Design and structural bioinformatic analysis of polypeptide antigens useful for the SRLV serodiagnosis

https://doi.org/10.1016/j.jviromet.2021.114266Get rights and content

Highlights

Abstract

Due to their intrinsic genetic, structural and phenotypic variability the Lentiviruses, and specifically small ruminant lentiviruses (SRLV), are considered viral quasispecies with a population structure that consists of extremely large numbers of variant genomes, termed mutant spectra or mutant cloud. Immunoenzymatic tests for SRLVs are available but the dynamic heterogeneity of the virus makes the development of a diagnostic “golden standard" extremely difficult. The ELISA reported in the literature have been obtained using proteins derived from a single strain or they are multi-strain based assay that may increase the sensitivity of the serological diagnosis. Hundreds of SRLV protein sequences derived from different viral strains are deposited in GenBank. The aim of this study is to verify if the database can be exploited with the help of bioinformatics in order to have a more systematic approach in the design of a set of representative protein antigens useful in the SRLV serodiagnosis. Clustering, molecular modelling, molecular dynamics, epitope predictions and aggregative/solubility predictions were the main bioinformatic tools used. This approach led to the design of SRLV antigenic proteins that were expressed by recombinant DNA technology using synthetic genes, analyzed by CD spectroscopy, tested by ELISA and preliminarily compared to currently commercially available detection kits.

Introduction

Infections by ovine and caprine lentiviruses, referred to as small ruminant lentiviruses (SRLV), cause slow-progressive, persistent and debilitating diseases that can lead to the death of the animal due to the failure of many organs. Herd productivity and international animal trade are also adversely affected. Two genetically, structurally and antigenically related viruses, members of the genus Lentivirus of the family Retroviridae, are in the SRLV group: Maedi Visna Virus (MVV) and Caprine Arthritis Encephalitis virus (CAEV) (Minguijón et al., 2015; Ramírez et al., 2013). In the past, sheep and goat lentivirus infections have been considered species-specific, with the MVV infecting the sheep and CAEV infecting the goats. More recently, sequence analyses and phylogenetic studies have concluded that the two apparently different viruses are part of a genetic continuum of lentiviral species (Leroux et al., 2010) and cross-species transmission has been demonstrated (Shah et al., 2004a,b; Minardi da Cruz et al., 2013; Fras et al., 2013).

SRLV have been classified in 5 genotypes or clades with 28 reported subtypes (Michiels et al., 2020; Molaee et al., 2020). Genotype A (subtypes A1-A22) corresponds to the original MMV, whereas genotype B (subtypes B1-B5) corresponds to the original CAEV; these two genotypes are widely distributed and comprise most of the subtypes. In addition, geographically restricted genotypes C, D and E have been reported (Reina et al., 2010; Shah et al., 2004a; Gjerset et al., 2006; Grego et al., 2007).

Diagnosis of SRLV infections can be made clinically, though only a small proportion of animals develop clinical signs. Serology represents a reliable and cost-effective method of diagnosing persistently SRLV infected animals (OIE, 2021, https://www.oie.int/fileadmin/Home/eng/Health_standards/tahm/2.07.02-03_CAE_MV.pdf/). In the past decades a number of methodologies have been developed for this purpose. These include the agar gel immunodiffusion (AGID), enzyme-linked immunosorbent assay (ELISA), radioimmunoprecipitation (RIPA), radioimmunoassay (RIA), and western blotting (WB) (de Andrés et al., 2005). Since no “gold standard’’ method of diagnosis exists, it is quite usual that estimates of performance of a certain test, in particular sensitivity and specificity, are made relative to some other measure. The quality of the SRLV serological diagnosis generally depends on several factors: the format of the assay, the sequences and structural homologies between the strain of virus used in the assay and the strains of virus present in the testing populations, and the viral antigen used in the assay (OIE). Regarding the ELISA both indirect and competitive ELISA format have been developed and mainly three different recombinant protein antigens have been selected and used: the capsid protein p25 (CA), the transmembrane protein gp46 (TM), and the gp135 envelope protein. Synthetic peptides derived from p25 or TM as well whole virus antigens have also been used (OIE). The combination of the CA and TM antigens has shown to be quite effective in indirect ELISA and has been used in certain tests (Brinkhof et van Maanen, 2007; Saman et al., 1999).

