RESUMEN
We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.
Asunto(s)
Proteómica , Control de Calidad , Programas Informáticos , Espectrometría de Masas en Tándem , Espectrometría de Masas en Tándem/métodos , Espectrometría de Masas en Tándem/normas , Proteómica/métodos , Proteómica/normasRESUMEN
Bothrops spp. is responsible for about 70% of snakebites in Brazil, causing a diverse and complex pathophysiological condition. Bothrops leucurus is the main species of medical relevance found in the Atlantic coast in the Brazilian Northeast region. The pathophysiological effects involved B. leucurus snakebite as well as the organism's reaction in response to this envenoming, it has not been explored yet. Thus, edema was induced in mice paw using 1.2, 2.5, and 5.0 µg of B. leucurus venom, the percentage of edema was measured 30 min after injection and the blood plasma was collected and analyzed by shotgun proteomic strategy. We identified 80 common plasma proteins with differential abundance among the experimental groups and we can understand the early aspects of this snake envenomation, regardless of the suggestive severity of an ophidian accident. The results showed B. leucurus venom triggers a thromboinflammation scenario where family's proteins of the Serpins, Apolipoproteins, Complement factors and Component subunits, Cathepsins, Kinases, Oxidoreductases, Proteases inhibitors, Proteases, Collagens, Growth factors are related to inflammation, complement and coagulation systems, modulators platelets and neutrophils, lipid and retinoid metabolism, oxidative stress and tissue repair. Our findings set precedents for future studies in the area of early diagnosis and/or treatment of snakebites. SIGNIFICANCE: The physiopathological effects that the snake venoms can cause have been investigated through classical and reductionist tools, which allowed, so far, the identification of action mechanisms of individual components associated with specific tissue damage. The currently incomplete limitations of this knowledge must be expanded through new approaches, such as proteomics, which may represent a big leap in understanding the venom-modulated pathological process. The exploration of the complete protein set that suffer modifications by the simultaneous action of multiple toxins, provides a map of the establishment of physiopathological phenotypes, which favors the identification of multiple toxin targets, that may or may not act in synergy, as well as favoring the discovery of biomarkers and therapeutic targets for manifestations that are not neutralized by the antivenom.
Asunto(s)
Bothrops , Venenos de Crotálidos , Mordeduras de Serpientes , Trombosis , Animales , Antivenenos/metabolismo , Bothrops/metabolismo , Venenos de Crotálidos/toxicidad , Inflamación , Ratones , Plasma/metabolismo , Proteoma , Proteómica , Venenos de Serpiente/toxicidadRESUMEN
Gastric cancer is the fifth most common malignant neoplasia and the third leading cause of cancer death worldwide. Mac-Cormick et al. recently showed the importance of considering the anatomical region of the tumor in proteomic gastric cancer studies; more differences were found between distinct anatomical regions than when comparing healthy versus diseased tissue. Thus, failing to consider the anatomical region could lead to differential proteins that are not disease specific. With this as motivation, we compared the proteomic profiles of intestinal and diffuse adenocarcinoma from the same anatomical region, the corpus. To achieve this, we used isobaric labeling (iTRAQ) of peptides, a 10-step HILIC fractionation, and reversed-phase nano-chromatography coupled online with a Q-Exactive Plus mass spectrometer. We updated PatternLab to take advantage of the new Comet-PEFF search engine that enables identifying post-translational modifications and mutations included in neXtProt's PSI Extended FASTA Format (PEFF) metadata. Our pipeline then uses a text-mining tool that automatically extracts PubMed IDs from the proteomic result metadata and drills down keywords from manuscripts related with the biological processes at hand. Our results disclose important proteins such as apolipoprotein B-100, S100 and 14-3-3 proteins, among many others, highlighting the different pathways enriched by each cancer type. SIGNIFICANCE: Gastric cancer is a heterogeneous and multifactorial disease responsible for a significant number of deaths every year. Despite the constant improvement of surgical techniques and multimodal treatments, survival rates are low, mostly due to limited diagnostic techniques and late symptoms. Intestinal and diffuse types of gastric cancer have distinct clinical and pathological characteristics; yet little is known about the molecular mechanisms regulating these two types of gastric tumors. Here we compared the proteomic profile of diffuse and intestinal types of gastric cancer from the same anatomical location, the corpus, from four male patients. This methodological design aimed to eliminate proteomic variations resulting from comparison of tumors from distinct anatomical regions. Our PEFF-tailored proteomic pipeline significantly increased the identifications as when compared to previous versions of PatternLab.