Biology subjects

Sinkala, M.

Publications and source records attributed to Sinkala, M..

9 recordsLinked to original sources

bioRxiv2025

Antibiotic Use and Resistance in Zambia's Aquaculture Sector: Assessing Knowledge, Attitudes, and Practices Among Fish Farmers

Aquaculture in Zambia is rapidly growing, contributing significantly to food security and income generation. However, the intensification of fish farming raises concerns about antimicrobial use (AMU) and the emergence of antimicrobial resistance (AMR). This study assessed the knowledge, attitudes, and practices (KAP) of fish farmers regarding AMU and AMR across 25 districts in Zambias ten provinces. Data were collected from fish farmers using a structured questionnaire distributed via district fisheries officers and analyzed through descriptive and inferential statistics, including logistic regression. The results revealed significant gaps in knowledge, with only 17.4% of farmers classified as knowledgeable about AMU and AMR. Attitude assessments showed that 60.5% exhibited positive attitudes toward responsible AMU practices, while the remaining 39.5% displayed negative perceptions. In terms of practices, 76.5% adhered to good practices, including consulting veterinary professionals and responsible antibiotic use, whereas 23.5% engaged in poor practices. Key factors influencing KAP outcomes included age, farming experience, and annual production capacity. Farmers aged 30-39 years and those with 1-5 years of experience demonstrated significantly more positive attitudes (p < 0.05), while those with higher production capacities (501-1000 kg) exhibited better practices (p < 0.001). The findings highlight critical knowledge gaps and inconsistent practices regarding AMU and AMR among Zambian fish farmers. Targeted interventions, including education programs, enhanced access to veterinary services, and strengthened regulatory frameworks, are essential to promote responsible AMU, mitigate AMR risks, and ensure the sustainability of aquaculture in Zambia.

scientific communication and education↗

bioRxiv2024

Unveiling the role of Tdark genes in genetic diseases and phenotypes through bioinformatics-based functional enrichment and network analyses

In recent years, there has been growing interest in understanding the role of dark genes in genetic diseases and phenotypes. Despite their lack of functional characterisation, dark genes account for a significant portion of the human genome and are believed to play a role in regulating gene expression and cellular processes. We investigated the role of dark genes in genetic diseases and phenotypes by conducting integrative network analyses and functional enrichment studies across multiple large-scale molecular datasets. Our investigation revealed a predominant association of both dark and light genes with psoriasis. Furthermore, we found that the transcription factors UBTF and NFE2L2 are potential regulators of both dark and light genes associated with tuberculosis. In contrast, the transcription factors SUZ12 and TP63 are potential regulators of both dark and light genes associated with interstitial cystitis. Further network analysis of dark genes, including CALHM6, HCP5, PRRG4, DDX60L and RASA2, revealed a notably high weighted degree of association with genetic diseases and phenotypes. Moreover, our analysis revealed that numerous genetic diseases and phenotypes, including psoriasis, pick disease, tuberculosis, ulcerative colitis, interstitial cystitis, and Crohns disease, exhibited shared gene linkages. Additionally, we conducted a protein-protein interaction analysis to reveal 16 dark genes that encode hub proteins, including R3HDM2, RPUSD4, FASTKD5, and MRPL15, that could play a role in many genetic diseases and phenotypes, and are widely expressed across body tissues. Our findings contribute to the understanding of the genetic basis of diseases and provide potential therapeutic targets for future research. Identifying dysregulated dark genes in disease states can lead to new strategies for prevention, diagnosis, and treatment, thus advancing our understanding of disease mechanisms.

bioinformatics↗

bioRxiv2023

Racial Disparities in the Genetic Landscape of Acute Myeloid Leukaemia from The Cancer Genome Atlas: Insights from a Bioinformatics Analysis

Acute myeloid leukaemia (AML) is a heterogeneous disease with complex pathogenesis that affects hematopoietic stem cells. Ethnic and racial disparities have been reported to affect treatment and survival outcomes in AML patients. Here, we analysed clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) to investigate potential differences in the genetic landscape of AML between African and European individuals. We found several differentially expressed mRNA transcripts between the AML of Africans and Europeans. Notably, AML in African patients exhibited enrichment for several pathways, including signalling by G-protein-coupled receptors, oncostatin M, and codeine and morphine metabolism. In contrast, AML in European patients showed enrichment for pathways related to the glial cell-line derived neurotrophic factor/rearranged during transfection signalling axis, gamma-aminobutyric acid receptor activation, and ligand-gated ion transport channels. Additionally, kinase enrichment analysis identified shared and distinct kinases in AML among Africans and Europeans: Africans showed an enrichment of cyclin-dependent kinases, while Europeans exhibited an enrichment of ULK2, CSNK2B, and CAMK1. Our study highlights the potential importance of considering race when evaluating the genetic landscape of AML, which may improve treatment strategies for this disease.

