By Michelle Hill, QIMR Berghofer Medical Research Institute, Brisbane Australia

Swapping shovels and brushes for mass spectrometers and proteomics knowledge, Prof Paul Haynes and Dr Caroline Solazzo are using ancient proteomics to reveal new understanding of human cultural heritage.

With a background in chemistry and a research program on food and environmental proteomics, Prof Paul Haynes journeyed into ancient proteomics with his Macquarie University (Australia) colleague Egyptologist Dr Jana Jones as well as Dr Raffaella Bianucci (University of Turin, Italy).

Archaeological material is highly valuable, and Bianucci had the first challenge to obtain permission to use even a small sample from precious Egyptian mummies for proteomics analysis. Having obtained permission to collect loose skin samples from 4,200-year old mummies originating from ancient Middle Egypt, the researchers were blown away by the proteomics results. In addition to the expected collagen proteins, which are known in the field as “Survivor proteins”, proteomics provided rare molecular insight into the medical histories of two of the mummies – the proteins identified suggest the individuals might have died from cancer and lung infection, respectively. This study was published in Philosophical Transactions of the Royal Society A.

At the Smithsonian Museum Conservation Institute, Dr Caroline Solazzo has been using proteomics to identify animal tissues in historical and archaeological textiles, to better understand the techniques of production of these cultural heritage artefacts. 

Solazzo used proteomics to confirm the use of dog fiber in Coast Salish blankets. The Coast Salish peoples are indigenous to the Pacific Northwest coastal areas of northern Washington and southern British Columbia, notable for large, finely woven blankets. The rich Salish oral history alludes to the use of dog hair was used as a weaving fiber, but the importance of dog fiber was questioned. Solazzo used proteomics to identify dog fiber in 19 textile samples, thus proving the oral tradition. Further, based on her finding that dog fibers were always weaved with other fibers such as mountain goat hair, more detailed information can be provided in museums.

An even more challenging question was the differentiation of sheep and goat wool in textiles used to wrap burial objects, due to their similarity, and degradation state of the buried ancient samples. Solazzo used peptide mass fingerprinting to analyse the wool wrapping from a 10th century Viking-age grave in Britain, and from 2,000 year old Mongolian bronze burial objects.

“At the time the keratin sequences were not well known for these two species, and although the two species are very close, I was able to determine one key peptide to differentiate them. Some of these archaeological fibers were challenging because they had been mineralized so microscopy was inconclusive.” says Solazzo.

Both Solazzo and Haynes highlight non-invasive sampling of ancient, precious materials as a challenge. To this end, recent development of innovative sampling techniques, such as strip-taping, should greatly facilitate ancient proteomics. While sample degradation and modern contamination are additional technical considerations, Haynes is intrigued by recent work on the use of deamidation levels as a molecular clock to estimate the age of proteins. On this point, Solazzo observed lower deamination levels in better preserved textiles, and suggested in her Journal of Archeological Science article, that the corroding copper salts from the wrapped bronze objects acted as a biocide to help preserve the textiles.

Now hooked on mummies, Haynes and several PhD students are part of an interdisciplinary team on The Mummy Project at The University of Sydney’s Chau Chak Wing Museum. Meanwhile, Solazzo has been developing proteomics tools to identify baleen, tortoiseshell and horn, materials that are difficult to recognize and are poorly preserved in archaeological contexts, making them challenging for DNA sequencing technologies, but are of cultural significance, often being used in buttons, jewellery and furniture.

Michelle M. Hill, QIMR Berghofer Medical Research Institute, Brisbane, Australia and Ellen D. McPhail, Mayo Clinic, Rochester, MN, USA

Joe's Story

Following a 32-year career in plant pathology R&D for agricultural and biosecurity applications, Joe Kochman, PhD, is well-versed in DNA-based diagnostic technologies. But he never imagined that at 68-years of age, he would be the topic of a difficult diagnostic investigation which required innovations in proteomics diagnostics.

