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Abstract Background Key discoveries and innovations in the field of human genetics have led to the foundation of molecular and personalized medicine. Here, we present the Genome Tunisia Project, a two-phased initiative (2022–2035) which aims to deliver the reference sequence of the Tunisian Genome and to support the implementation of personalized medicine in Tunisia, a North African country that represents a central hub of population admixture and human migration between African, European, and Asian populations. The main goal of this initiative is to develop a healthcare system capable of incorporating omics data for use in routine medical practice, enabling medical doctors to better prevent, diagnose, and treat patients. Methods A multidisciplinary partnership involving Tunisian experts from different institutions has come to discern all requirements that would be of high priority to fulfill the project’s goals. One of the most urgent priorities is to determine the reference sequence of the Tunisian Genome. In addition, extensive situation analysis and revision of the education programs, community awareness, appropriate infrastructure including sequencing platforms and biobanking, as well as ethical and regulatory frameworks, have been undertaken towards building sufficient capacity to integrate personalized medicine into the Tunisian healthcare system. Results In the framework of this project, an ecosystem with all engaged stakeholders has been implemented including healthcare providers, clinicians, researchers, pharmacists, bioinformaticians, industry, policymakers, and advocacy groups. This initiative will also help to reinforce research and innovation capacities in the field of genomics and to strengthen discoverability in the health sector. Conclusions Genome Tunisia is the first initiative in North Africa that seeks to demonstrate the major impact that can be achieved by Human Genome Projects in low- and middle-income countries to strengthen research and to improve disease management and treatment outcomes, thereby reducing the social and economic burden on healthcare systems. Sharing this experience within the African scientific community is a chance to turn a major challenge into an opportunity for dissemination and outreach. Additional efforts are now being made to advance personalized medicine in patient care by educating consumers and providers, accelerating research and innovation, and supporting necessary changes in policy and regulation.

The recombination plays a key role in promoting evolution of RNA viruses and emergence of potentially epidemic variants. Some studies investigated the recombination occurrence among SARS-CoV-2, without exploring its impact on virus-host interaction. In the aim to investigate the burden of recombination in terms of frequency and distribution, the occurrence of recombination was first explored in 44 230 Omicron sequences among BQ subvariants and the under investigation “ML” (Multiple Lineages) denoted sequences, using 3seq software. Second, the recombination impact on interaction between the Spike protein and ACE2 receptor as well as neutralizing antibodies (nAbs), was analyzed using docking tools. Recombination was detected in 56.91% and 82.20% of BQ and ML strains, respectively. It took place mainly in spike and ORF1a genes. For BQ recombinant strains, the docking analysis showed that the spike interacted strongly with ACE2 and weakly with nAbs. The mutations S373P, S375F and T376A constitute a residue network that enhances the RBD interaction with ACE2. Thirteen mutations in RBD (S373P, S375F, T376A, D405N, R408S, K417N, N440K, S477N, P494S, Q498R, N501Y, and Y505H) and NTD (Y240H) seem to be implicated in immune evasion of recombinants by altering spike interaction with nAbs. In conclusion, this “in silico” study demonstrated that the recombination mechanism is frequent among Omicron BQ and ML variants. It highlights new key mutations, that potentially implicated in enhancement of spike binding to ACE2 (F376A) and escape from nAbs (RBD: F376A, D405N, R408S, N440K, S477N, P494S, and Y505H; NTD: Y240H). Our findings present considerable insights for the elaboration of effective prophylaxis and therapeutic strategies against future SARS-CoV-2 waves.

Abstract Background Leishmaniasis are widespread parasitic-diseases with an urgent need for more active and less toxic drugs and for effective vaccines. Understanding the biology of the parasite especially in the context of host parasite interaction is a crucial step towards such improvements in therapy and control. Several experimental approaches including SAGE (Serial analysis of gene expression) have been developed in order to investigate the parasite transcriptome organisation and plasticity. Usual SAGE tag-to-gene mapping techniques are inadequate because almost all tags are normally located in the 3'-UTR outside the CDS, whereas most information available for Leishmania transcripts is restricted to the CDS predictions. The aim of this work is to optimize a SAGE libraries tag-to-gene mapping technique and to show how this development improves the understanding of Leishmania transcriptome. Findings The in silico method implemented herein was based on mapping the tags to Leishmania genome using BLAST then mapping the tags to their gene using a data-driven probability distribution. This optimized tag-to-gene mappings improved the knowledge of Leishmania genome structure and transcription. It allowed analyzing the expression of a maximal number of Leishmania genes, the delimitation of the 3' UTR of 478 genes and the identification of biological processes that are differentially modulated during the promastigote to amastigote differentiation. Conclusion The developed method optimizes the assignment of SAGE tags in trypanosomatidae genomes as well as in any genome having polycistronic transcription and small intergenic regions.

