Accurate Diagnostics for Bovine tuberculosis Based on High-Throughput Sequencing

Alexander Churbanov,Brook Milligan

doi:10.1371/journal.pone.0050147

Alexander Churbanov, Brook Milligan

Open Access

https://doi.org/10.1371/journal.pone.0050147

Copy DOI

Abstract

BackgroundBovine tuberculosis (bTB) is an enduring contagious disease of cattle that has caused substantial losses to the global livestock industry. Despite large-scale eradication efforts, bTB continues to persist. Current bTB tests rely on the measurement of immune responses in vivo (skin tests), and in vitro (bovine interferon-γ release assay). Recent developments are characterized by interrogating the expression of an increasing number of genes that participate in the immune response. Currently used assays have the disadvantages of limited sensitivity and specificity, which may lead to incomplete eradication of bTB. Moreover, bTB that reemerges from wild disease reservoirs requires early and reliable diagnostics to prevent further spread. In this work, we use high-throughput sequencing of the peripheral blood mononuclear cells (PBMCs) transcriptome to identify an extensive panel of genes that participate in the immune response. We also investigate the possibility of developing a reliable bTB classification framework based on RNA-Seq reads.Methodology/Principal FindingsPooled PBMC mRNA samples from unaffected calves as well as from those with disease progression of 1 and 2 months were sequenced using the Illumina Genome Analyzer II. More than 90 million reads were splice-aligned against the reference genome, and deposited to the database for further expression analysis and visualization. Using this database, we identified 2,312 genes that were differentially expressed in response to bTB infection (p<10−8). We achieved a bTB infected status classification accuracy of more than 99% with split-sample validation on newly designed and learned mixtures of expression profiles.Conclusions/SignificanceWe demonstrated that bTB can be accurately diagnosed at the early stages of disease progression based on RNA-Seq high-throughput sequencing. The inclusion of multiple genes in the diagnostic panel, combined with the superior sensitivity and broader dynamic range of RNA-Seq, has the potential to improve the accuracy of bTB diagnostics. The computational pipeline used for the project is available from http://code.google.com/p/bovine-tb-prediction.

Highlights

Bovine tuberculosis is an insidious, progressive disease of livestock that has cost the United States livestock industry millions of dollars in losses prior to and since the establishment of a national eradication campaign in 1917 [1]
We explore the possibility of using next-generation sequencing from peripheral blood mononuclear cells (PBMCs) mRNA for the purpose of diagnosing Bovine tuberculosis (bTB)
As mentioned in the section ssec:classification results, our experiments demonstrated that reliable classification could be achieved with 100 or more reads that map against informative loci

Summary

Introduction

Bovine tuberculosis (bTB) is an insidious, progressive disease of livestock that has cost the United States livestock industry millions of dollars in losses prior to and since the establishment of a national eradication campaign in 1917 [1]. Despite this large-scale eradication effort, bTB is a reemerging infectious disease in the U.S It is endemic in select areas of Michigan and recent outbreaks have occurred in Minnesota, California, and New Mexico. Current diagnostic tests are primarily based on immune responses to crude protein extracts from M. bovis (PPDb) injected intradermally. We investigate the possibility of developing a reliable bTB classification framework based on RNA-Seq reads

Methods

Results

Conclusion