Invasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the "Locally Fixed Alleles" approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to multiple genomic alleles becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population. 1R01AI139085-01 (FG and ALL) and the NC State Drexel Endowment (ALL). Contributions from other members of the Genetic Biocontrol of Invasive Rodents (GBIRd) consortium (http://www.geneticbiocontrol.org/) are acknowledged and greatly appreciated. We thank the referees for their constructive comments that helped improve this paper. Author ContributionsJS, BH, FG and ALL designed the model. JS, BH and ALL carried out model simulations and analysis. JS, BH, FG and ALL wrote the first draft of the paper. All authors discussed model results and contributed to editing and revision of the manuscript.

Invasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the “Locally Fixed Alleles” approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to alleles at multiple genomic loci becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population.

The absence of expression of the granule-bound starch synthase I (GBSSI) allele from chromosome 4A of wheat is associated with improved starch quality for making Udon noodles. Several PCR-based methods for the analysis of GBSS alleles have been developed for application in wheat. A widely applied approach has involved a simple PCR followed by electrophoretic separation of DNA products on agarose gels. The PCR amplifies one band from each of the loci on chromosomes 4A (Wx-B1), 7A (Wx-A1), and 7D (Wx-D1), and the band from the Wx-B1 locus is diagnostic for the occurrence of the null Wx-B1 allele that is associated with improved starch quality. The reliable detection of the null Wx-B1 allele has been important in identifying wheat breeding lines. Allele-specific PCR has also been used to successfully detect the occurrence of the null Wx-B1 allele. In the present paper the various protocols were evaluated by testing a segregating double haploid population from a cross between Cranbrook and Halberd and the tests gave good agreement in different laboratories. The application of the DNAbased tests applied in wheat breeding programs provides one of the first examples of a molecular marker selection for a grain quality trait being successfully applied in an Australian wheat breeding program.

Background We evaluated efficacy, pharmacokinetics (PK), and safety of clofazimine (CFZ) in HIV-infected patients with cryptosporidiosis. Methods We performed a randomized, double-blind, placebo-controlled study. Primary outcomes in Part A were reduction in Cryptosporidium shedding, safety, and PK. Primary analysis was according to protocol (ATP). Part B of the study compared CFZ PK in matched HIV-infected individuals without cryptosporidiosis. Results Twenty Part A and 10 Part B participants completed the study ATP. Almost all Part A participants had high viral loads and low CD4 counts, consistent with failure of antiretroviral (ARV) therapy. At study entry, the Part A CFZ group had higher Cryptosporidium shedding, total stool weight, and more diarrheal episodes compared to the placebo group. Over the inpatient period, compared to those who received placebo, the CFZ group Cryptosporidium shedding increased by 2.17 log2Cryptosporidium per gram stool (95% upper confidence limit: 3.82), total stool weight decreased by 45.3 g (p=0.37), and number of diarrheal episodes increased by 2.32 (p=0.87). The most frequent solicited adverse effects were diarrhea, abdominal pain, and malaise. Three CFZ and 1 placebo subjects died during the study. Plasma levels of CFZ in participants with cryptosporidiosis were 2-fold lower than Part B controls. Conclusion Our findings do not support the efficacy of CFZ for the treatment of cryptosporidiosis in a severely immunocompromised HIV population. However, this trial demonstrates a pathway to assess the therapeutic potential of drugs for cryptosporidiosis treatment. Screening persons with HIV for diarrhea, and especially Cryptosporidium infection, may identify those failing ARV therapy.

Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract