Biology subjects

MacCoss, M. J.

Publications and source records attributed to MacCoss, M. J..

9 recordsLinked to original sources

bioRxiv2018

Thesaurus: quantifying phosphoprotein positional isomers

Proteins can be phosphorylated at neighboring sites resulting in different functional states, and studying the regulation of these sites has been challenging. Here we present Thesaurus, a search engine that detects new positional isomers using site-specific fragment ions from parallel reaction monitoring and data independent acquisition mass spectrometry experiments. We apply Thesaurus to analyze phosphorylation events in the PI3K/AKT signaling pathway and show neighboring sites with distinct quantitative profiles, indicating regulation by different kinases.

bioinformatics↗

bioRxiv2018

Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has largely increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats that are generally accepted in the field and that have shown to lead to high-quality results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. From the results obtained, common protocols will be established. Our study serves as basis for establishing best practice guidelines in the field for conducting cross-linking experiments, performing data analysis, and reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

biochemistry↗

bioRxiv2018

Quantification of nuclear protein dynamics reveals chromatin remodeling during acute protein degradation

Sequencing-based technologies cannot measure post-transcriptional dynamics of the nuclear proteome, but unbiased mass-spectrometry measurements of chromatin-associated proteins remain difficult. In this work, we have combined facile nuclear sub-fractionation approaches with data-independent acquisition mass spectrometry to improve detection and quantification of nuclear proteins in human cells and tissues. Nuclei are isolated and subjected to a series of extraction conditions that enrich for nucleoplasm, euchromatin, heterochromatin and nuclear-membrane associated proteins. Using this approach, we can measure peptides from over 70% of the expressed nuclear proteome. As we are physically separating chromatin compartments prior to analysis, proteins can be assigned into functional chromatin environments to illuminate systems-wide nuclear protein dynamics. The integrity of nuclear sub-compartments were validated with immunofluorescence, which confirms the presence of key markers during chromatin extraction. We then apply this method to study the nuclear proteome-wide response to pharmacological degradation of the BET bromodomain proteins. BET degradation leads to widespread changes in chromatin composition, and we discover global HDAC1/2-mediated remodeling of chromatin previously bound by BET bromodomains. In summary, we have developed a technology for reproducible, comprehensive characterization of the nuclear proteome to observe the systems-wide nuclear protein dynamics.

systems biology↗

bioRxiv2018

Comprehensive peptide quantification for data independent acquisition mass spectrometry using chromatogram libraries

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. We introduce a new experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in an experiment. These coordinates calibrate information in spectrum libraries or protein databases to a specific mass spectrometer and chromatography setup, and enable sensitive peptide detection in quantitative experiments. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect and quantify >50% more peptides from DIA experiments than with DDA-based spectrum libraries alone.

biochemistry↗

bioRxiv2018

Novel phosphorylation states of the yeast spindle pole body

Phosphorylation regulates yeast spindle pole body (SPB) duplication and separation and likely regulates microtubule nucleation. We report a phosphoproteomic analysis using tandem mass spectrometry of purified Saccharomyces cerevisiae SPBs for two cell cycle arrests, G1/S and the mitotic checkpoint, expanding on previously reported phosphoproteomic data sets. We present a novel phosphoproteomic state of SPBs arrested in G1/S by a cdc4-1 temperature sensitive mutation, with particular interest in phosphorylation events on the {gamma}-tubulin small complex ({gamma}-TuSC). The cdc4-1 arrest is the earliest arrest at which microtubule nucleation has occurred at the newly duplicated SPB. Several novel phosphorylation sites were identified in G1/S and during mitosis on the microtubule nucleating {gamma}-TuSC. These sites were analyzed in vivo by fluorescence microscopy and were shown to be required for proper regulation of spindle length. Additionally, in vivo analysis of two mitotic sites in Spc97 found that phosphorylation of at least one of these sites is required for progression through the cell cycle. This phosphoproteomic data set not only broadens the scope of the phosphoproteome of SPBs, it also identifies several {gamma}-TuSC phosphorylation sites influencing microtubule regulation.

biochemistry↗

bioRxiv2018

The human Ska complex and Ndc80 complex interact to form a load-bearing assembly that strengthens kinetochore-microtubule attachments

