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.

SpliceProt 2.0: A Sequence Repository of Human, Mouse, and Rat Proteoforms.

SpliceProt 2.0 is a public proteogenomics database that aims to list the sequence of known proteins and potential new proteoforms in human, mouse, and rat proteomes. This updated repository provides an even broader range of computationally translated proteins and serves, for example, to aid with proteomic validation of splice variants absent from the reference UniProtKB/SwissProt database. We demonstrate the value of SpliceProt 2.0 to predict orthologous proteins between humans and murines based on transcript reconstruction, sequence annotation and detection at the transcriptome and proteome levels. In this release, the annotation data used in the reconstruction of transcripts based on the methodology of ternary matrices were acquired from new databases such as Ensembl, UniProt, and APPRIS. Another innovation implemented in the pipeline is the exclusion of transcripts predicted to be susceptible to degradation through the NMD pathway. Taken together, our repository and its applications represent a valuable resource for the proteogenomics community.

Rare genetic variants involved in multisystem inflammatory syndrome in children: a multicenter Brazilian cohort study.

Introduction: Despite the existing data on the Multisystem Inflammatory Syndrome in Children (MIS-C), the factors that determine these patients evolution remain elusive. Answers may lie, at least in part, in genetics. It is currently under investigation that MIS-C patients may have an underlying innate error of immunity (IEI), whether of monogenic, digenic, or even oligogenic origin. Methods: To further investigate this hypothesis, 30 patients with MIS-C were submitted to whole exome sequencing. Results: Analyses of genes associated with MIS-C, MIS-A, severe covid-19, and Kawasaki disease identified twenty-nine patients with rare potentially damaging variants (50 variants were identified in 38 different genes), including those previously described in IFNA21 and IFIH1 genes, new variants in genes previously described in MIS-C patients (KMT2D, CFB, and PRF1), and variants in genes newly associated to MIS-C such as APOL1, TNFRSF13B, and G6PD. In addition, gene ontology enrichment pointed to the involvement of thirteen major pathways, including complement system, hematopoiesis, immune system development, and type II interferon signaling, that were not yet reported in MIS-C. Discussion: These data strongly indicate that different gene families may favor MIS- C development. Larger cohort studies with healthy controls and other omics approaches, such as proteomics and RNAseq, will be precious to better understanding the disease dynamics.

Next Generation of Ovarian Cancer Detection Using Aptamers.

Ovarian cancer is among the seven most common types of cancer in women, being the most fatal gynecological tumor, due to the difficulty of detection in early stages. Aptamers are important tools to improve tumor diagnosis through the recognition of specific molecules produced by tumors. Here, aptamers and their potential targets in ovarian cancer cells were analyzed by in silico approaches. Specific aptamers were selected by the Cell-SELEX method using Caov-3 and OvCar-3 cells. The five most frequent aptamers obtained from the last round of selection were computationally modeled. The potential targets for those aptamers in cells were proposed by analyzing proteomic data available for the Caov-3 and OvCar-3 cell lines. Overexpressed proteins for each cell were characterized as to their three-dimensional model, cell location, and electrostatic potential. As a result, four specific aptamers for ovarian tumors were selected: AptaC2, AptaC4, AptaO1, and AptaO2. Potential targets were identified for each aptamer through Molecular Docking, and the best complexes were AptaC2-FXYD3, AptaC4-ALPP, AptaO1-TSPAN15, and AptaO2-TSPAN15. In addition, AptaC2 and AptaO1 could detect different stages and subtypes of ovarian cancer tissue samples. The application of this technology makes it possible to propose new molecular biomarkers for the differential diagnosis of epithelial ovarian cancer.

Identification of Novel Genes and Proteoforms in Angiostrongylus costaricensis through a Proteogenomic Approach.

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis. We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain.

Selecting Genetic Variants and Interactions Associated with Amyotrophic Lateral Sclerosis: A Group LASSO Approach.

Amyotrophic lateral sclerosis (ALS) is a multi-system neurodegenerative disease that affects both upper and lower motor neurons, resulting from a combination of genetic, environmental, and lifestyle factors. Usually, the association between single-nucleotide polymorphisms (SNPs) and this disease is tested individually, which leads to the testing of multiple hypotheses. In addition, this classical approach does not support the detection of interaction-dependent SNPs. We applied a two-step procedure to select SNPs and pairwise interactions associated with ALS. SNP data from 276 ALS patients and 268 controls were analyzed by a two-step group LASSO in 2000 iterations. In the first step, we fitted a group LASSO model to a bootstrap sample and a random subset of predictors (25%) from the original data set aiming to screen for important SNPs and, in the second step, we fitted a hierarchical group LASSO model to evaluate pairwise interactions. An in silico analysis was performed on a set of variables, which were prioritized according to their bootstrap selection frequency. We identified seven SNPs (rs16984239, rs10459680, rs1436918, rs1037666, rs4552942, rs10773543, and rs2241493) and two pairwise interactions (rs16984239:rs2118657 and rs16984239:rs3172469) potentially involved in nervous system conservation and function. These results may contribute to the understanding of ALS pathogenesis, its diagnosis, and therapeutic strategy improvement.

