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Over the past 25 years, the powerful combination of genome sequencing and bioinformatics analysis has played a crucial role in interpreting information encoded in bacterial genomes. High-throughput sequencing technologies have paved the way towards understanding an increasingly wide range of biological questions. This revolution has enabled advances in areas ranging from genome composition to how proteins interact with nucleic acids. This has created unprecedented opportunities through the integration of genomic data into clinics for the diagnosis of genetic traits associated with disease. Since then, these technologies have continued to evolve, and recently, long-read sequencing has overcome previous limitations in terms of accuracy, thus expanding its applications in genomics, transcriptomics and metagenomics. In this review, we describe a brief history of the bacterial genome sequencing revolution and its application in public health and molecular epidemiology. We present a chronology that encompasses the various technological developments: whole-genome shotgun sequencing, high-throughput sequencing, long-read sequencing. We mainly discuss the application of next-generation sequencing to decipher bacterial genomes. Secondly, we highlight how long-read sequencing technologies go beyond the limitations of traditional short-read sequencing. We intend to provide a description of the guiding principles of the 3rd generation sequencing applications and ongoing improvements in the field of microbial medical research.

The current research investigated the development of a multi-epitope mRNA vaccine against the rabies virus on the basis of viral proteomes via the use of bioinformatic tools and reverse vaccinology. The aim of this study was to address the limitations of the currently available rabies vaccine by eliciting strong and long-lasting humoral and cellular immune responses. The cytotoxic T lymphocytes (CTLs), helper T lymphocytes (HTLs), and linear B-cell epitopes (LBLs) were mapped and prioritized from four top-ranking vaccine targets (nucleoprotein, phosphoprotein, matrix, and glycoprotein) that were highly antigenic, nonallergenic, nontoxic, and nonhuman homologs. The selected epitopes exhibited strong binding affinity to high-frequency HLA alleles, as evidenced by highly negative ΔG values and low dissociation constants, predicting efficient T-cell recognition and broad population coverage (96.01% globally). A single mRNA construct encompassing 21 shortlisted epitopes (four CTL, four HTL, and thirteen LBL epitopes) was designed with appropriate linkers and the immunostimulatory 50 S ribosomal protein L7/L12 adjuvant. Physicochemical analysis revealed stable, soluble, and hydrophobic properties, with an overall Ramachandran score of 93.2%, an ERRAT quality factor of 94.724%, and a Z score of -5.39. Additionally, molecular docking and normal mode analysis demonstrated the strong binding affinity of the vaccine construct-TLR-4 complex, with a minimum energy of -1655.0 kcal/mol, which was maintained by 23 hydrogen bonds and 2 salt bridge interactions, indicating significant structural stability and stiffness. The structural integrity and stable interaction of the complex were validated through 200 ns molecular dynamics simulations, as evidenced by stable RMSD and radius of gyration values, minimal fluctuations in RMSF, consistent solvent-accessible surface area (SASA), and well-defined conformational transitions observed in principal component analysis (PCA). In silico immune simulation revealed the capacity of the vaccine to stimulate the release of high levels of immunoglobulin, TH, and TC and the release of cytokines. It also has the ability to produce long-lasting memory cells, induce macrophage activity, and promote natural killer cell and neutrophil production. Moreover, further validation, including codon optimization and mRNA secondary structure prediction, confirmed the stable structure and high level of expression in the host. Overall, this study proposed a promising multi-epitope-based mRNA vaccine as an innovative therapeutic candidate against rabies. However, experimental validations are needed with systemic animal studies.

Background Coronavirus Disease 2019 (COVID-19) is a viral pandemic disease that may induce severe pneumonia in humans. In this paper, we investigated the putative implication of 12 vaccines, including BCG, OPV and MMR in the protection against COVID-19. Sequences of the main antigenic proteins in the investigated vaccines and SARS-CoV-2 proteins were compared to identify similar patterns. The immunogenic effect of identified segments was, then, assessed using a combination of structural and antigenicity prediction tools. Results A total of 14 highly similar segments were identified in the investigated vaccines. Structural and antigenicity prediction analysis showed that, among the identified patterns, three segments in Hepatitis B, Tetanus, and Measles proteins presented antigenic properties that can induce putative protective effect against COVID-19. Conclusions Our results suggest a possible protective effect of HBV, Tetanus and Measles vaccines against COVID-19, which may explain the variation of the disease severity among regions.

