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C-HPP PIC meeting at HUPO Connect
HUPO Connect 2020 will be held between October 19 and 22 and C-HPP PIC meeting is planned on Monday, October 19, 17:15 EST time. The topics to be discussed will be
We ask all chromosome teams to update their results and potential team changes on C-HPP Wiki until HUPO Connect 2020.
Highlights from the C-HPP neXt-MP50 chromosome team reports:
Nominations for Co-Chair of the HPP
Please register and join us in HUPO Connect 2020 and donate to neXt-prot (https://www.hupo.org/Donate)
The C-HPP EC wish you and for all your family to stay safe and healthy and let’s go find proteomic evidence and clues for new cures!
Maggie Lam, University of Colorado, USA
If you have not had the chance to read them, I would like to draw your attention to a number of excellent HUPOST articles contributed by members of our community:
We are actively looking for more articles about various developments and applications in proteomics in the coming months on the HUPOST column. We are especially interested in articles coauthored by early career investigators with their mentors in any proteomics or related fields. So please feel free to reach out to us if you would like to contribute a HUPOST article. We think this is a fantastic way to showcase your research, write about recent developments that excite you and issues you care about, and share it with the HUPO community.
Lastly, we are excited to be preparing a number of outreach activities for HUPO B/D-HPP in the coming months, including social media outreach via Twitter and webinars. Please contact me via firstname.lastname@example.org if you are interested in participating.
By Yuanwei Xu and Hui Zhang, Center for Biomarker Discovery & Translation, Johns Hopkins University
Glycosylation is one of the most important protein modifications, playing an essential role in almost every aspect of biological processes. Despite being an important subdiscipline of proteomics, the investigations on glycoproteomics lagged behind not due to lack of interest, but a dearth of suitable methods for characterizing the tremendously complex glycoproteome. Luckily, we are able to characterize glycoproteome in an unprecedented depth with the help of advanced technologies. Glycoproteomics has come to the spotlight of completing the picture of human proteome.
The Human Genome Project transforms biology and medicine through its integrated big science approach to decipher the roles of the human genome. The genome is almost identical across different human cells and throughout the life 1. However, the coded proteins from human genome in cells are much more dynamic and highly diversified to facilitate different biological functions2 3. In this context, the human proteome holds significantly more functional proteins than the coding capacity of 20,000 to 25,000 genes 1, which could be two to three orders of magnitude more complex (>1,000,000 protein species) 4 (Figure 1). The major mechanism responsible for the expansion of proteome is that proteins are subject to elaborative modifications 1 4.
Identifying proteins that are modified by specific chemical groups and determining their modification sites are the key focuses in characterization of human protein modifications. Ever since the 1980s 5, phosphorylation has been the most characterized protein modifications (based on the number of publications on the topic of different modifications in human from 1970 to 2020 at PubMed). Up to ~50,000 phosphorylation sites could be identified in each sample in a single phosphoproteomic experiment 6 7 8 9 10 11. Glycosylation, along with other modifications such as acetylation, ubiquitination and SUMOylation are more pervasively investigated because of technological advancements. Approximately, glycoproteins take up ~50% of the proteome 12, unmatched by any other protein modifications, since glycosylation is highly diversified to facilitate an assortment of functions 13. Despite the significance of protein glycosylation, the investigation of glycoproteome remains challenging due to the diversity of glycoprotein isoforms (glycoforms) when compared to other modifications. A rather comprehensive characterization of protein glycosylation site and the fine details of these site-specific glycans (including composition, sequence, branching, linkage, and anomericity) 14 would require for glycoprotein characterization.
Eukaryotic protein glycosylation is usually via two major types of linkages to proteins: N- and O-linked. N-linked glycoproteins are mainly attachment to asparagine residues by the covalent N-glycosidic bond. The general consensus peptide sequence for N-glycan is Asn-X-Ser/Thr (where X is any amino acid except proline) 15 16, while unusual glycosites with atypical motifis such as Asn-X-Val and Asn-X-Cys were found with low occupancy 17. Moreover, N-glycans in eukaryotic cells share a common core sequence, Manα1-3(Manα1-6)Manβ1-4GlcNAcβ1–4GlcNAcβ1–Asn 16. In contrast, O-glycosylation is linked to the hydroxyl groups of serine or threonine residues without an obvious motif preference 16. The initiating monosaccharides for O-linked glycosylation include galactosamine (GalNAc), mannose, galactose, fucose, glucose, and glucosamine (GlcNAc) 16, linear or branched oligosaccharide chains of various lengths could be further extended from the initiating monosaccharides. Both N- and O-linked glycosylation could be capped or modified with certain monosaccharides and chemical groups or substitutions 14. All of these aspects of glycosylation compounded protein glycosylation with a multitude of complexities. Other glycan-protein complexes form structures such as GPI-anchored glycoproteins and proteoglycans are also presented in eukaryotic systems.