While undergoing prostate cancer treatment in 2015, amyloid deposits were detected in Joe’s prostate gland biopsy. The chance finding led to further investigation and a diagnosis of early systemic amyloidosis with heart involvement. Joe was very fortunate that he was referred to Dr Peter Mollee, a haematologist at the forefront of systemic amyloidosis diagnosis techniques in Australia.

“He was found to have a monoclonal lambda immunoglobulin free light chain in the blood which can be the causative protein underling AL amyloidosis.” Peter explains. “The alternative possibility was that the amyloid deposits were of transthyretin type (ATTR), and the circulating monoclonal immunoglobulin lambda free light chain was unrelated to the amyloidosis but due to condition called MGUS.”

Cardiac ATTR has a favourable survival rate compared to AL amyloidosis, with a median survival of 75 versus 11 months. As the treatments are completely different, it was important to determine the precise amyloid protein in the deposit.

The current standard diagnostic method of immunohistochemistry was conducted, but was inconclusive. Aware of this common problem and unmet diagnostic need, Peter had worked with my team to set up laser-capture microdissection-coupled tandem mass spectrometry for amyloidosis typing method at the Princess Alexandra Hospital (PAH) Amyloidosis Centre in Brisbane, Australia.

Using a section of Joe’s prostate biopsy tissue, the proteomics method identified immunoglobulin lambda light chain, as well as signature amyloid associated proteins (ApoE, SAP, ApoA4, vitronectin and clusterin). “Thus, a confident diagnosis of lambda light chain amyloidosis was made and appropriate treatment was able to be commenced.” says Peter.

Martin Middleditch, Lead Mass Spectrometry Technologist at the University of Auckland, New Zealand, is no stranger to the life-changing impact of proteomics, having typed ~140 systemic amyloidosis cases.

“We have seen many occasions where the current clinical assumption about the case based on other techniques has been overturned by our results, significantly changing the therapeutic direction.” says Martin.

Global collaboration to bring the benefits of proteomics diagnostics to all patients

Systemic amyloidosis is a rare disorder estimated to affect 5 to 13 people per million person-years. Due to the low prevalence, first-line clinicians frequently lack amyloidosis-specific experience, and getting the correct diagnosis is often a long process. However, it is crucial as an incorrect diagnosis can lead to potentially devastating outcomes.

There are 36 known types of amyloid, and establishing the correct amyloid type is critically important as prognosis and treatment vary widely depending on the amyloid type. As illustrated in Joe’s case, antibody-based methods can be inconclusive, that’s where proteomics has come to the rescue.

Since developing the laser-capture microdissection-coupled tandem mass spectrometry amyloidosis typing test for clinical use in 2008, the Mayo Clinic (Rochester, MN, USA) has typed over 20,000 amyloid specimens, and been prolific in reporting the applications and benefits of the proteomics test. As FFPE tissue blocks can be safely delivered by post, the Mayo Clinic offers proteomic service for domestic and international patients, when referred by clinicians.

Mass spectrometry-based amyloid typing is rapidly becoming the new gold standard in light of its outstanding sensitivity and specificity. Globally, the number of centres offering systemic amyloidosis typing by mass spectrometry is still limited, although interest in establishing testing centers is increasing. There are two entry barriers for new centers, namely, the cost of high-end instruments (laser capture microdissection, mass spectrometer) and the high level of laboratory and bioinformatics expertise.

So far, all of the established centres have had successful local clinician-proteomics scientist collaboration, and mostly established their protocols independently. A harmonized international effort in education, cross-training and standardization will further broaden the availability and use of this diagnostic test to benefit more patients.

For example, abdominal fat pad aspirate is another clinically useful sample type for amyloidosis diagnosis and typing, but can present different technical challenges compared to FFPE. Cross-training with centers with greater expertise for fat aspirates, such as the University Hospital San Matteo (Pavia, Italy) or the Mayo Clinic, would facilitate the adoption and availability of global centers offering proteomics typing for amyloidosis.

