Metaproteomics for Coinfections in the Upper Respiratory Tract: The Case of COVID-19.

The upper respiratory tract (URT) is home to a diverse range of microbial species. Respiratory infections disturb the microbial flora in the URT, putting people at risk of secondary infections. The potential dangers and clinical effects of bacterial and fungal coinfections with SARS-CoV-2 support the need to investigate the microbiome of the URT using clinical samples. Mass spectrometry (MS)-based metaproteomics analysis of microbial proteins is a novel approach to comprehensively assess the clinical specimens with complex microbial makeup. The coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2) is responsible for the COVID-19 pandemic resulting in a plethora of microbial coinfections impeding therapy, prognosis, and overall disease management. In this chapter, the corresponding workflows for MS-based shotgun proteomics and metaproteomic analysis are illustrated.

Giant Virus Global Proteomics Innovation: Comparative Evaluation of In-Gel and In-Solution Digestion Methods.

With their unusually large genome and particle sizes, giant viruses (GVs) defy the conventional definition of viruses. Although most GVs isolated infect unicellular protozoans, such as amoeba, studies in the last decade have established their much wider prevalence infecting most eukaryotic supergroups and some giant viral families with the potential to be human pathogens. Their complexity, almost autonomous life cycle, and enigmatic evolution necessitate the study of GVs. The accurate assessment of GV proteome is a veritable challenge. We have compared the coverage of global protein identification using different methods for GVs isolated in Mumbai, Mimivirus Bombay (MVB), Powai Lake Megavirus (PLMV), and Kurlavirus (KV), along with two previously studied GVs, Acanthamoeba polyphaga Mimivirus (APMV) and Marseillevirus (MV). Our study shows that the simultaneous use of in-gel and in-solution digestion methods can significantly increase the coverage of protein identification in the global proteome analysis of purified GV particles. Combining the two methods of analyses, we identified an additional 72 proteins in APMV and 114 in MV compared with what have been previously reported. Similarly, proteomes of MVB, PLMV, and KV were analyzed, and a total of 242 proteins in MVB, 287 proteins in PLMV, and 174 proteins in KV were identified. Our results suggest that a combined methodology of in-gel and in-solution methods is more efficient and opens up new avenues for innovation in global proteome analysis of GVs. Future planetary health research on GVs can benefit from consideration of a broader range of proteomics methodologies as illustrated by the present study.

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.

Multitarget Potential Drug Candidates for High-Grade Gliomas Identified by Multiple Reaction Monitoring Coupled with In Silico Drug Repurposing.

High-grade gliomas (HGGs) are extremely aggressive primary brain tumors with high mortality rates. Despite notable progress achieved by clinical research and biomarkers emerging from proteomics studies, efficacious drugs and therapeutic targets are limited. This study used targeted proteomics, in silico molecular docking, and simulation-based drug repurposing to identify potential drug candidates for HGGs. Importantly, we performed multiple reaction monitoring (MRM) on differentially expressed proteins with putative roles in the development and progression of HGGs based on our previous work and the published literature. Furthermore, in silico molecular docking-based drug repurposing was performed with a customized library of FDA-approved drugs to identify multitarget-directed ligands. The top drug candidates such as Pazopanib, Icotinib, Entrectinib, Regorafenib, and Cabozantinib were explored for their drug-likeness properties using the SwissADME. Pazopanib exhibited binding affinities with a maximum number of proteins and was considered for molecular dynamic simulations and cell toxicity assays. HGG cell lines showed enhanced cytotoxicity and cell proliferation inhibition with Pazopanib and Temozolomide combinatorial treatment compared to Temozolomide alone. To the best of our knowledge, this is the first study combining MRM with molecular docking and simulation-based drug repurposing to identify potential drug candidates for HGG. While the present study identified five multitarget-directed potential drug candidates, future clinical studies in larger cohorts are crucial to evaluate the efficacy of these molecular candidates. The research strategy and methodology used in the present study offer new avenues for innovation in drug discovery and development which may prove useful, particularly for cancers with low cure rates.

CoVProt: Toward a Mass Spectrometry Data Portal for COVID-19 Proteomics Research and Development.

