RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification.

Unlabelled: RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization.

Slx5/Slx8 Promotes Replication Stress Tolerance by Facilitating Mitotic Progression.

Loss of minichromosome maintenance protein 10 (Mcm10) causes replication stress. We uncovered that S. cerevisiae mcm10-1 mutants rely on the E3 SUMO ligase Mms21 and the SUMO-targeted ubiquitin ligase complex Slx5/8 for survival.

Improved intensity-based label-free quantification via proximity-based intensity normalization (PIN).

Researchers are increasingly turning to label-free MS1 intensity-based quantification strategies within HPLC-ESI-MS/MS workflows to reveal biological variation at the molecule level. Unfortunately, HPLC-ESI-MS/MS workflows using these strategies produce results with poor repeatability and reproducibility, primarily due to systematic bias and complex variability. While current global normalization strategies can mitigate systematic bias, they fail when faced with complex variability stemming from transient stochastic events during HPLC-ESI-MS/MS analysis.

Mass spectrometry-based proteomics: basic principles and emerging technologies and directions.

As the main catalytic and structural molecules within living systems, proteins are the most likely biomolecules to be affected by radiation exposure. Proteomics, the comprehensive characterization of proteins within complex biological samples, is therefore a research approach ideally suited to assess the effects of radiation exposure on cells and tissues. For comprehensive characterization of proteomes, an analytical platform capable of quantifying protein abundance, identifying post-translation modifications and revealing members of protein complexes on a system-wide level is necessary.

Sample collection and handling considerations for peptidomic studies in whole saliva; implications for biomarker discovery.

Background: Proteomic studies in saliva have demonstrated its potential as a diagnostic biofluid, however the salivary peptidome is less studied. Here we study the effects of several sample collection and handling factors on salivary peptide abundance levels.

Methods: Salivary peptides were isolated using an ultrafiltration device and analyzed by tandem mass spectrometry.

Hexapeptide libraries for enhanced protein PTM identification and relative abundance profiling in whole human saliva.

Dynamic range compression (DRC) by hexapeptide libraries increases MS/MS-based identification of lower-abundance proteins in complex mixtures. However, two unanswered questions impede fully realizing DRC's potential in shotgun proteomics. First, does DRC enhance identification of post-translationally modified proteins? Second, can DRC be incorporated into a workflow enabling relative protein abundance profiling? We sought to answer both questions analyzing human whole saliva.

LTQ-iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments.

Pulsed Q dissociation enables combining LTQ ion trap instruments with isobaric peptide tagging. Unfortunately, this combination lacks a technique which accurately reports protein abundance ratios and is implemented in a freely available, flexible software pipeline. We developed and implemented a technique assigning collective reporter ion intensity-based weights to each peptide abundance ratio and calculating a protein's weighted average abundance ratio and p-value.

A dynamic range compression and three-dimensional peptide fractionation analysis platform expands proteome coverage and the diagnostic potential of whole saliva.

Comprehensive identification of proteins in whole human saliva is critical for appreciating its full diagnostic potential. However, this is challenged by the large dynamic range of protein abundance within the fluid. To address this problem, we used an analysis platform that coupled hexapeptide libraries for dynamic range compression (DRC) with three-dimensional (3D) peptide fractionation.