Abstract Background Ionizing-radiation-resistant bacteria (IRRB) show a surprising capacity for adaptation to ionizing radiation and desiccation. Positive Darwinian selection is expected to play an important role in this trait, but no data are currently available regarding the role of positive adaptive selection in resistance to ionizing-radiation and tolerance of desiccation. We analyzed the four known genome sequences of IRRB (Deinococcus geothermalis, Deinococcus radiodurans, Kineococcus radiotolerans, and Rubrobacter xylanophilus) to determine the role of positive Darwinian selection in the evolution of resistance to ionizing radiation and tolerance of desiccation. Results We used the programs MultiParanoid and DnaSP to deduce the sets of orthologs that potentially evolved due to positive Darwinian selection in IRRB. We find that positive selection targets 689 ortholog sets of IRRB. Among these, 58 ortholog sets are absent in ionizing-radiation-sensitive bacteria (IRSB: Escherichia coli and Thermus thermophilus). The most striking finding is that all basal DNA repair genes in IRRB, unlike many of their orthologs in IRSB, are subject to positive selection. Conclusion Our results provide the first in silico prediction of positively selected genes with potential roles in the molecular basis of resistance to γ-radiation and tolerance of desiccation in IRRB. Identification of these genes provides a basis for future experimental work aimed at understanding the metabolic networks in which they participate.

Abstract Background Leishmania (L) are intracellular protozoan parasites that are able to survive and replicate within the harsh and potentially hostile phagolysosomal environment of mammalian mononuclear phagocytes. A complex interplay then takes place between the macrophage (MΦ) striving to eliminate the pathogen and the parasite struggling for its own survival. To investigate this host-parasite conflict at the transcriptional level, in the context of monocyte-derived human MΦs (MDM) infection by L. major metacyclic promastigotes, the quantitative technique of serial analysis of gene expression (SAGE) was used. Results After extracting mRNA from resting human MΦs, Leishmania-infected human MΦs and L. major parasites, three SAGE libraries were constructed and sequenced generating up to 28,173; 57,514 and 33,906 tags respectively (corresponding to 12,946; 23,442 and 9,530 unique tags). Using computational data analysis and direct comparison to 357,888 publicly available experimental human tags, the parasite and the host cell transcriptomes were then simultaneously characterized from the mixed cellular extract, confidently discriminating host from parasite transcripts. This procedure led us to reliably assign 3,814 tags to MΦs' and 3,666 tags to L. major parasites transcripts. We focused on these, showing significant changes in their expression that are likely to be relevant to the pathogenesis of parasite infection: (i) human MΦs genes, belonging to key immune response proteins (e.g., IFNγ pathway, S100 and chemokine families) and (ii) a group of Leishmania genes showing a preferential expression at the parasite's intra-cellular developing stage. Conclusion Dual SAGE transcriptome analysis provided a useful, powerful and accurate approach to discriminating genes of human or parasitic origin in Leishmania-infected human MΦs. The findings presented in this work suggest that the Leishmania parasite modulates key transcripts in human MΦs that may be beneficial for its establishment and survival. Furthermore, these results provide an overview of gene expression at two developmental stages of the parasite, namely metacyclic promastigotes and intracellular amastigotes and indicate a broad difference between their transcriptomic profiles. Finally, our reported set of expressed genes will be useful in future rounds of data mining and gene annotation.

