Development and evaluation of indirect-ELISA based on recombinant nucleoprotein for detection of Ganjam virus (GANV) specific antibodies in small ruminants

Abstract Ganjam virus (GANV) is a tick-borne zoonotic arbovirus that has been reported in India. It is the Asian variant of Nairobi sheep disease virus (NSDV), which causes significant morbidity and mortality in small ruminants. Sero-surveillance for GANV-specific antibodies among animals is relevant for identifying risk maps and implementing control strategies. In this study, we describe the development and evaluation of a recombinant nucleoprotein (rNP) based indirect-ELISA for detecting GANV specific IgG antibodies in sheep and goat populations. A full-length NP gene encoding for recombinant NP protein (516 aa, 57 kDa) was cloned, over-expressed, and purified from Escherichia coli under denaturing conditions using affinity chromatography. The checker board titration method determined the optimum antigen concentration of 200 ng/well and a test serum dilution of 1:50 with an appropriate species-specific HRPO conjugate. Evaluation of the optimal cut-off criterion by receiver operating characteristic (ROC) and Precision-Recall analyses revealed an area under the curve (AUC) of 0.999 [95% confidence interval (CI) 0.964–1.000], positive predictive value of 1.000 and F1 score of 0.9691 against the cut off criterion of > 32 PP in sheep and goats. Repeatability of the assay revealed the intra-assay % CV of 4.61 and inter-assay % CV of 12.51, which are within the accepted criteria of 10% and 15%, respectively. In addition, the assay demonstrated a reliable detection limit of up to 1:400, with no cross-reactivity with sera specific to major sheep and goat diseases. Further, the diagnostic performance of the iELISA through Bayesian two-test analysis revealed a diagnostic sensitivity of 96% and diagnostic specificity of 93%. Furthermore, screening of randomly collected sheep ( n = 311) and goat ( n = 547) sera revealed a GANV specific sero-positivity of 20.58% and 31.08%, respectively, among the small ruminant population of Odisha state, India. In conclusion, the developed GANV-rNP-iELISA could be potentially used in the screening of a large number of small ruminants’ serum samples to better understand the potential risk to public health in the region.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-10-07
DOI
https://doi.org/10.1038/s41598-026-71680-2
Primary Topic
Viral Infections and Vectors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and evaluation of indirect-ELISA based on recombinant nucleoprotein for detection of Ganjam virus (GANV) specific antibodies in small ruminants

Divakar Hemadri, Sathish Bhadravati Shivachandra, Suresh Bindu, Roopa Anandamurthy Hemanth et al.
Scientific Reports
Viral Infections and Vectors
article

Development and evaluation of indirect-ELISA based on recombinant nucleoprotein for detection of Ganjam virus (GANV) specific antibodies in small ruminants

Divakar Hemadri, Sathish Bhadravati Shivachandra, Suresh Bindu, Roopa Anandamurthy Hemanth, Mandrira Ramakrishna Namrutha, Anand Shirisha, Pillenahalli Sadashivappa Pooja, Mohammed Mudassar Chanda
article en

Abstract

Abstract Ganjam virus (GANV) is a tick-borne zoonotic arbovirus that has been reported in India. It is the Asian variant of Nairobi sheep disease virus (NSDV), which causes significant morbidity and mortality in small ruminants. Sero-surveillance for GANV-specific antibodies among animals is relevant for identifying risk maps and implementing control strategies. In this study, we describe the development and evaluation of a recombinant nucleoprotein (rNP) based indirect-ELISA for detecting GANV specific IgG antibodies in sheep and goat populations. A full-length NP gene encoding for recombinant NP protein (516 aa, 57 kDa) was cloned, over-expressed, and purified from Escherichia coli under denaturing conditions using affinity chromatography. The checker board titration method determined the optimum antigen concentration of 200 ng/well and a test serum dilution of 1:50 with an appropriate species-specific HRPO conjugate. Evaluation of the optimal cut-off criterion by receiver operating characteristic (ROC) and Precision-Recall analyses revealed an area under the curve (AUC) of 0.999 [95% confidence interval (CI) 0.964–1.000], positive predictive value of 1.000 and F1 score of 0.9691 against the cut off criterion of > 32 PP in sheep and goats. Repeatability of the assay revealed the intra-assay % CV of 4.61 and inter-assay % CV of 12.51, which are within the accepted criteria of 10% and 15%, respectively. In addition, the assay demonstrated a reliable detection limit of up to 1:400, with no cross-reactivity with sera specific to major sheep and goat diseases. Further, the diagnostic performance of the iELISA through Bayesian two-test analysis revealed a diagnostic sensitivity of 96% and diagnostic specificity of 93%. Furthermore, screening of randomly collected sheep ( n = 311) and goat ( n = 547) sera revealed a GANV specific sero-positivity of 20.58% and 31.08%, respectively, among the small ruminant population of Odisha state, India. In conclusion, the developed GANV-rNP-iELISA could be potentially used in the screening of a large number of small ruminants’ serum samples to better understand the potential risk to public health in the region.

Scientific Reports
Indian Council of Agricultural Research (IN), National Institute Of Veterinary Epidemiology And Disease Informatics (IN)
Openalex Percentile: Top 11%
Viral Infections and Vectors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.