Re-emergence of Gamma-like-II and emergence of Gamma-S:E661D SARS-CoV-2 lineages in the south of Brazil after the 2021 outbreak.

BACKGROUND: We report a genomic surveillance of SARS-CoV-2 lineages circulating in Paraná, southern Brazil, from March 2020 to April 2021. Our analysis, based on 333 genomes, revealed that the first variants detected in the state of Paraná in March 2020 were the B.1.1.33 and B.1.1.28 variants. The variants B.1.1.28 and B.1.1.33 were predominant throughout 2020 until the introduction of the variant P.2 in August 2020 and a variant of concern (VOC), Gamma (P.1), in January 2021. The VOC Gamma, a ramification of the B.1.1.28 lineage first detected in Manaus (northern Brazil), has grown rapidly since December 2020 and was thought to be responsible for the deadly second wave of COVID-19 throughout Brazil. METHODS: The 333 genomic sequences of SARS-CoV-2 from March 2020 to April 2021 were generated as part of the genomic surveillance carried out by Fiocruz in Brazil Genomahcov Fiocruz. SARS-CoV-2 sequencing was performed using representative samples from all geographic areas of Paraná. Phylogenetic analyses were performed using the 333 genomes also included other SARS-CoV-2 genomes from the state of Paraná and other states in Brazil that were deposited in the GISAID. In addition, the time-scaled phylogenetic tree was constructed with up to 3 random sequences of the Gamma variant from each state in Brazil in each month of 2021. In this analysis we also added the sequences identified as the B.1.1.28 lineage of the Amazonas state and and the Gamma-like-II (P.1-like-II) lineage identified in different regions of Brazil. RESULTS: Phylogenetic analyses of the SARS-CoV-2 genomes that were previously classified as the VOC Gamma lineage by WHO/PANGO showed that some genomes from February to April 2021 branched in a monophyletic clade and that these samples grouped together with genomes recently described with the lineage Gamma-like-II. Additionally, a new mutation (E661D) in the spike (S) protein has been identified in nearly 10% of the genomes classified as the VOC Gamma from Paraná in March and April 2021.Finally, we analyzed the correlation between the lineage and the Gamma variant frequency, age group (patients younger or older than 60 years old) and the clinical data of 86 cases from the state of Paraná. CONCLUSIONS: Our results provided a reliable picture of the evolution of the SARS-CoV-2 pandemic in the state of Paraná characterized by the dominance of the Gamma strain, as well as a high frequencies of the Gamma-like-II lineage and the S:E661D mutation. Epidemiological and genomic surveillance efforts should be continued to unveil the biological relevance of the novel mutations detected in the VOC Gamma in Paraná.

Proteogenomics Reveals Orthologous Alternatively Spliced Proteoforms in the Same Human and Mouse Brain Regions with Differential Abundance in an Alzheimer's Disease Mouse Model.

Alternative splicing (AS) may increase the number of proteoforms produced by a gene. Alzheimer's disease (AD) is a neurodegenerative disease with well-characterized AS proteoforms. In this study, we used a proteogenomics strategy to build a customized protein sequence database and identify orthologous AS proteoforms between humans and mice on publicly available shotgun proteomics (MS/MS) data of the corpus callosum (CC) and olfactory bulb (OB). Identical proteotypic peptides of six orthologous AS proteoforms were found in both species: PKM1 (gene PKM/Pkm), STXBP1a (gene STXBP1/Stxbp1), Isoform 3 (gene HNRNPK/Hnrnpk), LCRMP-1 (gene CRMP1/Crmp1), SP3 (gene CADM1/Cadm1), and PKCßII (gene PRKCB/Prkcb). These AS variants were also detected at the transcript level by publicly available RNA-Seq data and experimentally validated by RT-qPCR. Additionally, PKM1 and STXBP1a were detected at higher abundances in a publicly available MS/MS dataset of the AD mouse model APP/PS1 than its wild type. These data corroborate other reports, which suggest that PKM1 and STXBP1a AS proteoforms might play a role in amyloid-like aggregate formation. To the best of our knowledge, this report is the first to describe PKM1 and STXBP1a overexpression in the OB of an AD mouse model. We hope that our strategy may be of use in future human neurodegenerative studies using mouse models.

