Protein-protein interaction network analysis of insecticide resistance molecular mechanism in Drosophila melanogaster

Honeybee gut bacterial strain improved survival and gut microbiota homeostasis in Apis mellifera exposed in vivo to clothianidin

Pesticides are causing honeybee mortality worldwide. Research carried out on honeybees indicates that application of pesticides has a significant impact on the core gut community, which ultimately leads to an increase in the growth of harmful pathogens. Disturbances caused by pesticides also affect the way bacterial members interact, which results in gut microbial dysbiosis. Administration of beneficial microbes has been previously demonstrated to be effective in treating or preventing disease in honeybees. The objective of this study was to measure under in vivo conditions the ability of two bacterial strains (the Enterobacter sp. and Pantoea sp.) isolated from honeybee gut to improve survival and mitigate gut microbiota dysbiosis in honeybees exposed to a sublethal clothianidin dose (0.1 ppb). Both gut bacterial strains were selected for their ability to degrade clothianidin in vitro regardless of their host-microbe interaction characteristics (e.g., beneficial, neutral, or harmful). To this end, we conducted cage trials on 4- to 6-day-old newly emerging honeybees. During microbial administration, we jointly monitored the taxonomic distribution and activity level of bacterial symbionts quantifying 16S rRNA transcripts. First, curative administration of the Pantoea sp. strain significantly improved the survival of clothianidin-exposed honeybees compared to sugar control bees (i.e., supplemented with sugar [1:1]). Second, curative administration of the Enterobacter sp. strain significantly mitigated the clothianidin-induced dysbiosis observed in the midgut structural network, but without improving survival.

IMPORTANCE

The present work suggests that administration of bacterial strains isolated from honeybee gut may promote recovery of gut microbiota homeostasis after prolonged clothianidin exposure, while improving survival. This study highlights that gut bacterial strains hold promise for developing efficient microbial formulations to mitigate environmental pesticide exposure in honeybee colonies.

Gene expression differences consistent with water loss reduction underlie desiccation tolerance of natural Drosophila populations

BACKGROUND

Climate change is one of the main factors shaping the distribution and biodiversity of organisms, among others by greatly altering water availability, thus exposing species and ecosystems to harsh desiccation conditions. However, most of the studies so far have focused on the effects of increased temperature. Integrating transcriptomics and physiology is key to advancing our knowledge on how species cope with desiccation stress, and these studies are still best accomplished in model organisms.

RESULTS

Here, we characterized the natural variation of European D. melanogaster populations across climate zones and found that strains from arid regions were similar or more tolerant to desiccation compared with strains from temperate regions. Tolerant and sensitive strains differed not only in their transcriptomic response to stress but also in their basal expression levels. We further showed that gene expression changes in tolerant strains correlated with their physiological response to desiccation stress and with their cuticular hydrocarbon composition, and functionally validated three of the candidate genes identified. Transposable elements, which are known to influence stress response across organisms, were not found to be enriched nearby differentially expressed genes. Finally, we identified several tRNA-derived small RNA fragments that differentially targeted genes in response to desiccation stress.

CONCLUSIONS

Overall, our results showed that basal gene expression differences across individuals should be analyzed if we are to understand the genetic basis of differential stress survival. Moreover, tRNA-derived small RNA fragments appear to be relevant across stress responses and allow for the identification of stress-response genes not detected at the transcriptional level.

In Vivo Glutathione S-Transferases Superfamily Proteome Analysis: An Insight into Aedes albopictus Mosquitoes upon Acute Xenobiotic Challenges

