Baobab Index

This cross-sectional study characterized virulence factors, disinfectant resistance genes, and antimicrobial resistance determinants in multidrug-resistant Twenty-three isolates were identified using biochemical tests and MALDI-TOF, followed by antimicrobial susceptibility testing (AST) and whole-genome sequencing (WGS). Bioinformatic analyses assessed antimicrobial resistance genes (ARGs), virulence factors (VFs), disinfectant resistance genes (DRGs), sequence types, phylogenetic relationships, and co-occurrence with plasmid-associated sequences. High phenotypic resistance was observed to ampicillin (70%) and amoxicillin and cefuroxime (≥50%). WGS identified clinically important lineages, including Wastewater-based genomic surveillance provides an effective approach for characterizing AMR, virulence, and disinfectant resistance, supporting genome-informed surveillance and wastewater management in water-scarce settings.

The keloids scar is a skin scarring pathology with a higher frequency in the black population. Several genetic polymorphisms, including those of transforming growth factor receptors, have been identified as probable susceptibility genes. This study aimed to characterize the polymorphisms of This was a cross-sectional study that included 141 subjects with keloids and conducted from April 2021 to April 2022. Genomic DNA was extracted using the "PureLink The average age of the study population was 34 ± 15 years and O Rhesus positive blood group (O+) was predominant (36.88%). All subjects (100%) were heterozygous (TG) for rs121918710. Medical or surgical history, family history, blood type, and rs28934568 polymorphism were related to the number of sites of keloids on the body. Patients with a medical history (9.8%) were carriers of the mutant allele C for rs28934568. Mossi ethnic had more than 8 times risk of developing a keloid scar (p=0.030; OR=8.66 (95% CI: 1.230-60.902). The presence in all the patients of the mutated allele for the

Sub-Saharan Africa suffers devastating animal health losses exceeding $20 billion each year. By combining metagenomics with artificial intelligence (AI), a promising path emerges for faster diagnostics and proactive disease prediction. Our PRISMA-guided review of 1,225 studies reveals that metagenomics achieves 94.2% diagnostic sensitivity (compared to 67.3% with conventional methods), while AI dramatically shortens turnaround from 48-72h to just 4-8h, offering a valuable 14-18 day early warning window for epizootics.

Pathogen surveillance is vital for managing infectious diseases in Africa, where high disease burdens necessitate advanced tools like genomics and bioinformatics. While these technologies enable early detection, resistance monitoring, and targeted interventions, yet their adoption is hindered by limited training and educational resources. This scoping review maps existing training programmes in genomics and bioinformatics for pathogen surveillance in Africa, identifying gaps and opportunities to enhance capacity-building. Following PRISMA-ScR guidelines, we systematically searched databases (PubMed, Embase, Scopus, etc.) and grey literature for articles which described the design, implementation, delivery, or evaluation of a specific genomics/bioinformatics training programme or discussed training needs or status published between November 2014 and December 2025. Eligible articles focused on genomics or bioinformatics training for pathogen surveillance in Africa. Data were extracted on programme characteristics, outcomes, challenges, and recommendations, with findings synthesised narratively and thematically. Of 2491 identified articles, 40 were included, spanning 2014-2025. These comprised case studies (45%), opinion pieces (27.5%), reviews (15%), cross-sectional studies (10%), and a methodological study (2.8%). Twenty-three articles detailed specific training programmes, predominantly short-term (e.g., 2-14 days), with 60.9% of the training programmes covering both genomics and bioinformatics. Training programmes were mostly carried out in African countries (91.3%), often funded by external agencies like NIH (26.1%) and Wellcome Trust (13%). Key outcomes included enhanced technical skills (21.7%) and career development (17.4%). Challenges included inadequate infrastructure, skill gaps, and theoretical-heavy curricula, while opportunities encompassed virtual delivery, collaborative networks, and open-access resources. Seventeen studies were included as they examined training status and deficiencies in Africa, highlighting limited expertise and brain drain, and recommending investment in infrastructure, expansion of curricula, and development of local trainers. Genomics and bioinformatics training in Africa is growing but remains fragmented, donor-dependent, and resource-constrained. Sustainable capacity-building requires institutionalising training within academic systems, increasing government investment, and leveraging open-access and regional networks. These findings provide a foundation for policymakers and educators to develop targeted, inclusive programmes, strengthening Africa's pathogen surveillance capabilities. N/A.

Identifying the mechanisms of host-parasite interactions in vivo in malaria is essential for the development of antimalarial strategies tailored to clinically and physiologically relevant contexts. We analyzed 396 paired global serum lipidomes from pediatric patients sampled before and during blood-stage malaria infection in Burkina Faso, spanning three ethnic groups (Gouin, Mossi, and Fulani). Consistent infection-induced remodeling of the host lipidome was identified across populations, including depletion of 47 host-derived lipid species that correlated with parasitemia. Notably, we observed that Plasmodium falciparum selectively scavenges linoleic acid-containing phospholipids to support its proliferation and validated this with parasite culture assays. This integrative multi-omics analysis combining lipidomic profiles with host-parasite transcriptomes further identified a Plasmodium falciparum transcriptional program associated with lipid turnover in vivo. These results provide a high-resolution profile of lipidomic perturbations in malarial children and demonstrate how integrated clinical phenotyping, cross-ethnic population sampling, and multi-omics can reveal key host-parasite interactions and clinically relevant metabolic changes within the human host.

