Spatio-temporal characterization of phenotypic resistance in malaria vector species.

BACKGROUND: Malaria, a deadly disease caused by Plasmodium protozoa parasite and transmitted through bites of infected female Anopheles mosquitoes, remains a significant public health challenge in sub-Saharan Africa. Efforts to eliminate malaria have increasingly focused on vector control using insecticides. However, the emergence of insecticide resistance (IR) in malaria vectors pose a formidable obstacle, and the current IR mapping models remain static, relying on fixed coefficients. This study introduces a dynamic spatio-temporal approach to characterize phenotypic resistance in Anopheles gambiae complex and Anopheles arabiensis. We developed a cellular automata (CA) model and applied it to data collected from Ethiopia, Nigeria, Cameroon, Chad, and Burkina Faso. The data encompasses georeferenced records detailing IR levels in mosquito vector populations across various classes of insecticides. In characterizing the dynamic patterns of confirmed resistance, we identified key driving factors through correlation analysis, chi-square tests, and extensive literature review. RESULTS: The CA model demonstrated robustness in capturing the spatio-temporal dynamics of confirmed IR states in the vector populations. In our model, the key driving factors included insecticide usage, agricultural activities, human population density, Land Use and Land Cover (LULC) characteristics, and environmental variables. CONCLUSIONS: The CA model developed offers a robust tool for countries that have limited data on confirmed IR in malaria vectors. The embrace of a dynamical modeling approach and accounting for evolving conditions and influences, contribute to deeper understanding of IR dynamics, and can inform effective strategies for malaria vector control, and prevention in regions facing this critical health challenge.

Physiological and ecological warnings that dodders pose an exigent threat to farmlands in Eastern Africa.

Invasive holoparasitic plants of the genus Cuscuta (dodder) threaten African ecosystems due to their rapid spread and attack on various host plant species. Most Cuscuta species cannot photosynthesize and hence rely on host plants for nourishment. After attachment through a peg-like organ called a haustorium, the parasites deprive hosts of water and nutrients, which negatively affects host growth and development. Despite their rapid spread in Africa, dodders have attracted limited research attention, although data on their taxonomy, host range, and epidemiology are critical for their management. Here, we combine taxonomy and phylogenetics to reveal the presence of field dodder (Cuscuta campestris) and C. kilimanjari (both either naturalized or endemic to East Africa), in addition to the introduction of the giant dodder (C. reflexa), a south Asian species, in continental Africa. These parasites have a wide host range, parasitizing species across 13 angiosperm orders. We evaluated the possibility of C. reflexa to expand this host range to tea (Camelia sinensis), coffee (Coffea arabica), and mango (Mangifera indica), crops of economic importance to Africa, for which haustorial formation and vascular-bundle connections in all three crops revealed successful parasitism. However, only mango mounted a successful postattachment resistance response. Furthermore, species distribution models predicted high habitat suitability for Cuscuta spp. across major tea- and coffee-growing regions of Eastern Africa, suggesting an imminent risk to these crops. Our findings provide relevant insights into a poorly understood threat to biodiversity and economic wellbeing in Eastern Africa, and provide critical information to guide development of management strategies to avert Cuscuta spp. spread.

Using outbreak data to estimate the dynamic COVID-19 landscape in Eastern Africa.

