The proteome of the blood-brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture.

BACKGROUND: The active transport of molecules into the brain from blood is regulated by receptors, transporters, and other cell surface proteins that are present on the luminal surface of endothelial cells at the blood-brain barrier (BBB). However, proteomic profiling of proteins present on the luminal endothelial cell surface of the BBB has proven challenging due to difficulty in labelling these proteins in a way that allows efficient purification of these relatively low abundance cell surface proteins. METHODS: Here we describe a novel perfusion-based labelling workflow: in vivo glycocapture. This workflow relies on the oxidation of glycans present on the luminal vessel surface via perfusion of a mild oxidizing agent, followed by subsequent isolation of glycoproteins by covalent linkage of their oxidized glycans to hydrazide beads. Mass spectrometry-based identification of the isolated proteins enables high-confidence identification of endothelial cell surface proteins in rats and mice. RESULTS: Using the developed workflow, 347 proteins were identified from the BBB in rat and 224 proteins in mouse, for a total of 395 proteins in both species combined. These proteins included many proteins with transporter activity (73 proteins), cell adhesion proteins (47 proteins), and transmembrane signal receptors (31 proteins). To identify proteins that are enriched in vessels relative to the entire brain, we established a vessel-enrichment score and showed that proteins with a high vessel-enrichment score are involved in vascular development functions, binding to integrins, and cell adhesion. Using publicly-available single-cell RNAseq data, we show that the proteins identified by in vivo glycocapture were more likely to be detected by scRNAseq in endothelial cells than in any other cell type. Furthermore, nearly 50% of the genes encoding cell-surface proteins that were detected by scRNAseq in endothelial cells were also identified by in vivo glycocapture. CONCLUSIONS: The proteins identified by in vivo glycocapture in this work represent the most complete and specific profiling of proteins on the luminal BBB surface to date. The identified proteins reflect possible targets for the development of antibodies to improve the crossing of therapeutic proteins into the brain and will contribute to our further understanding of BBB transport mechanisms.

Cell surface profiling of cultured cells by direct hydrazide capture of oxidized glycoproteins.

Glycoproteins are a particularly interesting subset of the cellular proteome as a high proportion of proteins present on the extracellular cell surface are glycosylated. These cell surface proteins are ideal targets for biologic drug therapies or for diagnostics tests. Here, we describe a modification of the well-described Cell Surface Capture (CSC) method for the selective isolation and identification of cell surface glycoproteins that contain N-linked carbohydrates. This modification, which we refer to as Direct Cell Surface Capture (D-CSC), is based on oxidation of cell surface glycans on intact cells, followed by direct conjugation of the oxidized oligosaccharides to a solid support using hydrazide chemistry, with no biotinylation step. As a proof-of-principle, we applied D-CSC to the analysis of cell surface membrane proteins of three adherent cancer cell lines (A549, OVCAR3, and U87MG) and compared our results to those published using the well-established Cell Surface Capture (CSC) method, demonstrating comparable selectivity for cell surface proteins. •A method enabling the identification of cell surface proteins from cells in culture is described.•Application of this method to profile the cell surface on three different cancer cell lines is included.

Tuning the immune response: sulfated archaeal glycolipid archaeosomes as an effective vaccine adjuvant for induction of humoral and cell-mediated immunity towards the SARS-CoV-2 Omicron variant of concern.

