Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using Limited Proteolysis

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Identification of α-amanitin effector proteins in hepatocytes by limited proteolysis-coupled mass spectrometry

The misuse of poisonous mushrooms containing amatoxins causes acute liver failure (ALF) in patients and is a cause of significant mortality. Although the toxic mechanisms of α-amanitin (α-AMA) and its interactions with RNA polymerase II (RNAP II) have been studied, α-AMA effector proteins that can interact with α-AMA in hepatocytes have not been systematically studied. Limited proteolysis-coupled mass spectrometry (LiP-MS) is an advanced technology that can quickly identify protein-ligand interactions based on global comparative proteomics. This study identified the α-AMA effector proteins found in human hepatocytes, following the detection of conformotypic peptides using LiP-MS coupled with tandem mass tag (TMT) technology. Proteins that are classified into protein processing in the endoplasmic reticulum and the ribosome during the KEGG pathway can be identified through affinity evaluation, according to α-AMA concentration-dependent LiP-MS and LiP-MS in hepatocytes derived from humans and mice, respectively. The possibility of interaction between α-AMA and proteins containing conformotypic peptides was evaluated through molecular docking studies. The results of this study suggest a novel path for α-AMA to induce hepatotoxicity through interactions with various proteins involved in protein synthesis, as well as with RNAP II.

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.

Protein Folding Stability Profiling of Colorectal Cancer Chemoresistance Identifies Functionally Relevant Biomarkers

Reported here is the application of three protein folding stability profiling techniques (including the stability of proteins from rates of oxidation, thermal protein profiling, and limited proteolysis approaches) to identify differentially stabilized proteins in six patient-derived colorectal cancer (CRC) cell lines with different oxaliplatin sensitivities and eight CRC patient-derived xenografts (PDXs) derived from two of the patient derived cell lines with different oxaliplatin sensitivities. Compared to conventional protein expression level analyses, which were also performed here, the stability profiling techniques identified both unique and novel proteins and cellular components that differentiated the sensitive and resistant samples including 36 proteins that were differentially stabilized in at least two techniques in both the cell line and PDX studies of oxaliplatin resistance. These 36 differentially stabilized proteins included 10 proteins previously connected to cancer chemoresistance. Two differentially stabilized proteins, fatty acid synthase and elongation factor 2, were functionally validated in vitro and found to be druggable protein targets with biological functions that can be modulated to improve the efficacy of CRC chemotherapy. These results add to our understanding of CRC oxaliplatin resistance, suggest biomarker candidates for predicting oxaliplatin sensitivity in CRC, and inform new strategies for overcoming chemoresistance in CRC.

Protein painting reveals pervasive remodeling of conserved proteostasis machinery in response to pharmacological stimuli

The correct spatio-temporal organization of the proteome is essential for cellular homeostasis. However, a detailed mechanistic understanding of this organization and how it is altered in response to external stimuli in the intact cellular environment is as-yet unrealized. ‘Protein painting methods provide a means to address this gap in knowledge by monitoring the conformational status of proteins within cells at the proteome-wide scale. Here, we demonstrate the ability of a protein painting method employing tetraphenylethene maleimide (TPE-MI) to reveal proteome network remodeling in whole cells in response to a cohort of commonly used pharmacological stimuli of varying specificity. We report specific, albeit heterogeneous, responses to individual stimuli that coalesce on a conserved set of core cellular machineries. This work expands our understanding of proteome conformational remodeling in response to cellular stimuli, and provides a blueprint for assessing how these conformational changes may contribute to disorders characterized by proteostasis imbalance.

