Baobab Index

The Red Sea is a unique oligotrophic marine ecosystem characterized by high salinity, elevated temperatures, and increasing anthropogenic pressures along its coastal regions. However, coastal sediment-associated microbial communities and their functional potential, particularly regarding antimicrobial resistance and aromatic compound degradation, remain insufficiently explored. This study investigated bacterial diversity in coastal sediments from six sites along the eastern Red Sea using 16S rRNA gene amplicon sequencing and gained functional insights through genome sequencing of 21 cultured bacterial isolates. Amplicon sequencing revealed diverse bacterial communities dominated by Proteobacteria, followed by Bacteroidetes and Planctomycetes. Alpha diversity indices showed no significant variation among sites, whereas beta diversity analysis demonstrated distinct community clustering influenced by environmental parameters, including temperature, salinity, and pH. Genomic analysis of 21 isolates identified multiple antimicrobial resistance genes (ARGs), conferring resistance to clinically relevant antibiotics such as beta-lactams, fluoroquinolones, and tetracyclines, alongside metal resistance determinants. Putative carbapenem resistance genes were detected in Vibrio and Idiomarina isolates. Genomic annotation predicted substantial variability in aromatic hydrocarbon degradation capacity among isolates. Genera including Marinobacter, Ruegeria, and Halomonas exhibited extensive gene interaction networks, indicating enhanced metabolic adaptability and bioremediation potential, whereas other taxa displayed limited functional connectivity, suggesting niche specialization. Overall, this study identifies that Red Sea coastal sediments harbor taxonomically distinct bacterial communities that carry a reservoir of ARGs and possess pollutant-degradation capabilities, providing insights for environmental health monitoring and biotechnological applications in pollution remediation.

Despite major progress in generation of edited embryos and offspring via CRISPR/Cas9-RNP electroporation, editing outcomes remain highly variable. This variability may be due to intrinsic differences between in vivo-derived (IVV) and in vitro-derived (IVT) zygotes, which may play a more decisive role than previously anticipated. Therefore, this study aimed to determine how zygote origin shapes the sensitivity to electrical voltage field and editing susceptibility after CRISPR/Cas9-RNP electroporation in the bovine model. The present study systematically compared subsequent developmental competence and editing events in IVV- and IVT-derived bovine zygotes across defined electroporation voltages and pulse durations. Notably, CRISPR/Cas9-RNP electroporation of IVV-derived bovine zygotes of comparable age and collected by tubal embryo flushing (10-18 h post ovulation, hpo) resulted in markedly lower survival rates at 25 and 30 V compared to 20 V. In contrast, higher (p < 0.05) editing frequencies were observed at 25 V and 30 V. Clear differences, however, were observed between the two zygote groups. Following CRISPR/Cas9 RNP electroporation, IVV-derived zygotes yielded a higher proportion of unedited blastocysts (p < 0.05), absence of full edited embryos, a significantly increased frequency of monoallelic edits and reduced rates of mosaicism compared to IVT-derived zygotes. Collectively, the results of the present study clearly underscore a significant lower editing efficiency to pulse sensitivity ratio in IVV-derived zygotes compared to their IVT counterparts. To our knowledge, this is the first study to use bovine IVV-derived zygotes for genome editing using RNP-electroporation to elucidate how zygote origin shapes sensitivity to electrical voltage field and editing efficiency.

Antimicrobial resistance (AMR) is an emerging global problem, particularly for, resource-limited countries (RLCs) with limited capacity to diagnose diseases, inadequate surveillance systems, insufficient antimicrobial stewardship, and poor, health facilities. Conventional AMR surveillance relies primarily on post hoc laboratory, reporting and is not able to provide real-time data to aid in making effective clinical and, public health decisions. AMR surveillance is being revolutionized with the introduction, of point-of-care (PoC) diagnostics, digital health technologies, and artificial intelligence, (AI) that offer rapid pathogen identification, real-time data collection, and predictive, analysis. This review highlights the evolution of the AMR surveillance system from, conventional lab-based techniques to using AI and data to inform decision-making for, RLCs. Evidence is being collected on new PoC diagnostic platforms, biosensors, genomic surveillance, and Internet of Things (IoT) technologies and machine learning, (ML) algorithms developed from clinical, microbiological, genomic, and epidemiological, data to help improve resistance detection, antimicrobial prescribing, antimicrobial, stewardship, and outbreak prediction. We also explore the challenges of, implementation, such as lack of digital infrastructure, data interoperability, workforce, capacity, algorithmic bias, ethical and regulatory considerations, and sustainable, funding in AMR surveillance. The potential of new innovations like Mobile health, (mHealth), Internet of Things (IoT), Federated Learning (FL), and AI is highlighted as, necessary tools to help ensure greater scale, transparency, and equitable deployment., Lastly, we suggest an integrated approach, which brings together AMR PoC, diagnostics, clinical decision support using AI, and One Health surveillance to improve, the monitoring and response to AMR. Therefore, this review provides a pathway to, implementing resilient, intelligent, and equitable AMR surveillance systems and, illustrates how technological innovation can be linked to AMR system implementation, for better patient outcomes and implementation of evidence-based public health, policies in RLCs.

