Mass spectrometry-based proteomic analysis to characterize cisplatin induced early signaling events in head and neck squamous cell carcinoma.

Cisplatin is the commonly used chemotherapeutic drug in treatment of various cancers. However, development of resistance towards cisplatin results in tumor recurrence. Here, we aim to understand the mechanisms of action of cisplatin and emergence of resistance to cisplatin using mass spectrometry-based proteomic approach. A panel of head and neck squamous cell carcinoma (HNSCC) cell lines were treated with cisplatin at respective IC50 for 24 h and label-free mass spectrometry analysis was carried out. Proteomic analysis of A253, FaDu, Det562 and CAL27 cell lines upon cisplatin treatment resulted in the identification of 5,060, 4,816, 4,537 and 4,142 proteins, respectively. Bioinformatics analysis of differentially regulated proteins revealed proteins implicated in DNA damage bypass pathway, translation and mRNA splicing to be enriched. Further, proteins associated with cisplatin resistance exhibited alterations following short-term cisplatin exposure. Among these, class III tubullin protein (TUBB3) was found to be upregulated in cisplatin-treated cells compared to untreated cells. Western blot analysis confirmed the elevated expression of TUBB3 in cells treated with cisplatin for 24 h, and also in cisplatin resistant HNSCC cell lines. This study delineates the early signaling events that enable HNSCC cells to counteract the cytotoxic effects of cisplatin and facilitate the development of resistance.

Exploration of Nitrotyrosine-Containing Proteins and Peptides by Antibody-Based Enrichment Strategies.

Nitrotyrosine, or 3-nitrotyrosine, is an oxidative post-translational modification induced by reactive nitrogen species. Although nitrotyrosine is considered a marker of oxidative stress and has been associated with inflammation, neurodegeneration, cardiovascular disease, and cancer, identification of nitrotyrosine-modified proteins remains challenging owing to its low stoichiometric levels in biological samples. To facilitate a comprehensive analysis of proteins and peptides containing nitrotyrosine, we optimized an immunoprecipitation-based enrichment workflow using a cell line model. The identification of proteins and peptides containing nitrotyrosine residues was carried out after peroxynitrite treatment of cell lysates, which generated modified nitrotyrosine residues on susceptible sites on proteins. We evaluated the efficacy of enriching nitrotyrosine-modified proteins and peptides by employing four different commercially available monoclonal antibodies directed against nitrotyrosine. LC-MS/MS analysis resulted in the identification of 1377 and 1624 nitrotyrosine-containing peptides from protein- and peptide-based enrichment experiments, respectively. Although the yield of nitrotyrosine-containing peptides was higher in experiments where peptides rather than proteins were enriched, we found a substantial proportion (37-65%) of identified nitrotyrosine-containing peptides contained nitrotyrosine at the N-terminus. However, in protein-based immunoprecipitation <9% of nitrotyrosine-containing peptides had nitrotyrosine modification at the N-terminus of the peptide. Overall, our study resulted in the identification of 2603 nitrotyrosine-containing peptides of which >2000 have not previously been reported. We synthesized 101 novel nitrotyrosine-containing peptides identified in our analysis and analyzed them by LC-MS/MS to validate our findings. We have confirmed the validity of 70% of these peptides, as they demonstrated a similarity score exceeding 0.7 when compared to peptides identified through experimental methods. Finally, we also validated the presence of nitrotyrosine modification on PKM and EF2 proteins in peroxynitrite-treated samples by immunoblot analysis. The large catalog presented in this study along with the workflow should facilitate the investigation of nitrotyrosine as an oxidative modification in a variety of settings in greater detail.

Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics.

Although tandem mass tag (TMT)-based isobaric labeling has become a powerful approach for multiplexed protein quantitation, automating the workflow for this technique has not been easy to achieve for widespread adoption. This is because preparation of TMT-labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction, and alkylation to tryptic digestion, desalting, labeling, and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic, especially with large-scale clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for an automated proteomic workflow employing TMT labeling with the manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using an automated platform and a conventional manual protocol. Single-shot liquid chromatography with tandem mass spectrometry analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiency of tryptic digestion, alkylation, and TMT labeling were similar in both manual and automated processes. In addition, comparison of quantitation accuracy and precision showed similar performance in an automated workflow compared to manual sample preparation by an expert. Overall, we demonstrated that the automated platform performs at a level similar to a manual process performed by an expert for TMT-based proteomics. We anticipate that this automated workflow will increasingly replace manual pipelines and has the potential to be applied to large-scale TMT-based studies, providing robust results and high sample throughput.

Optimizing single cell proteomics using trapped ion mobility spectrometry for label-free experiments.