Dysregulation of Transcription Factor Networks Unveils Different Pathways in Human Papillomavirus 16-Positive Squamous Cell Carcinoma and Adenocarcinoma of the Uterine Cervix.

Squamous cell carcinoma (SCC) and adenocarcinoma (ADC) are the most common histological types of cervical cancer (CC). The worse prognosis of ADC cases highlights the need for better molecular characterization regarding differences between these CC types. RNA-Seq analysis of seven SCC and three ADC human papillomavirus 16-positive samples and the comparison with public data from non-tumoral human papillomavirus-negative cervical tissue samples revealed pathways exclusive to each histological type, such as the epithelial maintenance in SCC and the maturity-onset diabetes of the young (MODY) pathway in ADC. The transcriptional regulatory network analysis of cervical SCC samples unveiled a set of six transcription factor (TF) genes with the potential to positively regulate long non-coding RNA genes DSG1-AS1, CALML3-AS1, IGFL2-AS1, and TINCR. Additional analysis revealed a set of MODY TFs regulated in the sequence predicted to be repressed by miR-96-5p or miR-28-3p in ADC. These microRNAs were previously described to target LINC02381, which was predicted to be positively regulated by two MODY TFs upregulated in cervical ADC. Therefore, we hypothesize LINC02381 might act by decreasing the levels of miR-96-5p and miR-28-3p, promoting the MODY activation in cervical ADC. The novel TF networks here described should be explored for the development of more efficient diagnostic tools.

ExVe: The knowledge base of orthologous proteins identified in fungal extracellular vesicles.

Extracellular vesicles (EVs) are double-membrane particles associated with intercellular communication. Since the discovery of EV production in the fungus Cryptococcus neoformans, the importance of EV release in its physiology and pathogenicity has been investigated. To date, few studies have investigated the proteomic content of EVs from multiple fungal species. Our main objective was to use an orthology approach to compare proteins identified by EV shotgun proteomics in 8 pathogenic and 1 nonpathogenic species. Using protein information from the UniProt and FungiDB databases, we integrated data for 11,433 hits in fungal EVs with an orthology perspective, resulting in 3,834 different orthologous groups. OG6_100083 (Hsp70 Pfam domain) was the unique orthologous group that was identified for all fungal species. Proteins with this protein domain are associated with the stress response, survival and morphological changes in different fungal species. Although no pathogenic orthologous group was found, we identified 5 orthologous groups exclusive to S. cerevisiae. Using the criteria of at least 7 pathogenic fungi to define a cluster, we detected the 4 unique pathogenic orthologous groups. Taken together, our data suggest that Hsp70-related proteins might play a key role in fungal EVs, regardless of the pathogenic status. Using an orthology approach, we identified at least 4 protein domains that could be novel therapeutic targets against pathogenic fungi. Our results were compiled in the herein described ExVe database, which is publicly available at http://exve.icc.fiocruz.br.

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.

Downregulation of IGF2 expression in third trimester placental tissues from Zika virus infected women in Brazil.

OBJECTIVES: Screening for genes differentially expressed in placental tissues, aiming to identify transcriptional signatures that may be involved in ZIKV congenital pathogenesis. METHODS: Transcriptome data from placental tissues of pregnant women naturally infected with Zika virus during the third trimester were compared to those from women who tested negative for Zika infection. The findings were validated using both a cell culture model and an immunohistochemistry/morphological analysis of naturally infected placental tissues. RESULTS: Transcriptome analysis revealed that Zika virus infection induces downregulation of insulin-like growth factor II (IGF2) gene, an essential factor for fetal development. The Caco-2 cell culture model that constitutively expresses IGF2 was used for the transcriptome validation. Asiatic and African Zika virus strains infection caused downregulated IGF2 gene expression in Caco-2 cells, whereas other flaviviruses, such as dengue serotype 1, West Nile and wild-type yellow fever viruses, had no effect on this gene expression. Immunohistochemical assays on decidual tissues corroborated our transcriptome analysis, showing that IGF2 is reduced in the decidua of Zika virus-infected women. CONCLUSIONS: Our results draw attention to IGF2 modulation in uterine tissues, and this finding is expected to support future studies on strategies to ameliorate the harmful effects of Zika virus infection during pregnancy.