Liposomes composed of sulfated lactosyl archaeol (SLA) have been shown to be a safe and effective vaccine adjuvant with a multitude of antigens in preclinical studies. In particular, SLA-adjuvanted SARS-CoV-2 subunit vaccines based on trimeric spike protein antigens were shown to be immunogenic and efficacious in mice and hamsters. With the continued emergence of SARS-CoV-2 variants, we sought to evaluate next-generation vaccine formulations with an updated antigenic identity. This was of particular interest for the widespread Omicron variant, given the abundance of mutations and structural changes observed within its spike protein compared to other variants. An updated version of our resistin-trimerized SmT1 corresponding to the B.1.1.529 variant was successfully generated in our Chinese Hamster Ovary (CHO) cell-based antigen production platform and characterized, revealing some differences in protein profile and ACE2 binding affinity as compared to reference strain-based SmT1. We next evaluated this Omicron-based spike antigen for its immunogenicity and ability to generate robust antigen-specific immune responses when paired with SLA liposomes or AddaS03 (a mimetic of the AS03 oil-in-water emulsion adjuvant system found in commercialized SARS-CoV-2 protein vaccines). Immunization of mice with vaccine formulations containing this updated antigen with either adjuvant stimulated neutralizing antibody responses favouring Omicron over the reference strain. Cell-mediated responses, which play an important role in the neutralization of intracellular infections, were induced to a much higher degree with the SLA adjuvant relative to the AddaS03-adjuvanted formulations. As such, updated vaccines that are better capable of targeting towards SARS-CoV-2 variants can be generated through an optimized combination of antigen and adjuvant components.

Immunogenicity of SARS-CoV-2 spike antigens derived from Beta & Delta variants of concern.

Using our strongly immunogenic SmT1 SARS-CoV-2 spike antigen platform, we developed antigens based on the Beta & Delta variants of concern (VOC). These antigens elicited higher neutralizing antibody activity to the corresponding variant than comparable vaccine formulations based on the original reference strain, while a multivalent vaccine generated cross-neutralizing activity in all three variants. This suggests that while current vaccines may be effective at reducing severe disease to existing VOC, variant-specific antigens, whether in a mono- or multivalent vaccine, may be required to induce optimal immune responses and reduce infection against arising variants.

Increasing morphological disparity and decreasing optimality for jaw speed and strength during the radiation of jawed vertebrates.

The Siluro-Devonian adaptive radiation of jawed vertebrates, which underpins almost all living vertebrate biodiversity, is characterized by the evolutionary innovation of the lower jaw. Multiple lines of evidence have suggested that the jaw evolved from a rostral gill arch, but when the jaw took on a feeding function remains unclear. We quantified the variety of form in the earliest jaws in the fossil record from which we generated a theoretical morphospace that we then tested for functional optimality. By drawing comparisons with the real jaw data and reconstructed jaw morphologies from phylogenetically inferred ancestors, our results show that the earliest jaw shapes were optimized for fast closure and stress resistance, inferring a predatory feeding function. Jaw shapes became less optimal for these functions during the later radiation of jawed vertebrates. Thus, the evolution of jaw morphology has continually explored previously unoccupied morphospace and accumulated disparity through time, laying the foundation for diverse feeding strategies and the success of jawed vertebrates.

Proteome of the Luminal Surface of the Blood-Brain Barrier.

Interrogation of the molecular makeup of the blood-brain barrier (BBB) using proteomic techniques has contributed to the cataloguing and functional understanding of the proteins uniquely organized at this specialized interface. The majority of proteomic studies have focused on cellular components of the BBB, including cultured brain endothelial cells (BEC). Detailed proteome mapping of polarized BEC membranes and their intracellular endosomal compartments has led to an improved understanding of the processes leading to internalization and transport of various classes of molecules across the BBB. Quantitative proteomic methods have further enabled absolute and comparative quantification of key BBB transporters and receptors in isolated BEC and microvessels from various species. However, translational studies further require in vivo/in situ analyses of the proteins exposed on the luminal surface of BEC in vessels under various disease and treatment conditions. In vivo proteomics approaches, both profiling and quantitative, usually rely on 'capturing' luminally-exposed proteins after perfusion with chemical labeling reagents, followed by analysis with various mass spectrometry-based approaches. This manuscript reviews recent advances in proteomic analyses of luminal membranes of BEC in vitro and in vivo and their applications in translational studies focused on developing novel delivery methods across the BBB.

Identification of transcriptional subtypes in lung adenocarcinoma and squamous cell carcinoma through integrative analysis of microarray and RNA sequencing data.