BACKGROUND: The emergence of COVID-19 as a global pandemic presents a serious health threat to African countries and the livelihoods of its people. To mitigate the impact of this disease, intervention measures including self-isolation, schools and border closures were implemented to varying degrees of success. Moreover, there are a limited number of empirical studies on the effectiveness of non-pharmaceutical interventions (NPIs) to control COVID-19. In this study, we considered two models to inform policy decisions about pandemic planning and the implementation of NPIs based on case-death-recovery counts. METHODS: We applied an extended susceptible-infected-removed (eSIR) model, incorporating quarantine, antibody and vaccination compartments, to time series data in order to assess the transmission dynamics of COVID-19. Additionally, we adopted the susceptible-exposed-infectious-recovered (SEIR) model to investigate the robustness of the eSIR model based on case-death-recovery counts and the reproductive number (R0). The prediction accuracy was assessed using the root mean square error and mean absolute error. Moreover, parameter sensitivity analysis was performed by fixing initial parameters in the SEIR model and then estimating R0, ß and γ. RESULTS: We observed an exponential trend of the number of active cases of COVID-19 since March 02 2020, with the pandemic peak occurring around August 2021. The estimated mean R0 values ranged from 1.32 (95% CI, 1.17-1.49) in Rwanda to 8.52 (95% CI: 3.73-14.10) in Kenya. The predicted case counts by January 16/2022 in Burundi, Ethiopia, Kenya, Rwanda, South Sudan, Tanzania and Uganda were 115,505; 7,072,584; 18,248,566; 410,599; 386,020; 107,265, and 3,145,602 respectively. We show that the low apparent morbidity and mortality observed in EACs, is likely biased by underestimation of the infected and mortality cases. CONCLUSION: The current NPIs can delay the pandemic pea and effectively reduce further spread of COVID-19 and should therefore be strengthened. The observed reduction in R0 is consistent with the interventions implemented in EACs, in particular, lockdowns and roll-out of vaccination programmes. Future work should account for the negative impact of the interventions on the economy and food systems.

GWAS provides biological insights into mechanisms of the parasitic plant (Striga) resistance in sorghum.

BACKGROUND: Sorghum yields in sub-Saharan Africa (SSA) are greatly reduced by parasitic plants of the genus Striga (witchweed). Vast global sorghum genetic diversity collections, as well as the availability of modern sequencing technologies, can be potentially harnessed to effectively manage the parasite. RESULTS: We used laboratory assays - rhizotrons to screen a global sorghum diversity panel to identify new sources of resistance to Striga; determine mechanisms of resistance, and elucidate genetic loci underlying the resistance using genome-wide association studies (GWAS). New Striga resistant sorghum determined by the number, size and biomass of parasite attachments were identified. Resistance was by; i) mechanical barriers that blocked parasite entry, ii) elicitation of a hypersensitive reaction that interfered with parasite development, and iii) the inability of the parasite to develop vascular connections with hosts. Resistance genes underpinning the resistance corresponded with the resistance mechanisms and included pleiotropic drug resistance proteins that transport resistance molecules; xylanase inhibitors involved in cell wall fortification and hormonal regulators of resistance response, Ethylene Response Factors. CONCLUSIONS: Our findings are of fundamental importance to developing durable and broad-spectrum resistance against Striga and have far-reaching applications in many SSA countries where Striga threatens the livelihoods of millions of smallholder farmers that rely on sorghum as a food staple.

Metagenomic analysis of viruses associated with maize lethal necrosis in Kenya.

BACKGROUND: Maize lethal necrosis is caused by a synergistic co-infection of Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA. METHODS: We used next-generation sequencing to identify viruses associated to maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties. RESULTS: Complete and partial genomes were assembled for MCMV, SCMV, Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses (MCMV, SCMV, MSV and MYDV-RMV) were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for other four potyviruses and one polerovirus. CONCLUSION: Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different to isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved.

Metagenomic analysis demonstrates the diversity of the fecal virome in asymptomatic pigs in East Africa.

Pigs harbor a variety of viruses that are closely related to human viruses and are suspected to have zoonotic potential. Little is known about the presence of viruses in smallholder farms where pigs are in close contact with humans and wildlife. This study provides insight into viral communities and the prevalence and characteristics of enteric viral co-infections in smallholder pigs in East Africa. Sequence-independent amplification and high-throughput sequencing were applied to the metagenomics analysis of viruses in feces collected from asymptomatic pigs. A total of 47,213 de novo-assembled contigs were constructed and compared with sequences from the GenBank database. Blastx search results revealed that 1039 contigs (>200 nt) were related to viral sequences in the GenBank database. Of the 1039 contigs, 612 were not assigned to any viral taxa because they had little similarity to known viral genomic or protein sequences, while 427 contigs had a high level of sequence similarity to known viruses and were assigned to viral taxa. The most frequent contigs related to mammalian viruses resembling members of the viral genera Astrovirus, Rotavirus, Bocavirus, Circovirus, and Kobuvirus. Other less abundant contigs were related to members of the genera Sapelovirus, Pasivirus, Posavirus, Teschovirus and Picobirnavirus. This is the first report on the diversity of the fecal virome of pig populations in East Africa. The findings of the present study help to elucidate the etiology of diarrheal diseases in pigs and identify potential zoonotic and emerging viruses in the region. Further investigations are required to compare the incidence of these viruses in healthy and diseased pigs in order to better elucidate their pathogenic role.

