Applications & Publications

Investigating Marine, Freshwater, and Soil Biodiversity with Large Particle Imaging Flow Cytometry

Engineering of Bacillus thuringiensis insecticidal proteins

Bacillus thuringiensis (Bt) has been used as sprayable pesticides for many decades. Bt strains utilized in these products produce multiple insecticidal proteins to complement a narrow insect specificity of each protein. In the late 1990s, genes encoding Bt insecticidal proteins were expressed in crop plants such as cotton and corn to protect these crops from insect damage. The first Bt protein used in transgenic cotton was Cry1Ac to control Heliothis virescens (tobacco budworm). Cry1Ab was applied to corn to control Ostrinia nubilalis (European corn borer). Since these insects have developed resistance to Cry1Ac and Cry1Ab, new Bt proteins are required to overcome the resistance. In order to protect corn furthermore, it is desired to control Diabrotica virgifera (Western corn rootworm), Helicoverpa zea (corn earworm) and Spodoptera frugiperda (fall armyworm). Recently, many new Bt insecticidal proteins have been discovered, but most of them require protein engineering to meet the high activity standard for commercialization. The engineering process for higher activity necessary for Bt crops is called optimization. The seed industry has been optimizing Bt insecticidal proteins to improve their insecticidal activity. In this review, several optimization projects, which have led to substantial activity increases of Bt insecticidal proteins, are described.

The Smart Soil Organism Detector: An instrument and machine learning pipeline for soil species identification

Understanding the diversity of soil organisms is complicated by both scale and substrate. Every footprint we leave in the soil covers hundreds to millions of organisms yet we cannot see them without extremely laborious extraction and microsopy endeavors. Studying them is also challenging. Keeping them alive so that we can understand their lifecycles and ecological roles ranges from difficult to impossible. Functional and taxonomic identification of soil organisms, while possible, is also challenging. Here we present the Smart Soil Organism Detector, an instrument and machine learning pipeline that combines high-resolution imaging, multi-spectral sensing, large-bore flow cytometry, and machine learning to extract, isolate, count, identify, and separate soil organisms in a high-throughput, high-resolution, non-destructive, and reproducible manner. This system is not only capable of separating alive nematodes, dead nematodes, and nematode cuticles from soil with 100% out-of-sample accuracy, but also capable of identifying nematode strains (sub-species) with 95.5% out-of-sample accuracy and 99.4% specificity. Soil micro-arthropods were identified to class with 96.1% out-of-sample accuracy. Broadly applicable across soil taxa, the Smart SOD system is a tool for understanding global soil biodiversity.

Belowground Chemical Interactions: An Insight Into Host-Specific Behavior of Globodera spp. Hatched in Root Exudates From Potato and Its Wild Relative, Solanum sisymbriifolium

Understanding belowground chemical interactions between plant roots and plant-parasitic nematodes is immensely important for sustainable crop production and soilborne pest management. Due to metabolic diversity and ever-changing dynamics of root exudate composition, the impact of only certain molecules, such as nematode hatching factors, repellents, and attractants, has been examined in detail. Root exudates are a rich source of biologically active compounds, which plants use to shape their ecological interactions. However, the impact of these compounds on nematode parasitic behavior is poorly understood. In this study, we specifically address this knowledge gap in two cyst nematodes, Globodera pallida, a potato cyst nematode and the newly described species, Globodera ellingtonae. Globodera pallida is a devastating pest of potato (Solanum tuberosum) worldwide, whereas potato is a host for G. ellingtonae, but its pathogenicity remains to be determined. We compared the behavior of juveniles (J2s) hatched in response to root exudates from a susceptible potato cv. Desirée, a resistant potato cv. Innovator, and an immune trap crop Solanum sisymbriifolium (litchi tomato – a wild potato relative). Root secretions from S. sisymbriifolium greatly reduced the infection rate on a susceptible host for both Globodera spp. Juvenile motility was also significantly influenced in a host-dependent manner. However, reproduction on a susceptible host from juveniles hatched in S. sisymbriifolium root exudates was not affected, nor was the number of encysted eggs from progeny cysts. Transcriptome analysis by using RNA-sequencing (RNA-seq) revealed the molecular basis of root exudate-mediated modulation of nematode behavior. Differentially expressed genes are grouped into two major categories: genes showing characteristics of effectors and genes involved in stress responses and xenobiotic metabolism. To our knowledge, this is the first study that shows genome-wide root exudate-specific transcriptional changes in hatched preparasitic juveniles of plant-parasitic nematodes. This research provides a better understanding of the correlation between exudates from different plants and their impact on nematode behavior prior to the root invasion and supports the hypothesis that root exudates play an important role in plant-nematode interactions.