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Molecular cellular proteomics [journal]
- Mechanistic Peptidomics: Factors that Dictate the Specificity on the Formation of Endogenous Peptides in Human Milk. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 29.
An extensive mass spectrometry analysis of the human milk peptidome has revealed almost 700 endogenous peptides from 30 different proteins. Two in-house computational tools were created and used to visualize and interpret the data by both alignment of the peptide quasi-molecular ion intensities and estimation of the differential enzyme participation. These results reveal that the endogenous proteolytic activity in the mammary gland is remarkably specific and well-conserved. Certain proteins, not necessarily the most abundant ones, are digested by the proteases present in milk yielding endogenous peptides from selected regions. Our results strongly suggest that factors like the presence of specific proteases, the position and concentration of cleavage sites and, more importantly, the intrinsic disorder of segments of the protein drive this proteolytic specificity in the mammary gland. As a consequence of this selective hydrolysis, proteins that typically need to be cleaved at specific positions to exert their activity are properly digested and bioactive peptides encoded in certain protein sequences are released. On the other hand, proteins that must remain intact to maintain their activity in the mammary gland or in the neonatal gastrointestinal tract are unaffected by the hydrolytic environment present in milk. These results represent insight into the intrinsic structural mechanisms that facilitate the selectivity of the endogenous milk protease activity and may be useful to understand the peptidomes of other biofluids.
- A Pipeline for Determining Protein-Protein Interactions and Proximities in the Cellular Milieu. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 29.
It remains extraordinarily challenging to elucidate endogenous protein-protein interactions and proximities within the cellular milieu. The dynamic nature and the large range of affinities of these interactions augment the difficulty of this undertaking. Among the most useful tools for extracting such information are those based on affinity capture of target bait proteins in combination with mass spectrometric readout of the co-isolated species. Although highly enabling, the utility of affinity-based methods is generally limited by difficulties in distinguishing specific from non-specific interactors, preserving and isolating all unique interactions including those that are weak, transient or rapidly exchanging, and differentiating proximal interactions from those that are more distal. Here, we have devised and optimized a set of methods to address these challenges. The resulting pipeline involves flash-freezing cells in liquid nitrogen to preserve the cellular environment at the moment of freezing; cryomilling to fracture the frozen cells into intact sub-micron chunks to allow for rapid access of a chemical reagent and to +stabilize the intact endogenous subcellular assemblies and interactors upon thawing; and utilizing the high reactivity of glutaraldehyde to achieve sufficiently rapid stabilization at low temperatures to preserve native cellular interactions. In the course of this work, we determined that relatively low molar ratios of glutaraldehyde to reactive amines within the cellular milieu were sufficient to preserve even labile and transient interactions. This mild treatment enables efficient and rapid affinity capture of the protein assemblies of interest under non-denaturing conditions, followed by bottom-up MS to identify and quantify the protein constituents. For convenience, we have termed this approach Stabilized Affinity Capture Mass Spectrometry (SAC-MS). Here, we demonstrate that SAC-MS allows us to stabilize and elucidate local, distant and transient protein interactions within complex cellular milieux, many of which are not observed in the absence of chemical stabilization.
- Structural characterization by cross-linking reveals the detailed architecture of a coatomer-related heptameric module from the nuclear pore complex. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 26.
Most cellular processes are orchestrated by macromolecular complexes. However, structural elucidation of these endogenous complexes can be challenging because they frequently contain large numbers of proteins, are compositionally and morphologically heterogeneous, can be dynamic, and are often of low abundance in the cell. Here, we present a strategy for structural characterization of such complexes, which has at its center chemical cross-linking with mass spectrometric readout (CX-MS). In this strategy, we isolate the endogenous complexes using a highly optimized sample preparation protocol and generate a comprehensive, high-quality cross-linking dataset using two complementary cross-linking reagents. We then determine the structure of the complex using a refined integrative method that combines the cross-linking data with information generated from other sources, including electron microscopy, X-ray crystallography, and comparative protein structure modeling. We applied this integrative strategy to determine the structure of the native Nup84 complex , a stable hetero-heptameric assembly (~600 kDa), sixteen copies of which form the outer rings of the 50 MDa nuclear pore complex (NPC) in budding yeast. The unprecedented detail of the Nup84 complex structure reveals previously unseen features in its pentameric structural hub and provides information on the conformational flexibility of the assembly. These additional details further support and augment the protocoatomer hypothesis, which proposes an evolutionary relationship between vesicle coating complexes and the NPC, and indicates a conserved mechanism by which the NPC is anchored in the nuclear envelope.
