Monitoring matrix metalloproteinase activity at the epidermal-dermal interface by SILAC-iTRAQ-TAILS

Redefining metalloproteases specificity through network proteolysis

Proteolytic processes on cell surfaces and extracellular matrix (ECM) sustain cell behavior and tissue integrity in health and disease. Matrix metalloproteases (MMPs) and a disintegrin and metalloproteases (ADAMs) remodel cell microenvironments through irreversible proteolysis of ECM proteins and cell surface bioactive molecules. Pan-MMP inhibitors in inflammation and cancer clinical trials have encountered challenges due to promiscuous activities of MMPs. Systems biology advances revealed that MMPs initiate multifactorial proteolytic cascades, creating new substrates, activating or suppressing other MMPs, and generating signaling molecules. This review highlights the intricate network that underscores the role of MMPs beyond individual substrate-enzyme activities. Gaining insight into MMP function and tissue specificity is crucial for developing effective drug discovery strategies and novel therapeutics. This requires considering the dynamic cellular processes and consequences of network proteolysis.

Evaluating cPILOT Data toward Quality Control Implementation

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Degradomics technologies in matrisome exploration

Consisting of a defined set of extracellular proteins secreted from resident cells and with minor contributions from serum proteins, the extracellular matrix (ECM) is an essential component of all tissues. Maintaining tissue homeostasis, structural support and cellular control through cell-ECM communication, the ECM has come to be viewed as not just a passive structural entity but rather as a dynamic signaling conduit between cells and the extracellular compartment. Proteins and their cleavage products mediate this communication, and aberrant signaling, either directly or indirectly distorting the ECM, results in pathological conditions including cancer, inflammation, fibrosis, and neurodegenerative diseases. Characterization of ECM components, the matrisome, the extracellular environment and their changes in disease is therefore of importance to understand and mitigate by developing novel therapeutics. Liquid chromatography-mass spectrometry (LC-MS) proteomics has been integral to protein and proteome research for decades and long superseded the obsolescent gel-based approaches. A continuous effort has ensured progress with increased sensitivity and throughput as more advanced equipment has been developed hand in hand with specialized enrichment, detection, and identification methods. Part of this effort lies in the field of degradomics, a branch of proteomics focused on discovering novel protease substrates by identification of protease-generated neo-N termini, the N-terminome, and characterizing the responsible protease networks. Various methods to do so have been developed, some specialized for specific tissue types, others for particular proteases, throughput, or ease of use. This review aims to provide an overview of the state-of-the-art proteomics techniques that have successfully been recently utilized to characterize proteolytic cleavages in the ECM and thereby guided new research and understanding of the ECM and matrisome biology.

N-Terminomics Strategies for Protease Substrates Profiling

Proteases play a central role in various biochemical pathways catalyzing and regulating key biological events. Proteases catalyze an irreversible post-translational modification called proteolysis by hydrolyzing peptide bonds in proteins. Given the destructive potential of proteolysis, protease activity is tightly regulated. Dysregulation of protease activity has been reported in numerous disease conditions, including cancers, neurodegenerative diseases, inflammatory conditions, cardiovascular diseases, and viral infections. The proteolytic profile of a cell, tissue, or organ is governed by protease activation, activity, and substrate specificity. Thus, identifying protease substrates and proteolytic events under physiological conditions can provide crucial information about how the change in protease regulation can alter the cellular proteolytic landscape. In recent years, mass spectrometry-based techniques called N-terminomics have become instrumental in identifying protease substrates from complex biological mixtures. N-terminomics employs the labeling and enrichment of native and neo-N-termini peptides, generated upon proteolysis followed by mass spectrometry analysis allowing protease substrate profiling directly from biological samples. In this review, we provide a brief overview of N-terminomics techniques, focusing on their strengths, weaknesses, limitations, and providing specific examples where they were successfully employed to identify protease substrates in vivo and under physiological conditions. In addition, we explore the current trends in the protease field and the potential for future developments.