Other key areas that will benefit from international collaboration and standardization include data analysis, interpretation and reporting.

Joe Kochman was lucky to have the chance biopsy finding, and referral to the only amyloidosis clinic in Australia to perform the proteomics test. He describes the events as “life changing”, and has been a patient advocate of the PAH Amyloidosis Centre since 2019.

Now an international effort in dissemination, standardization and harmonization will allow more patients globally to benefit from precision proteomics diagnosis.

Michelle Hill, QIMR Berghofer Medical Research Institute, and The University of Queensland, Australia

Popularized by crime scene investigation dramas, forensic DNA technology is widely known to the public. The potential for using human DNA fingerprinting in forensic science was first reported by Professor Alec Jeffreys in 1985. By matching incriminating genetic material to DNA fingerprints from suspects (or a database), it’s possible to surmise “who” may or may not have been present at the crime scene. The same DNA fingerprinting technology has since been commercialised for ancestry tracing and parentage confirmation.

While DNA profiling has helped to solve the question of “who” in crime investigations, it has no or limited power to enlighten on the “what” or “how” of a crime. But never fear, the new super power protein profiling is here!!

The scientific term for protein profiling is “proteomics”, which is used to describe large scale analysis of known or unknown proteins. For unknown mixtures of proteins, such as that encountered in forensic investigations, the technique of mass spectrometry (shortened to MS) is used along with DNA sequence databases to compute the protein identities. The recent advances in MS and gene sequencing technologies have given birth to a new super power - forensic proteomics.

In Italy, the super power of forensic proteomics has been pioneered by Dr Gianluca Picariello (Institute Food Sciences at National Research Council of Italy) upon input of the forensic toxicologist Dr Maria Pieri (Legal Medicine Section of University of Naples). Normally, Gianluca’s research laboratory applies proteomics technique in the investigation of food composition and evolution, so he is used to analysing partly digested food of varying stage of decay. These skills became super powers to help Maria determine the truth of statements from persons of interest in 2 different criminal cases.

In the first case on the death of a mental health patient at a clinic, there was a discrepant account on whether the victim had eaten breakfast. The usual forensic methods of visual investigation of the gastric content at autopsy could not answer this question, even when examined under the microscope. Gianluca’s forensic proteomics super power provide unequivocal evidence that the victim had eaten recently milk and baked wheat food, consistently with a typical Italian breakfast. The inconsistency between evidence and declaration of the attending sanitary staff, prompted Legal Authority to undertake further investigations to ascertain facts and possible responsibilities.

Secondly, in rape case, the investigators had to determine whether traces of biological material was vomit. DNA profiling was not helpful because the dispute was whether the victim gave consent, or had vomited and fainted, and therefore could not have consented. The problem is, the car had been washed since the incident, leaving scant traces of biological material which could not be analysed by standard forensic methods. Once again, Gianluca’s super power easily provided the answers, identifying human proteins from saliva, stomach and intestine, in addition to food proteins. “Data were clearly indicative of vomit, thereby supporting consistence between victim's report and facts.”, said Gianluca.

The forensic proteomics super power was fuelled by Gianluca’s research, which has established marker proteins for different food types. Furthermore, his previous work with Professor Francesco Addeo of University of Naples on the dynamics of food degradation provided the knowledge to reconstruct the meal composition from the puzzle of the fragments of partially digested food. While these two cases demonstrate the power of ad hoc food proteomics in forensic science, the full super power of forensic proteomics can only be unleashed after establishing validated methods and reference standards. This is exactly what Dr Eric Merkley and colleagues Drs. Kristin Jarman and Karen Wahl at Pacific Northwest National Laboratory (PNNL), Washington, USA, has been doing, on the other side of the globe.

PNNL was tasked by US Department of Homeland Security to develop guidelines for the National Bioforensics Analysis Center to use in the analysis of ricin, a deadly biological toxin that had been used in several murders.

