Proteomic Analysis of a Rat Streptozotocin Model Shows Dysregulated Biological Pathways Implicated in Alzheimer's Disease.

Alzheimer's Disease (AD) is an age-related neurodegenerative disorder characterized by progressive memory loss and cognitive impairment, affecting 35 million individuals worldwide. Intracerebroventricular (ICV) injection of low to moderate doses of streptozotocin (STZ) in adult male Wistar rats can reproduce classical physiopathological hallmarks of AD. This biological model is known as ICV-STZ. Most studies are focused on the description of behavioral and morphological aspects of the ICV-STZ model. However, knowledge regarding the molecular aspects of the ICV-STZ model is still incipient. Therefore, this work is a first attempt to provide a wide proteome description of the ICV-STZ model based on mass spectrometry (MS). To achieve that, samples from the pre-frontal cortex (PFC) and hippocampus (HPC) of the ICV-STZ model and control (wild-type) were used. Differential protein abundance, pathway, and network analysis were performed based on the protein identification and quantification of the samples. Our analysis revealed dysregulated biological pathways implicated in the early stages of late-onset Alzheimer's disease (LOAD), based on differentially abundant proteins (DAPs). Some of these DAPs had their mRNA expression further investigated through qRT-PCR. Our results shed light on the AD onset and demonstrate the ICV-STZ as a valid model for LOAD proteome description.

The Point Mutation G461S in the MfCYP51 Gene is Associated with Tebuconazole Resistance in Monilinia fructicola Populations in Brazil.

The ascomycete Monilinia fructicola is the causal agent of brown rot of stone fruit in Brazil, causing major pre- and postharvest losses. For many years, the demethylation inhibitor (DMI) fungicide tebuconazole has been used as the most effective active ingredient for controlling brown rot and, as a result, strains of M. fructicola resistant to this ingredient have emerged in many Brazilian states producing stone fruit. The aim of this study was to investigate the mechanisms associated with the resistance of M. fructicola to DMI tebuconazole. By sequencing the M. fructicola CYP51 (MfCYP51) gene, encoding the azole target sterol 14α-demethylase, a mutation was identified at the nucleotide position 1,492, causing the amino acid substitution from glycine to serine at the codon position 461, associated with reduced tebuconazole sensitivity. In addition, it was observed that MfCYP51 gene expression could play a secondary role in DMI fungicide resistance of M. fructicola strains in Brazil. However, for the specific isolate found to exhibit elevated expression levels of MfCYP51, no insertions that would trigger gene expression were found. Based on the point mutation associated with tebuconazole resistance, an allele-specific polymerase chain reaction method was developed to quickly identify resistant genotypes within the Brazilian population. This is the first report determining molecular mechanisms for DMI resistance identification for M. fructicola isolates from Brazil. This information provides an important advancement for risk assessment of DMI fungicides used to manage brown rot of stone fruit.

Colorectal cancer DNA methylation patterns from patients in Manaus, Brazil.

BACKGROUND: DNA methylation is commonly linked with the silencing of the gene expression for many tumor suppressor genes. As such, determining DNA methylation patterns should aid, in times to come, in the diagnosis and personal treatment for various types of cancers. Here, we analyzed the methylation pattern from five colorectal cancer patients from the Amazon state in Brazil for four tumor suppressor genes, viz.: DAPK, CDH1, CDKN2A, and TIMP2 by employing a polymerase chain reaction (PCR) specific to methylation. Efforts in the study of colorectal cancer are fundamental as it is the third most of highest incidence in the world. RESULTS: Tumor biopsies were methylated in 1/5 (20%), 2/5 (40%), 4/5 (80%), and 4/5 (80%) for CDH1, CDKN2A, DAPK, and TIMP2 genes, respectively. The margin biopsies were methylated in 3/7 (43%), 2/7 (28%), 7/7 (100%), and 6/7 (86%) for CDH1, CDKN2A, DAPK, and TIMP2, respectively. CONCLUSIONS: Our findings showed DAPK and TIMP2 to be methylated in most samples from both tumor tissues and adjacent non-neoplastic margins; thus presenting distinct methylation patterns. This emphasizes the importance of better understanding of the relation of these patterns with cancer in the context of different populations.

