Quantitative Protease Cleavage Site Profiling using Tandem-Mass-Tag Labeling and LC–MALDI-TOF/TOF MS/MS Analysis

GeLC-FAIMS-MS workflow for in-depth middle-down proteomics

Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

The Antiviral Effect of Isatis Root Polysaccharide against NADC30-like PRRSV by Transcriptome and Proteome Analysis

(1) Background: In recent years, the porcine reproductive and respiratory syndrome virus (PRRSV) has become a virulent pathogen that has caused devastating diseases and economic losses worldwide in the swine industry. IRPS has attracted extensive attention in the field of virology. However, it is not clear that IRPS has an antiviral effect on PRRSV at gene and protein levels. (2) Methods: We used transcriptomic and proteomic analysis to investigate the antiviral effect of IRPS against PRRSV. Additionally, a microbiome was used to explore the effects of IRPS on gut microbes. (3) Results: IRPS significantly extenuated the pulmonary pathological lesions and inflammatory response. We used transcriptomic and proteomic analysis to investigate the antiviral effect of IRPS against PRRSV. In the porcine model, 1669 differentially expressed genes (DEGs) and 370 differentially expressed proteins (DEPs) were identified. Analysis of the DEG/DEP-related pathways indicated immune-system and infectious-disease (viral) pathways, such as the NOD-like receptor (NLR) signaling pathway, toll-like receptor (TLR) signaling pathway, and Influenza A-associated signaling pathways. It is noteworthy that IRPS can inhibit NLR-dependent gene expression, then reduce the inflammatory damage. IRPS could exert beneficial effects on the host by regulating the structure of intestinal flora. (4) Conclusions: The antiviral effect of IRPS on PRRSV can be directly achieved by omics techniques. Specifically, the antiviral mechanism of IPRS can be better elucidated by screening target genes and proteins using transcriptome and proteome sequencing, and then performing enrichment and classification according to DEGs and DEPs.

Candidate gene screening for lipid deposition using combined transcriptomic and proteomic data from Nanyang black pigs

Background

Lower selection intensities in indigenous breeds of Chinese pig have resulted in obvious genetic and phenotypic divergence. One such breed, the Nanyang black pig, is renowned for its high lipid deposition and high genetic divergence, making it an ideal model in which to investigate lipid position trait mechanisms in pigs. An understanding of lipid deposition in pigs might improve pig meat traits in future breeding and promote the selection progress of pigs through modern molecular breeding techniques. Here, transcriptome and tandem mass tag-based quantitative proteome (TMT)-based proteome analyses were carried out using longissimus dorsi (LD) tissues from individual Nanyang black pigs that showed high levels of genetic variation.

Results

A large population of Nanyang black pigs was phenotyped using multi-production trait indexes, and six pigs were selected and divided into relatively high and low lipid deposition groups. The combined transcriptomic and proteomic data identified 15 candidate genes that determine lipid deposition genetic divergence. Among them, FASN, CAT, and SLC25A20 were the main causal candidate genes. The other genes could be divided into lipid deposition-related genes (BDH2, FASN, CAT, DHCR24, ACACA, GK, SQLE, ACSL4, and SCD), PPARA-centered fat metabolism regulatory factors (PPARA, UCP3), transcription or translation regulators (SLC25A20, PDK4, CEBPA), as well as integrin, structural proteins, and signal transduction-related genes (EGFR).

Conclusions

This multi-omics data set has provided a valuable resource for future analysis of lipid deposition traits, which might improve pig meat traits in future breeding and promote the selection progress in pigs, especially in Nanyang black pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07764-2.

Bottom-up sample preparation for the LC-MS/MS quantification of anti-cancer monoclonal antibodies in bio matrices

Therapeutic monoclonal antibodies (mAbs) are rapidly taking over the treatment of many malignancies, and an astonishing number of mAbs is in development. This causes a high demand for quantification of mAbs in biomatrices both for measuring therapeutic mAb concentrations and to support pharmacokinetics and pharmacodynamics studies. Conventionally, ligand-binding assays are used for these purposes, but LC-MS is gaining popularity. Although intact (top-down) and subunit (middle-down) mAb quantification is reported, signature peptide (bottom-up) quantification is currently most advantageous. This review provides an overview of the reported bottom-up mAb quantification methods in biomatrices as well as general recommendations regarding signature peptide and internal standard selection, reagent use and optimization of digestion in bottom-up quantification methods.