The persistence of chlorine-tolerant Escherichia coli in wastewater treatment systems, which constitutes a major hazard to public health, highlights the need for alternative biological disinfection methods like phage-based biocontrol. However, relatively few studies have evaluated well-characterized bacteriophages under wastewater conditions that are similar to real-world treatment settings. This study aimed to isolate and characterize a bacteriophage targeting a putative chlorine-tolerant Escherichia coli, and evaluate it under wastewater conditions. Bacteriophage infecting an environmental Escherichia coli strain was isolated from wastewater. The phage was characterized via host range, transmission electron microscopy (TEM), thermal and pH stability, chlorine stability, and one-step growth curve dynamics. Whole-genome sequencing was performed for molecular profiling. After thorough biological characterization, the phage was tested in a spiked heat-sterilized wastewater microcosm and in conditions more similar to those found in real wastewater treatment settings. Phage vB_EcoM_Ww_Az2 infecting a putative chlorine-tolerant Escherichia coli Az_5 was isolated. It was classified within the class Caudoviricetes and the family Drexlerviridae based on genomic and phylogenetic analyses. It exhibited high stability across pH 4-12 and tolerated temperatures up to 55 °C for 15 min. The phage demonstrated an 84% adsorption rate within 15 min, a 30-min latent period, a 15-min rise period, and a burst size of 67 PFU/cell. At an MOI ≥ 5, it completely eliminated E. coli Az_5 within 2 h at 37 °C. In a spiked heat-sterilized wastewater microcosm (MOI = 5), the phage reduced the host population by 5 Log These results offer experimental evidence that using a well-characterized Drexlerviridae phage as a complementary biocontrol agent in real wastewater treatment systems is feasible and promising.

Black soldier fly larvae (BSFL) have emerged as a promising and sustainable source of ingredients for animal feed due to their rapid growth and ability to efficiently bioconvert different organic waste and by-products into high-nutritional-quality insect biomass. Although considerable research has focused on the optimization of larval rearing conditions to improve the chemical composition of the insect biomass, the interplay between diet composition and immune function in BSFL remains poorly understood. Herein, we investigated how two diets differing in their protein-to-carbohydrate (P:C) ratio affect larval performance and the immune response following bacterial challenge. Our results demonstrate that dietary P:C ratio influences both growth and immunity in BSFL. Specifically, larvae fed on the diet with lower P:C ratio (0.32) reached a higher body weight than those grown on the higher P:C ratio diet (1.28), while developmental time and adult emergence rate were unaffected. In contrast, BSFL reared on the higher P:C ratio diet exhibited an enhanced immune response, characterised by an increased number of circulating haemocytes and upregulated expression of antimicrobial peptides genes, resulting in a more rapid bacterial clearance. Collectively, our findings demonstrate that, under these two dietary conditions, macronutrient composition drives distinct trade-offs between growth and antibacterial immune response in BSFL. These results provide a foundation for future studies aimed at identifying nutritionally optimised feeding strategies that balance biomass production with disease resistance under industrial rearing conditions.

Malaria remains a major global health challenge, with the World Health Organization (WHO) African Region accounting for the overwhelming majority of malaria cases and deaths worldwide. This narrative review examines the contribution of community-centric malaria prevention approaches to malaria elimination pathways and their broader global health implications in Sub-Saharan Africa. A narrative literature review was conducted using PubMed/MEDLINE, Scopus, Web of Science, Google Scholar, and WHO databases. Literature published between January 2000 and December 2025 was identified using combinations of keywords including "malaria elimination," "community engagement," "community health workers," "vector control," "malaria prevention," and "Sub-Saharan Africa." Eligible evidence included peer-reviewed studies, implementation research, policy documents, and global malaria reports addressing community-based prevention, surveillance, diagnosis, treatment, and elimination strategies. Findings were synthesized thematically. The review identified community health workers, community-directed vector control, health education, environmental management, ITN promotion, IRS participation, SMC delivery, IPTp uptake, and digital surveillance as key drivers of malaria prevention. Community-centered approaches improved intervention acceptance, early diagnosis, treatment access, surveillance capacity, and local ownership of malaria programs. Emerging technologies, including artificial intelligence, geospatial mapping, and genomic surveillance, provide opportunities for precision malaria control when integrated with community systems. Community-centered malaria prevention represents a critical pathway toward sustainable elimination in Sub-Saharan Africa. Strengthening community empowerment, integrating scientific innovations with local knowledge, and improving health-system partnerships are essential for accelerating malaria elimination and advancing global health equity.

