Molecular Characterization of Indigenous Rhizobia from Kenyan Soils Nodulating with Common Beans.

Kenya is the seventh most prominent producer of common beans globally and the second leading producer in East Africa. However, the annual national productivity is low due to insufficient quantities of vital nutrients and nitrogen in the soils. Rhizobia are symbiotic bacteria that fix nitrogen through their interaction with leguminous plants. Nevertheless, inoculating beans with commercial rhizobia inoculants results in sparse nodulation and low nitrogen supply to the host plants because these strains are poorly adapted to the local soils. Several studies describe native rhizobia with much better symbiotic capabilities than commercial strains, but only a few have conducted field studies. This study aimed to test the competence of new rhizobia strains that we isolated from Western Kenya soils and for which the symbiotic efficiency was successfully determined in greenhouse experiments. Furthermore, we present and analyze the whole-genome sequence for a promising candidate for agricultural application, which has high nitrogen fixation features and promotes common bean yields in field studies. Plants inoculated with the rhizobial isolate S3 or with a consortium of local isolates (COMB), including S3, produced a significantly higher number of seeds and seed dry weight when compared to uninoculated control plants at two study sites. The performance of plants inoculated with commercial isolate CIAT899 was not significantly different from uninoculated plants (p > 0.05), indicating tight competition from native rhizobia for nodule occupancy. Pangenome analysis and the overall genome-related indices showed that S3 is a member of R. phaseoli. However, synteny analysis revealed significant differences in the gene order, orientation, and copy numbers between S3 and the reference R. phaseoli. Isolate S3 is phylogenomically similar to R. phaseoli. However, it has undergone significant genome rearrangements (global mutagenesis) to adapt to harsh conditions in Kenyan soils. Its high nitrogen fixation ability shows optimal adaptation to Kenyan soils, and the strain can potentially replace nitrogenous fertilizer application. We recommend that extensive fieldwork in other parts of the country over a period of five years be performed on S3 to check on how the yield changes with varying whether conditions.

Mutational signatures for breast cancer diagnosis using artificial intelligence.

BACKGROUND: Breast cancer is the most common female cancer worldwide. Its diagnosis and prognosis remain scanty, imprecise, and poorly documented. Previous studies have indicated that some genetic mutational signatures are suspected to lead to progression of various breast cancer scenarios. There is paucity of data on the role of AI tools in delineating breast cancer mutational signatures. This study sought to investigate the relationship between breast cancer genetic mutational profiles using artificial intelligence models with a view to developing an accurate prognostic prediction based on breast cancer genetic signatures. Prior research on breast cancer has been based on symptoms, origin, and tumor size. It has not been investigated whether diagnosis of breast cancer can be made utilizing AI platforms like Cytoscape, Phenolyzer, and Geneshot with potential for better prognostic power. This is the first ever attempt for a combinatorial approach to breast cancer diagnosis using different AI platforms. METHOD: Artificial intelligence (AI) are mathematical algorithms that simulate human cognitive abilities and solve difficult healthcare issues such as complicated biological abnormalities like those experienced in breast cancer scenarios. The current models aimed to predict outcomes and prognosis by correlating imaging phenotypes with genetic mutations, tumor profiles, and hormone receptor status and development of imaging biomarkers that combine tumor and patient-specific features. Geneshotsav 2021, Cytoscape 3.9.1, and Phenolyzer Nature Methods, 12:841-843 (2015) tools, were used to mine breast cancer-associated mutational signatures and provided useful alternative computational tools for discerning pathways and enriched networks of genes of similarity with the overall goal of providing a systematic view of the variety of mutational processes that lead to breast cancer development. The development of novel-tailored pharmaceuticals, as well as the distribution of prospective treatment alternatives, would be aided by the collection of massive datasets and the use of such tools as diagnostic markers. RESULTS: Specific DNA-maintenance defects, endogenous or environmental exposures, and cancer genomic signatures are connected. The PubMed database (Geneshot) search for the keywords yielded a total of 21,921 genes associated with breast cancer. Then, based on their propensity to result in gene mutations, the genes were screened using the Phenolyzer software. These platforms lend credence to the fact that breast cancer diagnosis using Cytoscape 3.9.1, Phenolyzer, and Geneshot 2021 reveals high profile of the following mutational signatures: BRCA1, BRCA2, TP53, CHEK2, PTEN, CDH1, BRIP1, RAD51C, CASP3, CREBBP, and SMAD3.