The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc globally. Beyond the pandemic, the long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in multiple organ systems are yet to be deciphered. This calls for continued systems science research. Moreover, the host response to SARS-CoV-2 varies person-to-person and gives rise to different degrees of morbidity and mortality. Mass spectrometry (MS) has been a proven asset in studies of the SARS-CoV-2 from an omics systems science lens. To strengthen the proteomics research dedicated to COVID-19, we introduce here a web-based portal, CoVProt. The portal is work in progress and aims for a comprehensive curation of MS-based proteomics data of COVID-19 clinical samples for deep proteomic investigations, data visualization, and easy data accessibility for life sciences innovations and planetary health research community. Currently, CoVProt contains information on 2725 different proteins and 37,125 different peptides from six data sets covering a total of 202 clinical samples. Moreover, all pertinent data sets extracted from the literature have been reanalyzed using a common analysis pipeline developed by combining multiple tools. Going forward, we anticipate that the CoVProt portal will also provide access to the clinical parameters of the patients. The CoVProt (v1.0) portal addresses an existing significant gap to study COVID-19 host proteomics, which, to the best of our knowledge, is the first effort in this direction. We believe that CoVProt is poised to make contributions as a community resource for proteomic applications and aims to broadly support clinical studies to facilitate the discovery of COVID-19 biomarkers and therapeutics with translational potential.

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.

High-Grade Gliomas from Subventricular Zone: Proteomic Drivers of Aggressiveness Using Fluorescence-Guided Multiple Sampling.

High-grade gliomas (HGGs) are among the most aggressive brain tumors and are characterized by dismally low median survival time. Of the many factors influencing the survival of patients with HGGs, proximity to the subventricular zone (SVZ) is one of the key influencers. In this context, 5-amino levulinic acid fluorescence-guided multiple sampling (FGMS) offers the prospect of understanding patient-to-patient molecular heterogeneity driving the aggressiveness of these tumors. Using high-resolution liquid chromatography-mass spectrometry (MS)/MS proteomics for HGGs from seven patients (four SVZ associated and three SVZ nonassociated), this study aimed to uncover the mechanisms driving the aggressiveness in SVZ-associated (SVZ+) HGGs. Differential proteomics analysis revealed significant dysregulation of 11 proteins, of which 9 proteins were upregulated and 2 were downregulated in SVZ+ HGGs compared to SVZ-non-associated (SVZ-) HGGs. The gene set enrichment analysis (GSEA) of the proteomics dataset revealed enrichment of MYC targets V1 and V2, G2M checkpoints, and E2F targets in SVZ+ HGGs. With GSEA, we also compared the pathways enriched in glioma stem cell subpopulations and observed a similar expression trend for most pathways in our data. In conclusion, this study reveals new and emerging insights on pathways that may potentially contribute to greater aggressiveness in SVZ+ HGGs. Future studies using FGMS in larger cohorts are recommended to help uncover the proteomics and molecular basis of aggressiveness and stemness in HGGs.

Molecular Mechanisms and the Interplay of Important Chronic Obstructive Pulmonary Disease Biomarkers Reveals Novel Therapeutic Targets.

Chronic Obstructive Pulmonary Disease (COPD) is a progressive, age-dependent, and unmet chronic inflammatory disease of the peripheral airways, leading to difficulty in exhalation. Several biomarkers have been tested in general towards the resolution for a long time, but no apparent success was achieved. Ongoing therapies of COPD have only symptomatic relief but no cure. Reactive oxygen species (ROS) are highly reactive species which include oxygen radicals and nonradical derivatives, and are the prominent players in COPD. They are produced as natural byproducts of cellular metabolism, but their levels can vary due to exposure to indoor air pollution, occupational pollution, and environmental pollutants such as cigarette smoke. In COPD, the lungs are continuously exposed to high levels of ROS thus leading to oxidative stress. ROS can cause damage to cells, proteins, lipids, and DNA which further contributes to the chronic inflammation in COPD and exacerbates the disease condition. Excessive ROS production can overwhelm cellular antioxidant systems and act as signaling molecules that regulate cellular processes, including antioxidant defense mechanisms involving glutathione and sirtuins which further leads to cellular apoptosis, cellular senescence, inflammation, and sarcopenia. In this review paper, we focused on COPD from different perspectives including potential markers and different cellular processes such as apoptosis, cellular senescence, inflammation, sirtuins, and sarcopenia, and tried to connect the dots between them so that novel therapeutic strategies to evaluate and target the possible underlying mechanisms in COPD could be explored.

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.

