Multiplex Quantitative Proteomics Research Articles

NHS-Ester Tandem Labeling in One Pot Enables 48-Plex Quantitative Proteomics.

Stable-isotope labeling strategies are extensively used for multiplex quantitative proteomics. Hybrid-isotope labeling strategies that combine the use of isotopic mass difference labeling and isobaric tags can greatly increase sample multiplexity. In this work, we present a novel hybrid-isotope labeling approach that we termed NHS-ester tandem labeling in one pot (NETLOP). We first optimized 16-plex isobaric TMTpro labeling of lysine residues followed by 2-plex or 3-plex isotopic mTRAQ labeling of peptide N-termini, both of which with commercially available NHS-ester reactive reagents. We then demonstrated the utility of the NETLOP approach by labeling HeLa cell samples and performing proof-of-principle quantitative 32-plex and 48-plex proteomic analyses, each in a single LC-MS/MS experiment. Compared to current hybrid-isotope labeling methods, our NETLOP approach requires no sample cleanup between different labeling steps to minimize sample loss, induces no retention time shifts that compromise quantification accuracy, can be adapted to other NHS-ester isotopic labeling reagents to further increase multiplexity, and is compatible with samples from any origin in a wide array of biological and clinical proteomics applications.

Systematic Localization of Escherichia coli Membrane Proteins.

The molecular architecture and function of the Gram-negative bacterial cell envelope are dictated by protein composition and localization. Proteins that localize to the inner membranes (IM) and outer membranes (OM) of Gram-negative bacteria play critical and distinct roles in cellular physiology; however, approaches to systematically interrogate their distribution across both membranes and the soluble cell fraction are lacking. Here, we employed multiplexed quantitative mass spectrometry using tandem mass tag (TMT) labeling to assess membrane protein localization in a proteome-wide fashion by separating IM and OM vesicles from exponentially growing Escherichia coli K-12 cells on a sucrose density gradient. The migration patterns for >1,600 proteins were classified in an unbiased manner, accurately recapitulating decades of knowledge in membrane protein localization in E. coli For 559 proteins that are currently annotated as peripherally associated with the IM (G. Orfanoudaki and A. Economou, Mol Cell Proteomics 13:3674-3687, 2014, https://doi.org/10.1074/mcp.O114.041137) and that display potential for dual localization to either the IM or cytoplasm, we could allocate 110 proteins to the IM and 206 proteins to the soluble cell fraction based on their fractionation patterns. In addition, we uncovered 63 cases, in which our data disagreed with current localization annotation in protein databases. For 42 of these cases, we were able to find supportive evidence for our localization findings in the literature. We anticipate that our systems-level analysis of the E. coli membrane proteome will serve as a useful reference data set to query membrane protein localization, as well as to provide a novel methodology to rapidly and systematically map membrane protein localization in more poorly characterized Gram-negative species.IMPORTANCE Current knowledge of protein localization, particularly outer membrane proteins, is highly dependent on bioinformatic predictions. To date, no systematic experimental studies have directly compared protein localization spanning the inner and outer membranes of E. coli By combining sucrose density gradient fractionation of inner membrane (IM) and outer membrane (OM) proteins with multiplex quantitative proteomics, we systematically quantified localization patterns for >1,600 proteins, providing high-confidence localization annotations for 1,368 proteins. Of these proteins, we resolve the predominant localization of 316 proteins that currently have dual annotation (cytoplasmic and IM) in protein databases and identify new annotations for 42 additional proteins. Overall, we present a novel quantitative methodology to systematically map membrane proteins in Gram-negative bacteria and use it to unravel the biological complexity of the membrane proteome architecture in E. coli.

A Host Proteome Atlas of Streptococcus pyogenes Infection.

Multiplex quantitative proteomics analysis of mice infected with Group A Streptococcus reveals organ-specific biomarkers of infection.

BPI Fold-Containing Family A Member 2/Parotid Secretory Protein Is an Early Biomarker of AKI.

AKI is a major cause of morbidity and mortality and an important contributor to the development and progression of CKD. Molecular biomarkers that improve the detection and prognostication of AKI are therefore required. We assessed the utility as such of BPI fold-containing family A member 2 (BPIFA2), also known as parotid secretory protein, which we identified via a multiplex quantitative proteomics screen of acutely injured murine kidneys. In physiologic conditions, BPIFA2 is expressed specifically in the parotid glands and is abundant in salivary secretions. In our study, AKI induced Bpifa2 expression in the kidneys of mice within 3 hours. Furthermore, we detected BPIFA2 protein in plasma and urine in these models as early as 6 hours after injury. However, renal injury did not induce the expression of Bpifa2 in mice lacking Nur77, an immediate early gene expressed in the kidneys during AKI. Notably, patients with AKI had higher blood and urine levels of BPIFA2 than did healthy individuals. Together, our results reveal that BPIFA2 is a potential early biomarker of AKI.

Evaluation and Application of Dimethylated Amino Acids as Isobaric Tags for Quantitative Proteomics of the TGF-β/Smad3 Signaling Pathway.

