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

Selective Non-toxics Inhibitors Targeting DHFR for Tuberculosis and Cancer Therapy: Pharmacophore Generation and Molecular Dynamics Simulation

Dihydrofolate reductase (DHFR) is a crucial enzyme that catalyzes the conversion of folic acid. Its reserved properties and significance in both human (h-DHFR) and mycobacterium (mt-DHFR) make it a challenging target for developing drugs against cancer and bacterial infections. Although methotrexate (MTX) is commonly used for cancer therapy and bacterial infections, it has a toxic profile. In this study, we aimed to identify selective and non-toxic inhibitors against h-DHFR and mt-DHFR using an in silico approach. From a data set of 8 412 inhibitors, 11 compounds passed the toxicity and drug-likeness tests, and their interaction with h-DHFR and mt-DHFR was studied by performing molecular docking. To evaluate the inhibitory activity of the compounds against mt-DHFR, five known reference ligands and the natural ligand (dihydrofolate) were used to generate a pharmacophoric map. Two potential selective inhibitors for mt-DHFR and h-DHFR were selected for further investigation using molecular dynamics for 100 ns. As a result, BDBM18226 was identified as the best compound selective for mt-DHFR, non-toxic, with five features listed in the map, with a binding energy of –9.6 kcal/mol. BDBM50145798 was identified as a non-toxic selective compound with a better affinity than MTX for h-DHFR. Molecular dynamics of the two best ligands suggest that they provide more stable, compact, and hydrogen bond interactions with the protein. Our findings could significantly expand the chemical space for new mt-DHFR inhibitors and provide a non-toxic alternative toward h-DHFR for the respective treatment of tuberculosis and cancer therapy