Differential Proteome Analysis of Chikungunya Virus and Dengue Virus Coinfection in Aedes Mosquitoes

Alteration of mitochondrial function in arthropods during arboviruses infection: a review of the literature

Arthropods serve as vectors for numerous arboviruses responsible for diseases worldwide. Despite their medical, veterinary, and economic significance, the interaction between arboviruses and arthropods remains poorly understood. Mitochondria in arthropods play a crucial role by supplying energy for cell survival and viral replication. Some arboviruses can replicate within arthropod vectors without harming the host. Successful transmission depends on efficient viral replication in the vector's tissues, ultimately reaching the salivary glands for transmission to a vertebrate host, including humans, via blood-feeding. This review summarizes current knowledge of mitochondrial function in arthropods during arbovirus infection, highlighting gaps compared to studies in mammals and other pathogens relevant to arthropods. It emphasizes mitochondrial processes in insects that require further investigation to uncover the mechanisms underlying arthropod-borne transmission.

Proteomic investigations of dengue virus infection: key discoveries over the last 10 years

INTRODUCTION

Dengue virus (DENV) infection remains one of the most significant infectious diseases in humans. Several efforts have been made to address its molecular mechanisms. Over the last 10 years, proteomics has been widely applied to investigate various aspects of DENV infection.

AREAS COVERED

In this review, we briefly introduce common proteomics approaches using various mass spectrometric modalities followed by summarizing all the discoveries obtained from proteomic investigations of DENV infection over the last 10 years. These include the data on DENV-vector interactions and host responses to address the DENV biology and disease mechanisms. Moreover, applications of proteomics to disease prevention, diagnosis, vaccine design, development of anti-DENV agents and other new treatment strategies are discussed.

EXPERT OPINION

Despite efforts on disease prevention, DENV infection is still a significant global healthcare burden that affects the general population. As summarized herein, proteomic technologies with high-throughput capabilities have provided more in-depth details of protein dynamics during DENV infection. More extensive applications of proteomics and other powerful research tools would provide a promise to better cope and prevent this mosquito-borne infectious disease.

Controlling arbovirus infection: high-throughput transcriptome and proteome insights

Arboviruses pose a significant threat to public health globally, demanding innovative approaches for their control. For this, a better understanding of the complex web of interactions established in arbovirus-infected mosquitoes is fundamental. High-throughput analyses allow a genome-wide view of arbovirus-induced alterations at different gene expression levels. This review provides a comprehensive perspective into the current literature in transcriptome and proteome landscapes in mosquitoes infected with arboviruses. It also proposes a coordinated research effort to define the critical nodes that determine arbovirus infection and transmission.

Coinfection with PEDV and BVDV induces inflammatory bowel disease pathway highly enriched in PK-15 cells

Background

From the 1078 diarrhea stools tested in our survey from 2017 to 2020 in local area of China, PEDV was the key pathogen that was closely related to the death of piglets with diarrhea. In addition, coinfection of PEDV-positive samples with BVDV reached 17.24%. Although BVDV infection in swine is typically subclinical, the effect of PEDV and BVDV coinfection on disease severity and the potential molecular mechanism of coinfection with these two viruses remain unknown.

Methods

In this study, we developed a model of coinfection with porcine epidemic diarrhea virus (PEDV) and bovine viral diarrhea virus (BVDV) in PK15 cells, and a tandem mass tag (TMT) combined with LC–MS/MS proteomic approach was used to identify differential protein expression profiles. Additionally, we performed drug experiments to explore the inflammatory response induced by PEDV or BVDV mono- or coinfection.

Results

A total of 1094, 1538, and 1482 differentially expressed proteins (DEPs) were identified upon PEDV monoinfection, BVDV monoinfection and PEDV/BVDV coinfection, respectively. KEGG pathway analysis revealed that PEDV and BVDV coinfection led to a highly significantly enrichment of the inflammatory bowel disease (IBD) pathway. In addition, the NF-κB signaling pathway was more intensively activated by PEDV and BVDV coinfection, which induced higher production of inflammatory cytokines, than PEDV or BVDV monoinfection.

Conclusions

Our study indicated that cattle pathogens might play synergistic roles in the pathogenesis of porcine diarrhea, which might also improve our understanding of the pathogenesis of multiple infections in diarrhea.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01845-8.