However, due to the “quasispecies” nature of these viruses the high structural and immunogenic variability of SRLV represents an important limitation in the use of the ELISA. In fact, as stated above, the homology between the strain of virus used in the assay and the strains of virus present in the testing populations should always be taken into account. The ELISA reported in the literature have been obtained using proteins derived from a single strain in certain cases (Saman et al., 1999; Konishi et al., 2010); in another case it has been reported that a double-strain-based immunoassay may increase the sensitivity of serological diagnosis of SRLV infections (Grego et al., 2002).

Certain commercial kits use proteins derived from more than one strain apparently chosen on empirical bases since they represent the main genotypes but no detailed information is available, to the best of our knowledge. On the other hand, hundreds of SRLV protein sequences derived from different viral strains are deposited in GenBank. The scope of this investigation is to verify if the database can be exploited with the help of bioinformatics in order to have a more systematic approach in the design of a set of representative protein antigens useful in the SRLV serodiagnosis, since our ultimate goal is the development of an efficient and highly cost effective in-house indirect ELISA test. The main bioinformatic tools used in this investigation were: protein clustering, molecular modelling, molecular dynamics, epitope predictions and aggregative/solubility predictions. The conclusions from these analyses led to the design of SRLV antigenic proteins that were expressed recombinantly, analyzed by CD spectroscopy, tested by ELISA and preliminarily compared to currently commercially available detection kits.

Section snippets

Sequence clustering analysis

The proteins investigated were the p25 capsid protein and the gp46 transmembrane (TM) protein that were chosen as suitable according to literature data (Saman et al., 1999). The exodomain of the TM protein was identified by using the program TMpred (Hofmann and Stoffel, 1993). Cd-Hit, a sequence-based clustering software (Huang et al., 2010), was used to analyze the protein sequences retrieved with BlastP from the Non-Redundant database.

Clustering can help to organize protein sequences into

Clustering analysis of the variable protein sequences of the SRLV P25 and TM proteins

Blastp retrieved 967 and 458 sequences for the SRLV P25 protein and for the 115-residue-polypeptide fragment of the SRLV TM (gp46) protein (sequence 680–794 envelope glycoprotein strain CAEV-cork accession P31626.1), respectively. In the Blastp analysis the lowest sequence identity was 70.7 % with respect to the query sequence (KV1772 strain) in the case of P25 and 67.8 % with respect to the query sequence (EV1 strain) in the case of the TM peptide. The 115-residue polypeptide represents the

Discussion and conclusions

RNA viruses generally exhibit heterogeneous and complex populations with similar but nonidentical genomes, since they evolve rapidly mainly due to the large population size, the high replication rate, the defective proofreading ability of their RNA-dependent RNA polymerase or their RNA-dependent DNA polymerase (Reverse Transcriptase) in the case of the retroviruses. The intrinsic genetic, structural and phenotypic variability of the Lentiviruses and specifically SRLV, has led numerous authors

Author contributions

Angela Ostuni: Investigation, Visualization, Writing - review & editing; Magnus Monné: Investigation, Writing - original draft,Visualization; Maria Antonietta Crudele: Data curation, Formal analysis; Pierluigi Cristinziano: Investigation; Stefano Cecchini: Investigation, Resources; Mario Amati: Investigation; Jolanda De Vendel: Investigation; Paolo Raimondi: Resources; Taxiarchis Chassalevris: Investigation; Chrysostomos I Dovas: Investigation; Alfonso Bavoso: Conceptualization, Project

Declaration of Competing Interest

The authors report no declarations of interest.

Acknowledgments

This Investigation was partially funded by Basilicata Innovazione project. Thanks are due to Dr. Carmine Del Galdo for providing serum samples from Campania region.

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