Lineage-specific proteome remodeling of diverse lung cancer cells by targeted epigenetic inhibitors.

Epigenetic inhibitors exhibit powerful antiproliferative and anticancer activities. However, cellular responses to small-molecule epigenetic inhibition are heterogenous and dependent on factors such as the genetic background, metabolic state, and on-/off-target engagement of individual small-molecule drugs. To determine the mechanisms that drive these heterogeneous cellular responses, we quantified chromatin, proteome, and transcriptome remodeling due to histone deacetylase inhibitor (HDACi) -treated cells derived from diverse genetic backgrounds. We utilized high-throughput sample multiplexed proteomics and integrated intelligent data acquisition methods to map proteomes of cancer cell lines in response to HDACi. We determined cell type-specific and ubiquitous cellular responses based on the quantification of 10,621 total proteins. We then established how coordinated remodeling of the proteome, transcriptome and chromatin state of HDACi treated cancer cells revealed convergent (JUN, MAP2K3, CDKN1A) and divergent (CCND3, ASF1B, BRD7) molecular phenotypes. HDACi-regulated proteins differ greatly across cell lines owing to heterogeneous molecular states of these cell lines. Finally, we demonstrated that HDACi treatment drove a highly cell-type specific response that may in part be explained by cell line-specific off-target drug engagement.

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies.

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications.

Large-scale characterization of drug mechanism of action using proteome-wide thermal shift assays.

In response to an ever-increasing demand of new small molecules therapeutics, numerous chemical and genetic tools have been developed to interrogate compound mechanism of action. Owing to its ability to characterize compound-dependent changes in thermal stability, the proteome-wide thermal shift assay has emerged as a powerful tool in this arsenal. The most recent iterations have drastically improved the overall efficiency of these assays, providing an opportunity to screen compounds at a previously unprecedented rate. Taking advantage of this advance, we quantified 1.498 million thermal stability measurements in response to multiple classes of therapeutic and tool compounds (96 compounds in living cells and 70 compounds in lysates). When interrogating the dataset as a whole, approximately 80% of compounds (with quantifiable targets) caused a significant change in the thermal stability of an annotated target. There was also a wealth of evidence portending off-target engagement despite the extensive use of the compounds in the laboratory and/or clinic. Finally, the combined application of cell- and lysate-based assays, aided in the classification of primary (direct ligand binding) and secondary (indirect) changes in thermal stability. Overall, this study highlights the value of these assays in the drug development process by affording an unbiased and reliable assessment of compound mechanism of action.

Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics.

Sample multiplexed quantitative proteomics assays have proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. Toward this end, we sought to develop and implement a new real-time spectral library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time compared to traditional methods. Taken together, the development of RTLS expands the IDA toolbox to improve instrument efficiency and quantitative accuracy for sample multiplexed analyses.

Global and tissue-specific aging effects on murine proteomes.

Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months). Consistent with previous studies, age-related changes in protein abundance often have no corresponding transcriptional change. Aging results in increases in immune proteins across all tissues, consistent with a global pattern of immune infiltration with age. Our protein-centric data reveal tissue-specific aging changes with functional consequences, including altered endoplasmic reticulum and protein trafficking in the spleen. We further observe changes in the stoichiometry of protein complexes with important roles in protein homeostasis, including the CCT/TriC complex and large ribosomal subunit. These data provide a foundation for understanding how proteins contribute to systemic aging across tissues.

CysDB: a human cysteine database based on experimental quantitative chemoproteomics.