Snake venom contains a number of active molecules that have been shown to possess high anti-tumor activities; disintegrins are an excellent example among these. Their ability to interact and bind with integrins suggests that they could be very valuable molecules for the development of new cancer therapeutic approaches. However, in the absence of a clear Lysine-Threonine-Serine (KTS) Disintegrins Integrin interaction model, the exact compound features behind it are still unknown. In this study, we investigated the structural characteristics of three KTS-disintegrins and the interaction mechanisms with the α1β1 integrin receptor using in silico bioinformatics approaches. Normal mode analysis showed that the flexibility of the KTSR motif and the C-terminal region play a key role and influence the KTS-Disintegrin-integrin interaction. Protein-protein docking also suggested that the interaction involving the KTSR motif is highly dependent on the residue following K21, S23 and R24. These findings contribute to a better understanding of the KTS-Disintegrin-Integrin structural differences and their interactions with α1β1 receptors, which could improve the selection process of the best active molecules for antitumor therapies.

Globally, Campylobacter is a significant contributor to gastroenteritis. Efficient pathogens are qualified by their virulence power, resistance to antibiotics and epidemic spread. However, the correlation between antimicrobial resistance (AR) and the pathogenicity power of pathogens is complex and poorly understood. In this study, we aimed to investigate genes encoding virulence and AR mechanisms in 177 Campylobacter isolates collected from layer hens and eggs in Tunisia and to assess associations between AR and virulence characteristics. Virulotyping was determined by searching 13 virulence genes and AR-encoding genes were investigated by PCR and MAMA-PCR. The following genes were detected in C. jejuni and C. coli isolates: tet(O) (100%/100%), blaOXA-61 (18.82%/6.25%), and cmeB (100%/100%). All quinolone-resistant isolates harbored the Thr-86-Ile substitution in GyrA. Both the A2074C and A2075G mutations in 23S rRNA were found in all erythromycin-resistant isolates; however, the erm(B) gene was detected in 48.38% and 64.15% of the C. jejuni and C. coli isolates, respectively. The machine learning algorithm Random Forest was used to determine the association of virulence genes with AR phenotypes. This analysis showed that C. jejuni virulotypes with gene clusters encompassing the racR, ceuE, virB11, and pldA genes were strongly associated with the majority of phenotypic resistance. Our findings showed high rates of AR and virulence genes among poultry Campylobacter, which is a cause of concern to human health. In addition, the correlations of specific virulence genes with AR phenotypes were established by statistical analysis.

Hereditary breast cancer accounts for 5–10% of all breast cancer cases. So far, known genetic risk factors account for only 50% of the breast cancer genetic component and almost a quarter of hereditary cases are carriers of pathogenic mutations in BRCA1/2 genes. Hence, the genetic basis for a significant fraction of familial cases remains unsolved. This missing heritability may be explained in part by Copy Number Variations (CNVs). We herein aimed to evaluate the contribution of CNVs to hereditary breast cancer in Tunisia. Whole exome sequencing was performed for 9 BRCA negative cases with a strong family history of breast cancer and 10 matched controls. CNVs were called using the ExomeDepth R-package and investigated by pathway analysis and web-based bioinformatic tools. Overall, 483 CNVs have been identified in breast cancer patients. Rare CNVs affecting cancer genes were detected, of special interest were those disrupting APC2 , POU5F1 , DOCK8 , KANSL1 , TMTC3 and the mismatch repair gene PMS2 . In addition, common CNVs known to be associated with breast cancer risk have also been identified including CNVs on APOBECA/B , UGT2B17 and GSTT1 genes. Whereas those disrupting SULT1A1 and UGT2B15 seem to correlate with good clinical response to tamoxifen. Our study revealed new insights regarding CNVs and breast cancer risk in the Tunisian population. These findings suggest that rare and common CNVs may contribute to disease susceptibility. Those affecting mismatch repair genes are of interest and require additional attention since it may help to select candidates for immunotherapy leading to better outcomes.