In this study, the induction of glutathione S-transferase (GST) enzymatic activities in Aedes albopictus under 24 h of xenobiotic challenges was investigated. From LCMS analysis, 23 GST isoforms were identified under Delta, Epsilon, Sigma, Zeta, Omega, and Iota classes, together with one GSTX1-1 isoform, in both treated and untreated samples. Using STRING 11.5, the functional enrichment network of Gene Ontology (GO) analysis, the identified peptides were found to be involved in the glutathione metabolic biological process (GO:0006749, p-value: 1.93 × 10−29), and the molecular functions involved are due to glutathione transferase (GO:0016848, p-value: 2.92 × 10−8) aside from carbon-halide lyase activity (GO:004364, p-value: 1.21 × 10−31). The Protein-Protein Interaction (PPI) network (STRING 11.5) showed significant interactions within the GST superfamily and some of the GST classes interacted with other proteins among the input domain of the identified peptides (p-value < 1.0 × 10−16). In TMT labeling for the quantification of peptide abundance, isoforms from Delta (GSTD1-2, GSTD1-3, GSTD1-4) and Epsilon (GSTE3-1, GSTE4-2) were found to be overexpressed (between 1.5-fold and 2-fold changes). In the PPI analysis, 12 common enriched pathways of Kyoto Encyclopedia of Genes and Genomes (KEGG) were found to be intercorrelated with the identified GSTs at PPI enrichment p-value < 1.0 × 10−16. Overall, this study indicates that distinct GST enzymes, which were identified up to their specific protein isoforms, are involved in the metabolic mechanisms underlying xenobiotic stress.

Metabolization and sequestration of plant specialized metabolites in insect herbivores: Current and emerging approaches

Herbivorous insects encounter diverse plant specialized metabolites (PSMs) in their diet, that have deterrent, anti-nutritional, or toxic properties. Understanding how they cope with PSMs is crucial to understand their biology, population dynamics, and evolution. This review summarizes current and emerging cutting-edge methods that can be used to characterize the metabolic fate of PSMs, from ingestion to excretion or sequestration. It further emphasizes a workflow that enables not only to study PSM metabolism at different scales, but also to tackle and validate the genetic and biochemical mechanisms involved in PSM resistance by herbivores. This review thus aims at facilitating research on PSM-mediated plant-herbivore interactions.

Unraveling the multi-targeted curative potential of bioactive molecules against cervical cancer through integrated omics and systems pharmacology approach

Molecular level understanding on the role of viral infections causing cervical cancer is highly essential for therapeutic development. In these instances, systems pharmacology along with multi omics approach helps in unraveling the multi-targeted mechanisms of novel biologically active compounds to combat cervical cancer. The immuno-transcriptomic dataset of healthy and infected cervical cancer patients was retrieved from the array express. Further, the phytocompounds from medicinal plants were collected from the literature. Network Analyst 3.0 has been used to identify the immune genes around 384 which are differentially expressed and responsible for cervical cancer. Among the 87 compounds reported in plants for treating cervical cancer, only 79 compounds were targeting the identified immune genes of cervical cancer. The significant genes responsible for the domination in cervical cancer are identified in this study. The virogenomic signatures observed from cervical cancer caused by E7 oncoproteins serve as the potential therapeutic targets whereas, the identified compounds can act as anti-HPV drug deliveries. In future, the exploratory rationale of the acquired results will be useful in optimizing small molecules which can be a viable drug candidate.

Identification of sex-biased and neurodevelopment genes via brain transcriptome in Ostrinia furnacalis

Insect brains play important roles in the regulation of sex-biased behaviors such as mating and oviposition. The neural structure and function of brain differences between males and females have been identified, in which the antenna lobes (AL) showed the most discrepancy, however, the whole repertoire of the genes expressed in the brains and the molecular mechanism of neural signaling and structural development are still unclear. In this study, high-throughput transcriptome analysis of male and female brains was carried on in the Asia corn borer, Ostrinia furnacalis, and a total of 39.23 Gb data and 34,092 unigenes were obtained. Among them, 276 genes displayed sex-biased expression by DEG analysis, of which 125 genes were highly expressed in the males and 151 genes were highly expressed in the females. Besides, by homology analysis against genes that have been confirmed to be related to brain neurodevelopment, a total of 24 candidate genes were identified in O. furnacalis. In addition, to further screen the core genes that may be important for sex-biased nerve signaling and neurodevelopment, protein-protein interaction networks were constructed for the sex-biased genes and neurodevelopment genes. We identified 10 (Mhc, Mlc1, Mlc2, Prm, Mf, wupA, TpnC25D, fln, l(2)efl, and Act5C), 11 (PPO2, GNBP3, Spn77Ba, Ppn, yellow-d2, PGRP-LB, PGRP-SD, PGRP-SC2, Hml, Cg25C, and vkg) and 8 (dac, wg, hh, ci, run, Lim1, Rbp9, and Bx) core hub genes that may be related to brain neural development from male-biased, female-biased, and neurodevelopment gene groups. Our results provide a reference for further analysis of the dimorphism of male and female brain structures in agricultural pests.

