RESUMEN

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.

RESUMEN

Background: Food allergy (FA) has become a major public health concern affecting millions of children and adults worldwide. In Tunisia, published data on FA are scarce. Methods: This study, was intended to fill the gap and estimate the frequency of allergy to different foods in the Sfax region, Tunisia, within self-reported FA. One hundred twenty-five (125) children (56% males, 1-17 years old), and 306 adults (17% males, 18-70 years old) were interviewed using a bilingual questionnaire. Results: The number of self-reported food allergens in this sample was 105; allergens were clustered in 8 foods: fruits, seafood, eggs, milk and dairy, cereals, nuts, vegetables, and peanuts. Cutaneous reactions were the most frequent symptoms, in both children and adults. About 40% of children and 30% of adults had a family history of FA. About 81% of adults and 38% of children are allergic to at least 1 non-food allergen. The most prevalent food allergen was the fruit group in both adults and children, followed by seafood. Most food allergies were mutually exclusive and 90% of individuals have a single FA. The relationship between self-declared FA was modeled using a Bayesian network graphical model in order to estimate conditional probabilities of each FA when other FA is present. Conclusions: Our findings suggest that the prevalence of self-reported FA in Tunisia depends on dietary habits and food availability since the most frequent allergens are from foods that are highly consumed by the Tunisian population.

RESUMEN

The coronary artery disease (CAD) is a chronic inflammatory disease involving genetic as well as environmental factors. Recent evidence suggests that the oral microbiome has a significant role in triggering atherosclerosis. The present study assessed the oral microbiome composition variation between coronary patients and healthy subjects in order to identify a potential pathogenic signature associated with CAD. We performed metagenomic profiling of salivary microbiomes by 16S ribosomal RNA (rRNA) next-generation sequencing. Oral microbiota profiling was performed for 30 individuals including 20 patients with CAD and ten healthy individuals without carotid plaques or previous stroke or myocardial infarction. We found that oral microbial communities in patients and healthy controls are represented by similar global core oral microbiome. The predominant taxa belonged to Firmicutes (genus Streptococcus, Veillonella, Granulicatella, Selenomonas), Proteobacteria (genus Neisseria, Haemophilus), Actinobacteria (genus Rothia), Bacteroidetes (genus Prevotella, Porphyromonas), and Fusobacteria (genus Fusobacterium, Leptotrichia). More than 60% relative abundance of each sample for both CAD patients and controls is represented by three major genera including Streptococcus (24.97 and 26.33%), Veillonella (21.43 and 19.91%), and Neisseria (14.23 and 15.33%). Using penalized regression analysis, the bacterial genus Eikenella was involved as the major discriminant genus for both status and Syntax score of CAD. We also reported a significant negative correlation between Syntax score and Eikenella abundance in coronary patients' group (Spearman rho = -0.68, P=0.00094). In conclusion, the abundance of Eikenella in oral coronary patient samples compared with controls could be a prominent pathological indicator for the development of CAD.

Asunto(s)

RESUMEN

The identification and the screening of Charged Clusters (CCs) residues in proteins is a key analysis to assess any quantitative structure-function correlation in proteins. Here, we present a proteome wide scan for the occurrence of (CCs) in 99292 proteins using a new tool. Finding Clusters Charge in Protein Sequences Program (FCCP). The FCCP has been employed to search CCs in 35 prokaryotic proteomes (7 Psychrophiles, 10 Mesophiles, 9 thermophiles and for 9 hyperthermophiles). A new repository of 855 CC has been created. Results showed that the mapped proteins containing positive and negative charge clusters are mostly transmembrane proteins while the conserved CCs within the same proteome are transposases or involved in DNA binding and integration. Interestingly, the negative charged cluster was associated to bacteria growth's temperature (p=0.002) acting as proteins' core signature. Taken together the various results provide a consistent picture of these screened CCs in terms of its potentials functional roles.

Asunto(s)

RESUMEN

BACKGROUND: Studying genetic variation distribution in proteins containing charged regions, called charge clusters (CCs), is of great interest to unravel their functional role. Charge clusters are 20 to 75 residue segments with high net positive charge, high net negative charge, or high total charge relative to the overall charge composition of the protein. We previously developed a bioinformatics tool (FCCP) to detect charge clusters in proteomes and scanned the human proteome for the occurrence of CCs. In this paper we investigate the genetic variations in the human proteins harbouring CCs. RESULTS: We studied the coding regions of 317 positively charged clusters and 1020 negatively charged ones previously detected in human proteins. Results revealed that coding parts of CCs are richer in sequence variants than their corresponding genes, full mRNAs, and exonic + intronic sequences and that these variants are predominately rare (Minor allele frequency < 0.005). Furthermore, variants occurring in the coding parts of positively charged regions of proteins are more often pathogenic than those occurring in negatively charged ones. Classification of variants according to their types showed that substitution is the major type followed by Indels (Insertions-deletions). Concerning substitutions, it was found that within clusters of both charges, the charged amino acids were the greatest loser groups whereas polar residues were the greatest gainers. CONCLUSIONS: Our findings highlight the prominent features of the human charged regions from the DNA up to the protein sequence which might provide potential clues to improve the current understanding of those charged regions and their implication in the emergence of diseases.