Genetic diversity of Kenyan native oyster mushroom (Pleurotus).

Members of the genus Pleurotus, also commonly known as oyster mushroom, are well known for their socioeconomic and biotechnological potentials. Despite being one of the most important edible fungi, the scarce information about the genetic diversity of the species in natural populations has limited their sustainable utilization. A total of 71 isolates of Pleurotus species were collected from three natural populations: 25 isolates were obtained from Kakamega forest, 34 isolates from Arabuko Sokoke forest and 12 isolates from Mount Kenya forest. Amplified fragment length polymorphism (AFLP) was applied to thirteen isolates of locally grown Pleurotus species obtained from laboratory samples using five primer pair combinations. AFLP markers and internal transcribed spacer (ITS) sequences of the ribosomal DNA were used to estimate the genetic diversity and evaluate phylogenetic relationships, respectively, among and within populations. The five primer pair combinations generated 293 polymorphic loci across the 84 isolates. The mean genetic diversity among the populations was 0.25 with the population from Arabuko Sokoke having higher (0.27) diversity estimates compared to Mount Kenya population (0.24). Diversity between the isolates from the natural population (0.25) and commercial cultivars (0.24) did not differ significantly. However, diversity was greater within (89%; P > 0.001) populations than among populations. Homology search analysis against the GenBank database using 16 rDNA ITS sequences randomly selected from the two clades of AFLP dendrogram revealed three mushroom species: P. djamor, P. floridanus and P. sapidus; the three mushrooms form part of the diversity of Pleurotus species in Kenya. The broad diversity within the Kenyan Pleurotus species suggests the possibility of obtaining native strains suitable for commercial cultivation.

Insights and challenges of insecticide resistance modelling in malaria vectors: a review.

BACKGROUND: Malaria is one of the most devastating tropical diseases, resulting in loss of lives each year, especially in children under the age of 5 years. Malaria burden, related deaths and stall in the progress against malaria transmission is evident, particularly in countries that have moderate or high malaria transmission. Hence, mitigating malaria spread requires information on the distribution of vectors and the drivers of insecticide resistance (IR). However, owing to the impracticality in establishing the critical need for real-world information at every location, modelling provides an informed best guess for such information. Therefore, this review examines the various methodologies used to model spatial, temporal and spatio-temporal patterns of IR within populations of malaria vectors, incorporating pest-biology parameters, adopted ecological principles, and the associated modelling challenges. METHODS: The review focused on the period ending March 2023 without imposing restrictions on the initial year of publication, and included articles sourced from PubMed, Web of Science, and Scopus. It was also limited to publications that deal with modelling of IR distribution across spatial and temporal dimensions and excluded articles solely focusing on insecticide susceptibility tests or articles not published in English. After rigorous selection, 33 articles met the review's elibility criteria and were subjected to full-text screening. RESULTS: Results show the popularity of Bayesian geostatistical approaches, and logistic and static models, with limited adoption of dynamic modelling approaches for spatial and temporal IR modelling. Furthermore, our review identifies the availability of surveillance data and scarcity of comprehensive information on the potential drivers of IR as major impediments to developing holistic models of IR evolution. CONCLUSIONS: The review notes that incorporating pest-biology parameters, and ecological principles into IR models, in tandem with fundamental ecological concepts, potentially offers crucial insights into the evolution of IR. The results extend our knowledge of IR models that provide potentially accurate results, which can be translated into policy recommendations to combat the challenge of IR in malaria control.

A mathematical model for mapping the insecticide resistance trend in the Anopheles gambiae mosquito population under climate variability in Africa.