As Eric explains, “Ricin is toxic because it enzymatically degrades ribosomes and shuts down protein synthesis. The proteomics approach complements and confirms results from existing biochemical assays, which have some limitations.”

To meet the specific and stringent requirements for admissible scientific evidence in the U.S. Federal court system, the PNNL team had to establish rigorous statistical and scientific methods for forensic proteomics. To this end, the efforts of Human Proteome Organisation in standardising mass spectrometry data reporting was appreciated by the PNNL team, who consulted the Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1, along with standards documents from the World Anti-Doping Organization and the Organization for the Prevention of Chemical Weapons.

PNNL’s effort in standardising proteomics analysis of ricin has allowed this super power to be routinely used in criminal case work to provide support previous methods. Clearly, the super power of forensic proteomics is beginning to emerge in different parts of globe!

To unleash the super power of proteomics, international standardization efforts are critical to establish proteomics as a rigorous scientific method that can progress beyond “research-only” to “application-ready” technology. This has been one of the objectives of the Human Proteome Organisation (HUPO), to cultivate more proteomics super powers.

Interested to know more? Read Gianluca and Maria’s detective work in their scientific articles published in Journal of Proteome Research and Journal of Proteomics. A new book edited by Dr Eric Merkley “Applications in Forensic Proteomics: Protein Identification and Profiling” published by The American Chemical Society provides an overview of proteomics in human body fluids, bone and microbial samples, as well as identification of toxins and considerations of accreditation and defensibility of proteomics evidence.

Mohamed Elzek and Kathryn S. Lilley, Cambridge Centre for Proteomics, Department of Biochemistry, The Milner Therapeutics Institute, University of Cambridge, Cambridge, UK

The interior of eukaryotic cells is characterised by a high degree of structural and functional partitioning into distinct microenvironments dedicated to diverse and specific roles. Trafficking between subcellular niches allows proteins to drive biological processes such as maintaining homeostasis and regulating stress response. Aberrant trafficking is known to be the root of many diseases ^1,2. Methods such as microscopy or affinity tagging are essential to determine the location of individual proteins or protein repertoires of purified organelles ^3,4. However, a thorough understanding of functional dynamics of the proteome, requires a high throughput ability to define the spatial context of the entire proteome of the cell across different cell types, conditions and time points. Many of the current spatial proteomics techniques have been inspired by the protein correlation profiling principle exploited by cell biologists in the 1950 and 1960 to uncover new organelle ^5–12. Membrane bound organelles and protein complexes co-fractionate upon centrifugation purely on the basis of their physical properties such as size, shape and density. Proteins with similar distributions to those exhibited by organelle marker proteins are assigned a single or multiple locations. Since its inception, the Cambridge Centre for Proteomics has contributed extensively to the establishment of spatial proteomics as a field primarily through the development of a technique known as Localization of Organelle Proteins by Isotope Tagging (LOPIT).

The LOPIT approach combines organelle separation based on their characteristic buoyant densities or sedimentation rate by ultracentrifugation, with quantitative proteomics employing multiplexed by in vitro stable isotope labelling, highly sensitive mass spectrometers and multivariate statistical analysis (figure 1). Dunkley et al published the first draft of LOPIT In 2004, providing localisation annotations in Arabidopsis thaliana using Isotope-coded affinity tag (ICAT)⁵. A partial least squares-discriminant analysis (PLS-DA) algorithm enabled novel localisation of a number of proteins to ER, Golgi, and mitochondrial/plastid. Subsequently, the LOPIT methodology has evolved with the development of the field of mass spectrometry-based proteomics with the emergence of the multiplexing capacity of isotope labelling and the higher resolution of Orbitrap mass spectrometers. Furthermore, data analysis and visualisation tools have been tailored towards the output of LOPIT analysis. The pRoloc and pRolocGUI R packages cover a broad range of computational methods from unsupervised, supervised and semi-supervised machine learning, novelty detection and cluster separation assessment to, more recently, transfer learning and Bayesian modelling ^13,14. Over the years, the applications of LOPIT extended to multiple biological systems, most recently the first protein atlas of Toxoplasma gondii ^15–19.

