1. The discovery and validation of kidney injury-related
protein biomarkers associated with antiretroviral treatment
in South Africa using mass spectrometry
Ireshyn Govendera, b, Stoyan Stoycheva, Demetra Mavri-Damelinb, Neil Martinsonc, Dalu Mancamaa
 a Council for Scientific and Industrial Research, Pretoria
b University of the Witwatersrand, Johannesburg
c Perinatal HIV Research Unit, Baragwanath Hospital and University of the Witwatersrand, Johannesburg -
Objective: To discover and validate putative protein biomarkers associated with renal impairment in HIV positive patients undergoing first-line antiretroviral therapy (ART).
Background:
The South African HIV/AIDS population accounts for approximately 10% of the global HIV/AIDS burden. ART is currently made freely available to more than than 90% of patients in South Africa. The vast majority of patients benefit greatly from ART treatment; however, ART is known to cause significant side effects in others. The side effect of particular interest in this study is kidney dysfunction. Current gold-standard clinical tests for kidney dysfunction/failure centre on changes in urinary creatinine levels which occur after significant kidney damage.
Urine has emerged as an attractive source for novel biomarker discovery due to the relative ease with which it can be obtained. Even though it is readily available, the protein concentration and complexity spans a range of approximately 10 orders of magnitude thus making it difficult to analyse. The majority of these are of high-molecular weight and are highly abundant (~98%) proteins [1]. Careful sample processing and data mining strategies need to be employed to ensure that the deepest proteome coverage is attained. This is essential in the pursuit of novel protein biomarkers as these are often expressed in minute quantities and are often undersampled due to the presence of abundant proteins.
Methodology:
Urinary proteins were isolated using the Norgen Biotek Urine Protein Concentration, Preservation and Isolation Kit according to the manufacturer’s instructions. Proteins were reduced (10 mM DTT, 37°C, 30 min), alkylated (30 mM IAA, RT-Dark, 30 min) and digested using sequencing grade trypsin (1:20 trypsin:protein,
37 °C, 16 hr).
Peptides were analysed by micro-RP-LCMSMS using a Dionex Ultimate 3500 UPLC system coupled to an AB Sciex TripleTOF® 6600 mass spectrometer in Data Dependent Acquisition (DDA) mode. A pre-concentration set-up was used where peptides were first desalted on a C18 trap column and subsequently eluted for MS analysis using a flow rate of 8 L/min with a 60-minute, 5-25% ACN, gradient via a C18 separation column. Protein identification was performed using Pilot 5.0 (AB Sciex) with a protein false discovery rate (FDR) set at 1%.
Figure 2: Transportation of Tenofovir in a proximal tubule kidney cell [2]. Normal transportation (a) and tenofovir retention (b).
Discussion:
Thorough method development in proteomics studies is essential to acquire high quality and reproducible data. The method for urinary protein biomarker discovery described here has been fully developed to attain high reproducibility and high quality data with little or no technical variability between replicates. Using this method we have been able to identify known biomarkers of urinary impairment such as cystatin c, β2-microglobulin and retinol binding protein from preliminary sample runs. Identification of these biomarkers show that the method has the potential to identify novel biomarkers in the patient cohort.
Future work:
SWATH-MS optimisation, processing and data analysis workflows need to be completed. Thereafter the entire workflow will be complete and patient samples can be run and analysed accordingly.
Acknowledgments:
We would like to thank the members of the PHRU (Klerksdorp) for patient recruiting, sample collection, patient data collection and management.
References:
1. Millioni, R. et al. (2011). "High abundance proteins depletion vs low abundance proteins enrichment: comparison of methods to reduce the plasma proteome complexity." PLoS One 6(5): e19603.
2. Perazella, M. A. (2010). "Tenofovir-induced kidney disease: an acquired renal tubular mitochondriopathy." Kidney Int 78(11):
Figure 1: Overview of the protein biomarker discovery workflow. Collection and processing of urine (a) and plasma (b), LCMSMS analysis (c), total ion chromatogram of LCMS data from technical replicates (d), protein identifications using varying gradient length (e) and Venn diagram of identifications using optimal gradient and sample load (f).