Metabolization and sequestration of plant specialized metabolites in insect herbivores: Current and emerging approaches

Herbivorous insects encounter diverse plant specialized metabolites (PSMs) in their diet, that have deterrent, anti-nutritional, or toxic properties. Understanding how they cope with PSMs is crucial to understand their biology, population dynamics, and evolution. This review summarizes current and emerging cutting-edge methods that can be used to characterize the metabolic fate of PSMs, from ingestion to excretion or sequestration. It further emphasizes a workflow that enables not only to study PSM metabolism at different scales, but also to tackle and validate the genetic and biochemical mechanisms involved in PSM resistance by herbivores. This review thus aims at facilitating research on PSM-mediated plant-herbivore interactions.

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.

Illustrative Tutorials for ProThermDB: Thermodynamic Database for Proteins and Mutants

ProThermDB (https://web.iitm.ac.in/bioinfo2/prothermdb/index.html) is a primary resource for protein stability, which contains experimentally determined thermodynamic data for proteins and their mutants. The most recent version of ProThermDB accumulates the data obtained from both high- and low-throughput experimental biophysical methods. It includes comprehensive information at four different levels, i.e.: (i) protein sequence and structure; (ii) experimental conditions; (iii) thermodynamic parameters such as Gibbs free energy, melting temperature, enthalpy, etc.; and (iv) literature. In the following protocols, we present detailed tutorials for retrieving data using different search, display and sorting options, interpretation of search results, description of each entry-level information category, data upload and download, cross-links with other databases, and visualization options. This protocol consists of six pictorial exercises, which are useful for biologists/users to understand the contents and organization of data in ProThermDB. Further, potential applications of ProThermDB in protein engineering are discussed. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Retrieval of experimental thermodynamic data for wild-type and mutants of a specific protein using a simple query Basic Protocol 2: Retrieval of stabilizing point mutations, which are located at the interior of α-helical regions, and obtaining data by thermal denaturation methods Basic Protocol 3: Retrieval of destabilizing point mutations, which are in β-sheets of exposed regions, and obtaining data by chemical denaturation methods (urea and GdnHCl) Basic Protocol 4: Retrieval of stabilizing and destabilizing point mutations in a range of physiological conditions (pH: 6-9 and T: 20°C-25°C) and publication years (2010-2020) Support Protocol: Downloading the entire data of the database for academic research purposes and submission of new data in ProThermDB.

Analysis of Brain Protein Stability Changes in Mouse Models of Normal Aging and α-Synucleinopathy Reveals Age- and Disease-Related Differences

Here, we utilize the stability of proteins from rates of oxidation (SPROX) technique, to profile the thermodynamic stabilities of proteins in brain tissue cell lysates from Huα-Syn(A53T) transgenic mice at three time points including at 1 month (n = 9), at 6 months (n = 7), and at the time (between 9 and 16 months) a mouse became symptomatic (n = 8). The thermodynamic stability profiles generated here on 332 proteins were compared to thermodynamic stability profiles generated on the same proteins from similarly aged wild-type mice using a two-way unbalanced analysis of variance (ANOVA) analysis. This analysis identified a group of 22 proteins with age-related protein stability changes and a group of 11 proteins that were differentially stabilized in the Huα-Syn(A53T) transgenic mouse model. A total of 9 of the 11 proteins identified here with disease-related stability changes have been previously detected in human cerebral spinal fluid and thus have potential utility as biomarkers of Parkinson's disease (PD). The differential stability observed for one protein, glutamate decarboxylase 2 (Gad2), with an age-related change in stability, was consistent with the differential presence of a known, age-related truncation product of this protein, which is shown here to have a higher folding stability than full-length Gad2. Mass spectrometry data were deposited at ProteomeXchange (PXD016985).

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.