Glycoproteomics focuses on the large-scale characterization of glycoproteins. Microarray-based approaches and mass spectrometry-based approaches have been used in glycoproteomics 14. Glycoprotein coding genes 18, purified glycoproteins 19, glycans 20 21 22 23, lectins 24 25 , or glycan-specific antibodies 26 have been used in microarray-based approach. Due to the plasticity of glycosylation, mass spectrometry (MS)-based glycoproteomics characterizes glycoproteins at different levels, including glycosylation sites (glycosites), glycans, and glycosite-specific glycans 27 28. Several enrichment methods have been published for these purposes, including hydrazide chemical tagging29 30, metabolic labeling 31 32, chemoenzymatic labeling 33, lectin chromatography 34 35 36, HILIC 37 38, ERLIC 39, “SimpleCell” technology with homogenized O-glycans 40 41 and EXoO42. The enriched glycosites, glycans, glycopeptides or glycoproteins would then be analyzed using different MS approaches, including CID-MS (often fragmenting glycans), ECD/ETD-MS (often cleaving peptide backbones), MALDI-MS (often for detailed glycan analysis using MSn), and HCD-MS (often generating both peptide backbone and glycan fragment ions). The MS results would then be searched against known databases to identify glycosylation sites, glycans, glycans at each glycosite, and the abundance of certain glycoforms at each glycosite. Up to June 2020, 14,644 unique N-glycosylation sites, 30,872 unique N-linked glycosite-containing peptides and 7,204 unique N-linked glycoproteins were identified in human (based on outputs at N-GlycositeAtlas 43: http://glycositeatlas.biomarkercenter.org/#). As for O-linked glycosylation, 4,672 unique O-glycosylation sites were identified across the human brain, kidney, T cells, and serum using EXoO 44. In total, 3,369 glycan structures (based on outputs at GlyCosmos Portal: https://glycosmos.org/glytoucans/list) are identified in human. Glycoproteomic databases are emerging, yet we are only beginning to see the tip of the iceberg.
Apart from developing a suitable MS-based analytical approach, advanced computing power is indispensable for the characterization of glycoproteins. Sophisticated algorithms have been developed into software to assist in the interpretation of mass spectra. SEQUEST 45 and the recently developed pFind 46 are dedicated for the high-throughput peptide and protein identification via tandem mass spectrometry. GlycoPep ID 47, GlycoPep DB 48, and GlycoMod 49 are some of the freely accessible web-based programs for glycopeptide analysis. Skyline 50 and MaxQuant 51 are frequently adopted for large-scale quantitative proteomic studies. GlycoWorkBench 52, SimGlycan 53, Cartoonist 54, and MultiGlycan 55 can be used for the interpretation of glycan spectra, UnicarbDB 56 57 holds one of the largest experimental MS/MS databases on released glycans, while Byonic 58, GPQuest 59, and pGlyco 60 61 are developed to analyze intact glycopeptide spectra.
The recent technology advancement has brought numerous innovative approaches in various aspects of analytical glycoproteomics, including sample preparation, enrichment, mass spectrometric analyses, data analysis tools, and databases. As a result, the complexities of glycosylation characterization are reduced to a large extend. Along with the growing attention placed upon the alterations of glycosylation in every biological perturbation, especially in pathological states, the glycosylation “enigma” has been unraveling at a faster pace. Being the center of glycomics, glycoproteomics finally comes to the spotlight of human proteome characterization.
Sri H. Ramarathinam and Anthony W. Purcell, Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton 3800, Victoria, Australia
Our immune system sources actionable intelligence in the fight against pathogens in many forms including peptides, lipids and other small molecules associated with infection and cancer. The Human Leukocyte Antigen (HLA) proteins, expressed on cell surface, play an important role in conveying the status of cellular health to the immune system by presenting short peptides to T-cells. These short peptides could be from a variety of cellular and extraneous sources forming a snapshot of proteins - synthesized or degraded within the cell. Two major pathways enable antigen presentation: the HLA class I, expressed on all nuclear cells, present endogenous antigen to CD8+ T cells and the HLA class II, found only on professional antigen-presenting cells (such as dendritic cells and macrophages) present antigen from endogenous and exogenous sources to CD4+ T cells (Figure 1).
Specific receptors on T-cells (TCRs) are used to survey the landscape of HLA-peptide ligands on cell surface to find their cognate peptide-HLA complex, much like going through social media feeds to find a specific post of interest. Each TCR can generally recognise a single HLA-peptide complex, due to the remarkable sequence diversity engendered in the TCR through recombination of different genetic elements during T-cell development. T-cells also undergo selection in the thymus such that they are poised to recognise foreign peptides that may arise from viral and bacterial proteins or from inappropriately expressed or somatic mutation-bearing peptides in cancer. Presentation of such foreign peptides in complex with HLA molecules on the surface of infected or malignant cells attracts scrutiny of T-cells bearing the TCR that can recognise this HLA-peptide complex resulting in activation of the immune response and eradication of the cell. The ‘status updates’ in form of immune-related peptides constitutes the ‘immunopeptidome’ of the cells and has been characterised in multiple host species including human, mouse, bat , bovine , swine  and chicken .