New strategies to identify protease substrates

Proteome dynamics is governed by transcription, translation, and post-translational modifications. Limited proteolysis is an irreversible post-translational modification that generates multiple but unique proteoforms from almost every native protein. Elucidating these proteoforms and understanding their dynamics at a system-wide level is of utmost importance because uncontrolled proteolytic cleavages correlate with many pathologies. Mass spectrometry-based degradomics has revolutionized protease research and invented workflows for global identification of protease substrates with resolution down to precise cleavage sites. In this review, we provide an overview of current strategies in protease substrate degradomics and introduce the concept of workflow, mass spectrometry-based and in silico enrichment of protein termini with the perspective of full deconvolution of digital proteome maps for precision medicine, and degradomics biomarker diagnostics.

An optimized quantitative proteomics method establishes the cell type-resolved mouse brain secretome

To understand how cells communicate in the nervous system, it is essential to define their secretome, which is challenging for primary cells because of large cell numbers being required. Here, we miniaturized secretome analysis by developing the “high‐performance secretome protein enrichment with click sugars” (hiSPECS) method. To demonstrate its broad utility, hiSPECS was used to identify the secretory response of brain slices upon LPS‐induced neuroinflammation and to establish the cell type‐resolved mouse brain secretome resource using primary astrocytes, microglia, neurons, and oligodendrocytes. This resource allowed mapping the cellular origin of CSF proteins and revealed that an unexpectedly high number of secreted proteins in vitro and in vivo are proteolytically cleaved membrane protein ectodomains. Two examples are neuronally secreted ADAM22 and CD200, which we identified as substrates of the Alzheimer‐linked protease BACE1. hiSPECS and the brain secretome resource can be widely exploited to systematically study protein secretion and brain function and to identify cell type‐specific biomarkers for CNS diseases.

HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics

Quantitative proteomics has evolved considerably over the last decade with the advent of higher order multiplexing (HOM) techniques. With the development of methods such as-multitagging, cPILOT, hyperplexing, BONPlex, and MITNCAT, the HOM technique is rapidly taking the center stage in multiplexed quantitative proteomics. These studies combined MS¹ and MS² labels in a single experiment enabling higher sample throughput. While HOM is highly promising, the computational analysis is still a big challenge, as the available tools cannot harness its power completely. We have developed a new quantitative pipeline, HyperQuant to aid in accurately quantitating complex HOM data. The pipeline uses identification results from either MaxQuant or any other search engine and quantitation results from QuantWiz^IQ. The Mapper and Combiner modules of HyperQuant allow facile integration of the labeled data, along with peptide spectrum match (PSM) intensity/ratio integration for proteins, respectively, for each PSM label combination. This also includes appropriate combination of replicates/fractions before summarizing the protein intensity/ratio, leading to robust quantitation. To the best of our knowledge, this is the first tool for the quantitation of HOM data with flexibility for any combination of MS¹ and MS² labels. We demonstrate its utility in analyzing two 18-plex data sets from the hyperplexing and the BONplex studies. The tool is open source and freely available for noncommercial use. HyperQuant is a highly valuable tool that will help in advancing the field of multiplexed quantitative proteomics.

Integration of Two In-depth Quantitative Proteomics Approaches Determines the Kallikrein-related Peptidase 7 (KLK7) Degradome in Ovarian Cancer Cell Secretome