Cysteine chemoproteomics provides proteome-wide portraits of the ligandability or potential "druggability" for thousands of cysteine residues. Consequently, these studies are facilitating resources for closing the druggability gap, namely, achieving pharmacological manipulation of ∼96% of the human proteome that remains untargeted by U.S. Food and Drug Administration (FDA) approved small molecules. Recent interactive datasets have enabled users to interface more readily with cysteine chemoproteomics datasets. However, these resources remain limited to single studies and therefore do not provide a mechanism to perform cross-study analyses. Here we report CysDB as a curated community-wide repository of human cysteine chemoproteomics data derived from nine high-coverage studies. CysDB is publicly available at https://backuslab.shinyapps.io/cysdb/ and features measures of identification for 62,888 cysteines (24% of the cysteinome), as well as annotations of functionality, druggability, disease relevance, genetic variation, and structural features. Most importantly, we have designed CysDB to incorporate new datasets to further support the continued growth of the druggable cysteinome.

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression.

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.

Oligonucleotide-directed proximity-interactome mapping (O-MAP): A unified method for discovering RNA-interacting proteins, transcripts and genomic loci in situ.

Throughout biology, RNA molecules form complex networks of molecular interactions that are central to their function, but remain challenging to investigate. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a straightforward method for elucidating the biomolecules near an RNA of interest, within its native cellular context. O-MAP uses programmable oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA, enabling nearby molecules to be enriched by streptavidin pulldown. O-MAP induces exceptionally precise RNA-localized in situ biotinylation, and unlike alternative methods it enables straightforward optimization of its targeting accuracy. Using the 47S pre-ribosomal RNA and long noncoding RNA Xist as models, we develop O-MAP workflows for unbiased discovery of RNA-proximal proteins, transcripts, and genomic loci. This revealed unexpected co-compartmentalization of Xist and other chromatin-regulatory RNAs and enabled systematic characterization of nucleolar-chromatin interactions across multiple cell lines. O-MAP is portable to cultured cells, organoids, and tissues, and to RNAs of various lengths, abundances, and sequence composition. And, O-MAP requires no genetic manipulation and uses exclusively off-the-shelf parts. We therefore anticipate its application to a broad array of RNA phenomena.

A proteome-wide atlas of drug mechanism of action.

Defining the cellular response to pharmacological agents is critical for understanding the mechanism of action of small molecule perturbagens. Here, we developed a 96-well-plate-based high-throughput screening infrastructure for quantitative proteomics and profiled 875 compounds in a human cancer cell line with near-comprehensive proteome coverage. Examining the 24-h proteome changes revealed ligand-induced changes in protein expression and uncovered rules by which compounds regulate their protein targets while identifying putative dihydrofolate reductase and tankyrase inhibitors. We used protein-protein and compound-compound correlation networks to uncover mechanisms of action for several compounds, including the adrenergic receptor antagonist JP1302, which we show disrupts the FACT complex and degrades histone H1. By profiling many compounds with overlapping targets covering a broad chemical space, we linked compound structure to mechanisms of action and highlighted off-target polypharmacology for molecules within the library.

Conditional Fragment Ion Probabilities Improve Database Searching for Nonmonoisotopic Precursors.

Stochastic, intensity-based precursor isolation can result in isotopically enriched fragment ions. This problem is exacerbated for large peptides and stable isotope labeling experiments using deuterium or 15N. For stable isotope labeling experiments, incomplete and ubiquitous labeling strategies result in the isolation of peptide ions composed of many distinct structural isomers. Unfortunately, existing proteomics search algorithms do not account for this variability in isotopic incorporation, and thus often yield poor peptide and protein identification rates. We sought to resolve this shortcoming by deriving the expected isotopic distributions of each fragment ion and incorporating them into the theoretical mass spectra used for peptide-spectrum-matching. We adapted the Comet search platform to integrate a modified spectral prediction algorithm we term Conditional fragment Ion Distribution Search (CIDS). Comet-CIDS uses a traditional database searching strategy, but for each candidate peptide we compute the isotopic distribution of each fragment to better match the observed m/z distributions. Evaluating previously generated D2O and 15N labeled data sets, we found that Comet-CIDS identified more confident peptide spectral matches and higher protein sequence coverage compared to traditional theoretical spectra generation, with the magnitude of improvement largely determined by the amount of labeling in the sample.

