Manor Askenazi

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype–phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or ‘passenger’, cancer mutations from causal, or ‘driver’, mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Improved Electrospray Ionization Efficiency Compensates for Diminished Chromatographic Resolution and Enables Proteomics Analysis of Tyrosine Signaling in Embryonic Stem Cells

Characterization of signaling pathways in embryonic stem cells is a prerequisite for future application of these cells to treat human disease and other disorders. Identification of tyrosine signaling cascades is of particular interest but is complicated by the relatively low levels of tyrosine phosphorylation in embryonic stem cells. These hurdles correlate with the primary limitations of mass spectrometry-based proteomics; namely, poor detection limit and dynamic range. To overcome these obstacles, we fabricated miniaturized LC-electrospray assemblies that provided approximately 15-fold improvement in LC-MS performance. Significantly, our characterization data demonstrate that electrospray ionization efficiency compensates for diminished chromatographic performance at effluent flow rates below Van Deemter minima. Use of these assemblies facilitated quantitative proteomics-based analysis of tyrosine signaling cascades in embryonic stem cells. Our results suggest that a renewed focus on miniaturized LC coupled to ultralow flow electrospray will provide a viable path for proteomic analysis of primary cells and rare post-translational modifications.

multiplierz: an extensible API based desktop environment for proteomics data analysis

BackgroundEfficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge.ResultsWe describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a zero infrastructure philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines.ConclusionCollectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.

Quantitative Assessment of Whole-Body Tumor Burden in Adult Patients with Neurofibromatosis

Purpose Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis are at risk for multiple nerve sheath tumors and premature mortality. Traditional magnetic resonance imaging (MRI) has limited ability to assess disease burden accurately. The aim of this study was to establish an international cohort of patients with quantified whole-body internal tumor burden and to correlate tumor burden with clinical features of disease. Methods We determined the number, volume, and distribution of internal nerve sheath tumors in patients using whole-body MRI (WBMRI) and three-dimensional computerized volumetry. We quantified the distribution of tumor volume across body regions and used unsupervised cluster analysis to group patients based on tumor distribution. We correlated the presence and volume of internal tumors with disease-related and demographic factors. Results WBMRI identified 1286 tumors in 145/247 patients (59%). Schwannomatosis patients had the highest prevalence of tumors (Pu200a=u200a0.03), but NF1 patients had the highest median tumor volume (Pu200a=u200a0.02). Tumor volume was unevenly distributed across body regions with overrepresentation of the head/neck and pelvis. Risk factors for internal nerve sheath tumors included decreasing numbers of café-au-lait macules in NF1 patients (Pu200a=u200a0.003) and history of skeletal abnormalities in NF2 patients (Pu200a=u200a0.09). Risk factors for higher tumor volume included female gender (Pu200a=u200a0.05) and increasing subcutaneous neurofibromas (Pu200a=u200a0.03) in NF1 patients, absence of cutaneous schwannomas in NF2 patients (Pu200a=u200a0.06), and increasing age in schwannomatosis patients (pu200a=u200a0.10). Conclusion WBMRI provides a comprehensive phenotype of neurofibromatosis patients, identifies distinct anatomic subgroups, and provides the basis for investigating molecular biomarkers that correlate with unique disease manifestations.

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 n nBased 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. n n n nFigure 1 n nArray Scanners, Telescopes, and Mass Spectrometers: XML, HDF, or API? n n n nWhile 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. n nMotivated 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.

DNA Ends Alter the Molecular Composition and Localization of Ku Multicomponent Complexes

The Ku heterodimer plays an essential role in non-homologous end-joining and other cellular processes including transcription, telomere maintenance and apoptosis. While the function of Ku is regulated through its association with other proteins and nucleic acids, the specific composition of these macromolecular complexes and their dynamic response to endogenous and exogenous cellular stimuli are not well understood. Here we use quantitative proteomics to define the composition of Ku multicomponent complexes and demonstrate that they are dramatically altered in response to UV radiation. Subsequent biochemical assays revealed that the presence of DNA ends leads to the substitution of RNA-binding proteins with DNA and chromatin associated factors to create a macromolecular complex poised for DNA repair. We observed that dynamic remodeling of the Ku complex coincided with exit of Ku and other DNA repair proteins from the nucleolus. Microinjection of sheared DNA into live cells as a mimetic for double strand breaks confirmed these findings in vivo.