LIPH promotes metastasis by enriching stem-like cells in triple-negative breast cancer

Lipase member H (LIPH), a novel member of the triglyceride lipase family. The clinical implications of its expression in breast cancer are still unclear. Therefore, in this study, we investigated the associations between LIPH and the tumorigenic behaviours of 144 triple-negative breast cancer (TNBC) patients. The ratio and mammosphere-forming ability of CD44+/CD24- stem-like cells were tested. The role of LIPH in breast cancer cell migration and invasion was also evaluated. In addition, the effect of LIPH silencing on mitochondrial respiration was determined using the Seahorse assay. Finally, the effect of LIPH silencing on protein expression was determined via tandem mass tag-based spectrometry and Western blotting. We found that LIPH expression was associated with metastasis in lymph nodes and distant organs (P = 0.025), resulting in poor survival among breast cancer patients (P = 0.027). LIPH knockdown significantly decreased both the ratio of CD44+ /CD24- stem-like cells and their mammosphere-forming ability. LIPH silencing promoted apoptosis, arrested cell cycle in the G2/M phase, mitigated the oxidation-related oxygen consumption rate in the mitochondria, and reduced metabolism. LIPH inhibited adhesion between tumour cells and enhanced the epithelial-mesenchymal transition. Tandem mass spectrometric analysis presented 68 proteins were differentially expressed in LIPH-silenced cells and LIPH-mediated modulation of tumour cell adhesion depended on integrin-related CAPN2 and paxillin signalling. Overall, our findings provided strong evidence that LIPH up-regulation promoted metastasis and the stemness of TNBC cells. Therefore, targeting LIPH is a potentially viable strategy for preventing metastasis in TNBC.

Top-Down Proteomic Characterization of Truncated Proteoforms

A top-down proteomic strategy with semiautomated analysis of data sets has proven successful for the global identification of truncated proteins without the use of chemical derivatization, enzymatic manipulation, immunoprecipitation, or other enrichment. This approach provides the reliable identification of internal polypeptides formed from precursor gene products by proteolytic cleavage of both the N- and C-termini, as well as truncated proteoforms that retain one or the other termini. The strategy has been evaluated by application to the immunosuppressive extracellular vesicles released by myeloid-derived suppressor cells. More than 1000 truncated proteoforms have been identified, from which binding motifs are derived to allow characterization of the putative proteases responsible for truncation.

Quantitative Multiplex Substrate Profiling of Peptidases by Mass Spectrometry

Proteolysis is an integral component of life and has been implicated in many disease processes. To improve our understanding of peptidase function, it is imperative to develop tools to uncover substrate specificity and cleavage efficiency. Here, we combine the quantitative power of tandem mass tags (TMTs) with an established peptide cleavage assay to yield quantitative Multiplex Substrate Profiling by Mass Spectrometry (qMSP-MS). This assay was validated with papain, a well-characterized cysteine peptidase, to generate cleavage efficiency values for hydrolysis of 275 unique peptide bonds in parallel. To demonstrate the breath of this assay, we show that qMSP-MS can uncover the substrate specificity of minimally characterized intramembrane rhomboid peptidases, as well as define hundreds of proteolytic activities in complex biological samples, including secretions from lung cancer cell lines. Importantly, our qMSP-MS library uses synthetic peptides whose termini are unmodified, allowing us to characterize not only endo- but also exo-peptidase activity. Each cleaved peptide sequence can be ranked by turnover rate, and the amino acid sequence of the best substrates can be used for designing fluorescent reporter substrates. Discovery of peptide substrates that are selectively cleaved by peptidases which are active at the site of disease highlights the potential for qMSP-MS to guide the development of peptidase-activating drugs for cancer and infectious disease.

Protease cleavage site fingerprinting by label-free in-gel degradomics reveals pH-dependent specificity switch of legumain

Determination of protease specificity is of crucial importance for understanding protease function. We have developed the first gel-based label-free proteomic approach (DIPPS-direct in-gel profiling of protease specificity) that enables quick and reliable determination of protease cleavage specificities under large variety of experimental conditions. The methodology is based on in-gel digestion of the gel-separated proteome with the studied protease, enrichment of cleaved peptides by gel extraction, and subsequent mass spectrometry analysis combined with a length-limited unspecific database search. We applied the methodology to profile ten proteases ranging from highly specific (trypsin, endoproteinase GluC, caspase-7, and legumain) to broadly specific (matrix-metalloproteinase-3, thermolysin, and cathepsins K, L, S, and V). Using DIPPS, we were able to perform specificity profiling of thermolysin at its optimal temperature of 75°C, which confirmed the applicability of the method to extreme experimental conditions. Moreover, DIPPS enabled the first global specificity profiling of legumain at pH as low as 4.0, which revealed a pH-dependent change in the specificity of this protease, further supporting its broad applicability.

Top-down proteomics for the analysis of proteolytic events - Methods, applications and perspectives

Mass spectrometry based proteomics is an indispensable tool for almost all research areas relevant for the understanding of proteolytic processing, ranging from the identification of substrates, products and cleavage sites up to the analysis of structural features influencing protease activity. The majority of methods for these studies are based on bottom-up proteomics performing analysis at peptide level. As this approach is characterized by a number of pitfalls, e.g. loss of molecular information, there is an ongoing effort to establish top-down proteomics, performing separation and MS analysis both at intact protein level. We briefly introduce major approaches of bottom-up proteomics used in the field of protease research and highlight the shortcomings of these methods. We then discuss the present state-of-the-art of top-down proteomics. Together with the discussion of known challenges we show the potential of this approach and present a number of successful applications of top-down proteomics in protease research. This article is part of a Special Issue entitled: Proteolysis as a Regulatory Event in Pathophysiology edited by Stefan Rose-John.

Multiplexed Protease Specificity Profiling Using Isobaric Labeling

The determination of a protease's cleavage site specificity is one of the major goals in degradomics. In the last years, the use of proteome-derived peptide libraries and liquid chromatography-mass spectrometry (LC-MS) in a proteomic identification of protease cleavage sites (PICS) experiment became popular for that purpose.In this chapter, we offer a step-by-step protocol for the execution of a quantitative proteomic identification of protease cleavage sites (Q-PICS) experiment, which enables the relative quantification of proteolytic events by isobaric labeling, e.g., with tandem mass tags (TMT). In this way, the cleavage site specificity and activity of a protease can be compared under different reaction conditions (e.g., buffer, pH, temperature, inhibitor). Multiplexing can further be used to analyze replicate experiments in parallel, decreasing instrument times and work effort significantly, or to perform internal controls.

Determinants of Macromolecular Specificity from Proteomics-Derived Peptide Substrate Data

BACKGROUND

Recent advances in proteomics methodologies allow for high throughput profiling of proteolytic cleavage events. The resulting substrate peptide distributions provide deep insights in the underlying macromolecular recognition events, as determinants of biomolecular specificity identified by proteomics approaches may be compared to structure-based analysis of corresponding protein-protein interfaces.

METHOD

Here, we present an overview of experimental and computational methodologies and tools applied in the area and provide an outlook beyond the protein class of proteases.

RESULTS AND CONCLUSION

We discuss here future potential, synergies and needs of the emerging overlap disciplines of proteomics and structure-based modelling.

Identification of Protease Specificity by Combining Proteome-Derived Peptide Libraries and Quantitative Proteomics

We present protease specificity profiling based on quantitative proteomics in combination with proteome-derived peptide libraries. Peptide libraries are generated by endoproteolytic digestion of proteomes without chemical modification of primary amines before exposure to a protease under investigation. After incubation with a test protease, treated and control libraries are differentially isotope-labeled using cost-effective reductive dimethylation. Upon analysis by liquid chromatography-tandem mass spectrometry, cleavage products of the test protease appear as semi-specific peptides that are enriched for the corresponding isotope label. We validate our workflow with two proteases with well-characterized specificity profiles: trypsin and caspase-3. We provide the first specificity profile of a protease encoded by a human endogenous retrovirus and for chlamydial protease-like activity factor (CPAF). For CPAF, we also highlight the structural basis of negative subsite cooperativity between subsites S1 and S2'. For A disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) -4, -5, and -15, we show a canonical preference profile, including glutamate in P1 and glycine in P3'. In total, we report nearly 4000 cleavage sites for seven proteases. Our protocol is fast, avoids enrichment or synthesis steps, and enables probing for lysine selectivity as well as subsite cooperativity. Due to its simplicity, we anticipate usability by most proteomic laboratories.

The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD)

The field of proteomics almost uniformly relies on peptide cation analysis, leading to an underrepresentation of acidic portions of proteomes, including relevant acidic posttranslational modifications. Despite the many benefits negative mode proteomics can offer, peptide anion analysis remains in its infancy due mainly to challenges with high-pH reversed-phase separations and a lack of robust fragmentation methods suitable for peptide anion characterization. Here, we report the first implementation of activated ion negative electron transfer dissociation (AI-NETD) on the chromatographic timescale, generating 7,601 unique peptide identifications from Saccharomyces cerevisiae in single-shot nLC-MS/MS analyses of tryptic peptides-a greater than 5-fold increase over previous results with NETD alone. These improvements translate to identification of 1,106 proteins, making this work the first negative mode study to identify more than 1,000 proteins in any system. We then compare the performance of AI-NETD for analysis of peptides generated by five proteases (trypsin, LysC, GluC, chymotrypsin, and AspN) for negative mode analyses, identifying as many as 5,356 peptides (1,045 proteins) with LysC and 4,213 peptides (857 proteins) with GluC in yeast-characterizing 1,359 proteins in total. Finally, we present the first deep-sequencing approach for negative mode proteomics, leveraging offline low-pH reversed-phase fractionation prior to online high-pH separations and peptide fragmentation with AI-NETD. With this platform, we identified 3,467 proteins in yeast with trypsin alone and characterized a total of 3,730 proteins using multiple proteases, or nearly 83% of the expressed yeast proteome. This work represents the most extensive negative mode proteomics study to date, establishing AI-NETD as a robust tool for large-scale peptide anion characterization and making the negative mode approach a more viable platform for future proteomic studies.

Proteomic approaches to uncover MMP function

Proteomics has revolutionized protease research and particularly contributed to the identification of novel substrates and their sites of cleavage as key determinants of protease function. New technologies and rapid advancements in development of powerful mass spectrometers allowed unprecedented insights into activities of matrix metalloproteinases (MMPs) within their complex extracellular environments. Mass spectrometry-based proteomics extended our knowledge on MMP cleavage specificities and will help to develop more specific inhibitors as new therapeutics. Quantitative proteomics and N-terminal enrichment strategies have revealed numerous novel MMP substrates and shed light on their modes of action in vitro and in vivo. In this review, we provide an overview of current proteomic technologies in protease research and their application to the functional characterization of MMPs.

LC-MS based cleavage site profiling of the proteases ADAM10 and ADAM17 using proteome-derived peptide libraries

A Disintegrin and Metalloproteinase 10 (ADAM10) and ADAM17 catalyze ectodomain shedding of a number of cell surface proteins important for embryonic development and tissue homeostasis. Changes in the expression levels or dysregulated proteolytic activity of ADAM10 and ADAM17 have been shown to play important roles in multiple diseases such as inflammation, cancer, and neurodegenerative disorders. Despite the well documented substrate repertoire of ADAM10 and ADAM17, little is known about their cleavage site specificity. We optimized Q-PICS (Quantitative Proteomics for the Identification of Cleavage Sites) to elucidate the cleavage site specificity of recombinant murine ADAM10 and ADAM17. Two different yeast proteome-derived peptide libraries were used and samples were analyzed by LC-MALDI and LC-ESI MS in parallel. We show that the largest difference in the cleavage site specificities of ADAM10 and ADAM17 is at the P1' site: while both enzymes cleave N-terminal of leucine, only ADAM10 shows additional preference toward aromatic amino acids, whereas ADAM17 exhibits the highest preference for valine. Together with further amino acid preferences more adjacent to the scissile bond, our data is in good agreement with ADAM10/17 cleavage sites previously identified in native substrates. Overall, the precise identification of ADAM10 and ADAM17 cleavage site specificity provides the basis for better substrate identification in vivo and the generation of specific inhibitors or activity based probes.

A novel UV-MALDI-MS analytical approach for determination of halogenated phenyl-containing pesticides

The paper highlighted the capability of the UV-MALDI mass spectrometry, employing the Orbitrap analyzer for solid-state assay of halogenated phenyl-pesticides in mixtures. It is successfully applied for the analysis of eighteen (1)-(18) molecular objects of Fenarimol (1) type and their condensation products (P5)-(P12). The full method and technique validation is performed using the dried droplet sample preparation technique on embedded analytes in novel organic matrix crystals of N-(1H-benzoimidazol-2-yl)-guanidine (M4) and (E)-phenyl-2-pyridyl ketone oxime (M5), resulting to successful ionization of the analytes. Since the sampling technique in the UV-MALDI method is a key step in the overall process impacting significantly the metrology through the reproducibility of the data, the crystallization of M4, M5 and matrix-analyte in situ morphology of the samples is controlled by single crystal X-ray diffraction. The achieved promising metrology of LODs, of 0.46ngkg(-1) (1.53ngkg(-1) LOQs), is several orders of magnitude lower than the reported ecotoxicological effect values of studied pesticides. It is confirmed by the partial validated protocol based on ESI-MS. Inasmuch that LC-MS/MS is a method of choice for foodstuffs monitoring of organic contaminations, due to its routine quantitative analytical procedures, it is often characterized with the difficulties of the chromatographic separation of the closely structured analytes at a large scale of experimental conditions, complex multi-step sampling pretreatments, which inevitably alert the variables through the systematic and random errors. In this respect, notwithstanding the complex quantitative UV-MALDI-Orbitrap-MS procedure, conceptually different from the LC-MS/MS one, its high resolving power, capability for achieving meaningful analytical qualitative, quantitative and structural information of low-molecular weight analytes, its instrumental and sampling operation flexibility, applicable for a large scale of foodstuff matrices, and operating at the analyte concentrations of up to fgg(-1) make UV-MALDI-Orbitrap-MS a perspective method of choice for an extensive implementation in the foodstuffs monitoring practice for control of the most essential task related to the assessment of the human health risks from environmental and foodstuff contaminations.

Glycocapture-based proteomics for secretome analysis

Protein glycosylation represents the most abundant extracellular posttranslational modification in multicellular organisms. These glycoproteins unequivocally comprise the major biomolecules involved in extracellular processes, such as growth factors, signaling proteins for cellular communication, enzymes, and proteases for on- and off-site processing. It is now known that altered protein glycosylation is a hallmark event in many different pathologies. Glycoproteins are found mostly in the so-called secretome, which comprises classically and nonclassically secreted proteins and protein fragments that are released from the cell surface through ectodomain shedding. Due to biological complexity and technical difficulty, comparably few studies have taken an in-depth investigation of cellular secretomes using system-wide approaches. The cellular secretomes are considered to be a valuable source of therapeutic targets and novel biomarkers. It is not surprising that many existing biomarkers, including biomarkers for breast, ovarian, prostate, and colorectal cancers are glycoproteins. Focused analysis of secreted glycoproteins could thus provide valuable information for early disease diagnosis, and surveillance. Furthermore, since most secreted proteins are glycosylated and glycosylation predominantly targets secreted proteins, the glycan/sugar moiety itself can be used as a chemical "handle" for the targeted analysis of cellular secretomes, thereby reducing sample complexity and allowing detection of low abundance proteins in proteomic workflows. This review will focus on various glycoprotein enrichment strategies that facilitate proteomics-based technologies for the quantitative analysis of cell secretomes and cell surface proteomes.

Improved reporter ion assignment of raw isobaric stable isotope labeled liquid chromatography/matrix-assisted laser desorption/ionization tandem time-of-flight mass spectral data for quantitative proteomics

RATIONALE

Isobaric labeling strategies (e.g. iTRAQ or TMT) are commonly applied in tandem mass spectrometric (MS/MS) level quantitative proteomics. However, we frequently observed missing isotope reporter ion signals in a large-scale liquid chromatography/matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometric (LC/MALDI-TOF/TOF) quantitative proteomics experiment. To understand this issue, we systematically investigated the processing of MS/MS spectra into peak lists prior to peptide identification and quantification.

METHODS

A 15-protein standard, with six proteins in different concentrations, was labeled with iTRAQ 4-plex, iTRAQ 8-plex or TMT 6-plex, tryptic digested and measured using LC/MALDI-TOF/TOF. Three commercially and open-source available peak list generation software tools were compared based on missing reporter ions, peptide identification and quantification.

RESULTS

We found that each tool discarded lower-intensity reporter ions, when they followed a higher intensity reporter ion, due to the implemented de-isotoping algorithms. By using the non-de-isotoping setting within TS2Mascot, we found that all reporter ions are exported, yet less peptides were identified with Mascot. Therefore, we developed a strategy merging the de-isotoped and non-de-isotoped outputs from TS2Mascot using the Perl script RICmerge.pl.

CONCLUSIONS

With this approach, we correctly quantified all labeled peptides that were identified within the 15-protein standard. This strategy allows improved annotation of isobaric tag labeled peptide MS/MS spectra and improves downstream peptide and protein quantification in proteomics studies.