Bluetongue virus (BTV) is an arbovirus considered as a major threat for the global livestock economy. Since 1999, Tunisia has experienced several incursions of BTV, during which numerous cases of infection and mortality have been reported. However, the geographical origin and epidemiological characteristics of these incursions remained unclear. To understand the evolutionary history of BTV emergence in Tunisia, we extracted from Genbank the segment 6 sequences of 7 BTV strains isolated in Tunisia during the period 2000 to 2017 and blasted them to obtain a final dataset of 67 sequences. We subjected the dataset to a Bayesian phylogeography framework inferring geographical origin and serotype as phylodynamic models. Our results suggest that BTV-2 was first introduced in Tunisia in the 1960s and that since 1990s, the country has witnessed the emergence of other typical and atypical BTV serotypes notably BTV-1, BTV-3 and BTV-Y. The reported serotypes have a diverse geographical origin and have been transmitted to Tunisia from countries in the Mediterranean Basin. Interserotype reassortments have been identified among BTV-1, BTV-2 and BTV-Y. This study has provided new insights on the temporal and geographical origin of BTV in Tunisia, suggesting the contribution of animal trade and environment conditions in virus spread.

Abstract Background Cross-species gene-expression comparison is a powerful tool for the discovery of evolutionarily conserved mechanisms and pathways of expression control. The usefulness of cDNA microarrays in this context is that broad areas of homology are compared and hybridization probes are sufficiently large that small inter-species differences in nucleotide sequence would not affect the analytical results. This comparative genomics approach would allow a common set of genes within a specific developmental, metabolic, or disease-related gene pathway to be evaluated in experimental models of human diseases. The objective of this study was to investigate the feasibility and reproducibility of cross-species analysis employing a human cDNA microarray as probe. Results As a proof of principle, total RNA derived from human and bovine fetal brains was used as a source of labelled targets for hybridisation onto a human cDNA microarray composed of 349 characterised genes. Each gene was spotted 20 times representing 6,980 data points thus enabling highly reproducible spot quantification. Employing high stringency hybridisation and washing conditions, followed by data analysis, revealed slight differences in the expression levels and reproducibility of the signals between the two species. We also assigned each of the genes into three expression level categories- i.e. high, medium and low. The correlation co-efficient of cross hybridisation between the orthologous genes was 0.94. Verification of the array data by semi-quantitative RT-PCR using common primer sequences enabled co-amplification of both human and bovine transcripts. Finally, we were able to assign gene names to previously uncharacterised bovine ESTs. Conclusions Results of our study demonstrate the harnessing and utilisation power of comparative genomics and prove the feasibility of using human microarrays to facilitate the identification of co-expressed orthologous genes in common tissues derived from different species.

ABSTRACT Enteroviruses are one of the most abundant viruses causing mild to serious acute infections in humans and also contributing to chronic diseases like type 1 diabetes. Presently, there are no approved antiviral drugs against enteroviruses. Here, we studied the potency of vemurafenib, an FDA-approved RAF kinase inhibitor for treating BRAFV600E mutant-related melanoma, as an antiviral against enteroviruses. We showed that vemurafenib prevented enterovirus translation and replication at low micromolar dosage in an RAF/MEK/ERK-independent manner. Vemurafenib was effective against group A, B, and C enteroviruses, as well as rhinovirus, but not parechovirus or more remote viruses such as Semliki Forest virus, adenovirus, and respiratory syncytial virus. The inhibitory effect was related to a cellular phosphatidylinositol 4-kinase type IIIβ (PI4KB), which has been shown to be important in the formation of enteroviral replication organelles. Vemurafenib prevented infection efficiently in acute cell models, eradicated infection in a chronic cell model, and lowered virus amounts in pancreas and heart in an acute mouse model. Altogether, instead of acting through the RAF/MEK/ERK pathway, vemurafenib affects the cellular PI4KB and, hence, enterovirus replication, opening new possibilities to evaluate further the potential of vemurafenib as a repurposed drug in clinical care. IMPORTANCE Despite the prevalence and medical threat of enteroviruses, presently, there are no antivirals against them. Here, we show that vemurafenib, an FDA-approved RAF kinase inhibitor for treating BRAFV600E mutant-related melanoma, prevents enterovirus translation and replication. Vemurafenib shows efficacy against group A, B, and C enteroviruses, as well as rhinovirus, but not parechovirus or more remote viruses such as Semliki Forest virus, adenovirus, and respiratory syncytial virus. The inhibitory effect acts through cellular phosphatidylinositol 4-kinase type IIIβ (PI4KB), which has been shown to be important in the formation of enteroviral replication organelles. Vemurafenib prevents infection efficiently in acute cell models, eradicates infection in a chronic cell model, and lowers virus amounts in pancreas and heart in an acute mouse model. Our findings open new possibilities to develop drugs against enteroviruses and give hope for repurposing vemurafenib as an antiviral drug against enteroviruses.

