Characterization of multiple myeloma vesicles by label‐free relative quantitation

Multiple myeloma (MM) is a hematological malignancy caused by a microenviromentally aided persistence of plasma cells in the bone marrow. The role that extracellular vesicles (EVs), microvesicles and exosomes, released by MM cells have in cell‐to‐cell communication and signaling in the bone marrow is currently unknown. This paper describes the proteomic content of EVs derived from MM.1S and U266 MM cell lines. First, we compared the protein identifications between the vesicles and cellular lysates of each cell line finding a large overlap in protein identifications. Next, we applied label‐free spectral count quantitation to determine proteins with differential abundance between the groups. Finally, we used bioinformatics to categorize proteins with significantly different abundances into functional groups. The results illustrate the first use of label‐free spectral counting applied to determine relative protein abundances in EVs.     

DeepQuanTR: MALDI‐MS‐based label‐free quantification of proteins in complex biological samples

The quantification of changes in protein abundance in complex biological specimens is essential for proteomic studies in basic and applied research. Here we report on the development and validation of the DeepQuanTR software for identification and quantification of differentially expressed proteins using LC‐MALDI‐MS. Following enzymatic digestion, HPLC peptide separation and normalization of MALDI‐MS signal intensities to the ones of internal standards, the software extracts peptide features, adjusts differences in HPLC retention times and performs a relative quantification of features. The annotation of multiple peptides to the corresponding parent protein allows the definition of a Protein Quant Value, which is related to protein abundance and which allows inter‐sample comparisons. The performance of DeepQuanTR was evaluated by analyzing 24 samples deriving from human serum spiked with different amounts of four proteins and eight complex samples of vascular proteins, derived from surgically resected human kidneys with cancer following ex vivo perfusion with a reactive ester biotin derivative. The identification and experimental validation of proteins, which were differentially regulated in cancerous lesions as compared with normal kidney, was used to demonstrate the power of DeepQuanTR. This software, which can easily be used with established proteomic methodologies, facilitates the relative quantification of proteins derived from a wide variety of different samples.     

Study of monocyte membrane proteome perturbation during lipopolysaccharide‐induced tolerance using iTRAQ‐based quantitative proteomic approach

Human monocytes' exposure to low‐level lipopolysaccharide (LPS) induces temporary monocytic insensitivity to subsequent LPS challenge. The underlying mechanism of this phenomenon could have important clinical utilities in preventing and/or treating severe infections. In this study, we used an iTRAQ‐based quantitative proteomic approach to comprehensively characterize the membrane proteomes of monocytes before and after LPS exposure. We identified a total of 1651 proteins, of which 53.6% were membrane proteins. Ninety‐four percent of the proteins were quantified and 255 proteins were shown to be tightly regulated by LPS. Subcellular location analysis revealed organelle‐specific response to LPS exposure: more than 90% of identified mitochondrial membrane proteins were significant downregulated, whereas the majority of proteins from other organelles such as ER, Golgi and ribosome were upregulated. Moreover, we found that the expression of most receptors potentially involved in LPS signal pathway (CD14, toll‐like receptor 4, CD11/CD18 complex) were substantially decreased, while the expression of molecules involved in LPS neutralization were enhanced after LPS challenge. Together, these findings could be of significance in understanding the mechanism of LPS tolerance and provide values for designing new approaches for regulating monocytic responses in sepsis patients.     

Differential label‐free quantitative proteomic analysis of avian eggshell matrix and uterine fluid proteins associated with eggshell mechanical property

Eggshell strength is a crucial economic trait for table egg production. During the process of eggshell formation, uncalcified eggs are bathed in uterine fluid that plays regulatory roles in eggshell calcification. In this study, a label‐free MS‐based protein quantification technology was used to detect differences in protein abundance between eggshell matrix from strong and weak eggs (shell matrix protein from strong eggshells and shell matrix protein from weak eggshells) and between the corresponding uterine fluids bathing strong and weak eggs (uterine fluid bathing strong eggs and uterine fluid bathing weak eggs) in a chicken population. Here, we reported the first global proteomic analysis of uterine fluid. A total of 577 and 466 proteins were identified in uterine fluid and eggshell matrix, respectively. Of 447 identified proteins in uterine fluid bathing strong eggs, up to 357 (80%) proteins were in common with proteins in uterine fluid bathing weak eggs. Similarly, up to 83% (328/396) of the proteins in shell matrix protein from strong eggshells were in common with the proteins in shell matrix protein from weak eggshells. The large amount of common proteins indicated that the difference in protein abundance should play essential roles in influencing eggshell strength. Ultimately, 15 proteins mainly relating to eggshell matrix specific proteins, calcium binding and transportation, protein folding and sorting, bone development or diseases, and thyroid hormone activity were considered to have closer association with the formation of strong eggshell.     