Systematic analysis of olfactory protein-protein interactions network of fruitfly, Drosophila melanogaster

Olfaction is one of the physiological traits of insect behavior. Insects have evolved a sophisticated olfactory system and use a combined coding strategy to process general odor. Drosophila melanogaster is a powerful model to reveal the molecular and cellular mechanisms of odor detection. Identifying new olfactory targets through complex interactions will contribute to a better understanding of the functions, interactions, and signaling pathways of olfactory proteins. However, the mechanism of D. melanogaster olfaction is still unclear, and more olfactory proteins are required to be discovered. In this study, we tried to explore essential proteins in the olfactory system of D. melanogaster and conduct protein-protein interactions (PPIs) analysis. We constructed the PPIs network of the olfactory system of D. melanogaster, consisting of 863 proteins and 18,959 interactions. Various methods were used to perform functional enrichment analysis, topological analysis and cluster analysis. Our results confirmed that Class B scavenger receptors (SR-Bs), glutathione S-transferases (GSTs), and UDP-glycosyltransferases (UGTs) play an essential role in olfaction of D. melanogaster. The proteins obtained in this study can be used for subsequent functional identification in D. melanogaster olfactory.

Construction and analysis of the protein-protein interaction network for the detoxification enzymes of the silkworm, Bombyx mori

Detoxification enzymes are necessary for insects to metabolize toxic substances and maintain physiological activities. Cytochromes P450 (CYPs), glutathione S-transferases (GSTs), and carboxylesterase (CarEs) are the main detoxification enzymes in insects. In addition, UDP-glucosyltransferase and ATP-binding cassette transporter also participate in the process of material metabolism. This study collected proteins related to detoxification in the silkworm, Bombyx mori (Lepidoptera: Bombycidae). And we performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on these proteins to understand their biological function. We constructed the protein-protein interaction network for the silkworm's detoxification enzymes and analyzed the network's topological properties. We found that BGIBMGA014046-TA, BGIBMGA003221-TA, BGIBMGA011092-TA, BGIBMGA000074-TA, and LOC732976 are the essential proteins in the network. These proteins are primarily involved in the process of ribosome biogenesis and may be related to protein synthesis. We integrated GO, KEGG, and network analysis and found that ribosome-associated protein and GSTs played a vital role in the detoxification process.

Dietary Contamination with a Neonicotinoid (Clothianidin) Gradient Triggers Specific Dysbiosis Signatures of Microbiota Activity along the Honeybee (Apis mellifera) Digestive Tract

Pesticides are increasing honeybee (Apis mellifera) death rates globally. Clothianidin neonicotinoid appears to impair the microbe–immunity axis. We conducted cage experiments on newly emerged bees that were 4–6 days old and used a 16S rRNA metataxonomic approach to measure the impact of three sublethal clothianidin concentrations (0.1, 1 and 10 ppb) on survival, sucrose syrup consumption and gut microbiota community structure. Exposure to clothianidin significantly increased mortality in the three concentrations compared to controls. Interestingly, the lowest clothianidin concentration was associated with the highest mortality, and the medium concentration with the highest food intake. Exposure to clothianidin induced significant variation in the taxonomic distribution of gut microbiota activity. Co-abundance network analysis revealed local dysbiosis signatures specific to each gut section (midgut, ileum and rectum) were driven by specific taxa. Our findings confirm that exposure to clothianidin triggers a reshuffling of beneficial strains and/or potentially pathogenic taxa within the gut, suggesting a honeybee’s symbiotic defense systems’ disruption, such as resistance to microbial colonization. This study highlights the role of weak transcriptional activity taxa in maintaining a stable honeybee gut microbiota. Finally, the early detection of gut dysbiosis in honeybees is a promising biomarker in hive management for assessing the impact exposure to sublethal xenobiotics.

The glutathione S-transferase (PxGST2L) may contribute to the detoxification metabolism of chlorantraniliprole in Plutella xylostella(L.)

