Potato Cyst Nematode Egg Viability Assessment and Preparasitic Juvenile Screening Using a Large Particle Flow Cytometer and Sorter

Exploring nematicidal biomolecules from Xenorhabdus nematophila as a novel source for Meloidogyne incognita management

Attempts were made to evaluate the purified bioactive compounds of Xenorhabdus nematophila against Meloidogyne incognita. In order to extract the purified compounds, a solid-supported liquid-liquid extraction system with a flow rate (1 mL/min) was used to purify bioactive molecules. Compounds were individually collected concentrated and evaluated against M. incognita. Among 25 fractions the L19 fraction, exhibited 98% inhibition in egg hatching and mortality of juveniles. The biomolecules were identified through Liquid Chromatography- Mass Spectroscopy (LC-MS) technique. To decipher the mode of action of compounds, molecular docking studies were performed with potential protein targets such as acetylcholinesterase, β-1,4-endoglucanase, glutathione S-transferase-1, cytochrome c oxidase, G-protein coupled receptor and Fatty acid and retinol-binding proteins of M. incognita. The results revealed that among eight compounds from the L19 fraction, malonate and pidopidon exhibited greater binding affinity towards the selected protein targets of M. incognita. In vitro studies with malonate and pidopidon against M. incognita showcased a 99% reduction in egg hatching and juvenile mortality. Moreover, greenhouse experiments revealed that malonate compounds not only reduced 94% of the M. incognita population but also enhanced the plant growth parameters in tomato by 60%. Hence the present study stands novel in exploiting the nematicidal compounds from X. nematophila giving limelight to explore pidopidon and malonate as novel nematicidal compounds for the management of M. incognita.

A high throughput method for egg size measurement in Drosophila

Life-history traits are used as proxies of fitness in insects including Drosophila. Egg size is an adaptive and ecologically important trait potentially with genetic variation across different populations. However, the low throughput of manual measurement of egg size has hampered the widespread use of this trait in evolutionary biology and population genetics. We established a method for accurate and high throughput measurement of Drosophila egg size using large particle flow cytometry (LPFC). The size estimates using LPFC are accurate and highly correlated with the manual measurements. The measurement of egg size is high throughput (average of 214 eggs measured per minute) and viable eggs of a specific size can be sorted rapidly (average of 70 eggs per minute). Sorting by LPFC does not reduce the survival of eggs making it a suitable approach for sorting eggs for downstream analyses. This protocol can be applied to any organism within the detectable size range (10-1500 µm) of the large particle flow cytometers. We discuss the potential applications of this method and provide recommendations for optimizing the protocol for other organisms.

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.

A Broad Review of Soybean Research on the Ongoing Race to Overcome Soybean Cyst Nematode

Plant pathogens greatly impact food security of the ever-growing human population. Breeding resistant crops is one of the most sustainable strategies to overcome the negative effects of these biotic stressors. In order to efficiently breed for resistant plants, the specific plant-pathogen interactions should be understood. Soybean is a short-day legume that is a staple in human food and animal feed due to its high nutritional content. Soybean cyst nematode (SCN) is a major soybean stressor infecting soybean worldwide including in China, Brazil, Argentina, USA and Canada. There are many Quantitative Trait Loci (QTLs) conferring resistance to SCN that have been identified; however, only two are widely used: rhg1 and Rhg4. Overuse of cultivars containing these QTLs/genes can lead to SCN resistance breakdown, necessitating the use of additional strategies. In this manuscript, a literature review is conducted on research related to soybean resistance to SCN. The main goal is to provide a current understanding of the mechanisms of SCN resistance and list the areas of research that could be further explored.

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.