Target identification by chromatographic co-elution: monitoring of drug-protein interactions without immobilization or chemical derivatization.

Bioactive molecules typically mediate their biological effects through direct physical association with one or more cellular proteins. The detection of drug-target interactions is therefore essential for the characterization of compound mechanism of action and off-target effects, but generic label-free approaches for detecting binding events in biological mixtures have remained elusive. Here, we report a method termed target identification by chromatographic co-elution (TICC) for routinely monitoring the interaction of drugs with cellular proteins under nearly physiological conditions in vitro based on simple liquid chromatographic separations of cell-free lysates. Correlative proteomic analysis of drug-bound protein fractions by shotgun sequencing is then performed to identify candidate target(s). The method is highly reproducible, does not require immobilization or derivatization of drug or protein, and is applicable to diverse natural products and synthetic compounds. The capability of TICC to detect known drug-protein target physical interactions (K(d) range: micromolar to nanomolar) is demonstrated both qualitatively and quantitatively. We subsequently used TICC to uncover the sterol biosynthetic enzyme Erg6p as a novel putative anti-fungal target. Furthermore, TICC identified Asc1 and Dak1, a core 40 S ribosomal protein that represses gene expression, and dihydroxyacetone kinase involved in stress adaptation, respectively, as novel yeast targets of a dopamine receptor agonist.

Synthetic peptide arrays for pathway-level protein monitoring by liquid chromatography-tandem mass spectrometry.

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including "label-free" quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations.

A lentiviral functional proteomics approach identifies chromatin remodeling complexes important for the induction of pluripotency.

Protein complexes and protein-protein interactions are essential for almost all cellular processes. Here, we establish a mammalian affinity purification and lentiviral expression (MAPLE) system for characterizing the subunit compositions of protein complexes. The system is flexible (i.e. multiple N- and C-terminal tags and multiple promoters), is compatible with Gateway cloning, and incorporates a reference peptide. Its major advantage is that it permits efficient and stable delivery of affinity-tagged open reading frames into most mammalian cell types. We benchmarked MAPLE with a number of human protein complexes involved in transcription, including the RNA polymerase II-associated factor, negative elongation factor, positive transcription elongation factor b, SWI/SNF, and mixed lineage leukemia complexes. In addition, MAPLE was used to identify an interaction between the reprogramming factor Klf4 and the Swi/Snf chromatin remodeling complex in mouse embryonic stem cells. We show that the SWI/SNF catalytic subunit Smarca2/Brm is up-regulated during the process of induced pluripotency and demonstrate a role for the catalytic subunits of the SWI/SNF complex during somatic cell reprogramming. Our data suggest that the transcription factor Klf4 facilitates chromatin remodeling during reprogramming.

Molecular mechanisms of chronic kidney transplant rejection via large-scale proteogenomic analysis of tissue biopsies.

The most common cause of kidney transplant failure is the poorly characterized histopathologic entity interstitial fibrosis and tubular atrophy (IFTA). There are no known unifying mechanisms, no effective therapy, and no proven preventive strategies. Possible mechanisms include chronic immune rejection, inflammation, drug toxicity, and chronic kidney injury from secondary factors. To gain further mechanistic insight, we conducted a large-scale proteogenomic study of kidney transplant biopsies with IFTA of varying severity. We acquired proteomic data using tandem mass spectrometry with subsequent quantification, analysis of differential protein expression, validation, and functional annotations to known molecular networks. We performed genome-wide expression profiling in parallel. More than 1400 proteins with unique expression profiles traced the progression from normal transplant biopsies to biopsies with mild to moderate and severe disease. Multiple sets of proteins were mapped to different functional pathways, many increasing with histologic severity, including immune responses, inflammatory cell activation, and apoptosis consistent with the chronic rejection hypothesis. Two examples include the extensive population of the alternative rather than the classical complement pathway, previously not appreciated for IFTA, and a comprehensive control network for the actin cytoskeleton and cell signaling of the acute-phase response. In summary, this proteomic effort using kidney tissue contributes mechanistic insight into several biologic processes associated with IFTA.

Single amino acid resolution of proteolytic fragments generated in individual cells.

The complex nature of enzyme regulation mandates that enzyme activity profiles be measured in the context of the intact cell. Single-cell capillary electrophoresis (CE) coupled with laser-induced fluorescence is a powerful approach for quantitation and separation of analytes present in small samples and single live cells; however, it does not allow for the definitive identification of the reaction products. On the other hand, mass spectrometry (MS) is able to identify analytes but still lacks the requisite sensitivity for most single-cell analysis applications. Thus, it follows that by determining the relative amounts of reaction products generated in single cells using CE and by producing larger quantities of these products using bulk cell populations to identify them using MS, it is possible to determine enzyme activity profiles in single cells. In this study, the applicability of this approach was demonstrated by examining the intracellular fate of a protease substrate derived from the beta-amyloid precursor protein (beta-APP). In single live TF-1 cells, three distinct fragments were generated from the beta-APP peptide, which differed by a single uncharged amino acid. The CE measurements indicated that the proteolytic fragment profiles (i.e., the relative amounts of each fragment) were consistent from cell to cell but that they were different from those obtained in cell lysates. Furthermore, measurements obtained at the single cell level made it possible to observe a modest but statistically significant negative correlation between the total amount of beta-APP peptide loaded in cells and the fraction of peptide that remained intact. This study demonstrates how single-cell CE, MS, and peptide substrates can be combined to identify and measure enzyme activities in single live cells.