Proteomic Analysis Demonstrates Activator- and Chromatin-specific Recruitment to Promoters

Background: Quantitative proteomic analyses of transcription complexes were performed to compare different activators on naked and chromatin templates. Results: Gal4-VP16 and Gal4-Gcn4 recruit SAGA, NuA4, and Swi/Snf but to different extents. Chromatin suppresses basal factor binding, leading to enhanced activation. Conclusion: Different activators have distinct preferences in coactivators. Significance: Quantitative mass spectrometry is a useful tool for analyzing transcription mechanisms. In-depth characterization of RNA polymerase II preinitiation complexes remains an important and challenging goal. We used quantitative mass spectrometry to explore context-dependent Saccharomyces cerevisiae preinitiation complex formation at the HIS4 promoter reconstituted on naked and chromatinized DNA templates. The transcription activators Gal4-VP16 and Gal4-Gcn4 recruited a limited set of chromatin-related coactivator complexes, namely the chromatin remodeler Swi/Snf and histone acetyltransferases SAGA and NuA4, suggesting that transcription stimulation is mediated through these factors. Moreover, the two activators differentially recruited the coactivator complexes, consistent with specific activator-coactivator interactions. Chromatinized templates suppressed recruitment of basal transcription factors, thereby amplifying the effect of activators, compared with naked DNA templates. This system is sensitive, highly reproducible, and easily applicable to mapping the repertoire of proteins found at any promoter.

mzServer: Web-based Programmatic Access for Mass Spectrometry Data Analysis

Continued progress toward systematic generation of large-scale and comprehensive proteomics data in the context of biomedical research will create project-level data sets of unprecedented size and ultimately overwhelm current practices for results validation that are based on distribution of native or surrogate mass spectrometry files. Moreover, the majority of proteomics studies leverage discovery-mode MS/MS analyses, rendering associated data-reduction efforts incomplete at best, and essentially ensuring future demand for re-analysis of data as new biological and technical information become available. Based on these observations, we propose to move beyond the sharing of interpreted spectra, or even the distribution of data at the individual file or project level, to a system much like that used in high-energy physics and astronomy, whereby raw data are made programmatically accessible at the site of acquisition. Toward this end we have developed a web-based server (mzServer), which exposes our common API (mzAPI) through very intuitive (RESTful) uniform resource locators (URL) and provides remote data access and analysis capabilities to the research community. Our prototype mzServer provides a model for lab-based and community-wide data access and analysis.

Protected amine labels: a versatile molecular scaffold for multiplexed nominal mass and sub-Da isotopologue quantitative proteomic reagents.

AbstractWe assemble a versatile molecular scaffold from simple building blocks to create binary and multiplexed stable isotope reagents for quantitative mass spectrometry. Termed Protected Amine Labels (PAL), these reagents offer multiple analytical figures of merit including, (1) robust targeting of peptide N-termini and lysyl side chains, (2) optimal mass spectrometry ionization efficiency through regeneration of primary amines on labeled peptides, (3) an amino acid-based mass tag that incorporates heavy isotopes of carbon, nitrogen, and oxygen to ensure matched physicochemical and MS/MS fragmentation behavior among labeled peptides, and (4) a molecularly efficient architecture, in which the majority of hetero-atom centers can be used to synthesize a variety of nominal mass and sub-Da isotopologue stable isotope reagents. We demonstrate the performance of these reagents in well-established strategies whereby up to four channels of peptide isotopomers, each separated by 4xa0Da, are quantified in MS-level scans with accuracies comparable to current commercial reagents. In addition, we utilize the PAL scaffold to create isotopologue reagents in which labeled peptide analogs differ in mass based on the binding energy in carbon and nitrogen nuclei, thereby allowing quantification based on MS or MS/MS spectra. We demonstrate accurate quantification for reagents that support 6-plex labeling and propose extension of this scheme to 9-channels based on a similar PAL scaffold. Finally, we provide exemplar data that extend the application of isotopologe-based quantification reagents to medium resolution, quadrupole time-of-flight mass spectrometers.n Figure115F

Library dependent LC‐MS/MS acquisition via mzAPI/Live

The use of MS for characterization of small molecules, nucleotides, and proteins in model organisms as well as primary tissues and clinical samples continues to proliferate at a rapid pace. The complexity and dynamic range of target analytes in biological systems hinders comprehensive analysis and simultaneously drives improvements in instrument hardware and software. As a result, state‐of‐the‐art commercial mass spectrometers are equipped with sophisticated embedded control systems that provide robust acquisition methods accessed through intuitive graphical interfaces. Although optimized for speed, these preconfigured scan functions are otherwise closed to end‐user customization beyond simple, analytical‐centric parameters supplied by the manufacturer. Here, we present an open‐source framework (mzAPI/Live) that enables users to generate arbitrarily complex LC‐MSn acquisition methods via simple Python scripting. As a powerful proof‐of‐concept, we demonstrate real‐time assignment of tandem mass spectra through rapid query of NIST peptide libraries. This represents an unprecedented capability to make acquisition decisions based on knowledge of analyte structures determined during the run itself, thus providing a path toward biology‐driven MS data acquisition for the broader community.