Biology subjects

Ngonga, F.

Publications and source records attributed to Ngonga, F..

2 recordsLinked to original sources

bioRxiv2025

Co-occurrence of Antibiotic Residues and Antimicrobial Resistance Genes in Animal Manure and Agricultural Soils from Machakos, Kiambu, and Kajiado Counties, Kenya

The excessive and often unregulated use of antibiotics in livestock production and human health has led to the dissemination of antibiotic residues and antibiotic resistance genes (ARGs) posing a serious threat to the environment and public health. This study investigates the co-occurrence and spatial distribution of antibiotic residues and ARGs in livestock manure and agricultural soils from Machakos, Kiambu, and Kajiado counties in Kenya, regions characterized by intensive livestock farming. A total of 180 samples from 30 farms across the three counties were collected and pooled into 18 samples. Antibiotic residues were extracted and quantified using high-performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Nine ARGs (aadA, ermB, sul1, tetQ, tetW, dfrA1, blaMOX, blaOXA and qnrB were quantified via absolute and relative qPCR, normalized to 16s rRNA gene copy numbers. Multivariate analyses, including PCoA and Spearman Correlation, were conducted to explore ARG structure and co-occurrence. Tetracycline, particularly oxytetracycline, was the most abundant antibiotic (up to 1150 ng/mL), especially in pig manure from Kiambu. Sulfadimethoxin was undetectable in nearly all samples except in soil mixed with pig manure from Kajiado county, which showed a concentration above 70 ng/mL, the pig manure from the same county had levels below 2 ng/mL. Sulfadimidin, sulfamethoxanol and erythromycin were not detected in all samples. A three-way ANOVA showed that animal source and sample type were generally not significant factors in antibiotic concentration, but oxytetracycline (p= 0.0421, 0.0901) and sulfadimethoxin (P =0.0904, 0.044, 0.054) showed marginal significance by sample type (P=0.0785). Antibiotic resistance genes were widely distributed, with aadA, ermB and sul1 being the most prevalent, especially in soils from Kiambu and Machakos. TetQ showed extremely high relative abundance, indicating intense tetracycline selection pressure. Strong positive correlations were observed between co-occurring ARGs, including tetQ and tetW and erm and sul1. The concurrent detection of persistent antibiotic residues and high ARG loads in both manure and soils underscores the urgent need for improved antibiotic stewardship, sustainable manure management, and environmental monitoring in Kenyan agroecosystems.

molecular biology↗

bioRxiv2025

Mutational and Expression Profile of ZNF217, ZNF750, ZNF703 Zinc Finger Genes in Kenya Women diagnosed with Breast Cancer

ObjectiveTo characterize the mutational landscape and expression profiles of ZNF217, ZNF703, and ZNF750, and assess their clinical relevance in breast cancer patients from Kenya. MethodsWhole-exome sequencing (WES) and RNA sequencing (RNA-Seq) data from 23 paired tumor-normal samples were analyzed in a Linux-based environment. Somatic mutations were identified using MuTect2 following alignment to the hg38 reference genome and annotation with VEP. Variants were classified by type, coding consequence, and protein position, and mapped to functional domains. Recurrent mutations were identified, and comparisons were made with The Cancer Genome Atlas (TCGA). Gene expression was quantified using STAR and featureCounts, normalized with DESeq2, and analyzed using paired statistical tests with multiple testing correction. Principal component analysis (PCA) and regression analyses were performed to assess expression patterns and clinical associations. ResultsZNF217 and ZNF750 exhibited high mutational burdens, whereas ZNF703 showed a lower mutation frequency. Mutations were predominantly single nucleotide variants, with missense and synonymous variants as the major classes. Variants were distributed across protein sequences, with limited domain enrichment and no clear hotspot clustering. Recurrent mutations were gene-specific and infrequent. Comparison with TCGA data showed concordant mutation prevalence for ZNF217, low frequency for ZNF703, and absence of ZNF750 mutations. All three genes were significantly upregulated in tumors compared to matched normal tissues (ZNF217: p = 0.00068; ZNF703: p = 0.00475; ZNF750: p = 0.00366). Tumor expression exceeded normal expression in 74% of cases for ZNF217, 64% for ZNF703, and 83% for ZNF750. PCA demonstrated partial separation between tumor and normal samples. ZNF703 expression was positively associated with body mass index ({beta} = 0.194, p = 0.025), and ZNF750 expression was higher in estrogen receptor-positive tumors ({beta} = 1.050, p = 0.005). ConclusionZNF217, ZNF703, and ZNF750 display distinct mutation and expression profiles in breast cancer, with evidence of cohort-specific variation. These findings highlight gene-specific mechanisms of dysregulation and emphasize the value of integrating genomic and transcriptomic analyses.

cancer biology↗