Biology subjects

Alicai, T.

Publications and source records attributed to Alicai, T..

5 recordsLinked to original sources

bioRxiv2025

Predicting the cross-continental spread of the cassava brown streak disease epidemic in sub-Saharan Africa

Cassava brown streak disease (CBSD) is a major threat to smallholder farmers in sub-Saharan Africa (SSA), where cassava is a staple crop. Caused by cassava brown streak ipomoviruses (CBSIs), CBSD has spread extensively since its detection in Uganda in 2004, raising concerns about ongoing spread through Southern and Central Africa and potential expansion to West Africa, home to the worlds largest cassava producer, Nigeria. Building on a stochastic epidemiological model that predicts CBSD spread at the scale of Uganda, we incorporate extensive field surveillance records to extend the model to all thirty-two major cassava-producing countries in SSA. We then deploy the model to address key strategic questions such as estimating the present day CBSD distribution and predicting rates of ongoing spread towards West Africa. We also evaluate the risk of direct introductions resulting from long range movement of infected planting material, which could trigger outbreaks beyond predicted localised dispersal limits. Our model predicts the likely arrival of CBSD in Nigeria via cross-continental spread within 25 years, and if directly introduced anywhere in West Africa, spreading to most West African nations within 10 years. The risks of ongoing and future CBSD spread highlighted in this study underscore the need for proactive phytosanitation measures, including clean seed programs, vector control, and quarantine policies to curb CBSD spread. Moreover, the model described in this study not only provides estimates for arrival times across SSA, but also lays the foundations for a continental-scale quantitative framework wherein both surveillance and management options can be explored and optimised.

ecology↗

bioRxiv2022

Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa

The agricultural productivity of smallholder farmers in sub-Saharan Africa (SSA) is severely constrained by pests and pathogens, impacting economic stability and food security. Since 2004, an epidemic of cassava brown streak disease (CBSD) has been spreading rapidly from Uganda, with the disease causing necrosis of the edible root tissue. Based on sparse surveillance data, the epidemic front is currently believed to be at least as far west as central DRC and as far south as Zambia. The DRC is the worlds highest per capita consumer of cassava and future spread threatens production in West Africa which includes Nigeria, the worlds largest producer of cassava. Here, we take a unique Ugandan CBSD surveillance dataset spanning 2004 to 2017 and develop, parameterise, and validate a landscape-scale, spatiotemporal epidemic model of CBSD at a 1 km2 resolution. While this paper focuses on Uganda, the model is designed to be readily extended to make predictions beyond Uganda for all 32 major cassava producing countries of SSA, laying the foundations for a tool capable of informing strategic policy decisions at a national and regional scale.

ecology↗

bioRxiv2019

Tree Lab: Portable genomics for early detection of plant viruses and pests in Sub-Saharan Africa

In this case study we successfully teamed the PDQeX DNA purification technology developed by MicroGEM, New Zealand, with the MinION and MinIT mobile sequencing devices developed by Oxford Nanopore Technologies to produce an effective point-of-need field diagnostic system. The PDQeX extracts DNA using a cocktail of thermophilic proteinases and cell wall degrading enzymes, thermo-responsive extractor cartridges and a temperature control unit. This single-step closed system delivers purified DNA with no cross contamination. The MinIT is a newly released data processing unit that converts MinION raw signal output into base called data locally in real time, removing the need for high specification computers and large file transfers from the field. All three devices are battery powered with an exceptionally small footprint that facilitates transport and set up.\n\nTo evaluate and validate capability of the system for unbiased pathogen identification by realtime sequencing in a farmers field setting, we analysed samples collected from cassava plants grown by subsistence farmers in three sub-Sahara African countries (Tanzania, Uganda and Kenya). A range of viral pathogens, all with similar symptoms, greatly reduce yield or completely destroy cassava crops. 800 million people worldwide depend on cassava for food and yearly income, and viral diseases are a significant constraint on its production (https://cassavavirusactionproject.com). Early pathogen detection at a molecular level has great potential to rescue crops within a single growing season by providing results that inform decisions on disease management, use of appropriate virus resistant or replacement planting.\n\nThis case study presented conditions of working in-field with limited or no access to mains power, laboratory infrastructure, internet connectivity and highly variable ambient temperature. An additional challenge is that, generally, plant material contains inhibitors of downstream molecular processes making effective DNA purification critical. We successfully undertook real-time on-farm genome sequencing of samples collected from cassava plants on three farms, one in each country. Cassava mosaic begomoviruses were detected by sequencing leaf, stem, tuber and insect samples. The entire process, from arrival on farm to diagnosis including sample collection, processing and provisional sequencing results was complete in under 4 hours. The need for accurate, rapid and on-site diagnosis grows as globalized human activity accelerates. This technical breakthrough has applications that are relevant to human and animal health, environmental management and conservation.

genomics↗

bioRxiv2019

Recombination detected in the Heat Shock Protein 90 (HSP90) of the Bemisia tabaci species complex

BackgroundBemisia tabaci (whiteflies) are a global insect pest causing billions of dollars in damage each year, leaving farmers with low yields. In East Africa, whiteflies are superabundant and present on cassava plants throughout the year. Whiteflies do not decrease in number in the hot dry seasons in East Africa, therefore, it has been suggested that the synthesis of Heat Shock Protein (HSP) may protect the whitefly from heat stress and other biotic factors. In this study we used data sequence generated from individual whiteflies to assess variability and recombination of the HSP90 gene in members of the B. tabaci species complex.\n\nResultsA total of 21 samples were sequenced on Illumina Hiseq 2500 and Hiseq 4000. These included eight genetic groups of B. tabaci: 7 SSA1, 5 SSA2, 2 Australia I (AUSI), 2 New World Africa (NWAfrica), B. afer, Uganda, Mediterranean (MED), and Middle East Asia Minor 1 (MEAM1). An alignment of 21 HSP90 sequences was generated after mapping and de novo assembly. Recombination analysis was performed on an alignment of 27 HSP90 sequences (we added an additional 6 sequences from GenBank). There were 18 recombination events detected in the HSP90 gene of the B. tabaci species complex, 7 of which were regarded as events that could be caused by evolutionary mechanisms such as gene duplication other than recombination. The phylogenetic analysis carried out on dataset without recombination events revealed a tree pattern with short terminal branches.\n\nConclusionRecombination events were detected for members of the B. tabaci species complex in the HSP90 gene. This could explain the variability in the HSP90 gene of the B. tabaci species complex and highlight the phenomenon of the increased chance of survival and reproductive abundance of whiteflies in hot conditions in East Africa, since recombination is a major driving force of evolution.

evolutionary biology↗

bioRxiv2018

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↗