Whole Transcriptome Analysis of Differentially Expressed Genes in Cultured Nile Tilapia (O. niloticus) Subjected to Chronic Stress Reveals Signaling Pathways Associated with Depressed Growth.

Chronic stress is a serious threat to aquaculture as it lowers fish growth performance and compromises fish welfare. The exact mechanism by which growth is retarded is, however, not clearly understood. This study sought to elucidate the gene expression profiles associated with chronic stress in cultured Nile tilapia (Oreochromis niloticus) reared for 70 days at different ammonia concentrations and stocking densities. Fish in the treatment groups showed negative growth, while the controls showed positive allometric growth. The specific condition factor (Kn) ranged from 1.17 for the controls to 0.93 for the ammonia and 0.91 for the stocking density treatments. RNA was extracted from muscle tissue using TRIzol followed by library construction and Illumina sequencing. Comparative transcriptome analysis revealed 209 differentially expressed genes (DEGs) (156 up- and 53 down-regulated) in the ammonia and 252 DEGs (175 up- and 77 down-regulated) in the stocking density treatment. In both treatments, 24 and 17 common DEGs were up- and down-regulated, respectively. DEGs were significantly enriched in six pathways associated with muscle activity, energy mobilization and immunity. The heightened muscular activity consumes energy which would otherwise have been utilized for growth. These results bring to fore the molecular mechanisms underlying chronic stress' suppression of growth in cultured Nile tilapia.

In-silico analysis of potent Mosquirix vaccine adjuvant leads.

BACKGROUND: World Health Organization recommend the use of malaria vaccine, Mosquirix, as a malaria prevention strategy. However, Mosquirix has failed to reduce the global burden of malaria because of its inefficacy. The Mosquirix vaccine's modest effectiveness against malaria, 36% among kids aged 5 to 17 months who need at least four doses, fails to aid malaria eradication. Therefore, highly effective and efficacious malaria vaccines are required. The well-characterized P. falciparum circumsporozoite surface protein can be used to discover adjuvants that can increase the efficacy of Mosquirix. Therefore, the study sought to undertake an in-silico discovery of Plasmodium falciparum circumsporozoite surface protein inhibitors with pharmacological properties on Mosquirix using hierarchical virtual screening and molecular dynamics simulation. RESULTS: Monoclonal antibody L9, an anti-Plasmodium falciparum circumsporozoite surface protein molecule, was used to identify Plasmodium falciparum circumsporozoite surface protein inhibitors with pharmacological properties on Mosquirix during a virtual screening process in ZINCPHARMER that yielded 23 hits. After drug-likeness and absorption, distribution, metabolism, excretion, and toxicity property analysis in the SwissADME web server, only 9 of the 23 hits satisfied the requirements. The 9 compounds were docked with Plasmodium falciparum circumsporozoite surface protein using the PyRx software to understand their interactions. ZINC25374360 (-8.1 kcal/mol), ZINC40144754 (-8.3 kcal/mol), and ZINC71996727 (-8.9 kcal/mol) bound strongly to Plasmodium falciparum circumsporozoite surface protein with binding affinities of less than -8.0 kcal/mol. The stability of these molecularly docked Plasmodium falciparum circumsporozoite surface protein-inhibitor complexes were assessed through molecular dynamics simulation using GROMACS 2022. ZINC25374360 and ZINC71996727 formed stable complexes with Plasmodium falciparum circumsporozoite surface protein. They were subjected to in vitro validation for their inhibitory potential. The IC50 values ranging between 250 and 350 ng/ml suggest inhibition of parasite development. CONCLUSION: Therefore, the two Plasmodium falciparum circumsporozoite surface protein inhibitors can be used as vaccine adjuvants to increase the efficacy of the existing Mosquirix vaccine. Nevertheless, additional in vivo tests, structural optimization studies, and homogenization analysis are essential to determine the anti-plasmodial action of these adjuvants in humans.