Semen proteomics reveals alterations in fertility-related proteins post-recovery from COVID-19.

Introduction: Changes to sperm quality and decline in reproductive function have been reported in COVID-19-recovered males. Further, the emergence of SARS-CoV-2 variants has caused the resurgences of COVID-19 cases globally during the last 2 years. These variants show increased infectivity and transmission along with immune escape mechanisms, which threaten the already burdened healthcare system. However, whether COVID-19 variants induce an effect on the male reproductive system even after recovery remains elusive. Methods: We used mass-spectrometry-based proteomics approaches to understand the post-COVID-19 effect on reproductive health in men using semen samples post-recovery from COVID-19. The samples were collected between late 2020 (1st wave, n = 20), and early-to-mid 2021 (2nd wave, n = 21); control samples were included (n = 10). During the 1st wave alpha variant was prevalent in India, whereas the delta variant dominated the second wave. Results: On comparing the COVID-19-recovered patients from the two waves with control samples, using one-way ANOVA, we identified 69 significantly dysregulated proteins among the three groups. Indeed, this was also reflected by the changes in sperm count, morphology, and motility of the COVID-19- recovered patients. In addition, the pathway enrichment analysis showed that the regulated exocytosis, neutrophil degranulation, antibacterial immune response, spermatogenesis, spermatid development, regulation of extracellular matrix organization, regulation of peptidase activity, and regulations of calcium ion transport were significantly dysregulated. These pathways directly or indirectly affect sperm parameters and function. Our study provides a comprehensive landscape of expression trends of semen proteins related to male fertility in men recovering from COVID-19. Discussion: Our study suggests that the effect of COVID-19 on the male reproductive system persists even after recovery from COVID-19. In addition, these post-COVID-19 complications persist irrespective of the prevalent variants or vaccination status.

Integrated Meta-Omics Analysis Unveils the Pathways Modulating Tumorigenesis and Proliferation in High-Grade Meningioma.

Meningioma, a primary brain tumor, is commonly encountered and accounts for 39% of overall CNS tumors. Despite significant progress in clinical research, conventional surgical and clinical interventions remain the primary treatment options for meningioma. Several proteomics and transcriptomics studies have identified potential markers and altered biological pathways; however, comprehensive exploration and data integration can help to achieve an in-depth understanding of the altered pathobiology. This study applied integrated meta-analysis strategies to proteomic and transcriptomic datasets comprising 48 tissue samples, identifying around 1832 common genes/proteins to explore the underlying mechanism in high-grade meningioma tumorigenesis. The in silico pathway analysis indicated the roles of extracellular matrix organization (EMO) and integrin binding cascades in regulating the apoptosis, angiogenesis, and proliferation responsible for the pathobiology. Subsequently, the expression of pathway components was validated in an independent cohort of 32 fresh frozen tissue samples using multiple reaction monitoring (MRM), confirming their expression in high-grade meningioma. Furthermore, proteome-level changes in EMO and integrin cell surface interactions were investigated in a high-grade meningioma (IOMM-Lee) cell line by inhibiting integrin-linked kinase (ILK). Inhibition of ILK by administrating Cpd22 demonstrated an anti-proliferative effect, inducing apoptosis and downregulating proteins associated with proliferation and metastasis, which provides mechanistic insight into the disease pathophysiology.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.

BACKGROUND: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. METHODS: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. RESULTS: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. CONCLUSIONS: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

A Proteomics Investigation of Cigarette Smoke Exposed Wistar Rats Revealed Improved Anti-Inflammatory Effects of the Cysteamine Nanoemulsions Delivered via Inhalation.