The term immunopeptidomics describes the systematic, high-throughput analysis of HLA-bound peptides using mass spectrometry [5-7]. Understanding and deciphering the cellular communication updates (peptide sequences) by the immune system is crucial in the development of new vaccines against viruses as well as immunotherapies against cancer and auto-immune diseases [8-10].
Identifying HLA-peptides involves immunoprecipitation of HLA molecules from cells or tissues followed by separation of peptides from heavy chains, fractionation and subsequent analysis by mass spectrometers . In contrast to global proteomic analysis, the HLA peptides pose unique challenges requiring exacting sample preparation and analysis strategies. There is a need to have dedicated and specialised labs and informatics pipelines to overcome some common challenges. The yield depends on expression of HLA molecules, choice of appropriate methodologies to isolate the peptides, fine tuning of parameters for acquisition of high-quality mass spectrometry data and ultimately appropriate software to interpret data and identify peptide sequences.
One of the biggest hurdles is the amount of material required to do an in-depth immunopeptidomics analysis. To overcome the sample limitation, several algorithms have been developed to predict peptides that bind to specific HLA [12, 13]. While the prediction tools are invaluable, they do not yet consider post-translationally modified (PTM) peptides. Additionally, there is a disparity between peptides identified by mass spectrometry and the top results from prediction algorithms with the majority only explaining at most 10% of peptides as strong and or weak binders. Developments in sample processing and sensitive instrumentation are reducing the need to have large sample sizes and several studies already analysing patient material either individually or in small pools. The HLA-peptides bearing diverse C-termini, for example, may require analysis of singly-charged ions which are traditionally ignored in proteomics workflows .
The software to search the MS data is another area that has contributed significantly to improve the number of peptides identified. There is scope for improvement, especially development of appropriate decoy databases for HLA peptides that tend to have a variety of N- and C-termini and in developing peptide-centric algorithms without any influence of protein grouping. Endogenous processing in cells and HLA type result in varied peptide, requiring significant computing resources during database search.
A community standard of cell lines that can be used to benchmark the complete process (cell line to data) will also be an invaluable tool to improve upon and push the limits of current techniques. Additionally, there is a need for robust well-defined, widely-available synthetic HLA-peptide standards (>1000-5000 peptides) to benchmark various peptide identification and informatics pipelines.
Formation of HUPO-Human Immunopeptidome Project (HUPO-HIPP) in 2015, brought the leaders in the field together to advance research, support collaborative efforts including development of standards for publication [15, 16]. HUPO-HIPP organised two successful events so far, including a summer school and a precision oncology meeting that introduced the techniques and highlighted some key challenges in the path forward. New members are welcome to join us at HUPO-HIPP for latest updates.
In recent times, there is a growing appreciation for presence of PTM peptides  and peptides that are non-genomically templated in addition to the linear peptide sequences. While they challenge known dogmas, peptides from Defective Ribosomal Products (DRIPs) , post-translationally spliced peptides [19, 20] and peptides from UTRs and non-coding regions are worthy of consideration to explore their potential role in health and disease. As a field, tremendous achievements have led to a deeper understanding of the antigen presentation and processing machinery, yet we continue to be surprised by the intricate network of cells and proteins that keep us safe
Figure 1: A) HLA-class I and II molecules play a crucial role in key immunological pathways. Understanding the peptide repertoire offers insight into immunosurveillance machinery and its modulation. B) HLA class I and II pathways present antigen to CD8+ and CD4+ T-cells respectively.
1. Wynne, J.W., et al., Characterization of the Antigen Processing Machinery and Endogenous Peptide Presentation of a Bat MHC Class I Molecule. J Immunol, 2016. 196(11): p. 4468-76.
2. Nielsen, M., T. Connelley, and N. Ternette, Improved Prediction of Bovine Leucocyte Antigens (BoLA) Presented Ligands by Use of Mass-Spectrometry-Determined Ligand and in Vitro Binding Data. Journal of Proteome Research, 2018. 17(1): p. 559-567.
3. Pedersen, L.E., et al., Porcine major histocompatibility complex (MHC) class I molecules and analysis of their peptide-binding specificities. Immunogenetics, 2011. 63(12): p. 821-834.
4. Cumberbatch, J.A., et al., Chicken major histocompatibility complex class II molecules of the B19 haplotype present self and foreign peptides. Animal Genetics, 2006. 37(4): p. 393-396.
5. Caron, E., et al., The structure and location of SIMP/STT3B account for its prominent imprint on the MHC I immunopeptidome. Int Immunol, 2005. 17(12): p. 1583-96.