Aedes aegypti Aag-2 Cell Proteome Modulation in Response to Chikungunya Virus Infection

Chikungunya virus (CHIKV) is a single-stranded positive RNA virus that belongs to the genus Alphavirus and is transmitted to humans by infected Aedes aegypti and Aedes albopictus bites. In humans, CHIKV usually causes painful symptoms during acute and chronic stages of infection. Conversely, virus–vector interaction does not disturb the mosquito’s fitness, allowing a persistent infection. Herein, we studied CHIKV infection of Ae. aegypti Aag-2 cells (multiplicity of infection (MOI) of 0.1) for 48 h through label-free quantitative proteomic analysis and transmission electron microscopy (TEM). TEM images showed a high load of intracellular viral cargo at 48 h postinfection (hpi), as well as an unusual elongated mitochondria morphology that might indicate a mitochondrial imbalance. Proteome analysis revealed 196 regulated protein groups upon infection, which are related to protein synthesis, energy metabolism, signaling pathways, and apoptosis. These Aag-2 proteins regulated during CHIKV infection might have roles in antiviral and/or proviral mechanisms and the balance between viral propagation and the survival of host cells, possibly leading to the persistent infection.

Computational analysis of human host binding partners of chikungunya and dengue viruses during coinfection

Mosquito-borne viral diseases like chikungunya and dengue infections can cause severe illness and have become major public health concerns. Chikungunya virus (CHIKV) and dengue virus (DENV) infections share similar primary clinical manifestations and are transmitted by the same vector. Thus, the probability of their coinfection gets increased with more severe clinical complications in the patients. The present study was undertaken to elucidate the common human interacting partners of CHIKV and DENV proteins during coinfection. The viral-host protein-protein interactome was constructed using Cytoscape. Subsequently, significant host interactors were identified during coinfection. The network analysis elucidated 57 human proteins interacting with both CHIKV and DENV, represented as hub-bottlenecks. The functional and biological analyses of the 40 hub-bottlenecks revealed that they are associated with phosphoinositide 3-kinases (PI3K)/AKT, p53 signaling pathways, regulation of cell cycle and apoptosis during coinfection. Moreover, the molecular docking analysis uncovered the tight and robust binding of selected hub-bottlenecks with CHIKV/DENV proteins. Additionally, 23 hub-bottlenecks were predicted as druggable candidates that could be targeted to eradicate the host-viral interactions. The elucidated common host binding partners during DENV and CHIKV coinfection as well as indicated approved drugs can support the therapeutics development.

The anti-rotavirus effect of baicalin via the gluconeogenesis-related p-JNK-PDK1-AKT-SIK2 signaling pathway

Rotavirus (RV) infection is a leading cause of severe, dehydrating gastroenteritis in children < 5 years of age, and by now, the prevention and treatment of RV are still the major public health problems due to a lack of specific clinical drugs. Thus, the aims of this study are to explore the anti-RV effect of baicalin and its influence on glucose metabolism. Here, we demonstrated for the first time that baicalin had an anti-RV attachment effect with the strongest effect at a concentration of 100 μM, and also inhibited the replication of RV at concentrations of 100, 125, 150, 175, and 200 μM. Moreover, baicalin helped to overcome the weight loss and reduced the diarrhea rate and score with the best therapeutic effect at a concentration of 0.3 mg/g in RV-infected neonatal mice. Interestingly, baicalin decreased glucose consumption in RV-infected Caco-2 cells with the optimal concentration of 125 μM. Next, metabolomic analysis indicated that there were 68 differentially expressed metabolites, including an increase in pyruvic acid, asparagine, histidine and serine, and a decrease in dihydroxyacetone phosphate, which suggested that the underlying signaling pathway was gluconeogenesis. Further studies demonstrated that baicalin inhibited gluconeogenesis via improving glucose 6-phosphatase (G-6-Pase) and phosphoenolpyruvate carboxylase (PEPCK). Moreover, baicalin upregulated the potential gluconeogenesis proteins named salt inducible kinase 2, pyruvate dehydrogenase kinase 1, AKT serine/threonine kinase 1 and down-regulated phosphorylated c-Jun NH2-terminal kinase, which are associated with G-6-Pase and PEPCK expressions. Therefore, baicalin improved the gluconeogenesis disruption caused by RV.

