Paolo Cifani

Critical Comparison of Multidimensional Separation Methods for Increasing Protein Expression Coverage

We present a comparison of two-dimensional separation methods and how they affect the degree of coverage of protein expression in complex mixtures. We investigated the relative merits of various protein and peptide separations prior to acidic reversed-phase chromatography directly coupled to an ion trap mass spectrometer. The first dimensions investigated were density gradient organelle fractionation of cell extracts, 1D SDS-PAGE protein separation followed by digestion by trypsin or GluC proteases, strong cation exchange chromatography, and off-gel isoelectric focusing of tryptic peptides. The number of fractions from each first dimension and the total data accumulation RP-HPLC-MS/MS time was kept constant and the experiments were run in triplicate. We find that the most critical parameters are the data accumulation time, which defines the level of under-sampling and the avoidance of peptides from high expression level proteins eluting over the entire gradient.

Quantitative analysis of a phosphoproteome readily altered by the protein kinase CK2 inhibitor quinalizarin in HEK-293T cells.

CK2 is an extremely pleiotropic Ser/Thr protein kinase, responsible for the generation of a large proportion of the human phosphoproteome and implicated in a wide variety of biological functions. CK2 plays a global role as an anti-apoptotic agent, a property which is believed to partially account for the addiction of many cancer cells to high CK2 levels. To gain information about the CK2 targets whose phosphorylation is primarily implicated in its pro-survival signaling advantage has been taken of quinalizarin (QZ) a cell permeable fairly specific CK2 inhibitor, previously shown to be able to block endogenous CK2 triggering an apoptotic response. HEK-293T cells either treated or not for 3h with 50μM QZ were exploited to perform a quantitative SILAC phosphoproteomic analysis of phosphosites readily responsive to QZ treatment. Our analysis led to the identification of 4883 phosphosites, belonging to 1693 phosphoproteins. 71 phosphosites (belonging to 47 proteins) underwent a 50% or more decreased occupancy upon QZ treatment. Almost 50% of these fulfilled the typical consensus sequence recognized by CK2 (S/T-x-x-E/D/pS) and in several cases were validated as bona fide substrates of CK2 either based on data in the literature or by performing in vitro phosphorylation experiments with purified proteins. The majority of the remaining phosphosites drastically decreased upon QZ treatment display the pS/T-P motif typical of proline directed protein kinases and a web logo extracted from them differentiates from the web logo extracted from all the proline directed phosphosites quantified during our analysis (1151 altogether). A paradoxical outcome of our study was the detection of 116 phosphosites (belonging to 92 proteins altogether) whose occupancy is substantially increased (50% or more), rather than decreased by QZ treatment: 40% of these display the typical motif recognized by proline directed kinases, while about 25% fulfill the CK2 consensus. Collectively taken our data on one side have led to the disclosure of a subset of CK2 targets which are likely to be implicated in the early steps of CK2 signaling counteracting apoptosis, on the other they provide evidence for the existence of side and off-target effects of the CK2 inhibitor quinalizarin, paving the road toward the detection of other kinases susceptible to this compound. This article is part of a Special Issue entitled: Medical Proteomics.

Relative quantification of membrane proteins in wild-type and prion protein (PrP)-knockout cerebellar granule neurons.

Approximately 25% of eukaryotic proteins possessing homology to at least two transmembrane domains are predicted to be embedded in biological membranes. Nevertheless, this group of proteins is not usually well represented in proteome-wide experiments due to their refractory nature. Here we present a quantitative mass spectrometry-based comparison of membrane protein expression in cerebellar granule neurons grown in primary culture that were isolated from wild-type mice and mice lacking the cellular prion protein. This protein is a cell-surface glycoprotein that is mainly expressed in the central nervous system and is involved in several neurodegenerative disorders, though its physiological role is unclear. We used a low specificity enzyme α-chymotrypsin to digest membrane proteins preparations that had been separated by SDS-PAGE. The resulting peptides were labeled with tandem mass tags and analyzed by MS. The differentially expressed proteins identified using this approach were further analyzed by multiple reaction monitoring to confirm the expression level changes.

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease.

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high‐accuracy MS in combination with high‐resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism‐focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high‐resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.

Genomics of primary chemoresistance and remission induction failure in paediatric and adult acute myeloid leukaemia

Cure rates of children and adults with acute myeloid leukaemia (AML) remain unsatisfactory partly due to chemotherapy resistance. We investigated the genetic basis of AML in 107 primary cases by sequencing 670 genes mutated in haematological malignancies. SETBP1, ASXL1 and RELN mutations were significantly associated with primary chemoresistance. We identified genomic alterations not previously described in AML, together with distinct genes that were significantly overexpressed in therapy‐resistant AML. Defined gene mutations were sufficient to explain primary induction failure in only a minority of cases. Thus, additional genetic or molecular mechanisms must cause primary chemoresistance in paediatric and adult AML.

A High-Efficiency Cellular Extraction System for Biological Proteomics.

