Proteome data of neuroblastoma cells overexpressing Neuroglobin

Methylmalonic acidemia triggers lysosomal-autophagy dysfunctions

BACKGROUND

Methylmalonic acidemia (MMA) is a rare inborn error of propionate metabolism caused by deficiency of the mitochondrial methylmalonyl-CoA mutase (MUT) enzyme. As matter of fact, MMA patients manifest impairment of the primary metabolic network with profound damages that involve several cell components, many of which have not been discovered yet. We employed cellular models and patients-derived fibroblasts to refine and uncover new pathologic mechanisms connected with MUT deficiency through the combination of multi-proteomics and bioinformatics approaches.

RESULTS

Our data show that MUT deficiency is connected with profound proteome dysregulations, revealing molecular actors involved in lysosome and autophagy functioning. To elucidate the effects of defective MUT on lysosomal and autophagy regulation, we analyzed the morphology and functionality of MMA-lysosomes that showed deep alterations, thus corroborating omics data. Lysosomes of MMA cells present as enlarged vacuoles with low degradative capabilities. Notwithstanding, treatment with an anti-propionigenic drug is capable of totally rescuing lysosomal morphology and functional activity in MUT-deficient cells. These results indicate a strict connection between MUT deficiency and lysosomal-autophagy dysfunction, providing promising therapeutic perspectives for MMA.

CONCLUSIONS

Defective homeostatic mechanisms in the regulation of autophagy and lysosome functions have been demonstrated in MUT-deficient cells. Our data prove that MMA triggers such dysfunctions impacting on autophagosome-lysosome fusion and lysosomal activity.

Analysis and functional relevance of the chaperone TRAP-1 interactome in the metabolic regulation and mitochondrial integrity of cancer cells

The 90 kDa heat shock protein, Hsp90, functions as a cancer chaperone contributing to tumor proliferation. We have encountered the mitochondrial homolog of Hsp90, the TRAP-1, regulating mitochondrial dynamics, metabolism, and tumor metastasis. Although Hsp90 is associated with a broad network of proteins regulating various cellular processes, TRAP-1-mediated cellular networks are unclear. Therefore, using TRAP-1 knockdown (KD) and overexpression (OE) systems, we compared their quantitative transcriptome (RNA Sequencing) and proteomic (LC-MS/MS) patterns to obtain molecular signatures that are altered in response to TRAP-1 KD or OE. We report TRAP-1 modulating vital metabolic pathways such as the tricarboxylic acid cycle, oxidative phosphorylation, electron transport chain, glycolysis, and gluconeogenesis. In addition, TRAP-1 facilitated the pentose phosphate pathway to shunt carbons back to glycolysis or gluconeogenesis, a much-solicited tumor response. Subsequently, we examined the TRAP-1 interactome using the tandem affinity purification system and identified 255 unique proteins. These diverse proteins appear to regulate several cellular processes, including energy metabolism, suggesting that TRAP-1, in addition to metabolic rewiring, maintains mitochondrial integrity. Our study exposes the unknown functions of TRAP-1 in cancer cells. Systematic evaluation of TRAP-1 interactors may uncover novel regulatory mechanisms in disease aggression. Since metabolic inhibitors are emerging as potential anticancer agents, our study gains importance.

Deciphering the Relationship between SARS-CoV-2 and Cancer

Some viruses are known to be associated with the onset of specific cancers. These microorganisms, oncogenic viruses or oncoviruses, can convert normal cells into cancer cells by modulating the central metabolic pathways or hampering genomic integrity mechanisms, consequently inhibiting the apoptotic machinery and/or enhancing cell proliferation. Seven oncogenic viruses are known to promote tumorigenesis in humans: human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV), Epstein-Barr virus (EBV), human T-cell leukemia virus 1 (HTLV-1), Kaposi sarcoma-associated herpesvirus (KSHV), and Merkel cell polyomavirus (MCPyV). Recent research indicates that SARS-CoV-2 infection and COVID-19 progression may predispose recovered patients to cancer onset and accelerate cancer development. This hypothesis is based on the growing evidence regarding the ability of SARS-CoV-2 to modulate oncogenic pathways, promoting chronic low-grade inflammation and causing tissue damage. Herein, we summarize the main relationships known to date between virus infection and cancer, providing a summary of the proposed biochemical mechanisms behind the cellular transformation. Mechanistically, DNA viruses (such as HPV, HBV, EBV, and MCPyV) encode their virus oncogenes. In contrast, RNA viruses (like HCV, HTLV-1) may encode oncogenes or trigger host oncogenes through cis-/-trans activation leading to different types of cancer. As for SARS-CoV-2, its role as an oncogenic virus seems to occur through the inhibition of oncosuppressors or controlling the metabolic and autophagy pathways in the infected cells. However, these effects could be significant in particular scenarios like those linked to severe COVID-19 or long COVID. On the other hand, looking at the SARS-CoV-2─cancer relationship from an opposite perspective, oncolytic effects and anti-tumor immune response were triggered by SARS-CoV-2 infection in some cases. In summary, our work aims to recall comprehensive attention from the scientific community to elucidate the effects of SARS-CoV-2 and, more in general, β-coronavirus infection on cancer susceptibility for cancer prevention or supporting therapeutic approaches.

