Current and future scenarios of suitability and expansion of cassava brown streak disease, Bemisia tabaci species complex, and cassava planting in Africa.

Cassava (Manihot esculenta) is among the most important staple crops globally, with an imperative role in supporting the Sustainable Development Goal of 'Zero hunger'. In sub-Saharan Africa, it is cultivated mainly by millions of subsistence farmers who depend directly on it for their socio-economic welfare. However, its yield in some regions has been threatened by several diseases, especially the cassava brown streak disease (CBSD). Changes in climatic conditions enhance the risk of the disease spreading to other planting regions. Here, we characterise the current and future distribution of cassava, CBSD and whitefly Bemisia tabaci species complex in Africa, using an ensemble of four species distribution models (SDMs): boosted regression trees, maximum entropy, generalised additive model, and multivariate adaptive regression splines, together with 28 environmental covariates. We collected 1,422 and 1,169 occurrence records for cassava and Bemisia tabaci species complex from the Global Biodiversity Information Facility and 750 CBSD occurrence records from published literature and systematic surveys in East Africa. Our results identified isothermality as having the highest contribution to the current distribution of cassava, while elevation was the top predictor of the current distribution of Bemisia tabaci species complex. Cassava harvested area and precipitation of the driest month contributed the most to explain the current distribution of CBSD outbreaks. The geographic distributions of these target species are also expected to shift under climate projection scenarios for two mid-century periods (2041-2060 and 2061-2080). Our results indicate that major cassava producers, like Cameron, Ivory Coast, Ghana, and Nigeria, are at greater risk of invasion of CBSD. These results highlight the need for firmer agricultural management and climate-change mitigation actions in Africa to combat new outbreaks and to contain the spread of CBSD.

Assessing the effect of sample storage time on viral detection using a rapid and cost-effective CTAB-based extraction method.

BACKGROUND: Cassava leaf samples degrade quickly during storage and transportation from distant areas. Proper sampling and efficient, low-cost storage methods are critical for obtaining sufficient quality DNA and RNA for plant virus epidemiology and improving disease control understanding. This is useful when samples are collected from remote areas far from a laboratory or in developing countries where money and materials for virus diagnostics are scarce. RESULTS: The effect of sample storage duration on nucleic acid (N.A.) quality on virus detection was investigated in this study. A simple, rapid, and cost-effective CTAB-based approach (M3) for single N.A. extraction was optimized and tested alongside two existing CTAB-based methods (M1 and M2) for N.A. extraction from fresh and herbarium cassava leaves stored for; 1, 8, 26, and 56 months. The amount and quality of DNA and RNA were determined using Nanodrop 2000 c U.V.-vis Spectrophotometer and agarose gel electrophoreses. The sample degradation rate was estimated using a simple mathematical model in Matlab computational software. The results show no significant difference in mean DNA concentration between M1 and M2 but a significant difference between M3 and the other two methods at p < 0.005. The mean DNA concentration extracted using M3 was higher for 1 and 8 months of leave storage. M3 and M2 produced high concentrations at 26 and 56 months of leave storage. Using a developed scale for quality score, M3 and M2 produced high-quality DNA from fresh samples. All methods produced poor-quality DNA and RNA at 8 and 26 months of leave storage and no visual bands at the age of 56 months. Statistically, there was a significant difference in the mean DNA quality between M1 and M2, but there was no significant difference between M3 and the other two methods at p < 0.005. However, Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) were readily detected by RT-PCR from RNA isolated using M3. The quality of DNA declined per storage time at 0.0493 and 0.0521/month, while RNA was 0.0678 and 0.0744/month. Compared to the existing two methods, modified CTAB extracted enough high-quality N.A. in one-third the time of the existing two methods. CONCLUSION: Our method provides cost-effective, quick, and simple processing of fresh and dry samples, which will quicken and guide the decision on when and what type of sample to process for plant disease management and surveillance actions.

Estimating epidemiological parameters from experiments in vector access to host plants, the method of matching gradients.

Estimation of pathogenic life-history values, for instance the duration a pathogen is retained in an insect vector (i.e., retention period) is of particular importance for understanding plant disease epidemiology. How can we extract values for these epidemiological parameters from conventional small-scale laboratory experiments in which transmission success is measured in relation to durations of vector access to host plants? We provide a solution to this problem by deriving formulae for the empirical curves that these experiments produce, called access period response curves (i.e., transmission success vs access period). We do this by writing simple equations for the fundamental life-cycle components of insect vectors in the laboratory. We then infer values of epidemiological parameters by matching the theoretical and empirical gradients of access period response curves. Using the example of Cassava brown streak virus (CBSV), which has emerged in sub-Saharan Africa and now threatens regional food security, we illustrate the method of matching gradients. We show how applying the method to published data produces a new understanding of CBSV through the inference of retention period, acquisition period and inoculation period parameters. We found that CBSV is retained for a far shorter duration in its insect vector (Bemisia tabaci whitefly) than had previously been assumed. Our results shed light on a number of critical factors that may be responsible for the transition of CBSV from sub- to super-threshold R0 in sub-Saharan Africa. The method is applicable to plant pathogens in general, to supply epidemiological parameter estimates that are crucial for practical management of epidemics and prediction of pandemic risk.