Jignesh R. Parikh

Niobium(V) oxide (Nb2O5): application to phosphoproteomics.

Proteomics-based analysis of signaling cascades relies on a growing suite of affinity resins and methods aimed at efficient enrichment of phosphorylated peptides from complex biological mixtures. Given the heterogeneity of phosphopeptides and the overlap in chemical properties between phospho- and unmodified peptides, it is likely that the use of multiple resins will provide the best combination of specificity, yield, and coverage for large-scale proteomics studies. Recently titanium and zirconium dioxides have been used successfully for enrichment of phosphopeptides. Here we report the first demonstration that niobium pentoxide (Nb 2O 5) provides for efficient enrichment and recovery ( approximately 50-100%) of phosphopeptides from simple mixtures and facilitates identification of several hundred putative sites of phosphorylation from cell lysate. Comparison of phosphorylated peptides identified from Nb 2O 5 and TiO 2 with sequences in the PhosphoELM database suggests a useful degree of divergence in the selectivity of these metal oxide resins. Collectively our data indicate that Nb 2O 5 provides efficient enrichment for phosphopeptides and offers a complementary approach for large-scale phosphoproteomics studies.

mzAPI: a new strategy for efficiently sharing mass spectrometry data

To The Editor: The call for data access standards in mass spectrometry-based proteomics has led to proposals focused on the extraction of native data to XML-based formats. 1,2 While self-describing and human-readable formats represent laudable goals, particularly for archival purposes, they are not well suited to large numeric datasets. Consequently, while metadata in mzML2 remain human-readable, the vast majority of the file is devoted to a hexadecimal representation of the mass spectra. Moreover, the transition from mzXML to a true XML format (mzML2) eliminates embedded indexing schemes; consequently, extracted files are compromised in both content and access efficiency.1,3 Based on similarities in data structure and access patterns, we suggest that fields such as astronomy are better models for proteomics data analysis (Figure 1). These fields also rely on common formats, but typically utilize binary standards such as HDF54 or netCDF5. By contrast, the commercial nature of mass spectrometry has led to the evolution of proprietary binary file formats. In light of these observations, we propose that a common and redistributable application programming interface (API) represents a more viable approach to data access in mass spectrometry. In effect, we propose to shift the burden of standards compliance to the manufacturers’ existing data access libraries. Figure 1 Array Scanners, Telescopes, and Mass Spectrometers: XML, HDF, or API? While our proposal for abstraction through a common API represents a clear departure from current attempts to define a universal file format, it is by no means unique within the broader scientific community. For example, standardized APIs have enabled the development of portable applications in such diverse areas as computer graphics (OpenGL7) and parallel processing (Message Passing Interface, MPI8). More importantly, we believe that a common API will benefit all stakeholders. For example, free redistribution of compiled, vendor-supplied dynamically linked libraries (DLLs) will protect the proprietary layout of native files and provide users with direct and flexible access to data system- and instrument-specific functionality which are typically ignored by lowest common denominator export routines. In addition, we note that mzAPI naturally supports the FDA’s 21 CFR part 11 regulatory requirements for electronic records9 Finally, a community-driven API standard will facilitate manufacturer support of UNIX, in addition to Windows, by highlighting the subset of procedures, from each data system (Xcalibur™, Analyst™, etc.), which need to be ported. Motivated originally by our desire to provide a more intimate environment for flexible and in-depth exploration of mass spectrometry data, particularly from low-throughput experiments, we developed a preliminary common API (mzAPI) – consisting of just five procedures (http://blais.dfci.harvard.edu/mzAPI). To maximize accessibility we exposed mzAPI in the form of a Python library within a flexible, mass-informatics desktop framework called multiplierz (http://blais.dfci.harvard.edu/multiplierz). We are encouraged by results from this test harness, in particular how well mzAPI and our desktop environment support a variety of data analytic operations. Equally impressive is how quickly non-programmers can customize scripts for their specific tasks. Despite success to date in our own lab, we recognize that mzAPI will benefit from further refinement and stress testing. Accordingly, we are actively seeking input from the research community with respect to both concept and implementation of a comprehensive API-based standard for mass spectrometry data access and analysis.

Discovering causal signaling pathways through gene-expression patterns

High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant membership of the translated proteins in various signaling pathways. However, such membership enrichment algorithms do not provide insight into which pathways caused the genes to be differentially expressed in the first place. Here, we present an intuitive approach for discovering upstream signaling pathways responsible for regulating these differentially expressed genes. We identify consistently regulated signature genes specific for signal transduction pathways from a panel of single-pathway perturbation experiments. An algorithm that detects overrepresentation of these signature genes in a gene group of interest is used to infer the signaling pathway responsible for regulation. We expose our novel resource and algorithm through a web server called SPEED: Signaling Pathway Enrichment using Experimental Data sets. SPEED can be freely accessed at http://speed.sys-bio.net/.

Mass Spectrometry-based Proteomics: Qualitative Identification to Activity-based Protein Profiling

Mass spectrometry has become the method of choice for proteome characterization, including multicomponent protein complexes (typically tens to hundreds of proteins) and total protein expression (up to tens of thousands of proteins), in biological samples. Qualitative sequence assignment based on MS/MS spectra is relatively well‐defined, while statistical metrics for relative quantification have not completely stabilized. Nonetheless, proteomics studies have progressed to the point whereby various gene‐, pathway‐, or network‐oriented computational frameworks may be used to place mass spectrometry data into biological context. Despite this progress, the dynamic range of protein expression remains a significant hurdle, and impedes comprehensive proteome analysis. Methods designed to enrich specific protein classes have emerged as an effective means to characterize enzymes or other catalytically active proteins that are otherwise difficult to detect in typical discovery mode proteomics experiments. Collectively, these approaches will facilitate identification of biomarkers and pathways relevant to diagnosis and treatment of human disease. WIREs Syst Biol Med 2012, 4:141–162. doi: 10.1002/wsbm.166

Multi-Edge Gene Set Networks Reveal Novel Insights into Global Relationships between Biological Themes

Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.