Targeted lipidomics data of COVID-19 patients

The dataset provided with this article describes a targeted lipidomics analysis performed on the serum of COVID-19 patients characterized by different degree of severity. As the ongoing pandemic has posed a challenging threat for humanity, the data here presented belong to one of the first lipidomics studies carried out on COVID-19 patients’ samples collected during the first pandemic waves. Serum samples were obtained from hospitalized patients with a molecular diagnosis of SARS-CoV-2 infection detected after nasal swab, and categorized as mild, moderate, or severe according to pre-established clinical descriptors. The MS-based targeted lipidomic analysis was performed by MRM using a Triple Quad 5500+ mass spectrometer, and the quantitative data were acquired on a panel of 483 lipids. The characterization of this lipidomic dataset has been outlined using multivariate and univariate descriptive statistics and bioinformatics tools.

Sex-Gender-Based Differences in Metabolic Diseases

Sexual dimorphism creates different biological and cellular activities and selective regulation mechanisms in males and females, thus generating differential responses in health and disease. In this scenario, the sex itself is a source of physiologic metabolic disparities that depend on constitutive genetic and epigenetic features that characterize in a specific manner one sex or the other. This has as a direct consequence a huge impact on the metabolic routes that drive the phenotype of an individual. The impact of sex is being clearly recognized also in disease, whereas male and females are more prone to the development of some disorders, or have selective responses to drugs and therapeutic treatments. Actually, very less is known regarding the probable differences guided by sex in the context of inherited metabolic disorders, owing to the scarce consideration of sex in such restricted field, accompanied by an intrinsic bias connected with the rarity of such diseases. Metabolomics technologies have been ultimately developed and adopted for being excellent tools for the investigation of metabolic mechanisms, for marker discovery or monitoring, and for supporting diagnostic procedures of metabolic disorders. Hence, metabolomic approaches can excellently embrace the discovery of sex differences, especially when associated to the outcome or the management of certain inborn errors of the metabolism.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

Case report: Biochemical and clinical phenotypes caused by cysteine substitutions in the epidermal growth factor-like domains of fibrillin-1

Marfan syndrome, an autosomal dominant disorder of connective tissue, is primarily caused by mutations in the fibrillin-1 (FBN1) gene, which encodes the protein fibrillin-1. The protein is composed of epidermal growth factor-like (EGF-like) domains, transforming growth factor beta-binding protein-like (TB) domains, and hybrid (Hyb) domains and is an important component of elastin-related microfibrils in elastic fiber tissue. In this study, we report a cysteine to tyrosine substitution in two different domains of fibrillin-1, both of which cause Marfan syndrome with ocular abnormalities, in two families. Using protease degradation and liquid chromatography-tandem mass spectrometry analyses, we explored the different effects of substitution of cysteine by tyrosine in an EGF-like and a calcium-binding (cb) EGF-like domain on protein stability. The results showed that cysteine mutations in the EGF domain are more likely to result in altered proteolytic sensitivity and thermostability than those in the cbEGF domain. Furthermore, cysteine mutations can lead to new enzymatic sites exposure or hidden canonical cleavage sites. These results indicate the differential clinical phenotypes and molecular pathogenesis of Marfan syndrome caused by cysteine mutations in different fibrillin-1 domains. These results strongly suggest that failure to form disulfide bonds and abnormal proteolysis of fibrillin-1 caused by cysteine mutations may be an important factor underlying the pathogenesis of diseases caused by fibrillin-1 mutations, such as Marfan syndrome.

A review of suspension trapping digestion method in bottom-up proteomics

The standard bottom-up proteomic workflow is comprised of sample preparation, data acquisition, and data analysis. While the latter two parts have made considerable advances in the last decade, sample preparation has remained an important challenge within the workflow due to the multi-step nature of complex biological samples, and still requires much development. Several sample preparation methods have been developed and used in the last two decades, including in-gel, in-solution, on-bead, filter-aided sample preparation, and suspension trapping, to improve reproducibility, efficiency, scalability, and reduce handling time of this process. One of the most recent methods developed and applied in proteomics studies in recent years is suspension trapping, which combines rapid detergent removal, reactor-type protein digestion, and peptide clean-up in a tip or spin column. Suspension trapping is a simple, rapid, and reproducible digestion method that can effectively handle proteins in low microgram or sub-microgram amounts. This review discusses the benefits of the suspension trapping digestion method in relation to its development and application in bottom-up proteomics studies. We also discuss recent applications of suspension trapping digestion to different sample types and the features of the suspension trapping digestion method compared with other sample preparation methods. This article is protected by copyright. All rights reserved.

COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.