Shotgun Metagenomic Analyses of Microbial Assemblages in the Aquatic Ecosystem of Winam Gulf of Lake Victoria, Kenya Reveals Multiclass Pollution.

Lake Victoria, the second-largest freshwater lake in the world, provides an important source of food and income, particularly fish for both domestic consumption and for export market. In recent years, Lake Victoria has suffered massive pollution from both industrial and wastewater discharge. Microplastic biomes, pharmaceutical residues, drugs of abuse, heavy metals, agrochemicals, and personal care products are ubiquitous in the aquatic ecosystem of Winam Gulf. These pollutants are known to alter microbial assemblages in aquatic ecosystems with far-reaching ramification including a calamitous consequence to human health. Indeed, some of these pollutants have been associated with human cancers and antimicrobial resistance. There is a paucity of data on the microbial profiles of this important but heavily polluted aquatic ecosystem. The current study sought to investigate the metagenomic profiles of microbial assemblages in the Winam Gulf ecosystem. Water and sediment samples were collected from several locations within the study sites. Total genomic DNA pooled from all sampling sites was extracted and analyzed by whole-genome shotgun sequencing. Analyses revealed three major kingdoms: bacteria, archaea and eukaryotes belonging to 3 phyla, 13 classes, 14 families, 9 orders, 14 genera, and 10 species. Proteobacteria, Betaproteobacteria, Comamonadaceae, Burkholdariales, and Arcobacter were the dominated phyla, class, family, order, genera, and species, respectively. The Kyoto Encyclopedia of Genes and Genomes indicated the highest number of genes involved in metabolism. The presence of carbohydrate metabolism genes and enzymes was used to infer organic pollutions from sewage and agricultural runoffs. Similarly, the presence of xylene and nutrotoluene degradation genes and enzyme was used to infer industrial pollution into the lake. Drug metabolism genes lend credence to the possibility of pharmaceutical pollutants in water. Taken together, there is a clear indication of massive pollution. In addition, carbohydrate-active enzymes were the most abundant and included genes in glycoside hydrolases. Shotgun metagenomic analyses conveyed an understanding of the microbial communities of the massively polluted aquatic ecosystem of Winam Gulf, Lake Vicoria, Kenya. The current study documents the presence of multiclass pollutants in Lake Victoria and reveals information that might be useful for a potential bioremediation strategy using the native microbial communities.

Impact of Malaria Diagnostic Technologies on the Disease Burden in the Sub-Saharan Africa.