Mining Immune Epitopes in the Inner Ear

Etiologies for many inner ear disorders, including autoimmune inner ear disease, sudden sensorineural hearing loss, and Meniere’s disease, remain unknown. Indirect evidence suggests an immune-mediated process involving an allergic or autoimmune mechanism. We examined whether known immunogenic proteins share sequence similarity with inner ear proteins, which may lead to cross-reactivity and detrimental immune activation. Comprehensive bioinformatic analyses of primary sequences of intact and mutated proteins associated with human hearing loss and all proteins known to be expressed in the human inner ear were compared with all immune epitopes in the Immune Epitope Database. The exact match and basic local alignment search tool computational algorithms identified 3036 and 106 unique epitope matches, respectively, the majority of which were infectious epitopes. If validated in future clinical trials, these candidate immune epitopes in the inner ear would be potential novel targets for diagnosis and treatment of some inner ear disorders and the resulting hearing loss.

The Wnt signaling network in cancer

An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer

Mining Immune Epitopes in Ménière’s Disease and Sudden Sensorineural Hearing Loss

Objective: Etiologies for Ménière’s disease and sudden sensorineural hearing loss remain unknown. Indirect evidence exists for allergy-mediated or autoimmune process. The purpose of this study is to determine whether immunogenic proteins share similar sequences with inner ear proteins, which may lead to cross-reactivity and immune activation in inner ear disorders. Method: Comprehensive bioinformatic primary sequence analyses of intact and mutated proteins associated with human syndromic and nonsyndromic hearing loss and proteins expressed in the human inner ear was performed. Comparison of sequences to epitopes in the Immune Epitope Database was performed by exact match, BLAST, and BLOSUM62 score computational algorithms. Results: Computational analysis of primary protein sequence for 81 known inner ear proteins, 102 proteins from genes identified in syndromic and non-syndromic hearing loss, and 438 protein sequences with known mutations that contribute to sensorineural hearing loss was compared to 151,086 epitopes previously implicated in allergic, autoimmune, and infectious disorders within the Immune Epitope Database. The exact match and BLAST algorithms identified 1925 and 97 unique epitope matches, respectively. Top BLOSUM62 score algorithm resulted in a single hit for the 47 kDa membrane antigen. Other epitopes included those seen in allergic rhinitis, infectious diseases, and autoimmune disorders. Conclusion: Abnormal immune activation is suspected in Ménière’s disease and SSNHL. Candidate immune epitopes were identified that may contribute to pathogenesis of these disorders. While these epitopes await clinical validation, they present novel targets for diagnosis and treatment of sensorineural hearing loss.

Abstract B51: Dynamic remodeling of CEBPα complexes in myeloid differentiation

Acute myeloid leukemia (AML) remains a highly lethal malignancy with limited therapeutic options. An integral component of the AML phenotype is an inability of hematopoietic progenitors to differentiate into mature myeloid cells. Mounting evidence indicates that the basic leucine zipper transcription factor C/EBPα plays a critical role in development of granulocytes, and that impaired function of C/EBPα may disrupt myeloid differentiation and ultimately lead to blast crisis in AML. Recent studies demonstrated that oncogenic Flt3 signaling leads to phosphorylation of C/EBPα on serine 21, with concomitant impairment of myeloid differentiation in cell line models and primary hematopoietic cells. While these data provide compelling evidence for the central role of C/EBPα in normal hematopoiesis and leukemia, the mechanism by which pS21 disrupts differentiation remains unresolved. Given the general thesis that cellular control of biological processes is orchestrated through a delicate balance of protein‐protein interactions and post‐translational modifications, we speculated that C/EBPα phosphorylation catalyzes the assembly of a transcriptionally inactive protein complex. To test this hypothesis we established affinity tagged C/EBPα under control of a tet‐inducible promoter in myeloid progenitors with constitutive Flt3 activity. Treatment of these cells with Flt3 inhibitors modulated pS21 in a dose‐dependent manner. Next advanced quantitative proteomics methodology, including true nanoflow LC coupled with multidimensional fractionation and on‐column iTRAQ stable isotope labeling, was used to monitor remodeling of C/EBPα protein complexes as a function of pS21. Our data represent by far the largest catalog C/EBPα interactors involved in chromatin organization, transcriptional modulation, and cell cycle regulation. Furthermore, our quantitative proteomics data demonstrate that 1) C/EBPα interacts with proteins genetically linked to leukemia (DEK, SET and other); and 2) many of these interact with C/EBPα in a phosphorylation‐dependent manner. Our functional validation studies show that DEK and SET bind to C/EBPα‐target promoters in C/EBPα‐dependent manner to enhance C/EBPα attachment to its DNA binding site. Knock‐down of newly‐identified, leukemia‐associated interactors, DEK and SET, reduce the ability of C/EBPα to drive expression of granulocytic target genes. Furthermore the depletion of DEK and SET reduce capacity of myeloid cells to undergo terminal granulocytic differentiation. Our data demonstrate that phosphorylation on serine 21 modulates association of C/EBPα with protein partners that are functionally relevant for myeloid differentiation. Our ability to quantitatively monitor multiple leukemia‐related gene products in the context of C/EBPα protein complexes provides valuable insight into the mechanisms by which oncogenic kinase activity disrupts transcription and leads to leukemogenesis. Citation Information: Cancer Res 2009;69(23 Suppl):B51.