Detection of Growth hormone by LC-MS Analysis
One of the strategies for the detection of growth hormone (GH) administration is the identification of abnormal ratios between the main GH proteoforms in blood circulation. However, the high sequence similarity between them complicates a precise differentiation when relying on antibody-based quantification.
For unambiguous and precise protein identification, we will use liquid chromatography - mass spectrometry (LC-MS) analysis for the quantification of the 22 and 20 kDa GH proteoforms. Before, we will develop a sample preparation strategy for blood samples based on a novel type of (hydrogel) nanoparticles, for sample simplification and reduction of the blood matrix complexity. These nanoparticles have shown the capacity to simultaneously deplete blood from abundant proteins and enrich it in low abundance proteins through several types of particles and protocols, i.e. allowing for detection of low abundance proteins by LC-MS.
We will apply this methodology for the quantification of the 22 and 20 kDa proteoforms. We will further expand this strategy for the analysis of the 23 and 45 kDa proteoforms for which little information is available. The former showed a high concentration in post-exercise states. The latter could exist at higher amounts after administration of pharmaceutical GH. We will investigate their relevance within anti-doping analysis.
At the same time, we will purify blood extracellular microvesicles from blood samples to assess potential GH detection. These vesicles represent a blood sub-type of samples that have a much reduced matrix complexity as compared to blood. As such, the detection of low abundance proteins by LC-MS in this type of samples is significantly more accessible.
Here we have explored three different strategies for GH purification from plasma samples through antibody-based, precipitation-based and ProteoCAP-based protocols, aimed for a later LC-MS/MS quantification. This quantification has also moved from the previous SRM method to a state-of-the-art PRM method that employed last-generation orbitrap-based instruments. From the three strategies, best results corresponded to precipitation based protocols that were combined with a subsequent fractionation at the protein level with disposable C4 TopTip micro-columns. Together with the PRM method and the use of trypsin, an enzyme that has a higher proteolysis efficacy than the previous Glu-C and that here we have been able to use it due to a new LC gradient configuration, our method detected GH at the spiked concentration of 5 ng/mL of each 20 and 22 kDa proteoform.
This sensitivity does not reflect the presumed true limit of detection, but it is comparable from what we obtained with our previous method, albeit here without the usage of antibodies and with potential improvements that makes
us believe that we will be able to lower these values. Currently we have three precipitation-based methods that could be all of them valid for GH detection. We have unsuccessfully tried to concatenate these methods with additional protocols for further fractionation to gain more sensitivity. We attribute these results to a too reduced protein recovery after the precipitation methods. This low recovery did maximize the impact of the protein losses that occur in any sample preparation step. This led us to escalate these protocols to provide 3-4 times higher protein recovery, where we succeed, and importantly we also succeed in removing the phospholipid contamination that was also escalated in the protocols. As a result we have protocols that now have sufficient protein amount to be amenable for concatenation of additional protocols for increased GH enrichment.
Thus, the next steps of this project will be to test the escalated protocols with and without added concatenated protocols by LC-MS to determine the assay sensitivity and to evaluate its suitability as a method for GH quantification. We believe that the strategy that we have developed in this project has the potential for detecting GH below the ng/mL frontier, thus being able to quantify GH variants at levels close to basal state.