Proteomics analysis of differentially abundant proteins in the rohu kidney infected with Edwardsiella tarda.

Edwardsiella tarda (Et) is a zoonotic gram-negative pathogen with a diverse host range, including fish. However, the in-depth molecular mechanisms underlying the response of Labeo rohita (rohu) kidney to Et are poorly understood. A proteomic and histopathological analysis was performed for the rohu kidney after Et infection. The histopathology of the infected rohu kidney showed vacuolation and necrosis. After LC-MS/MS analysis, ~1240 proteins were identified with ≥2 unique peptides. A total of 96 differentially abundant proteins (DAPs) were observed between the control and Et infected group (ET). Metascape and STRING analysis were used for the gene ontology (GO), and protein-protein interaction network (PPI) for the significant pathways of DAPs. In PPI, low-abundant proteins were mapped to metabolic pathways and oxidative phosphorylation (cox5ab, uqcrfs1). High-abundance proteins were mapped to ribosomes (rplp2), protein process in the ER (hspa8), and immune system (ptgdsb.1, muc2). Our label-free proteomic approach in the rohu kidney revealed abundant enriched proteins involved in vesicle coat (ehd4), complement activation (c3a.1, c9, c7a), phagosome (thbs4, mapk1), metabolic reprogramming (hao1, glud1a), wound healing (vim, alox5), and the immune system (psap) after Et infection. A targeted proteomics approach of multiple reaction monitoring (MRM) validated the DAPs (nprl3, ambp, vmo1a, hspg2, muc2, hao1 and glud1a) between control and ET. Overall, the current analysis of histology and proteome in the rohu kidney provides comprehensive data on pathogenicity and the potential immune proteins against Et.

IL-17A Orchestrates Reactive Oxygen Species/HIF1α-Mediated Metabolic Reprogramming in Psoriasis.

Immune cell-derived IL-17A is one of the key pathogenic cytokines in psoriasis, an immunometabolic disorder. Although IL-17A is an established regulator of cutaneous immune cell biology, its functional and metabolic effects on nonimmune cells of the skin, particularly keratinocytes, have not been comprehensively explored. Using multiomics profiling and systems biology-based approaches, we systematically uncover significant roles for IL-17A in the metabolic reprogramming of human primary keratinocytes (HPKs). High-throughput liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy revealed IL-17A-dependent regulation of multiple HPK proteins and metabolites of carbohydrate and lipid metabolism. Systems-level MitoCore modeling using flux-balance analysis identified IL-17A-mediated increases in HPK glycolysis, glutaminolysis, and lipid uptake, which were validated using biochemical cell-based assays and stable isotope-resolved metabolomics. IL-17A treatment triggered downstream mitochondrial reactive oxygen species and HIF1α expression and resultant HPK proliferation, consistent with the observed elevation of these downstream effectors in the epidermis of patients with psoriasis. Pharmacological inhibition of HIF1α or reactive oxygen species reversed IL-17A-mediated glycolysis, glutaminolysis, lipid uptake, and HPK hyperproliferation. These results identify keratinocytes as important target cells of IL-17A and reveal its involvement in multiple downstream metabolic reprogramming pathways in human skin.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy.

INTRODUCTION: Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation. AREAS COVERED: This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches. EXPERT OPINION: Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Brain tumors are complex and diverse types of cancer that present significant challenges in their diagnosis, prognosis, and treatment. Proteomics, a field that focuses on studying proteins and their functions on a large scale has emerged as a powerful tool for understanding how brain tumors work at the molecular level. In this review, we offer a detailed look into the role of proteomics in studying brain tumor regulation, discussing recent advancements and insights gained from proteomic techniques. We explore various mass spectrometry-based proteomic methods, which help uncover unique protein patterns associated with brain tumors. By analyzing changes in protein expression, modifications, interactions, and location within cells, researchers have gained important knowledge about the underlying mechanisms of brain tumors. Proteomics also plays a crucial role in identifying potential biomarkers for early detection, predicting patient outcomes, and developing targeted therapies and immunotherapies. However, there are still challenges to overcome, such as integrating data from different 'omics' fields, standardizing protocols and analysis procedures and utilizing artificial intelligence to interpret complex proteomic data. We require more robust attempts at validating and translating all these findings for patient benefit.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai.

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Mass spectrometry and proteome analysis to identify SARS-CoV-2 protein from COVID-19 patient swab samples.

With new emerging SARS-CoV-2 strains and their increased pathogenicity, diagnosis has become more challenging. Molecular diagnosis often involves the use of nasopharyngeal swabs and subsequent real-time PCR-based tests. Although this test is the gold standard, it has several limitations; therefore, more complementary assays are required. This protocol describes how to identify SARS-CoV-2 protein from patients' nasopharyngeal swab samples. We first introduce the approach of label-free quantitative proteomics. We then detail target verification by triple quadrupole mass spectrometry (MS)-based targeted proteomics. For complete details on the use and execution of this profile, please refer to Bankar et al. (2021).

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue.

The proteomic analysis of the human brain tissue over the last decade has greatly enhanced our understanding of the brain. However, brain related disorders continue to be a major contributor of deaths around the world, necessitating the need for even greater understanding of their pathobiology. Traditional antibody-based techniques like western blotting or immunohistochemistry suffer from being low-throughput besides being labor-intensive and qualitative or semi-quantitative. Even conventional mass spectrometry-based shotgun approaches fail to provide conclusive evidence to support a certain hypothesis. Targeted proteomics approaches are largely hypothesis driven and differ from the conventional shotgun proteomics approaches that have been long in use. Multiple reaction monitoring is one such targeted approach that requires the use of a special mass spectrometer called the tandem quadrupole mass spectrometer or triple quadrupole mass spectrometer. In the current study, we have systematically highlighted the major steps involved in performing a successful tandem quadrupole mass spectrometry-based proteomics workflow using human brain tissue with an aim to introduce this workflow to a broader research community.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

Multiple Reaction Monitoring-Based Targeted Assays for the Validation of Protein Biomarkers in Brain Tumors.

The emergence of omics technologies over the last decade has helped in advancement of research and our understanding of complex diseases like brain cancers. However, barring genomics, no other omics technology has been able to find utility in clinical settings. The recent advancements in mass spectrometry instrumentation have resulted in proteomics technologies becoming more sensitive and reliable. Targeted proteomics, a relatively new branch of mass spectrometry-based proteomics has shown immense potential in addressing the shortcomings of the standard molecular biology-based techniques like Western blotting and Immunohistochemistry. In this study we demonstrate the utility of Multiple reaction monitoring (MRM), a targeted proteomics approach, in quantifying peptides from proteins like Apolipoprotein A1 (APOA1), Apolipoprotein E (APOE), Prostaglandin H2 D-Isomerase (PTGDS), Vitronectin (VTN) and Complement C3 (C3) in cerebrospinal fluid (CSF) collected from Glioma and Meningioma patients. Additionally, we also report transitions for peptides from proteins - Vimentin (VIM), Cystatin-C (CST3) and Clusterin (CLU) in surgically resected Meningioma tissues; Annexin A1 (ANXA1), Superoxide dismutase (SOD2) and VIM in surgically resected Glioma tissues; and Microtubule associated protein-2 (MAP-2), Splicing factor 3B subunit 2 (SF3B2) and VIM in surgically resected Medulloblastoma tissues. To our knowledge, this is the first study reporting the use of MRM to validate proteins from three types of brain malignancies and two different bio-specimens. Future studies involving a large cohort of samples aimed at accurately detecting and quantifying peptides of proteins with roles in brain malignancies could potentially result in a panel of proteins showing ability to classify and grade tumors. Successful application of these techniques could ultimately offer alternative strategies with increased accuracy, sensitivity and lower turnaround time making them translatable to the clinics.

Proteomic investigation reveals dominant alterations of neutrophil degranulation and mRNA translation pathways in patients with COVID-19.

The altered molecular proteins and pathways in response to COVID-19 infection are still unclear. Here, we performed a comprehensive proteomics-based investigation of nasopharyngeal swab samples from patients with COVID-19 to study the host response by employing simple extraction strategies. Few of the host proteins such as interleukin-6, L-lactate dehydrogenase, C-reactive protein, Ferritin, and aspartate aminotransferase were found to be upregulated only in COVID-19-positive patients using targeted multiple reaction monitoring studies. The most important pathways identified by enrichment analysis were neutrophil degranulation, interleukin-12 signaling pathways, and mRNA translation of proteins thus providing the detailed investigation of host response in COVID-19 infection. Thus, we conclude that mass spectrometry-detected host proteins have a potential for disease severity progression; however, suitable validation strategies should be deployed for the clinical translation. Furthermore, the in silico docking of potential drugs with host proteins involved in the interleukin-12 signaling pathway might aid in COVID-19 therapeutic interventions.