A label‐free internal standard method for the differential analysis of bioactive lupin proteins using nano HPLC‐Chip coupled with Ion Trap mass spectrometry

Quantitative proteomics based on MS is useful for pointing out the differences in some food proteomes relevant to human nutrition. Stable isotope label‐free (SIF) techniques are suitable for comparing an unlimited number of samples by the use of relatively simple experimental workflows. We have developed an internal standard label‐free method based on the intensities of peptide precursor ions from MS/MS spectra, collected in data dependent runs, for the simultaneous qualitative characterization and relative quantification of storage proteins of Lupinus albus seeds in protein extracts of four lupin cultivars (cv Adam, Arés, Lucky, Multitalia). The use of an innovative microfluidic system, the HPLC‐Chip, coupled with a classical IT mass spectrometer, has allowed a complete qualitative characterization of all proteins. In particular, the homology search mode has permitted to identify single amino acid substitutions in the sequences of vicilins (β‐conglutin precursor and vicilin‐like protein). The MS/MS sequencing of substituted peptides confirms the high heterogeneity of vicilins according to the peculiar characteristics of the vicilin‐encoding gene family. Two suitable bioinformatics parameters were optimized for the differential analyses of the main bioactive proteins: the “normalized protein average of common reproducible peptides” (N‐ACRP) for γ‐conglutin, which is a homogeneous protein, and the “normalized protein mean peptide spectral intensity” (N‐MEAN) for the highly heterogenous class of the vicilins.     

LFQuant: A label‐free fast quantitative analysis tool for high‐resolution LC‐MS/MS proteomics data

Database searching based methods for label‐free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross‐assignment among different runs. Here, we present a new label‐free fast quantitative analysis tool, LFQuant, for high‐resolution LC‐MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large‐scale label‐free data with fractionation such as SDS‐PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL‐Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/ .     

Temporal proteomic analysis of IGF‐1R signalling in MCF‐7 breast adenocarcinoma cells

Dysregulation of the insulin‐like growth factor 1 receptor signalling network is implicated in tumour growth and resistance to chemotherapy. We explored proteomic changes resulting from insulin‐like growth factor 1 stimulation of MCF‐7 adenocarcinoma cells as a function of time. Quantitative analysis using iTRAQ? reagents and 2‐D LC‐MS/MS analysis of three biological replicates resulted in the identification of 899 proteins (p≤0.05) with an estimated mean false‐positive rate of 2.6%. Quantitative protein expression was obtained from 681 proteins. Further analysis by supervised k‐means clustering identified five temporal clusters, which were submitted to the FuncAssociate server to assign overrepresented gene ontology terms. Proteins associated with vesicle transport were significantly overrepresented. We further analyzed our data set for proteins showing temporal significance using the software, extraction and analysis of differential gene expression, resulting in 20 significantly and temporally changing proteins (p≤0.1). These significant proteins play roles in, among others, altered glucose metabolism (lactate dehydrogenase A and pyruvate kinase M1/M2) and cellular stress (nascent polypeptide‐associated complex subunit α and heat shock (HSC70) proteins). We used multiple reaction monitoring to validate these interesting proteins and have revealed several differences in relative peptide expression corresponding to protein isoforms and variants.     

Assessment of reproducibility in depletion and enrichment workflows for plasma proteomics using label‐free quantitative data‐independent LC‐MS

Quantitation in plasma‐based proteomics necessitates the reproducible removal of highly abundant proteins to enable the less abundant proteins to be visible to the mass spectrometer. We have evaluated immunodepletion (proteoprep20) and enrichment (Bio‐Rad beads), as the current predominant approaches. Label‐free analysis offers an opportunity to estimate the effectiveness of this approach without incorporating chemical labels. Human plasma samples were used to quantitatively assess the reproducibility of these two methods using nano‐LC‐data‐independent acquisition MS. We have selected 18 candidate proteins and a comparison of both methodologies showed that both of the methods were reproducible and fell below 20% residual SD. With the same candidate proteins, individual inter‐day variability for the samples was also processed, allowing us to monitor instrument reproducibility. Overall, a total of 131 proteins were identified by both methods with 272 proteins identified by enrichment and 200 identified by immunodepletion. Reproducibility of measurements of the amount of protein in the processed sample for individual proteins is within analytically acceptable standards for both methodologies. This enables both methods to be used for biomarker studies. However, when sample is limited, enrichment is not suitable as larger volumes (>1.0 mL) are required. In experiments where sample is not limited then a greater number of proteins can be reliably identified using enrichment.     

iTRAQ proteomic analysis of N‐acetylmuramic acid mediated anti‐inflammatory capacity in LPS‐induced RAW 264.7 cells

