An Unbiased Chemical Proteomics Method Identifies FabI as the

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An Unbiased Chemical Proteomics Method Identifies FabI as the Primary Target of 6-OH-BDE-47 Hui Peng, Hongbo Guo, Oxana Pogoutse, Cuihong Wan, Lucas Z. Hu, Zuyao Ni, and Andrew Emili Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03541 • Publication Date (Web): 28 Sep 2016 Downloaded from http://pubs.acs.org on October 6, 2016

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An Unbiased Chemical Proteomics Method Identifies FabI as the

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Primary Target of 6-OH-BDE-47

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Hui Penga#, Hongbo Guoa#, Oxana Pogoutsea, Cuihong Wana, Lucas Z. Hua, b, Zuyao Nia,

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and Andrew Emilia, b,*

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a

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b

Department of Molecular Genetics, University of Toronto, Toronto, Ontario, M5S 1A8, Canada

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co-first author: H. Peng and H. Guo contributed equally to the work.

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Corresponding author: Andrew Emili, Donnelly Centre for Cellular and Biomolecular

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Research, University of Toronto, 160 College Street, Toronto, Ontario, Canada; Tel: 416-946-

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7281; Fax: 416-978-7437; e-mail: [email protected]

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, M5S 3E1, Canada

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ABSTRACT

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Determination of the physical interactions of environmental chemicals with cellular proteins is

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important for characterizing biological and toxic mechanism of action. Yet despite the discovery

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of numerous bioactive natural brominated compounds, such as hydroxylated polybrominated

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diphenyl ethers (OH-PBDEs), their corresponding protein targets remains largely unclear. Here,

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we reported a systematic and unbiased chemical proteomics assay (Target Identification by

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Ligand Stabilization, TILS) for target identification of bioactive molecules based on monitoring

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ligand-induced thermal stabilization. We first validated the broad applicability of this approach

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by identifying both known and unexpected proteins bound by diverse compounds (anti-cancer

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drugs, antibiotics). We then applied TILS to identify the bacterial target of 6-OH-BDE-47 as

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enoyl-acyl carrier protein reductase (FabI), an essential and widely-conserved enzyme. Using

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affinity pull-down and in vitro enzymatic assays, we confirmed the potent antibacterial activity

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of 6-OH-BDE-47 occurs via direct binding and inhibition of FabI. Conversely, over-expression

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of FabI rescued the growth inhibition of E. coli by 6-OH-BDE-47, validating it as the primary in

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vivo target. This study documents a chemical proteomics strategy for identifying the physical and

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functional targets of small molecules, and its potential high-throughput application to investigate

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the modes-of-action of environmental compounds.

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KEYWORDS: Thermal stability profiling; chemical proteomic screens; antibacterial compound;

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natural product; drug

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INTRODUCTION The growing number of chemicals introduced into commerce over the past several decades

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poses a great challenge to the traditional single-chemical risk assessment strategy.1, 2 Thus, to

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meet evolving regulatory needs, the U.S. Environmental Protection Agency (EPA) ToxCast

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Program has developed innovative approaches for screening and prioritization to facilitate rapid

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hazard assessments of chemicals.3, 4 Notably, in vitro high-throughput screening (HTS)

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assessments that incorporate both exposure and toxicity data have been paid particular attention.2,

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5

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are focused on phenotypic toxicity,5 whereas elucidating the precise protein targets of lead

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compounds remains a critical bottleneck. Consequently, the mechanism of action of most

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bioactive environmental chemicals remains unknown even when their phenotypic toxicities have

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been well documented.4

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Yet despite the growing interest in development of HTS assays, most of the current approaches

By identifying the proteins physically bound by a chemical, one can potentially elucidate

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biological mechanism and novel cellular pathways. For example, identification of the

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mammalian target of rapamycin (mTOR) as the cellular target of a potent natural product

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immunosuppressant isolated from Streptomyces revealed critical signaling pathways

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dysregulated in human diseases such as diabetes, obesity and certain cancers.6 Documenting

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variation in protein-ligand binding patterns can also explain the varied phenotypic responses (e.g.