Exploring the proteomic landscape of a gastric cancer biopsy with the shotgun imaging analyzer.

Accessing localized proteomic profiles has emerged as a fundamental strategy to understand the biology of diseases, as recently demonstrated, for example, in the context of determining cancer resection margins with improved precision. Here, we analyze a gastric cancer biopsy sectioned into 10 parts, each one subjected to MudPIT analysis. We introduce a software tool, named Shotgun Imaging Analyzer and inspired in MALDI imaging, to enable the overlaying of a protein's expression heat map on a tissue picture. The software is tightly integrated with the NeXtProt database, so it enables the browsing of identified proteins according to chromosomes, quickly listing human proteins never identified by mass spectrometry (i.e., the so-called missing proteins), and the automatic search for proteins that are more expressed over a specific region of interest on the biopsy, all of which constitute goals that are clearly well-aligned with those of the C-HPP. Our software has been able to highlight an intense expression of proteins previously known to be correlated with cancers (e.g., glutathione S-transferase Mu 3), and in particular, we draw attention to Gastrokine-2, a "missing protein" identified in this work of which we were able to clearly delineate the tumoral region from the "healthy" with our approach. Data are available via ProteomeXchange with identifier PXD000584.

Intra-Individual Paired Mass Spectrometry Dataset for Decoding Solar-Induced Proteomic Changes in Facial Skin.

Photoaging is the premature aging of the skin caused by prolonged exposure to solar radiation. The visual alterations manifest as wrinkles, reduced skin elasticity, uneven skin tone, as well as other signs that surpass the expected outcomes of natural aging. Beyond these surface changes, there is a complex interplay of molecular alterations, encompassing shifts in cellular function, DNA damage, and protein composition disruptions. This data descriptor introduces a unique dataset derived from ten individuals, each with a minimum of 18 years of professional experience as a driver, who are asymmetrically and chronically exposed to solar radiation due to their driving orientation. Skin samples were independently collected from each side of the face using a microdermabrasion-like procedure and analyzed on an Exploris 240 mass spectrometer. Our adapted proteomic statistical framework leverages the sample pairing to provide robust insights. This dataset delves into the molecular differences in exposed skin and serves as a foundational resource for interdisciplinary research in photodermatology, targeted skincare treatments, and computational modelling of skin health.

Urinary proteomics reveals biological processes related to acute kidney injury in Bothrops atrox envenomings.

Acute kidney injury (AKI) is a critical systemic complication caused by Bothrops envenoming, a neglected health problem in the Brazilian Amazon. Understanding the underlying mechanisms leading to AKI is crucial for effectively mitigating the burden of this complication. This study aimed to characterize the urinary protein profile of Bothrops atrox snakebite victims who developed AKI. We analyzed three groups of samples collected on admission: healthy subjects (controls, n = 10), snakebite victims who developed AKI (AKI, n = 10), and those who did not evolve to AKI (No-AKI, n = 10). Using liquid-chromatography tandem mass spectrometry, we identified and quantified (label-free) 1190 proteins. A panel of 65 proteins was identified exclusively in the urine of snakebite victims, with 32 exclusives to the AKI condition. Proteins more abundant or exclusive in AKI's urine were associated with acute phase response, endopeptidase inhibition, complement cascade, and inflammation. Notable proteins include serotransferrin, SERPINA-1, alpha-1B-glycoprotein, and NHL repeat-containing protein 3. Furthermore, evaluating previously reported biomarkers candidates for AKI and renal injury, we found retinol-binding protein, beta-2-microglobulin, cystatin-C, and hepcidin to be significant in cases of AKI induced by Bothrops envenoming. This work sheds light on physiological disturbances caused by Bothrops envenoming, highlighting potential biological processes contributing to AKI. Such insights may aid in better understanding and managing this life-threatening complication.

Proteomics reveals differentially regulated pathways when comparing grade 2 and 4 astrocytomas.