Isobaric labeling has become a widespread tool for quantitative proteomic studies. Here, we report the development and evaluation of several dimethylated amino acids as novel isobaric tags for quantitative proteomics. Four-plex dimethylated alanine (DiAla), valine (DiVal), and leucine (DiLeu) have been synthesized, sharing common features of peptide tagging and reporter ion production. DiAla and DiLeu are shown to achieve complete labeling. These two tags' impacts on peptide fragmentation and quantitation are further evaluated using HEK293 cell lysate. DiAla labeling generates more abundant backbone fragmentation whereas DiLeu labeling produces more intense reporter ions. Nonetheless, both tags enable accurate quantitative analysis of HEK293 cell proteomes. DiAla and DiLeu tags are then applied to study the TGF-β/Smad3 pathway with four differentially treated mouse vascular smooth muscle (MOVAS) cells. Our MS data reveal proteome-wide changes of AdSmad3 as compared to the GFP control, consistent with previous findings of causing smooth muscle cell (SMC) dedifferentiation.1 Additionally, the other two novel mutations on the hub protein Smad3, Y226A, and D408H, show compromised TGF-β/Smad3-dependent gene transcription and reversed phenotypic switch. These results are further corroborated with Western blotting and demonstrate that the novel DiAla and DiLeu isobaric tagging reagents provide useful tools for multiplex quantitative proteomics.

Investigation of Pokemon-Regulated Proteins in Hepatocellular Carcinoma Using Mass Spectrometry-Based Multiplex Quantitative Proteomics

Pokemon is a transcription regulator involved in embryonic development, cellular differentiation and oncogenesis. It is aberrantly overexpressed in multiple human cancers including Hepatocellular carcinoma (HCC) and is considered as a promising biomarker for HCC. In this work, the isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics strategy was used to investigate the proteomic profile associated with Pokemon in human HCC cell line QGY7703 and human hepatocyte line HL7702. Samples were labeled with four-plex iTRAQ reagents followed by two-dimensional liquid chromatography coupled with tandem mass spectrometry analysis. A total of 24 differentially expressed proteins were selected as significant. Nine proteins were potentially up-regulated by Pokemon while 15 proteins were potentially down-regulated and many proteins were previously identified as potential biomarkers for HCC. Gene ontology (GO) term enrichment revealed that the listed proteins were mainly involved in DNA metabolism and biosynthesis process. The changes of glucose-6-phosphate 1-dehydrogenase (G6PD, up-regulated) and ribonucleoside-diphosphate reductase large sub-unit (RIM1, down-regulated) were validated by Western blotting analysis and denoted as Pokemon's function of oncogenesis. We also found that Pokemon potentially repressed the expression of highly clustered proteins (MCM3, MCM5, MCM6, MCM7) which played key roles in promoting DNA replication. Altogether, our results may help better understand the role of Pokemon in HCC and promote the clinical applications.

A multiplex quantitative proteomics strategy for protein biomarker studies in urinary exosomes

Urinary exosomes have received considerable attention as a potential biomarker source for the diagnosis of renal diseases. Notwithstanding, their use in protein biomarker research is hampered by the lack of efficient methods for vesicle isolation, lysis, and protein quantification. Here we report an improved ultracentrifugation-based method that facilitates the solubilization and removal of major impurities associated with urinary exosomes. A double-cushion sucrose/D(2)O centrifugation step was used after a two-step differential centrifugation to separate exosomes from the heavier vesicles. After the removal of uromodulin, 378 and 79 unique proteins were identified, respectively, in low- and high-density fractions. Comparison of our data with two previously published data sets helped to define proteins commonly found in urinary exosomes. Lysis, protein extraction, and in-solution digestion of exosomes were then optimized for MudPIT application. More than a hundred exosomal proteins were quantified by four-plex iTRAQ analysis of single and pooled samples from two different age groups. For healthy men, six proteins (TSN1, PODXL, IDHC, PPAP, ACBP, and ANXA5) showed significant expression differences between exosome pools of those aged 25-50 and 50-70 years old. Thus, exosomes isolated by our method provide the basis for the development of robust quantitative methods for protein biomarker research.

Discovery of biomarker candidates for coronary artery disease from an APOE‐knock out mouse model using iTRAQ‐based multiplex quantitative proteomics

Due to the lack of precise markers indicative of its occurrence and progression, coronary artery disease (CAD), the most common type of heart diseases, is currently associated with high mortality in the United States. To systemically identify novel protein biomarkers associated with CAD progression for early diagnosis and possible therapeutic intervention, we employed an iTRAQ-based quantitative proteomic approach to analyze the proteome changes in the plasma collected from a pair of wild-type versus apolipoprotein E knockout (APOE(-/-) ) mice which were fed with a high fat diet. In a multiplex manner, iTRAQ serves as the quantitative 'in-spectra' marker for 'cross-sample' comparisons to determine the differentially expressed/secreted proteins caused by APOE knock-out. To obtain the most comprehensive proteomic data sets from this CAD-associated mouse model, we applied both MALDI and ESI-based mass spectrometric (MS) platforms coupled with two different schemes of multidimensional liquid chromatography (2-D LC) separation. We then comparatively analyzed a series of the plasma samples collected at 6 and 12 wk of age after the mice were fed with fat diets, where the 6- or 12-wk time point represents the early or intermediate phase of the fat-induced CAD, respectively. We then categorized those proteins showing abundance changes in accordance with APOE depletion. Several proteins such as the γ and β chains of fibrinogen, apolipoprotein B, apolipoprotein C-I, and thrombospondin-4 were among the previously known CAD markers identified by other methods. Our results suggested that these unbiased proteomic methods are both feasible and a practical means of discovering potential biomarkers associated with CAD progression.