Kallikrein-related peptidase 7 (KLK7) is a serine peptidase that is over expressed in ovarian cancer. In vitro functional analyses have suggested KLK7 to play a cancer progressive role, although monitoring of KLK7 expression has suggested a contradictory protective role for KLK7 in ovarian cancer patients. In order to help delineate its mechanism of action and thereby the functional roles, information on its substrate repertoire is crucial. Therefore, in this study a quantitative proteomics approach-PROtein TOpography and Migration Analysis Platform (PROTOMAP)-coupled with SILAC was used for in-depth analysis of putative KLK7 substrates from a representative ovarian cancer cell line, SKOV-3, secreted proteins. The Terminal Amine Isotopic Labeling of Substrates (TAILS) approach was used to determine the exact cleavage sites and to validate qPROTOMAP-identified putative substrates. By employing these two technically divergent approaches, exact cleavage sites on 16 novel putative substrates and two established substrates, matrix metalloprotease (MMP) 2 and insulin growth factor binding protein 3 (IGFBP3), were identified in the SKOV-3 secretome. Eight of these substrates were also identified on TAILS analysis of another ovarian cancer cell (OVMZ-6) secretome, with a further seven OVMZ-6 substrates common to the SKOV-3 qPROTOMAP profile. Identified substrates were significantly associated with the common processes of cell adhesion, extracellular matrix remodeling and cell migration according to the gene ontology (GO) biological process analysis. Biochemical validation supports a role for KLK7 in directly activating pro-MMP10, hydrolysis of IGFBP6 and cleavage of thrombospondin 1 with generation of a potentially bioactive N-terminal fragment. Overall, this study constitutes the most comprehensive analysis of the putative KLK7 degradome in any cancer to date, thereby opening new avenues for KLK7 research.

Multidimensional Analysis of Protease Substrates and Their Cellular Origins in Mixed Secretomes from Multiple Cell Types

Although extracellular proteases are confronted with substrate proteins expressed by multiple cell types in vivo, in most protease substrate discovery approaches, the test protease is exposed to a test proteome (secretome) derived only from a single cell type. This limits the potential substrate space and prohibits the formation of protein complexes constituted of components derived from multiple cellular origins. Mixing of secretomes collected from multiple cell types addresses this issue, but information on the cellular origin of a substrate protein is lost. Here, we describe a protocol and the corresponding data analysis workflow for a multidimensional substrate discovery approach termed SILAC -iTRAQ -TAILS that is based on hyperplexed terminal amine isotopic labeling of substrates (TAILS ), allowing identification of substrates and concomitant assignment to cellular origins in mixed secretomes within the same experiment.

Proteolytic signatures define unique thrombin-derived peptides present in human wound fluid in vivo

The disease burden of failing skin repair and non-healing ulcers is extensive. There is an unmet need for new diagnostic approaches to better predict healing activity and wound infection. Uncontrolled and excessive protease activity, of endogenous or bacterial origin, has been described as a major contributor to wound healing impairments. Proteolytic peptide patterns could therefore correlate and “report” healing activity and infection. This work describes a proof of principle delineating a strategy by which peptides from a selected protein, human thrombin, are detected and attributed to proteolytic actions. With a particular focus on thrombin-derived C-terminal peptides (TCP), we show that distinct peptide patterns are generated in vitro by the human S1 peptidases human neutrophil elastase and cathepsin G, and the bacterial M4 peptidases Pseudomonas aeruginosa elastase and Staphylococcus aureus aureolysin, respectively. Corresponding peptide sequences were identified in wound fluids from acute and non-healing ulcers, and notably, one peptide, FYT21 (FYTHVFRLKKWIQKVIDQFGE), was only present in wound fluid from non-healing ulcers colonized by P. aeruginosa and S. aureus. Our result is a proof of principle pointing at the possibility of defining peptide biomarkers reporting distinct proteolytic activities, of potential implication for improved diagnosis of wound healing and infection.