bioinformatics↗

bioRxiv2023

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Investigating the human genome is vital for identifying risk factors and devising effective therapies to combat genetic disorders and cancer. Despite the extensive knowledge of the "light genome", the poorly understood "dark genome" remains understudied. In this study, we integrated data from 20,412 protein-coding genes in Pharos and 8,395 patient-derived tumours from The Cancer Genome Atlas (TCGA) to examine the genetic and pharmacological dependencies in human cancers and their treatment implications. We discovered that dark genes exhibited high mutation rates in certain cancers, similar to light genes. By combining the drug response profiles of cancer cells with cell fitness post-CRISPR-mediated gene knockout, we identified the crucial vulnerabilities associated with both dark and light genes. Our analysis also revealed that tumours harbouring dark gene mutations displayed worse overall and disease-free survival rates than those without such mutations. Furthermore, dark gene expression levels significantly influenced patient survival outcomes. Our findings demonstrated a similar distribution of genetic and pharmacological dependencies across the light and dark genomes, suggesting that targeting the dark genome holds promise for cancer treatment. This study underscores the need for ongoing research on the dark genome to better comprehend the underlying mechanisms of cancer and develop more effective therapies.

bioinformatics↗

bioRxiv2022

Mutational Landscape of Cancer-Driver Genes Across Human Cancers

The cancer driver genes are involved in transforming healthy cells into cancerous cells. The molecular aberrations which lead to cancer involve gain and loss of function mutations in various cancer driver genes. Here, we examine the genome sequences of 20,066 primary tumours representing 43 distinct human cancers to identify and catalogue driver mutations in 729 known cancer genes. We show that the frequency of driver mutations in these genes varies significantly between cancer types. We find that the class of cancer driver genes most frequently mutated are the tumour suppressor genes (94%), followed by oncogenes (93%), transcription factors (72%), kinases (64%), cell surface receptors (63%), and phosphatases (22%). Furthermore, we identify the subset of these genes within which mutations exhibit a co-occurrence or mutually exclusive pattern. Interestingly, we find that patients with tumours with different combinations of driver gene mutation patterns tend to exhibit variable survival outcomes. Here, among the well-studied cancer genes, we showed that patients with tumours with KRAS and TP53 mutations are associated with the worst disease outcomes, and those with PI3KCA and BRAF mutations are associated with favourable survival outcomes. Besides providing new insights into cancer driver mutations, we unearth mutation patterns associated with disease outcomes and various hallmarks of cancer that bring us closer to fully understanding various forms of cancer.

bioinformatics↗

bioRxiv2022

A Bioinformatics Analysis Reveals that the Transcription Levels of Cell Surface Receptor Encoding Genes are Associated with the Drug Response of Breast Cancer Cells and the Drug Off-Target Effects

Breast cancer is characterised by varied responses to different anticancer therapies, which may provoke several different off-target effects. We hypothesise that for drugs that target cell surface receptors (CSRs), the different responses of tumours and the adverse events produced by these drugs may be attributed to variations in the transcriptional landscapes of CSRs in both breast tumours and healthy tissues. Here, we use data from various sources to compare the CSR transcriptional landscapes of breast tumours and a range of different non-diseased human tissues. We demonstrate an association between the responses to drug perturbation of breast cancer cell lines and the transcription levels of their targeted CSRs. Furthermore, we reveal important differences in the CSR transcriptional landscapes of primary breast tumour subtypes and the CSR transcriptional landscapes of breast cancer cell lines, which will likely impact the accuracy of drug response predictions. Finally, applying clinical trial data, we expose a link between the expression levels of CSR genes in healthy tissues and adverse reactions of patients to anticancer drugs. Altogether, this approach allows for the isolation of the most suitable CSR target(s) among the expressed transcripts, solely based on the measured dose-responses of cell lines to small molecules, the CSR transcriptional landscape in health patient tissues, and reported adverse responses of patients to drugs targeting CSRs.

