Frequency of Resistance to Bacillus thuringiensis Toxin Cry1Ab in an Iowa Population of European Corn Borer (Lepidoptera: Crambidae)

The refuge plus high-dose strategy for resistance management assumes that the frequency of resistance alleles is low. We used an F2 screen to estimate the frequency of resistance to transgenic corn that produces Bacillus thuringiensis Berliner Cry1Ab toxin (Bt corn) in an Iowa population of European corn borer, Ostrinia nubilalis (Hu¨ bner). We also proposed a modiÞcation to the statistical analysis of the F2 screen that extends its application for nonuniform prior distributions and for repeated sampling of a single population. Based on a sample of 188 isofemale lines derived from females caught at light traps during the 2nd ßight of 1997, we show with 95% conÞdence that the frequency of resistance to Bt corn was ,3.9 3 1023 in this Iowa population. These results provide weak evidence that the refuge plus high-dose strategy may be effective for managing resistance in O. nubilalis to Bt corn. Partial resistance to Cry1Ab toxin was found commonly. The 95% CI for the frequency of partial resistance were [8.231024, 9.431023] for the Iowa population. Variable costs of the method were $14.90 per isofemale line, which was a reduction of 25% compared with our initial estimate

Estimating arthropod survival probability from field counts: a case study with monarch butterflies

Survival probability is fundamental for understanding population dynamics. Methods for estimating survival probability from field data typically require marking individuals, but marking methods are not possible for arthropod species that molt their exoskeleton between life stages. We developed a novel Bayesian state‐space model to estimate arthropod larval survival probability from stage‐structured count data. We performed simulation studies to evaluate estimation bias due to detection probability, individual variation in stage duration, and study design (sampling frequency and sample size). Estimation of cumulative survival probability from oviposition to pupation was robust to potential sources of bias. Our simulations also provide guidance for designing field studies with minimal bias. We applied the model to the monarch butterfly (Danaus plexippus), a declining species in North America for which conservation programs are being implemented. We estimated cumulative survival from egg to pupation from monarch counts conducted at 18 field sites in three landcover types in Iowa, USA, and Ontario, Canada: road right‐of‐ways, natural habitats (gardens and restored meadows), and agricultural field borders. Mean predicted survival probability across all landcover types was 0.014 (95% CI: 0.004–0.024), four times lower than previously published estimates using an ad hoc estimator. Estimated survival probability ranged from 0.002 (95% CI: 7.0E−7 to 0.034) to 0.058 (95% CI: 0.013–0.113) at individual sites. Among landcover types, agricultural field borders in Ontario had the highest estimated survival probability (0.025 with 95% CI: 0.008–0.043) and natural areas had the lowest estimated survival probability (0.008 with 95% CI: 0.009–0.024). Monarch production was estimated as adults produced per milkweed stem by multiplying survival probabilities by eggs per milkweed at these sites. Monarch production ranged from 1.0 (standard deviation [SD] = 0.68) adult in Ontario natural areas in 2016 to 29.0 (SD = 10.42) adults in Ontario agricultural borders in 2015 per 6809 milkweed stems. Survival estimates are critical to monarch population modeling and habitat restoration efforts. Our model is a significant advance in estimating survival probability for monarch butterflies and can be readily adapted to other arthropod species with stage‐structured life histories

Climate change impacts on mycotoxin risks in US maize

To ensure future food security, it is crucial to understand how potential climate change scenarios will affect agriculture. One key area of interest is how climatic factors, both in the near- and the long-term future, could affect fungal infection of crops and mycotoxin production by these fungi. The objective of this paper is to review the potential impact of climate change on three important mycotoxins that contaminate maize in the United States, and to highlight key research questions and approaches for understanding this impact. Recent climate change analyses that pertain to agriculture and in particular to mycotoxigenic fungi are discussed, with respect to the climatic factors – temperature and relative humidity – at which they thrive and cause severe damage. Additionally, we discuss how climate change will likely alter the life cycles and geographic distribution of insects that are known to facilitate fungal infection of crops

Genetic similarity among pheromone and voltinism races of Ostrinia nubilalis (Hubner) (Lepidoptera: Crambidae)

The genetic variability of seven European corn borer populations, Ostrinia nubilalis, from North America and Europe was assessed by polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) analysis and DNA sequencing. The nuclear ribosomal internal transcribed spacer 1 (ITS-1) region (≈ 500 base pair [bp]) and four mitochondrial (mtDNA) regions (1550 bp total) were examined. The smartweed borer, Ostrinia obumbratalis, and south-Western corn borer, Diatraea grandiosella, were used for comparisons. Of 106 restriction sites identified (80 in mtDNA and 26 in ITS-1), none differentiated geographical populations, pheromone races, or voltine ecotypes of the European corn borer. The lack of variation in the ITS-1 of European corn borer was confirmed by DNA sequence analysis. The genetic similarity of European corn borer populations, despite their wide geographical range and physiological differences, may be explained by a relatively recent origin for the voltinism and pheromone races, gene flow among races, and/or expansion from genetic bottlenecks