- KISS, a mammalian in situ protein interaction sensor. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 25.
Probably every cellular process is governed by protein-protein interactions (PPIs), which are often highly dynamic in nature being modulated by in- or external stimuli. Here we present KISS, for KInase Substrate Sensor, a mammalian two-hybrid approach designed to map intracellular PPIs and some of the dynamic features they exhibit. Benchmarking experiments indicate that in terms of sensitivity and specificity KISS is on a par with other binary protein interaction technologies whilst being complementary with regard to the subset of PPIs it is able to detect. We used KISS to evaluate interactions between different types of proteins, including transmembrane proteins, expressed at their native subcellular location. In situ analysis of endoplasmic reticulum (ER) stress-induced clustering of the ER stress sensor ERN1 and ligand-dependent β-arrestin recruitment to GPCRs illustrated the method's potential to study functional PPI modulation in complex cellular processes. Exploring its use as a tool for in cell evaluation of pharmacological interference with PPIs, we showed that reported effects of known GPCR antagonists and PPI inhibitors are properly recapitulated. In a three-hybrid setup, KISS was able to map interactions between small molecules and proteins. Taken together, we established KISS as a sensitive approach for in situ analysis of protein interactions and their modulation in a changing cellular context or in response to pharmacological challenges.
- High-content analysis of antibody phage-display library selection outputs identifies tumor selective macropinocytosis-dependent rapidly internalizing antibodies. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 22.
Many forms of antibody-based targeted therapeutics, including antibody drug conjugates, utilize the internalizing function of the targeting antibody to gain intracellular entry into tumor cells. Ideal antibodies for developing such therapeutics should be capable of both tumor-selective binding and efficient endocytosis. The macropinocytosis pathway is capable of both rapid and bulk endocytosis, and recent studies have demonstrated that it is selectively upregulated by cancer cells. We hypothesize that receptor-dependent macropinocytosis can be achieved using tumor-targeting antibodies that internalize via the macropinocytosis pathway, improving potency and selectivity of the antibody-based targeted therapeutic. While phage antibody display libraries have been utilized to find antibodies that bind and internalize to target cells, no methods have been described to screen for antibodies that internalize specifically via macropinocytosis. We hereby describe a novel screening strategy to identify phage antibodies that bind and rapidly enter tumor cells via macropinocytosis. We utilized an automated microscopic imaging-based, High Content Analysis platform to identify novel internalizing phage antibodies that colocalize with macropinocytic markers from antibody libraries that we have generated previously by laser capture microdissection-based selection, which are enriched for internalizing antibodies binding to tumor cells in situ residing in their tissue microenvironment . Full-length human IgG molecules derived from macropinocytosing phage antibodies retained the ability to internalize via macropinocytosis, validating our screening strategy. The target antigen for a cross-species binding antibody with a highly active macropinocytosis activity was identified as ephrin type-A receptor 2. Antibody-toxin conjugates created using this macropinocytosing IgG were capable of potent and receptor-dependent killing of a panel of EphA2-positive tumor cell lines in vitro. These studies identify novel methods to screen for and validate antibodies capable of receptor-dependent macropinocytosis, allowing further exploration of this highly efficient and tumor-selective internalization pathway for targeted therapy development.
- Global Proteome Analysis identifies Active Immunoproteasome subunits in Human Platelets. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 21.
The discovery of new functions for platelets, particularly in inflammation and immunity, has expanded the role of these anucleate cell fragments beyond their primary hemostatic function. Here, four in-depth human platelet proteomic datasets were generated to explore potential new functions for platelets based on their protein content and this led to the identification of 2,559 high confidence proteins. During a more detailed analysis consistently high expression of the proteasome was discovered, and the composition and function of this complex, whose role in platelets has not been thoroughly investigated, was examined. Dataset mining resulted in identification of nearly all members of the 26S proteasome in one or more datasets, except the β5 subunit. However, β5i, a component of the immunoproteasome, was identified. Biochemical analyses confirmed the presence of all catalytically active subunits of the standard 20S proteasome and immunoproteasome in human platelets, including β5, which was predominantly found in its precursor form. It was demonstrated that these components were assembled into the proteasome complex and that standard proteasome as well as immunoproteasome subunits were constitutively active in platelets. These findings suggest potential new roles for platelets in the immune system. For example, the immunoproteasome may be involved in MHC (major histocompatibility complex) I peptide generation, as the MHC I machinery was also identified in our datasets.