bioinformatics↗

bioRxiv2020

Proteogenomic Analysis of Pancreatic Cancer Subtypes

Pancreatic cancer remains a significant public health problem with an ever-rising incidence of disease. Cancers of the pancreas are characterised by various molecular aberrations, including changes in the proteomics and genomics landscape of the tumour cells. There is a need, therefore, to identify the proteomic landscape of pancreatic cancer and the specific genomic and molecular alterations associated with disease subtypes. Here, we carry out an integrative bioinformatics analysis of The Cancer Genome Atlas dataset that includes proteomics and whole-exome sequencing data collected from pancreatic cancer patients. We apply unsupervised clustering on the proteomics dataset to reveal the two distinct subtypes of pancreatic cancer. Using functional and pathway analysis, we demonstrate the different molecular processes and signalling aberrations of the pancreatic cancer subtypes. We explore the clinical characteristic of these subtypes to show differences in disease outcome. Using datasets of mutations and copy number alterations, we show that various signalling pathways are altered among pancreatic tumours, including the Wnt pathway, Notch pathway and PI3K-mTOR pathways. Altogether, we reveal the proteogenomic landscape of pancreatic cancer subtypes and the altered molecular processes which can be leveraged to devise more effective treatments.

bioinformatics↗

bioRxiv2020

EFFECTS OF BLOOD SUGAR LEVELS, KIDNEY DISEASE AND MEDICATION ON ANAEMIA STATUS OF TYPE 2 DIABETES MELLITUS PATIENTS

IntroductionLifestyle-related diseases like type 2 diabetes mellitus, have emerged as a significant public health problem due to rapid urbanization and industrialization. In 2018, the prevalence of type 2 diabetes mellitus was estimated to be 500 million cases worldwide and was comparable between high- and low-income countries. Diabetes leads to multiple complications, including end-stage renal disease, cardiovascular disease, infection, and death. Anaemia in diabetic individuals has severe adverse effects on the quality of life and is associated with disease progression. A cross-sectional study was conducted that included 101 participants. The study aimed to determine the prevalence of anaemia and kidney disease and their interplay with medication and/or blood glucose levels in T2D patients. Resultsseventy-one per cent of participants were females. Majority of patients 62% were on Insulin, 30% on metformin, 7% on a combination of metformin and glimepiride and 1% on glimepiride. Ninety-five (94%) of the participants were HIV negative. The prevalence of anaemia among the participants was 23% out of which 56% had moderate anaemia, and 44% had mild anaemia. Twenty-one per cent (21%) of the participants had high creatinine levels signifying impaired kidney function or kidney disease. Anaemia was significantly associated with kidney function, fasting blood glucose and use of metformin; p = 0.042 beta = 2.5, p = 0.025 beta = 2.7 and p = 0.040 beta = -2.5 respectively. ConclusionThe study found the prevalence of anaemia of 23%, which was of moderate public health concern. Also, the prevalence of kidney disease was high in patients with Type 2 Diabetes Mellitus. It also found that kidney disease and high blood glucose levels increase the chances of developing anaemia. However, we found that metformin had a protective role against the development of anaemia in Type 2 Diabetes Mellitus patients.

pathology↗

bioRxiv2020

Integrated Molecular Characterisation of the MAPK Pathways in Human Cancers

The mitogen-activated protein kinase (MAPK) pathways are a crucial regulator of the cellular processes that fuel the malignant transformation of normal cells. The genetic underpinnings of molecular aberrations which lead to cancer involve mutations in and, transcription variations of, various MAPK pathway genes. Here, we use datasets of 40,848 patient-derived tumours representing 101 distinct human cancers to identify cancer-associated mutations in MAPK signalling pathway genes. We identify the subset of these genes within which mutations tend to be associated with the worst disease outcomes. Furthermore, by integrating information extracted from various large-scale molecular datasets, we expose the relationship between the fitness of cancer cells after CRISPR mediated gene knockout of MAPK pathway genes, and their dose-responses to MAPK pathway inhibitors. Besides providing new insights into MAPK pathways, we unearth vulnerabilities in specific pathway genes that are reflected in the responses of cancer cells to MAPK drug perturbations: a revelation with great potential for guiding the development of innovative therapeutic strategies.

bioinformatics↗