Kais Ghedira

Basal DNA repair machinery is subject to positive selection in ionizing-radiation-resistant bacteria

BackgroundIonizing-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.ResultsWe 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.ConclusionOur 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.

Bioinformatics Education—Perspectives and Challenges out of Africa

The discipline of bioinformatics has developed rapidly since the complete sequencing of the first genomes in the 1990s. The development of many high-throughput techniques during the last decades has ensured that bioinformatics has grown into a discipline that overlaps with, and is required for, the modern practice of virtually every field in the life sciences. This has placed a scientific premium on the availability of skilled bioinformaticians, a qualification that is extremely scarce on the African continent. The reasons for this are numerous, although the absence of a skilled bioinformatician at academic institutions to initiate a training process and build sustained capacity seems to be a common African shortcoming. This dearth of bioinformatics expertise has had a knock-on effect on the establishment of many modern high-throughput projects at African institutes, including the comprehensive and systematic analysis of genomes from African populations, which are among the most genetically diverse anywhere on the planet. Recent funding initiatives from the National Institutes of Health and the Wellcome Trust are aimed at ameliorating this shortcoming. In this paper, we discuss the problems that have limited the establishment of the bioinformatics field in Africa, as well as propose specific actions that will help with the education and training of bioinformaticians on the continent. This is an absolute requirement in anticipation of a boom in high-throughput approaches to human health issues unique to data from African populations.

Development of Bioinformatics Infrastructure for Genomics Research in H3Africa

BACKGROUND Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNets role has evolved in response to changing needs from the consortium and the African bioinformatics community. OBJECTIVES H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. METHODS AND RESULTS Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. CONCLUSIONS For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa.

Phylogenetic Analysis and Epidemic History of Hepatitis C Virus Genotype 2 in Tunisia, North Africa

HCV genotype 2 (HCV-2) has a worldwide distribution with prevalence rates that vary from country to country. High genetic diversity and long-term endemicity were suggested in West African countries. A global dispersal of HCV-2 would have occurred during the 20th century, especially in European countries. In Tunisia, genotype 2 was the second prevalent genotype after genotype 1 and most isolates belong to subtypes 2c and 2k. In this study, phylogenetic analyses based on the NS5B genomic sequences of 113 Tunisian HCV isolates from subtypes 2c and 2k were carried out. A Bayesian coalescent-based framework was used to estimate the origin and the spread of these subtypes circulating in Tunisia. Phylogenetic analyses of HCV-2c sequences suggest the absence of country-specific or time-specific variants. In contrast, the phylogenetic grouping of HCV-2k sequences shows the existence of two major genetic clusters that may represent two distinct circulating variants. Coalescent analysis indicated a most recent common ancestor (tMRCA) of Tunisian HCV-2c around 1886 (1869–1902) before the introduction of HCV-2k in 1901 (1867–1931). Our findings suggest that the introduction of HCV-2c in Tunisia is possibly a result of population movements between Tunisia and European population following the French colonization.

Proceedings of a Sickle Cell Disease Ontology workshop — Towards the first comprehensive ontology for Sickle Cell Disease

Sickle cell disease (SCD) is a debilitating single gene disorder caused by a single point mutation that results in physical deformation (i.e. sickling) of erythrocytes at reduced oxygen tensions. Up to 75% of SCD in newborns world-wide occurs in sub-Saharan Africa, where neonatal and childhood mortality from sickle cell related complications is high. While SCD research across the globe is tackling the disease on multiple fronts, advances have yet to significantly impact on the health and quality of life of SCD patients, due to lack of coordination of these disparate efforts. Ensuring data across studies is directly comparable through standardization is a necessary step towards realizing this goal. Such a standardization requires the development and implementation of a disease-specific ontology for SCD that is applicable globally. Ontology development is best achieved by bringing together experts in the domain to contribute their knowledge. The SCD community and H3ABioNet members joined forces at a recent SCD Ontology workshop to develop an ontology covering aspects of SCD under the classes: phenotype, diagnostics, therapeutics, quality of life, disease modifiers and disease stage. The aim of the workshop was for participants to contribute their expertise to development of the structure and contents of the SCD ontology. Here we describe the proceedings of the Sickle Cell Disease Ontology Workshop held in Cape Town South Africa in February 2016 and its outcomes. The objective of the workshop was to bring together experts in SCD from around the world to contribute their expertise to the development of various aspects of the SCD ontology.

The RadioP1 – An Integrative Web Resource for Radioresistant Prokaryotes

The extremely radioresistant eubacterium Deinococcus radiodurans and the phenotyp‐ ically related prokaryotes, whose genomes have been completely sequenced, are presently used as model species in several laboratories to study the lethal effects of DNA-damaging and protein-oxidizing agents, particularly the effects of ionizing radiation (IR). Unfortunately, providing relevant information about radioresistant prokaryotes (RP) in a neatly centralized and organized manner still remains a need. In this study, we designed RadioP1 Web resource (www.radiop.org.tn) to gather information about RP defined by the published literature with specific emphasis on (i) predicted genes that produce and protect against oxidative stress, (ii) predicted proteins involved in DNA repair mechanisms and (iii) potential uses of RP in biotechnology. RadioP1 allows the complete RP proteogenomes to be queried using various patterns in a user-friendly and interactive manner. The output data can be saved in plain text, Excel or HyperText Markup Language (HTML) formats for subsequent analyses. Moreover, RadioP1 provides for users a tool “START ANALY‐ SIS”, including the previously described R-packages “drc” and “lethal”, to generate exponential or sigmoid survival curves with D10 and D50 values. Furthermore, when accessible, links to external databases are provided. Supplementary data will be included in the future when the sequences of other RP genomes will become available.