- Integrative structure-function mapping of the nucleoporin Nup133 suggests a conserved mechanism for membrane anchoring of the nuclear pore complex. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 19.
The nuclear pore complex (NPC) is the sole passageway for the transport of macromolecules across the nuclear envelope. Nup133, a major component in the Y- shaped Nup84 complex, is an essential scaffold protein of the NPC's outer ring structure. Here, we describe an integrative modeling approach that produces atomic models for multiple states of Saccharomyces cerevisiae (Sc) Nup133, based on the crystal structures of the sequence segments and their homologs including the related Vanderwaltozyma polyspora (Vp) Nup133 residues 55 to 502 (VpNup133(55-502)) determined in this study, small angle X-ray scattering (SAXS) profiles for 18 constructs of ScNup133 and one construct of VpNup133, and 23 negative-stain electron microscopy (EM) class averages of ScNup133(2-1157). Using our integrative approach, we then computed a multi-state structural model of the full-length ScNup133, followed by validation with mutational studies and 45 chemical cross-links determined by mass spectrometry. Finally, the model of ScNup133 allowed us to annotate a potential ArfGAP1 lipid packing sensor (ALPS) motif in Sc and VpNup133 and discuss its potential significance in the context of the whole NPC; we suggest that ALPS motifs are scattered throughout the NPC's scaffold of all eukaryotes and play a major role in the assembly and membrane anchoring of the NPC in the nuclear envelope. Our results are consistent with a common evolutionary origin of Nup133 with membrane coating complexes (the protocoatomer hypothesis); the presence of the ALPS motifs in coatomer-like nucleoporins suggests an ancestral mechanism for membrane recognition present in early membrane coating complexes.
- Determining protein complex structures based on a Bayesian model of in vivo FRET data. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 19.
The use of in vivo Forster resonance energy transfer (FRET) data to determine the molecular architecture of a protein complex in living cells is challenging due to data sparseness, sample heterogeneity, signal contributions from multiple donors and acceptors, unequal fluorophore brightness, photobleaching, flexibility of the linker connecting the fluorophore to the tagged protein, and spectral cross-talk. We address these challenges by using a Bayesian approach that produces the posterior probability of a model, given the input data. The posterior probability is defined as a function of the dependence of our FRET metric FRETR on a structure (forward model), a model of noise in the data, as well as prior information about the structure, relative populations of distinct states in the sample, forward model parameters, and data noise. The forward model was validated against Kinetic Monte Carlo simulations and in vivo experimental data collected on 9 systems of known structure. In addition, our Bayesian approach was validated by a benchmark of 16 protein complexes of known structure. Given the structures of each subunit of the complexes, models were computed from synthetic FRETR data with a distance RMSD error of 14 -17 Å. The approach is implemented in the open source Integrative Modeling Platform (http://integrativemodeling.org), allowing us to determine macromolecular structures by a combination of in vivo FRETR data with data from other sources, such as electron microscopy and chemical cross-linking.
- The development and application of a quantitative peptide microarray based approach to protein interaction domain specificity space. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 18.
Protein interaction domain (PID) linear peptide motif interactions direct diverse cellular processes in a specific and coordinated fashion. PID specificity, or the interaction selectivity derived from affinity preferences between possible PID-peptide pairs is the basis of this ability. Here, we develop an integrated experimental and computational cellulose peptide conjugate microarray (CPCMA) based approach for the high throughput analysis of PID specificity that provides unprecedented quantitative resolution and reproducibility. As a test system, we quantify the specificity preferences of four Src Homology 2 (SH2) domains and 124 physiological phosphopeptides to produce a novel quantitative interactome. The quantitative dataset covers a broad affinity range, is highly precise, and agrees well with orthogonal biophysical validation, in vivo interactions and peptide library trained algorithm predictions. In contrast to preceding approaches, the CPCMAs proved capable of confidently assigning interactions into affinity categories, resolving the subtle affinity contributions of residue correlations, and yielded predictive peptide motif affinity matrices. Unique CPCMA enabled modes of systems level analysis reveal a physiological interactome with expected node degree value decreasing as a function of affinity, resulting in minimal high affinity binding overlap between domains; uncover that SH2 domains bind ligands with a similar average affinity yet strikingly different levels of promiscuity and binding dynamic range; and parse with unprecedented quantitative resolution contextual factors directing specificity. The CPCMA platform promises broad application within the fields of PID specificity, synthetic biology, specificity focused drug design, and network biology.
- Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements. [JOURNAL ARTICLE]
- Mol Cell Proteomics 2014 Aug 16.
As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.