Classification of tumors into subtypes can inform personalized approaches to treatment including the choice of targeted therapies. The two most common lung cancer histological subtypes, lung adenocarcinoma and lung squamous cell carcinoma, have been previously divided into transcriptional subtypes using microarray data, and corresponding signatures were subsequently used to classify RNA-seq data. Cross-platform unsupervised classification facilitates the identification of robust transcriptional subtypes by combining vast amounts of publicly available microarray and RNA-seq data. However, cross-platform classification is challenging because of intrinsic differences in data generated using the two gene expression profiling technologies. In this report, we show that robust gene expression subtypes can be identified in integrated data representing over 3500 normal and tumor lung samples profiled using two widely used platforms, Affymetrix HG-U133 Plus 2.0 Array and Illumina HiSeq RNA sequencing. We tested and analyzed consensus clustering for 384 combinations of data processing methods. The agreement between subtypes identified in single-platform and cross-platform normalized data was then evaluated using a variety of statistics. Results show that unsupervised learning can be achieved with combined microarray and RNA-seq data using selected preprocessing, cross-platform normalization, and unsupervised feature selection methods. Our analysis confirmed three lung adenocarcinoma transcriptional subtypes, but only two consistent subtypes in squamous cell carcinoma, as opposed to four subtypes previously identified. Further analysis showed that tumor subtypes were associated with distinct patterns of genomic alterations in genes coding for therapeutic targets. Importantly, by integrating quantitative proteomics data, we were able to identify tumor subtype biomarkers that effectively classify samples on the basis of both gene and protein expression. This study provides the basis for further integrative data analysis across gene and protein expression profiling platforms.

Defining the epitope of a blood-brain barrier crossing single domain antibody specific for the type 1 insulin-like growth factor receptor.

Ligand-activated signaling through the type 1 insulin-like growth factor receptor (IGF1R) is implicated in many physiological processes ranging from normal human growth to cancer proliferation and metastasis. IGF1R has also emerged as a target for receptor-mediated transcytosis, a transport phenomenon that can be exploited to shuttle biotherapeutics across the blood-brain barrier (BBB). We employed differential hydrogen-deuterium exchange mass spectrometry (HDX-MS) and nuclear magnetic resonance (NMR) to characterize the interactions of the IGF1R ectodomain with a recently discovered BBB-crossing single-domain antibody (sdAb), VHH-IR5, in comparison with IGF-1 binding. HDX-MS confirmed that IGF-1 induced global conformational shifts in the L1/FnIII-1/-2 domains and α-CT helix of IGF1R. In contrast, the VHH-IR5 sdAb-mediated changes in conformational dynamics were limited to the α-CT helix and its immediate vicinity (L1 domain). High-resolution NMR spectroscopy titration data and linear peptide scanning demonstrated that VHH-IR5 has high-affinity binding interactions with a peptide sequence around the C-terminal region of the α-CT helix. Taken together, these results define a core linear epitope for VHH-IR5 within the α-CT helix, overlapping the IGF-1 binding site, and suggest a potential role for the α-CT helix in sdAb-mediated transcytosis.

Adding polyvinylpyrrolidone to low level protein samples significantly improves peptide recovery in FASP digests: An inexpensive and simple modification to the FASP protocol.

Filter-aided sample preparation (FASP) remains a popular choice for proteomic sample preparation, particularly for its ability to produce a 'clean' peptide sample clear of large molecule contaminants. However, sample loss continues to be a problem particularly for sample inputs that contain less than ten micrograms of protein. Here, we describe that the simple addition of a polymer, polyvinylpyrrolidone-40 (PVP-40) to the protein sample prior to FASP digest significantly improves peptide recovery and identifications, especially with lower level sample inputs. PVP-FASP produces clean samples which required no additional sample clean-up prior to nanoLC-MS analysis. In addition, PVP-FASP is compatible with other FASP modifications, including the use of sodium deoxycholate (DOC) to improve trypsin digestion. SIGNIFICANCE: Simple modification to FASP procedure improves sample recovery during proteomic digests in SDS, improving peptide identifications and median peptide intensity.

The use of extruded finite-element models as a novel alternative to tomography-based models: a case study using early mammal jaws.

