Applications of Proteomic Tools to Study Insect Vector–Plant Virus Interactions

Abstract

Proteins are crucial players of biological interactions within and between the organisms and thus it is important to understand the role of proteins in successful partnerships, such as insect vectors and their plant viruses. Proteomic approaches have identified several proteins at the interface of virus acquisition and transmission by their insect vectors which could be potential molecular targets for sustainable pest and viral disease management strategies. Here we review the proteomic techniques used to study the interactions of insect vector and plant virus. Our review will focus on the techniques available to identify the infection, global changes at the proteome level in insect vectors, and protein-protein interactions of insect vectors and plant viruses. Furthermore, we also review the integration of other techniques with proteomics and the available bioinformatic tools to analyze the proteomic data.

Leveraging Biotic Interaction Knowledge Graph and Network Analysis to Uncover Insect Vectors of Plant Virus

“…For future work, we recommend trying to use RDF data and perform analysis directly via SPARQL queries rather than our data acquisition step, which requires data conversion and analysis, which may require more execution time. This is also related to the [44] study, which states that querying graph data is faster than tabular relational data. Apart from that, we also recommend conducting research to uncover more information on taxonomic association patterns of insects and viruses and documenting them into knowledge graphs or ontologies.…”

“…However, a notable distinction lies in the objective that [43] primarily centered around COVID-19 information, whereas our investigation was specifically oriented towards insect vectors. For comparison, there is another study [44] that also uses analytical data for studies on insect-plant-virus interactions, but this research uses proteomic techniques. However, research on proteomic techniques has several gaps that can be covered by our research.…”

Real-Time Detection and Classification of Scirtothrips dorsalis on Fruit Crops with Smartphone-Based Deep Learning System: Preliminary Results

“…Morphometric analyses conducted on populations of S. dorsalis from different continents showed significant distinctions between Asian populations and four other populations, based on two to five morphological characteristics, depending on the specific populations being compared [ 38 ]. Protein analysis, while providing a 100% accuracy rate for distinguishing S. dorsalis from other species, is impractical for field use due to the need for specialized equipment and expertise [ 39 ]. Molecular methods such as PCR and DNA barcoding have shown promise, with accuracy rates reaching 86% [ 40 ].…”

Phytovirus Vectors, Detection Techniques, and Future Directions

“…These interactions could be facilitated by proteins within plant viruses, and insect vectors. For instance, proteomic proteins are used to interact with plant viruses and insect vectors for transmission (Mittapelly and Rajarapu, 2020). The proteins found in the host plant cells also respond to efficient plant virus transmission.…”