Defining the response of a microorganism to temperatures that span its complete growth temperature range (−2°C to 28°C) using multiplex quantitative proteomics

The growth of all microorganisms is limited to a specific temperature range. However, it has not previously been determined to what extent global protein profiles change in response to temperatures that incrementally span the complete growth temperature range of a microorganism. As a result it has remained unclear to what extent cellular processes (inferred from protein abundance profiles) are affected by growth temperature and which, in particular, constrain growth at upper and lower temperature limits. To evaluate this, 8-plex iTRAQ proteomics was performed on the Antarctic microorganism, Methanococcoides burtonii. Methanococcoides burtonii was chosen due to its importance as a model psychrophilic (cold-adapted) member of the Archaea, and the fact that proteomic methods, including subcellular fractionation procedures, have been well developed. Differential abundance patterns were obtained for cells grown at seven different growth temperatures (-2°C, 1°C, 4°C, 10°C, 16°C, 23°C, 28°C) and a principal component analysis (PCA) was performed to identify trends in protein abundances. The multiplex analysis enabled three largely distinct physiological states to be described: cold stress (-2°C), cold adaptation (1°C, 4°C, 10°C and 16°C), and heat stress (23°C and 28°C). A particular feature of the thermal extremes was the synthesis of heat- and cold-specific stress proteins, reflecting the important, yet distinct ways in which temperature-induced stress manifests in the cell. This is the first quantitative proteomic investigation to simultaneously assess the response of a microorganism to numerous growth temperatures, including the upper and lower growth temperatures limits, and has revealed a new level of understanding about cellular adaptive responses.

Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics

Discovery of biomarker candidates for coronary artery disease from an APOE-knock out mouse model using iTRAQ-based multiplex quantitative proteomics

Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics

Accurate quantification of protein expression in biological systems is an increasingly important part of proteomics research. Incorporation of differential stable isotopes in samples for relative protein quantification has been widely used. Stable isotope incorporation at the peptide level using dimethyl labeling is a reliable, cost-effective and undemanding procedure that can be easily automated and applied in high-throughput proteomics experiments. Although alternative multiplex quantitative proteomics approaches introduce isotope labels at the organism level ('stable isotope labeling by amino acids in cell culture' (SILAC)) or enable the simultaneous analysis of eight samples (isobaric tagging for relative and absolute quantification (iTRAQ)), stable isotope dimethyl labeling is advantageous in that it uses inexpensive reagents and is applicable to virtually any sample. We describe in-solution, online and on-column protocols for stable isotope dimethyl labeling of sample amounts ranging from sub-micrograms to milligrams. The labeling steps take approximately 60-90 min, whereas the full protocol including digestion and (two-dimensional) liquid chromatography-mass spectrometry takes approximately 1.5-3 days to complete.

O3-01-03: Multiplex quantitative proteomics of human cerebral spinal fluid from patients with neurodegenerative diseases

Background & Objective: Biomarkers are needed to assist in the diagnosis and medical management of various neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and dementia with Lewy body (DLB) diseases. Method: We have employed a multiplex quantitative proteomics method, isobaric Tagging for Relative and Absolute protein Quantification (iTRAQ), in conjunction with multidimensional chromatography, followed by tandem mass spectrometry (MS), to simultaneously measure relative changes in the proteome of human cerebrospinal fluid (CSF) obtained from the lumbar cistern of patients with AD (n 10), PD (n 10), or DLB (n 5) as well as from age-matched controls (n 10). Subsequent pathologic verification was obtained in all cases of AD and DLB. PD patients and age-matched controls had no change in diagnosis with follow-up evaluations for at least 3 years after lumbar tap. Proteomic results demonstrated that among 1,540 identified proteins, quantitative changes in 154, 81, and 113 proteins were associated with AD, PD, and DLB, respectively. Eight unique proteins were validated by Western blot. Using paired combinations of these validated CSF protein biomarkers, comparison among the four groups while holding specificity at 95% gave sensitivity of 100% for AD, 78% for PD, and 50% for DLB. Conclusion: Here, we have presented the most comprehensive characterization of the adult human CSF proteome. Although these results require confirmation in larger patient populations, our quantitative proteomics of CSF allowed us to generate small protein panels that distinguished among AD, DLB, PD, and controls with high specificity and moderate to high sensitivity. This approach may be developed further into even more robust CSF protein biomarker panels for AD, DLB, and PD patients.