Astrocytic tumors are known for their high progression capacity and high mortality rates; in this regard, proteins correlated to prognosis can aid medical conduct. Although several genetic changes related to progression from grade 2 to grade 4 astrocytoma are already known, mRNA copies do not necessarily correlate with protein abundance and therefore could shadow further comprehension about this tumor's biology. This motivates us to seek for complementary strategies to study tumor progression at the protein level. Here we compare the proteomic profile of biopsies from patients with grade 2 (diffuse, n = 6) versus grade 4 astrocytomas (glioblastomas, n = 10) using shotgun proteomics. Data analysis performed with PatternLab for proteomics identified 5,206 and 6,004 proteins in the 2- and 4-grade groups, respectively. Our results revealed seventy-four differentially abundant proteins (p < 0.01); we then shortlist those related to greater malignancy. We also describe molecular pathways distinctly activated in the two groups, such as differences in the organization of the extracellular matrix, decisive both in tumor invasiveness and in signaling for cell division, which, together with marked contrasts in energy metabolism, are determining factors in the speed of growth and dissemination of these neoplasms. The degradation pathways of GABA, enriched in the grade 2 group, is consistent with a favorable prognosis. Other functions such as platelet degranulation, apoptosis, and activation of the MAPK pathway were correlated to grade 4 tumors and, consequently, unfavorable prognoses. Our results provide an important survey of molecular pathways involved in glioma pathogenesis for these histopathological groups.

DiagnoMass: A proteomics hub for pinpointing discriminative spectral clusters.

MOTIVATION: There are several well-established paradigms for identifying and pinpointing discriminative peptides/proteins using shotgun proteomic data; examples are peptide-spectrum matching, de novo sequencing, open searches, and even hybrid approaches. Such an arsenal of complementary paradigms can provide deep data coverage, albeit some unidentified discriminative peptides remain. RESULTS: We present DiagnoMass, software tool that groups similar spectra into spectral clusters and then shortlists those clusters that are discriminative for biological conditions. DiagnoMass then communicates with proteomic tools to attempt the identification of such clusters. We demonstrate the effectiveness of DiagnoMass by analyzing proteomic data from Escherichia coli, Salmonella, and Shigella, listing many high-quality discriminative spectral clusters that had thus far remained unidentified by widely adopted proteomic tools. DiagnoMass can also classify proteomic profiles. We anticipate the use of DiagnoMass as a vital tool for pinpointing biomarkers. AVAILABILITY: DiagnoMass and related documentation, including a usage protocol, are available at http://www.diagnomass.com.

PatternLab V Handles Multiplex Spectra in Shotgun Proteomic Searches and Increases Identification.

Complex protein mixtures typically generate many tandem mass spectra produced by different peptides coisolated in the gas phase. Widely adopted proteomic data analysis environments usually fail to identify most of these spectra, succeeding at best in identifying only one of the multiple cofragmenting peptides. We present PatternLab V (PLV), an updated version of PatternLab that integrates the YADA 3 deconvolution algorithm to handle such cases efficiently. In general, we expect an increase of 10% in spectral identifications when dealing with complex proteomic samples. PLV is freely available at http://patternlabforproteomics.org.

Beyond the identifiable proteome: Delving into the proteomics of polymyxin-resistant and non-resistant Acinetobacter baumannii from Brazilian hospitals.

This work discloses a unique, comprehensive proteomic dataset of Acinetobacter baumannii strains, both resistant and non-resistant to polymyxin B, isolated in Brazil generated using Orbitrap Fusion Lumos. From nearly 4 million tandem mass spectra, the software DiagnoMass produced 240,685 quality-filtered mass spectral clusters, of which PatternLab for proteomics identified 44,553 peptides mapping to 3479 proteins. Crucially, DiagnoMass shortlisted 3550 and 1408 unique mass spectral clusters for the resistant and non-resistant strains, respectively, with only about a third with sequences (and PTMs) identified by PatternLab. Further open-search attempts via FragPipe yielded an additional ∼20% identifications, suggesting the remaining unidentified spectra likely arise from complex combinations of post-translational modifications and amino-acid substitutions. This highlights the untapped potential of the dataset for future discoveries, particularly given the importance of PTMs, which remain elusive to nucleotide sequencing approaches but are crucial for understanding biological mechanisms. Our innovative approach extends beyond the identifications that are typically subjected to the bias of a search engine; we discern which spectral clusters are differential and subject them to increased scrutiny, akin to spectral library matching by comparing captured spectra to themselves. Our analysis reveals adaptations in the resistant strain, including enhanced detoxification, altered protein synthesis, and metabolic adjustments. SIGNIFICANCE: We present comprehensive proteomic profiles of non-resistant and resistant Acinetobacter baumannii from Brazilian Hospitals strains, and highlight the presence of discriminative and yet unidentified mass spectral clusters. Our work emphasizes the importance of exploring this overlooked data, as it could hold the key to understanding the complex dynamics of antibiotic resistance. This approach not only informs antimicrobial stewardship efforts but also paves the way for the development of innovative diagnostic tools. Thus, our findings have profound implications for the field, as far as methods for providing a new perspective on diagnosing antibiotic resistance as well as classifying proteomes in general.