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differential ligand sensitivities) of different individuals or species. For example, it is well known

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that the sequence variation of aryl hydrocarbon receptor (AhR) leads to specie-specific toxicity

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sensitivity to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) exposure.7-9

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To address these issues systematically, unbiased high-throughput methods are urgently

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needed to monitor the spectrum of protein-compound interactions so as to elucidate a compounds

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fundamental mechanism of action. Yet while chemical-genomics methods have been developed

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to assess the impact of chemicals on biological pathways,10 most existing approaches are limited

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to genetically tractable models or do not pinpoint the actual protein(s) physically contacted by a

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compound. Conversely, established chemical proteomics methods, such as activity based probe

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profiling,11 offer the potential to directly isolate proteins bound by a ligand,11 but typically

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require synthesis of suitable chemical probes bearing functional moieties or affinity tags which

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may perturb compound action. Hence, more effective, convenient and efficient chemical

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proteomics methods for proteome-wide target identification are warranted for the routine

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determination of the protein targets of small molecules under physiologically relevant conditions.

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Hydroxylated polybrominated diphenyl ethers (OH-PBDEs) are a class of prominent

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environmental pollutants. Previous studies have reported their occurrence in sediments, wild fish,

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as well as humans.12-14 It is well known that some OH-PBDEs (e.g., 6-OH-BDE-47) are naturally

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produced as secondary metabolites by marine microbes.15, 16 Besides OH-PBDEs, our group has

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identified more than 2,000 natural brominated compounds in environmental samples.17, 18

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Although it was postulated that these compounds may be important for environmental adaptation

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by microbes,19 to date, there is no previous experimental study reporting their putative protein

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targets and mechanism of antibiotic action.

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Here, we describe, validate and deploy an unbiased chemical proteomics assay – termed

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TILS (Target Identification by Ligand Stabilization) – based on isotope labeled quantitative mass

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spectrometric analysis of ligand concentration-dependent reductions in target precipitation after

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sample heating to identify the cellular protein targets bound by small molecules. We use this 4 ACS Paragon Plus Environment

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platform to identify and characterize enoyl-acyl carrier protein reductase (FabI), which is

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essential and widely-conserved, as the primary antimicrobial target of 6-OH-BDE-47.

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Materials and Methods

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Reagents and Recombinant Proteins. Chemicals including antibiotics, radicicol and MTX

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were from Sigma-Aldrich. 6-OH-BDE-47 was purchased from Wellington Laboratories. Stock

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solutions of the drugs (10mM) were prepared in DMSO and stored at -20oC, while working

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solutions were prepared fresh by dilution just prior to use. Cancer drugs were obtained from the

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Developmental Therapeutics Program (NTP) of the U.S. National Cancer Institute (NCI).

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Recombinant polyhistidine-tagged DHFR fusion protein was produced in E. coli BL21 (DE3)

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pLys cells using the Pst39-HIS-DHFR expression vector (courtesy of S. Tan). Sequencing grade

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trypsin (Roche Applied Science) and HPLC grade solvents (Fisher Scientific) were used for all

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mass spectrometry analyses.

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Preparation of Cell Lysates. E. coli and human whole cell lysates were prepared using HEPES

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buffer (10 mM HEPES, 100 mM NaCl, 0.2 mM EDTA, 10% glycerol, 0.5mM DTT and protease

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inhibitors cocktail (Sigma S8830, PH=7.4 ) as described previously.20 Soluble protein was

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separated from insoluble debris by centrifugation at 20,000 g for 30 min at 4oC and diluted by

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HEPES buffer (10 mM HEPES, 100 mM NaCl, PH=7.4) to the volume calculated based on

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200uL/sample. SILAC (stable isotope labeling with amino acids) labeling of HEK293 cells was

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performed essentially as described.21

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Ligand / heat Treatment and Sample Processing. After adding ligand (1% v/v in DMSO) or

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vehicle alone, protein mixtures were incubated at 4oC for 60 min to allow for target engagement, 5 ACS Paragon Plus Environment

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then aliquoted (200uL/sample) into separate 1.5 mL microcentrifuge tubes, followed by

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incubation at room temperature for an additional 30 min. Individual samples were then heated to

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a set final temperature (e.g. 55oC) at a rate of 2oC/min. Precipitates were recovered by