Identification of key mechanisms controlling gene expression in Leishmania infected macrophages using genome-wide promoter analysis

The present study describes the in silico prediction of the regulatory network of Leishmania infected human macrophages. The construction of the gene regulatory network requires the identification of Transcription Factor Binding Sites (TFBSs) in the regulatory regions (promoters, enhancers) of genes that are regulated upon Leishmania infection. The promoters of human, mouse, rat, dog and chimpanzee genes were first identified in the whole genomes using available experimental data on full length cDNA sequences or deep CAGE tag data (DBTSS, FANTOM3, FANTOM4), mRNA models (ENSEMBL), or using hand annotated data (EPD, TRANSFAC). A phylogenetic footprinting analysis and a MATCH analysis of the promoter sequences were then performed to predict TFBS. Then, an SQL database that integrates all results of promoter analysis as well as other genome annotation information obtained from ENSEMBL, TRANSFAC, TRED (Transcription Regulatory Element Database), ORegAnno and the ENCODE project, was established. Finally publicly available expression data from human Leishmania infected macrophages were analyzed using the genome-wide information on predicted TFBS with the computer system ExPlain™. The gene regulatory network was constructed and activated signal transduction pathways were revealed. The Irak1 pathway was identified as a key pathway regulating gene expression changes in Leishmania infected macrophages.

The PEG-responding desiccome of the alder microsymbiont Frankia alni

Actinorhizal plants are ecologically and economically important. Symbiosis with nitrogen-fixing bacteria allows these woody dicotyledonous plants to colonise soils under nitrogen deficiency, water-stress or other extreme conditions. However, proteins involved in xerotolerance of symbiotic microorganisms have yet to be identified. Here we characterise the polyethylene glycol (PEG)-responding desiccome from the most geographically widespread Gram-positive nitrogen-fixing plant symbiont, Frankia alni, by next-generation proteomics, taking advantage of a Q-Exactive HF tandem mass spectrometer equipped with an ultra-high-field Orbitrap analyser. A total of 2,052 proteins were detected and quantified. Under osmotic stress, PEG-grown F. alni cells increased the abundance of envelope-associated proteins like ABC transporters, mechano-sensitive ion channels and Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-associated (cas) components. Conjointly, dispensable pathways, like nitrogen fixation, aerobic respiration and homologous recombination, were markedly down-regulated. Molecular modelling and docking simulations suggested that the PEG is acting on Frankia partly by filling the inner part of an up-regulated osmotic-stress large conductance mechanosensitive channel.

A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study

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.

Family specific genetic predisposition to breast cancer: results from Tunisian whole exome sequenced breast cancer cases

BackgroundA family history of breast cancer has long been thought to indicate the presence of inherited genetic events that predispose to this disease. In North Africa, many specific epidemio-genetic characteristics have been observed in breast cancer families when compared to Western populations. Despite these specificities, the majority of breast cancer genetics studies performed in North Africa remain restricted to the investigation of the BRCA1 and BRCA2 genes. Thus, comprehensive data at a whole exome or whole genome level from local patients are lacking.MethodsA whole exome sequencing (WES) of seven breast cancer Tunisian families have been performed using a family-based approach. We focused our analysis on BC-TN-F001 family that included two affected members that have been sequenced using WES. Relevant variants identified in BC-TN-F001 have been confirmed using Sanger sequencing. Then, we conducted an integrative analysis by combining our results with those from other WES studies in order to figure out the genetic transmission model of the newly identified genes. Biological network construction and protein–protein interactions analyses have been performed to decipher the molecular mechanisms likely accounting for the role of these genes in breast cancer risk.ResultsSequencing, filtering strategies, and validation analysis have been achieved. For BC-TN-F001, no deleterious mutations have been identified on known breast cancer genes. However, 373 heterozygous, exonic and rare variants have been identified on other candidate genes. After applying several filters, 12 relevant high-risk variants have been selected. Our results showed that these variants seem to be inherited in a family specific model. This hypothesis has been confirmed following a thorough analysis of the reported WES studies. Enriched biological process and protein–protein interaction networks resulted in the identification of four novel breast cancer candidate genes namely MMS19, DNAH3, POLK and KATB6.ConclusionsIn this first WES application on Tunisian breast cancer patients, we highlighted the impact of next generation sequencing technologies in the identification of novel breast cancer candidate genes which may bring new insights into the biological mechanisms of breast carcinogenesis. Our findings showed that the breast cancer predisposition in non-BRCA families may be ethnic and/or family specific.