FZD4 Marks Lateral Plate Mesoderm and Signals with NORRIN to Increase Cardiomyocyte Induction from Pluripotent Stem Cell-Derived Cardiac Progenitors.

The identification of cell surface proteins on stem cells or stem cell derivatives is a key strategy for the functional characterization, isolation, and understanding of stem cell population dynamics. Here, using an integrated mass spectrometry- and microarray-based approach, we analyzed the surface proteome and transcriptome of cardiac progenitor cells (CPCs) generated from the stage-specific differentiation of mouse and human pluripotent stem cells. Through bioinformatics analysis, we have identified and characterized FZD4 as a marker for lateral plate mesoderm. Additionally, we utilized FZD4, in conjunction with FLK1 and PDGFRA, to further purify CPCs and increase cardiomyocyte (CM) enrichment in both mouse and human systems. Moreover, we have shown that NORRIN presented to FZD4 further increases CM output via proliferation through the canonical WNT pathway. Taken together, these findings demonstrate a role for FZD4 in mammalian cardiac development.

Targeted protein identification, quantification and reporting for high-resolution nanoflow targeted peptide monitoring.

Mass spectrometry-based targeted proteomic assays are experiencing a surge in awareness due to the diverse possibilities arising from the re-application of traditional LC-SRM technology. The FDA-approved quantitative LC-SRM-pipeline in drug discovery motivates the use to quantitatively validate putative proteomic biomarkers. However, complexity of biological specimens bears a huge challenge to identify, in parallel, specific peptides and proteins of interest from large biomarker candidate lists. Methods have been devised to increase scan speeds, improve detection specificity and verify quantitative SRM-features. In contrast, high-resolution mass spectrometers could be used to improve reliability and precision of targeted proteomics assays. Here, we present a new method for identifying, quantifying and reporting peptides in high-resolution targeted proteomics experiments performed on an orbitrap hybrid instrument using stable isotope-labeled internal reference peptides. This high precision targeted peptide monitoring (TPM) method has unique advantages over existing techniques, including the need to only detect the most abundant product ion of a given target for confident peptide identification using a scoring function that evaluates assay performance based on 1) m/z-mass accuracy, 2) retention time accuracy of observed species relative to prediction, and 3) retention time accuracy relative to internal reference peptides. Further, we show management of multiplexed precision TPM-assays using sentinel peptide standards. This article is part of a Special Issue entitled: From protein structures to clinical applications.

Identification of enzyme-converted peptide products from single cells using capillary electrophoresis and liquid chromatography-mass spectrometry.

Single-cell analysis using chemical methods, otherwise known as chemical cytometry, promises to provide significant leaps in understanding signaling processes which result in cellular behavior. Sensitive methods for chemical cytometry such as capillary electrophoresis can detect and quantify multiple targets; however, conclusive identification of detected analytes is required for useful data to be obtained. Here, we demonstrate a method for determining the identity of enzyme-converted peptide products from single cells using a combination of capillary electrophoresis and liquid chromatography-mass spectrometry (LC-MS).

Large-scale characterization and analysis of the murine cardiac proteome.

Recent advances in mass spectrometry and bioinformatics have provided the means to characterize complex protein landscapes from a wide variety of organisms and cell types. Development of standard proteomes exhibiting all of the proteins involved in normal physiology will facilitate the delineation of disease mechanisms. Here, we examine the wild-type cardiac proteome using data obtained from a subcellular fractionation protocol in combination with a multidimensional protein identification proteomics approach. We identified 4906 proteins which were allocated to either cytosolic, microsomal, mitochondrial matrix or mitochondrial membrane fractions with relative abundance values in each fraction. We subjected these proteins to hierarchical clustering, gene ontology terms analysis, immunoblotting, comparison to publicly available protein databases, comparison to 4 distinct cardiac transcriptomes, and finally, to 6 other related proteomic data sets. This study provides an exhaustive analysis of the cardiac proteome and is the first large-scale investigation of the subcellular location for over 2000 unannotated proteins. With the use of a subtractive transcriptomics approach, we have also extended our analysis to identify 'cardiac selective' factors in our proteome. Finally, using specific filtering criteria, we identified proteotypic peptides for subsequent use in targeted studies of both mouse and human. Therefore, we offer this as a major contribution to the advancement of the field of proteomics in cardiovascular research.

Biomarkers for early and late stage chronic allograft nephropathy by proteogenomic profiling of peripheral blood.