6. Hunt, D.F., et al., Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry. Science, 1992. 255(5049): p. 1261.
7. Falk, K., et al., Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature, 1991. 351(6324): p. 290-296.
8. Engelhard, V.H., et al., MHC-restricted phosphopeptide antigens: preclinical validation and first-in-humans clinical trial in participants with high-risk melanoma. J Immunother Cancer, 2020. 8(1).
9. He, Q., et al., Targeting cancers through TCR-peptide/MHC interactions. Journal of Hematology & Oncology, 2019. 12(1): p. 139.
10. Serra, P. and P. Santamaria, Antigen-specific therapeutic approaches for autoimmunity. Nature Biotechnology, 2019. 37(3): p. 238-251.
11. Purcell, A.W., S.H. Ramarathinam, and N. Ternette, Mass spectrometry-based identification of MHC-bound peptides for immunopeptidomics. Nat Protoc, 2019. 14(6): p. 1687-1707.
12. Jurtz, V., et al., NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. J Immunol, 2017. 199(9): p. 3360-3368.
13. Peters, B., M. Nielsen, and A. Sette, T Cell Epitope Predictions. Annual Review of Immunology, 2020. 38(1): p. 123-145.
14. Pandey, K., et al., In-depth mining of the immunopeptidome of an acute myeloid leukemia cell line using complementary ligand enrichment and data acquisition strategies. Mol Immunol, 2020. 123: p. 7-17.
15. Lill, J.R., et al., Minimal Information About an Immuno-Peptidomics Experiment (MIAIPE). Proteomics, 2018. 18(12): p. e1800110.
16. Admon, A. and M. Bassani-Sternberg, The Human Immunopeptidome Project, a suggestion for yet another postgenome next big thing. Mol Cell Proteomics, 2011. 10(10): p. O111.011833.
17. Mei, S., et al., Immunopeptidomic analysis reveals that deamidated HLA-bound peptides arise predominantly from deglycosylated precursors. Mol Cell Proteomics, 2020.
18. Wei, J. and J.W. Yewdell, Flu DRiPs in MHC Class I Immunosurveillance. Virol Sin, 2019. 34(2): p. 162-167.
19. Faridi, P., et al., A subset of HLA-I peptides are not genomically templated: Evidence for cis- and trans-spliced peptide ligands. Sci Immunol, 2018. 3(28).
20. Liepe, J., et al., A large fraction of HLA class I ligands are proteasome-generated spliced peptides. Science, 2016. 354(6310): p. 354-358.
Ed Nice and Stephen Pennington, co-Chairs, HPP Pathology Resource Pillar
Some of you may have heard already that, due to increased pressures of work due to the COVID-19 pandemic, Prof Dan Chan will stand down as the inaugural Chair of the HPP Pathology Resource Pillar. Dan has been outstanding in the drive and passion he has brought to this role and to getting the Pathology Pillar operational. I am sure you would like to join us in thanking Dan.
We now, of course, need to find a suitable replacement – a new Chair of the HPP Pathology Resource Pillar. The Chair is responsible for developing pillar strategic plans and projects, expanding membership of Pillar and reporting to HPP EC.
Dan has kindly offered to ‘guide’ the incoming Chair, and of course, receive active support from the co-Chairs. If you think you have the necessary drive and enthusiasm for this important HUPO role, please send the following information to HUPO office (office@HUPO.org) by Friday 31st July. This will be a 2 year appointment in the first instance.
i) Proteomics track record
ii) HUPO/HPP track record
iii) Evidence of national/international visibility
iv) Your vision for future development of the HPP Pathology Resource Pillar
v) A one-page CV/bio
vi) Names and contact details of 2 scientific/clinical referees
Thank you for your consideration.
Cora N. Betsinger and Ileana M. Cristea, Princeton University, Department of Molecular Biology, Princeton, New Jersey, USA
A mission of the HUPO Biology/Disease-driven Human Proteome Project (B/D-HPP) is to explore how the human proteome can provide a lens for understanding human disease. The Human Infectious Diseases team (HID-HPP) of the B/D-HPP, is specifically devoted to the study of human diseases caused by infectious pathogens (https://www.hupo.org/Infectious-Disease-Initiative). One objective of HID-HPP is to develop, make broadly available, and apply proteomic methods to understand the biology and pathogenicity of viruses. For example, members of the HID-HPP have applied a range of proteomic methods to define alterations in the cellular proteome, protein interactome, and protein posttranslational modifications during infection with diverse viral pathogens1, such as herpesviruses and influenza A2–6. Given the ongoing global pandemic derived from infection with the novel SARS-CoV-2 virus7, here we highlight the demonstrated and promised power of proteomics to provide urgently needed insight into the biology and pathogenicity of this coronavirus and to uncover therapeutic targets.