Lactobacillus acidophilus probiotic bacteria have lasting beneficial health effects in the gastrointestinal tract, including protecting against pathogens, improving immunomodulation, and producing beneficial bacteria‐derived molecules. In lipopolysaccharide (LPS) induced RAW 264.7 cells treated with peptidoglycan or N‐acetylmuramic acid (NAM) from L. acidophilus, 390 differentially expressed proteins (8.76%) were identified by iTRAQ analysis, 257 (5.77%) of which were upregulated and 133 (2.99%) were downregulated under LPS‐induced conditions. Most of these proteins were grouped into the following inflammation‐related cellular signaling: lysosome pathway, calcium signaling pathway, and Toll‐like receptor (TLR) signaling pathway. Among them, clathrin, SERCA, and interleukin 1 receptor antagonist were differentially expressed to a significant degree in peptidoglycan or NAM pretreated RAW 264.7 cells. Bioinformatics analysis indicated that NAM may mediate an anti‐inflammatory process via a Ca²⁺‐dependent NF‐κB pathway. These observations reveal new insights into the molecular mechanisms involved in the suppression of LPS‐induced macrophage inflammation by L. acidophilus.     

Proteomic profiles of human lung adeno and squamous cell carcinoma using super‐SILAC and label‐free quantification approaches

Nonsmall cell lung cancer (NSCLC) accounts for 85% of lung cancers, and is subdivided into two major histological subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). There is an unmet need to further subdivide NSCLC according to distinctive molecular features that may be associated with responsiveness to therapies. Four primary tumor‐derived xenograft proteomes (two‐each ADC and SCC) were quantitatively compared by using a super‐SILAC labeling approach together with ultrahigh‐resolution MS. Proteins highly differentially expressed in the two subtypes were identified, including 30 that were validated in an independent cohort of 12 NSCLC primary tumor‐derived xenograft tumors whose proteomes were quantified by an alternative, label‐free shotgun MS methodology. The 30‐protein signature contains metabolism enzymes including phosphoglycerate dehydrogenase, which is more highly expressed in SCC, as well as a comprehensive set of cytokeratins and other components of the epithelial barrier, which is therefore distinctly different between ADC and SCC. These results demonstrate the utility of the super‐SILAC method for the characterization of primary tissues, and compatibility with datasets derived from different MS‐based platforms. The validation of proteome signatures of NSCLC subtypes supports the further development and application of MS‐based quantitative proteomics as a basis for precision classifications and treatments of tumors. All MS data have been deposited in the ProteomeXchange with identifier PXD000438 ( http://proteomecentral.proteomexchange.org/dataset/PXD000438 ).     

Mesenchymal stem cells promote cell invasion and migration and autophagy‐induced epithelial‐mesenchymal transition in A549 lung adenocarcinoma cells

Mesenchymal stem cells (MSCs) are recruited into the tumour microenvironment and promote tumour growth and metastasis. Tumour microenvironment‐induced autophagy is considered to suppress primary tumour formation by impairing migration and invasion. Whether these recruited MSCs regulate tumour autophagy and whether autophagy affects tumour growth are controversial. Our data showed that MSCs promote autophagy activation, reactive oxygen species production, and epithelial‐mesenchymal transition (EMT) as well as increased migration and invasion in A549 cells. Decreased expression of E‐cadherin and increased expression of vimentin and Snail were observed in A549 cells cocultured with MSCs. Conversely, MSC coculture‐mediated autophagy positively promoted tumour EMT. Autophagy inhibition suppressed MSC coculture‐mediated EMT and reduced A549 cell migration and invasion slightly. Furthermore, the migratory and invasive abilities of A549 cells were additional increased when autophagy was further enhanced by rapamycin treatment. Taken together, this work suggests that microenvironments containing MSCs can promote autophagy activation for enhancing EMT; MSCs also increase the migratory and invasive abilities of A549 lung adenocarcinoma cells. Mesenchymal stem cell‐containing microenvironments and MSC‐induced autophagy signalling may be potential targets for blocking lung cancer cell migration and invasion.     

