The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Effect of identified non-synonymous mutations in DPP4 receptor binding residues among highly exposed human population in Morocco to MERS-CoV through computational approach

Dipeptidyl peptidase 4 (DPP4) has been identified as the main receptor of MERS-CoV facilitating its cellular entry and enhancing its viral replication upon the emergence of this novel coronavirus. DPP4 receptor is highly conserved among many species, but the genetic variability among direct binding residues to MERS-CoV restrained its cellular tropism to humans, camels and bats. The occurrence of natural polymorphisms in human DPP4 binding residues is not well characterized. Therefore, we aimed to assess the presence of potential mutations in DPP4 receptor binding domain (RBD) among a population highly exposed to MERS-CoV in Morocco and predict their effect on DPP4 –MERS-CoV binding affinity through a computational approach. DPP4 synonymous and non-synonymous mutations were identified by sanger sequencing, and their effect were modelled by mutation prediction tools, docking and molecular dynamics (MD) simulation to evaluate structural changes in human DPP4 protein bound to MERS-CoV S1 RBD protein. We identified eight mutations, two synonymous mutations (A291 =, R317 =) and six non-synonymous mutations (N229I, K267E, K267N, T288P, L294V, I295L). Through docking and MD simulation techniques, the chimeric DPP4 –MERS-CoV S1 RBD protein complex models carrying one of the identified non-synonymous mutations sustained a stable binding affinity for the complex that might lead to a robust cellular attachment of MERS-CoV except for the DPP4 N229I mutation. The latter is notable for a loss of binding affinity of DPP4 with MERS-CoV S1 RBD that might affect negatively on cellular entry of the virus. It is important to confirm our molecular modelling prediction with in-vitro studies to acquire a broader overview of the effect of these identified mutations.</jats:p

Computational analysis of structural and functional evaluation of the deleterious missense variants in the human <i>CTLA4</i> gene

CTLA-4 is an immune checkpoint receptor that negatively regulates the T-cell function expressed after T-cell activation to break the immune response. The current study predicted the genomic analysis to explore the functional variations of missense SNPs in the human CTLA4 gene using PolyPhen2, SIFT, PANTHER, PROVEAN, Fathmm, Mutation Assessor, PhD-SNP, SNPs&GO, SNAP2, and MutPred2. Phylogenetic conservation protein was predicted by ConSurf. Protein structural analysis was carried out by I-Mutant3, MUpro, iStable2, PremPS, and ERIS servers. Molecular dynamics trajectory analysis (RMSD, RMSF, Rg, SASA, H-bonds, and PCA) was performed to analyze the dynamic behavior of native and mutant CTLA-4 at the atomic level. Our in-silico analysis suggested that C58S, G118R, P137Q, P137R, P137L, P138T, and G146L variants were predicted to be the most deleterious missense variants and highly conserved residues. Moreover, the molecular dynamics analysis proposed a decrease in the protein stability and compactness with the P137R and P138T highlighting the impact of these variants on the function of the CTLA-4 protein. Communicated by Ramaswamy H. Sarma</p

Number of hydrogen bonds at the interface level of interacting residues of MERS-CoV S1 RBD protein and human <i>DPP4</i> wild and mutant types during 150 ns of the molecular dynamics simulation period.

(a) H-bond 4L72-WT vs 4L72-N229I. (b) H-bond 4L72-WT vs 4L72-K267N. (c) H-bond 4L72-WT vs 4L72-K267E. (d) H-bond 4L72-WT vs 4L72-T288P. (e) H-bond 4L72-WT vs 4L72-L294V. (f) H-bond 4L72-WT vs 4L72-I295L.</p

Cα-Backbone rayon of gyration (Rg) and solvent accessible surface area (SASA) of individual component <i>DPP4</i> and MERS-CoV S1 RBD.

(a) Cα-Backbone Radius of gyration (Rg) of the human DPP4 protein during 150 ns of the molecular dynamics simulation period. (b) Cα-Backbone Radius of gyration (Rg) of MERS-CoV S1 RBD protein during 150 ns of the molecular dynamics simulation period. (c) Solvent accessible surface area (SASA) of the human DPP4 protein during 150 ns of the molecular dynamics simulation period. (d) Solvent accessible surface area (SASA) of the MERS-CoV S1 RBD protein during 150 ns of the molecular dynamics simulation period. (TIF)</p

Structural model of wild and mutant 4L72 models after 150 ns MD simulation.

Residues substituted are marked in red, residues involved in hydrophobic interactions are indicated in magenta, residues engaging simultaneous hydrogen bonding and hydrophobic contacts are indicated in green. DPP4 (chain A) and MERS-CoV S1 RBD protein (chain B) are dyed respectively with grey and blue. Ligands (NAG, BMA) are highlighted in pink. Hydrogen bonds are shown in black line and hydrophobic/ionic contacts are shown in yellow line.</p

Alignment of human and animal <i>DPP4</i> protein sequences by Clustal W.

Identical amino acid residues in different species are highlighted with the same residue colour. Mutations identified in this study are highlighted in black.</p

Assessment of the effect of human <i>DPP4</i> mutations identified among the population study on protein-protein interaction (PPI) using computational prediction tools Mutabind2 and DynaMut.

Assessment of the effect of human DPP4 mutations identified among the population study on protein-protein interaction (PPI) using computational prediction tools Mutabind2 and DynaMut.</p