Living a dream Dr. Bin Ma, Bioinformatics Solutions Inc.

---

By Shawn Lawrence

Biologists and pharmaceutical researchers often need to know what proteins are present in biological samples. Mass spectrometry has become the standard way to procure this information. Through the use of computer software and manual research, researchers are able to analyze this data and report what proteins are in the sample. However, one problem that bioinformatics researchers have had difficulty with is finding a precise way to identify novel proteins.

It took Dr. Bin Ma to succeed in finding a solution to this problem. As the chief technology officer with Waterloo-based Bioinformatics Solutions Inc., Dr. Ma has helped develop multiple products that are now used by leading pharmaceutical companies, biotechnology firms, research hospitals, government labs and university research centres for the purpose of protein identification. These products, PEAKS and PatternHunter are able to not only report what proteins are in a sample but also identify novel proteins.

From his earliest childhood memory, Dr. Ma says he always dreamed of being a scientist.

Growing up in China, the dream wasn’t that different from many of his peers.

Competition was fierce but he studied hard and enrolled at Beijing University. That was just the first step. What came after was a series of decisions, a few moments of serendipity and a drastic life choice to leave China and move to Canada.

Ma was first introduced to bioinformatics while taking a summer course taught by the man that would eventually become his mentor, friend and future business partner, Professor Ming Li.

“In 1996, Professor Ming Li offered a short course in bioinformatics and I sat in his class and did well, so he started to give me research problems to solve. This worked well for me because at the time I was looking for a topic to do my Ph.D. thesis on, solving these research problems offered the perfect opportunity.”

The friendship between the two men grew.

After Ma received his Ph.D., he followed Professor Li to Canada, specifically to the University of Waterloo. There he continued his research under Li’s tutelage working towards his post doc. Some time in 1999, Ma developed a software program that could be used for DNA homology searches. The program was called PatternHunter and it gained the immediate attention of bioinformatics researchers worldwide. In early 2000, Ming Li and Ma, together with a few other researchers decided to found Bioinformatics Solutions Inc. Pattern Hunter would be the first software that Li and Ma would commercialize.

As the company continued to grow, Dr. Ma joined the University of Western Ontario as an assistant professor. It was a wise career move as he was promoted to the position of associate professor, and appointed the Canada Research Chair in Bioinformatics.

Not long after that Dr. Ma experienced another breakthrough in his research.

“I collaborated with a few colleagues on a problem called “de novo sequencing with mass spectrometry.” This is a computational problem to calculate the sequencing information of a peptide from its tandem mass spectrum. We published a novel algorithm to do this computation and solved the problem,” said Ma.

Based on the algorithm, the developers at Bioinformatics Solutions Inc. developed the software called PEAKS, and released it in June 2002. Since then, PEAKS has gradually become the standard de novo sequencing software and the company’s most successful product.

The reason for PEAKS success explains Ma, is that up until now there were only two approaches to do protein data analysis. One method is a “database search,” basically that the to-be-identified proteins are listed in a known protein database (for example, the human protein database). One only needs to find out which protein it is.

But according to Ma, this approach cannot identify proteins that are not already in the database.

“Modern pharmaceutical researchers needed to know what proteins were in disease samples. Many of these proteins found in disease are heavily modified after the synthesis of cells and there are slight mutations between the same proteins of different individuals. There are also un-sequenced organisms out there. Thus, a protein sequence database is never complete making the identification of novel proteins very difficult to do.”

The solution to this problem before PEAKS was for researchers to manually identify the novel proteins.

“In this approach one needs to construct (instead of to find) a peptide sequence that best fits the data. This presents a problem because you don’t have the sequencing database as a reference. Before we developed the PEAKS software, no other software could do the de novo sequencing well and the data analysis could only be done by an experienced human. The problem is each experiment generates thousands of tandem mass spectra, which cannot be interpreted by a human in a timely manner. Some computer software for de novo sequencing was developed elsewhere but they were all very rudimentary and inaccurate. So, People in this field were waiting for an automated and accurate computer program.”

