A recent article has demonstrated the validity of a new top-down proteomics approach to identifying low-abundance biomarkers in the one per cent of serum/plasma proteins known as the deep proteome.
Applying this methodology, French researchers identified a potential biomarker that might be used to track a patient's recovery from a myocardial infarction (heart attack).
Specifically, their goal was to develop indicators that would more accurately predict a complex process called 'left ventricular remodelling' that occurs in response to heart damage and leads to heart failure.
The researchers followed a four-step strategy for discovering and identifying candidate biomarkers in plasma samples and serum samples of post-infarction patients.
First, they developed a study design using patient samples taken four times during the one year following myocardial infarction, including those who had either no remodelling, low remodelling, or high remodelling.
They then fractionated the plasma and serum samples using Proteominer bead technology to enrich for low-abundance proteins in preparation for biomarker discovery.
Biomarker discovery was then performed using Seldi (surface-enhanced laser desorption/ionisation) TOF mass spectrometric analysis.
They then identified biomarkers using the Lucid Proteomics System, which combines Bio-Rad's Seldi-based Proteinchip array technology and Bruker's high-resolution mass spectrometers.
This four-step strategy builds on previous methods by effectively bridging the gap between discovery of low-abundance biomarkers and their identification.
'The workflow in this publication provides scientists with a promising approach for accessing, profiling, and identifying clinically relevant biomarkers,' said Dominic Casenas, Bio-Rad product manager.
'The Lucid Proteomics System enables scientists to use a top-down analysis of intact proteins; this is a superior method for protein biomarker discovery since truncated or modified forms of proteins may be important biomarkers,' he added.
To gain access to low-abundance proteins, a fractionation step to deplete high-abundance proteins before using Seldi Proteinchip arrays is recommended.
For this study, researchers pre-treated plasma and serum samples using the combinatorial library of hexapeptides employed in Bio-Rad's Proteominer protein enrichment kit.
After binding the sample to Proteominer beads and subsequent elution, high-abundance proteins were effectively diluted, while low-abundance proteins were concentrated and therefore better detected by mass spectrometry technologies, in this case the Lucid Proteomics System.
The researchers looked for candidate biomarkers in the deep proteome of post-infarction patients by comparing the profiles of Proteominer-treated samples of patients with no and high remodelling at a series of time points.
They used a variety of Seldi Proteinchip arrays: CM10, Q10 and H50 arrays for plasma samples and IMAC30 Cu2+ and IMAC30 Ni2+ arrays for serum samples.
Applying the same sample to different array types allowed for the detection of more low-abundance proteins for further analysis.
The study demonstrates the effectiveness of Proteominer-treated samples: most of the peaks found to be differentially expressed between patients with no and high remodelling were not detected in the control plasma.
After fractionation with the Proteominer technology, scientists uncovered 77 peaks with the CM10 array and 69 with the Q10 array that had not been observed in samples without fractionation.
Researchers discovered 26 peaks whose intensity modulated between groups, most of which appeared only in Proteominer-treated plasma/serum.
One of the peaks (2,777m/z), an N-terminal human albumin fragment, was directly identified without purification from the Proteinchip array using the Lucid Proteomics System and Mascot software.
As part of the Lucid Proteomics System, Bruker's autoflex or ultraflex series of TOF/TOF mass spectrometers interface with Bio-Rad's Proteinchip Seldi-based array technology and provide the necessary resolution, sensitivity and accuracy for high confidence identification.