Finite-element (FE) analysis has been used in palaeobiology to assess the mechanical performance of the jaw. It uses two types of models: tomography-based three-dimensional (3D) models (very accurate, not always accessible) and two-dimensional (2D) models (quick and easy to build, good for broad-scale studies, cannot obtain absolute stress and strain values). Here, we introduce extruded FE models, which provide fairly accurate mechanical performance results, while remaining low-cost, quick and easy to build. These are simplified 3D models built from lateral outlines of a relatively flat jaw and extruded to its average width. There are two types: extruded (flat mediolaterally) and enhanced extruded (accounts for width differences in the ascending ramus). Here, we compare mechanical performance values resulting from four types of FE models (i.e. tomography-based 3D, extruded, enhanced extruded and 2D) in Morganucodon and Kuehneotherium. In terms of absolute values, both types of extruded model perform well in comparison to the tomography-based 3D models, but enhanced extruded models perform better. In terms of overall patterns, all models produce similar results. Extruded FE models constitute a viable alternative to the use of tomography-based 3D models, particularly in relatively flat bones.

Antigen Identification for Cell-Binding Antibodies Using Ligand-Directed Crosslinking and Biotin Transfer.

Panning approaches using antibody libraries often result in the isolation of antibodies that bind to cells through an unknown cellular receptor. Here, we describe a protocol that uses ligand-directed crosslinking with the aminooxy-sulfhydryl-biotin (ASB) trifunctional crosslinker followed by a proteomic analysis to identify the cellular receptors for orphan ligands. We describe the synthesis of the ASB crosslinker, labelling of the ligand with ASB, and cell binding of the labelled ligands. Next, biotin affinity purification and trypsin digestion of cell surface proteins that have been crosslinked by ASB are described. Lastly, several hints and tips to improve the proteomic analysis for these types of samples are provided.

Llama peripheral B-cell populations producing conventional and heavy chain-only IgG subtypes are phenotypically indistinguishable but immunogenetically distinct.

Camelid ungulates produce homodimeric heavy chain-only antibodies (HCAbs) in addition to conventional antibodies consisting of paired heavy and light chains. In the llama, HCAbs are made up by at least two subclasses (long-hinge IgG2b and short-hinge IgG2c HCAbs vs. conventional heterotetrameric IgG1s). Here, we generated murine monoclonal antibodies (mAbs) specific for the hinge-CH2 boundary of llama IgG2b (mAb 1C10) and the Fc of llama IgG2c HCAbs (mAb 5E4). Flow cytometric analysis of llama peripheral blood lymphocytes revealed that IgG1+, IgG2b+ and IgG2c+ B cells could be distinguished using mAbs 1C10/5E4 but had equivalent expression of three other cell-surface markers. MiSeq sequencing of the peripheral B cell repertoires of three llamas showed that (i) IgG2b and IgG2c HCAbs were present in similar proportions in the repertoire, (ii) a subset of IgG2b and IgG2c HCAbs, but not IgG1s, entirely lacked a hinge exon and showed direct VHH-CH2 splicing; these "hingeless" HCAbs were clonally expanded, somatically mutated and derived from hinged HCAb precursors, (iii) substantial repertoire overlap existed between IgG subclasses, especially between IgG2b and IgG2c HCAbs, (iv) the complementarity-determining region (CDR)-H3 length distributions of IgG2b and IgG2c HCAbs were broader and biased towards longer lengths compared with IgG1s due to increased N-nucleotide addition, (v) IgG2b and IgG2c HCAbs used a more restricted set of IGHV genes compared with IgG1s, and (vi) IgG2b and IgG2c HCAbs had elevated somatic mutations rates of both CDRs and framework regions (FRs) compared with IgG1s, especially of CDR-H1 and FR3. The distinct molecular features of llama IgG1, IgG2b and IgG2c antibodies imply that these subclasses may have divergent immunological functions and suggest that specific mechanisms operate to diversify HCAb repertoires in the absence of a light chain.

An accurate TMT-based approach to quantify and model lysine susceptibility to conjugation via N-hydroxysuccinimide esters in a monoclonal antibody.