BACKGROUND: Despite significant improvements in life expectancy of kidney transplant patients due to advances in surgery and immunosuppression, Chronic Allograft Nephropathy (CAN) remains a daunting problem. A complex network of cellular mechanisms in both graft and peripheral immune compartments complicates the non-invasive diagnosis of CAN, which still requires biopsy histology. This is compounded by non-immunological factors contributing to graft injury. There is a pressing need to identify and validate minimally invasive biomarkers for CAN to serve as early predictors of graft loss and as metrics for managing long-term immunosuppression. METHODS: We used DNA microarrays, tandem mass spectroscopy proteomics and bioinformatics to identify genomic and proteomic markers of mild and moderate/severe CAN in peripheral blood of two distinct cohorts (n = 77 total) of kidney transplant patients with biopsy-documented histology. FINDINGS: Gene expression profiles reveal over 2400 genes for mild CAN, and over 700 for moderate/severe CAN. A consensus analysis reveals 393 (mild) and 63 (moderate/severe) final candidates as CAN markers with predictive accuracy of 80% (mild) and 92% (moderate/severe). Proteomic profiles show over 500 candidates each, for both stages of CAN including 302 proteins unique to mild and 509 unique to moderate/severe CAN. CONCLUSIONS: This study identifies several unique signatures of transcript and protein biomarkers with high predictive accuracies for mild and moderate/severe CAN, the most common cause of late allograft failure. These biomarkers are the necessary first step to a proteogenomic classification of CAN based on peripheral blood profiling and will be the targets of a prospective clinical validation study.

High-resolution biomarker discovery: Moving from large-scale proteome profiling to quantitative validation of lead candidates.

Diverse proteomic techniques based on protein MS have been introduced to systematically characterize protein perturbations associated with disease. Progress in clinical proteomics is essential for personalized medicine, wherein treatments will be tailored to individual needs based on patient stratification using noninvasive disease monitoring procedures to reveal the most appropriate therapeutic targets. However, breakthroughs await the successful development and application of a robust proteomic pipeline capable of identifying and rigorously assessing the relevance of multiple candidate proteins as informative diagnostic and prognostic indicators or suitable drug targets involved in a pathological process. While steady progress has been made toward more comprehensive proteome profiling, the emphasis must now shift from in depth screening of reference samples to stringent quantitative validation of selected lead candidates in a broader clinical context. Here, we present an overview of the emerging proteomic strategies for high-throughput protein detection focused primarily on targeted MS/MS as the basis for biomarker verification in large clinical cohorts. We discuss the conceptual promise and practical pitfalls of these methods in terms of achieving higher dynamic range, higher throughput, and more reliable quantification, highlighting research avenues that merit additional inquiry.

Evaluation of data-dependent versus targeted shotgun proteomic approaches for monitoring transcription factor expression in breast cancer.

In breast cancer, there is a significant degree of molecular diversity among tumors. Multiple perturbations in signal transduction pathways impinge on transcriptional networks that in turn dictate malignant transformation and metastatic progression. Detailed knowledge of the sequence-specific transcription factors that become activated or repressed within a tumor and comparison of their relative levels of expression in cancer versus normal tissue should therefore provide insight into disease mechanisms, improving patient stratification and facilitating personalized treatment. While high-throughput tandem mass spectrometry methods for global proteome profiling have been developed, existing approaches have limited sensitivity and are often unable to detect low-abundance transcription factors in a complex biological specimen like a biopsy or tumor cell extract. To this end, we have undertaken a systematic comparative evaluation of three MS/MS methods for the ability to detect reference transcription factors spiked in known amounts into a cell-free breast cancer nuclear extract: Data-Dependent Acquisition (DDA), wherein precursor ion intensity dictates selection for fragmentation; Targeted Peptide Monitoring (TPM), a directed approach using successive isolation and fragmentation of predefined m/ z ratios; and Multiple Reaction Monitoring (MRM), in which specific precursor ion to product ion transitions are selectively monitored. Through a series of controlled, parallel benchmarking experiments, we have determined the relative figures-of-merit of each approach, and have established that prior knowledge of signature proteotypic peptides markedly improves overall detection sensitivity, reliability, and quantification.

Isolation and angiogenesis by endothelial progenitors in the fetal liver.

Endothelial progenitor cells (EPCs) have significant therapeutic potential. However, the low quantity of such cells available from bone marrow and their limited capacity to proliferate in culture make their use difficult. Here, we present the first definitive demonstration of the presence of true EPCs in murine fetal liver capable of forming blood vessels in vivo connected to the host's vasculature after transplantation. This population is particularly interesting because it can be obtained at high yield and has a high angiogenic capacity as compared with bone marrow-derived EPCs. The EPC capacity is contained within the CD31+Sca1+ cell subset. We demonstrate that these cells are dependent for survival and proliferation on a feeder cell monolayer derived from the fetal liver. In addition, we describe a novel and easy method for the isolation and ex vivo proliferation of these EPCs. Finally, we used gene expression profiling and tandem mass spectrometry proteomics to examine the fetal liver endothelial progenitors and the feeder cells to identify possible proangiogenic growth factor and endothelial differentiation-associated genes.