The development of PEAKS for the first time satisfied this marketing need. In fact there are now many examples of the program being used today, from theoretical research to practical research, as well as for pharmaceutical research and food safety.

Some of the better known users include a group from Department of Chemistry and Department of Agricultural, Food, and Nutritional Science at University of Alberta. These researchers have used PEAKS to assist their de novo sequencing of a protein isolated from fresh pork.

The protein has the potential to be used for safer food preservation and for human therapeutics. In another example, PEAKS was used by researchers from the Department of Pediatrics, Oregon Health and Science University for a Down syndrome biomarker study.

The next step says Ma, is continuing to develop the PEAKS software to the point that it can be used for protein quantification.
“Researchers not only want to know what proteins are in a sample, but also the quantity of proteins. Protein quantification is also very helpful in finding biomarkers,” he said.

Dr. Ma has been equally innovative in marketing PEAKS, increasing sales by 20 to 40 per cent a year since its launch and helping Bioinformatics Solutions become the world’s second largest protein identification software provider.

“Marketing properly is extremely important. For us, The American Society of Mass Spectrometry Conference opened a few doors. We spent lots of money initially on marketing at this conference, to get face to face with potential customers, for feedback as to what they needed from our software. We’ve attended other trade shows as well, just to get people talking about us and our software programs. Another important thing we’ve done is to provide one-month free and full-functional trial versions to potential users. That’s the thing, we believe in our products, and we rely on their reputation. And because the product works, more and more people are hearing about us by word of mouth.”

There are some challenges that Dr. Ma admits he’s faced in transitioning from the role of scientist into someone who is running a business that go beyond just marketing the products, but so far he’s managed to overcome them.

“One challenge I’ve faced is that it’s very different writing a research paper as opposed to developing successful commercial software. As a researcher all you need is a brilliant idea, and some experimental data that shows the idea works. In order to develop a successful commercial product you have to consider other things, like size of market, who your customers are and building strong relationships. One thing we’ve tried to do is make our software work with as many mass spectrometers as there are on the market which of course leads to other challenges. Everyone has different file formats, different properties, and so we have to ensure our software is adaptable to this wide variety. So as much as we rely on building strong relationships with our customers, it’s been equally important to have developed some strong relationships with mass spectrometry vendors.”

Does he regret the choice of turning his research idea into a business, going the commercial route rather than making it available to all that could use it in academia? His answer is a resounding no.

“I wanted to make my research more useful and more accessible to the end users. There is a common misunderstanding in the research community that commercializing the software limits its accessibility. I don’t think that’s the case. Although many open source projects are successful, many others just die out because of lack of support. That might’ve happened to both PatternHunter and PEAKS had I gone that route. So, I feel it would have been irresponsible to my research result just throwing it out there as an open source project and then forgetting it. By making my research idea commercially available, the development of the product became well-supported and has been driven by the end-users needs. I feel lucky that I chose to do things the way I did because it did help to promote the software and make it more accepted by the community. Plus, if I had chosen to make it open-source and free, I would have never been able to secure enough funding support to gather the group of developers together that I’ve had working on the product. Lastly, I don’t think Peaks are Pattern Hunter would’ve become this successful.”

References
1.     Leah A. Martin-Visscher, Marco J. van Belkum, Sylvie Garneau-Tsodikova, Randy M. Whittal, Jing Zheng, Lynn M. McMullen, and John C. Vederas. Isolation and Characterization of Carnocyclin A, a Novel Circular Bacteriocin Produced by Carnobacterium maltaromaticum UAL307, Applied and Environmental Microbiology, Aug. 2008, p. 4756–4763.
2.     Nagalla SR, Canick JA, Jacob T, Schneider KA, Reddy AP, Thomas A, Dasari S, Lu X, Lapidus JA, Lambert-Messerlian GM, Gravett MG, Roberts CT Jr, Luthy D, Malone FD, D’Alton ME. Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers. Journal of Proteome Research. 2007 Apr;6(4):1245-57.