Conjugation of small molecules to proteins through N-hydroxysuccinimide (NHS) esters results in a random distribution of small molecules on lysine residues and the protein N-terminus. While mass spectrometry methods have improved characterization of these protein conjugates, it remains a challenge to quantify the occupancy at individual sites of conjugation. Here, we present a method using Tandem Mass Tags (TMT) that enabled the accurate and sensitive quantification of occupancy at individual conjugation sites in the NIST monoclonal antibody. At conjugation levels relevant to antibody drug conjugates in the clinic, site occupancy data was obtained for 37 individual sites, with average site occupancy data across 2 adjacent lysines obtained for an additional 12 sites. Thus, altogether, a measure of site occupancy was obtained for 98% of the available primary amines. We further showed that removal of the Fc-glycan on the NIST mAb increased conjugation at two specific sites in the heavy chain, demonstrating the utility of this method to identify changes in the susceptibility of individual sites to conjugation. This improved site occupancy data allowed calibration of a bi-parametric linear model for predicting the susceptibility of individual lysines to conjugation from 3D-structure based on their solvent exposures and ionization constants. Trained against the experimental data for lysines from the Fab fragment, the model provided accurate predictions of occupancies at lysine sites from the Fc region and the protein N-terminus (R2 = 0.76). This predictive model will enable improved engineering of antibodies for optimal labeling with fluorophores, toxins, or crosslinkers.

Biotin-transfer from a trifunctional crosslinker for identification of cell surface receptors of soluble protein ligands.

Here we describe a novel crosslinker and its application as a biotin-transfer reagent to identify cell surface receptors of soluble protein ligands on live cells. This crosslinker contains three functional groups: an aldehyde-reactive aminooxy group, a sulfhydryl, and a biotin (ASB). It is readily synthesized via a 3-step addition reaction using standard solid-phase peptide synthesis methods and commercially available intermediates, allowing access to laboratories without specialized synthetic chemistry capabilities. For the biotin-transfer method, ASB is linked to a protein ligand through the sulfhydryl group in a two-step process that allows the introduction of a disulfide bond between the ligand and the crosslinker. Incubation of the labelled ligand with oxidized live cells leads to the formation of crosslinks with aldehyde-containing glycans on the cell surface receptor. Subsequent reduction of the disulfide bond results in biotin transfer from the ligand to the cell surface receptor. Protein biotinylation that is mediated by ligand binding to its receptor is differentiated from background biotinylation events by comparison with a similarly labelled control protein using comparative proteomic mass spectrometry to quantify streptavidin-bound proteins. Using this method, we successfully identified the cell surface receptors of a peptide hormone, a monoclonal antibody, and a single-domain antibody-Fc fusion construct.

Computational selection of antibody-drug conjugate targets for breast cancer.

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics.

Glycoproteomic comparison of clinical triple-negative and luminal breast tumors.

Triple-negative (TN) breast cancer accounts for ∼ 15% of breast cancers and is characterized by a high likelihood of relapse and a lack of targeted therapies. In contrast, luminal-type tumors that express the estrogen and progesterone receptors (ER+/PR+) and lack expression of human epidermal growth factor receptor 2 (Her2-) are treated with targeted hormonal therapy and carry a better prognosis. To identify potential targets for the development of future therapeutics aimed specifically at TN breast cancers, we have used a hydrazide-based glycoproteomic workflow to compare protein expression in clinical tumors from nine TN (Her2-/ER-/PR-) and nine luminal (Her2-/ER+/PR+) patients. Using a label-free LC-MS based approach, we identified and quantified 2264 proteins. Of these, 90 proteins were more highly expressed and 86 proteins were underexpressed in the TN tumors relative to the luminal tumors. The expression level of four of these potential targets was verified in the original set of tumors by Western blot and correlated well with our mass-spectrometry-based quantification. Furthermore, 30% of the proteins differentially expressed between luminal and TN tumors were validated in a larger cohort of 406 TN and 469 luminal tumors through corresponding differences in their mRNA expression in publically available microarray data. A group of 29 of these differentially expressed proteins was shown to correctly classify 88% of TN and luminal tumors using microarray data of their associated mRNA levels. Interestingly, even within a group of TN breast cancer patients, the expression levels of these same mRNAs were able to significantly predict patient survival, suggesting that these proteins play a role in the aggressiveness seen in TN tumors. This study provides a comprehensive list of potential targets for the development of diagnostic and therapeutic agents specifically aimed at treating TN breast cancer and demonstrates the utility of using publicly available microarray data to further prioritize potential targets.