Upon the emergence of a new viral pathogen in the human population, some of the first steps undertaken are to isolate the virus from patient samples and sequence the viral genome. This is critical for the taxonomic classification of the virus, determination of its phylogenetic relationship to other viruses, and identification of zoonotic host species. However, genetic analysis cannot fully address many aspects of virus biology, including the identity and function of virus proteins, how the virus interacts with host cells during its entry and replication, and what changes infection elicits at the cell and system level. Over the past twenty years, three of the emergent viruses that have resulted in widespread human disease and fatality have been members of the Coronaviridae family. SARS-CoV was identified as the causative agent of the 2003 severe acute respiratory syndrome (SARS) outbreak, which had a fatality rate of 10%8. MERS-CoV emerged ten years later, in 2013, and had a case fatality rate of more than 30%8. The most recent emergent coronavirus is SARS-CoV-2, the agent responsible for the current global COVID-19 disease pandemic that has resulted in over 2.8 million infections and 193,710 deaths to date7.
The application of proteomic techniques to the study of these different types of coronaviruses has allowed for a more complete characterization of each virus and its pathogenesis. Proteomic methods were successfully applied to the study of SARS-CoV immediately following the 2003 SARS outbreak and contributed significantly to our understanding of SARS-CoV structure, replication, and pathology, as well as identified potential therapeutic targets. Mass spectrometry-based methods were initially used to characterize the structure and components of SARS infectious virus particles9–11. These studies confirmed virus protein sequences predicted by nucleotide sequencing, identified antigenic virus proteins, located glycosylation sites decorating the virus spike protein necessary for entry into host cells, and revealed host proteins which were incorporated into the virus particles during assembly. An affinity purification mass spectrometry analysis of the coronavirus spike protein led to the identification of angiotensin-converting enzyme 2 (ACE2) as the cell surface receptor for SARS-CoV12. As the same host receptor is also targeted by the novel SARS-CoV-2, these findings led to the recent testing of the clinically approved compound, camostat mesylate, as a mean to block CoV-2 infection13.
Other research teams applied proteomic methods to investigate changes in the cellular proteome during SARS-CoV infection14–16. These studies revealed host processes that are dysregulated during infection for the benefit of virus replication. For instance, the host protein BCL2-associated athanogene 3 (BAG3) was identified as upregulated during SARS-CoV replication16. Knockdown of BAG3 suppressed SARS-CoV replication and protein synthesis, demonstrating its pro-viral function during infection and identifying it as a potential therapeutic target. Another group used mass spectrometry to identify two phosphorylation sites on the virus nucleocapsid (N) protein, which regulates viral RNA transcription and replication17. As phosphorylation impacts the ability of N to bind RNA, this finding could aid in the development of antivirals regulating the phosphorylation status of N. Mass spectrometry was also used in the search for biomarkers of SARS-CoV infection in human plasma samples18–21. These studies provided insight into the pathogenesis of SARS and revealed diagnostic markers, as well as markers correlated with disease progression, prognosis, and viral load. The aim of these studies was to develop a SARS-specific fingerprint that could differentiate SARS patients from non-SARS patients early during infection and predict the expected progression and severity of disease for each individual, allowing for personalized treatment and appropriate resource allocation.
Considering the current SARS-CoV-2 pandemic, proteomic techniques will be highly beneficial for investigating the efficacy of antiviral therapies, identifying new therapeutic targets, and developing fast and effective early diagnostic tests for coronavirus infection. For instance, monitoring virus and host protein levels following treatment with trial antivirals would demonstrate drug efficacy and reveal off-target effects. Proteomics could also be used to identify candidates for the rational design of antivirals targeting pro-viral host processes, which are often more effective long-term treatment options due to the propensity of RNA viruses to mutate. Quantification of temporal changes in host protein levels throughout the time-course of coronavirus infection would illuminate proteins and cellular processes that are dysregulated by coronavirus as potential therapeutic targets. Furthermore, a range of proteomic methods are available for studying host-viral protein-protein and protein-nucleic acid interactions, promising to provide insight into interactions that could be disrupted to restore host defense and inhibit virus replication. Such methods include affinity purification, crosslinking, proximity labeling, and thermal proximity coaggregation. Proteomic techniques could also be used to overcome what has been a major challenge during the current pandemic, i.e., the development of a fast, effective, and reliable diagnostic test for early detection of coronavirus infection. Targeted mass spectrometry could be used to identify diagnostic and prognostic markers of SARS-CoV-2 infection in patient serum samples, similar to investigations done during the 2003 SARS-CoV outbreak18–21. This potential for the implementation of diverse proteomic methods for studying SARS-CoV-2 can already be seen in the impressive number of recent manuscripts either published or in prepublication format on bioRxiv.