Reducing Peptide Sequence Bias in Quantitative Mass Spectrometry Data with Machine Learning.

Quantitative mass spectrometry measurements of peptides necessarily incorporate sequence-specific biases that reflect the behavior of the peptide during enzymatic digestion and liquid chromatography and in a mass spectrometer. These sequence-specific effects impair quantification accuracy, yielding peptide quantities that are systematically under- or overestimated. We provide empirical evidence for the existence of such biases, and we use a deep neural network, called Pepper, to automatically identify and reduce these biases. The model generalizes to new proteins and new runs within a related set of tandem mass spectrometry experiments, and the learned coefficients themselves reflect expected physicochemical properties of the corresponding peptide sequences. The resulting adjusted abundance measurements are more correlated with mRNA-based gene expression measurements than the unadjusted measurements. Pepper is suitable for data generated on a variety of mass spectrometry instruments and can be used with labeled or label-free approaches and with data-independent or data-dependent acquisition.

Redox-dependent structure and dynamics of macrophage migration inhibitory factor reveal sites of latent allostery.

Macrophage migration inhibitory factor (MIF) is a multifunctional immunoregulatory protein that is a key player in the innate immune response. Given its overexpression at sites of inflammation and in diseases marked by increasingly oxidative environments, a comprehensive understanding of how cellular redox conditions impact the structure and function of MIF is necessary. We used NMR spectroscopy and mass spectrometry to investigate biophysical signatures of MIF under varied solution redox conditions. Our results indicate that the MIF structure is modified and becomes increasingly dynamic in an oxidative environment, which may be a means to alter the MIF conformation and functional response in a redox-dependent manner. We identified latent allosteric sites within MIF through mutational analysis of redox-sensitive residues, revealing that a loss of redox-responsive residues attenuates CD74 receptor activation. Leveraging sites of redox sensitivity as targets for structure-based drug design therefore reveals an avenue to modulate MIF function in its "disease state."

Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging.

INTRODUCTION: Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomic analyses. AREAS COVERED: This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization. EXPERT OPINION: Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant findings from phosphoproteomics studies.

Dual proteome-scale networks reveal cell-specific remodeling of the human interactome.

Thousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins-half the proteome-in 293T cells and includes 118,162 interactions among 14,586 proteins. The second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome whose structure encodes protein function, localization, and complex membership. Comparison across cell lines validates thousands of interactions and reveals extensive customization. Whereas shared interactions reside in core complexes and involve essential proteins, cell-specific interactions link these complexes, "rewiring" subnetworks within each cell's interactome. Interactions covary among proteins of shared function as the proteome remodels to produce each cell's phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.

Advances in quantitative high-throughput phosphoproteomics with sample multiplexing.

Eukaryotic protein phosphorylation modulates nearly every major biological process. Phosphorylation regulates protein activity, mediates cellular signal transduction, and manipulates cellular structure. Consequently, the dysregulation of kinase and phosphatase pathways has been linked to a multitude of diseases. Mass spectrometry-based proteomic techniques are increasingly used for the global interrogation of perturbations in phosphorylation-based cellular signaling. Strategies for studying phosphoproteomes require high-specificity enrichment, sensitive detection, and accurate localization of phosphorylation sites with advanced LC-MS/MS techniques and downstream informatics. Sample multiplexing with isobaric tags has also been integral to recent advancements in throughput and sensitivity for phosphoproteomic studies. Each of these facets of phosphoproteomics analysis present distinct challenges and thus opportunities for improvement and innovation. Here, we review current methodologies, explore persistent challenges, and discuss the outlook for isobaric tag-based quantitative phosphoproteomic analysis.

Reimagining high-throughput profiling of reactive cysteines for cell-based screening of large electrophile libraries.