The control of arthropod disease vectors using chemical insecticides is vital in combating malaria, however the increasing insecticide resistance (IR) poses a challenge. Furthermore, climate variability affects mosquito population dynamics and subsequently IR propagation. We present a mathematical model to decipher the relationship between IR in Anopheles gambiae populations and climate variability. By adapting the susceptible-infected-resistant (SIR) framework and integrating temperature and rainfall data, our model examines the connection between mosquito dynamics, IR, and climate. Model validation using field data achieved 92% accuracy, and the sensitivity of model parameters on the transmission potential of IR was elucidated (e.g. µPRCC = 0.85958, p-value < 0.001). In this study, the integration of high-resolution covariates with the SIR model had a significant impact on the spatial and temporal variation of IR among mosquito populations across Africa. Importantly, we demonstrated a clear association between climatic variability and increased IR (width = [0-3.78], α = 0.05). Regions with high IR variability, such as western Africa, also had high malaria incidences thereby corroborating the World Health Organization Malaria Report 2021. More importantly, this study seeks to bolster global malaria combat strategies by highlighting potential IR 'hotspots' for targeted intervention by National malria control programmes.

WiPFIM: A digital platform for interlinking biocollections of wild plants, fruits, associated insects, and their molecular barcodes.

The current knowledge on insects feeding on fruits is limited, and some of the scarce existing data on the fruit-associated insects are secluded within the host institutions. Consequently, their value is not fully realized. Moreover, in countries like Kenya, the integration of biocollections data within a digital framework has not been fully exploited. To address these gaps, this article presents a description of the development of a web-based platform for data sharing and integrating biodiversity historical data of wild plants, fruits, associated insects, and their molecular barcodes (WiPFIM) while leveraging data science technologies. The barcodes corresponding to the biocollections data were retrieved from BOLD database. The platform is an online resource about fruit-insect interactions that can be of interest to a worldwide community of users and can be useful in building innovative tools. The platform is accessible online at https://test-dmmg.icipe.org/wpfhi.

Comparative transcriptome analysis of false codling moth, Thaumatotibia leucotreta in response to high and low-temperature treatments.

The false codling moth (FCM), Thaumatotibia leucotreta, is a major quarantine pest native to Africa. Physical postharvest phytosanitary measures such as cold and heat treatments are championed to control its spread to new regions. However, the molecular changes that T. leucotreta undergoes as it attempts to adjust to its surroundings during the treatments and withstand the extreme temperatures remain largely unknown. The current study employs RNA-seq using the next-generation Illumina HiSeq platform to produce transcriptome profiles for differential gene expression analysis of T. leucotreta larvae under thermal stress. The transcriptome assembly analysis revealed 226,067 transcripts, clustering into 127,018 unigenes. In comparison to the 25 °C treated group, 874, 91, 159, and 754 individual differentially expressed genes (DEGs) co-regulated at -10, 0, 40, and 50 °C, respectively were discovered. Annotation of the DEGs by gene ontology (GO) revealed several genes, previously implicated in low and high-temperature stresses, including heat shock proteins, cytochrome P450, cuticle proteins, odorant binding proteins, and immune system genes. Kyoto Encyclopedia of Genes and Genomics (KEGG) classification analysis revealed that substantive DEGs were those involved in metabolic pathways such as thiamine, purine, folate, and glycerolipid metabolism pathways. The RT-qPCR validation of several significantly up- and down-regulated DEGs showed congruence between RNA-seq and qPCR data. This baseline study lays a foundation for future research into the molecular mechanisms underlying T. leucotreta's cold/heat tolerance by providing a thorough differential gene expression analysis that has identified multiple genes that may be associated with the insect's ability to withstand cold and heat.

Development and Validation of Rapid Colorimetric Reverse Transcription Loop-Mediated Isothermal Amplification for Detection of Rift Valley Fever Virus.