In 2016, Christoforou and colleagues exquisitely portrayed the protein map of mouse stem cells in a single experiment¹⁵. This improved version of LOPIT was rebranded as hyperplexed LOPIT (hyperLOPIT) thanks to higher multiplexing capabilities of amine-reactive tandem mass tags (TMT) 10-plex, MS/MS acquisition using synchronous precursor selection to improve quantitative accuracy and application of support vector machines (SVM) for data analysis. Almost half of the mouse stem cell proteome were annotated to multiple subcellular locations which was later also supported by the human cell atlas project3. Moreover, hyperLOPIT enabled subcellular localisation of some protein isoforms, protein complexes and signalling pathways. A year ago, a comparable system-wide resolution was also obtained differential ultracentrifugation based LOPIT, or LOPIT-DC, in which the spatial proteome of human osteosarcoma U-2 OS cell line was fully characterised using less time, material and resources¹⁸.

Figure 1: A schematic overview of HyperLOPIT (left) and LOPIT-DC (right) workflows

Membrane trafficking is an exemplar field which could benefit greatly from LOPIT. In particular, retrograde trafficking from endosomes to the trans-Golgi network (TGN) involves multiple partially redundant pathways that generate distinct pools of vesicles which are difficult to purify using other antibodies based techniques. Recently, Shin et al applied LOPIT-DC to characterise the endosome-to-Golgi vesicles that are selectively captured by golgin tethers at the TGN¹⁹. These golgins were ectopically redirected to mitochondria in order to determine the content of the specific endosome-to-Golgi vesicles they capture. Bayesian non-parametric testing was employed to identify protein movements towards the mitochondria. A profile shift of 45 transmembrane proteins and 51 peripheral membrane proteins of the endosomal network were detected including known cargo and trafficking machinery of the clathrin/AP-1, retromer-dependent and -independent transport pathways.These findings opens the exciting prospect of using LOPIT to interrogate dynamic spatial protein movements.

Spatial proteomics is still an emerging technology. The continual development of multiplexed mass spectrometry analysis promises enhanced subcellular resolution and motivating dynamic protein localisation studies while alleviating the technical variability ²⁰. Furthermore, LOPIT is a modular technique which facilitates the use of complementary techniques such as RNA sequencing and metabolic profiling. The combination of LOPIT with transcriptomic and metabolic profiling in a spatial multi-omics map has the capacity to drastically reshape our understanding of cell biology. In conclusion, LOPIT has been substantially developed to be a user-friendly approach with the availability of detailed online experimental protocols and an open-source bioinformatics suite ^14,21,22. We encourage our readers to consider applying workflows such as LOPIT to their experiments to harness the power of spatial proteomics.

References

1. Wang, E. T. et al. Dysregulation of mRNA Localization and Translation in Genetic Disease. J. Neurosci. Off. J. Soc. Neurosci. 36, 11418–11426 (2016).

2. Bridges, R. J. & Bradbury, N. A. Cystic Fibrosis, Cystic Fibrosis Transmembrane Conductance Regulator and Drugs: Insights from Cellular Trafficking. in Targeting Trafficking in Drug Development (eds. Ulloa-Aguirre, A. & Tao, Y.-X.) 385–425 (Springer International Publishing, 2018). doi:10.1007/164_2018_103.

3. Thul, P. J. et al. A subcellular map of the human proteome. Science 356, (2017).

4. Go, C. D. et al. A proximity biotinylation map of a human cell. bioRxiv 796391 (2019) doi:10.1101/796391.

5. Dunkley, T. P. J., Watson, R., Griffin, J. L., Dupree, P. & Lilley, K. S. Localization of organelle proteins by isotope tagging (LOPIT). Mol. Cell. Proteomics MCP 3, 1128–1134 (2004).