Worldwide, transmission of emerging and reemerging malaria infections poses a significant threat to human health in the Sub-Saharan Africa, one that can quickly overwhelm public health resources. While the disease burden of malaria in the Sub-Saharan Africa appears to be on a gradual decline, it is characterized by spatial and temporal variability occasioning a sorry state for the Global South Countries. New evidence on long-term complications of malaria heightens our awareness of its public health impact. Given the likelihood of misdiagnosis, and the unknown levels of malaria transmission across different landscapes, many missed opportunities for prevention occur. Africa's population growth, unplanned urbanization, habitat destruction, and trans-border travel are contributing to a rise in the calamitous epidemiology of malaria. Despite empirical statistics demonstrating a downward trend in the malaria disease burden attributable to the scale-up of multiple control strategies, including new diagnostic technologies, malaria remains a global threat to human health in Sub-Sahara Africa. Malaria is a severe public health threat globally, despite several advancements and innovations in its control. Six species of the genus Plasmodium including Plasmodium malariae, Plasmodium falciparum, Plasmodium cynomolgi, Plasmodium knowlesi, Plasmodium ovale, and Plasmodium vivax are known to infect humans. However, greatest disease burden and fatalities are caused by Plasmodium falciparum. Globally, about 3 billion individuals are at risk of contracting malaria disease every year, with over 400,000 fatalities reported in the Sub-Saharan Africa. World Health Organization (WHO) 2018 malaria report indicated that approximately 405,000 mortalities and 228 million cases were reported worldwide, with Africa carrying the highest disease burden. Over the last decade, there has been a significant decline in malaria deaths and infections, which may be related to the availability of effective diagnostic techniques. However, in certain areas, the rate of decline has slowed or even reversed the gains made so far. Accurate diagnosis, adequate treatment, and management of the disease are critical WHO-set goals of eliminating malaria by 2030. Microscopy, rapid diagnostic tests (RDTs), nucleic acid amplification tests (NAATs), and biosensors are all currently accessible diagnostic methods. These technologies have substantial flaws and triumphs that could stymie or accelerate malaria eradication efforts. The cost, ease, accessibility, and availability of skilled persons all influence the use of these technologies. These variables have a direct and indirect ramification on the entire management portfolio of patients. Despite the overall decline in the malaria disease burden driven partly by new diagnostic technologies, a sobering pattern marked by limited number of studies and spatial as well as temporal heterogeneity remains a concern. This review summarizes the principle, performance, gaps, accomplishments, and applicability of numerous malaria diagnostic techniques and their potential role in reducing the malaria disease burden in Sub-Saharan Africa.

Scope of SARS-CoV-2 variants, mutations, and vaccine technologies.

Background: The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 is disseminated by respiratory aerosols. The virus uses the spike protein to target epithelial cells by binding to the ACE2 receptor on the host cells. As a result, effective vaccines must target the viral spike glycoprotein. However, the appearance of an Omicron variant with 32 mutations in its spike protein raises questions about the vaccine's efficacy. Vaccines are critical in boosting immunity, lowering COVID-19-related illnesses, reducing the infectious burden on the healthcare system, and reducing economic loss, according to current data. An efficient vaccination campaign is projected to increase innate and adaptive immune responses, offering better protection against SARS-CoV-2 variants. Main body: The presence of altered SARS-CoV-2 variants circulating around the world puts the effectiveness of vaccines already on the market at risk. The problem is made even worse by the Omicron variant, which has 32 mutations in its spike protein. Experts are currently examining the potential consequences of commercial vaccines on variants. However, there are worries about the vaccines' safety, the protection they provide, and whether future structural changes are required for these vaccines to be more effective. As a result of these concerns, new vaccines based on modern technology should be developed to guard against the growing SARS-CoV-2 variations. Conclusion: The choice of a particular vaccine is influenced by several factors including mode of action, storage conditions, group of the vaccinee, immune response mounted, cost, dosage protocol, age, and side effects. Currently, seven SARS-CoV-2 vaccine platforms have been developed. This comprises of inactivated viruses, messenger RNA (mRNA), DNA vaccines, protein subunits, nonreplicating and replicating vector viral-like particles (VLP), and live attenuated vaccines. This review focuses on the SARS-CoV-2 mutations, variants of concern (VOCs), and advances in vaccine technologies.

SARS-CoV-2 origin, myths and diagnostic technology developments.