A comparative proteomic analysis of HepG2 cells incubated by S(−) and R(+) enantiomers of anti‐coagulating drug warfarin

Warfarin is a commonly prescribed oral anti‐coagulant with narrow therapeutic index. It interferes with vitamin K cycle to achieve anti‐coagulating effects. Warfarin has two enantiomers, S(?) and R(+) and undergoes stereoselective metabolism, with the S(?) enantiomer being more effective. We reported that the intracellular protein profile in HepG2 cells incubated with S(?) and R(+) warfarin, using iTRAQ‐coupled 2‐D LC‐MS/MS. In samples incubated with S(?) and R(+) warfarin alone, the multi‐task protein Protein SET showed significant elevation in cells incubated with S(?) warfarin but not in those incubated with R(+) warfarin. In cells incubated with individual enantiomers of warfarin in the presence of vitamin K, protein disulfide isomerase A3 which is known as a glucose‐regulated protein, in cells incubated with S(?) warfarin was found to be down‐regulated compared to those incubated with R(+) warfarin. In addition, Protein DJ‐1 and 14‐3‐3 Proteinσ were down‐regulated in cells incubated with either S(?) or R(+) warfarin regardless of the presence of vitamin K. Our results indicated that Protein DJ‐1 may act as an enzyme for expression of essential enzymes in vitamin K cycle. Taken together, our findings provided molecular evidence on a comprehensive protein profile on warfarin–cell interaction, which may shed new lights on future improvement of warfarin therapy.     

Rho‐kinase inhibitor Y‐27632 increases cellular proliferation and migration in human foreskin fibroblast cells

The idea of direct differentiation of somatic cells into other differentiated cell types has attracted a great interest recently. Rho‐kinase inhibitor Y‐27632 (ROCKi) is a potential drug molecule, which has been reported to support the gene expressions typical for the chondrocytes, thus restricting their phenotypic conversion to fibroblastic cells upon the cellular expansion. In this study, we have investigated the short‐term biological responses of ROCKi to human primary foreskin fibroblasts. The fibroblast cells were exposed to 1 and 10 μM ROCKi treatments. A proteomics analysis revealed expression changes of 56 proteins, and a further protein pathway analysis suggested their association with the cell morphology, the organization, and the increased cellular movement and the proliferation. These functional responses were confirmed by a Cell‐IQ time‐lapse imaging analysis. Rho‐kinase inhibitor treatment increased the cellular proliferation up to twofold during the first 12 h, and a wound model based migration assay showed 50% faster filling of the mechanically generated wound area. Additionally, significantly less vinculin‐associated focal adhesions were present in the ROCKi‐treated cells. Despite the marked changes in the cell behavior, ROCKi was not able to induce the expression of the chondrocyte‐specific genes, such as procollagen α₁(II) and aggrecan.     

Rapid label‐free quantitative analysis of the E. coli BL21(DE3) inner membrane proteome

Biological membranes define cells and cellular compartments and are essential in regulating bidirectional flow of chemicals and signals. Characterizing their protein content therefore is required to determine their function, nevertheless, the comprehensive determination of membrane‐embedded sub‐proteomes remains challenging. Here, we experimentally characterized the inner membrane proteome (IMP) of the model organism E. coli BL21(DE3). We took advantage of the recent extensive re‐annotation of the theoretical E. coli IMP regarding the sub‐cellular localization of all its proteins. Using surface proteolysis of IMVs with variable chemical treatments followed by nanoLC‐MS/MS analysis, we experimentally identified ～45% of the expressed IMP in wild type E. coli BL21(DE3) with 242 proteins reported here for the first time. Using modified label‐free approaches we quantified 220 IM proteins. Finally, we compared protein levels between wild type cells and those over‐synthesizing the membrane‐embedded translocation channel SecYEG proteins. We propose that this proteomics pipeline will be generally applicable to the determination of IMP from other bacteria.     

Cross‐species analysis of nicotine‐induced proteomic alterations in pancreatic cells

Toxic compounds in tobacco, such as nicotine, may adversely affect pancreatic function. We aim to determine nicotine‐induced protein alterations in pancreatic cells, thereby revealing links between nicotine exposure and pancreatic disease. We compared the proteomic alterations induced by nicotine treatment in cultured pancreatic cells (mouse, rat, and human stellate cells and human duct cells) using MS‐based techniques, specifically SDS‐PAGE (gel) coupled with LC‐MS/MS and spectral counting. We identified thousands of proteins in pancreatic cells, hundreds of which were identified exclusively or in higher abundance in either nicotine‐treated or untreated cells. Interspecies comparisons of stellate cell proteins revealed several differentially abundant proteins (in nicotine treated versus untreated cells) common among the three species. Proteins appearing in all nicotine‐treated stellate cells include amyloid beta (A4), procollagen type VI alpha 1, integral membrane protein 2B, and toll‐interacting protein. Proteins that were differentially expressed upon nicotine treatment across cell lines were enriched in certain pathways, including nicotinic acetylcholine receptor, cytokine, and integrin signaling. At this analytical depth, we conclude that similar pathways are affected by nicotine, but alterations at the protein level among stellate cells of different species vary. Further interrogation of such pathways will lead to insights into the potential effect of nicotine on pancreatic cells at the biomolecular level and the extension of this concept to the effect of nicotine on pancreatic disease.