Dr. Shi-Jian Ding, an assistant professor in the University of Nebraska’s College of Medicine, is a researcher in the field of proteomics – the large scale study of proteins and their functions. He develops methods to address biological and biomedical problems through the identification and quantification of proteins and their post-translational modifications (PTMs) in diverse biological systems. PTMs are the changes in the protein’s chain of amino acids that extend its range of functions. The goal is disease prevention.
Abnormal PTMs are often a cause or consequence of many pathological and disease conditions. When scientists study PTMs, they are usually studying only one modification at a time. Now, however, using the power of the Open Science Grid, Ding and his colleagues are able to ask which global modifications occur not only on a single protein, but also on a group of proteins like histone proteins (the major structural proteins of chromosomes). They can then delineate the functions of these modifications, asking how the proteins coordinate with each other – and, perhaps more importantly, how the modifications regulate protein functions.
Over 300 different modifications naturally occur in the proteins of human cells, making Ding’s research especially challenging: Once you get the search results, how do you evaluate the confidence level of each modification? As far as Dr. Ding can tell, his team is the first to simultaneously address the accurate localization of multiple modifications. Using the Open Mass Spectrometry Search Algorithm (OMSSA), an open source search engine for analyzing and identifying peptides, Ding and colleagues evaluate the confidence level of each modification identified by OMSSA.
With the help of the University of Nebraska’s Holland Computing Center (HCC), directed by Dr. David Swanson and integrated with the Open Science Grid, the team has modified OMMSA so they can now search as many modifications as needed. But, this isn’t possible without the resources of the Open Science Grid. Global modifications pose a big computational problem. Much like gene sequencing, mass spectrometry instrumentation generates big data. Effective analysis of data is also a significant challenge.
“OSG allows us to ask what the global protein PTM changes are,” said Ding. “Previously, we couldn’t ask certain questions because of limited computing power. Now, with essentially unlimited computing power, we can perform this kind of research.”
HCC provides services to researchers throughout the University of Nebraska system. “Dr. Swanson is proactive in reaching out to researchers here. That was how we found out about the OSG, and that has transformed our research,” notes Ding. “Now, we are working with Swanson’s group to develop an interface for proteomics researchers – otherwise it will be difficult for them to utilize the OSG.” Once the interface is fully developed, Swanson and Ding plan to publish it for other researchers to use.
“I wish more researchers knew about the OSG,” added Ding. “It is freely accessible and has seemingly unlimited computing power. It allows them to ask questions they didn’t dare ask before. Plus, OSG has workshops and a great support system.”
Ding would eventually like to see a resource akin to the Apple App Store – “an OSG store.” In the last few years, his group has developed UNiquant (software for protein quantification from multiple database search engines) for analyzing quantitative proteomics data. “These are the kinds of tools that would encourage other labs to look at the OSG and think about developing even more interfaces – tools we could put in the store for other researchers to find,” said Ding.
Proteins play important roles in cells and what happens to them, both normally and abnormally. With in-depth studies of proteins, researchers like Ding can find markers for early diagnosis and prognosis of disease – and further their ability to predict whether a patient will respond to a given drug treatment. This work helps with discovering new drug targets, overcoming drug resistance in existing drug targets, and developing better therapeutic approaches.
Ding is currently involved in two projects. The first involves studying epigenetic memory during the stem cell reprogramming process. Epigenetic memory makes it easier for cells to reprogram to stem cells and subsequently back into any semantic cell type. Together with colleagues in Nebraska’s Pharmacology and Experimental Neuroscience, Ding is looking specifically at neural progenitor cells – biological cells that offer more specificity than stem cells and can be pushed to differentiate into target cells – that could be transplantable. This might lead to new approaches to neural degenerative diseases like Alzheimer’s and Parkinson’s, which are notoriously difficult to treat.
Ding’s second project involves studying nuclear matrix proteins, which play an important role in DNA. Collaborating with another colleague, Ding seeks to understand how protein PTMs regulate in a nuclear matrix that triggers a DNA damage response. For example, the two hope to understand why some people are resistant to chemotherapy drugs, and how to overcome that resistance to better treat cancer patients. Ultimately, the Open Science Grid is indispensable to the bold new approaches that Dr. Ding and his colleagues are taking to study proteins and PTMs – approaches that have the potential for breakthroughs in disease diagnosis and treatment.