Accurate segregation of chromosomes relies on the force-bearing capabilities of the kinetochore to robustly attach chromosomes to dynamic microtubule tips. The human Ska complex and Ndc80 complex are outer-kinetochore components that bind microtubules and are required to fully stabilize kinetochore-microtubule attachments in vivo. While purified Ska complex tracks with disassembling microtubule tips, it remains unclear whether the Ska complex-microtubule interaction is sufficiently strong to make a significant contribution to kinetochore-microtubule coupling. Alternatively, Ska complex might affect kinetochore coupling indirectly, through recruitment of phospho-regulatory factors. Using optical tweezers, we show that the Ska complex itself bears load on microtubule tips, strengthens Ndc80 complex-based tip attachments, and increases the switching dynamics of the attached microtubule tips. Crosslinking mass spectrometry suggests the Ska complex directly binds Ndc80 complex through interactions between the Ska3 unstructured C-terminal region and the coiled-coil regions of each Ndc80 complex subunit. Deletion of the Ska complex microtubule-binding domain or the Ska3 C-terminus prevents Ska complex from strengthening Ndc80 complex-based attachments. Together our results indicate that the Ska complex can directly strengthen the kinetochore microtubule interface and regulate microtubule tip dynamics by forming an additional connection between the Ndc80 complex and the microtubule.\n\nSIGNIFICANCE STATEMENTMicrotubules are dynamic, tube-like structures that drive the segregation of duplicated chromosomes during cell division. The Ska complex is part of a molecular machine that forms force-bearing connections between chromosomes and microtubule ends. Depletion of the Ska complex destabilizes these connections and disrupts cell division. The Ska complex binds microtubules but it is unknown if it directly holds force at microtubules or indirectly stabilizes the connections. Here, we show that the Ska complex makes a direct force-bearing linkage with microtubule ends and assembles with another microtubule binding component, the Ndc80 complex, to strengthen its ability to withstand force. Our results suggest that the Ska and Ndc80 complexes work together to maintain the connections between chromosomes and microtubule ends.

biochemistry↗

bioRxiv2017

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations

Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays -- one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome -- for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.\n\nHighlightsO_LIFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagens\nC_LIO_LIDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell lines\nC_LIO_LIExtends Connectivity Map concept to proteomic data for integration with transcriptional data\nC_LIO_LIEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities\nC_LI

systems biology↗

bioRxiv2017

Time-resolved Interaction Proteomics of the Putative Scaffold Protein GIGANTEA in Arabidopsis thaliana

The large, plant-specific protein GIGANTEA (GI) is involved in many physiological processes, mediating rhythmic, post-translational regulation in part through circadian and light regulation of GI RNA expression. GI binds several proteins implicated in the circadian clock, the control of photoperiodic flowering, and abiotic stress responses, and has co-chaperone activity. By extension, further interaction partners might mediate the less well-understood roles of GI but the number and rhythmicity of these interactors is unknown. Here, we seek potential interactors in a time-specific manner, using quantitative proteomics from a time series study of transgenic Arabidopsis thaliana plants constitutively expressing an epitope-tagged GI protein. Previously-identified, direct and indirect interactors of GI were detected but no further F-box proteins related to known GI partners ZTL/FKF1/LKP2. The predominantly non-rhythmic, interacting proteins were implicated in protein folding or degradation, metabolism and chromatin modification, including a small set of partners shared with other clock-related proteins. A transcription factor homologue that we name CYCLING DOF FACTOR 6 (CDF6) was shown to interact both with GI and the ZTL/FKF1/LKP2 proteins and to control photoperiodic flowering. Our results indicate the biochemical pathways, beyond circadian and flowering regulation, that might be affected by GIGANTEAs rhythmic, post-translational control.\n\nSignificance StatementSignificance statement of up to two sentences of no more than 75 words total;\n\nThe GIGANTEA protein of Arabidopsis was known for circadian and flowering functions, mediated by the FKF1/LKP2/ZTL family of GI-interacting, F-box proteins, then for a co-chaperone activity of unknown scope. We performed time-resolved, interaction proteomics, identifying CDF6 (At1g26790) as a morning-specific GI interactor that controls flowering time. Unlike FKF1 and CDF proteins, most of the 240 candidate partners were not rhythmically enriched. They link GI to proteostasis and metabolic functions that might mediate GIs physiological functions.

plant biology↗

bioRxiv2017

Specter: linear deconvolution as a new paradigm for targeted analysis of data-independent acquisition mass spectrometry proteomics

Mass spectrometry with data-independent acquisition (DIA) has emerged as a promising method to greatly improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory systematically measuring all peptide precursors within a biological sample. Despite the technical maturity of DIA, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms and alternative site localizations in phosphoproteomics data. We have developed Specter, an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly in terms of a spectral library, circumventing the problems associated with typical fragment correlation-based approaches. We validate the sensitivity of Specter and its performance relative to other methods by means of several complex datasets, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

bioinformatics↗