High throughput proteomic analysis and a comparative review identify the nuclear chaperone, Nucleophosmin among the common set of proteins modulated in Chikungunya virus infection

Abstract

Global re-emergence of Chikungunya virus (CHIKV) has renewed the interest in its cellular pathogenesis. We subjected CHIKV-infected Human Embryo Kidney cells (HEK293), a widely used cell-based system for CHIKV infection studies, to a high throughput expression proteomics analysis by Liquid Chromatography-tandem mass spectrometry. A total of 1047 differentially expressed proteins were identified in infected cells, consistently in three biological replicates. Proteins involved in transcription, translation, apoptosis and stress response were the major ones among the 209 proteins that had significant up-regulation. In the set of 45 down-regulated proteins, those involved in carbohydrate and lipid metabolism predominated. A STRING network analysis revealed tight interaction of proteins within the apoptosis, stress response and protein synthesis pathways. We short-listed a common set of 30 proteins that can be implicated in cellular pathology of CHIKV infection by comparing our results and results of earlier CHIKV proteomics studies. Modulation of eight proteins selected from this set was re-confirmed at transcript level. One among them, Nucleophosmin, a nuclear chaperone, showed temporal modulation and cytoplasmic aggregation upon CHIKV infection in double immunofluorescence staining and confocal microscopy. The short-listed cellular proteins will be potential candidates for targeted study of the molecular interactions of CHIKV with host cells.

Biological significance: Chikungunya remained as a neglected tropical disease till its re-emergence in 2005 in the La RéUnion islands and subsequently, in India and many parts of South East Asia. These and the epidemics that followed in subsequent years ran an explosive course leading to extreme morbidity and attributed mortality to this originally benign virus infection. Apart from classical symptoms of acute fever and debilitating polyarthralgia lasting for several weeks, a number of complications were documented. These included aphthous-like ulcers and vesiculo-bullous eruptions on the skin, hepatic involvement, central nervous system complications such as encephalopathy and encephalitis, and transplacental transmission. The disease has recently spread to the Americas with its initial documentation in the Caribbean islands. The Asian genotype of this positive-stranded RNA virus of the Alphavirus genus has been attributed in these outbreaks. However, the disease ran a similar course as the one caused by the East, Central and South African (ECSA) genotype in the other parts of the world. Studies have documented a number of mutations in the re-emerging strains of the virus that enhances mosquito adaptability and modulates virus infectivity. This might support the occurrence of fiery outbreaks in the absence of herd immunity in affected population. Several research groups work to understand the pathogenesis of chikungunya and the mechanisms of complications using cellular and animal models. A few proteomics approaches have been employed earlier to understand the protein level changes in the infected cells. Our present study, which couples a high throughput proteomic analysis and a comparative review of these earlier studies, identifies a few critical molecules as hypothetical candidates that might be important in this infection and for future study.

Keywords: Chikungunya virus; Differential expression; LC–MS/MS; Shotgun proteomics.

Graphical abstract

Fig. 1

(a) Immunofluorescence images of CHIKV infection in HEK293 cells. Monolayer cultures of the cells were infected at MOI 1. At 48 h p.i., CHIKV infected and mock-infected cells were fixed using 4% paraformaldehyde and subjected to immunofluorescence analysis. The virus infection was detected using anti-CHIKV E2 envelope protein rabbit polyclonal serum at 1:50 dilution. Alexafluor 488 anti-rabbit IgG was used as the secondary antibody. A focus of infection in the infected cells indicated by the green cytoplasmic fluorescence is shown. (b) Hoechst staining of CHIKV infected HEK293 cells. Monolayer cultures of the cells were infected at MOI 1. Infected and mock-infected cells were stained at 24 h, 48 h, and 72 h p.i. with the nuclear staining dye Hoechst 33342 for 20 min at 37 °C in the dark before visualization. Images were captured with a LucaR (Andor) EMCCD camera using NIS elements software under identical exposure and gain settings for the infected cells as well as the controls. (c) Quantitative estimation of the condensed nuclei in infected HEK293 cells. Each value is an average of four fields from three independent experiments. (d) Quantification of apoptosis and necrosis in infected HEK 293 cells. Cells infected at MOI 1 and mock infected cells were collected at respective time points and stained with Annexin V-EnzoGold and Necrosis Detection Reagent as per manufacturer's directions and analyzed by flow cytometry (FACS Aria Special order system) at 585/42 and 695/40 band filters. Q1 represents the non-viable cells undergone necrosis, Q2 has cells from both late apoptosis and necrosis stages, Q3 the most viable healthy cells and Q4, cells from early apoptosis stage. Representative images of two independent experiments are shown.

Fig. 2

Number of proteins identified in proteomic analysis, sub-cellular localization and biological functions. (a) Number of proteins identified in proteomic analysis. The data from the three biological replicates were analyzed in Venny software and the results are shown. (b) Sub-cellular localization of up-regulated proteins (11 unique proteins in infected + 198 up-regulated = 209); (c) sub-cellular localization of down-regulated proteins (5 unique in control + 40 down-regulated = 45); (d) biological functions of up-regulated proteins; (e) biological functions of down-regulated proteins. Analysis was done using existing information from Swiss-Prot/TrEMBL database.

Fig. 3

Network interactions of differentially expressed proteins by STRING analysis at confidence level 0.4. A subset of the total proteins, which were identified by the software, were used in the analysis: (a) up-regulated proteins (184 out of 209 proteins) and (b) down-regulated proteins(40 out of 45 proteins).

Fig. 4

Network interactions of differentially expressed proteins under various biological functions by STRING analysis at confidence level 0.7. Proteins functionally categorized under each group based on existing information from Swiss-Prot/TrEMBL database were analyzed: (a) energy metabolism (53 proteins); (b) apoptosis, cell cycle and stress response (68 proteins); (c) cytoskeleton (23 proteins); (d) transcription and translation (61 proteins).

Fig. 5

Differential expression analyses of the transcripts of selected proteins by quantitative real-time RT-PCR. The fold-change of expression was calculated with respect to the expression levels in mock-infected controls at the respective time points, after normalizing the values with that of the house-keeping gene β-actin. Values from three independent experiments each done in triplicates are indicated for the different time points.

Fig. 6

NPMI expression in CHIKV infected cells. (a) Monolayer cultures of the cells were infected at different MOIs. At 24 and 48 h p.i., CHIKV infected and mock-infected cells were fixed using 4% paraformaldehyde and subjected to immunofluorescence analysis. The virus infection was detected using anti-CHIKV E2 envelope protein rabbit polyclonal serum at 1:50 dilution. Alexafluor 488 anti-rabbit IgG was used as the secondary antibody. For NPMI detection, the cells were again stained using 1:50 dilution of NPMI antibody and anti mouse Cy3 was used as the secondary antibody. Nuclei was counterstained with DAPI staining and visualized at 60 × objective through confocal microscopy.(b) Zoomed image of mock and CHIKV infected cells (zoom factor 2.5) showing the speckle formation of NPMI in infected cells.