LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors

Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data are suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody-drug conjugates and immunotherapeutic agents.

Peptidomics

Peptides are biopolymers, typically consisting of 2-50 amino acids. They are biologically produced by the cellular ribosomal machinery or by non-ribosomal enzymes and, sometimes, other dedicated ligases. Peptides are arranged as linear chains or cycles, and include post-translational modifications, unusual amino acids and stabilizing motifs. Their structure and molecular size render them a unique chemical space, between small molecules and larger proteins. Peptides have important physiological functions as intrinsic signalling molecules, such as neuropeptides and peptide hormones, for cellular or interspecies communication, as toxins to catch prey or as defence molecules to fend off enemies and microorganisms. Clinically, they are gaining popularity as biomarkers or innovative therapeutics; to date there are more than 60 peptide drugs approved and more than 150 in clinical development. The emerging field of peptidomics comprises the comprehensive qualitative and quantitative analysis of the suite of peptides in a biological sample (endogenously produced, or exogenously administered as drugs). Peptidomics employs techniques of genomics, modern proteomics, state-of-the-art analytical chemistry and innovative computational biology, with a specialized set of tools. The complex biological matrices and often low abundance of analytes typically examined in peptidomics experiments require optimized sample preparation and isolation, including in silico analysis. This Primer covers the combination of techniques and workflows needed for peptide discovery and characterization and provides an overview of various biological and clinical applications of peptidomics.

Absolute quantification of cellular levels of photosynthesis-related proteins in Synechocystis sp. PCC 6803

Quantifying cellular components is a basic and important step for understanding how a cell works, how it responds to environmental changes, and for re-engineering cells to produce valuable metabolites and increased biomass. We quantified proteins in the model cyanobacterium Synechocystis sp. PCC 6803 given the general importance of cyanobacteria for global photosynthesis, for synthetic biology and biotechnology research, and their ancestral relationship to the chloroplasts of plants. Four mass spectrometry methods were used to quantify cellular components involved in the biosynthesis of chlorophyll, carotenoid and bilin pigments, membrane assembly, the light reactions of photosynthesis, fixation of carbon dioxide and nitrogen, and hydrogen and sulfur metabolism. Components of biosynthetic pathways, such as those for chlorophyll or for photosystem II assembly, range between 1000 and 10,000 copies per cell, but can be tenfold higher for CO₂ fixation enzymes. The most abundant subunits are those for photosystem I, with around 100,000 copies per cell, approximately 2 to fivefold higher than for photosystem II and ATP synthase, and 5-20 fold more than for the cytochrome b₆f complex. Disparities between numbers of pathway enzymes, between components of electron transfer chains, and between subunits within complexes indicate possible control points for biosynthetic processes, bioenergetic reactions and for the assembly of multisubunit complexes.

Biofunctionality of Enzymatically Derived Peptides from Codfish (Gadus morhua) Frame: Bulk In Vitro Properties, Quantitative Proteomics, and Bioinformatic Prediction

Protein hydrolysates show great promise as bioactive food and feed ingredients and for valorization of side-streams from e.g., the fish processing industry. We present a novel approach for hydrolysate characterization that utilizes proteomics data for calculation of weighted mean peptide properties (length, molecular weight, and charge) and peptide-level abundance estimation. Using a novel bioinformatic approach for subsequent prediction of biofunctional properties of identified peptides, we are able to provide an unprecedented, in-depth characterization. The study further characterizes bulk emulsifying, foaming, and in vitro antioxidative properties of enzymatic hydrolysates derived from cod frame by application of Alcalase and Neutrase, individually and sequentially, as well as the influence of heat pre-treatment. All hydrolysates displayed comparable or higher emulsifying activity and stability than sodium caseinate. Heat-treatment significantly increased stability but showed a negative effect on the activity and degree of hydrolysis. Lower degrees of hydrolysis resulted in significantly higher chelating activity, while the opposite was observed for radical scavenging activity. Combining peptide abundance with bioinformatic prediction, we identified several peptides that are likely linked to the observed differences in bulk emulsifying properties. The study highlights the prospects of applying proteomics and bioinformatics for hydrolysate characterization and in food protein science.

Different Research Approaches in Unraveling the Venom Proteome of Naja ashei

The dynamic development of venomics in recent years has resulted in a significant increase in publicly available proteomic data. The information contained therein is often used for comparisons between different datasets and to draw biological conclusions therefrom. In this article, we aimed to show the possible differences that can arise, in the final results of the proteomic experiment, while using different research workflows. We applied two software solutions (PeptideShaker and MaxQuant) to process data from shotgun LC-MS/MS analysis of Naja ashei venom and collate it with the previous report concerning this species. We were able to provide new information regarding the protein composition of this venom but also present the qualitative and quantitative limitations of currently used proteomic methods. Moreover, we reported a rapid and straightforward technique for the separation of the fraction of proteins from the three-finger toxin family. Our results underline the necessary caution in the interpretation of data based on a comparative analysis of data derived from different studies.