Biology subjects

Dibavar, A. S.

Publications and source records attributed to Dibavar, A. S..

4 recordsLinked to original sources

bioRxiv2024

Causality Analysis of Protein Corona Composition: Phosphatidylcholine-Enhances Plasma Proteome Profiling by Proteomics

The study of the protein corona, the immediate and evolving biomolecular coating that forms on the surface of nanoparticles when exposed to a biological environment, is a crucial area in nanomedicine. This phenomenon significantly influences the behavior, functionality, and biological interactions of nanoparticles with biosystems. Until now, conclusions regarding the role of the protein corona in specific biological applications have been based on establishing correlation rather than causation. By understanding causality, researchers can predict how changes in nanoparticle properties or biological conditions will affect protein corona composition, in turn affecting the nanoparticle interactions with the biosystems and their applications. This predictive capability is essential for designing nanoparticles with specific characteristics tailored for therapeutic and diagnostic nanomedicine applications. Here, we explore the concept of "actual causality" (by Halpern and Pearl) to mathematically prove how various small molecules, including metabolites, lipids, vitamins, and nutrients, spiked into plasma can induce diverse protein corona patterns on identical nanoparticles. This approach significantly enhances the depth of plasma proteome profiling. Our findings reveal that among the various spiked small molecules, phosphatidylcholine was the actual cause of the observed increase in the proteomic depth of the plasma sample. By considering the concept of causality in the field of protein corona, the nanomedicine community can substantially improve their ability to design safer and more efficient nanoparticles for both diagnostic and therapeutic purposes.

bioengineering↗

bioRxiv2024

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L--phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 {micro}g/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in a single plasma sample. Our molecular dynamic results revealed that phosphatidylcholine interacts with albumin via hydrophobic interactions, h-bonds, and water-bridges. Addition of phosphatidylcholine also enabled the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. These significant achievements are made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in plasma proteome profiling. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

bioengineering↗

bioRxiv2022

Monitoring Functional Post-Translational Modifications Using a Data-Driven Proteome Informatic Pipeline Based on PEIMAN2

Post-translational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor- intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

biochemistry↗

bioRxiv2021

Abnormal (hydroxy)prolines deuterium content redefines hydrogen chemical mass

Analysing the {delta}2H in individual amino acids of proteins extracted from vertebrates, we unexpectedly found in some samples, notably bone collagen from seals, more than twice as much deuterium in proline and hydroxyproline residues than in seawater. This corresponds to at least four times higher {delta}2H than in any previously reported biogenic sample. We ruled out diet as a plausible mechanism for such anomalous enrichment. This finding puts into question the old adage that you are what you eat. SUMMARYThe chemical mass of hydrogen is defined as an interval from the lowest to the highest content of deuterium 2H, hydrogens heavy stable isotope. Measurements of the deviations {delta}2H in the deuterium content from the standard (ocean water, {delta}2H = 0{per thousand}) are used to characterise biological samples, such as animal bone collagen. The results are often interpreted in terms of the trophic level and diet of the animal as well as prevailing climate during its lifetime. The majority of the published bone collagen {delta}2H data fall into a narrow {delta}2H range limited to {+/-}100{per thousand}. Using novel analysis method, we unexpectedly found greatly higher {delta}2H values, up to 1500{per thousand}, in seal bone collagen. Such anomalous deuterium enrichment is detected only in two amino acid residues, proline and its derivative hydroxyproline, while other residues show much smaller {delta}2H values. Anomalously high {delta}2H values, albeit of lower magnitudes, are also found for these residues in other biological sources. This finding substantially expands the upper bound of the hydrogen chemical mass for biogenic sources. Since neither diet nor environment explain these mysteriously high enrichment levels amounting to more than twice deuterium content in sea water, our understanding of stable isotopes in nature, as well as the old adage "you are what you eat", are put in question.

biochemistry↗