A regionally based precision medicine implementation initiative in North Africa:The PerMediNA consortium.

Precision Medicine is being increasingly used in the developed world to improve health care. While several Precision Medicine (PM) initiatives have been launched worldwide, their implementations have proven to be more challenging particularly in low- and middle-income countries. To address this issue, the "Personalized Medicine in North Africa" initiative (PerMediNA) was launched in three North African countries namely Tunisia, Algeria and Morocco. PerMediNA is coordinated by Institut Pasteur de Tunis together with the French Ministry for Europe and Foreign Affairs, with the support of Institut Pasteur in France. The project is carried out along with Institut Pasteur d'Algérie and Institut Pasteur du Maroc in collaboration with national and international leading institutions in the field of PM including Institut Gustave Roussy in Paris. PerMediNA aims to assess the readiness level of PM implementation in North Africa, to strengthen PM infrastructure, to provide workforce training, to generate genomic data on North African populations, to implement cost effective, affordable and sustainable genetic testing for cancer patients and to inform policy makers on how to translate research knowledge into health products and services. Gender equity and involvement of young scientists in this implementation process are other key goals of the PerMediNA project. In this paper, we are describing PerMediNA as the first PM implementation initiative in North Africa. Such initiatives contribute significantly in shortening existing health disparities and inequities between developed and developing countries and accelerate access to innovative treatments for global health.

Mycobacterium tuberculosis-THP-1 like macrophages protein-protein interaction map revealed through dual RNA-seq analysis and a computational approach.

Introduction. Infection caused by Mycobacterium tuberculosis (M. tb) is still a leading cause of mortality worldwide with estimated 1.4 million deaths annually.Hypothesis/Gap statement. Despite macrophages' ability to kill bacterium, M. tb can grow inside these innate immune cells and the exploration of the infection has traditionally been characterized by a one-sided relationship, concentrating solely on the host or examining the pathogen in isolation.Aim. Because of only a handful of M. tb-host interactions have been experimentally characterized, our main goal is to predict protein-protein interactions during the early phases of the infection.Methodology. In this work, we performed an integrative computational approach that exploits differentially expressed genes obtained from Dual RNA-seq analysis combined with known domain-domain interactions.Results. A total of 2381 and 7214 genes were identified as differentially expressed in M. tb and in THP-1-like macrophages, respectively, revealing different transcriptional profiles in response to infection. Over 48 h of infection, the host-pathogen network revealed 25 016 PPIs. Analysis of the resulting predicted network based on cellular localization information of M. tb proteins, indicated the implication of interacting nodes including the bacterial PE/PPE/PE_PGRS family. In addition, M. tb proteins interacted with host proteins involved in NF-kB signalling pathway as well as interfering with the host apoptosis ability via the potential interaction of M. tb TB16.3 with human TAB1 and M. tb GroEL2 with host protein kinase C delta, respectively.Conclusion. The prediction of the full range of interactions between M. tb and host will contribute to better understanding of the pathogenesis of this bacterium and may provide advanced approaches to explore new therapeutic targets against tuberculosis.

DisintegrinDB: The first integrated database resource of disintegrins from snake venoms.

Nowadays, a large number of databases have been developed gathering different types of therapeutic peptides including antimicrobial, antiviral and scorpion toxins peptides facilitating the searching for these molecules and their structural characteristics and pharmacology. Disintegrins, a family of small non-enzymatic and cysteine-rich proteins found in the snake venom may have a potential role in terms of novel therapeutic leads for cancer treatment. Despite their therapeutic effect, no database dedicated to disintegrins is available yet. Indeed, accessible information related to disintegrins are either scattered or fragmented in different databases from which it becomes extremely difficult to collect all the properties related to a particular disintegrin without exploring numerous databases available through distinct websites. Here, we propose DisintegrinDB as a first unique resource centralizing data related to disintegrins from snake venom. DisintegrinDB aims to facilitate the search on a given disintegrin and centralizes all the information on these peptides, helping researchers to retrieve all relevant related information.

The First Snake Venom KTS/Disintegrins-Integrin Interactions Using Bioinformatics Approaches.

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 α1ß1 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 α1ß1 receptors, which could improve the selection process of the best active molecules for antitumor therapies.