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Deconvoluting complex protein interaction networks through reductionist strategies in peptide biochemistry: Modern approaches and research questions

Following the decoding of the first human genome, researchers have vastly improved their understanding of cell biology and its regulation. As a result, it has become clear that it is not merely genetic information, but the aberrant changes in the functionality and connectivity of its encoded proteins that drive cell response to periods of stress and external cues. Therefore, proper utilization of refined methods that help to describe protein signalling or regulatory networks (i.e., functional connectivity), can help us understand how change in the signalling landscape effects the cell. However, given the vast complexity in 'how and when' proteins communicate or interact with each other, it is extremely difficult to define, characterize, and understand these interaction networks in a tangible manner. Herein lies the challenge of tackling the functional proteome; its regulation is encoded in multiple layers of interaction, chemical modification and cell compartmentalization. To address and refine simple research questions, modern reductionist strategies in protein biochemistry have successfully used peptide-based experiments; their summation helping to simplify the overall complexity of these protein interaction networks. In this way, peptides are powerful tools used in fundamental research that can be readily applied to comparative biochemical research. Understanding and defining how proteins interact is one of the key aspects towards understanding how the proteome functions. To date, reductionist peptide-based research has helped to address a wide range of proteome-related research questions, including the prediction of enzymes substrates, identification of posttranslational modifications, and the annotation of protein interaction partners. Peptide arrays have been used to identify the binding specificity of reader domains, which are able to recognise the posttranslational modifications; forming dynamic protein interactions that are dependent on modification state. Finally, representing one of the fastest growing classes of inhibitor molecules, peptides are now begin explored as "disruptors" of protein-protein interactions or enzyme activity. Collectively, this review will discuss the use of peptides, peptide arrays, peptide-oriented computational biochemistry as modern reductionist strategies in deconvoluting the functional proteome.

xiSPEC: web-based visualization, analysis and sharing of proteomics data

We present xiSPEC, a standard compliant, next-generation web-based spectrum viewer for visualizing, analyzing and sharing mass spectrometry data. Peptide-spectrum matches from standard proteomics and cross-linking experiments are supported. xiSPEC is to date the only browser-based tool supporting the standardized file formats mzML and mzIdentML defined by the proteomics standards initiative. Users can either upload data directly or select files from the PRIDE data repository as input. xiSPEC allows users to save and share their datasets publicly or password protected for providing access to collaborators or readers and reviewers of manuscripts. The identification table features advanced interaction controls and spectra are presented in three interconnected views: (i) annotated mass spectrum, (ii) peptide sequence fragmentation key and (iii) quality control error plots of matched fragments. Highlighting or selecting data points in any view is represented in all other views. Views are interactive scalable vector graphic elements, which can be exported, e.g. for use in publication. xiSPEC allows for re-annotation of spectra for easy hypothesis testing by modifying input data. xiSPEC is freely accessible at http://spectrumviewer.org and the source code is openly available on https://github.com/Rappsilber-Laboratory/xiSPEC.

Systematic analysis of synergistic proteome modulations in a drug combination of cisplatin and MLN4924

Chemotherapeutic treatment regimens often take advantage of synergistic effects of drug combinations. Anticipating that synergistic effects on the cell biological level likely manifest on the proteome level, the analysis of proteome modulations represents an appropriate strategy to study drug combinations on a molecular level. More specifically, the detection of single proteins exhibiting synergistic abundance changes could be helpful to shed light on key molecules, which contribute in mechanisms facilitating the synergistic interaction and therefore represent potential targets for specific therapeutic approaches. In the reported study we aimed to provide evidence for this assumption and investigated the drug combination of cisplatin and the neddylation inhibitor MLN4924 in HCT-116 cells via cell biological analyses and mass spectrometry-based quantitative proteomics. From 1789 proteins quantified with two unique peptides, activated RNA polymerase II transcriptional coactivator p15 (SUB1) was highlighted as the most synergistically regulated protein using a synergistic scoring approach. Western blotting and analyses of cellular processes associated with this protein (DNA damage, oxidative stress and apoptosis) revealed supporting evidence for the synergistic regulation. Whereas the distinct role of SUB1 in the investigated drug combination needs to be elucidated in future studies, the presented results demonstrated the benefit and feasibility of synergistic scoring of proteome alterations to highlight proteins that likely contribute to the underlying molecular mechanisms of synergistic effects. Data are available via ProteomeXchange with identifier PXD009185.

Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer

Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.

A Mass Spectrometry-Based Profiling of Interactomes of Viral DDB1- and Cullin Ubiquitin Ligase-Binding Proteins Reveals NF-κB Inhibitory Activity of the HIV-2-Encoded Vpx

Viruses and hosts are situated in a molecular arms race. To avoid morbidity and mortality, hosts evolved antiviral restriction factors. These restriction factors exert selection pressure on the viruses and drive viral evolution toward increasingly efficient immune antagonists. Numerous viruses exploit cellular DNA damage-binding protein 1 (DDB1)-containing Cullin RocA ubiquitin ligases (CRLs) to induce the ubiquitination and subsequent proteasomal degradation of antiviral factors expressed by their hosts. To establish a comprehensive understanding of the underlying protein interaction networks, we performed immuno-affinity precipitations for a panel of DDB1-interacting proteins derived from viruses such as mouse cytomegalovirus (MCMV, Murid herpesvirus [MuHV] 1), rat cytomegalovirus Maastricht MuHV2, rat cytomegalovirus English MuHV8, human cytomegalovirus (HCMV), hepatitis B virus (HBV), and human immunodeficiency virus (HIV). Cellular interaction partners were identified and quantified by mass spectrometry (MS) and validated by classical biochemistry. The comparative approach enabled us to separate unspecific interactions from specific binding partners and revealed remarkable differences in the strength of interaction with DDB1. Our analysis confirmed several previously described interactions like the interaction of the MCMV-encoded interferon antagonist pM27 with STAT2. We extended known interactions to paralogous proteins like the interaction of the HBV-encoded HBx with different Spindlin proteins and documented interactions for the first time, which explain functional data like the interaction of the HIV-2-encoded Vpr with Bax. Additionally, several novel interactions were identified, such as the association of the HIV-2-encoded Vpx with the transcription factor RelA (also called p65). For the latter interaction, we documented a functional relevance in antagonizing NF-κB-driven gene expression. The mutation of the DDB1 binding interface of Vpx significantly impaired NF-κB inhibition, indicating that Vpx counteracts NF-κB signaling by a DDB1- and CRL-dependent mechanism. In summary, our findings improve the understanding of how viral pathogens hijack cellular DDB1 and CRLs to ensure efficient replication despite the expression of host restriction factors.

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics

The first stable version of the Proteomics Standards Initiative mzIdentML open data standard (version 1.1) was published in 2012-capturing the outputs of peptide and protein identification software. In the intervening years, the standard has become well-supported in both commercial and open software, as well as a submission and download format for public repositories. Here we report a new release of mzIdentML (version 1.2) that is required to keep pace with emerging practice in proteome informatics. New features have been added to support: (1) scores associated with localization of modifications on peptides; (2) statistics performed at the level of peptides; (3) identification of cross-linked peptides; and (4) support for proteogenomics approaches. In addition, there is now improved support for the encoding of de novo sequencing of peptides, spectral library searches, and protein inference. As a key point, the underlying XML schema has only undergone very minor modifications to simplify as much as possible the transition from version 1.1 to version 1.2 for implementers, but there have been several notable updates to the format specification, implementation guidelines, controlled vocabularies and validation software. mzIdentML 1.2 can be described as backwards compatible, in that reading software designed for mzIdentML 1.1 should function in most cases without adaptation. We anticipate that these developments will provide a continued stable base for software teams working to implement the standard. All the related documentation is accessible at http://www.psidev.info/mzidentml.

Label-free Proteomic Analysis of Exosomes Derived from Inducible Hepatitis B Virus-Replicating HepAD38 Cell Line

Hepatitis B virus (HBV) infection is a major health problem worldwide. Recent evidence suggests that some viruses can manipulate the infection process by packing specific viral and cellular components into exosomes, small nanometer-sized (30-150 nm) vesicles secreted from various cells. However, the impact of HBV replication on the content of exosomes produced by hepatocytes has not been fully delineated. In this work, an HBV-inducible cell line HepAD38 was used to directly compare changes in the protein content of exosomes secreted from HepAD38 cells with or without HBV replication. Exosomes were isolated from supernantants of HepAD38 cells cultured with or without doxycycline (dox) and their purity was confirmed by transmission electron microscopy (TEM) and Western immunoblotting assays. Ion-intensity based label-free LC-MS/MS quantitation technologies were applied to analyze protein content of exosomes from HBV replicating cells [referred as HepAD38 (dox^-)-exo] and from HBV nonreplicating cells [referred as HepAD38 (dox⁺)-exo]. A total of 1412 exosomal protein groups were identified, among which the abundance of 35 proteins was significantly changed following HBV replication. Strikingly, 5 subunit proteins from the 26S proteasome complex, including PSMC1, PSMC2, PSMD1, PSMD7 and PSMD14 were consistently enhanced in HepAD38 (dox^-)-exo. Bioinformatic analysis of differential exosomal proteins confirmed the significant enrichment of components involved in the proteasomal catabolic process. Proteasome activity assays further suggested that HepAD38 (dox^-)-exo had enhanced proteolytic activity compared with HepAD38 (dox⁺)-exo. Furthermore, human peripheral monocytes incubated with HepAD38 (dox^-)-exo induced a significantly lower level of IL-6 secretion compared with IL-6 levels from HepAD38 (dox⁺)-exo. Irreversible inhibition of proteasomal activity within exosomes restored higher production of IL-6 by monocytes, suggesting that transmission of proteasome subunit proteins by HepAD38 (dox^-)-exo might modulate the production of pro-inflammatory molecules in the recipient monocytes. These results revealed the composition and potential function of exosomes produced during HBV replication, thus providing a new perspective on the role of exosomes in HBV-host interaction.

C-Terminal Charge-Reversal Derivatization and Parallel Use of Multiple Proteases Facilitates Identification of Protein C-Termini by C-Terminomics

The identification of protein C-termini in complex proteomes is challenging due to the poor ionization efficiency of the carboxyl group. Amidating the negatively charged C-termini with ethanolamine (EA) has been suggested to improve the detection of C-terminal peptides and allows for a directed depletion of internal peptides after proteolysis using carboxyl reactive polymers. In the present study, the derivatization with N,N-dimethylethylenediamine (DMEDA) and (4-aminobutyl)guanidine (AG) leading to a positively charged C-terminus was investigated. C-terminal charge-reversed peptides showed improved coverage of b- and y-ion series in the MS/MS spectra compared to their noncharged counterparts. DMEDA-derivatized peptides resulted in many peptides with charge states of 3+, which benefited from ETD fragmentation. This makes the charge-reversal strategy particularly useful for the analysis of protein C-termini, which may also be post-translationally modified. The labeling strategy and the indirect enrichment of C-termini worked with similar efficiency for both DMEDA and EA, and their applicability was demonstrated on an E. coli proteome. Utilizing two proteases and different MS/MS activation mechanisms allowed for the identification of >400 C-termini, encompassing both canonical and truncated C-termini.