Rift Valley fever virus (RVFV) is a high-priority zoonotic pathogen with the ability to cause massive loss during its outbreak within a very short period of time. Lack of a highly sensitive, instant reading diagnostic method for RVFV, which is more suitable for on-site testing, is a big gap that needs to be addressed. The aim of this study was to develop a novel one-step reverse transcription loop-mediated isothermal amplification (RT-LAMP) method for the rapid detection of RVFV. To achieve this, the selected RVFV M segment nucleotide sequences were aligned using Multiple Sequence Comparison by Log-Expectation (MUSCLE) software in MEGA11 version 11.0.11 program to identify conserved regions. A 211 pb sequence was identified and six different primers to amplify it were designed using NEB LAMP Primer design tool version 1.1.0. The specificity of the designed primers was tested using primer BLAST, and a primer set, specific to RVFV and able to form a loop, was selected. In this study, we developed a single-tube test based on calorimetric RT-LAMP that enabled the visual detection of RVFV within 30 minutes at 65°C. Diagnostic sensitivity and specificity of the newly developed kit were compared with RVFV qRT-PCR, using total RNA samples extracted from 118 blood samples. The colorimetric RT-LAMP assay had a sensitivity of 98.36% and a specificity of 96.49%. The developed RT-LAMP was found to be tenfold more sensitive compared to the RVFV qRT-PCR assay commonly used in the confirmatory diagnosis of RVFV.

Assessing the impact of non-pharmaceutical interventions (NPIs) and BCG vaccine cross-protection in the transmission dynamics of SARS-CoV-2 in eastern Africa.

OBJECTIVE: The outbreak of the novel coronavirus disease 2019 (COVID-19) is still affecting African countries. The pandemic presents challenges on how to measure governmental, and community responses to the crisis. Beyond health risks, the socio-economic implications of the pandemic motivated us to examine the transmission dynamics of COVID-19 and the impact of non-pharmaceutical interventions (NPIs). The main objective of this study was to assess the impact of BCG vaccination and NPIs enforced on COVID-19 case-death-recovery counts weighted by age-structured population in Ethiopia, Kenya, and Rwanda. We applied a semi-mechanistic Bayesian hierarchical model (BHM) combined with Markov Chain Monte Carlo (MCMC) simulation to the age-structured pandemic data obtained from the target countries. RESULTS: The estimated mean effective reproductive number (Rt) for COVID-19 was 2.50 (C1: 1.99-5.95), 3.51 (CI: 2.28-7.28) and 3.53 (CI: 2.97-5.60) in Ethiopia, Kenya and Rwanda respectively. Our results indicate that NPIs such as lockdowns, and curfews had a large effect on reducing Rt. Current interventions have been effective in reducing Rt and thereby achieve control of the epidemic. Beyond age-structure and NPIs, we found no significant association between COVID-19 and BCG vaccine-induced protection. Continued interventions should be strengthened to control transmission of SARS-CoV-2.

Potential distribution of fall armyworm in Africa and beyond, considering climate change and irrigation patterns.

The fall armyworm, Spodoptera frugiperda (FAW), first invaded Africa in 2016 and has since become established in many areas across the continent where it poses a serious threat to food and nutrition security. We re-parameterized the existing CLIMEX model to assess the FAW global invasion threat, emphasizing the risk of transient and permanent population establishment in Africa under current and projected future climates, considering irrigation patterns. FAW can establish itself in almost all countries in eastern and central Africa and a large part of western Africa under the current climate. Climatic barriers, such as heat and dry stresses, may limit the spread of FAW to North and South Africa. Future projections suggest that FAW invasive range will retract from both northern and southern regions towards the equator. However, a large area in eastern and central Africa is projected to have an optimal climate for FAW persistence. These areas will serve as FAW 'hotspots' from where it may migrate to the north and south during favorable seasons and then pose an economic threat. Our projections can be used to identify countries at risk for permanent and transient FAW-population establishment and inform timely integrated pest management interventions under present and future climate in Africa.

A deadly encounter: Alien invasive Spodoptera frugiperda in Africa and indigenous natural enemy, Cotesia icipe (Hymenoptera, Braconidae).