Background Whole-genome sequencing using high throughput technologies has revolutionized and speeded up the scientific investigation of bacterial genetics, biochemistry, and molecular biology. Lactic acid bacteria (LABs) have been extensively used in fermentation and more recently as probiotics in food products that promote health. Genome sequencing and functional genomics investigations of LABs varieties provide rapid and important information about their diversity and their evolution, revealing a significant molecular basis. This study investigated the whole genome sequences of the Enterococcus faecium strain (HG937697), isolated from the mucus of freshwater fish in Tunisian dams. Genomic DNA was extracted using the Quick-GDNA kit and sequenced using the Illumina HiSeq2500 system. Sequences quality assessment was performed using FastQC software. The complete genome annotation was carried out with the Rapid Annotation using Subsystem Technology (RAST) web server then NCBI PGAAP. Results The Enterococcus faecium R.A73 assembled in 28 contigs consisting of 2,935,283 bps. The genome annotation revealed 2884 genes in total including 2834 coding sequences and 50 RNAs containing 3 rRNAs (one rRNA 16 s, one rRNA 23 s and one rRNA 5 s) and 47 tRNAs. Twenty-two genes implicated in bacteriocin production are identified within the Enterococcus faecium R.A73 strain. Conclusion Data obtained provide insights to further investigate the effective strategy for testing this Enterococcus faecium R.A73 strain in the industrial manufacturing process. Studying their metabolism with bioinformatics tools represents the future challenge and contribution to improving the utilization of the multi-purpose bacteria in food.

Hepatitis C virus (HCV) has a high genetic diversity. Eight genotypes and 90 subtypes are currently described. Genotypes are clinically significant for therapeutic management and their determination is necessary for epidemiological studies. Tunisian patients plasma samples (n = 6) with unassigned HCV-2 subtype using partial sequencing in the NS5B and Core/E1 regions were analyzed by realizing whole-genome sequencing analysis. Phylogenetic analyses were performed to assign subtypes. Phylogenetic analysis of the full genome sequences of Tunisian strains shows two subtypes within HCV-2. These later were genetically distinct from all previously established HCV-2 subtypes with nucleotide divergence greater than 15% (20% -31%). These two subtypes are proposed as new subtypes 2v and 2w. The discovery of two new HCV-2 subtypes circulating in the Tunisian population confirms the great diversity of HCV-2 viruses and increases the total number of HCV-2 subtypes from 21 to 23.

Coronavirus disease 2019 (COVID-19) has been associated with a significant fatality rate and persistent evolution in immunocompromised patients. In this prospective study, we aimed to determine the duration of excretion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 37 Tunisian patients with hematological malignancies (40.5% with lymphoma and 37.8% with leukemia). In order to investigate the accumulation of viral mutations, we carried out genetic investigation on longitudinal nasopharyngeal samples using RT-PCR and whole-genome sequencing. Patients’ samples were collected until the RT-PCR results became negative. SARS-CoV-2 infection was symptomatic in 48.6% of cases with fever, and cough was symptomatic in 61% of cases; the mortality rate was estimated to be 13.5%. The duration of viral RNA shedding ranged from 7 to 92 days after onset; it exceeded 18 days in 79.4% of cases. An intermittent PCR positivity was observed in two symptomatic patients. Persistent PCR positivity, defined as the presence of viral RNA for more than 30 days, was found in 51.4% of cases. No significant differences were observed for age, sex, type of hematological malignancy, or COVID-19 evolution between this group and a second one characterized by non-persistent PCR positivity. Lymphopenia was an independent predictor of prolonged SARS-CoV-2 RNA detection (p = 0.04). Three types of variants were detected; the most frequent was the Omicron. Globally, the mean intra-host variability in the SARS-CoV-2 genome was 1.31 × 10−3 mutations per site per year; it was 1.44 × 10−3 in the persistent group and 1.3 × 10−3 in the non-persistent group. Three types of mutations were detected; the most frequent were nucleotide substitutions in the spike (S) gene. No statistically significant difference was observed between the two groups as to the type and mean number of observed mutations in the whole genome and the S region (p = 0.650). Sequence analysis revealed the inclusion of one to eight amino acid-changing events in seventeen cases; it was characterized by genetic stability from the third to the twentieth day of evolution in six cases. For the two patients with intermittent PCR positivity, sequences obtained from samples before and after negative PCR were identical in the whole genome, confirming an intra-host evolution of the same viral strain. This study confirms the risk of persistent viral shedding in patients with hematological malignancies. However, persistence of PCR positivity seems to be correlated only with a continuous elimination of viral RNA debris. Additional studies based on cell culture analysis are needed to confirm these findings.

A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.