ProThermDB: thermodynamic database for proteins and mutants revisited after 15 years

ProThermDB is an updated version of the thermodynamic database for proteins and mutants (ProTherm), which has ∼31 500 data on protein stability, an increase of 84% from the previous version. It contains several thermodynamic parameters such as melting temperature, free energy obtained with thermal and denaturant denaturation, enthalpy change and heat capacity change along with experimental methods and conditions, sequence, structure and literature information. Besides, the current version of the database includes about 120 000 thermodynamic data obtained for different organisms and cell lines, which are determined by recent high throughput proteomics techniques using whole-cell approaches. In addition, we provided a graphical interface for visualization of mutations at sequence and structure levels. ProThermDB is cross-linked with other relevant databases, PDB, UniProt, PubMed etc. It is freely available at https://web.iitm.ac.in/bioinfo2/prothermdb/index.html without any login requirements. It is implemented in Python, HTML and JavaScript, and supports the latest versions of major browsers, such as Firefox, Chrome and Safari.

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.

A Simplified Thermal Proteome Profiling Approach to Screen Protein Targets of a Ligand

Thermal proteome profiling is a powerful energetic-based chemical proteomics method to reveal the ligand-protein interaction. However, the costly multiplexed isotopic labeling reagent, mainly Multiplexed isobaric tandem mass tag (TMT), and the long mass spectrometric time limits the wide application of this method. Here a simple and cost-effective strategy by using dimethyl labeling technique instead of TMT labeling is reported to quantify proteins and by using the peptides derived from the same protein to determine significantly changed proteins in one LC-MS run. This method is validated by identifying the known targets of methotrexate and geldanamycin. In addition, several potential off-targets involved in detoxification of reactive oxygen species pathway are also discovered for geldanamycin. This method is further applied to map the interactome of adenosine triphosphate (ATP) in the 293T cell lysate by using ATP analogue, adenylyl imidodiphosphate (AMP-PNP), as the ligand. As a result, a total of 123 AMP-PNP-sensitive proteins are found, of which 59 proteins are stabilized by AMP-PNP. Approximately 53% and 20% of these stabilized candidate protein targets are known as ATP and RNA binding proteins. Overall, above results demonstrated that this approach could be a valuable platform for the unbiased target proteins identification with reduced reagent cost and mass spectrometric time.

A Global Screen for Assembly State Changes of the Mitotic Proteome by SEC-SWATH-MS

Living systems integrate biochemical reactions that determine the functional state of each cell. Reactions are primarily mediated by proteins. In proteomic studies, these have been treated as independent entities, disregarding their higher-level organization into complexes that affects their activity and/or function and is thus of great interest for biological research. Here, we describe the implementation of an integrated technique to quantify cell-state-specific changes in the physical arrangement of protein complexes concurrently for thousands of proteins and hundreds of complexes. Applying this technique to a comparison of human cells in interphase and mitosis, we provide a systematic overview of mitotic proteome reorganization. The results recall key hallmarks of mitotic complex remodeling and suggest a model of nuclear pore complex disassembly, which we validate by orthogonal methods. To support the interpretation of quantitative SEC-SWATH-MS datasets, we extend the software CCprofiler and provide an interactive exploration tool, SECexplorer-cc.

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Global quantification of assembly state changes in the mitotic proteome

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Improved performance over thermostability measurement of proteome states

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Discovery of a mitotic disassembly intermediate of the nuclear pore complex

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Introduction of SECexplorer-cc, a publicly available online platform

'Shotgun' proteomic analyses without alkylation of cysteine

It is a common belief that reduction of disulfide bridges and alkylation of thiols in proteins are indispensable steps in proteomic sample preparation. Since this chemical procedure is often incomplete and prone to side reactions we reexamined its importance. We found that reduction and alkylation do not increase the depth of analysis and quality of proteomic quantification and therefore these steps are not essential in 'shotgun'-type investigations of proteomes. Moreover, we found that compared to a standard procedure using iodoacetamide for thiol-alkylation, sample preparation under conditions protecting thiols from oxidation improves quality of peptides and allows identifying of 10-20% more peptides and proteins. Excluding thiol-alkylation from proteomic sample preparation shortens the workflows and decreases the probability of biases resulting from occurrence of artificially modified peptides.

