Low molecular weight (LMW) proteins have biological significance as potential biomarkers and are found in circulating bodily fluids like serum and plasma. The abundance of large molecular weight proteins, which obscure the identification and quantification of lower molecular weight proteins, is a significant barrier to mass spectrometry-based proteomics of serum. Affinity resins are used in traditional ways to remove high molecular weight proteins like albumin and immunoglobulin G while simultaneously losing lower molecular weight proteins. This research analyses an affinity resin, a gel filter, and an acetonitrile (ACN) precipitation method to successfully remove high molecular weight proteins and recover lower molecular weight proteins, taking into account the significance of reducing high molecular proteins.

Methods: ACN precipitation, the commercially available serum protein micro kit, and the gel filter method were only a few of the techniques used to enrich serum. An AB SCIEX ESI QTOF mass spectrometer was used for the mass spectrometric runs. For the purpose of global proteome profiling, mass spectrometry analysis of the enriched serum produced by the ACN precipitation and gel filter technique was carried out. Additionally, ACN-precipitated enriched serum was subjected to quantitative mass spectrometry using isobaric tags for relative and absolute quantification (iTRAQ).

Results: The gel filter approach was better suited for global proteome analysis and was not recommended for quantitative proteomic research, although providing for the resolution and identification of LMW proteins. On the other hand, enrichment using the ACN precipitation approach enabled the accurate identification and measurement of LMW proteins with molecular weights under 4 kDa.

Conclusions: The majority of the very abundant proteins were efficiently extracted from the serum using merely cold ACN and centrifugation, and a sizeable fraction of the LMW proteome was recovered. The elucidation of a quicker technique that is compatible with iTRAQ labelling to produce better results has made it possible to screen and identify potential biomarkers more effectively.