CD9 predicts ETV6-RUNX1 in childhood B-cell precursor acute lymphoblastic leukemia

ABSTRACT Introduction: The ETV6-RUNX1 is a fusion gene associated with a good outcome in B-cell precursor lymphoblastic leukemia. Objective: This study aimed to re-evaluate the CD9 cellular expression by flow cytometry (FC) as a possible tool to predict the presence of ETV6-RUNX1. Method: Childhood B-cell precursor lymphoblastic leukemia cases were included (n = 186). The percentage of CD9-labeled cells and the median fluorescence intensity ratio were used for correlation with the molecular tests. Receiver Operating Characteristic curves were performed to determine the likelihood of the CD9 expression predicting ETV6-RUNX1. Results: The ETV6-RUNX1 was found in 44/186 (23.6%) cases. Data analysis revealed that the best cutoff for CD9 percentage was 64%, with an accuracy of 0.84, whereas the best cutoff for CD9 median fluorescence intensity ratio was 12.52, with an accuracy of 0.80. A strong association was observed between the level of CD9 expression and the presence of ETV6-RUNX1. Conclusion: These data confirm that the CD9 expression could be used for risk stratification in clinical practice.

CD9 predicts ETV6-RUNX1 in childhood B-cell precursor acute lymphoblastic leukemia.

INTRODUCTION: The ETV6-RUNX1 is a fusion gene associated with a good outcome in B-cell precursor lymphoblastic leukemia. OBJECTIVE: This study aimed to re-evaluate the CD9 cellular expression by flow cytometry (FC) as a possible tool to predict the presence of ETV6-RUNX1. METHOD: Childhood B-cell precursor lymphoblastic leukemia cases were included (n=186). The percentage of CD9-labeled cells and the median fluorescence intensity ratio were used for correlation with the molecular tests. Receiver Operating Characteristic curves were performed to determine the likelihood of the CD9 expression predicting ETV6-RUNX1. RESULTS: The ETV6-RUNX1 was found in 44/186 (23.6%) cases. Data analysis revealed that the best cutoff for CD9 percentage was 64%, with an accuracy of 0.84, whereas the best cutoff for CD9 median fluorescence intensity ratio was 12.52, with an accuracy of 0.80. A strong association was observed between the level of CD9 expression and the presence of ETV6-RUNX1. CONCLUSION: These data confirm that the CD9 expression could be used for risk stratification in clinical practice.

Unraveling RNA dynamical behavior of TPP riboswitches: a comparison between Escherichia coli and Arabidopsis thaliana.

Riboswitches are RNA sensors that affect post-transcriptional processes through their ability to bind to small molecules. Thiamine pyrophosphate (TPP) riboswitch class is the most widespread riboswitch occurring in all three domains of life. Even though it controls different genes involved in the synthesis or transport of thiamine and its phosphorylated derivatives in bacteria, archaea, fungi, and plants, the TPP aptamer has a conserved structure. In this study, we aimed at understanding differences in the structural dynamics of TPP riboswitches from Escherichia coli and Arabidopsis thaliana, based on their crystallographic structures (TPPswec and TPPswat, respectively) and dynamics in aqueous solution, both in apo and holo states. A combination of Molecular Dynamics Simulations and Network Analysis empowered to find out slight differences in the dynamical behavior of TPP riboswitches, although relevant for their dynamics in bacteria and plants species. Our results suggest that distinct interactions in the microenvironment surrounding nucleotide U36 of TPPswec (and U35 in TPPswat) are related to different responses to TPP. The network analysis showed that minor structural differences in the aptamer enable enhanced intramolecular communication in the presence of TPP in TPPswec, but not in TPPswat. TPP riboswitches of plants present subtler and slower regulation mechanisms than bacteria do.

The Challenge to Search for New Nervous System Disease Biomarker Candidates: the Opportunity to Use the Proteogenomics Approach.

Alzheimer's disease, Parkinson's disease, prion diseases, schizophrenia, and multiple sclerosis are the most common nervous system diseases, affecting millions of people worldwide. The current scientific literature associates these pathological conditions to abnormal expression levels of certain proteins, which in turn improved the knowledge concerning normal and affected brains. However, there is no available cure or preventive therapy for any of these disorders. Proteogenomics is a recent approach defined as the data integration of both nucleotide high-throughput sequencing and protein mass spectrometry technologies. In the last years, proteogenomics studies in distinct diseases have emerged as a strategy for the identification of uncharacterized proteoforms, which are all the different protein forms derived from a single gene. For many of these diseases, at least one protein used as biomarker presents more than one proteoform, which fosters the analysis of publicly available data focusing proteoforms. Given this context, we describe the most important biomarkers for each neurodegenerative disease and how genomics, transcriptomics, and proteomics separately contributed to unveil them. Finally, we present a selection of proteogenomics studies in which the combination of nucleotide and proteome high-throughput data, from cell lines or brain tissue samples, is used to uncover proteoforms not previously described. We believe that this new approach may improve our knowledge about nervous system diseases and brain function and an opportunity to identify new biomarker candidates.

cDNA microarray analysis of human keratinocytes cells of patients submitted to chemoradiotherapy and oral photobiomodulation therapy: pilot study.