Although single cell RNA-seq has had a tremendous impact on biological research, a corresponding technology for unbiased mass spectrometric analysis of single cells has only recently become available. Significant technological breakthroughs including miniaturized sample handling have enabled proteome profiling of single cells. Furthermore, trapped ion mobility spectrometry (TIMS) in combination with parallel accumulation-serial fragmentation operated in data-dependent acquisition mode (DDA-PASEF) allowed improved proteome coverage from low-input samples. It has been demonstrated that modulating the ion flux in TIMS affects the overall performance of proteome profiling. However, the effect of TIMS settings on the analysis of low-input samples has been less investigated. Thus, we sought to optimize the conditions of TIMS with regard to ion accumulation/ramp times and ion mobility range for low-input samples. We observed that an ion accumulation time of 180 ms and monitoring a narrower ion mobility range from 0.7 to 1.3 V s cm-2 resulted in a substantial gain in the depth of proteome coverage and in detecting proteins with low abundance. We used these optimized conditions for proteome profiling of sorted human primary T cells, which yielded an average of 365, 804, 1116, and 1651 proteins from single, five, ten, and forty T cells, respectively. Notably, we demonstrated that the depth of proteome coverage from a low number of cells was sufficient to delineate several essential metabolic pathways and the T cell receptor signaling pathway. Finally, we showed the feasibility of detecting post-translational modifications including phosphorylation and acetylation from single cells. We believe that such an approach could be applied to label-free analysis of single cells obtained from clinically relevant samples.

A High-Throughput Workflow for FFPE Tissue Proteomics.

Laser capture microdissection (LCM) has become an indispensable tool for mass spectrometry-based proteomic analysis of specific regions obtained from formalin-fixed paraffin-embedded (FFPE) tissue samples in both clinical and research settings. Low protein yields from LCM samples along with laborious sample processing steps present challenges for proteomic analysis without sacrificing protein and peptide recovery. Automation of sample preparation workflows is still under development, especially for samples such as laser-capture microdissected tissues. Here, we present a simplified and rapid workflow using adaptive focused acoustics (AFA) technology for sample processing for high-throughput FFPE-based proteomics. We evaluated three different workflows: standard extraction method followed by overnight trypsin digestion, AFA-assisted extraction and overnight trypsin digestion, and AFA-assisted extraction simultaneously performed with trypsin digestion. The use of AFA-based ultrasonication enables automated sample processing for high-throughput proteomic analysis of LCM-FFPE tissues in 96-well and 384-well formats. Further, accelerated trypsin digestion combined with AFA dramatically reduced the overall processing times. LC-MS/MS analysis revealed a slightly higher number of protein and peptide identifications in AFA accelerated workflows compared to standard and AFA overnight workflows. Further, we did not observe any difference in the proportion of peptides identified with missed cleavages or deamidated peptides across the three different workflows. Overall, our results demonstrate that the workflow described in this study enables rapid and high-throughput sample processing with greatly reduced sample handling, which is amenable to automation.

Four-dimensional proteomics analysis of human cerebrospinal fluid with trapped ion mobility spectrometry using PASEF.

A quadrupole time-of-flight mass spectrometer coupled with a trapped ion mobility spectrometry (timsTOF) operated in parallel accumulation-serial fragmentation (PASEF) mode has recently emerged as a platform capable of providing four-dimensional (4D) features comprising of elution time, collision cross section (CCS), mass-to-charge ratio, and intensity of peptides. The PASEF mode provides ∼100% ion sampling efficiency both in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes without sacrificing sensitivity. In addition, targeted measurements using PASEF integrated parallel reaction monitoring (PRM) mode have also been described. However, only limited number of studies have used timsTOF for analysis of clinical samples. Although Orbitrap mass spectrometers have been used for biomarker discovery from cerebrospinal fluid (CSF) in a variety of neurological diseases, these Orbitrap-derived datasets cannot readily be applied for driving experiments on timsTOF mass spectrometers. We generated a catalog of peptides and proteins in human CSF in DDA mode on a timsTOF mass spectrometer and used these data to build a spectral library. This strategy allowed us to use elution times and ion mobility values from the spectral library to design PRM experiments for quantifying previously discovered biomarkers from CSF samples in Alzheimer's disease. When the same samples were analyzed using a DIA approach combined with a spectral library search, a higher number of proteins were identified than in a library-free approach. Overall, we have established a spectral library of CSF as a resource and demonstrated its utility for PRM and DIA studies, which should facilitate studies of neurological disorders.

Cerebrospinal fluid lipidomics for biomarkers of Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia and is associated with serious neurologic sequelae resulting from neurodegenerative changes. Identification of markers of early-stage AD could be important for designing strategies to arrest the progression of the disease. The brain is rich in lipids because they are crucial for signal transduction and anchoring of membrane proteins. Cerebrospinal fluid (CSF) is an excellent specimen for studying the metabolism of lipids in AD because it can reflect changes occurring in the brain. We aimed to identify CSF lipidomic alterations associated with AD, using untargeted lipidomics, carried out in positive and negative ion modes. We found CSF lipids that were significantly altered in AD cases. In addition, comparison of CSF lipid profiles between persons with mild cognitive impairment (MCI) and AD showed a strong positive correlation between the lipidomes of the MCI and AD groups. The novel lipid biomarkers identified in this study are excellent candidates for validation in a larger set of patient samples and as predictive biomarkers of AD through future longitudinal studies. Once validated, the lipid biomarkers could lead to early detection, disease monitoring and the ability to measure the efficacy of potential therapeutic interventions in AD.

Proteomic and phosphoproteomic profiling of shammah induced signaling in oral keratinocytes.

Shammah is a smokeless tobacco product often mixed with lime, ash, black pepper and flavorings. Exposure to shammah has been linked with dental diseases and oral squamous cell carcinoma. There is limited literature on the prevalence of shammah and its role in pathobiology of oral cancer. In this study, we developed a cellular model to understand the effect of chronic shammah exposure on oral keratinocytes. Chronic exposure to shammah resulted in increased proliferation and invasiveness of non-transformed oral keratinocytes. Quantitative proteomics of shammah treated cells compared to untreated cells led to quantification of 4712 proteins of which 402 were found to be significantly altered. In addition, phosphoproteomics analysis of shammah treated cells compared to untreated revealed hyperphosphorylation of 36 proteins and hypophosphorylation of 83 proteins (twofold, p-value ≤ 0.05). Bioinformatics analysis of significantly altered proteins showed enrichment of proteins involved in extracellular matrix interactions, necroptosis and peroxisome mediated fatty acid oxidation. Kinase-Substrate Enrichment Analysis showed significant increase in activity of kinases such as ROCK1, RAF1, PRKCE and HIPK2 in shammah treated cells. These results provide better understanding of how shammah transforms non-neoplastic cells and warrants additional studies that may assist in improved early diagnosis and treatment of shammah induced oral cancer.

A network map of thrombopoietin signaling.

Thrombopoietin (THPO), also known as megakaryocyte growth and development factor (MGDF), is a cytokine involved in the production of platelets. THPO is a glycoprotein produced by liver and kidney. It regulates the production of platelets by stimulating the differentiation and maturation of megakaryocyte progenitors. It acts as a ligand for MPL receptor, a member of the hematopoietic cytokine receptor superfamily and is essential for megakaryocyte maturation. THPO binding induces homodimerization of the receptor which results in activation of JAKSTAT and MAPK signaling cascades that subsequently control cellular proliferation, differentiation and other signaling events. Despite the importance of THPO signaling in various diseases and biological processes, a detailed signaling network of THPO is not available in any publicly available database. Therefore, in this study, we present a resource of signaling events induced by THPO that was manually curated from published literature on THPO. Our manual curation of thrombopoietin pathway resulted in identification of 48 molecular associations, 66 catalytic reactions, 100 gene regulation events, 19 protein translocation events and 43 activation/inhibition reactions that occur upon activation of thrombopoietin receptor by THPO. THPO signaling pathway is made available on NetPath, a freely available human signaling pathway resource developed previously by our group. We believe this resource will provide a platform for scientific community to accelerate further research in this area on potential therapeutic interventions.

Cigarette smoke and chewing tobacco alter expression of different sets of miRNAs in oral keratinocytes.

Carcinogenic effect of tobacco in oral cancer is through chewing and/or smoking. Significant differences exist in development of oral cancer between tobacco users and non-users. However, molecular alterations induced by different forms of tobacco are yet to be fully elucidated. We developed cellular models of chronic exposure to chewing tobacco and cigarette smoke using immortalized oral keratinocytes. Chronic exposure to tobacco resulted in increased cell scattering and invasiveness in immortalized oral keratinocytes. miRNA sequencing using Illumina HiSeq 2500 resulted in the identification of 10 significantly dysregulated miRNAs (4 fold; p ≤ 0.05) in chewing tobacco treated cells and 6 in cigarette smoke exposed cells. We integrated this data with global proteomic data and identified 36 protein targets that showed inverse expression pattern in chewing tobacco treated cells and 16 protein targets that showed inverse expression in smoke exposed cells. In addition, we identified 6 novel miRNAs in chewing tobacco treated cells and 18 novel miRNAs in smoke exposed cells. Integrative analysis of dysregulated miRNAs and their targets indicates that signaling mechanisms leading to oncogenic transformation are distinct between both forms of tobacco. Our study demonstrates alterations in miRNA expression in oral cells in response to two frequently used forms of tobacco.