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centrifugation at 14,000g for 30 min at 4oC and washed twice using 200 µL of cold water, and

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dissolved in 50 µL of 8 M urea with vigorous shaking. Samples were then diluted with a 5-fold

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volume of digestion buffer (50 mM NH4HCO3, 1 mM CaCl2). For SILAC experiments, the

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control and drug samples were mixed together after heat shock and dilution. Protein samples

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were reduced with 5 mM TCEP for 60 min, carboxymethylated with 15 mM iodoacetamide in

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the dark at RT for 30 min, and digested overnight with trypsin (4µg) with gentle shaking.

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Digestion was terminated by adding formic acid to 1% (v/v). For dimethylabeling, C18 Toptips

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(Glygen: TT2C18.96) were used for peptide desalting and on column chemical labeling. Control

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and ligand treated protein peptide digests were labeled using isotopically native/light (CH2O) and

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heavy (13CD2O) formaldehyde, essentially as described.22 Heavy and light samples were mixed

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before MS analysis.

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Peptides mixtures were analyzed with a nanoLC- electrospray ion source (Proxeon)

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interfaced to an LTQ Orbitrap Velos hybrid instrument (ThermoFisher). Raw MS files were

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processed by MaxQuant (version 1.3. 0. 5).23 MS/MS spectra were searched against a protein

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database containing forward and reversed (decoy) sequences, for protein identification. Details

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of the mass spectrometry analysis and proteome data analysis were provided in Supporting

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Information (SI).

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In Vitro and in Vivo Assays of 6-OH-BDE-47. Enzymatic assays of FabI were conducted

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according to a previous study.24 Briefly, reaction mixtures containing 100 nM recombinant His-

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tagged FabI, 400 µM NADH and 40 µM NAD+, were initiated with the addition of 300 µM 6 ACS Paragon Plus Environment

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butyryl-CoA. Oxidation of NADH to NAD+ was then measured at 340 nm using a POLARStar

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OPTIMA microplate reader (BMG Labtech, Offenburg, Germany).

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Affinity pull-down experiments were conducted by use of E. coli cells overexpressing histagged FabI, to confirm the binding of 6-OH-BDE-47to FabI, as described in SI. Bacterial growth was determined using Mueller-Hinton agar, with or without serial

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concentrations of 6-OH-BDE-47 (0.39-12.5 mg/L); experiments were repeated twice. Inoculums

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of wild-type or FabI-overexpressing late log-phase E. coli cultures (1.5 µL) were spotted onto

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the media, followed by incubation for 16 h at 37oC. The lowest concentration of 6-OH-BDE-47

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that completely inhibited growth was identified as the MIC. For broth based experiments, 10 µL

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of wild type or FabI-overexpressing E. coli were diluted into Mueller-Hinton broth having serial

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concentrations of 6-OH-BDE-47 (0.04-20 mg/L); experiments were repeated four times. After

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culture for 16 h at 37oC, the cultures were transferred to a 96-well plate and cell number

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quantified using a microplate reader at 600 nm.

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Curve Fitting and Stability Ratio Calculation. For all quantitative proteome experiments,

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stability ratios based on normalized H/L ratios for each protein in the MaxQuant

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“proteinGroups.txt” file were used. As a heavy isotope label was used for all the ligand treatment,

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stability ratios were calculated by reversing the default H/L ratios generated by MaxQuant.

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Considering target stability typically increases sigmoidally under increasing ligand

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concentrations, the protein stability ratios determined at multiple concentrations were

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incorporated in the statistical analysis to exclude irrelevant proteins. For large-scale proteome

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data, we found nonlinear sigmoid model fitting is very sensitive to initial model parameters,

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sample size and target detection frequency. It is well known that log transformed dose-

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dependent ligand binding curves are linear in a concentration range before saturation, thus, log-

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linear was tested for curve fitting to increase the robustness of the regression analysis. Akaike’s

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information criteria (AIC) 25 was used to quantitatively compare the sigmoid and log-linear

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model, and log-linear model was found to perform better especially for proteins with limited data

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points because of sample size or detection frequency (good performance of the regression

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analysis results were validated by positive controls of MTX, cancer drugs and antibiotics).