Typhoid fever remains a major public health concern in South Africa. However, the role of urban waterways as environmental reservoirs and contributors to the spread of resistant Salmonella Typhi remains poorly understood. This study characterized four S. Typhi isolates recovered from the Jukskei River in Johannesburg, South Africa, using whole-genome sequencing. Genomic DNA was extracted and sequenced on the Illumina NextSeq. 2000 platform, and assembled genomes were analyzed for sequence types (STs), AMR determinants, plasmids, virulence factors, and phylogenetic relatedness using 124 clinical Salmonella genomes for comparison. All isolates were confirmed as S. Typhi, comprising ST1 (n = 2) and ST2 (n = 2). The ST1 isolates belonged to the H58 lineage (genotype 4.3.1.1), with isolate BRSA001 further classified as a sublineage 4.3.1.1. EA1. The ST1 isolates were multidrug-resistant, carrying the IncQ1 plasmid and resistant genes, including aph(6)-Id, aph(3″)-Ib, bla

Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. The logit-scale heritability of breast cancer ranged from h2=0.47 (SE = 0.07) in EAS to AFR h2=0.61 (SE = 0.10), with no significant differences across ancestries (p = 0.63). The model-implied number of non-null susceptibility SNPs in the sparse normal-mixture effect-size model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p = 0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (ρ=0.79, SE = 0.08) and weakest between AFR and H/L (ρ=0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.

Allergic rhinitis is a common chronic inflammatory disease affecting millions of people worldwide and substantially impairing quality of life. This study aimed to investigate the association of the IL-4 rs2243250 polymorphism with allergic rhinitis, inflammatory markers, and leukocyte profiles. A total of 182 participants were included, comprising 91 patients with allergic rhinitis and 91 healthy controls. Peripheral blood samples were collected for complete blood count, DNA extraction, and measurement of IL-4, IL-13, and IgE levels using enzyme-linked immunosorbent assays. Skin prick testing for weed, grass, tree, and mite allergens was performed to confirm IgE-mediated sensitization. The IL-4 rs2243250 polymorphism was detected by polymerase chain reaction followed by restriction fragment length polymorphism analysis using the AvaII restriction enzyme. Significant differences (P < 0.001) between patients and controls were observed for all investigated immunological markers and differential white blood cell counts. For rs2243250, the CC genotype was associated with a reduced likelihood of allergic rhinitis (OR = 0.25; 95% CI: 0.11-0.55), whereas the TT genotype was associated with an increased likelihood (OR = 3.8; 95% CI: 1.82-8.17). Similarly, the C allele was associated with reduced disease likelihood (OR = 0.35; 95% CI: 0.23-0.53), while the T allele was associated with increased likelihood (OR = 2.88; 95% CI: 1.88-4.41; P < 0.001). Significant positive correlations among several white blood cell types were also observed. The findings demonstrate an association between the IL-4 rs2243250 polymorphism and allergic rhinitis. The C allele and CC genotype were associated with reduced disease likelihood, whereas the T allele and TT genotype were associated with increased likelihood. These genetic associations, together with alterations in inflammatory markers and leukocyte profiles, may contribute to understanding susceptibility to allergic rhinitis.

GABA-producing lactic acid bacteria are gaining attention as psychobiotics capable of influencing the microbiota-gut-brain axis, yet marine-derived strains remain poorly characterized. Here, the complete genomic characterization is reported for the marine strain Lactiplantibacillus plantarum EI6, focusing on its probiotic potential, GABA production, and safety. The 3.3 Mb genome (44.5% GC) encodes multiple probiotic-associated genes for acid/bile tolerance, adhesion, and stress response (including heat and cold-shock adaptation), antioxidant activity, and immunomodulation. Genome mining identified the glutamate decarboxylase system (gadB), and GABA production was experimentally confirmed by TLC and HPLC analysis, with a production level of 0.96 g/L. The genome also contains putative bacteriocin gene clusters (plantaricins and sactipeptides) and secondary metabolite BGCs (terpenes, RiPP-like, T3PKS). Safety analysis revealed no major virulence factors or antibiotic resistance genes, supporting a non-pathogenic profile. These findings position L. plantarum EI6 as a promising safe potential psychobiotic candidate for neuroactive and functional food applications.