Oral mucositis is an acute toxicity that occurs in patients submitted to chemoradiotherapy to treat head and neck squamous cell carcinoma. In this study, we evaluated differences in gene expression in the keratinocytes of the oral mucosa of patients treated with photobiomodulation therapy and tried to associate the molecular mechanisms with clinical findings. From June 2009 to December 2010, 27 patients were included in a randomized double-blind pilot study. Buccal smears from 13 patients were obtained at days 1 and 10 of chemoradiotherapy, and overall gene expression of samples from both dates were analyzed by complementary DNA (cDNA) microarray. In addition, samples from other 14 patients were also collected at D1 and D10 of chemoradiotherapy for subsequent validation of cDNA microarray findings by qPCR. The expression array analysis identified 105 upregulated and 60 downregulated genes in our post-treatment samples when compared with controls. Among the upregulated genes with the highest fold change, it was interesting to observe the presence of genes related to keratinocyte differentiation. Among downregulated genes were observed genes related to cytotoxicity and immune response. The results indicate that genes known to be induced during differentiation of human epidermal keratinocytes were upregulated while genes associated with cytotoxicity and immune response were downregulated in the laser group. These results support previous clinical findings indicating that the lower incidence of oral mucositis associated with photobiomodulation therapy might be correlated to the activation of genes involved in keratinocyte differentiation.

snoRNA and piRNA expression levels modified by tobacco use in women with lung adenocarcinoma.

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

Unveiling alterative splice diversity from human oligodendrocyte proteome data.

Oligodendrocytes produce and maintain the myelin sheath of axons in the central nervous system. Because misassembled myelin sheaths have been associated with brain disorders such as multiple sclerosis and schizophrenia, recent advances have been made towards the description of the oligodendrocyte proteome. The identification of splice variants represented in the proteome is as important as determining the level of oligodendrocyte-associated proteins. Here, we used an oligodendrocyte proteome dataset deposited in ProteomeXchange to search against a customized protein sequence file containing computationally predicted splice variants. Our approach resulted in the identification of 39 splice variants, including one variant from the GTPase KRAS gene and another from the human glutaminase gene family. We also detected the mRNA expression of five selected splice variants and demonstrated that a fraction of these have their canonical proteins participating in direct protein-protein interactions. In conclusion, we believe our findings contribute to the molecular characterization of oligodendrocytes and may encourage other research groups working with central nervous system disorders to investigate the biological significance of these splice variants. The splice variants identified in this study may encode proteins that could be targeted in novel treatment strategies and diagnostic methods. SIGNIFICANCE: Several disorders of the central nervous system (CNS) are associated with misassembled myelin sheaths, which are produced and maintained by oligodendrocytes (OL). Recently, the OL proteome has been explored to identify key proteins and molecular functions associated with CNS disorders. We developed an innovative approach to select, with a higher level of confidence, a relevant list of splice variants from a proteome dataset and detected the mRNA expression of five selected variants: EEF1D, KRAS, MFF, SDR39U1, and SUGT1. We also described splice variants extracted from OL proteome data. Among the splice variants identified, some are from genes previously linked to CNS and related disorders. Our findings may contribute to oligodendrocyte characterization and encourage other research groups to investigate the biological role of splice variants and to improve current treatments and diagnostic methods for CNS disorders.

Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools.

RNA molecules are essential players in many fundamental biological processes. Prokaryotes and eukaryotes have distinct RNA classes with specific structural features and functional roles. Computational prediction of protein structures is a research field in which high confidence three-dimensional protein models can be proposed based on the sequence alignment between target and templates. However, to date, only a few approaches have been developed for the computational prediction of RNA structures. Similar to proteins, RNA structures may be altered due to the interaction with various ligands, including proteins, other RNAs, and metabolites. A riboswitch is a molecular mechanism, found in the three kingdoms of life, in which the RNA structure is modified by the binding of a metabolite. It can regulate multiple gene expression mechanisms, such as transcription, translation initiation, and mRNA splicing and processing. Due to their nature, these entities also act on the regulation of gene expression and detection of small metabolites and have the potential to helping in the discovery of new classes of antimicrobial agents. In this review, we describe software and web servers currently available for riboswitch aptamer identification and secondary and tertiary structure prediction, including applications.