Overview of quantitative LC-MS techniques for proteomics and activitomics

Analysing Complex Oral Protein Samples: Complete Workflow and Case Analysis of Salivary Pellicles

Studies on small quantity, highly complex protein samples, such as salivary pellicle, have been enabled by recent major technological and analytical breakthroughs. Advances in mass spectrometry-based computational proteomics such as Multidimensional Protein Identification Technology have allowed precise identification and quantification of complex protein samples on a proteome-wide scale, which has enabled the determination of corresponding genes and cellular functions at the protein level. The latter was achieved via protein-protein interaction mapping with Gene Ontology annotation. In recent years, the application of these technologies has broken various barriers in small-quantity-complex-protein research such as salivary pellicle. This review provides a concise summary of contemporary proteomic techniques contributing to (1) increased complex protein (up to hundreds) identification using minute sample sizes (µg level), (2) precise protein quantification by advanced stable isotope labelling or label-free approaches and (3) the emerging concepts and techniques regarding computational integration, such as the Gene Ontology Consortium and protein-protein interaction mapping. The latter integrates the structural, genomic, and biological context of proteins and genes to predict protein interactions and functional connections in a given biological context. The same technological breakthroughs and computational integration concepts can also be applied to other low-volume oral protein complexes such as gingival crevicular or peri-implant sulcular fluids.

Protein nanoparticles in drug delivery: animal protein, plant proteins and protein cages, albumin nanoparticles

In this article, we will describe the properties of albumin and its biological functions, types of sources that can be used to produce albumin nanoparticles, methods of producing albumin nanoparticles, its therapeutic applications and the importance of albumin nanoparticles in the production of pharmaceutical formulations. In view of the increasing use of Abraxane and its approval for use in the treatment of several types of cancer and during the final stages of clinical trials for other cancers, to evaluate it and compare its effectiveness with conventional non formulations of chemotherapy Paclitaxel is paid. In this article, we will examine the role and importance of animal proteins in Nano medicine and the various benefits of these biomolecules for the preparation of drug delivery carriers and the characteristics of plant protein Nano carriers and protein Nano cages and their potentials in diagnosis and treatment. Finally, the advantages and disadvantages of protein nanoparticles are mentioned, as well as the methods of production of albumin nanoparticles, its therapeutic applications and the importance of albumin nanoparticles in the production of pharmaceutical formulations.

Recent advances in the analysis of nanoparticle-protein coronas

In spite of radical advances in nanobiotechnology, the clinical translation of nanoparticle (NP)-based agents is still a major challenge due to various physiological factors that influence their interactions with biological systems. Recent decade witnessed meticulous investigation on protein corona (PC) that is the first surrounds NPs once administered into the body. Formation of PC around NP surface exhibits resilient effects on their circulation, distribution, therapeutic activity, toxicity and other factors. Although enormous literature is available on the role of PC in altering pharmacokinetics and pharmacodynamics of NPs, understanding on its analytical characterization methods still remains shallow. Therefore, the current review summarizes the impact of PC on biological fate of NPs and stressing on analytical methods employed for studying the NP-PC.

Proteomic profiling of ovarian cancer models using TMT-LC-MS/MS

Herein, we have utilized two cellular models of epithelial ovarian cancer (EOC), where transfer of normal chromosome 18 material into the EOC cell lines TOV-112D and TOV-21G induced in vitro and in vivo suppression of tumorigenic phenotype in derived hybrid clones. Two-dimensional-liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) with tandem mass tagging (TMT) was then employed to profile the whole cell, secreted and crude membrane proteomes of the parental and hybrid cell models to identify differentially expressed proteins as potential markers of ovarian tumor suppression. Protein changes of interest were confirmed by immunoblotting in additional hybrid and revertant cell lines. This method afforded quantitative coverage of around 1,000 unique proteins and is applicable to the analysis of any cell model, tissue or biofluid.