The invasion and wide spread of Spodoptera frugiperda represent real impediments to food security and the livelihood of the millions of maize and sorghum farming communities in the sub-Saharan and Sahel regions of Africa. Current management efforts for the pest are focused on the use of synthetic pesticides, which are often economically unviable and are extremely hazardous to the environment. The use of biological control offers a more economically and environmentally safer alternative. In this study, the performance of the recently described parasitoid, Cotesia icipe, against the pest was elucidated. We assessed the host stage acceptability by and suitability for C. icipe, as well as its ovigenic status. Furthermore, the habitat suitability for the parasitoid in the present and future climatic conditions was established using Maximum Entropy (MaxEnt) algorithm and the Genetic Algorithm for Rule-set Prediction (GARP). Cotesia icipe differentially accepted the immature stages of the pest. The female acceptance of 1st and 2nd instar larvae for oviposition was significantly higher with more than 60% parasitism. No oviposition on the egg, 5th and 6th larval instars, and pupal stages was observed. Percentage of cocoons formed, and the number of emerged wasps also varied among the larval stages. At initial parasitism, parasitoid progenies, time to cocoon formation and overall developmental time were significantly affected by the larval stage. Egg-load varied significantly with wasp age, with six-day-old wasps having the highest number of mature eggs. Ovigeny index of C. icipe was 0.53. Based on the models, there is collinearity in the ecological niche of the parasitoid and the pest under current and future climate scenarios. Eastern, Central and parts of coastal areas of western Africa are highly suitable for the establishment of the parasitoid. The geographic distribution of the parasitoid would remain similar under future climatic conditions. In light of the findings of this study, we discuss the prospects for augmentative and classical biological control of S. frugiperda with C. icipe in Africa.

Comparative in silico study of congocidine congeners as potential inhibitors of African swine fever virus.

African swine fever virus (ASFV) infection is fatal in domesticated pigs, with a mortality rate approaching 100%. This may result in economic losses and threats to food security. Currently, there are no approved vaccines or antiviral therapies for ASFV. Therefore, in this study, we evaluated congocidine congeners and a tris-benzimidazole as potential inhibitors of ASFV transcription using an in silico approach. We applied redocking of congocidine and docking of its congeners and a tris-benzimidazole to a receptor containing B-DNA with AT-motifs as a target to mimic conserved ASFV late gene promoters. Subsequently, the binding scores of DNA-ligand docked complexes were evaluated and their binding affinity was estimated. Molecular dynamics (MD) simulation was then used to assess ligand behavior within the minor groove. From our results, it is evident the less toxic congocidine congeners and tris-benzimidazole could dock to AT-rich regions significantly. Additionally, the predicted binding affinities had suitable values comparable to other experimentally determined minor groove binders, MD simulation of the docked DNA-ligand complexes and subsequent molecular trajectory visualization further showed that the ligands remained embedded in the minor groove during the time course of simulation, indicating that these ligands may have potential applications in abrogating ASFV transcription.

Metagenomics analysis of cocoa bean fermentation microbiome identifying species diversity and putative functional capabilities.

Fermentation of Theobroma cacao L. beans is the most critical stage in the production of cocoa products such as chocolates and its derivatives. There is a limited understanding of the complex response of microbial diversity during cocoa bean fermentation. The aim of the present study was to investigate microbial communities in the cocoa bean fermentation heap using a culture-independent approach to elucidate microbial diversity, structure, functional annotation and mapping unto metabolic pathways. Genomic DNA was extracted and purified from a sample of cocoa beans fermentation heap and was followed by library preparations. Sequence data was generated on Illumina Hiseq 2000 paired-end technology (Macrogen Inc). Taxonomic analysis based on genes predicted from the metagenome identified a high percentage of Bacteria (90.0%), Yeast (9%), and bacteriophages (1%) from the cocoa microbiome. Lactobacillus (20%), Gluconacetobacter (9%), Acetobacter (7%) and Gluconobacter (6%) dominated this study. The mean species diversity, measured by Shannon alpha-diversity index, was estimated at 142.81. Assignment of metagenomic sequences to SEED database categories at 97% sequence similarity identified a genetic profile characteristic of heterotrophic lactic acid fermentation of carbohydrates and aromatic amino acids. Metabolism of aromatic compounds, amino acids and their derivatives and carbohydrates occupied 0.6%, 8% and 13% respectively. Overall, these results provide insights into the cocoa microbiome, identifying fermentation processes carried out broadly by complex microbial communities and metabolic pathways encoding aromatic compounds such as phenylacetaldehyde, butanediol, acetoin, and theobromine that are required for flavour and aroma production. The results obtained will help develop targeted inoculations to produce desired chocolate flavour or targeted metabolic pathways for the selection of microbes for good aroma and flavour compounds formation.

In silico structural and functional prediction of African swine fever virus protein-B263R reveals features of a TATA-binding protein.