The desire of the international scientific community to rapidly respond to the new SARS-CoV-2 pandemic has been evident on all fronts of science, including within the proteomics field. This is exemplified by efforts from the Human Infectious Diseases team (HID-HPP) of the B/D-HPP, as well as the timely organization of the COVID-19 Mass Spectrometry Coalition (covid19-msc.org), spearheaded by Dr. Perdita Barran (University of Manchester). This coalition now involves a continuously growing number of HUPO and HPP scientists, including Drs. Fernando Corrales, Edward Emmott, Andrea Sinz, Catherine Costello, Gilberto B Domont, Stephen Pennington, Yu-Ju Chen, John Yates, and our group to name just a few. Through the combined experience and expertise of scientists globally, we will continue to illuminate the underlying biology and pathogenicity of SARS-CoV-2 and contribute this knowledge toward the development of antiviral treatment options.
1. Greco, T. M., Diner, B. A. & Cristea, I. M. The Impact of Mass Spectrometry–Based Proteomics on Fundamental Discoveries in Virology. Annu. Rev. Virol. (2014) doi:10.1146/annurev-virology-031413-085527.
2. Emmott, E. et al. Quantitative proteomics using SILAC coupled to LC-MS/MS reveals changes in the nucleolar proteome in influenza A virus-infected cells. J. Proteome Res. 9, 5335–5345 (2010).
3. Dove, B. K. et al. A quantitative proteomic analysis of lung epithelial (A549) cells infected with 2009 pandemic influenza A virus using stable isotope labelling with amino acids in cell culture. Proteomics (2012) doi:10.1002/pmic.201100470.
4. Murray, L. A., Sheng, X. & Cristea, I. M. Orchestration of protein acetylation as a toggle for cellular defense and virus replication. Nat. Commun. (2018) doi:10.1038/s41467-018-07179-w.
5. Lum, K. K. et al. Interactome and Proteome Dynamics Uncover Immune Modulatory Associations of the Pathogen Sensing Factor cGAS. Cell Syst. (2018) doi:10.1016/j.cels.2018.10.010.
6. Hashimoto, Y., Sheng, X., Murray-Nerger, L. A. & Cristea, I. M. Temporal dynamics of protein complex formation and dissociation during human cytomegalovirus infection. Nat. Commun. (2020) doi:10.1038/s41467-020-14586-5.
7. Practice, B. B. Coronavirus disease 2019. World Heal. Organ. 2019, 2633 (2020).
8. Ng, L. F. P. & Hiscox, J. A. Coronaviruses in animals and humans. The BMJ (2020) doi:10.1136/bmj.m634.
9. Krokhin, O. et al. Mass spectrometric characterization of proteins from the SARS virus: a preliminary report. Mol. Cell. Proteomics (2003) doi:10.1074/mcp.M300048-MCP200.
10. Ying, W. et al. Proteomic analysis on structural proteins of Severe Acute Respiratory Syndrome coronavirus. in Proteomics (2004). doi:10.1002/pmic.200300676.
11. Neuman, B. W. et al. Proteomics Analysis Unravels the Functional Repertoire of Coronavirus Nonstructural Protein 3. J. Virol. (2008) doi:10.1128/jvi.02631-07.
12. Li, W. et al. Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature (2003) doi:10.1038/nature02145.
13. Hoffmann, M. et al. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell (2020) doi:10.1016/j.cell.2020.02.052.
14. Zeng, R. et al. Proteomic analysis of SARS associated coronavirus using two-dimensional liquid chromatography mass spectrometry and one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis followed by mass spectroemtric analysis. J. Proteome Res. (2004) doi:10.1021/pr034111j.
15. Jiang, X. S. et al. Quantitative analysis of Severe Acute Respiratory Syndrome (SARS)-associated coronavirus-infected cells using proteomic approaches: Implications for cellular responses to virus infection. Mol. Cell. Proteomics 4, 902–913 (2005) doi: 10.1074/mcp.M400112-MCP200
16. Zhang, L., Zhang, Z. P., Zhang, X. E., Lin, F. S. & Ge, F. Quantitative Proteomics Analysis Reveals BAG3 as a Potential Target To Suppress Severe Acute Respiratory Syndrome Coronavirus Replication. J. Virol. (2010) doi:10.1128/jvi.00213-10.
17. Lin, L. et al. Identification of phosphorylation sites in the nucleocapsid protein (N protein) of SARS-coronavirus. Int. J. Mass Spectrom. (2007) doi:10.1016/j.ijms.2007.05.009.
18. Chen, J. H. et al. Plasma proteome of severe acute respiratory syndrome analyzed by two-dimensional gel electrophoresis and mass spectrometry. Proc. Natl. Acad. Sci. U. S. A. (2004) doi:10.1073/pnas.0407992101.
19. Poon, T. C. W. et al. Serial analysis of plasma proteomic signatures in pediatric patients with severe acute respiratory syndrome and correlation with viral load. Clin. Chem. (2004) doi:10.1373/clinchem.2004.035352.
20. Kang, X. et al. Proteomic fingerprints for potential application to early diagnosis of severe acute respiratory syndrome. Clin. Chem. (2005) doi:10.1373/clinchem.2004.032458.
21. Pang, R. T. K. et al. Serum proteomic fingerprints of adult patients with severe acute respiratory syndrome. Clin. Chem. (2006) doi:10.1373/clinchem.2005.061689.
