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Over the past decade, developments in high resolution mass spectrometry have enabled the high throughput analysis of intact proteins from complex proteomes, leading to the identification of thousands of proteoforms. Several previous reports on top-down proteomics (TDP) relied on hybrid ion trap-Fourier transform mass spectrometers combined with data-dependent acquisition strategies. To further reduce TDP to practice, we use a quadrupole-Orbitrap instrument coupled with software for proteoform-dependent data acquisition to identify and characterize nearly 2000 proteoforms at a 1% false discovery rate from human fibroblasts. By combining a 3 m/z isolation window with short transients to improve specificity and signal-to-noise for proteoforms >30 kDa, we demonstrate improving proteome coverage by capturing 439 proteoforms in the 30-60 kDa range. Three different data acquisition strategies were compared and resulted in the identification of many proteoforms not observed in replicate data-dependent experiments. Notably, the data set is reported with updated metrics and tools including a new viewer and assignment of permanent proteoform record identifiers for inclusion of highly characterized proteoforms (i.e., those with C-scores >40) in a repository curated by the Consortium for Top-Down Proteomics.

Histones, and their modifications, are critical components of cellular programming and epigenetic inheritance. Recently, cancer genome sequencing has uncovered driver mutations in chromatin modifying enzymes spurring high interest how such mutations change histone modification patterns. Here, we applied Top-Down mass spectrometry for the characterization of combinatorial modifications (i.e. methylation and acetylation) on full length histone H3 from human cell lines derived from multiple myeloma patients with overexpression of the histone methyltransferase MMSET as the result of a t(4;14) chromosomal translocation. Using the latest in Orbitrap-based technology for clean isolation of isobaric proteoforms containing up to 10 methylations and/or up to two acetylations, we provide extensive characterization of histone H3.1 and H3.3 proteoforms. Differential analysis of modifications by electron-based dissociation recapitulated antagonistic crosstalk between K27 and K36 methylation in H3.1, validating that full-length histone H3 (15 kDa) can be analyzed with site-specific assignments for multiple modifications. It also revealed K36 methylation in H3.3 was affected less by the overexpression of MMSET because of its higher methylation levels in control cells. The co-occurrence of acetylation with a minimum of three methyl groups in H3K9 and H3K27 suggested a hierarchy in the addition of certain modifications. Comparative analysis showed that high levels of MMSET in the myeloma-like cells drove the formation of hypermethyled proteoforms containing H3K36me2 co-existent with the repressive marks H3K9me2/3 and H3K27me2/3. Unique histone proteoforms with such "trivalent hypermethylation" (K9me2/3-K27me2/3-K36me2) were not discovered when H3.1 peptides were analyzed by Bottom-Up. Such disease-correlated proteoforms could link tightly to aberrant transcription programs driving cellular proliferation, and their precise description demonstrates that Top-Down mass spectrometry can now decode crosstalk involving up to three modified sites., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Efforts to map the human protein interactome have resulted in information about thousands of multi-protein assemblies housed in public repositories, but the molecular characterization and stoichiometry of their protein subunits remains largely unknown. Here, we report a computational search strategy that supports hierarchical top-down analysis for precise identification and scoring of multi-proteoform complexes by native mass spectrometry.

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Mass spectrometry based proteomics generally seeks to identify and fully characterize protein species with high accuracy and throughput. Recent improvements in protein separation have greatly expanded the capacity of top-down proteomics (TDP) to identify a large number of intact proteins. To date, TDP has been most tightly associated with Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry. Here, we couple the improved separations to a Fourier-transform instrument based not on ICR but using the Orbitrap Elite mass analyzer. Application of this platform to H1299 human lung cancer cells resulted in the unambiguous identification of 690 unique proteins and over 2000 proteoforms identified from proteins with intact masses<50 kDa. This is an early demonstration of high throughput TDP (>500 identifications) in an Orbitrap mass spectrometer and exemplifies an accessible platform for whole protein mass spectrometry.

A full description of the human proteome relies on the challenging task of detecting mature and changing forms of protein molecules in the body. Large-scale proteome analysis has routinely involved digesting intact proteins followed by inferred protein identification using mass spectrometry. This 'bottom-up' process affords a high number of identifications (not always unique to a single gene). However, complications arise from incomplete or ambiguous characterization of alternative splice forms, diverse modifications (for example, acetylation and methylation) and endogenous protein cleavages, especially when combinations of these create complex patterns of intact protein isoforms and species. 'Top-down' interrogation of whole proteins can overcome these problems for individual proteins, but has not been achieved on a proteome scale owing to the lack of intact protein fractionation methods that are well integrated with tandem mass spectrometry. Here we show, using a new four-dimensional separation system, identification of 1,043 gene products from human cells that are dispersed into more than 3,000 protein species created by post-translational modification (PTM), RNA splicing and proteolysis. The overall system produced greater than 20-fold increases in both separation power and proteome coverage, enabling the identification of proteins up to 105 kDa and those with up to 11 transmembrane helices. Many previously undetected isoforms of endogenous human proteins were mapped, including changes in multiply modified species in response to accelerated cellular ageing (senescence) induced by DNA damage. Integrated with the latest version of the Swiss-Prot database, the data provide precise correlations to individual genes and proof-of-concept for large-scale interrogation of whole protein molecules. The technology promises to improve the link between proteomics data and complex phenotypes in basic biology and disease research.