Background: After the first case of COVID-19 being announced in China in December 2019, various diagnostic technologies have been developed at unprecedented pace with the aim of providing a basis for accurate clinical intervention. However, some assays including CRISPR-based diagnostics and loop-mediated isothermal amplification (LAMP) have been less explored. As new COVID-19 technologies emerge, there is need for them to be assessed, validated and improved upon. Moreover, there is paucity of data on the essential factors governing the selection of an appropriate diagnostic approach within the correct timeframe. Myths and origin of SARS-CoV-2 remain to be controversial. Consequently, this review aims at exploring the current COVID-19 diagnostic technologies, performance evaluation, principles, suitability, specificity, sensitivity, successes and challenges of the technologies for laboratory and bedside testing. Main Body: To date, there exist more publications on COVID-19 diagnostics as compared to the Zika virus. The SARS-CoV-2 virus genome profiles were readily available by 31st of December 2019. This was attributed to the fast-paced sharing of the epidemiological and diagnostics data of COVID-19. Timely profiling of the virus genome accelerated the development of diagnostic technologies. Furthermore, the rapid publication of studies that evaluated several diagnostic methods available provided baseline information on how the various technologies work and paved way for development of novel technologies. Conclusion: Up to date, RT-PCR is the most preferred as compared to the other assays. This is despite the repeated false negatives reported in many of the study findings. Considering that COVID-19 has caused devastating effects on the economy, healthcare systems, agriculture and culture, timely and accurate detection of the virus is paramount in the provision of targeted therapy hence reducing chances of drug resistance, increased treatment costs and morbidity. However, information on the origin of SARS-CoV-2 still remains elusive. Furthermore, knowledge and perception of the patients toward management of SARS-CoV-2 are also paramount to proper diagnosis and management of the pandemic. Future implications of the misperceptions are that they may lead to increased non-compliance to SARS-CoV-2-related World Health Organization (WHO) policies and guidelines.

Red cell distribution width as a surrogate marker of haemoglobinopathies in western Kenya.

Background: Haemoglobinopathies are inherited haemoglobin disorders that result in anaemia characterised by erythrocyte anisopoikilocytosis. Red cell distribution width (RDW) measures anisopoikiloytosis and is readily reported by haematology analysers as a complete blood count parameter. The utility of RDW as a diagnostic marker of haemoglobinopathies in Kenya remains undetermined and undocumented. Objective: This study aimed to determine the diagnostic efficacy of RDW in discriminating haemoglobinopathy and haemoglobinopathy-free cases in Kenya. Methods: The case-control study used randomly selected haematology analyser outputs for haemoglobinopathy-free (241, 49.4%) and haemoglobinopathy cases (247, 50.1%) aged 1 month to 66 years old tested in the Aga Khan Hospital, Kisumu, and its satellite centres in western Kenya from 01 January 2015 to 31 December 2020. Results were verified using high performance liquid chromatography. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic power of RDW as a biomarker for sickle cell disease (SCD) and sickle cell trait phenotypes and ß-thalassaemia. Results: The RDW showed diagnostic significance in SCD phenotypes at 21.1 ROC curve coordinate with 67.7% sensitivity, 90.0% specificity, 0.789 accuracy, 70.5% positive predictive validity, 88.8% negative predictive validity, 6.77 positive likelihood ratio, 0.36 negative likelihood ratio and 18.94 (11.4-31.4) odds ratio. Conclusion: An RDW of 21.1% is potentially a predictor of SCD haemoglobin phenotypes and should be included in the haematology screening algorithm as a critical value, above which suspected cases qualify to be investigated for SCD.

In Silico Identification of New Anti-SARS-CoV-2 Main Protease (Mpro) Molecules with Pharmacokinetic Properties from Natural Sources Using Molecular Dynamics (MD) Simulations and Hierarchical Virtual Screening.