The Journal of Proteome Research will publish its eighth annual Special Issue dedicated to highlight the progress made on the HUPO Human Proteome Project (HPP). The Special Issue considers research papers encompassing both the Chromosome-Centric Human Proteome Project (C-HPP) and the Biology and Disease Human Proteome Project (B/D-HPP), as well from the Resource Pillars (Antibody, MS, Pathology, and Knowledgebase), and short definitive reports, submitted in the Letters format, on the discovery of a Missing Protein(s). To be considered, the missing protein(s) must meet the Guidelines v 3.0 and be cast in the context of the HPP and biological setting in which they were discovered.
Manuscripts must be submitted by 31st May, 2020 to be considered for this Special Issue. Manuscripts must be submitted electronically through the ACS Paragon Plus Environment online submission system. Specify in the authors’ cover letter that the manuscript is intended for the HPP Special Issue. Editorial triage will determine whether manuscripts are appropriate for the HPP Special Issue, fulfil the HPP Guidelines 3.0 (2019-10-15) checklist and protein evidence based on the 2020-01-17 neXtprot release to be considered for publication. The completed checklist must be included with the cover letter. The full MS data submission to ProteomeXchange must also be completed prior to initial submission, and the PXD number provided in the abstract. As papers are accepted they will go online and be available in time for HUPO-2020. Due to the publication schedule, only papers that are accepted by September 31, 2020 will be published in the December 2020 HPP Special Issue.
Submit your manuscript to Journal of Proteome Research for the 2020 HUPO Human Proteome Project Special Issue. Submission deadline is June 30th, 2020. The Special Issue considers papers encompassing both the Chromosome-Centric Human Proteome Project (C-HPP) and the Biology and Disease Human Proteome Project (B/D-HPP). In addition, we will now consider short definitive reports, submitted in the Letters format, on the discovery of a Missing Protein(s). Click here for more information.
The Annual HUPO Congress in 2019 in Adelaide, Australia is approaching and will again host a rich C-HPP and HPP program and activities to share progress and results of the international chromosome teams and the whole C-HPP. Status reports will be presented on the status of missing protein identification (neXt-MP50) and the identification of functions of uPE1 proteins in the neXt-CP50 projects, to seek new joint projects with B/D-HPP teams, and to discuss the future directions of C-HPP.
HPP Workshop Days
The various activities of the C-HPP are listed and continuously updated on the C-HPP Wiki. Especially relevant are the pre- and post-congress HPP Workshops. On Sunday September 15th is the HPP Investigators Program, Hall A, Adelaide Convention Centre jointly coordinated by Chris Overall and Fernando Corrales. The Post-Congress HPP workshop, organized by Mark Baker, is being held 9 – 5pm, Thursday Sept 19th, Bradley Forum, Level 5 Hawke Building, City West Campus, UniSA, 50 – 55 Nth Terrace, Adelaide, about 500 m west on North Terrace towards the new Hospital. Again, the program is posted on the C-HPP Wiki and the C-HPP Portal.
C-HPP Poster Session
Outside the submitted abstracts stream for HUPO, again we will have a separate C-HPP poster session running the entire meeting. Please bring extra posters relevant to the C-HPP that you wish to present, especially unpublished recent data. Note, abstracts do not have to be uploaded to the HUPO-Adelaide web site, just bring your research along to present. We encourage you to bring additional extra posters for this section to translate your research, highlight your trainees, and accelerate C-HPP discussions. The C-HPP Poster Discussion, led by Gil Omenn will be at morning coffee/tea Tuesday 10:00-10:40 and possibly in the afternoon tea break also. Lightning 2-minute talks at each poster will be followed by Q & A. This will be a key part in deciding Poster Awards!
Please put up the posters Sunday afternoon or Monday morning at the latest to ensure ample viewing and discussion time. We have a great location, posters numbers 1 – 20, just as you enter the main exhibit hall on the left and en route to the Bioinformatics Hub. These posters will be displayed for the entire length of the congress. Protifi (https://www.protifi.com/) is sponsoring 3 @ USD200 C-HPP Poster Awards, which along with Certificates, will be presented at the Awards Ceremony on Wednesday at the close of the congress.
Again, Eric Deutsch has mastered a wide ranging and practical program on bioinformatics challenges (click for the program) in MP hunting, data analysis and implementing the new Human Proteome Project Data Interpretation Guidelines (Version 3.0) in a friendly atmosphere that encourages Q & A and for attendees to come away truly knowing the answer to their questions. The Hub is perfectly located at the main entrance of the exhibit hall to the left, incidentally with the C-HPP posters on one of its outside walls.
The new HPP Data Guidelines v 3.0
A key take home message from the HPP workshop days in Adelaide and the bioinformatics hub will be presentation and discussion on implementation of the new guidelines for MP discovery and promotion to PE1. Please read the preprint here Human Proteome Project Data Interpretation Guidelines (Version 3.0).
