Bhat, Firdous Ahmad

ABSTRACT T‐cell receptor (TCR) signaling plays a crucial role in various biological processes and is usually studied using global mass spectrometry‐based phosphoproteomic studies. Despite advancements in targeted mass spectrometry‐based assays for protein quantification, their application in studying signaling processes, for example, reproducible measurements of post‐translational modifications (PTMs) such as phosphorylation, remains limited. Tyrosine phosphorylation is critical for many signaling pathways but presents challenges due to the low abundance of phosphotyrosine‐containing peptides. Conventional untargeted methods often encounter data gaps when analyzing large sample sets, particularly for low‐abundance peptides. To address this issue, a targeted proteomics method called “SureQuant” was employed, which relies on triggered data acquisition with heavy isotope‐labeled peptides. This method has been shown to provide sensitive and reproducible quantification of low‐abundance peptides. Here we describe the development of a SureQuant‐based method to quantify phosphotyrosine peptides that are involved in the TCR signaling pathway. To monitor the change in phosphotyrosine signals upon activation, the T‐cells were stimulated with anti‐CD3/CD28 antibodies. We successfully quantified changes in important phosphotyrosine peptides in primary T‐cells upon stimulation with anti‐CD3/CD28 antibodies. This study showcases the ability of the SureQuant approach to accurately quantify low‐abundance phosphotyrosine peptides, highlighting its broader potential to study a diverse set of PTMs in physiological or clinical settings. Summary T‐cell receptor (TCR) signaling plays a fundamental role in immune responses, regulating T‐cell activation, differentiation, and function. While tyrosine phosphorylation is a key regulatory mechanism in this pathway, the low abundance of phosphotyrosine peptides presents a major challenge for their detection and quantification in complex biological samples. By employing the SureQuant targeted mass spectrometry approach, we achieved highly sensitive and reproducible quantification of key phosphotyrosine sites involved in T‐cell activation. This study provides a systematic view of TCR signaling dynamics, revealing distinct phosphorylation patterns across different activation timepoints. Our findings demonstrate the effectiveness of SureQuant in quantifying low‐abundance, post‐translationally modified peptides, offering a valuable tool for studying signaling pathways with greater precision. Additionally, this methodological framework can be extended to investigate other signaling networks, immune cell functions, and disease‐associated phosphotyrosine modifications.

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

We present optimized settings for ramp times and ion mobility range in trapped ion mobility spectrometry experiments involving single cell analysis.

Abstract 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.

Abstract 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.