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Significance (p values) were calculated based on the curve fitting, and only proteins with slopes

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differing significantly from 0 (p60oC) tested

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even in the absence of ligand (Figure S1, SI). Hence, we opt instead to use mass spectrometry to

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measure changes in the heat-denatured protein precipitate that forms in the presence or absence

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of compound, which substantively boosts assay dynamic range and sensitivity as compared to

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analyses of the soluble supernatant. Because the amount of aggregated protein present in the

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pellet after centrifugation is proportional to the degree of target denaturation, but independent of

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the overall precipitation propensity, we reasoned this strategy would be effective regardless of

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sample source or complexity.

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As initial proof of principle, we heat shocked (45-70oC) purified recombinant

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dihydrofolate reductase (DHFR), either alone or in the presence of a saturating amount of an

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enzyme inhibitor, the folate analogue methotrexate (MTX). MTX is an anti-cancer drug, and

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interactions of MTX with DHFR have been extensively used to study interactions between 9 ACS Paragon Plus Environment

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proteins and small molecules.28-30 After recovering the precipitate by centrifugation, we

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performed tryptic digestion and quantitative proteomics on both the pellet and supernatant

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fractions (Supplementary Data 1). Based on measurements of peptide spectral counts and

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precursor ion intensities, we found that soluble DHFR levels decreased modestly with increasing

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temperature, and hence were only moderately impacted by binding to MTX (Figure 2a). Yet

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most protein remained soluble even at the highest temperature (70oC), effectively limiting the

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maximal stabilization ratio induced by ligand relative to control to 99%) showed no change (i.e. L/H

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ratios ~1), we observed modest, but significantly enriched, dose-dependent changes in the

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stability of several components of both the 30S and 50S ribosomal subunits (Figures 3e and 3f;

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Figure S3) along with several other ribosome assembly and translational co-factors (e.g. yhbY)

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known to physically associate with the ribosome 32, 33. These results are consistent with the mode

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of actions of the five antibiotics which targeted ribosomes, confirming that TILS can be used to

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characterize large, complex macromolecules of antibiotics.

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Identification of the Protein Target of 6-OH-BDE-47. Having benchmarked assay

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performance, motivated by the good performance of TILS assay on antibiotics as mentioned

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above, we next performed an unbiased discovery screening, using TILS, to characterize the

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bacterial protein target(s) of 6-OH-BDE-47 (Figure 4a), a brominated secondary metabolite

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produced by invertebrates, algae and bacteria that is especially abundant in marine microbes.34

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We verified that 6-OH-BDE-47 strongly inhibits E. coli growth at submicromolar concentrations

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in broth culture (Figure 4a), with a minimum inhibitory concentration (MIC) of 0.78 mg/L, by

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agar plate assay, which is more potent than many existing antibiotics (typically effective at >1

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mg/L). Given that the MIC of 6-OH-BDE-47 is comparable to its native concentration in marine

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microorganisms (0.11-0.22 µg/g),34 its antibacterial activity likely serves an important function

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in defense or resource competition.

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To establish its mechanism of action, we used TILS in combination with dimethyl (stable

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isotope) labeling to measure shifts in heat (55oC) induced E. coli protein precipitation in the

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absence or presence of 6-OH-BDE-47. Strikingly, among the 1,470 proteins detected, the most

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highly impacted candidate was enoyl-acyl carrier protein reductase (FabI), with stability ratio of

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2.8 and p value of 0.002 (Figure 4b and Supplementary Data3). FabI was the only essential 13 ACS Paragon Plus Environment

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protein among 8 identified potential targets passing the stability ratio (1.5) and p value (0.05)

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threshold, and, notably, its stabilization by 6-OH-BDE-47 was concentration-dependent (Figure

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S4), coherent with its potency as an antimicrobial. Since it is well documented that antibiotics

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killed the bacteria by targeting one of the ~300 essential proteins of the ~6000 total proteins,

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considering the fact that FabI is the essential protein for E. coli, and thus FabI is particular

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interesting for its potential role mediating the antibacterial activity of 6-OH-BDE-47.