6. Foster, L. J. et al. A mammalian organelle map by protein correlation profiling. Cell 125, 187–199 (2006).

7. Jean Beltran, P. M., Mathias, R. A. & Cristea, I. M. A Portrait of the Human Organelle Proteome In Space and Time during Cytomegalovirus Infection. Cell Syst. 3, 361-373.e6 (2016).

8. De Duve, C. Tissue fractionation. Past and present. J. Cell Biol. 50, 20d–55d (1971).

9. Itzhak, D. N. et al. A Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neurons. Cell Rep. 20, 2706–2718 (2017).

10. Krahmer, N. et al. Organellar Proteomics and Phospho-Proteomics Reveal Subcellular Reorganization in Diet-Induced Hepatic Steatosis. Dev. Cell 47, 205-221.e7 (2018).

11. Orre, L. M. et al. SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization. Mol. Cell 73, 166-182.e7 (2019).

12. Jadot, M. et al. Accounting for Protein Subcellular Localization: A Compartmental Map of the Rat Liver Proteome. Mol. Cell. Proteomics MCP 16, 194–212 (2017).

13. Gatto, L., Breckels, L. M., Wieczorek, S., Burger, T. & Lilley, K. S. Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata. Bioinformatics 30, 1322–1324 (2014).

14. Crook, O. M., Breckels, L. M., Lilley, K. S., Kirk, P. D. W. & Gatto, L. A Bioconductor workflow for the Bayesian analysis of spatial proteomics. F1000Research 8, 446 (2019).

15. Christoforou, A. et al. A draft map of the mouse pluripotent stem cell spatial proteome. Nat. Commun. 7, 1–12 (2016).

16. Nightingale, D. J., Geladaki, A., Breckels, L. M., Oliver, S. G. & Lilley, K. S. The subcellular organisation of Saccharomyces cerevisiae. Curr. Opin. Chem. Biol. 48, 86–95 (2019).

17. Barylyuk, K. et al. A subcellular atlas of Toxoplasma reveals the functional context of the proteome. bioRxiv 2020.04.23.057125 (2020) doi:10.1101/2020.04.23.057125.

18. Geladaki, A. et al. Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics. Nat. Commun. 10, 1–15 (2019).

19. Shin, J. J. H. et al. Determining the content of vesicles captured by golgin tethers using LOPIT-DC. bioRxiv 841965 (2019) doi:10.1101/841965.

20. Thompson, A. et al. TMTpro: Design, Synthesis, and Initial Evaluation of a Proline-Based Isobaric 16-Plex Tandem Mass Tag Reagent Set. Anal. Chem. 91, 15941–15950 (2019).

21. Mulvey, C. M. et al. Using hyperLOPIT to perform high-resolution mapping of the spatial proteome. Nat. Protoc. 12, 1110–1135 (2017).

22. Breckels, L. M., Mulvey, C. M., Lilley, K. S. & Gatto, L. A Bioconductor workflow for processing and analysing spatial proteomics data. F1000Research 5, 2926 (2018).

Sudhir Srivastava, National Insititues of Health, National Cancer Institute, USA

The National Cancer Institute has recently announced the funding opportunity for Single Cell Proteomics in Interrogating the premalignant and early malignant lesions. The purpose of this Notice of Special Interest (NOSI) is to: (1) encourage investigators to apply single-cell proteomics for interrogation of premalignant and early malignant lesions; (2) develop new multiparametric biomarkers for cancer screening, early detection and risk assessment; and, (3) establish a biomarkers workflow for a wide coverage of disease variability and individuals at the population level.