Leishmaniases are a group of diseases with different clinical manifestations. Macrophage-Leishmania interactions are central to the course of the infection. The outcome of the disease depends not only on the pathogenicity and virulence of the parasite, but also on the activation state, the genetic background, and the underlying complex interaction networks operative in the host macrophages. Mouse models, with mice strains having contrasting behavior in response to parasite infection, have been very helpful in exploring the mechanisms underlying differences in disease progression. We here analyzed previously generated dynamic transcriptome data obtained from Leishmania major (L. major) infected bone marrow derived macrophages (BMdMs) from resistant and susceptible mouse. We first identified differentially expressed genes (DEGs) between the M-CSF differentiated macrophages derived from the two hosts, and found a differential basal transcriptome profile independent of Leishmania infection. These host signatures, in which 75% of the genes are directly or indirectly related to the immune system, may account for the differences in the immune response to infection between the two strains. To gain further insights into the underlying biological processes induced by L. major infection driven by the M-CSF DEGs, we mapped the time-resolved expression profiles onto a large protein-protein interaction (PPI) network and performed network propagation to identify modules of interacting proteins that agglomerate infection response signals for each strain. This analysis revealed profound differences in the resulting responses networks related to immune signaling and metabolism that were validated by qRT-PCR time series experiments leading to plausible and provable hypotheses for the differences in disease pathophysiology. In summary, we demonstrate that the host’s gene expression background determines to a large degree its response to L. major infection, and that the gene expression analysis combined with network propagation is an effective approach to help identifying dynamically altered mouse strain-specific networks that hold mechanistic information about these contrasting responses to infection.

Patients with Primary immunodeficiency (PIDs) may be infected by Polioviruses (PVs), especially when vaccinated with live Oral Polio Vaccine before diagnosis. They may establish long‐term shedding of divergent strains and may act as reservoirs of PV transmission. This study delved into the effect of the genetic evolution of complete PV genomes, from MHC class II‐deficient patients, on the excretion duration and clinical outcomes. Stool samples from three PID patients underwent analysis for PV detection through inoculation on cell culture and real‐time PCR, followed by VP1 partial sequencing and full genome sequencing using the Illumina technology. Our findings revealed a low number of mutations for one patient who cleared the virus, while two exhibited a high intra‐host diversity favoring the establishment of severe outcomes. Neurovirulence‐reverse mutations were detected in two patients, possibly leading to paralysis development. Furthermore, a recombination event, between type 3 Vaccine‐Derived Poliovirus and Sabin‐like1 (VDPV3/SL1), occurred in one patient. Our findings have suggested an association between intra‐host diversity, recombination, prolonged excretion of the virus, and emergence of highly pathogenic strains. Further studies on intra‐host diversity are crucial for a better understanding of the virus evolution as well as for the success of the Global Polio Eradication Initiative. [ABSTRACT FROM AUTHOR]

Modern biomedical research is characterised by its high-throughput and interdisciplinary nature. Multiproject and consortium-based collaborations requiring meaningful analysis of multiple heterogeneous phenotypic datasets have become the norm; however, such analysis remains a challenge in many regions across the world. An increasing number of data harmonisation efforts are being undertaken by multistudy collaborations through either prospective standardised phenotype data collection or retrospective phenotype harmonisation. In this regard, the Phenotype Harmonisation Working Group (PHWG) of the Human Heredity and Health in Africa (H3Africa) consortium aimed to facilitate phenotype standardisation by both promoting the use of existing data collection standards (hosted by PhenX), adapting existing data collection standards for appropriate use in low- and middle-income regions such as Africa, and developing novel data collection standards where relevant gaps were identified. Ultimately, the PHWG produced 11 data collection kits, consisting of 82 protocols, 38 of which were existing protocols, 17 were adapted, and 27 were novel protocols. The data collection kits will facilitate phenotype standardisation and harmonisation not only in Africa but also across the larger research community. In addition, the PHWG aims to feed back adapted and novel protocols to existing reference platforms such as PhenX.