C-HPP Annual Report
The C-HPP Annual report can be found here.
The C-HPP Wiki
The C-HPP wiki is updated, but we require your input for the individual chromosome teams. Please refer to Peter Horvatovich for log in info to post and edit entries. Peter will be presenting how to edit the wiki in the bioinformatics hub on Monday, September 16, 2019 at 10:30-11:00 and is available during the meeting to help members work with the wiki. Each chromosome group is also requested to send their respective neXt-MP50 and neXt-CP50 reports and update their chromosome C-HPP Wiki page.
We look forward to seeing you at (C)-HPP events of the HUPO 2019 Congress in Adelaide. Let’s go!
Chris Overall (chair), Young-Ki Paik (co-chair), Lydie Lane (co-chair), Gilberto B. Domont (MAL), Fernando Corrales (MAL), Pengyuan Yang (MAL) and Peter Horvatovich (secretary general).
Vera Ignjatovic,University of Melbourne, Australia
Q: Can you please tell us about when did you first become involved in HUPO activities?Ruedi Aebersold: I got involved with HUPO pretty early. One of the early activities was the formation of what is today the PSI working group. Around 2000 it was pretty clear to us that as proteomics researchers we would run into problems if the computational analysis of MS and MS/MS data could not become more transparent and better benchmarked. We developed in our group at ISB in Seattle some tools that we presented at HUPO meetings, I believe first in Montreal. These included a data representation scheme in xml format (mzXML) developed by Patrick Pedrioli and statistical models developed by Alexey Nesvizhskii and Andy Keller to assign probabilities to peptide identifications (PeptideProphet) and inferred protein identifications (ProteinProphet). Out of these developments and the perceived need to discuss and benchmark these and other tools came the PSI.With Albert Heck and Anne-Claude Gavin I was a co-organizer of the Amsterdam meeting and was subsequently heavily involved in the HPP, specifically the B/D part of the project.
Q: What major achievements over the past 10 years have contributed to the success of HUPO?Ruedi Aebersold: I think the major success of HUPO overall is that it provides a worldwide forum for proteomic scientists and a face of proteomics to the other fields of science. As specific achievements I would name the successful annual congresses, the initiatives which have had a large effect on how proteomic experiments are planned, carried out and reported and the support of young scientists. All these have contributed to increasing the visibility of proteomics.
Q: What made you interested in becoming the HPP-SAB Chair?Ruedi Aebersold:I was for a while chair of the B/D-HPP project before I had to step down due to obligations at my home institution. It is therefore very interesting for me to become involved in the project again in another role. I look forward to catching up on what has happened and to work with the SAB members and the project leaders to further develop the project.
Q: Where do you see the HPP heading both in the short and the long-term?Ruedi Aebersold: I think in the short term and long term the HPP should continue to help making proteomics a mainstream technology for the life sciences including clinical research. The HPP has already accomplished a lot in that direction with providing results, techniques, resources and knowledge towards the exploration of the (human) proteome. Importantly, this has been accomplished in the spirit of international cooperation. I would like to see a convergence of the two HPP directions towards that goal.
Q: What do you think that the SAB can/may deliver in the short and long term?Ruedi Aebersold: I hope that that the SAB can be an effective sounding board, provide feedback on the HPP plans and activities developed by the project leaders and provide suggestions as to how the project could develop. In my opinion, it is important that the roles of the project leadership and the SAB are clearly defined and separate. SAB’s in general should be advisory and not become operationally active or intrusive.
Q: Could you please list three practical steps that all proteomics researchers can take in improving the visibility of proteomics globally?Ruedi Aebersold: Unfortunately, in many circles proteomics still has the reputation of being complicated, slow, expensive and to only work in few places. This is distinctively not the case anymore (if it was ever the case). I think proteomics researchers could and should take steps to counter these wrong impressions. They could do this by: i) conveying the capabilities of the field and the excitement to colleagues in different fields, ii) by collaborating on interesting projects, iii) by focusing the conversations and communication on what is possible as opposed to what is not (yet) possible, i.e. focus communication on solutions and not problems.
Q: What are the major hurdles that proteomics faces on the way to it's integration into daily clinical practice?Ruedi Aebersold: There are of course technical hurdles that need to be overcome. However, I think the main hurdles that hamper integration of proteomics into daily clinical practice (and for that matter into basic life science as well) are access and perception (as explained above).
Q: Last but not least....What advice would you give to Early Career "proteomics practitioners" to best set up themselves for a long and prosperous career?Ruedi Aebersold: The amazing advances in instrumentation and techniques realized over the past few years make the measurement of proteomes routine compared to the situation some years ago and provide data of high quality. To best set themselves up for a successful career in proteomics I would recommend to young scientists to learn as much as possible about experimental design and computational analysis of large datasets, and to learn about the important biological and clinical questions where proteomics can make a unique contribution and then to go for it.
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