Cigarette smoking is the major cause of chronic inflammatory diseases such as chronic obstructive pulmonary disease (COPD). It is paramount to develop pharmacological interventions and delivery strategies against the cigarette smoke (CS) associated oxidative stress in COPD. This study in Wistar rats examined cysteamine in nanoemulsions to counteract the CS distressed microenvironment. In vivo, 28 days of CS and 15 days of cysteamine nanoemulsions treatment starting on 29th day consisting of oral and inhalation routes were established in Wistar rats. In addition, we conducted inflammatory and epithelial-to-mesenchymal transition (EMT) studies in vitro in human bronchial epithelial cell lines (BEAS2B) using 5% CS extract. Inflammatory and anti-inflammatory markers, such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, IL-1ß, IL-8, IL-10, and IL-13, have been quantified in bronchoalveolar lavage fluid (BALF) to evaluate the effects of the cysteamine nanoemulsions in normalizing the diseased condition. Histopathological analysis of the alveoli and the trachea showed the distorted, lung parenchyma and ciliated epithelial barrier, respectively. To obtain mechanistic insights into the CS COPD rat model, "shotgun" proteomics of the lung tissues have been carried out using high-resolution mass spectrometry wherein genes such as ABI1, PPP3CA, PSMA2, FBLN5, ACTG1, CSNK2A1, and ECM1 exhibited significant differences across all the groups. Pathway analysis showed autophagy, signaling by receptor tyrosine kinase, cytokine signaling in immune system, extracellular matrix organization, and hemostasis, as the major contributing pathways across all the studied groups. This work offers new preclinical findings on how cysteamine taken orally or inhaled can combat CS-induced oxidative stress.

Metaproteomic Analysis of Nasopharyngeal Swab Samples to Identify Microbial Peptides in COVID-19 Patients.

During the COVID-19 pandemic, impaired immunity and medical interventions resulted in cases of secondary infections. The clinical difficulties and dangers associated with secondary infections in patients necessitate the exploration of their microbiome. Metaproteomics is a powerful approach to study the taxonomic composition and functional status of the microbiome under study. In this study, the mass spectrometry (MS)-based data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. We have established a robust bioinformatics workflow within the Galaxy platform, which includes (a) generation of a tailored database of the common respiratory tract pathogens, (b) database search using multiple search algorithms, and (c) verification of the detected microbial peptides. The microbial peptides detected in this study, belong to several opportunistic pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were found to be upregulated in severe patients compared to negative patients. Using parallel reaction monitoring (PRM), we confirmed some of the microbial peptides in fresh clinical samples. MS-based clinical metaproteomics can serve as a powerful tool for detection and characterization of potential pathogens, which can significantly impact the diagnosis and treatment of patients.

Biochemical Reconstitution of the Mimiviral Base Excision Repair Pathway.

Viruses are believed to be the obligate intracellular parasites that only carry genes essential for infecting and hijacking the host cell machinery. However, a recently discovered group of viruses belonging to the phylum nucleocytovirocota, also known as the nucleo-cytoplasmic large DNA viruses (NCLDVs), possess a number of genes that code for proteins predicted to be involved in metabolism, and DNA replication, and repair. In the present study, first, using proteomics of viral particles, we show that several proteins required for the completion of the DNA base excision repair (BER) pathway are packaged within the virions of Mimivirus as well as related viruses while they are absent from the virions of Marseillevirus and Kurlavirus that are NCLDVs with smaller genomes. We have thoroughly characterized three putative base excision repair enzymes from Mimivirus, a prototype NCLDV and successfully reconstituted the BER pathway using the purified recombinant proteins. The mimiviral uracil-DNA glycosylase (mvUDG) excises uracil from both ssDNA and dsDNA, a novel finding contrary to earlier studies. The putative AP-endonuclease (mvAPE) specifically cleaves at the abasic site created by the glycosylase while also exhibiting the 3'-5' exonuclease activity. The Mimivirus polymerase X protein (mvPolX) can bind to gapped DNA substrates and perform single nucleotide gap-filling followed by downstream strand displacement. Furthermore, we show that when reconstituted in vitro, mvUDG, mvAPE, and mvPolX function cohesively to repair a uracil-containing DNA predominantly by long patch BER and together, may participate in the BER pathway during the early phase of Mimivirus life-cycle.

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.

Deep proteome investigation of high-grade gliomas reveals heterogeneity driving differential metabolism of 5-aminolevulinic acid.