Search engine processor: Filtering and organizing peptide spectrum matches.

The search engine processor (SEPro) is a tool for filtering, organizing, sharing, and displaying peptide spectrum matches. It employs a novel three-tier Bayesian approach that uses layers of spectrum, peptide, and protein logic to lead the data to converge to a single list of reliable protein identifications. SEPro is integrated into the PatternLab for proteomics environment, where an arsenal of tools for analyzing shotgun proteomic data is provided. By using the semi-labeled decoy approach for benchmarking, we show that SEPro significantly outperforms a commercially available competitor.

Proteomic profiling of the influence of iron availability on Cryptococcus gattii.

Iron is essential and ubiquitous in living organisms. The competition for this micronutrient between the host and its pathogens has been related to disease establishment. Cryptococcus gattii is an encapsulated yeast that causes cryptococcosis mainly in immunocompetent individuals. In this study, we analyzed the proteomic profile of the C. gattii R265 Vancouver Island isolate under iron-depleted and -repleted conditions by multidimensional protein identification technology (MudPIT) and by 2D-GE. Proteins and key mechanisms affected by alteration of iron levels such as capsule production, cAMP-signaling pathway, response to stress, and metabolic pathways related to mitochondrial function were identified. Our results also show both proteomic methodologies employed to be complementary.

Are gastric cancer resection margin proteomic profiles more similar to those from controls or tumors?

A strategy for treating cancer is to surgically remove the tumor together with a portion of apparently healthy tissue surrounding it, the so-called "resection margin", to minimize recurrence. Here, we investigate whether the proteomic profiles from biopsies of gastric cancer resection margins are indeed more similar to those from healthy tissue than from cancer biopsies. To this end, we analyzed biopsies using an offline MudPIT shotgun proteomic approach and performed label-free quantitation through a distributed normalized spectral abundance factor approach adapted for extracted ion chromatograms (XICs). A multidimensional scaling analysis revealed that each of those tissue-types is very distinct from each other. The resection margin presented several proteins previously correlated with cancer, but also other overexpressed proteins that may be related to tumor nourishment and metastasis, such as collagen alpha-1, ceruloplasmin, calpastatin, and E-cadherin. We argue that the resection margin plays a key role in Paget's "soil to seed" hypothesis, that is, that cancer cells require a special microenvironment to nourish and that understanding it could ultimately lead to more effective treatments.

Analyzing marginal cases in differential shotgun proteomics.

SUMMARY: We present an approach to statistically pinpoint differentially expressed proteins that have quantitation values near the quantitation threshold and are not identified in all replicates (marginal cases). Our method uses a Bayesian strategy to combine parametric statistics with an empirical distribution built from the reproducibility quality of the technical replicates. AVAILABILITY: The software is freely available for academic use at http://pcarvalho.com/patternlab.

Simple, efficient and thorough shotgun proteomic analysis with PatternLab V.

