Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

Human follicular fluid proteomic and peptidomic composition quantitative studies by SWATH-MS methodology. Applicability of high pH RP-HPLC fractionation

Analysis of proteomic composition of human follicular fluid (hFF) has been previously proposed as a potential tool of oocyte quality evaluation. In order to develop an efficient method to investigate the hFF proteome and peptidome components, we applied and tested a few prefractionation schemes of hFF material consisting of ultrafiltration, optional immunodepletion, and high pH RP-HPLC separation by building spectral libraries and comparing their quantification capabilities of unfractionated samples. Low Molecular-Weight Fraction peptides (LMWF, <10 kDa) and High Molecular-Weight Fraction proteins (HMWF, >10 kDa) resulting from ultrafiltration were analyzed separately. We identified 302 proteins in HMWF and 161 proteins in LMWF in all qualitative experiments. All LMWF peptidomic libraries turned out to be of poor quantification quality, however they enabled measurement of higher numbers of peptides with increasing input of experiment data, in contrast to HMWF proteomic libraries. We were able to quantify a total of 108 HMWF proteins and 250 LMWF peptides (from 84 proteins) in all experiments. Employment of high RP-HPLC fractionation allowed for identification of a much broader set of proteins, however did not significantly improve the quantification capabilities of the applied method. Data are available via ProteomeXchange with identifier PXD008073. SIGNIFICANCE: In the search of biomarkers for assessment of oocyte quality in assisted reproductive technology, many studies are devoted to analysis of follicular fluid composition. Candidates for such biomarkers can be located in both the proteome and the recently investigated peptidome of hFF. Reliable qualitative and especially quantitative analysis of complex mixtures such as hFF, requires development of a fast and preferably inexpensive analytical procedure. The powerful SWATH-MS technique is well suited for quantitative label-free analysis of complex protein and peptide mixtures. However, for efficient usage it needs well designed and constructed MS-spectral libraries as well as a proper protocol for sample preparation. We investigated the influence of the size and quality of MS-spectral libraries (different spectral libraries are constructed using various sample prefractionation protocols) on SWATH experiments on hFF proteome and peptidome. In the case of peptidome investigation, increasing the size of spectral libraries led to quantification of more peptides in a single experiment. For the proteome, increasing the size of spectral libraries improved quantification only to a limited extend, and further extension of spectral libraries even worsened results. Nevertheless, using the best selected prefractionation schemes and spectral libraries we were able to quantify as many as 79 proteins of hFF proteome and 106 peptides (from 53 proteins) of hFF peptidome in single experiments. The spectral libraries and prefractionation protocols we developed allow for a large scale fast scan of hundreds of clinical hFF samples in the search for biomarkers for evaluation of oocyte quality.

Updates on resources, software tools, and databases for plant proteomics in 2016-2017

Proteomics data processing, annotation, and analysis can often lead to major hurdles in large-scale high-throughput bottom-up proteomics experiments. Given the recent rise in protein-based big datasets being generated, efforts in in silico tool development occurrences have had an unprecedented increase; so much so, that it has become increasingly difficult to keep track of all the advances in a particular academic year. However, these tools benefit the plant proteomics community in circumventing critical issues in data analysis and visualization, as these continually developing open-source and community-developed tools hold potential in future research efforts. This review will aim to introduce and summarize more than 50 software tools, databases, and resources developed and published during 2016-2017 under the following categories: tools for data pre-processing and analysis, statistical analysis tools, peptide identification tools, databases and spectral libraries, and data visualization and interpretation tools. Intended for a well-informed proteomics community, finally, efforts in data archiving and validation datasets for the community will be discussed as well. Additionally, the author delineates the current and most commonly used proteomics tools in order to introduce novice readers to this -omics discovery platform.

Proteomic Profiling of Integrin Adhesion Complex Assembly

Cell adhesion to components of the cellular microenvironment via cell-surface adhesion receptors controls many aspects of cell behavior in a range of physiological and pathological processes. Multimolecular complexes of scaffolding and signaling proteins are recruited to the intracellular domains of adhesion receptors such as integrins, and these adhesion complexes tether the cytoskeleton to the plasma membrane and compartmentalize cellular signaling events. Integrin adhesion complexes are highly dynamic, and their assembly is tightly regulated. Comprehensive, unbiased, quantitative analyses of the composition of different adhesion complexes over the course of their formation will enable better understanding of how the dynamics of adhesion protein recruitment influence the functions of adhesion complexes in fundamental cellular processes. Here, a pipeline is detailed integrating biochemical isolation of integrin adhesion complexes during a time course, quantitative proteomic analysis of isolated adhesion complexes, and computational analysis of temporal proteomic data. This approach enables the characterization of adhesion complex composition and dynamics during complex assembly.

Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques

INTRODUCTION

While selected/multiple-reaction monitoring (SRM or MRM) is considered the gold standard for quantitative protein measurement, emerging data-independent acquisition (DIA) using high-resolution scans have opened a new dimension of high-throughput, comprehensive quantitative proteomics. These newer methodologies are particularly well suited for discovery of biomarker candidates from human disease samples, and for investigating and understanding human disease pathways. Areas covered: This article reviews the current state of targeted and untargeted DIA mass spectrometry-based proteomic workflows, including SRM, parallel-reaction monitoring (PRM) and untargeted DIA (e.g., SWATH). Corresponding bioinformatics strategies, as well as application in biological and clinical studies are presented. Expert commentary: Nascent application of highly-multiplexed untargeted DIA, such as SWATH, for accurate protein quantification from clinically relevant and disease-related samples shows great potential to comprehensively investigate biomarker candidates and understand disease.