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Validation of FabI as the Primary Antibacterial Target of 6-OH-BDE-47. As independent

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confirmation, we performed affinity pull down experiments using the recombinant FabI. The

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yield of 6-OH-BDE-47 recovered from affinity-purified FabI from cell lysates of engineered E.

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coli FabI-overexpression strain was >40-fold higher than from a mock control pull-down from

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parental (wild type) E. coli cells (peak abundance was 3.4×106 vs 8.3×104) (Figure 4c),

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confirming the physical interaction of 6-OH-BDE-47 with FabI tentatively identified by TILS.

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FabI is an essential enzyme of the type II fatty acid synthesis system, which mediates the

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biosynthesis of endogenous lipids in bacteria.35 Thus, to further verify if the physical interaction

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with 6-OH-BDE-47 may impact the biochemical activity of FabI, we performed an in vitro

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enzyme assay.24 The results shown in Figure 4d indicate that the catalysis of substrate by FabI

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enzyme was strongly inhibited by 6-OH-BDE-47 at submicromolar concentrations, comparable

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to the MIC of 6-OH-BDE-47.

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As a final line of supporting evidence, we investigated if inhibition of FabI pathway is

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responsible for the antibacterial activity of 6-OH-BDE-47. As shown in Figure 4a, an E. coli

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strain over-expressing FabI was found to be highly resistant to 6-OH-BDE-47 as compared to

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parental wild-type cells (Figure 4a). Thus, FabI was validated as the primary protein target of 6-

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OH-BDE-47 mediated inhibition of bacterial growth.

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Because of the essential role of FabI in metabolism and its sequence conservation across

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many bacterial species, 6-OH-BDE-47 may exhibit a broad spectrum of antibacterial activity. 6-

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OH-BDE-47 is produced as the secondary metabolites by microbes,16 along with >2,000 other

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natural brominated compounds,17 whose biological functions remain unclear. The observation of

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strong antibacterial activity and the identification of a conserved FabI protein target of 6-OH-

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BDE-47 suggests it may serve a potential role in environmental adaption or the competition

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between microbes, but further studies are warranted to clarify these hypotheses as well as the

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identity of the targets of other bioactive natural halogenated compounds, by use of the TILS

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assay described here.

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Implications

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High-throughput characterization of toxicity profiles of environmental chemicals is important to

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meet the regulatory needs of fast growing number of chemicals.5 In parallel to the current

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phenotypic toxicity screening methods,5 unbiased proteome-wide determination of the physical

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interactions of environmental chemicals with cellular proteins is important to understand their

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mechanism of actions. To this end, we developed the TILS platform as a means to routinely

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identify the protein targets of bioactive molecules with high detection sensitivity, specificity and

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signal-to-noise. We demonstrated the broad applicability of our approach by identifying both

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known and unexpected proteins bound by diverse chemicals (anti-cancer drugs, antibiotics,

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natural products). Compared to existing chemical probe-based target detection assays,36, 37 the

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TILS method can be easily adapted to evaluate different bioactive compounds without the need

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for immobilization or synthesis of reactive species. In addition, TILS can potentially be applied

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to different species (e.g. both human cell lines and bacteria in this study), providing a platform to

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investigate potential differential (e.g. species-specific) protein-ligand associations or affinities.

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Yet despite its versatility, TILS is not without caveats. Some proteins bound by a ligand of

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interest may not have a propensity to form detectable aggregates, and some ligands may exert

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only a minor thermodynamic stabilization effect. We have also not shown how well TILS will

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work with membrane-associated proteins, although the general concept seems applicable.38

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Nevertheless, we believe our assay fills an important gap for unbiased, routine and systematic

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characterization of protein targets of diverse ligands, particularly environmental compounds,

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natural products and synthetic chemical ‘hits’ emanating from large-scale phenotypic screens,

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many of which are predicted to have large protein binding interfaces. Thus, further deployment

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and exploration of potential applications of TILS on more diverse bioactive molecules are

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warranted in future studies.