Infectious agents such as SARS-CoV, MERS-CoV, and SARS-CoV-2 have emerged in recent years causing epidemics with high mortality rates. The quick development of novel therapeutic compounds is required in the fight against such pathogenic agents. Unfortunately, the traditional drug development methods are time-consuming and expensive. In this study, computational algorithms were utilized for virtual screening of a library of natural compounds in the ZINC database for their affinity towards SARS-CoV-2 Mpro. Compounds such as cinanserin, nelfinavir, baicalin, baicalein, candesartan cilexetil, chloroquine, dipyridamole, and hydroxychloroquine have the ability to prevent SARS-CoV-2 Mpro from facilitating COVID 19 infection; thus, they treat COVID 19. However, these drugs majorly act to reduce the symptoms of the disease. No anti-viral drug against COVID 19 virus infection has been discovered and approved. Therefore, this study sought to explore natural inhibitors of SARS-CoV-2 Mpro to develop a pharmacophore model for virtual screening of natural compounds in the ZINC database as potential candidates for SARS-CoV-2 Mpro inhibitors and as therapeutic molecules against COVID 19. This study undertook in silico methods to identify the best anti-viral candidates targeting SAR-CoV-2 Mpro from natural sources in the ZINC database. Initially, reported anti-SARS-CoV-2 Mpro molecules were integrated into designing a pharmacophore model utilizing PharmaGist. Later, the pharmacophore model was loaded into ZINCPHARMER and screened against the ZINC database to identify new probable drug candidates. The root means square deviation (RMSD) values of the potential drug candidates informed the selection of some of them, which were docked with SARS-CoV-2 Mpro to comprehend their interactions. From the molecular docking results, the top four candidates (ZINC000254823011, ZINC000072307130, ZINC000013627512, and ZINC000009418994) against SARS-CoV-2 Mpro, with binding energies ranging from -8.2 kcal/mol to -8.6 kcal/mol, were examined for their oral bioavailability and other pharmacokinetic properties. Consequently, ZINC000072307130 emerged as the only orally bioavailable drug candidate with desirable pharmacokinetic properties. This candidate drug was used to perform MD simulations, and the outcomes revealed that ZINC000072307130 formed a stable complex with the viral main protease. Consequently, ZINC000072307130 emerges as a potential anti-SARS-CoV-2 Mpro inhibitor for the production of new COVID 19 drugs.

Rhizobia Contribute to Salinity Tolerance in Common Beans (Phaseolus vulgaris L.).

Rhizobia are soil bacteria that induce nodule formation on leguminous plants. In the nodules, they reduce dinitrogen to ammonium that can be utilized by plants. Besides nitrogen fixation, rhizobia have other symbiotic functions in plants including phosphorus and iron mobilization and protection of the plants against various abiotic stresses including salinity. Worldwide, about 20% of cultivable and 33% of irrigation land is saline, and it is estimated that around 50% of the arable land will be saline by 2050. Salinity inhibits plant growth and development, results in senescence, and ultimately plant death. The purpose of this study was to investigate how rhizobia, isolated from Kenyan soils, relieve common beans from salinity stress. The yield loss of common bean plants, which were either not inoculated or inoculated with the commercial R. tropici rhizobia CIAT899 was reduced by 73% when the plants were exposed to 300 mM NaCl, while only 60% yield loss was observed after inoculation with a novel indigenous isolate from Kenyan soil, named S3. Expression profiles showed that genes involved in the transport of mineral ions (such as K+, Ca2+, Fe3+, PO43-, and NO3-) to the host plant, and for the synthesis and transport of osmotolerance molecules (soluble carbohydrates, amino acids, and nucleotides) are highly expressed in S3 bacteroids during salt stress than in the controls. Furthermore, genes for the synthesis and transport of glutathione and γ-aminobutyric acid were upregulated in salt-stressed and S3-inocculated common bean plants. We conclude that microbial osmolytes, mineral ions, and antioxidant molecules from rhizobia enhance salt tolerance in common beans.

The Burden of Cystic Echinococcosis in Kenya: A Review Article.

BACKGROUND: Cystic echinococcosis (CE), caused by the larval stage of Echinococcus granulosus sensu lato (s.l), is a zoonotic parasitic disease with a worldwide distribution. Kenya is one of the high endemic countries of CE with the endemic areas in the country being under immense occupation of traditional pastoralists. Turkana area in Kenya, has in the past recorded the highest prevalence of CE in the world. METHODS: The keywords cystic echinococcosis; Prevalence; Diagnosis; Risk-factors; Kenya were searched on google scholar and PubMed and the important literature materials retrieved for further analysis. RESULTS: The most notable infection risk factor for this disease in the country is the close association between man, dogs, and livestock. Successful control of CE in Kenya requires application of innovative interventions achieved after the review of the disease situation in the country. With the emergence and advent of new diagnostic techniques, CE organ-specific infections and transmission pattern in Kenya differ from what is commonly reported in literature. CONCLUSION: A better understanding of CE prevalence of different hosts, its transmission pattern and the pathogenicity might make it possible to set up more effective control programs in future.