Proteome-Wide Characterization of Phosphorylation-Induced Conformational Changes in Breast Cancer

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Comparative Analysis of Protein Folding Stability-Based Profiling Methods for Characterization of Biological Phenotypes

Recently, a new suite of mass spectrometry-based proteomic methods has been developed that enables evaluation of protein folding stability on the proteomic scale. These methods utilize chemical and thermal denaturation approaches (SPROX and TPP, respectively) as well as proteolysis strategies (DARTS, LiP, and PP) to assess protein folding stability. The analytical capabilities of these technique have been well-established for protein target discovery applications. However, less is known about the relative advantages and disadvantages of using these different strategies to characterize biological phenotypes. Reported here is a comparative study of SPROX, TPP, LiP, and conventional protein expression level measurements using both a mouse model of aging and a mammalian cell culture model of breast cancer. Analyses on proteins in brain tissue cell lysates derived from 1- and 18-month-old mice (n = 4-5 at each time point) and on proteins in cell lysates derived from the MCF-7 and MCF-10A cell lines revealed a majority of the differentially stabilized protein hits in each phenotype analysis had unchanged expression levels. In both phenotype analyses, TPP generated the largest number and fraction of differentially stabilized protein hits. Only a quarter of all the protein hits identified in each phenotype analysis had a differential stability that was detected using multiple techniques. This work also reports the first peptide-level analysis of TPP data, which was required for the correct interpretation of the phenotype analyses performed here. Studies on selected protein stability hits also uncovered phenotype-related functional changes.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Hsp40 Affinity to Identify Proteins Destabilized by Cellular Toxicant Exposure

Environmental toxins and toxicants can damage proteins and threaten cellular proteostasis. Most current methodologies to identify misfolded proteins in cells survey the entire proteome for sites of changed reactivity. We describe and apply a quantitative proteomics methodology to identify destabilized proteins based on their binding to the human Hsp40 chaperone DNAJB8. These protein targets are validated by an orthogonal limited proteolysis assay using parallel reaction monitoring. We find that a brief exposure of HEK293T cells to meta-arsenite increases the affinity of two dozen proteins to DNAJB8, including known arsenite-sensitive proteins. In particular, arsenite treatment destabilizes both the pyruvate dehydrogenase complex E1 subunit and several RNA-binding proteins. This platform can be used to explore how environmental toxins impact cellular proteostasis and to identify the susceptible proteome.

Direct visualization and profiling of protein misfolding and aggregation in live cells

Over the past few years, research tools have been developed to monitor the multistep protein aggregation process in live cells, a process that has been associated with a growing number of human diseases. Herein, we describe recent advances in methods that can either survey the distribution of aggregation at the level of the cellular proteome using mass spectroscopy or discern the multistep aggregation process of specific proteins of interest via fluorescence signals. Future development and application of such technologies are expected to provide insights on mechanisms, diagnosis, and treatment of diseases rooted in protein aggregation.

Recent advances in identifying protein targets in drug discovery

Phenotype-based screening has emerged as an alternative route for discovering new chemical entities toward first-in-class therapeutics. However, clarifying their mode of action has been a significant bottleneck for drug discovery. For target protein identification, conventionally bioactive small molecules are conjugated onto solid supports and then applied to isolate target proteins from whole proteome. This approach requires a high binding affinity between bioactive small molecules and their target proteins. Besides, the binding affinity can be significantly hampered after structural modifications of bioactive molecules with linkers. To overcome these limitations, two major strategies have recently been pursued: (1) the covalent conjugation between small molecules and target proteins using photoactivatable moieties or electrophiles, and (2) label-free target identification through monitoring target engagement by tracking the thermal, proteolytic, or chemical stability of target proteins. This review focuses on recent advancements in target identification from covalent capturing to label-free strategies.

