Liquid chromatography-mass spectrometry-based quantitative proteomics

Identification and detection sensitivity of Microcystis aeruginosa from mixed and field samples using MALDI-TOF MS

To verify the applicability of identifying Microcystis aeruginosa by matrix-assisted laser desorption-ionization-time-of-flight mass spectrometry (MALDI-TOF MS), mixed and field samples were employed to study the sensitivity and the analysis power, respectively. Series diluted samples and artificially mixed samples by the M. aeruginosa NIES-843 strain were designed to verify the sensitivity. The lowest detection limit was 1.955 × 10⁶ cells in pure samples, while for mixed samples, the lowest detection limit and ratio of NIES-843 strain were 2.88 × 10⁶ cells and 33.7%, respectively. The results provided a reference for the reasonable volume of the water sample in which the M. aeruginosa could be detected. Ribosomal protein biomarkers for identifying M. aeruginosa which were successfully detected from the field samples in Taihu Lake, indicated that the identification of M. aeruginosa by MALDI-TOF MS could be applied in field samples. Furthermore, different genetic types of M. aeruginosa strains were also detected at different locations in Taihu Lake, which revealed the diversity of M. aeruginosa and the detection power of MALDI-TOF MS at the strain level for the field samples. The sensitivity and detection power in the analysis of M. aeruginosa by the MALDI-TOF MS demonstrated the applicability of this method in routine environmental monitoring.

Quantitation of glutathione S-transferases in rice (Oryza sativa L.) roots exposed to cadmium by liquid chromatography-tandem mass spectrometry using isotope-labeled wing peptides as an internal standard

BACKGROUND

Plant glutathione S-transferases (GSTs, EC 2.5.1.18) are multifunctional enzymes involved in heavy metal cellular detoxification by conjugating the tripeptide (g-Glu-Cys-Gly) glutathione to heavy metals. Previous studies demonstrated that individual rice GSTs were differentially induced by heavy metal exposure at the mRNA transcript level. However, little information is available concerning changes in protein concentration of rice GSTs under heavy metal stress. Because the correlation between changes in protein concentration and gene expression under abiotic stress is poor, direct determination of rice GSTs protein concentrations during cadmium (Cd) exposure is a more effective and reliable approach to explore possible mechanisms of rice Cd translocation and accumulation.

RESULTS

This study established an optimized and advanced liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based targeted proteomics assay for quantification of OsGSTF14 and OsGSTU6 proteins in Cd-stressed rice roots. The tryptic signature peptides were chosen as surrogate analytes and winged peptides containing the isotope-labeled signature peptides were used as the internal standards. The signature peptides exhibited good linearity in the range of 0.6-60 and 0.3-30 nM, respectively. The limit of detection and limit of quantification were 4.5 and 14.5 µg/g for OsGSTF14, respectively, and 2.1 and 7.0 µg/g for OsGSTU6. The spiking recoveries rates at low, medium and high levels were in the range of 72.5-93.4%, with intra- and inter-day precisions of 5.5-9.1 and 4.2-10.2%, respectively.

CONCLUSIONS

The assay successfully quantified the temporal and dose responses of OsGSTF14 and OsGSTU6 proteins in Cd-stressed rice roots, with good accuracy, precision and high-throughput. This assay will have significant application in developing quantification methods of other proteins in Cd-stressed rice, which may provide more insight into the mechanisms of Cd translocation and accumulation in rice.

Nanomaterial and toxicity: what can proteomics tell us about the nanotoxicology?

1. In the last few years, a substantial scientific work is focused to identify the potential toxicity of nanomaterials by studying the cellular pathways under in vitro and in vivo conditions. Owing to high surface area to volume ratio nanoparticles (NPs) can pass through cell membranes which might be responsible for creating adverse interactions in biological systems. Simultaneously, researchers are also interested to assess the fate of NP inside the living system, which may lead to altered protein expression as well as protein corona formation. 2. According to published reports, NP-mediated toxicity involves altered cellular system including cell morphology, cell differentiation, cell metabolism, cell mobility, cellular immunity, which is derived from the side effects of nanoformulation and leading to apoptosis and necrosis. These results indicate the existence of potential toxic effect of these particles to human health. 3. The advent of proteomics with sophisticated technical improvement coupled with advanced bioinformatics has led to identify altered proteins due to nanomaterial exposure that could provide a new avenue to biomarker discovery. 4. This review aims to provide the current status of safe production and use of nanomaterials.

Issues and applications in label-free quantitative mass spectrometry

To address the challenges associated with differential expression proteomics, label-free mass spectrometric protein quantification methods have been developed as alternatives to array-based, gel-based, and stable isotope tag or label-based approaches. In this paper, we focus on the issues associated with label-free methods that rely on quantitation based on peptide ion peak area measurement. These issues include chromatographic alignment, peptide qualification for quantitation, and normalization. In addressing these issues, we present various approaches, assembled in a recently developed label-free quantitative mass spectrometry platform, that overcome these difficulties and enable comprehensive, accurate, and reproducible protein quantitation in highly complex protein mixtures from experiments with many sample groups. As examples of the utility of this approach, we present a variety of cases where the platform was applied successfully to assess differential protein expression or abundance in body fluids, in vitro nanotoxicology models, tissue proteomics in genetic knock-in mice, and cell membrane proteomics.

Divide and conquer: the application of organelle proteomics to heart failure

Chronic heart failure is a worldwide cause of mortality and morbidity and is the final outcome of a number of different etiologies. This reflects both the complexity of the disease and our incomplete understanding of its underlying molecular mechanisms. One experimental approach to address this is to study subcellular organelles and how their functions are activated and synchronized under physiological and pathological conditions. In this review, we discuss the application of proteomic technologies to organelles and how this has deepened our perception of the cellular proteome and its alterations with heart failure. The use of proteomics to monitor protein quantity and posttranslational modifications has revealed a highly intricate and sophisticated level of protein regulation. Posttranslational modifications have the potential to regulate organelle function and interplay most likely by targeting both structural and signaling proteins throughout the cell, ultimately coordinating their responses. The potentials and limitations of existing proteomic technologies are also discussed emphasizing that the development of novel methods will enhance our ability to further investigate organelles and decode intracellular communication.

Functional proteomics to dissect tyrosine kinase signalling pathways in cancer

Advances in the generation and interpretation of proteomics data have spurred a transition from focusing on protein identification to functional analysis. Here we review recent proteomics results that have elucidated new aspects of the roles and regulation of signal transduction pathways in cancer using the epidermal growth factor receptor (EGFR), ERK and breakpoint cluster region (BCR)-ABL1 networks as examples. The emerging theme is to understand cancer signalling as networks of multiprotein machines which process information in a highly dynamic environment that is shaped by changing protein interactions and post-translational modifications (PTMs). Cancerous genetic mutations derange these protein networks in complex ways that are tractable by proteomics.