Chemonges, Saul

Kopp, Steven

Mills, Paul

Sadowski, Pawel

University of Queensland eSpace

Sheep proteogenomics 
Advancing veterinary clinical pathology & diagnostics 
.  
Saul Chemoges1,2, Paul Mills1, Steven Kopp1 and Pawel Sadowski2 
   
1 School of Veterinary Science, The University of Queensland 
2 Central Analytical Research Facility, Queensland University of Technology 
Correspondence: saul.chemonges@qut.edu.au 
FURTHER WORK 
We are currently generating calibration curve data with and without 
sheep serum background to verify that the selected transitions can be 
used for quantitation of selected putative biomarkers in the biological 
samples.  
Figure 1. Skyline software (MacCoss Lab) is the heart of our peptide SID-MRM-MS workflow. The 
workflow  starts with collecting peptide ion fragmentation spectra on AB Sciex 5600+ instrument. 
Spectra are then annotated with amino acid sequences using Mascot search engine (Matrix 
Science) and imported into Skyline as spectral libraries. Based on these libraries, Skyline helps us to 
choose the optimal combination of peptide ions and fragment ions (transitions) used for 
quantification of proteins of interest. Skyline then exports a method file for Shimadzu LCMS-8050 
instrument, predicting optimal fragmentation energies (CEs). After initial data has been acquired 
using LCMS-8050, Skyline can read it and perform automatic peak integration and identity 
verification. Finally, a list of peptides is exported for evaluation. 
Figure 2. Skyline software considerably simplifies the development of peptide SID-MRM-MS 
assays using Shimadzu instrument available at QUT-CARF. The left panel shows a list of target 
peptides in a Skyline window. The upper right panel shows library spectrum generated using 
the 5600+ instrument for the highlighted heavy-labeled synthetic peptide. The lower right 
panel shows an MRM chromatogram for 3 transitions monitored using LCMS-8050 instrument for 
the same peptide. 
.  
 
 
PRELIMINARY RESULTS 
Using Skyline, we predicted 2 best peptides to be monitored for 5 
cytokines (putative inflammation biomarkers) using SID-MRM-MS 
assay. We then synthesized 10 selected peptides in their unlabeled 
and stable isotope-labeled version. Finally, for each peptide we 
selected 3 MRM transitions (60 transitions in total) for which we 
optimized liquid chromatography and mass spectrometry 
conditions with the support from Skyline. 
INTRODUCTION 
Proteogenomics tools available for veterinary applications are 
comparatively lagging behind those for humans. Alternatives to 
expensive and low throughput ELISA assays are urgently needed 
for diagnosis and monitoring of animal diseases. Proteogenomics 
technologies provide a promising option but they remain 
underutilised in veterinary science due to a lack of complete 
genome sequencing data and relevant expertise. Here, we 
present a proof of concept work on the development of a mass 
spectrometry-based assay aiming to explain a differential response 
to a simulated disease challenge in sheep. Our work could be 
beneficial to the veterinary industry and in the long term, it might 
benefit animal welfare and production.  
STRATEGY 
Our earlier work has shown that despite having similar breed 
characteristics, sheep that we were taking care of at QUT Medical 
Engineering Research Facility (QUT-MERF) responded differently to 
Escherichia coli endotoxin challenge. We hypothesised that serum 
proteogenomic biomarker change patterns contribute in defining 
and predicting sheep response to endotoxin. We are developing a 
stable isotope dilution(SID) multiple reaction monitoring (MRM)-
based assay to monitor the levels of 5 cytokines in  serum collected 
from healthy and endotoxin-treated animals on two instrument 
platforms available at CARF (AB Sciex 5600+ and Shimadzu LCMS-
8050). In this initial stage, we have tested the recently implemented 
compatibility of Skyline software platform with Shimadzu instrument. 
 
 
Saul is  a veterinarian and PhD candidate at The 
University of Queensland. His  interests include 
large animals used as models of intensive care. 
Collaborative research with QUT is driven by the 
state-of-the-art instrumentation and expertise in 
the field of proteomics at CARF. 
Input: Mascot search 
results from AB Sciex 
5600+ 
Selection of target peptides 
Output: Spectral library 
Data acquisition Data analysis 
Output: 
Comprehensive results 
report 
Output: Method file for 
Shimadzu LCMS-8050 (CE 
prediction) 
Input: List of target 
peptides/MRM transitions 
Input: LCMS-8050 data file 
Output: Automatic peak 
integration and verification (RT 
prediction, dot-product score) 
List of final peptides for 
evaluation 
Input: Integrated 
peaks, report 
parameters 


Sheep proteogenomics: advancing veterinary clinical pathology and diagnostics

http://espace.library.uq.edu.au/view/UQ:347314/B3_symposium_poster_QUT.pdf

Sheep proteogenomics: advancing veterinary clinical pathology and diagnostics

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