Differential genotypic signatures of Toll-like receptor polymorphisms among dengue-chikungunya mono- and co-infected Eastern Indian patients

Dengue (DENV) and chikungunya (CHIKV) viral infections trigger high patient morbidity and mortality. Mono-/co-infection of these viruses activates innate immune response, triggering Toll-like receptor (TLR) pathways. The present study investigated the differential role of TLR3, 7 and 8 single-nucleotide polymorphisms (SNPs) between mono- and co-infected Eastern Indian patients. Interaction of TLR polymorphic variants with signal peptidase complex (SPC18) was explored which might affect immune signalling against DENV/CHIKV infections. Out of 550 febrile symptomatic patients, 128 DENV-CHIKV co-infected samples were genotyped for eight SNPs of TLR3 (rs3775290-chr4:186083063), TLR7 (rs179008-chrX:12885540, rs5741880-chrX:12869297, rs179010-chrX:12884766, rs3853839-chrX:12889539) and TLR8 (rs5744080-chrX:12919685, rs3764879-chrX:12906578, rs3764880-chrX:12906707) by PCR-RFLP along with 157 healthy individuals. Statistical analysis established genotypic association of TLR SNPs with DENV-CHIKV co-infection, and difference between mono- and co-infected patients and their role in determining high viral load (HVL) during competitive viral replication among co-infected patients. In silico protein-protein docking evaluated interactive effect of TLR variants with SPC18. The findings revealed patients with CC genotypes of TLR7 and 8 SNPs were significantly susceptible towards co-infection, whereas specific genotypes of TLR7 and 8 imparted protection against co-infection. Differential analysis between mono-/co-infected patients revealed distinct genotypic distribution of TLR3, 7 and 8 SNPs. Co-infected patients with TT-rs179010 exhibited DENV-HVL, whereas CHIKV-HVL was detected among patients with other genotypes. Molecular docking of TLR7-rs179008 Q variant and TLR8-rs3764880 V variant with SPC18 generated better free binding energy. This study underlined the importance of TLR7 and 8 SNPs towards mono-/co-infection of DENV/CHIKV, with certain genotypes associated with co-infection susceptibility. Moreover, it suggested a probable role of specific genotypes of TLR7 and 8 polymorphisms imparting high dengue/chikungunya viral load among co-infected patients.

Update on Proteomic approaches to uncovering virus-induced protein alterations and virus -host protein interactions during the progression of viral infection

INTRODUCTION

Viruses induce profound changes in the cells they infect. Understanding these perturbations will assist in designing better therapeutics to combat viral infection. System-based proteomic assays now provide unprecedented opportunity to monitor large numbers of cellular proteins.

AREAS COVERED

This review will describe various quantitative and functional mass spectrometry-based methods, and complementary non-mass spectrometry-based methods, such as aptamer profiling and proximity extension assays, and examples of how each are used to delineate how viruses affect host cells, identify which viral proteins interact with which cellular proteins, and how these change during the course of a viral infection. PubMed was searched multiple times prior to manuscript submissions and revisions, using virus, viral, proteomics; in combination with each keyword. The most recent examples of published works from each search were then analyzed.

EXPERT OPINION

There has been exponential growth in numbers and types of proteomic analyses in recent years. Continued development of reagents that allow increased multiplexing and deeper proteomic probing of the cell, at quantitative and functional levels, enhancements that target more important protein modifications, and improved bioinformatics software tools and pathway prediction algorithms will accelerate this growth and usher in a new era of host proteome understanding.

MASS SPECTROMETRY IN VIROLOGICAL SCIENCES

Virology, as a branch of the life sciences, discovered mass spectrometry (MS) to be the pivotal tool around two decades ago. The technique unveiled the complex network of interactions between the living world of pro- and eukaryotes and viruses, which delivered "a piece of bad news wrapped in protein" as defined by Peter Medawar, Nobel Prize Laureate, in 1960. However, MS is constantly evolving, and novel approaches allow for a better understanding of interactions in this micro- and nanoworld. Currently, we can investigate the interplay between the virus and the cell by analyzing proteomes, interactomes, virus-cell interactions, and search for the compounds that build viral structures. In addition, by using MS, it is possible to look at the cell from the broader perspective and determine the role of viral infection on the scale of the organism, for example, monitoring the crosstalk between infected tissues and the immune system. In such a way, MS became one of the major tools for the modern virology, allowing us to see the infection in the context of the whole cell or the organism. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Quantitative Proteomic Analysis of Chikungunya Virus-Infected Aedes aegypti Reveals Proteome Modulations Indicative of Persistent Infection

