Search bioRxiv⌕ Search

Biology subjects

Wainaina, J. M.

Publications and source records attributed to Wainaina, J. M..

4 recordsLinked to original sources

CheckAMG: Accurate Identification of Auxiliary Viral Genes with Genome-Language Models

Viruses shape microbial metabolism through auxiliary viral genes (AVGs) that reprogram host metabolism, physiology, and gene regulation during infection. Identifying AVGs is complicated by ambiguous viral versus cellular assignment, inconsistent curation, and reliance on sequence homology that misses divergent functions. Here we present CheckAMG, which pairs annotation-based AVG prediction, curated with a per-gene viral scoring system and ontological mapping of metabolic function, with a finetuned genome-language model for annotation-independent discovery. Benchmarked against DRAM-V and VIBRANT across three ecosystems, CheckAMG produced more strongly supported auxiliary metabolic gene (AMG) calls, and uniquely among AMG tools reports auxiliary physiological (APGs) and regulatory (AReGs) genes. Applied to 1,005,980 fragmented or complete soil and human-gut viral genomes, CheckAMG identified 541,199 AVGs tracking biome-specific protein clusters and functions, including 109,107 proteins with no detectable sequence similarity to any reference database. CheckAMG thus provides a reproducible, scalable framework for identifying the genes through which viruses reprogram host biology.

bioinformatics↗

RNA virus ecogenomics along a subarctic permafrost thaw gradient

Climate change thaws permafrost, which releases greenhouse gases partly from dormant microorganisms awakening and metabolizing organic matter. Though DNA viruses that infect these soil microbes have been studied, little is known on soil RNA viruses, which typically infect microeukaryotes. Here we identify and characterize 2,651 RNA viruses from a 4-year time series of bulk soil metatranscriptomes derived from the climatically fragile Stordalen Mire ecosystem --a long studied permafrost peatland. RNA virus diversity was structured by habitat (palsa, bog, and fen), and these patterns correlated with pH and carbon dioxide and methane emissions. Further, host prediction, virus-encoded metabolite-transforming and information-processing functions suggested roles in ecosystem-scale carbon fluxes and contribute to greenhouse gases emissions. Together, these RNA virus ecogenomic data in permafrost provide essential baseline information for integration into predictive models to support hypothesis testing.

microbiology↗

Real time portable genome sequencing for global food security

The United Nations has listed Zero Hunger as one of the 17 global sustainable development goals to end extreme poverty by 2030. Plant viruses are a major constraint to crop production globally causing an estimated $30 billion in damage 1 leaving millions of people food insecure 2. In Africa, agriculture employs up to 50% of the workforce, yet only contributes 15% to the GDP on average 3, suggesting that there is low productivity and limited value addition. This can be addressed through continued innovation in the fields of science and technology as suggested in the Science Agenda for Agriculture in Africa (S3A) 4. Sustainable management of plant viruses and their associated vectors must include efficient diagnostics for surveillance, detection and identification to inform disease management, including the development and strategic deployment of virus resistant varieties. To date, researchers have been utilizing conventional methods such as; PCR, qPCR, high throughput sequencing (RNA-Seq, DNA-Seq) and Sanger sequencing for pathogen identification. However, these methods are both costly and time consuming, delaying timely control actions. The emergence of new tools for real-time diagnostics, such as the Oxford Nanopore MinION, have recently proven useful for early detection of Ebola 6 and Zika 7,8, even in low resourced laboratories. For the first time globally, the MinION portable pocket DNA sequencer was used to sequence whole plant virus genomes. We used this technology to identify the begomoviruses causing the devastating CMD which is ravaging smallholder farmers crops in sub-Saharan Africa. Cassava, a carbohydrate crop from which tapioca originates, is a major source of calories for over eight hundred (800) million people worldwide. With this technology, farmers struggling with diseased crops can take immediate, restorative action to improve their livelihoods based on information about the health of their plants, generated using a portable, real-time DNA sequencing device.

plant biology↗

Evolutionary insights into Bean common mosaic necrosis virus and Cowpea aphid borne mosaic virus using global isolates and thirteen new near complete genomes from Kenya

Plant viral diseases are one of the major limitations in legume production within sub Saharan Africa (SSA), as they account for up to 100 % in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out. The main aim was to gain insights into the selection pressure and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV), within symptomatic common beans and cowpeas. Eleven near complete genomes of BCMNV and two for CABMV sequences were obtained from SSA. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes was carried out. Three distinct well-supported clades were identified across the whole genome tree, and were in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. These results will contribute greatly to the knowledge gap surrounding the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and support the current breeding efforts towards resistance for BCMNV and CABMV.

evolutionary biology↗