The diamondback moth (Plutella xylostella L.), is an economic pest of cruciferous plants worldwide, which causes great economic loss to cruciferous plants production. However, the pest has developed resistance to insecticides. One of such insecticides is chlorantraniliprole. The study of the mechanisms underlying resistance is key for the effective management of resistance. In this study, a comparative proteomics approach was used to isolate and identify various proteins that differed between chlorantraniliprole-susceptible and -resistant strains of P. xylostella. Eleven proteins were significantly different and were successfully identified by MALDI-TOF-MS. Metabolism-related proteins accounted for the highest proportion among the eleven different proteins. The function of the PxGST2L protein was validated by RNAi. Knockdown of PxGST2L reduced the GST activity and increased the toxicity of chlorantraniliprole to the diamondback moth. The resistance ratio of diamondback moth to chlorantraniliprole was reduced from 1029 to 505. The results indicated that PxGST2L is partly responsible for chlorantraniliprole insecticide resistance in DBM. Our finding contributes to the understanding of the mechanism underlying resistance to chlorantraniliprole in the DBM, to develop effective resistance management tactics.

XSP10 and SlSAMT, Fusarium wilt disease responsive genes of tomato (Solanum lycopersicum L.) express tissue specifically and interact with each other at cytoplasm in vivo

Fusarium wilt caused by Fusarium oxysporum f. sp. lycopersici (Fol) is a major fungal disease of tomato (Solanum lycopersicum L.). Xylem sap protein 10 (XSP10) and Salicylic acid methyl transferase (SlSAMT) have been identified as putative negative regulatory genes associated with Fusarium wilt of tomato. Despite their importance as potential genes for developing Fusarium wilt disease tolerance, very little knowledge is available about their expression, cell biology, and functional genomics. Semi-quantitative and quantitative real-time PCR expression analysis of XSP10 and SlSAMT, in this study, revealed higher expression in root and flower tissue respectively in different tomato cultivars viz. Micro-Tom (MT), Arka Vikas (AV), and Arka Abhed (AA). Therefore, the highly up-regulated expression of XSP10 and SlSAMT in biotic stress susceptible tomato cultivar (AV) than a multiple disease resistant cultivar (AA) suggested the disease susceptibility nature of these genes for Fusarium wilt. Sub-cellular localization analysis through the expression of gateway cloning constructs in tomato protoplasts and seedlings showed the predominant localization of XSP10 in the nucleus and SlSAMT at the cytoplasm. A strong in vivo protein-protein interaction of XSP10 with SlSAMT at cytoplasm from bi-molecular fluorescent complementation study suggested that these two proteins function together in regulating responses to Fusarium wilt tolerance in tomato.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01025-y.

A structural analysis of the hypoxia response network

Background

The hypoxia-inducible factor-1 (HIF-1) signaling pathway is an important topic in high-altitude medicine. Network analysis is a novel method for integrating information on different aspects and levels of biological networks. However, this method has not been used in research on the HIF-1 signaling pathway network. To introduce this method into HIF-1-related research fields and verify its feasibility and effectiveness, we used a network analytical method to explore the structural attributes of the HIF-1 signaling pathway network.

Methods

First, we analyzed the overall network of the HIF-1 signaling pathway using information retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG). We performed topology analysis, centrality analysis, and subgroup analysis of the network. Then, we analyzed the core network based on the overall network analysis. We analyzed the properties of the topology, the bow-tie structure, and the structural complexity of the core network.

Results

We obtained topological structure diagrams and quantitative indicators of the overall and core networks of the HIF-1 signaling pathway. For the structure diagrams, we generated topology diagrams of the network and the bow-tie structure of the core network. As quantitative indicators, we identified topology, centrality, subgroups, the bow-tie structure, and structural complexity. The topology indicators were the number of nodes, the number of lines, the network diameter, and the network density. The centrality indicators were the degree, closeness, and betweenness. The cohesive subgroup indicator was the components of the network. The bow-tie structure indicators included the core, input, and tendril-like structures. The structural complexity indicators included a power-law fitting model and its scale parameter.

Conclusions

The core network could be extracted based on the subgroup analysis of the overall network of the HIF-1 signaling pathway. The critical elements of the network could be identified in the centrality analysis. The results of the study show the feasibility and effectiveness of the network analytical method used to explore the network properties of the HIF-1 signaling pathway and provide support for further research.