A combinatorial approach to the peptide feature matching problem for label-free quantification

MOTIVATION

Label-free quantification is an important approach to identify biomarkers, as it measures the quantity change of peptides across different biological samples. One of the fundamental steps for label-free quantification is to match the peptide features that are detected in two datasets to each other. Although ad hoc software tools exist for the feature matching, the definition of a combinatorial model for this problem is still not available.

RESULTS

A combinatorial model is proposed in this article. Each peptide feature contains a mass value and a retention time value, which are used to calculate a matching weight between a pair of features. The feature matching is to find the maximum-weighted matching between the two sets of features, after applying a to-be-computed time alignment function to all the retention time values of one set of the features. This is similar to the maximum matching problem in a bipartite graph. But we show that the requirement of time alignment makes the problem NP-hard. Practical algorithms are also provided. Experiments on real data show that the algorithm compares favorably with other existing methods.

CONTACT

binma@uwaterloo.ca

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Antigen generation and display in therapeutic antibody drug discovery -- a neglected but critical player

Disease intervention by targeting a critical pathway molecule through a blocking antibody or interference by therapeutic proteins is currently en vogue. Generation of blocking antibodies or therapeutic proteins inevitably requires the production of recombinant proteins or cell-based immunogens. Thus, one could call the antigen molecule the neglected player in antibody drug discovery. The variety of methods available for making recombinant proteins or recombinant cell lines that present the target on the cell surface is extensive. These need to be addressed in conjunction with biochemical and biophysical quality criteria and the experimental application intended. Fundamentally, successful production and isolation of monoclonal antibodies requires optimized antigen preparation and presentation to the immune host. This review summarizes the most important aspects of antigen generation and display, enabling logical decision making to give rise to potent high-affinity antibodies.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Application of proteomics in the mechanistic study of traditional Chinese medicine

Systems biology is considered to be the possible technology that could bring breakthroughs in the study of TCM (traditional Chinese medicine). Proteomics, as one of the major components of systems biology, has been used in the mechanistic study of TCM, providing some interesting results. In the present paper, we review the current application of proteomics in the mechanistic study of TCM. Proteomics technologies and strategies that might be used in the future to improve study of TCM are also discussed.

OMICS-strategies and methods in the fight against doping

During the past decade OMICS-methods not only continued to have their impact on research strategies in life sciences and in particular molecular biology, but also started to be used for anti-doping control purposes. Research activities were mainly reasoned by the fact that several substances and methods, which were prohibited by the World Anti-Doping Agency (WADA), were or still are difficult to detect by direct methods. Transcriptomics, proteomics, and metabolomics in theory offer ideal platforms for the discovery of biomarkers for the indirect detection of the abuse of these substances and methods. Traditionally, the main focus of transcriptomics and proteomics projects has been on the prolonged detection of the misuse of human growth hormone (hGH), recombinant erythropoietin (rhEpo), and autologous blood transfusion. An additional benefit of the indirect or marker approach would also be that similarly acting substances might then be detected by a single method, without being forced to develop new direct detection methods for new but comparable prohibited substances (as has been the case, e.g. for the various forms of Epo analogs and biosimilars). While several non-OMICS-derived parameters for the indirect detection of doping are currently in use, for example the blood parameters of the hematological module of the athlete's biological passport, the outcome of most non-targeted OMICS-projects led to no direct application in routine doping control so far. The main reason is the inherent complexity of human transcriptomes, proteomes, and metabolomes and their inter-individual variability. The article reviews previous and recent research projects and their results and discusses future strategies for a more efficient application of OMICS-methods in doping control.

Biological signalling activity measurements using mass spectrometry

MS (mass spectrometry) techniques are rapidly evolving to high levels of performance and robustness. This is allowing the application of these methods to the interrogation of signalling networks with unprecedented depth and accuracy. In the present review we discuss how MS-based multiplex quantification of kinase activities and phosphoproteomics provide complementary means to assess biological signalling activity. In addition, we discuss how a wider application of these analytical concepts to quantify kinase signalling will result in a more comprehensive understanding of normal and disease biology at the system level.