Clinical Implications of Compounds Designed to Inhibit ECM-Modifying Metalloproteinases

Remodeling of the extracellular matrix (ECM) is crucial in development and homeostasis, but also has a significant role in disease progression. Two metalloproteinase families, the matrix metalloproteinases (MMPs) and a disintegrin and metalloproteases (ADAMs), participate in the remodeling of the ECM, either directly or through the liberation of growth factors and cell surface receptors. The correlation of MMP and ADAM activity to a variety of diseases has instigated numerous drug development programs. However, broad-based and Zn²⁺ -chelating MMP and ADAM inhibitors have fared poorly in the clinic. Selective MMP and ADAM inhibitors have been described recently based on (a) antibodies or antibody fragments or (b) small molecules designed to take advantage of protease secondary binding sites (exosites) or allosteric sites. Clinical trials have been undertaken with several of these inhibitors, while others are in advanced pre-clinical stages.

Proteomic definitions of basement membrane composition in health and disease

Basement membranes are formed from condensed networks of extracellular matrix (ECM) proteins. These structures underlie all epithelial, mesothelial and endothelial sheets and provide an essential structural scaffold. Candidate-based investigations have established that predominant components of basement membranes are laminins, collagen type IV, nidogens and heparan sulphate proteoglycans. More recently, global proteomic approaches have been applied to investigate ECM and these analyses confirm tissue-specific ECM proteomes with a high degree of complexity. The proteomes consist of structural as well as regulatory ECM proteins such as proteases and growth factors. This review is focused on the proteomic analysis of basement membranes and illustrates how this approach can be used to build our understanding of ECM regulation in health and disease.

TIMPs: versatile extracellular regulators in cancer

A compelling long-term goal of cancer biology is to understand the crucial players during tumorigenesis in order to develop new interventions. Here, we review how the four non-redundant tissue inhibitors of metalloproteinases (TIMPs) regulate the pericellular proteolysis of a vast range of matrix and cell surface proteins, generating simultaneous effects on tumour architecture and cell signalling. Experimental studies demonstrate the contribution of TIMPs to the majority of cancer hallmarks, and human cancers invariably show TIMP deregulation in the tumour or stroma. Of the four TIMPs, TIMP1 overexpression or TIMP3 silencing is consistently associated with cancer progression or poor patient prognosis. Future efforts will align mouse model systems with changes in TIMPs in patients, will delineate protease-independent TIMP function, will pinpoint therapeutic targets within the TIMP-metalloproteinase-substrate network and will use TIMPs in liquid biopsy samples as biomarkers for cancer prognosis.

Matrix Metalloproteinase 10 Degradomics in Keratinocytes and Epidermal Tissue Identifies Bioactive Substrates With Pleiotropic Functions

Matrix metalloproteinases (MMPs) are important players in skin homeostasis, wound repair, and in the pathogenesis of skin cancer. It is now well established that most of their functions are related to processing of bioactive proteins rather than components of the extracellular matrix (ECM). MMP10 is highly expressed in keratinocytes at the wound edge and at the invasive front of tumors, but hardly any non-ECM substrates have been identified and its function in tissue repair and carcinogenesis is unclear. To better understand the role of MMP10 in the epidermis, we employed multiplexed iTRAQ-based Terminal Amine Isotopic Labeling of Substrates (TAILS) and monitored MMP10-dependent proteolysis over time in secretomes from keratinocytes. Time-resolved abundance clustering of neo-N termini classified MMP10-dependent cleavage events by efficiency and refined the MMP10 cleavage site specificity by revealing a so far unknown preference for glutamate in the P1 position. Moreover, we identified and validated the integrin alpha 6 subunit, cysteine-rich angiogenic inducer 61 and dermokine as novel direct MMP10 substrates and provide evidence for MMP10-dependent but indirect processing of phosphatidylethanolamine-binding protein 1. Finally, we sampled the epidermal proteome and degradome in unprecedented depth and confirmed MMP10-dependent processing of dermokine in vivo by TAILS analysis of epidermis from transgenic mice that overexpress a constitutively active mutant of MMP10 in basal keratinocytes. The newly identified substrates are involved in cell adhesion, migration, proliferation, and/or differentiation, indicating a contribution of MMP10 to local modulation of these processes during wound healing and cancer development. Data are available via ProteomeXchange with identifier PXD002474.