African swine fever virus (ASFV) is the etiological agent of ASF, a fatal hemorrhagic fever that affects domestic pigs. There is currently no vaccine against ASFV, making it a significant threat to the pork industry. The ASFV genome sequence has been published; however, about half of ASFV open reading frames have not been characterized in terms of their structure and function despite being essential for our understanding of ASFV pathogenicity. The present study reports the three-dimensional structure and function of uncharacterized protein, pB263R (NP_042780.1), an open reading frame found in all ASFV strains. Sequence-based profiling and hidden Markov model search methods were used to identify remote pB263R homologs. Iterative Threading ASSEmbly Refinement (I-TASSER) was used to model the three-dimensional structure of pB263R. The posterior probability of fold family assignment was calculated using TM-fold, and biological function was assigned using TM-site, RaptorXBinding, Gene Ontology, and TM-align. Our results suggests that pB263R has the features of a TATA-binding protein and is thus likely to be involved in viral gene transcription.

Metagenomic Analysis of Plant Virus Occurrence in Common Bean (Phaseolus vulgaris) in Central Kenya.

Two closely related potyviruses, bean common mosaic virus (BCMV) and bean common mosaic necrosis virus (BCMNV), are regarded as major constraints on production of common bean (Phaseolus vulgaris L.) in Eastern and Central Africa, where this crop provides a high proportion of dietary protein as well as other nutritional, agronomic, and economic benefits. Previous studies using antibody-based assays and indicator plants indicated that BCMV and BCMNV are both prevalent in bean fields in the region but these approaches cannot distinguish between these potyviruses or detect other viruses that may threaten the crop. In this study, we utilized next generation shotgun sequencing for a metagenomic examination of viruses present in bean plants growing at two locations in Kenya: the University of Nairobi Research Farm in Nairobi's Kabete district and at sites in Kirinyaga County. RNA was extracted from leaves of bean plants exhibiting apparent viral symptoms and sequenced on the Illumina MiSeq platform. We detected BCMNV, cucumber mosaic virus (CMV), and Phaseolus vulgaris alphaendornaviruses 1 and 2 (PvEV1 and 2), with CMV present in the Kirinyaga samples. The CMV strain detected in this study was most closely related to Asian strains, which suggests that it may be a recent introduction to the region. Surprisingly, and in contrast to previous surveys, BCMV was not detected in plants at either location. Some plants were infected with PvEV1 and 2. The detection of PvEV1 and 2 suggests these seed transmitted viruses may be more prevalent in Eastern African bean germplasm than previously thought.

Novel Sources of Witchweed (Striga) Resistance from Wild Sorghum Accessions.

Sorghum is a major food staple in sub-Saharan Africa (SSA), but its production is constrained by the parasitic plant Striga that attaches to the roots of many cereals crops and causes severe stunting and loss of yield. Away from cultivated farmland, wild sorghum accessions grow as weedy plants and have shown remarkable immunity to Striga. We sought to determine the extent of the resistance to Striga in wild sorghum plants. Our screening strategy involved controlled laboratory assays of rhizotrons, where we artificially infected sorghum with Striga, as well as field experiments at three sites, where we grew sorghum with a natural Striga infestation. We tested the resistance response of seven accessions of wild sorghum of the aethiopicum, drummondii, and arundinaceum races against N13, which is a cultivated Striga resistant landrace. The susceptible control was farmer-preferred variety, Ochuti. From the laboratory experiments, we found three wild sorghum accessions (WSA-1, WSE-1, and WSA-2) that had significantly higher resistance than N13. These accessions had the lowest Striga biomass and the fewest and smallest Striga attached to them. Further microscopic and histological analysis of attached Striga haustorium showed that wild sorghum accessions hindered the ingression of Striga haustorium into the host endodermis. In one of the resistant accessions (WSE-1), host and parasite interaction led to the accumulation of large amounts of secondary metabolites that formed a dark coloration at the interphase. Field experiments confirmed the laboratory screening experiments in that these same accessions were found to have resistance against Striga. In the field, wild sorghum had low Area under the Striga Number Progressive curve (AUSNPC), which measures emergence of Striga from a host over time. We concluded that wild sorghum accessions are an important reservoir for Striga resistance that could be used to expand the genetic basis of cultivated sorghum for resistance to the parasite.