Shotgun proteomics aims to identify and quantify the thousands of proteins in complex mixtures such as cell and tissue lysates and biological fluids. This approach uses liquid chromatography coupled with tandem mass spectrometry and typically generates hundreds of thousands of mass spectra that require specialized computational environments for data analysis. PatternLab for proteomics is a unified computational environment for analyzing shotgun proteomic data. PatternLab V (PLV) is the most comprehensive and crucial update so far, the result of intensive interaction with the proteomics community over several years. All PLV modules have been optimized and its graphical user interface has been completely updated for improved user experience. Major improvements were made to all aspects of the software, ranging from boosting the number of protein identifications to faster extraction of ion chromatograms. PLV provides modules for preparing sequence databases, protein identification, statistical filtering and in-depth result browsing for both labeled and label-free quantitation. The PepExplorer module can even pinpoint de novo sequenced peptides not already present in the database. PLV is of broad applicability and therefore suitable for challenging experimental setups, such as time-course experiments and data handling from unsequenced organisms. PLV interfaces with widely adopted software and community initiatives, e.g., Comet, Skyline, PEAKS and PRIDE. It is freely available at http://www.patternlabforproteomics.org .

Chemo-resistant protein expression pattern of glioblastoma cells (A172) to perillyl alcohol.

Glioblastoma multiform (GBM) is by far the most malignant glioma. We have introduced a new treatment for GBMs that comprises the inhalation of a naturally occurring terpene with chemotherapeutic properties known as perillyl alcohol (POH). Clinical trial results on recurrent GBM patients showed that POH extends the average life by more than eight months, temporarily slows tumor growth, and in some cases even decreases tumor size. After approximately seven months, the tumor continues to grow and leads to a dismal prognosis. To investigate how these tumors become resistant to POH, we generated an A172 human glioblastoma cell culture tolerant to 0.06 mM of POH (A172r). We used Multidimensional Protein Identification Technology (MudPIT) to compare the protein expression profile of A172r cells to the established glioblastoma A172 cell line. Our results include a list of identified proteins unique to either the resistant or the nonresistant cell line. These proteins are related to cellular growth, negative apoptosis regulation, Ras pathway, and other key cellular functions that could be connected to the underlying mechanisms of resistance.

Proteogenomic Analysis Reveals Proteins Involved in the First Step of Adipogenesis in Human Adipose-Derived Stem Cells.

BACKGROUND: Obesity is characterized as a disease that directly affects the whole-body metabolism and is associated with excess fat mass and several related comorbidities. Dynamics of adipocyte hypertrophy and hyperplasia play an important role in health and disease, especially in obesity. Human adipose-derived stem cells (hASC) represent an important source for understanding the entire adipogenic differentiation process. However, little is known about the triggering step of adipogenesis in hASC. Here, we performed a proteogenomic approach for understanding the protein abundance alterations during the initiation of the adipogenic differentiation process. METHODS: hASC were isolated from adipose tissue of three donors and were then characterized and expanded. Cells were cultured for 24 hours in adipogenic differentiation medium followed by protein extraction. We used shotgun proteomics to compare the proteomic profile of 24 h-adipogenic, differentiated, and undifferentiated hASC. We also used our previous next-generation sequencing data (RNA-seq) of the total and polysomal mRNA fractions of hASC to study posttranscriptional regulation during the initial steps of adipogenesis. RESULTS: We identified 3420 proteins out of 48,336 peptides, of which 92 proteins were exclusively identified in undifferentiated hASC and 53 proteins were exclusively found in 24 h-differentiated cells. Using a stringent criterion, we identified 33 differentially abundant proteins when comparing 24 h-differentiated and undifferentiated hASC (14 upregulated and 19 downregulated, respectively). Among the upregulated proteins, we shortlisted several adipogenesis-related proteins. A combined analysis of the proteome and the transcriptome allowed the identification of positive correlation coefficients between proteins and mRNAs. CONCLUSIONS: These results demonstrate a specific proteome profile related to adipogenesis at the beginning (24 hours) of the differentiation process in hASC, which advances the understanding of human adipogenesis and obesity. Adipogenic differentiation is finely regulated at the transcriptional, posttranscriptional, and posttranslational levels.

Proteomic changes in Trypanosoma cruzi epimastigotes treated with the proapoptotic compound PAC-1.