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Halogenated natural products are one of the most important sources of antibiotics, such as

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chlotetracycline and salinosporamide A.39 These halogenated compounds may also pose great

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toxicity to human or wild life.40, 41 While more than 2,000 brominated compounds have been

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discovered in our recent studies,17, 18 limited information is available on their protein targets and

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mechanism of actions. Here, using 6-OH-BDE-47 as a case study, we identified FabI as its

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primary protein target by use of TILS assay. To our best knowledge, this is the first report on the

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physically-interacted protein targets of brominated compounds in bacteria. Future studies are

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warranted to clarify the protein targets and mechanism of actions of other natural brominated

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compounds.

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Acknowledgements

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We thank S. Tan for generously providing plasmids. This work was supported by a Discovery

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Operating grant to A.E. from the Natural Sciences and Engineering Research Council of Canada

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and equipment funds from the Canada Foundation for Innovation.

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Supporting Information Available

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This material is available free of charge via the Internet at http://pubs.acs.org.

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Text and figures addressing (1) Proteomics mass spectrometry data processing and analysis; (2)

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Affinity pull-down experiments; (3) List of anti-cancer drugs examined by TILS; (4) List of

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antibiotics evaluated in this study; (5) Spectral counts recorded by LC/MS for proteins identified

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at different temperatures; (6) Stability ratios of proteins after anti-cancer drug treatment; (7)

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Enrichment for ribosomal protein stabilization after antibiotic treatment; (8) Dose-dependent

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thermal stabilization of FabI in presence of OH-BDE47.

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References (1) Collins, F. S.; Gray, G. M.; Bucher, J. R., Toxicology - transforming environmental health protection. Science 2008, 319 (5865), 906-907. (2) Judson, R.; Richard, A.; Dix, D. J.; Houck, K.; Martin, M.; Kavlock, R.; Dellarco, V.; Henry, T.; Holderman, T.; Sayre, P.; Tan, S.; Carpenter, T.; Smith, E., The toxicity data landscape for environmental chemicals. Environ. Health Perspect. 2009, 117 (5), 685-695. (3) Judson, R. S.; Houck, K. A.; Kavlock, R. J.; Knudsen, T. B.; Martin, M. T.; Mortensen, H. M.; Reif, D. M.; Rotroff, D. M.; Shah, I.; Richard, A. M.; Dix, D. J., In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project. Environ. Health Perspect. 2010, 118 (4), 485-492. (4) Dix, D. J.; Houck, K. A.; Martin, M. T.; Richard, A. M.; Setzer, R. W.; Kavlock, R. J., The ToxCast program for prioritizing toxicity testing of environmental chemicals. Toxicological Sciences 2007, 95 (1), 5-12. (5) Boyd, W. A.; Smith, M. V.; Co, C. A.; Pirone, J. R.; Rice, J. R.; Shockley, K. R.; Freedman, J. H., Developmental effects of the ToxCast (TM) phase I and phase II chemicals in caenorhabditis elegans and corresponding responses in zebrafish, rats, and rabbits. Environ. Health Perspect. 2016, 124 (5), 586-593. (6) Corradetti, M. N.; Guan, K. L., Upstream of the mammalian target of rapamycin: do all roads pass through mTOR? Oncogene 2006, 25 (48), 6347-6360. (7) Karchner, S. I.; Franks, D. G.; Kennedy, S. W.; Hahn, M. E., The molecular basis for differential dioxin sensitivity in birds: Role of the aryl hydrocarbon receptor. Proc. Natl. Acad. Sci. U. S. A. 2006, 103 (16), 6252-6257. (8) Doering, J. A.; Farmahin, R.; Wiseman, S.; Beitel, S. C.; Kennedy, S. W.; Giesy, J. P.; Hecker, M., Differences in activation of aryl hydrocarbon receptors of White Sturgeon relative to Lake Sturgeon are predicted by identities of key amino acids in the ligand binding domain. Environ. Sci. Technol. 2015, 49 (7), 4681-4689. (9) Zhang, R.; Zhang, X. W.; Zhang, J. J.; Qu, R. J.; Zhang, J. M.; Liu, X.; Chen, J.; Wang, Z. Y.; Yu, H. X., Activation of avian aryl hydrocarbon receptor and inter-species sensitivity variations by polychlorinated diphenylsulfides. Environ. Sci. Technol. 2014, 48 (18), 1094810956. (10) Hillenmeyer, M. E.; Fung, E.; Wildenhain, J.; Pierce, S. E.; Hoon, S.; Lee, W.; Proctor, M.; St Onge, R. P.; Tyers, M.; Koller, D.; Altman, R. B.; Davis, R. W.; Nislow, C.; Giaever, G., The chemical genomic portrait of yeast: Uncovering a phenotype for all genes. Science 2008, 320 (5874), 362-365. (11) Hulce, J. J.; Cognetta, A. B.; Niphakis, M. J.; Tully, S. E.; Cravatt, B. F., Proteome-wide mapping of cholesterol-interacting proteins in mammalian cells. Nat. Methods 2013, 10 (3), 259264. (12) Wan, Y.; Jones, P. D.; Wiseman, S.; Chang, H.; Chorney, D.; Kannan, K.; Zhang, K.; Hu, J. Y.; Khim, J. S.; Tanabe, S.; Lam, M. H. W.; Giesy, J. P., Contribution of synthetic and naturally occurring organobromine compounds to bromine mass in marine organisms. Environ. Sci. Technol. 2010, 44 (16), 6068-6073. (13) Zhang, K.; Wan, Y.; Jones, P. D.; Wiseman, S.; Giesy, J. P.; Hu, J. Y., Occurrences and fates of hydroxylated polybrominated diphenyl ethers in marine sediments in relation to trophodynamics. Environ. Sci. Technol. 2012, 46 (4), 2148-2155.