Identification of vascular breast tumor markers by laser capture microdissection and label-free LC-MS.

Blood vessels in tumors frequently show abnormal characteristics, such as tortuous morphology or leakiness, but very little is known about protein expression in tumor vessels. In this study, we have used laser capture microdissection (LCM) to isolate microvessels from clinical samples of invasive ductal carcinoma (IDC), the most common form of malignant breast cancer, and from patient-matched adjacent nonmalignant tissue. This approach eliminates many of the problems associated with the heterogeneity of clinical tumor tissues by controlling for differences in protein expression between both individual patients and different cell types. Proteins from the microvessels were trypsinized and the resulting peptides were quantified by a label-free nanoLC-MS method. A total of 86 proteins were identified that are overexpressed in tumor vessels relative to vessels isolated from the adjacent nonmalignant tissue. These proteins include well-known breast tumor markers such as Periostin and Tenascin C but also proteins with lesser-known or emerging roles in breast cancer and tumor angiogenesis (i.e., Serpin H1, Clic-1, and Transgelin 2). We also identified 40 proteins that were relatively under-expressed in IDC tumor vessels, including several components of the basement membrane whose lower expression could be responsible for weakening tumor vessels. Lastly, we show that a subset of 29 proteins, derived from our list of differentially expressed proteins, is able to predict survival in three publicly available clinical breast cancer microarray data sets, which suggests that this subset of proteins likely plays a functional role in cancer progression and outcome.

Methods to study glycoproteins at the blood-brain barrier using mass spectrometry.

Glycosylation is the most common posttranslational modification of proteins in mammalian cells and is limited mainly to membrane and secreted proteins. Glycoproteins play several key roles in the physiology and pathophysiology of the blood-brain barrier (BBB) and are attractive as diagnostic markers and therapeutic targets for many neurological diseases. However, large-scale glycoproteomic studies of the BBB have been lacking, largely due to the complexity of analyzing glycoproteins and a lack of available tools for this analysis. Recent development of the hydrazide capture method and significant advances in mass spectrometry (MS)-based proteomics over the last few years have enabled selective enrichment of glycoproteins from complex biological samples and their quantitative comparisons in multiple conditions. In this chapter, we describe methods for: (1) isolating membrane and secreted proteins from BEC and other cells of the neurovascular unit, (2) enriching glycoproteins using hydrazide capture, and (3) performing label-free quantitative proteomics to identify differential glycoprotein expression in various biological conditions. Hydrazide capture, when coupled with label-free quantitative proteomics, is a reproducible and sensitive method that allows for quantitative profiling of a large number of glycoproteins from biological samples for the purposes of differential expression measurements and biomarker discovery.

Identification of secreted proteins regulated by cAMP in glioblastoma cells using glycopeptide capture and label-free quantification.

Exposure of glioblastoma U87MG cells to a cAMP analog leads to a decrease in proliferation, invasion, and angiogenic potential. Here, we apply a label-free MS-based approach to identify formerly N-linked glycopeptides that change in abundance upon cAMP treatment. Over 150 unique glycopeptides in three biological repetitions were quantified, leading to the identification of 14 upregulated proteins and 21 downregulated proteins due to cAMP treatment. Of these, eight have been validated, either through comparison with microarray data or by Western blot. We estimate our ability to identify differentially expressed peptides at greater than 85% in a single biological repetition, while the analysis of multiple biological repetitions lowers the false positive rate to approximately 2%. Many of the proteins identified in this study are involved in cell signaling and some, such as Tenascin C, Cathepsin L, Neuroblastoma suppressor of tumorigenicity, and AXL/UFO tyrosine-protein kinase receptor, have been previously shown to be involved in glioblastoma progression. We also identify several semitryptic peptides that increase in abundance upon cAMP treatment, suggesting that cAMP regulates protease activity in these cells. Overall, these results demonstrate the benefits of using a highly specific enrichment method for quantitative proteomic experiments.