Bioinformatics Analysis of Metabolomics Data Unveils Association of Metabolic Signatures with Methylation in Breast Cancer

Breast cancer (BC) contributes the highest global cancer mortality in women. BC tumors are highly heterogeneous, so subtyping by cell-surface markers is inadequate. Omics-driven tumor stratification is urgently needed to better understand BC and tailor therapies for personalized medicine. We used unsupervised k-means and partition around medoids (pam) to cluster metabolomics data from two data sets. The first comprised 271 BC tumors (data set 1) that were estrogen receptor (ER) positive (ER+, n = 204) or negative (ER-, n = 67) with 162 identified and validated metabolites. The second data set contained 67 BC samples (data set 2; ER+, n = 33; ER-, n = 34) and 352 known metabolites. Significance Analysis of Microarrays (SAM) was used to identify the most significant metabolites among these clusters, which were then reassigned into new clusters using prediction analysis of microarrays (PAM). Generally, metabolome-defined BC subtypes identified from either data set 1 or data set 2 were different from the well-known receptor- or transcriptome-defined subtypes. Metabolomics-directed clustering of data set 2 identified distinctive BC tumors characterized by metabolome profiles that associated with DNA methylation (p-value = 0.000 048, χ² test). Pathway analysis of cluster metabolites revealed that nitrogen metabolism and aminoacyl-tRNA biosynthesis were highly related to BC subtyping. The pipeline may be run from GitHub: https://github.com/FADHLyemen/Metabolomics_signature. Our proposed bioinformatics pipeline analyzed metabolomics data from BC tumors, revealing clusters characterized by unique metabolic signatures that may potentially stratify BC patients and tailor precision treatment.

Single droplet detection of immune checkpoints on a multiplexed electrohydrodynamic biosensor

Monitoring soluble immune checkpoints in circulating fluids has the potential for minimally-invasive diagnostics and personalised therapy in precision medicine. Yet, the sensitive detection of multiple immune checkpoints from small volumes of liquid biopsy samples is challenging. In this study, we develop a multiplexed immune checkpoint biosensor (MICB) for parallel detection of soluble immune checkpoints PD-1, PD-L1, and LAG-3. MICB integrates a microfluidic sandwich immunoassay using engineered single chain variable fragments and alternating current electrohydrodynamic in situ nanofluidic mixing for promoting biosensor-target interaction and reducing non-specific non-target binding. MICB provides advantages of simultaneous analysis of up to 28 samples in <2 h, requires as little as a single sample drop (i.e., 20 μL) per target immune checkpoint, and applies high-affinity yeast cell-derived single chain variable fragments as a cost-effective alternative to monoclonal antibodies. We investigate the assay performance of MICB and demonstrate its capability for accurate immune checkpoint detection in simulated patient serum samples at clinically-relevant levels. MICB provides a dynamic range of 5 to 200 pg mL-1 for PD-1 and PD-L1, and 50 to 1000 pg mL-1 for LAG-3 with a coefficient of variation <13.8%. Sensitive immune checkpoint detection was achieved with limits of detection values of 5 pg mL-1 for PD-1, 5 pg mL-1 for PD-L1, and 50 pg mL-1 for LAG-3. The multiplexing capability, sensitivity, and relative assay simplicity of MICB make it capable of serving as a bioanalytical tool for immune checkpoint therapy monitoring.

Chemo-Selection Strategy for Limited Proteolysis Experiments on the Proteomic Scale

Described here is a chemo-selective enrichment strategy, termed the semitryptic peptide enrichment strategy for proteolysis procedures (STEPP), to isolate the semitryptic peptides generated in mass spectrometry-based proteome-wide applications of limited proteolysis methods. The strategy involves reacting the ε-amino groups of lysine side chains and any N-termini created in the limited proteolysis reaction with isobaric mass tags. A subsequent digestion of the sample with trypsin and the chemo-selective reaction of the newly exposed N-termini of the tryptic peptides with N-hydroxysuccinimide (NHS)-activated agarose resin removes the tryptic peptides from solution, leaving only the semitryptic peptides with one nontryptic cleavage site generated in the limited proteolysis reaction for subsequent LC-MS/MS analysis. As part of this work, the STEPP technique is interfaced with two different proteolysis methods, including the pulse proteolysis (PP) and limited proteolysis (LiP) methods. The STEPP-PP workflow is evaluated in two proof-of-principle experiments involving the proteins in a yeast cell lysate and two well-studied drugs, cyclosporin A and geldanamycin. The STEPP-LiP workflow is evaluated in a proof-of-principle experiment involving the proteins in two cell culture models of human breast cancer, MCF-7 and MCF-10A cell lines. The STEPP protocol increased the number of semitryptic peptides detected in the LiP and PP experiments by 5- to 10-fold. The STEPP protocol not only increases the proteomic coverage, but also increases the amount of structural information that can be gleaned from limited proteolysis experiments. Moreover, the protocol also enables the quantitative determination of ligand binding affinities.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.