Recent advances in single-cell genomic and transcriptomic technologies enabled a better understanding of the cellular content of tumorigenic lesions, including early detection of clonal evolution, detection of the emergence of drug-resistant cells and improved phenotypic characterization of the lesion’s cellular heterogeneity. Single-cell mass spectroscopy-based proteomics and antibody-based targeted proteomics are emerging as powerful complementary approaches for the characterization of individual cell types within a lesion, their intercellular networks, and their dynamic physiological state. In addition, these approaches can be used to identify, map and visualize aberrant subcellular structures, intracellular networks, molecular interactomes, and proteoforms some with cancer-associated posttranslational modifications that cannot be predicted by genomic/transcriptomic analysis. The detected molecular, structural and functional aberrations are potential cancer markers and targets for prevention and therapy.

For further details on how to apply, click here. Any questions regarding this NOSI can be addressed to:

Sudhir Srivastava, Ph.D., MPH
srivasts@mail.nih.gov

Jacob Kagan, Ph.D.
kaganj@mail.nih.gov

Sanjeeva Srivastava, IIT Bombay, India

Prof. Sanjeeva Srivastava, convener of this event, delivered a lecture on “Precision Medicine” and seeded the concept of latest revolutions in DNA and Protein based OMICS technologies to the budding scientists. Further, several renowned scientists gave mentorship to the student & glimpse of “magic of science”.

From all over India over 850 teams participated in such innovative competition and top 10 teams displayed their innovative science & technology projects. This education and outreach initiative was highly appreciated by the community.

Sanjeeva Srivastava, IIT Bombay, India

Omics Big Data handling and making sense out of the data for its usage in precision medicine has become a hot topic recently with technical advancements and researchers better understanding of big data analysis and management. IIT Bombay, India and NTU, UK in collaboration organized this event to provide training and spread knowledge of big data handling and analysis with the help of Artificial Neural Networking and Machine learning using basic softwares available to us.

This event was a success due to eminent scientists and researchers from India and abroad sharing their knowledge and expertise’ about the field. Additionally, clinicians’ contributed to the issues being faced currently in various cancers like ovarian, breast, cervical, brain and others, along with infectious diseases like tuberculosis and malaria. This provided researchers’ and scientists’ idea to work on various collaborative projects on infectious diseases and cancers.

This advanced workshop was conducted for limited number of young faculty and researchers to be able to understand advances in the field of big data research and how it could be used translation into the clinics.

Hands-on sessions for proteomics sample preparation, Mass spectrometry based label-free, labeled (TMT/iTRAQ) and targeted proteomics sessions were intensive but very useful. Participants also got training for metabolomics, genome sequencing basics and data interpretation.

Additionally, an Indo-UK round table brainstorming session was conducted to bring great minds of the fields (researchers, academia, industry, clinicians and policy makers) together to conceive collaborative project(s) and initiatives to make a common database for big data handling, which could be shared with the community. This will help us taking steps towards converting the idea of personalized medicine to reality.

This event was supported from Department of Science and Technology, Government of India and UKIERI, British Council UK.

The ECR initiative is excited to welcome two new members: Drs. Rob Rivers and Omar Mendoza Porras. They will play key organizing roles in ECR activities, such as the HUPO Manuscript Competition, Mentoring Day and Ph.D. Poster Competition. Please have a look at their short biographies to get to know them a little better.

Rob Rivers, PhD is a program director in the Office of Minority Health Research Coordination (OMHRC) at the National Institute of Diabetes, Digestive and Kidney Diseases, one of the Institutes that comprises the United States National Institutes of Health. In his role as a program director he leads programs focused on increasing the diversity of the biomedical research work force and expanding NIDDK’s research portfolio in health disparities related research. Previously, Rob worked in the Office of Cancer Clinical Research at the National Cancer Institute where he helped to fund and guide proteomics initiatives in cancer. His doctoral research focused on the study of intrinsically disordered proteins and their propensity to aggregate, and their implications in disease. In addition to his work in science, he is active in the local and global community and was instrumental in starting the international non-profit organization Umbrella Initiatives Foundation that helps in providing improved educational opportunities to children living in poverty in Peru, Bolivia and Montgomery County, MD (www.umbrellainitiatives.org). He holds a Ph.D. degree in Chemistry (2008) from the University of Cambridge and a B.S. degree in Chemistry (2003) from Kentucky State University.

