Lais Lacerda Brasil de Oliveira¹, Clarissa Moraes de Castro ¹, Maria Gilnara Lima Bandeira ¹, Sheheryar ¹, Carlos Roberto Koscky Paier^1,2, Maria Elisabete Amaral de Moraes¹

The qualitative-quantitative analysis of circulating proteins in blood plasma can lead to the detection of pathogenesis mechanisms, disease biomarkers, and potential drug targets. However, the presence of high-abundance proteins in plasma complicates bottom-up LC-MS/MS analyses - a technique based on detecting ionized peptides for protein characterization. These high-abundance plasma proteins suppress the signal of low-abundance proteins, which are precisely the ones that provide relevant information about the biological system of origin. Thus, this study aimed to test different plasma depletion methods to select the approach that least suppresses the signal of low-abundance proteins. Blood plasma samples were obtained after informed consent from 10 healthy volunteers and subjected to three different methods for depleting highly abundant proteins. Two methods were based on protein precipitation with organic solvents - one using acetonitrile (ACN) and the other using isopropanol with 1.0% trichloroacetic acid (TCA). The third method (COL) relied on sample fractionation by immunoaffinity chromatography. After depletion, the samples were quantified by spectrofluorimetry and analyzed via denaturing electrophoresis, compared to non-depleted samples. The depleted samples were then reduced with 5 mM dithiothreitol, alkylated with 14 mM iodoacetamide, digested with trypsin at a 1:100 (enzyme:substrate) ratio, desalted by solid-phase extraction with C18 resin, and lyophilized. The samples were resuspended in 0.1% formic acid, quantified, and analyzed in triplicate (1 µg each) by LC-MS/MS. A linear 150.5-minute elution gradient was used with 0.1% formic acid (equilibration) and 80:20 ACN/formic acid (elution). MS1 spectra were generated between 375–1500 *m/z* at a resolution of 70,000 (at 140 *m/z*), with an AGC target of 3×10⁶ and a maximum ion injection time (IT max) of 100 ms. The 20 most intense precursor ions (*z* > 2) were selected and fragmented at 30% NCE; product ions were analyzed at a resolution of 17,500 (at 140 *m/z*), with an AGC target of 1×10⁵ and IT max of 50 ms. Raw data were processed using the MaxQuant algorithm for protein identification and quantification via XIC. The RawVegetable, Perseus, and MetaboAnalyst algorithms were used for statistical comparisons. Gene ontology, interactome, and pathway enrichment analyses were performed using STRING and Reactome. Among the results, the COL and TCA methods showed higher efficiency in depleting immunoglobulins and albumin, with more similar outcomes compared to the ACN method. TCA enabled the identification of a greater diversity of proteins. Proteins uniquely identified via ACN were linked to lipid transport, while TCA highlighted immune system proteins, and COL emphasized cellular energy metabolism, exosomes, and cell signaling pathways. In conclusion, each major protein depletion method demonstrated high uniqueness, enabling applications in different clinical contexts. For example, the ACN method is efficient for identifying chronic inflammatory conditions (e.g., long COVID) and dyslipidemias. COL is suited for neuropathies and cardiovascular diseases, while TCA enriched pathways related to neurodegenerative dysfunctions

Agradecimentos: Ao Ministério da Saúde, à FUNCAP, à Central Multiusuário do NPDM.