Asunto(s)

RESUMEN

BACKGROUND: The identification of charge clusters (runs of charged residues) in proteins and their mapping within the protein structure sequence is an important step toward a comprehensive analysis of how these particular motifs mediate, via electrostatic interactions, various molecular processes such as protein sorting, translocation, docking, orientation and binding to DNA and to other proteins. Few algorithms that specifically identify these charge clusters have been designed and described in the literature. In this study, 197 distinctive human viral proteomes were screened for the occurrence of charge clusters (CC) using a new computational approach. RESULTS: Three hundred and seventy three CC have been identified within the 2549 viral protein sequences screened. The number of protein sequences that are CC-free is 2176 (85.3 %) while 150 and 180 proteins contained positive charge (PCC) and negative charge clusters (NCC), respectively. The NCCs (211 detected) were more prevalent than PCC (162). PCC-containing proteins are significantly longer than those having NCCs (p = 2.10-16). The most prevalent virus families having PCC and NCC were Herpesviridae followed by Papillomaviridae. However, the single-strand RNA group has in average three times more NCC than PCC. According to the functional domain classification, a significant difference in distribution was observed between PCC and NCC (p = 2. 10-8) with the occurrence of NCCs being more frequent in C-terminal region while PCC more often fall within functional domains. Only 29 proteins sequences contained both NCC and PCC. Moreover, 101 NCC were conserved in 84 proteins while only 62 PCC were conserved in 60 protein sequences. To understand the mechanism by which the membrane translocation functionalities are embedded in viral proteins, we screened our PCC for sequences corresponding to cell-penetrating peptides (CPPs) using two online databases: CellPPd and CPPpred. We found that all our PCCs, having length varying from 7 to 30 amino-acids were predicted as CPPs. Experimental validation is required to improve our understanding of the role of these PCCs in viral infection process. CONCLUSIONS: Screening distinctive cluster charges in viral proteomes suggested a functional role of these protein regions and might provide potential clues to improve the current understanding of viral diseases in order to tailor better preventive and therapeutic approaches.

Asunto(s)

RESUMEN

Clusters of charged residues are one of the key features of protein primary structure since they have been associated to important functions of proteins. Here, we present a proteome wide scan for the occurrence of Charge Clusters in Protein sequences using a new search tool (FCCP) based on a score-based methodology. The FCCP was run to search charge clusters in seven eukaryotic proteomes: Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Mus musculus, and Saccharomyces cerevisiae. We found that negative charge clusters (NCCs) are three to four times more frequent than positive charge clusters (PCCs). The Drosophila proteome is on average the most charged, whereas the human proteome is the least charged. Only 3 to 8% of the studied protein sequences have negative charge clusters, while 1.6 to 3% having PCCs and only 0.07 to 0.6% have both types of clusters. NCCs are localized predominantly in the N-terminal and C-terminal domains, while PCCs tend to be localized within the functional domains of the protein sequences. Furthermore, the gene ontology classification revealed that the protein sequences with negative and PCCs are mainly binding proteins.

Asunto(s)

RESUMEN

Hearing impairment (HI) is the most frequent sensory defect. Genetic causes are involved in two thirds of prelingual cases. Moreover, the autosomal recessive HI frequency is increased in countries where there is a high rate of consanguinity, such as in North African Mediterranean countries. This population shares several features, including history and social behavior, that promote the spread of founder mutations. HI is characterized by tremendous heterogeneity in both the genetic and clinical aspects. The identification of the causal mutation is important for early diagnosis, clinical follow-up, and genetic counseling. Addressing the extreme genetic heterogeneity of HI using classic molecular methods would be expensive and time-consuming. We designed a cost-effective North African Deafness chip for rapid and simultaneous analysis of 58 mutations using multiplex PCR coupled with dual-color arrayed primer extension. These mutations are found in North African HI patients and are distributed over 31 exons and five introns in 21 distinct genes. Assay specificity was initially optimized using 103 archived DNA samples of known genotypes. Blind validation of HI-unrelated patients revealed mutant alleles in 13 samples, and these mutations were confirmed by Sanger sequencing. The North African Deafness chip allows for simultaneous genotyping of eight different samples, at a minimal cost and in a single day, and is therefore amenable to large-scale molecular screening of HI in North Africa.

Asunto(s)