Design and fabrication of 3D-printed anatomically shaped lumbar cage for intervertebra disc (IVD) degeneration treatment

Spinal fusion is the gold standard surgical procedure for degenerative spinal conditions when conservative therapies have been unsuccessful in rehabilitation of patients. Novel strategies are required to improve biocompatibility and osseointegration of traditionally used materials for lumbar cages. Furthermore, new design and technologies are needed to bridge the gap due to the shortage of optimal implant sizes to fill the intervertebral disc defect. Within this context, additive manufacturing technology presents an excellent opportunity to fabricate ergonomic shape medical implants. The goal of this study is to design and manufacture a 3D-printed lumbar cage for lumbar interbody fusion. Optimisations of the proposed implant design and its printing parameters were achieved via in silico analysis. The final construct was characterised via scanning electron microscopy, contact angle, x-ray micro computed tomography (μCT), atomic force microscopy, and compressive test. Preliminary in vitro cell culture tests such as morphological assessment and metabolic activities were performed to access biocompatibility of 3D-printed constructs. Results of in silico analysis provided a useful platform to test preliminary cage design and to find an optimal value of filling density for 3D printing process. Surface characterisation confirmed a uniform coating of nHAp with nanoscale topography. Mechanical evaluation showed mechanical properties of final cage design similar to that of trabecular bone. Preliminary cell culture results showed promising results in terms of cell growth and activity confirming biocompatibility of constructs. Thus for the first time, design optimisation based on computational and experimental analysis combined with the 3D-printing technique for intervertebral fusion cage has been reported in a single study. 3D-printing is a promising technique for medical applications and this study paves the way for future development of customised implants in spinal surgical applications

Selection of Reference Genes for RT-qPCR Analysis in the Monarch Butterfly, \u3cem\u3eDanaus plexippus\u3c/em\u3e (L.), a Migrating Bio-Indicator

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a powerful technique to quantify gene expression. To facilitate gene expression study and obtain accurate results, normalization relative to stably expressed reference genes is crucial. The monarch butterfly, Danaus plexippus (L.), is one of the most recognized insect species for its spectacular annual migration across North America. Besides its great voyages, D. plexippus has drawn attention to its role as a bio-indicator, ranging from genetically modified organisms (GMOs) to natural ecosystems. In this study, nine reference genes from D. plexippus genome were selected as the candidate reference genes. The expression profiles of these candidates under various biotic and abiotic conditions were evaluated using the four readily available computational programs, BestKeeper, Normfinder, geNorm, and ΔCt method, respectively. Moreover, RefFinder, a web-based computational platform integrating the four above mentioned algorisms, provided a comprehensive ranking of the stability of these reference genes. As a result, a suite of reference genes were recommended for each experimental condition. Specifically, elongation factor 1α (EF1A) and ribosomal protein 49 (RP49) were the most stable reference genes, respectively, under biotic (development, tissue, and sex) and abiotic (photoperiod, temperature, and dietary RNAi) conditions. With the recent release of a 273-million base pair draft genome, results from this study allow us to establish a standardized RT-qPCR analysis and lay a foundation for the subsequent genomic and functional genomic research in D. plexippus, a major bio-indicator and an emerging model for migratory animals

Dietary Risk Assessment of \u3cem\u3ev-ATPase A\u3c/em\u3e dsRNAs on Monarch Butterfly Larvae

By suppressing the expression of genes with essential biological functions, in plantaRNAi can negatively affect the development and survival of target pests. As a part of a concerted effort to assess the risks of RNAi transgenic crops on non-target organisms, we developed an in vivo toxicity assay to examine the impacts of ingested dsRNAs incurred to the monarch butterfly, Danaus plexippus (L.), an iconic eco-indicator in North America. To create the worst case scenario, the full-length v-ATPase A cDNAs from the target pest, western corn rootworm, Diabrotica virgifera virgifera, and the non-target D. plexippus were respectively cloned. A 400 bp fragment with the highest sequence similarity between the two species was used as the template to synthesize dsRNAs for the subsequent dietary RNAi toxicity assay. Specifically, newly hatched neonates were provisioned with leaf disks surface-coated with v-ATPase A dsRNAs synthesized from D. v. virgifera and D. plexippus, respectively, a control dsRNA, β-glucoruronidase, from plants, and H2O. The endpoint measurements included gene expressions and life history traits. The 2283 bp D. plexippus v-ATPase A cDNA contains a 99 bp 5′-untranslated region, a 330 bp 3′-untranslated region, and an 1851 bp ORF encoding 617 amino acids. The temporal RNAi study did not detect any impact to D. plexippus v-ATPase A expression by the assay days and treatments. This was reflected in the phenotypic impacts of dietary RNAi, in which both survival rate and development time were not affected by the uptake of ingested dsRNAs. These combined results suggest that D. plexippus larvae are not susceptible to dietary RNAi, therefore, the impact of transgenic RNAi plants on this non-target organism is, likely, negligible