Selective Enrichment and Identification of Azide-tagged Cross-Linked Peptides Using Chemical Ligation and Mass Spectrometry

Protein-protein interaction is one of the key regulatory mechanisms for controlling protein function in various cellular processes. Chemical cross-linking coupled with mass spectrometry has proven to be a powerful method not only for mapping protein-protein interactions of all natures, including weak and transient ones, but also for determining their interaction interfaces. One critical challenge remaining in this approach is how to effectively isolate and identify cross-linked products from a complex peptide mixture. In this work, we have developed a novel strategy using conjugation chemistry for selective enrichment of cross-linked products. An azide-tagged cross-linker along with two biotinylated conjugation reagents were designed and synthesized. Cross-linking of model peptides and cytochrome c as well as enrichment of the resulting cross-linked peptides has been assessed. Selective conjugation of azide-tagged cross-linked peptides has been demonstrated using two strategies: copper catalyzed cycloaddition and Staudinger ligation. While both methods are effective, Staudinger ligation is better suited for enriching the cross-linked peptides since there are fewer issues with sample handling. LC MSn analysis coupled with database searching using the Protein Prospector software package allowed identification of 58 cytochrome c cross-linked peptides after enrichment and affinity purification. The new enrichment strategy developed in this work provides useful tools for facilitating identification of cross-linked peptides in a peptide mixture by MS, thus presenting a step forward in future studies of protein-protein interactions of protein complexes by cross-linking and mass spectrometry

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates

Hybrid Gene Origination Creates Human-Virus Chimeric Proteins during Infection

RNA viruses are a major human health threat. The life cycles of many highly pathogenic RNA viruses like influ-enza A virus (IAV) and Lassa virus depends on host mRNA, because viral polymerases cleave 50-m7G-cappedhost transcripts to prime viral mRNA synthesis (‘‘cap-snatching’’). We hypothesized that start codons withincap-snatched host transcripts could generate chimeric human-viral mRNAs with coding potential. We reportthe existence of this mechanism of gene origination, which we named ‘‘start-snatching.’’ Depending on thereading frame, start-snatching allows the translation of host and viral ‘‘untranslated regions’’ (UTRs) to createN-terminally extended viral proteins or entirely novel polypeptides by genetic overprinting. We show thatboth types of chimeric proteins are made in IAV-infected cells, generate T cell responses, and contributeto virulence. Our results indicate that during infection with IAV, and likely a multitude of other human, animaland plant viruses, a host-dependent mechanism allows the genesis of hybrid genes

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19

Profiling of Protein Interaction Networks of Protein Complexes Using Affinity Purification and Quantitative Mass Spectrometry*

Protein-protein interactions are important for nearly all biological processes, and it is known that aberrant protein-protein interactions can lead to human disease and cancer. Recent evidence has suggested that protein interaction interfaces describe a new class of attractive targets for drug development. Full characterization of protein interaction networks of protein complexes and their dynamics in response to various cellular cues will provide essential information for us to understand how protein complexes work together in cells to maintain cell viability and normal homeostasis. Affinity purification coupled with quantitative mass spectrometry has become the primary method for studying in vivo protein interactions of protein complexes and whole organism proteomes. Recent developments in sample preparation and affinity purification strategies allow the capture, identification, and quantification of protein interactions of protein complexes that are stable, dynamic, transient, and/or weak. Current efforts have mainly focused on generating reliable, reproducible, and high confidence protein interaction data sets for functional characterization. The availability of increasing amounts of information on protein interactions in eukaryotic systems and new bioinformatics tools allow functional analysis of quantitative protein interaction data to unravel the biological significance of the identified protein interactions. Existing studies in this area have laid a solid foundation toward generating a complete map of in vivo protein interaction networks of protein complexes in cells or tissues

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology