Refinements of LC-MS/MS Spectral Counting Statistics Improve Quantification of Low Abundance Proteins

Mass spectrometry-based spectral count has been a common choice of label-free proteome quantification due to the simplicity for the sample preparation and data generation. The discriminatory nature of spectral count in the MS data-dependent acquisition, however, inherently introduces the spectral count variation for low-abundance proteins in multiplicative LC-MS/MS analysis, which hampers sensitive proteome quantification. As many low-abundance proteins play important roles in cellular processes, deducing low-abundance proteins in a quantitatively reliable manner greatly expands the depth of biological insights. Here, we implemented the Moment Adjusted Imputation error model in the spectral count refinement as a post PLGEM-STN for improving sensitivity for quantitation of low-abundance proteins by reducing spectral count variability. The statistical framework, automated spectral count refinement by integrating the two statistical tools, was tested with LC-MS/MS datasets of MDA-MB468 breast cancer cells grown under normal and glucose deprivation conditions. We identified about 30% more quantifiable proteins that were found to be low-abundance proteins, which were initially filtered out by the PLGEM-STN analysis. This newly developed statistical framework provides a reliable abundance measurement of low-abundance proteins in the spectral count-based label-free proteome quantification and enabled us to detect low-abundance proteins that could be functionally important in cellular processes.

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

LC-MS/MS Identification of a Bromelain Peptide Biomarker fromAnanas comosusMerr

Bromelain (Br) is a cysteine peptidase (GenBank AEH26024.1) from pineapple, with over 40 years of clinical use. The constituents mediating its anti-inflammatory activity are not thoroughly characterized and no peptide biomarker exists. Our objective is to characterize Br raw material and identify peptides in the plasma of Br treated mice. After SDS-PAGE in-gel digestion, Br (VN#3507; Middletown, CT, USA) peptides were analyzed via LC/MS/MS using 95% protein probability, 95% peptide probability, and a minimum peptide number = 5. Br spiked mouse plasma (1 ug/ul) and plasma from i.p. treated mice (12 mg/kg) were assessed using SRM. In Br raw material, we identified seven proteins: four proteases, one jacalin-like lectin, and two protease inhibitors. In Br spiked mouse plasma, six proteins (ananain, bromelain inhibitor, cysteine proteinase AN11, FB1035 precursor, FBSB precursor, and jacalin-like lectin) were identified. Using LC/MS/MS, we identified the unique peptide, DYGAVNEVK, derived from FB1035, in the plasma of i.p. Br treated mice. The spectral count of this peptide peaked at 6 hrs and was undetectable by 24 hrs. In this study, a novel Br peptide was identified in the plasma of treated mice for the first time. This Br peptide could serve as a biomarker to standardize the therapeutic dose and maximize clinical utility.