The human gut virome is a critical yet understudied component of the microbiome that shapes microbial community structure and host-microbe interactions. However, most existing human gut virome reference databases have been constructed predominantly from populations in high-income countries, resulting in the substantial underrepresentation of African populations. To help address this disparity, we developed the Kenyan Human Gut Virome Catalogue (KHGVC), the first comprehensive human gut virome resource for Kenya and the first country-specific human gut virome catalogue from Africa. Using a standardized viromics pipeline applied to 626 fecal metagenomes spanning infants and adults across three Kenyan counties, we reconstructed 116,968 viral operational taxonomic units (vOTUs). Cross-catalogue comparisons revealed extensive novelty where 65.6% of KHGVC's vOTUs larger than 10 kb lacked matches in five major human gut virome databases, and 95% remained unique relative to the Unified Human Gut Virome (UHGV). Temperate bacteriophages accounted for ~ 70% of vOTUs, supporting a major role for lysogeny in gut ecosystem stability. Functional annotation assigned putative roles to ~ 27% of predicted viral proteins, primarily structural and replication-associated functions. Application of KHGVC revealed pronounced age-dependent virome structuring in which infant viromes were less diverse and enriched in Bifidobacterium-infecting phages, including Bifidobacterium longum, whereas adult viromes exhibited greater diversity and expansion of Prevotella-associated phages. Together, the KHGVC substantially expands known human gut viral diversity and provides a foundational reference for Kenyan and African virome research. The KHGVC can be accessed freely through a publicly available interactive web interface (https://igmr.org/software/kenyavirocat).

Antimicrobial resistance (AMR) is an urgent global health threat, intensified by the widespread use of antimicrobials in livestock production. This study synthesizes the current landscape of combining metagenomic sequencing with artificial intelligence (machine learning and deep learning) to characterize, surveil, and predict AMR within the One Health framework. A comprehensive multi-database literature search was conducted, and, following PRISMA guidelines, 10 peer-reviewed studies meeting the inclusion criteria were selected for full synthesis. Metagenomic shotgun sequencing significantly surpasses conventional culture-based methods by directly capturing antimicrobial resistance genes (ARGs) from complex biological communities. AI algorithms substantially outperform traditional bioinformatic tools, achieving high predictive accuracy (AUC-ROC > 0.90) and revealing consistent ARG transfer pathways that link livestock, human, and environmental compartments. Integrating metagenomics with AI delivers a paradigm shift for proactive AMR surveillance. However, standardization, interpretability, and technological adaptation to resource-limited settings-especially in sub-Saharan Africa-remain urgent priorities to inform effective public health policy.

The Anopheles gambiae species complex comprises about nine sibling species, including An. gambiae, An. coluzzii, and An. arabiensis, three of the four major malaria vector species across Africa. Insecticide-based vector control remains the most critical tool in the fight against malaria, with a heavy reliance on pyrethroid insecticides. However, widespread pyrethroid resistance jeopardises the effectiveness of these methods. Currently, the number of diagnostic markers available to track pyrethroid resistance in endemic settings is limited, focusing mainly on changes at the insecticide target site. Genetic analysis of seven insecticide-resistant populations from West Africa, a region with intense insecticide resistance, reveals shared loci associated with pyrethroid resistance among the sister species An. gambiae, An. coluzzii, and An. arabiensis including kdr, GSTE1-8 and the CYP6P region. Notably, a mutation in the voltage-gated sodium channel, I1527T, previously identified in An. coluzzii and An. gambiae, was detected in wild-caught An. arabiensis from Burkina Faso. Additionally, a mutation, L207I, in GSTE7 common to An. coluzzii and An. arabiensis, significantly increases survivorship to deltamethrin. With the additional integration of RNAseq and data from the Anopheles gambiae 1000 genomes project, we were able to identify putative eQTLs associated with the expression of major insecticide resistance-related transcripts, such as CYP6P3, CYP9K1 and CYP6AA1. This study reveals several potential diagnostic markers of resistance that can be implemented in endemic settings and identifies putative introgression between An. arabiensis and An. coluzzii in Burkina Faso.

In order to meet the expected maize yield by 2050, breeders must work to improve breeding program efficiency by intensifying the implementation of new and improved technologies such as marker-assisted selection (MAS). Dissecting the genomic regions associated with drought tolerance is the first step forward in MAS program deployment for maize improvement under drought stress. Genome-wide association studies (GWAS) were used to investigate and identify quantitative trait loci (QTLs) associated with six traits under drought stress. One hundred and eighty-seven extra-early orange maize inbred lines were evaluated under managed drought stress at Ikenne, in Nigeria, during the 2022 and 2023 dry seasons. The materials were also genotyped using 9355 DArTseq SNP markers and analyzed using the enriched compressed mixed linear model (ECMLM). Enriched compressed mixed linear model was used for association-trait analysis. The ECMLM-based GWAS identified 45 candidate genomic loci associated with the six traits, including five for grain yield, with R