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Figure 1. Workflow of the Target Identification by Ligand Stabilization (TILS) Assay. After exposure to ligand or control (e.g. vehicle only), protein mixtures (soluble cell extracts) are subjected briefly to heat shock (high temperature), after which any denatured precipitate (i.e. aggregated protein) is separated from the remaining soluble protein supernatant by centrifugation. Target precipitation, evident by significant changes in protein levels in the precipitate or supernatant, is determined by mass spectrometry, as quantified using label-free (e.g. spectral counting) or stable isotope-based (e.g. L/H ratio) relative abundance measurements.

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Figure 2. Assay optimization and validation. (a) Box plot showing fraction of recombinant DHFR in solution after heat shock at different temperatures. (b) Box plot showing corresponding fraction of denatured (precipitated) DHFR. (c) Stability ratio (ion intensities) of soluble DHFR (0.005 mg/mL) in control (DMSO) relative to MTX (10 µM) treated supernatant samples. (d) Stability ratio of precipitated DHFR (ion intensities) after centrifugation of control versus MTX samples. (e) Isotope based measurements of heat precipitated DHFR showing ligand stabilization (L/H ratio) at different temperatures. (f) Stabilization (reduced precipitation) of DHFR with different ligand (MTX) concentrations at 55 oC.

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Figure 3. Benchmarking TILS assay performance. (a) Volcano plot showing statistically significant ligand (MTX) stabilization of recombinant DHFR (0.005 mg/mL; red) relative to irrelevant heat precipitated E. coli proteins (1 mg/mL; blue). (b) Selective differential precipitation of endogenous Hsp90 upon heating a human cell (HEK293) extract in presence of radicicol. (c) Volcano plot of SILAC-labeled human proteins stabilized by anti-cancer drugs (putative targets in red). (d) Ligand concentration-dependent stabilization (i.e. reduced precipitation) of HDAC1. (e) Volcano plot of heat precipitated E. coli proteins in presence of antibiotics targeting the ribosome (components and cofactors in red). (f) Ligand concentrationdependent stabilization of representative ribosomal proteins.

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Figure 4. TILS-based target discovery for 6-OH-BDE-47. (a) Dose-dependent growth inhibition of wild-type (WT) E. coli by 6-OH-BDE-47 (structure shown in inset), and resistance conferred by FabI overexpression (red). (b) Volcano plot showing preferential stabilization of FabI by 6OH-BDE-47 relative to other heat precipitated E. coli proteins. (c) Affinity pull-down assay confirming 6-OH-BDE-47 binds directly to FabI; plot shows compound abundance co-purifying with his-tagged FabI versus control (wild type lysates). (d) Concentration-dependent inhibition of FabI enzyme activity in vitro by 6-OH-BDE-47.

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