Abstract Artificial Neural Network (ANN) algorithms have been widely used to analyse genomic data. Single Nucleotide Polymorphisms(SNPs) represent the genetic variations, the most common in the human genome, it has been shown that they are involved in many genetic diseases, and can be used to predict their development. Developing ANN to handle this type of data can be considered as a great success in the medical world. However, the high dimensionality of genomic data and the availability of a limited number of samples can make the learning task very complicated. In this work, we propose a New Neural Network classification method based on input perturbation. The idea is first to use SVD to reduce the dimensionality of the input data and to train a classification network, which prediction errors are then reduced by perturbing the SVD projection matrix. The proposed method has been evaluated on data from individuals with different ancestral origins, the experimental results have shown the effectiveness of the proposed method. Achieving up to 96.23% of classification accuracy, this approach surpasses previous Deep learning approaches evaluated on the same dataset.

The recombination plays a key role in promoting evolution of RNA viruses and emergence of potentially epidemic variants. Some studies investigated the recombination occurrence among SARS-CoV-2, without exploring its impact on virus-host interaction. In the aim to investigate the burden of recombination in terms of frequency and distribution, the occurrence of recombination was first explored in 44 230 Omicron sequences among BQ subvariants and the under investigation "ML" (Multiple Lineages) denoted sequences, using 3seq software. Second, the recombination impact on interaction between the Spike protein and ACE2 receptor as well as neutralizing antibodies (nAbs), was analyzed using docking tools. Recombination was detected in 56.91% and 82.20% of BQ and ML strains, respectively. It took place mainly in spike and ORF1a genes. For BQ recombinant strains, the docking analysis showed that the spike interacted strongly with ACE2 and weakly with nAbs. The mutations S373P, S375F and T376A constitute a residue network that enhances the RBD interaction with ACE2. Thirteen mutations in RBD (S373P, S375F, T376A, D405N, R408S, K417N, N440K, S477N, P494S, Q498R, N501Y, and Y505H) and NTD (Y240H) seem to be implicated in immune evasion of recombinants by altering spike interaction with nAbs. In conclusion, this "in silico" study demonstrated that the recombination mechanism is frequent among Omicron BQ and ML variants. It highlights new key mutations, that potentially implicated in enhancement of spike binding to ACE2 (F376A) and escape from nAbs (RBD: F376A, D405N, R408S, N440K, S477N, P494S, and Y505H; NTD: Y240H). Our findings present considerable insights for the elaboration of effective prophylaxis and therapeutic strategies against future SARS-CoV-2 waves. [ABSTRACT FROM AUTHOR]

In this research, natural convection of power law fluid in a square cavity, with a porous deposit in the shape of a semi-cylinder is studied numerically, using the multiple-relaxation-time lattice Boltzmann method. The modified Darcy-Brinkman model is applied for modelling the momentum equations in porous medium and the Boussinesq assumption is adopted to model the buoyancy force term. The influences of power law index (0.6 ≤ n ≤ 1.4), Darcy number (10−5 ≤ Da ≤ 10−2), Rayleigh number (103 ≤ Ra ≤ 106) and the radius ratio of the semi-cylindrical porous deposit (0.05 ≤ R ≤ 0.5) on hydrodynamic and heat transfer are studied. The obtained results show that these parameters have an important effect, on the structure of hydrodynamic and thermal transfer. The improvement of the power law index leads to a decrease in the heat transfer rate, illustrated by the average Nusselt number, and the augmentation in Darcy number induces an increase in that rate. Moreover, the variation of the Rayleigh number and the porous deposit radius has a significant effect on the transfer rate and convective structure. Besides, an unusual phenomenon is noticed for high Rayleigh numbers, where a better heat evacuation from the porous deposit is noticed for the dilatant fluid compared to the pseudoplastic one.