Network-based approach to identify principal isoforms among four cancer types

Protein isoforms are structurally similar proteins produced by alternative splicing of a single gene or genes from the same family. Isoforms of a protein can perform the same, similar, or even opposite biological functions. A previous study identified principal isoforms of proteins based on the extent of interactions per isoform in a functional relationship network, focusing on data from normal tissues. Additionally, the expression levels of specific isoforms of various genes associated with tumorigenesis and prognosis are frequently altered in tumors compared with those in normal tissues. In this study, we aimed to identify higher degree isoforms (HDIs) of multi-isoform genes (MIGs) in cancer by applying a meta-analytical framework to calculate co-expression between each pair of isoforms in two large datasets of RNA-seq profiles from breast cancer, lung cancer, leukemia, and colon cancer cell lines. Then, we compared HDIs with isoforms identified by proteomic data and prognostic and predictive evidence in various cancers. In addition, we separately analyzed the associations between HDIs and non-HDIs (nHDIs) of the same genes according to transcript expression and drug responses in various cancer type cell lines. Collectively, these results indicated the complex properties of HDIs per gene identified by cancer type-based isoform-isoform co-expression networks and showed the potential of HDIs as novel therapeutic targets for cancer treatment.

A one-pot analysis approach to simplify measurements of protein stability and folding kinetics

To achieve a good understanding of the characteristics of a protein, it is important to study its stability and folding kinetics. Investigations of protein stability have been recently applied to drug-target identification, drug screening, and proteomic studies. The efficiency of the experiments performed to study protein stability and folding kinetics is now a crucial factor that needs to be optimized for these potential applications. However, the standard procedures used to carry out these experiments are usually complicated and time consuming. Large number of measurements is the bottleneck that limits the application of protein folding to large-scale experiments. To overcome this limitation, we developed a method denoted as "one-pot analysis" which is based on taking a single measurement from a mixture of samples rather than from every sample. We combined one-pot analysis with pulse proteolysis to determine the effects of the binding of maltose to maltose-binding protein on the protein folding properties. After carrying out a simple optimization, we demonstrated that protein stability or unfolding kinetics could be measured accurately with just one detection measurement. We then further applied the optimized conditions to cellular thermal shift assay (CETSA). Combining one-pot analysis with CETSA led to a successful determination of the effects of the binding of methotrexate to dihydrofolate reductase in HCT116 cancer cells. Our results demonstrated the applicability of one-pot analysis to energetics-based methods for studying protein folding. We expect the combination of one-pot analysis and energetics-based methods to significantly benefit studies such as drug-target identification, proteomic investigations, and drug screening.

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.

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

Because of the close link between protein function and protein folding stability, knowledge about phosphorylation-induced protein folding stability changes can lead to a better understanding of the functional effects of protein phosphorylation. Here, the stability of proteins from rates of oxidation (SPROX) and limited proteolysis (LiP) techniques are used to compare the conformational properties of proteins in two MCF-7 cell lysates including one that was and one that was not dephosphorylated with alkaline phosphatase. A total of 168 and 251 protein hits were identified with dephosphorylation-induced stability changes using the SPROX and LiP techniques, respectively. Many protein hits are previously known to be differentially phosphorylated or differentially stabilized in different human breast cancer subtypes, suggesting that the phosphorylation-induced stability changes detected in this work are disease related. The SPROX hits were enriched in proteins with aminoacyl-tRNA ligase activity. These enriched protein hits included many aminoacyl-tRNA synthetases (aaRSs), which are known from previous studies to have their catalytic activity modulated by phosphorylation. The SPROX results revealed that the magnitudes of the destabilizing effects of dephoshporylation on the different aaRSs were directly correlated with their previously reported aminoacylation activity change upon dephosphorylation. This substantiates the close link between protein folding and function.

Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using SILAC-SPROX

Proteomic methods for disease state characterization and biomarker discovery have traditionally utilized quantitative mass spectrometry methods to identify proteins with altered expression levels in disease states. Here we report on the large-scale use of protein folding stability measurements to characterize different subtypes of breast cancer using the stable isotope labeling with amino acids in cell culture and stability of proteins from rates of oxidation (SILAC-SPROX) technique. Protein folding stability differences were studied in a comparison of two luminal breast cancer subtypes, luminal-A and -B (i.e., MCF-7 and BT-474 cells, respectively), and in a comparison of a luminal-A and basal subtype of the disease (i.e., MCF-7 and MDA-MB-468 cells, respectively). The 242 and 445 protein hits identified with altered stabilities in these comparative analyses included a large fraction with no significant expression level changes. This suggests thermodynamic stability measurements create a new avenue for protein biomarker discovery. A number of the identified protein hits are known from other biochemical studies to play a role in tumorigenesis and cancer progression. This not only substantiates the biological significance of the protein hits identified using the SILAC-SPROX approach, but it also helps elucidate the molecular basis for their disregulation and/or disfunction in cancer.

Systematic Evaluation of Protein Reduction and Alkylation Reveals Massive Unspecific Side Effects by Iodine-containing Reagents

Reduction and alkylation of cysteine residues is part of virtually any proteomics workflow. Despite its frequent use, up to date no systematic investigation of the impact of different conditions on the outcome of proteomics studies has been performed. In this study, we compared common reduction reagents (dithiothreitol, tris-(2-carboxyethyl)-phosphine, and β-mercaptoethanol) and alkylation reagents (iodoacetamide, iodoacetic acid, acrylamide, and chloroacetamide). Using in-gel digests as well as SAX fractionated in-solution digests of cytosolic fractions of HeLa cells, we evaluated 13 different reduction and alkylation conditions resulting in considerably varying identification rates. We observed strong differences in offsite alkylation reactions at 7 amino acids as well as at the peptide N terminus, identifying single and double adducts of all reagents. Using dimethyl labeling, mass tolerant searches, and synthetic peptide experiments, we identified alkylation of methionine residues by iodine-containing alkylation reagents as one of the major factors for the differences. We observed differences of more than 9-fold in numbers of identified methionine-containing peptide spectral matches for in-gel digested samples between iodine- and noniodine-containing alkylation reagents. This was because of formation of carbamidomethylated and carboxymethylated methionine side chains and a resulting prominent neutral loss during ESI ionization or in MS/MS fragmentation, strongly decreasing identification rates of methionine-containing peptides. We achieved best results with acrylamide as alkylation reagent, whereas the highest numbers of peptide spectral matches were obtained when reducing with dithiothreitol and β-mercaptoethanol for the in-solution and the in-gel digested samples, respectively.

The LINK-A lncRNA interacts with PtdIns(3,4,5)P3 to hyperactivate AKT and confer resistance to AKT inhibitors

Phosphatidylinositol-3,4,5-trisphosphate (PIP₃) mediates signaling pathways as a second messenger in response to extracellular signals. Although primordial functions of phospholipids and RNAs have been hypothesized in the “RNA world”, physiological RNA-phospholipid interactions and their involvement in essential cellular processes has remained a mystery. We explicate the contribution of lipid-binding long non-coding RNAs (lncRNAs) in cancer cells. Among them, Long Intergenic Noncoding RNA for Kinase Activation (LINK-A) directly interacts with AKT pleckstrin homology domain and PIP₃ at the single nucleotide level, facilitating AKT-PIP₃ interaction and consequent enzymatic activation. LINK-A-dependent AKT hyperactivation leads to tumorigenesis and resistance to AKT inhibitors. Genomic deletions of the LINK-A PIP₃-binding motif dramatically sensitized breast cancer cells to AKT inhibitors. Furthermore, meta-analysis showed the correlation between LINK-A expression and incidence of a SNP (rs12095274: A>G), AKT phosphorylation status, and poor outcomes for breast and lung cancer patients. PIP₃-binding lncRNA modulates AKT activation with broad clinical implications.