Recent developments in quantitative high-resolution mass spectrometry have led to significant improvements in the sensitivity and specificity of the biochemical analyses of cellular reactions, protein-protein interactions, and small-molecule-drug discovery. These approaches depend on cellular proteome extraction that preserves native protein activities. Here, we systematically analyzed mechanical methods of cell lysis and physical protein extraction to identify those that maximize the extraction of cellular proteins while minimizing their denaturation. Cells were mechanically disrupted using Potter-Elvehjem homogenization, probe- or adaptive-focused acoustic sonication, and were in the presence of various detergents, including polyoxyethylene ethers and esters, glycosides, and zwitterions. Using fluorescence spectroscopy, biochemical assays, and mass spectrometry proteomics, we identified the combination of adaptive focused acoustic (AFA) sonication in the presence of a binary poloxamer-based mixture of octyl-β-glucoside and Pluronic F-127 to maximize the depth and yield of the proteome extraction while maintaining native protein activity. This binary poloxamer extraction system allowed for native proteome extraction comparable in coverage to the proteomes extracted using denaturing SDS or guanidine-containing buffers, including the efficient extraction of all major cellular organelles. This high-efficiency cellular extraction system should prove useful for a variety of cell biochemical studies, including structural and functional proteomics.

MEF2C phosphorylation is required for chemotherapy resistance in acute myeloid leukemia

In acute myeloid leukemia (AML), chemotherapy resistance remains prevalent and poorly understood. Using functional proteomics of patient AML specimens, we identified MEF2C S222 phosphorylation as a specific marker of primary chemoresistance. We found that Mef2cS222A/S222A knock-in mutant mice engineered to block MEF2C phosphorylation exhibited normal hematopoiesis, but were resistant to leukemogenesis induced by MLL-AF9 MEF2C phosphorylation was required for leukemia stem cell maintenance and induced by MARK kinases in cells. Treatment with the selective MARK/SIK inhibitor MRT199665 caused apoptosis and conferred chemosensitivity in MEF2C-activated human AML cell lines and primary patient specimens, but not those lacking MEF2C phosphorylation. These findings identify kinase-dependent dysregulation of transcription factor control as a determinant of therapy response in AML, with immediate potential for improved diagnosis and therapy for this disease.Significance: Functional proteomics identifies phosphorylation of MEF2C in the majority of primary chemotherapy-resistant AML. Kinase-dependent dysregulation of this transcription factor confers susceptibility to MARK/SIK kinase inhibition in preclinical models, substantiating its clinical investigation for improved diagnosis and therapy of AML. Cancer Discov; 8(4); 478-97. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 371.

Proteomic analysis of breast tumors confirms the mRNA intrinsic molecular subtypes using different classifiers: a large-scale analysis of fresh frozen tissue samples

BackgroundBreast cancer is a complex and heterogeneous disease that is usually characterized by histological parameters such as tumor size, cellular arrangements/rearrangments, necrosis, nuclear grade and the mitotic index, leading to a set of around twenty subtypes. Together with clinical markers such as hormone receptor status, this classification has considerable prognostic value but there is a large variation in patient response to therapy. Gene expression profiling has provided molecular profiles characteristic of distinct subtypes of breast cancer that reflect the divergent cellular origins and degree of progression.MethodsHere we present a large-scale proteomic and transcriptomic profiling study of 477 sporadic and hereditary breast cancer tumors with matching mRNA expression analysis. Unsupervised hierarchal clustering was performed and selected proteins from large-scale tandem mass spectrometry (MS/MS) analysis were transferred into a highly multiplexed targeted selected reaction monitoring assay to classify tumors using a hierarchal cluster and support vector machine with leave one out cross-validation.ResultsThe subgroups formed upon unsupervised clustering agree very well with groups found at transcriptional level; however, the classifiers (genes or their respective protein products) differ almost entirely between the two datasets. In-depth analysis shows clear differences in pathways unique to each type, which may lie behind their different clinical outcomes. Targeted mass spectrometry analysis and supervised clustering correlate very well with subgroups determined by RNA classification and show convincing agreement with clinical parameters.ConclusionsThis work demonstrates the merits of protein expression profiling for breast cancer stratification. These findings have important implications for the use of genomics and expression analysis for the prediction of protein expression, such as receptor status and drug target expression. The highly multiplexed MS assay is easily implemented in standard clinical chemistry practice, allowing rapid and cheap characterization of tumor tissue suitable for directing the choice of treatment.

Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.

Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines matching all major cancer subgroups and shows that despite their different classification, these cell lines display a very high level of similarity. A proteome-wide comparison with the RNA levels observed in the same samples showed very little to no correlation. Finally, we demonstrate that the proteomes of in vitro models of breast cancer display surprisingly little overlap with those of clinical samples.

Multimodel Pathway Enrichment Methods for Functional Evaluation of Expression Regulation.

Functional analysis of quantitative expression data is becoming common practice within the proteomics and transcriptomics fields; however, a gold standard for this type of analysis has yet not emerged. To grasp the systemic changes in biological systems, efficient and robust methods are needed for data analysis following expression regulation experiments. We discuss several conceptual and practical challenges potentially hindering the emergence of such methods and present a novel method, called FEvER, that utilizes two enrichment models in parallel. We also present analysis of three disparate differential expression data sets using our method and compare our results to other established methods. With many useful features such as pathway hierarchy overview, we believe the FEvER method and its software implementation will provide a useful tool for peers in the field of proteomics. Furthermore, we show that the method is also applicable to other types of expression data.