Current methods used for measuring amino acid side-chain reactivity lack the throughput needed to screen large chemical libraries for interactions across the proteome. Here we redesigned the workflow for activity-based protein profiling of reactive cysteine residues by using a smaller desthiobiotin-based probe, sample multiplexing, reduced protein starting amounts and software to boost data acquisition in real time on the mass spectrometer. Our method, streamlined cysteine activity-based protein profiling (SLC-ABPP), achieved a 42-fold improvement in sample throughput, corresponding to profiling library members at a depth of >8,000 reactive cysteine sites at 18 min per compound. We applied it to identify proteome-wide targets of covalent inhibitors to mutant Kirsten rat sarcoma (KRAS)G12C and Bruton's tyrosine kinase (BTK). In addition, we created a resource of cysteine reactivity to 285 electrophiles in three human cell lines, which includes >20,000 cysteines from >6,000 proteins per line. The goal of proteome-wide profiling of cysteine reactivity across thousand-member libraries under several cellular contexts is now within reach.

Improved Monoisotopic Mass Estimation for Deeper Proteome Coverage.

Accurate assignment of monoisotopic peaks is essential for the identification of peptides in bottom-up proteomics. Misassignment or inaccurate attribution of peptidic ions leads to lower sensitivity and fewer total peptide identifications. In the present work, we present a performant, open-source, cross-platform algorithm, Monocle, for the rapid reassignment of instrument-assigned precursor peaks to monoisotopic peptide assignments. We demonstrate that the present algorithm can be integrated into many common proteomic pipelines and provides rapid conversion from multiple data source types. Finally, we show that our monoisotopic peak assignment results in up to a twofold increase in total peptide identifications compared to analyses lacking monoisotopic correction and a 44% improvement over previous monoisotopic peak correction algorithms.

Homogeneous Oligomers of Pro-apoptotic BAX Reveal Structural Determinants of Mitochondrial Membrane Permeabilization.

BAX is a pro-apoptotic protein that transforms from a cytosolic monomer into a toxic oligomer that permeabilizes the mitochondrial outer membrane. How BAX monomers assemble into a higher-order conformation, and the structural determinants essential to membrane permeabilization, remain a mechanistic mystery. A key hurdle has been the inability to generate a homogeneous BAX oligomer (BAXO) for analysis. Here, we report the production and characterization of a full-length BAXO that recapitulates physiologic BAX activation. Multidisciplinary studies revealed striking conformational consequences of oligomerization and insight into the macromolecular structure of oligomeric BAX. Importantly, BAXO enabled the assignment of specific roles to particular residues and α helices that mediate individual steps of the BAX activation pathway, including unexpected functionalities of BAX α6 and α9 in driving membrane disruption. Our results provide the first glimpse of a full-length and functional BAXO, revealing structural requirements for the elusive execution phase of mitochondrial apoptosis.

Facultative protein selenation regulates redox sensitivity, adipose tissue thermogenesis, and obesity.

Oxidation of cysteine thiols by physiological reactive oxygen species (ROS) initiates thermogenesis in brown and beige adipose tissues. Cellular selenocysteines, where sulfur is replaced with selenium, exhibit enhanced reactivity with ROS. Despite their critical roles in physiology, methods for broad and direct detection of proteogenic selenocysteines are limited. Here we developed a mass spectrometric method to interrogate incorporation of selenium into proteins. Unexpectedly, this approach revealed facultative incorporation of selenium as selenocysteine or selenomethionine into proteins that lack canonical encoding for selenocysteine. Selenium was selectively incorporated into regulatory sites on key metabolic proteins, including as selenocysteine-replacing cysteine at position 253 in uncoupling protein 1 (UCP1). This facultative utilization of selenium was initiated by increasing cellular levels of organic, but not inorganic, forms of selenium. Remarkably, dietary selenium supplementation elevated facultative incorporation into UCP1, elevated energy expenditure through thermogenic adipose tissue, and protected against obesity. Together, these findings reveal the existence of facultative protein selenation, which correlates with impacts on thermogenic adipocyte function and presumably other biological processes as well.

Sample multiplexing for targeted pathway proteomics in aging mice.

Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (∼10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community.