Microbiota colonization is a dynamic process that impacts the health status during an individual's lifetime. The composition of the gut microbiota of newborns is conditioned by multiple factors, including the delivery mode (DM). Nonetheless, the DM's influence remains uncertain and is still the subject of debate. In this context, the medical indication and the emergency of a cesarean delivery might have led to confounding conclusions regarding the composition and diversity of the neonatal microbiome. Herein, we used high-resolution shotgun sequencing to decipher the composition and dynamics of the gut microbiota composition of Tunisian newborns. Stool samples were collected from 5 elective cesarean section (ECS) and 5 vaginally delivered (VD) newborns at the following time points: Day 0, Day 15, and Day 30. The ECS and VD newborns showed the same level of bacterial richness and diversity. In addition, our data pointed to a shift in microbiota community composition during the first 2 weeks, regardless of the DM. Both ECS and VD showed a profile dominated by Proteobacteria, Actinobacteria, and Firmicutes. However, ECS showed an underrepresentation of Bacteroides and an enrichment of opportunistic pathogenic species of the ESKAPE group, starting from the second week. Besides revealing the intestinal microbiota of Tunisian newborns, this study provides novel insights into the microbiota perturbations caused by ECS.

Precise knowledge of the soil organic carbon (SOC) stocks under various land uses is needed to meet the Kyoto Protocol and for the sustainability of natural resources. The purpose of the present study was to (1) gauge the depth and spatial distribution of the soil bulk density (BD), soil organic carbon (OC) stocks, and soil organic matter (OM) among the various land uses in the northern Nile Delta in Egypt; (2) estimate the soil carbon sequestration rate (CSR) under different land uses in the region; and (3) establish baseline data for SOC stocks in future studies on the dynamics of SOC. The study area was divided into ten sampling zones to represent each land use in the northern Nile Delta. Each sampling zone was further divided into four sampling sites to represent virgin lands and fish farms, and twelve sites were used to represent three crop types and four cultivation histories. The crops included clover, (Trifolium alexandrinum L.), sugar beet (Beta vulgaris L.), and rice, (Oryza sativa L.) and the years spanned were 5, 15, 30 and 50. The effects of the crop type on the SBD, SOC content, and SOC stocks were significant. In general, the SOC stocks increase as the number of years of cultivation increased. Thematic maps were produced using Geographical Information Systems (GIS) mapping. The Inverse Distance Weighted (IDW) technique in ArcGIS10.4 software revealed that the spatial pattern of the SBD, OC content, and stocks conformed to the soil analysis results. The SOC stocks of the croplands and fish farms were 1.6 and 1.5 times higher, respectively, compared to those of virgin land. Rice cropland had the lowest SBD (1.34 g cm−3) and the highest OC stocks (7.46 g C kg−1). The conversion of virgin land into croplands or fish farms actively contributed to the carbon storage rate (CSR).

Deep Learning algorithms have achieved a great success in many domains where large scale datasets are used. However, training these algorithms on high dimensional data requires the adjustment of many parameters. Avoiding overfitting problem is difficult. Regularization techniques such as L1 and L2 are used to prevent the parameters of training model from being large. Another commonly used regularization method called Dropout randomly removes some hidden units during the training phase. In this work, we describe some architectures of Deep Learning algorithms, we explain optimization process for training them and attempt to establish a theoretical relationship between L2-regularization and Dropout. We experimentally compare the effect of these techniques on the learning model using genomics datasets.

Equid herpesvirus (EHV) is a contagious viral disease affecting horses, causing illness characterized by respiratory symptoms, abortion and neurological disorders. It is common worldwide and causes severe economic losses to the equine industry. The present study was aimed at investigating the incidence of EHVs, the genetic characterization of Tunisian isolates and a spatiotemporal study, using 298 collected samples from diseased and clinically healthy horses. The global incidence of EHV infection was found to be about 71.81%. EHV2 and EHV5 were detected in 146 (48.99%) and 159 (53.35%) sampled horses, respectively. EHV1 was detected in 11 samples (3.69%); EHV4 was not detected. Co-infections with EHV1-EHV2, EHV1-EHV5 and EHV2-EHV5 were observed in 0.33%, 1.34% and 31.54% of tested horses, respectively. Phylogenetic analyses showed that gB of EHV2 and EHV5 displays high genetic diversity with a nucleotide sequence identity ranging from 88 to 100% for EHV2 and 97.5 to 100% for EHV5. Phylogeography suggested Iceland and USA as the most likely countries of origin of the Tunisian EHV2 and EHV5 isolates. These viruses detected in Tunisia seemed to be introduced in the 2000s. This first epidemiological and phylogeographic study is important for better knowledge of the evolution of equid herpesvirus infections in Tunisia.