Apoptosis is a highly regulated process of cell death in metazoans. Therefore, understanding the biochemical changes associated with apoptosis-like death in Trypanosoma cruzi is key to drug development. PAC-1 was recently shown to induce apoptosis in T. cruzi; with this as motivation, we used quantitative proteomics to unveil alterations of PAC-1-treated versus untreated epimastigotes. The PAC-1 treatment reduced the abundance of putative vesicle-associated membrane protein, putative eukaryotic translation initiation factor 1 eIF1, coatomer subunit beta, putative amastin, and a putative cytoskeleton-associated protein. Apoptosis-like signaling also increases the abundance of proteins associated with actin cytoskeleton remodeling, cell polarization, apoptotic signaling, phosphorylation, methylation, ergosterol biosynthesis, vacuolar proteins associated with autophagy, and flagellum motility. We shortlist seventeen protein targets for possible use in chemotherapy for Chagas disease. Almost all differentially abundant proteins belong to a family of proteins previously associated with apoptosis in metazoans, suggesting that the apoptotic pathway's key functions have been preserved from trypanosomatids and metazoans. SIGNIFICANCE: Approximately 8 million people worldwide are infected with Trypanosoma cruzi. The treatment of Chagas disease comprises drugs with severe side effects, thus limiting their application. Thus, developing new pharmaceutical solutions is relevant, and several molecules targeting apoptosis are therapeutically efficient for parasitic, cardiac, and neurological diseases. Apoptotic processes lead to specific morphological features that have been previously observed in T. cruzi. Here, we investigate changes in epimastigotes' proteomic profile treated with the proapoptotic compound PAC-1, providing data concerning the regulation of both metabolic and cellular processes in nonmetazoan apoptotic cells. We shortlist seventeen protein target candidates for use in chemotherapy for Chagas disease.

The impact of blood-processing time on the proteome of human peripheral blood mononuclear cells.

Human peripheral blood mononuclear cells (PBMC) are key to several diagnostics assays and basic science research. Blood pre-analytical variations that occur before obtaining the PBMC fraction can significantly impact the assays results, including viability, composition, integrity, and gene expression changes of immune cells. With this as motivation, we performed a quantitative shotgun proteomics analysis using Isobaric Tag for Relative and Absolute Quantitation (iTRAQ 8plex) labeling to compare PBMC obtained from 24 h-stored blood at room temperature versus freshly isolated. We identified a total of 3195 proteins, of which 245 were differentially abundant (101 upregulated and 144 downregulated). Our results revealed enriched pathways of downregulated proteins related to exocytosis, localization, vesicle-mediated transport, cell activation, and secretion. In contrast, pathways related to exocytosis, neutrophil degranulation and activation, granulocyte activation, leukocyte degranulation, and myeloid leukocyte activation involved in immune response were enriched in upregulated proteins, which may indicate probable granulocyte contamination and activation due to blood storage time and temperature. Examples of upregulated proteins in the 24 h-PBMC samples are CAMP, S100A8, LTA4H, RASAL3, and S100A6, which are involved in an adaptive immune system and antimicrobial activity, proinflammatory mediation, aminopeptidase activities, and naïve T cells survival. Moreover, examples of downregulated proteins are NDUFA5, TAGLN2, H3C1, TUBA8, and CCT2 that are related to the cytoskeleton, cell junction, mitochondrial respiratory chain. In conclusion, the delay in blood-processing time directly impacts the proteomic profile of human PBMC, possibly through granulocyte contamination and activation.

Proteomics reveals that quinoa bioester promotes replenishing effects in epidermal tissue.

The continuous search for natural products that attenuate age-related losses has increasingly gained notice; among them, those applicable for skin care have drawn significant attention. The bioester generated from the Chenopodium quinoa's oil is a natural-origin ingredient described to produce replenishing skin effects. With this as motivation, we used shotgun proteomics to study the effects of quinoa bioester on human reconstructed epidermis tridimensional cell cultures after 0, 3, 6, 12, 24, and 48 h of exposure. Our experimental setup employed reversed-phase nano-chromatography coupled online with an Orbitrap-XL and PatternLab for proteomics as the data analysis tool. Extracted ion chromatograms were obtained as surrogates for relative peptide quantitation. Our findings spotlight proteins with increased abundance, as compared to the untreated cell culture counterparts at the same timepoints, that were related to preventing premature aging, homeostasis, tissue regeneration, protection against ultraviolet radiation and oxidative damage.