Construction and analysis of the protein-protein interaction network for the olfactory system of the silkworm Bombyx mori

Olfaction plays an essential role in feeding and information exchange in insects. Previous studies on the olfaction of silkworms have provided a wealth of information about genes and proteins, yet, most studies have only focused on a single gene or protein related to the insect's olfaction. The aim of the current study is to determine key proteins in the olfactory system of the silkworm, and further understand protein-protein interactions (PPIs) in the olfactory system of Lepidoptera. To achieve this goal, we integrated Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and network analyses. Furthermore, we selected 585 olfactory-related proteins and constructed a (PPI) network for the olfactory system of the silkworm. Network analysis led to the identification of several key proteins, including GSTz1, LOC733095, BGIBMGA002169-TA, BGIBMGA010939-TA, GSTs2, GSTd2, Or-2, and BGIBMGA013255-TA. A comprehensive evaluation of the proteins showed that glutathione S-transferases (GSTs) had the highest ranking. GSTs also had the highest enrichment levels in GO and KEGG. In conclusion, our analysis showed that key nodes in the biological network had a significant impact on the network, and the key proteins identified via network analysis could serve as new research targets to determine their functions in olfaction.

Direct protein-protein interaction network for insecticide resistance based on subcellular localization analysis in Drosophila melanogaster

In present study, we constructed the direct protein-protein interaction network of insecticide resistance based on subcellular localization analysis. Totally 177 of 528 resistance proteins were identified and they were located in 11 subcellular localizations. We further analyzed topological properties of the network and the biological characteristics of resistance proteins, such as k-core, neighborhood connectivity, instability index and aliphatic index. They can be used to predict the key proteins and potential mechanisms from macro-perspective. The problem of resistance has not been solved fundamentally, because the development of new insecticides can't keep pace with the development speed of resistance, and the lack of understanding of molecular mechanism of resistance. As the further analysis to reduce data noise, we constructed the direct protein-protein interaction network of insecticide resistance based on subcellular localization analysis. The interaction between proteins located at the same subcellular location belongs to direct interactions, thus eliminating indirect interaction. Totally 177 of 528 resistance proteins were identified and they were located in 11 subcellular localizations. We further analyzed topological properties of the network and the biological characteristics of resistance proteins, such as k-core, neighborhood connectivity, instability index and aliphatic index. They can be used to predict the hub proteins and potential mechanisms from macro-perspective. This is the first study to explore the insecticide resistance molecular mechanism of Drosophila melanogaster based on subcellular localization analysis. It can provide the bioinformatics foundation for further understanding the mechanisms of insecticide resistance. It also provides a reference for the study of molecular mechanism of insecticide resistance of other insects.

Proteomic analysis reveals the damaging role of low redox laccase from Yersinia enterocolitica strain 8081 in the midgut of Helicoverpa armigera

OBJECTIVE

Earlier, we have found that the enteropathogenic Yersinia enterocolitica have evolved the survival mechanisms that regulate the expression of laccase-encoding genes in the gut. The present study aims to characterize the purified recombinant laccase from Y. enterocolitica strain 8081 biovar 1B and understand its effect on the midgut of cotton bollworm, Helicoverpa armigera (Hübner) larvae.

RESULTS

The recombinant laccase protein showed high purity fold and low molecular mass (~ 43 kDa). H. armigera larvae fed with laccase protein showed a significant decrease in body weight and damage in the midgut. Further, transmission electron microscopy (TEM) studies revealed the negative effect of laccase protein on trachea, malpighian tubules, and villi of the insect. The proteome comparison between control and laccase-fed larvae of cotton bollworm showed significant expression of proteolytic enzymes, oxidoreductases, cytoskeletal proteins, ribosomal proteins; and proteins for citrate (TCA cycle) cycle, glycolysis, stress response, cell redox homeostasis, xenobiotic degradation, and insect defence. Moreover, it also resulted in the reduction of antioxidants, increased melanization (insect innate immune response), and enhanced free radical generation.

CONCLUSIONS

All these data collectively suggest that H. armigera (Hübner) larvae can be used to study the effect of microbes and their metabolites on the host physiology, anatomy, and survival.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.