Background: Fluorescence-guided surgery (FGS) using 5-aminolevulinic acid (5-ALA) as adjunct for high-grade gliomas (HGGs) has been on the rise in recent years. Despite being largely effective, we observed multiple histologically similar sub-regions of the same tumor from a few individuals with varying protoporphyrin IX (PpIX) levels. The current study aims at understanding the proteomic changes driving differential metabolism of 5-ALA in HGGs. Methods: Biopsies were histologically and biochemically assayed. Following this, a deep proteomics investigation was carried out using high resolution liquid chromatography-mass spectrometry (HR LC-MS) to identify protein expression in differentially fluorescing regions of HGGs. Results: Our analysis identified 5437 proteins with high confidence. Differential analysis in the subgroup with HGGs carrying IDH mutation (IDH mt.) revealed 93 differentially regulated proteins (raw p-value ≤ 0.05 and absolute FC ≥ 1.5). Similar analysis in the IDH wild type (IDH wt.) subgroup revealed 20 differentially regulated proteins. Gene set enrichment analysis (GSEA) identified key pathways like ion channel transport, trafficking of AMPA receptors, and regulation of heme-oxygenase-1 in the IDH wt. subgroup. Pathways such as scavenging of heme, signaling by NOTCH4, negative regulation of PI3-AKT pathway, and iron uptake and transport were observed to be differentially regulated in the IDH mt. subgroup. Conclusions: Tumor regions from the same patient exhibiting differential fluorescence following 5-ALA administration were observed to have different proteome profiles. Future studies aimed at a better molecular understanding of 5-ALA metabolism in HGGs hold the potential to increase the efficacy of FGS and the use of 5-ALA as a theragnostic tool.

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome.

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of applications. The cell surface proteome ("surfaceome") in human disease is of significant interest, as plasma membrane proteins are the primary target of most clinically approved therapeutics, as well as a key feature by which to diagnostically distinguish diseased cells from healthy tissues. However, focused characterization of membrane and surface proteins of the cell has remained challenging, primarily due to the complexity of cellular lysates, which mask proteins of interest by other high-abundance proteins. To overcome this technical barrier and accurately define the cell surface proteome of various cell types using mass spectrometry proteomics, it is necessary to enrich the cell lysate for cell surface proteins prior to analysis on the mass spectrometer. This paper presents a detailed workflow for labeling cell surface proteins from cancer cells, enriching these proteins out of the cell lysate, and subsequent sample preparation for mass spectrometry analysis.

Detection of Mutant Peptides of SARS-CoV-2 Variants by LC/MS in the DDA Approach Using an In-House Database.

Equipped with a dramatically high mutation rate, which happens to be a signature of RNA viruses, SARS-CoV-2 trampled across the globe infecting individuals of all ages and ethnicities. As the variants of concern (VOC) loomed large, definitive detection of SARS-CoV-2 strains became a matter of utmost importance in epidemiological and clinical research. Besides, unveiling the disease pathogenesis at the molecular level and deciphering the therapeutic targets became key priorities since the emergence of the pandemic. Mass spectrometry has been largely used in this regard. A critical part of mass spectrometric analyses is the proteome database required for the identification of peptides. Presently, the mutational information on proteins available on SARS-CoV-2 databases cannot be used to analyze data extracted from mass spectrometers. Hence, we developed the novel Mutant Peptide Database (MPD) for the mass spectrometry (MS)-based identification of mutated peptides, which contains information from 11 proteins of SARS-CoV-2 from a total of 21,549 SARS-CoV-2 variants across different regions of India. The database was validated using clinical samples, and its applicability was also demonstrated with the mutated peptides extracted from the literature. We believe that MPD will support broad-spectrum MS-based studies like viral detection, disease pathogenesis, and therapeutics with respect to SARS-CoV-2 and its variants.

Advances in Drug Discovery based on Genomics, Proteomics and Bioinformatics in Malaria.

Malaria is one of the neglected infectious diseases, and drugs are the first line of action taken against the onset of malaria as therapeutics. The drugs can be of either natural or artificial origin. Drug development has multiple impediments grouped under three categories, a. drug discovery and screening, b. the drug's action on the host and the pathogen, and c. clinical trials. Drug development takes coon's age from discovery to the market after FDA approval. At the same time, targeted organisms develop drug resistance quicker than drug approval, raising the requirement for advancement in drug development. The approach to explore drug candidates using the classical methods from natural sources, computation-based docking, mathematical and machine learningbased high throughput in silico models or drug repurposing has been investigated and developed. Also, drug development with information about the interaction between Plasmodium species and its host, humans, may facilitate obtaining an efficient drug cohort for further drug discovery or repurposing expedition. However, drugs may have side effects on the host system. Hence, machine learning and systems-based approaches may provide a holistic view of genomic, proteomic, and transcriptomic data and their interaction with the selected drug candidates. This review comprehensively describes the drug discovery workflows using drug and target screening methodologies, followed by possible ways to check the binding affinity of the drug and targets using various docking software.