The mosquito-borne chikungunya virus (CHIKV) poses a threat to human health in tropical countries throughout the world. The molecular interactions of CHIKV with its mosquito vector Aedes aegypti are not fully understood. Following oral acquisition of CHIKV via salinemeals, we analyzed changes in the proteome of Ae. aegypti in 12 h intervals by label-free quantification using a timsTOF Pro mass spectrometer. For each of the seven time points, between 2647 and 3167 proteins were identified among CHIKV-infected and noninfected mosquito samples, and fewer than 6% of those identified proteins were affected by the virus. Functional enrichment analysis revealed that the three pathways, Endocytosis, Oxidative phosphorylation, and Ribosome biogenesis, were enriched during CHIKV infection. On the other hand, three pathways of the cellular RNA machinery and five metabolism related pathways were significantly attenuated in the CHIKV-infected samples. Furthermore, proteins associated with cytoskeleton and vesicular transport, as well as various serine-type endopeptidases and metallo-proteinases, were modulated in the presence of CHIKV. Our study reveals biological pathways and novel proteins interacting with CHIKV in the mosquito. Overall, CHIKV infection caused minor changes to the mosquito proteome demonstrating a high level of adaption between the vector and the virus, essentially coexisting in a nonpathogenic relationship. The mass spectrometry data have been deposited to the MassIVE repository (https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=abfd14f7015243c69854731998d55df1) with the data set identifier MSV000085115.

Pathogen blocking in Wolbachia-infected Aedes aegypti is not affected by Zika and dengue virus co-infection

Background

Wolbachia’s ability to restrict arbovirus transmission makes it a promising tool to combat mosquito-transmitted diseases. Wolbachia-infected Aedes aegypti are currently being released in locations such as Brazil, which regularly experience concurrent outbreaks of different arboviruses. A. aegypti can become co-infected with, and transmit multiple arboviruses with one bite, which can complicate patient diagnosis and treatment.

Methodology/principle findings

Using experimental oral infection of A. aegypti and then RT-qPCR, we examined ZIKV/DENV-1 and ZIKV/DENV-3 co-infection in Wolbachia-infected A. aegypti and observed that Wolbachia-infected mosquitoes experienced lower prevalence of infection and viral load than wildtype mosquitoes, even with an extra infecting virus. Critically, ZIKV/DENV co-infection had no significant impact on Wolbachia’s ability to reduce viral transmission. Wolbachia infection also strongly altered expression levels of key immune genes Defensin C and Transferrin 1, in a virus-dependent manner.

Conclusions/significance

Our results suggest that pathogen interference in Wolbachia-infected A. aegypti is not adversely affected by ZIKV/DENV co-infection, which suggests that Wolbachia-infected A. aegypti will likely prove suitable for controlling mosquito-borne diseases in environments with complex patterns of arbovirus transmission.

Wolbachia is an endosymbiotic bacterium that infects insects. It has been artificially transferred into Aedes aegypti, a mosquito species that can transmit medically important viruses including dengue, chikungunya, and Zika. Wolbachia in A. aegypti limits infection with these viruses, making the mosquitoes much less capable of transmitting them to people. In tropical areas, where these viral pathogens are commonly found, it is not unusual for outbreaks of different viruses to occur at the same time, which can complicate diagnosis and treatment for those afflicted. Mosquitoes with Wolbachia are currently being released into these areas to reduce transmission of these diseases. In our study, we assessed whether Wolbachia infection in A. aegypti mosquitoes could still effectively inhibit the dengue and Zika viruses if the mosquitoes were fed both viruses at the same time. We found that Wolbachia was still very effective at inhibiting the replication of both viruses in the mosquito, and likewise still greatly reduced the chance of transmission of either virus. Our results suggest that Wolbachia-infected mosquitoes should be able to limit infection with more than one virus, should they encounter them in the field.

Mapping Arbovirus-Vector Interactions Using Systems Biology Techniques

Studying how arthropod-borne viruses interact with their arthropod vectors is critical to understanding how these viruses replicate and are transmitted. Until recently, these types of studies were limited in scale because of the lack of classical tools available to study virus-host interaction for non-model viruses and non-model organisms. Advances in systems biology "-omics"-based techniques such as next-generation sequencing (NGS) and mass spectrometry can rapidly provide an unbiased view of arbovirus-vector interaction landscapes. In this mini-review, we discuss how arbovirus-vector interaction studies have been advanced by systems biology. We review studies of arbovirus-vector interactions that occur at multiple time and length scales, including intracellular interactions, interactions at the level of the organism, viral and vector populations, and how new techniques can integrate systems-level data across these different scales.