase to release TG and yield a fluorescence signal, which can be used to spatially image and measure chitinase activity in the rhizosphere. To demonstrate the application of this technique, we grew switchgrass (Panicum virgatum) in rhizoboxes amended with a horizontal layer supplemented with chitin. We extracted mobile proteins from the rhizobox using a nitrocellulose membrane blotting technique which offers non-destructive enzyme extraction while preserving the 2D spatial position of the enzymes. We then subjected these membranes to the synthesized chitotriose-TG stain to spatially visualize the distribution of chitinase activity within the rhizosphere. We observed increased chitinase activity near switchgrass roots and higher activity within the soil zone enriched in chitin, showing an adaptive response of chitinase production with spatial focusing in areas of higher chitin abundance. Thus, the enzyme extraction and visualization strategy we describe here can enhance efforts to better understand spatial controls on chitin breakdown in rhizosphere, further elucidating the role of chitin as a C and N source in these systems.

ABSTRACT The microbiome is an underappreciated contributor to intestinal drug metabolism with broad implications for drug efficacy and toxicity. While considerable progress has been made toward identifying the gut bacterial genes and enzymes involved, the role of environmental factors in shaping their activity remains poorly understood. Here, we focus on the gut bacterial reduction of azo bonds (R-N = N-R’), found in diverse chemicals in both food and drugs. Surprisingly, the canonical azoR gene in Escherichia coli was dispensable for azo bond reduction. Instead, azoreductase activity was controlled by the fumarate and nitrate reduction (fnr) regulator, consistent with a requirement for the anoxic conditions found within the gastrointestinal tract. Paired transcriptomic and proteomic analysis of the fnr regulon revealed that in addition to altering the expression of multiple reductases, FNR is necessary for the metabolism of L-Cysteine to hydrogen sulfide, enabling the degradation of azo bonds. Furthermore, we found that FNR indirectly regulates this process through the small noncoding regulatory RNA fnrS. Taken together, these results show how gut bacteria sense and respond to their intestinal environment to enable the metabolism of chemical groups found in both dietary and pharmaceutical compounds. IMPORTANCE This work has broad relevance due to the ubiquity of dyes containing azo bonds in food and drugs. We report that azo dyes can be degraded by human gut bacteria through both enzymatic and nonenzymatic mechanisms, even from a single gut bacterial species. Furthermore, we revealed that environmental factors, oxygen, and L-Cysteine control the ability of E. coli to degrade azo dyes due to their impacts on bacterial transcription and metabolism. These results open up new opportunities to manipulate the azoreductase activity of the gut microbiome through the manipulation of host diet, suggest that azoreductase potential may be altered in patients suffering from gastrointestinal disease, and highlight the importance of studying bacterial enzymes for drug metabolism in their natural cellular and ecological context.

ADVERTISEMENT RETURN TO ISSUEPREVEditorialNEXTCall for Papers: Special Issue on Chemical Biology Approaches for Investigating Toxicological MechanismsAaron T. Wright*Aaron T. WrightBiology, Baylor University, Baylor Science Building, One Bear Place, Waco, Texas 76798-7151, United States*[email protected]More by Aaron T. Wrighthttps://orcid.org/0000-0002-3172-5253 and Daniel K. NomuraDaniel K. NomuraUniversity of California Berkeley, 2151 Berkeley Way, Room 312G, Berkeley, California 94720, United StatesMore by Daniel K. Nomurahttps://orcid.org/0000-0003-1614-8360Cite this: Chem. Res. Toxicol. 2023, 36, 9, 1440Publication Date (Web):August 17, 2023Publication History Received7 August 2023Published online17 August 2023Published inissue 18 September 2023https://pubs.acs.org/doi/10.1021/acs.chemrestox.3c00235https://doi.org/10.1021/acs.chemrestox.3c00235editorialACS PublicationsCopyright © Published 2023 by American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views526Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (854 KB) Get e-AlertscloseSUBJECTS:Chemical biology,Chemoproteomics,Environmental pollution,Mechanisms of action,Small molecules Get e-Alerts

ABSTRACT Glutathione transferases (GSTs) represent a large and diverse enzyme family involved in detoxification of small molecules by glutathione conjugation in crops, weeds and model plants. Here, we introduce an easy and quick assay for photoaffinity labeling of GSTs to study global GST activation in various plant species. The small molecule probe contains glutathione, a photoreactive group, and a minitag for coupling to reporter tags via click chemistry. Under UV irradiation, this probe quickly and robustly labels GSTs in crude protein extracts. Enrichment and MS analysis of labeled proteins from Arabidopsis identified ten GSTs from the Phi(F) and Tau(U) classes. Photoaffinity labeling of GSTs demonstrated GST activation in wheat seedlings upon treatment with safeners, and in Arabidopsis leaves upon infection with avirulent bacteria. Photoaffinity labeling and proteomics identified six Phi- and Tau-class GSTs that are induced upon treatment with salicylic acid (SA) analog benzothiadiazole (BTH) and these were tested for enhancing immunity in disease assays. Our data confirm that BTH-induced GST activation is independent of NPR1, the master regulator of SA signaling.

Abstract Motivation The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families. Results Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes. Availability and implementation Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Multi-omic analyses can provide information on the potential for activity within a microbial community but often lack specificity to link functions to cell, primarily offer potential for function or rely on annotated databases. Functional assays are necessary for understanding in situ microbial activity to better describe and improve microbiome biology. Targeting enzyme activity through activity-based protein profiling enhances the accuracy of functional studies. Here, we introduce a pipeline of coupling activity-based probing with fluorescence-activated cell sorting, culturing, and downstream activity assays to isolate and examine viable populations of cells expressing a function of interest. We applied our approach to a soil microbiome using two activity-based probes to enrich for communities with elevated activity for lignocellulose-degradation phenotypes as determined by four fluorogenic kinetic assays. Our approach efficiently separated and identified microbial members with heightened activity for glycosyl hydrolases, and by expanding this workflow to various probes for other function, this process can be applied to unique phenotype targets of interest.

Host-associated and environmental microbiomes play central roles in human health, biogeochemical cycling, response to ecosystem change, and agriculture. Scientific approaches that can reveal the functional activities that contribute to observed phenotypes are needed in microbiome research. Broad characterization of the functional activity of microbes within microbiomes is currently hampered by approaches that rely on inference of function from metagenomes or indirect measurements. Activity-based protein profiling is uniquely positioned to overcome these challenges and reveal the protein-level mechanisms associated with microbiome phenotypes. In this review we describe the progress made to date using ABPP in gut microbiome, plant-microbe interaction, and soil microbiome research, and suggest how ABPP data can be coupled with advanced computational methods to enable phenotype prediction and bioengineering of microbiomes for applied purposes.

Xanthohumol, the principle prenylflavonoid found in hops (Humulus lupulus) and a reported anti-inflammatory agent, has great potential for pharmaceutical interventions related to inflammatory disorders in the gut. A suite of probes was prepared from xanthohumol and its structural isomer isoxanthohumol to enable profiling of both protein affinity binding and catalytic enzyme reactivity. The regiochemistry of the reactive group on the probes was altered to reveal how probe structure dictates protein labeling, and which probes best emulate the natural flavonoids. Affinity- and activity-based probes were applied to Escherichia coli, and protein labeling was measured by chemoproteomics. Structurally dependent activity-based probe protein labeling demonstrates how subtle alterations in flavonoid structure and probe reactive groups can result in considerably different protein interactions. This work lays the groundwork to expand upon unexplored cellular activities related to xanthohumol interactions, metabolism, and anti-inflammatory mechanisms.