Dr. Omar Mendoza-Porras is a Postdoctoral Research Fellow at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia, where he enables proteomics research into commercial aquaculture species. His research focuses on identifying markers for growth and immunity in plasma of cultured shrimp and salmon with the goal to help develop sustainable diets that stimulate optimal growth and health. Dr. Mendoza-Porras also investigates the importance of hemocyanin subunit heterogeneity in human allergenicity following shrimp consumption with a focus on epitope identification. Dr. Mendoza-Porras obtained his B.Sc. in Oceanography and M.Sc. in Marine Biotechnology at the University of Colima and CICESE, Mexico. His Ph.D. was conferred at Flinders University, Australia, where he identified sexual maturation markers in gonads of cultured abalone using proteomics.

Olga Vitek, Northeastern University, USA

The May Institute on Computation and Statistics for Mass Spectrometry and Proteomics, taking place on April 27 – May 8, 2020 on the campus of Northeastern University in Boston MA, is now accepting applications. The application deadline is January 31, 2020.

New this year is a "Future developers meeting", a 2-day program that brings together developers (and aspiring developers) of R/Python tools for mass spectrometry and proteomics. We invite you to submit an abstract and present your research at the workshop.

Participants can select a subset of the following programs:

* Targeted proteomics with Skyline

* Proteomics and metabolomics with OpenMS

* Beginner’s statistics in R

* Intermediate R and data visualization

* [NEW THIS YEAR!] Future developers meeting

* Statistics for quantitative mass spectrometry

* Scientific writing

* Capstone – case studies in data-independent acquisition (DIA)

Instructors are leading experts, who contributed numerous experimental and computational methods and software. The target audiences are both beginners and experienced scientists, with both experimental and computational expertise.

Tuition fee waivers and travel fellowships will be available for students and postdocs affiliated with academic or nonprofit institutions in the US. Accepted presenters at the Future developers meeting will have a free admission to this part of the program.

More information is at https://computationalproteomics.khoury.northeastern.edu/

C-HPP Executive Committee (EC)

The C-HPP EC members wish all members of HUPO a Happy and Successful Year in 2020!

We look forward to the chromosome teams continuing their efforts on identifying more missing proteins and characterizing uPE1 proteins at this juncture of new decade. The following events and publications will highlight our scientific endeavors for exploring new proteins and their functions which you are always welcome to join us.

February, 2020: New release of neXtProt that will update the status of Missing Proteins, uPE1 protein and other related information for the Human Proteome Project of HUPO.

May 15-18, 2020: 23rd C-HPP Workshop on the theme of “From chromosome-centric project to the human proteome, which commemorates the 10th Anniversary of the C-HPP Initiative”. This annual C-HPP workshop will be taking place in Saint Petersbourg, Russia and on a cruise ship. The Preliminary Program and registration information will be available soon at the end of January.

May 31, 2020: Deadline of manuscript submission for JPR Special Issue on the Human Proteome Project (Targeted Publication Date: 1st week of December, 2020)

August 1, 2020: Publication of C-HPP Newsletter No. 9

October 18, 2020: 24rd C-HPP Workshop during the 19th HUPO Congress, Stockholm, Sweden.

October 21-22, 2020: HPP Workshop, Upsala, Sweden

The C-HPP Wiki

The C-HPP wiki is continually being updated and we require your input for the individual chromosome teams. Each chromosome group can upload themselves or send their neXt-MP50, neXt-CP50 progress and other update for their chromosome to Peter Horvatovich (see C-HPP Wiki).

We anticipate that you will join us and contribute to these exciting events and publications throughout this year of new decade.