Thursday, November 15, 2012

Massive computing power needed to unravel gut bug/cancer link

The human microbiome - the bacteria, viruses and fungi living on and in us - made news in June when the Human Microbiome Project first cataloged the mix of bugs for a healthy American.

With the typical set of bugs now outlined, researchers are searching for the bug profiles that correlate with diseases. New understanding of our complex microbial communities is laying the foundation for advances in the treatment of infectious, autoimmune and inflammatory diseases, including the process by which inflammation contributes to cancer.

Against this backdrop, the UAB Comprehensive Cancer Center chose "cancer and the microbiome" as the theme for its recent research retreat. The Mix interviewed several retreat presenters will be featuring the chats as a podcast series over the next few weeks.

Our guest today is bioinformatics expert Elliot Lefkowitz, Ph.D., associate professor in the UAB Department of Microbiology. We talked about how efforts to integrate research on cancer and the microbiome depend on bioinformatics, the high-powered computational analysis needed to reveal patterns within the mountains of data generated around the human microbiome. The data sets involved are many, many times larger than even the three billion coding units making up human genetic material.

Show notes for the podcast:

2:14  Researchers estimate that about 100 trillion microbes live on and in the human body, ten times as many as there are cells in the human body.

2:37  Research on the microbiome is revealing that, along with efforts by the human immune system to keep disease-causing microbes (e.g. bacteria) in check, certain sets of bugs in our body also help to defend against their pathogenic brethren.

3:11 Making matters more complex, the human microbiome is in flux, so it may change from a helpful mix of bugs to one that contributes to disease with changing circumstances. Being able to watch for that profile change would represent a medical advance. This change may be driven by a disease process, or may cause it in some cases.

3:33 The UAB cancer center is interested in changes in the microbiome because evidence suggests that bug profiles are changed by, and may change, cancer processes.

3:53 Bioinformatics is the computational analysis of biological data. Frequently, it deals with genetic sequence information, the DNA coding units that make up the genetic instructions for the building of a human. The order, or sequence, in which those units occur with DNA chains makes up the letters and words in these instructions. They are translated under the right circumstances into the proteins and regulatory elements that make up the body's structures and carry its messages.

4:30 After Michael Crowley, Ph.D., and his team at UAB's Heflin Center for Genomic Science, determine the sequences of the DNA chains in the bug genetic material, Eliott Lefkowitz, Ph.D., and his team at UAB's Molecular and Genetic Bioinformatics Facilty use bioinformatics to analyze them in different ways.

5:05  When Lefkowitz started in bioinformatics 25 years ago, the field was engaged in determining the sequence of a single gene, perhaps made up of about 1,000 coding units, otherwise known as codons.  It was a challenge with the computers of the day, but they did it. A few years later, Lefkowitz and others began looking at viral DNA sequences, which required them to analyze perhaps 200,000 coding units, and then bacteria, with perhaps 2 million coding units in play. With modern day next-gen sequencing, researchers may have to analyze 20 billion genetic units per sample.

7:11 The amount of information that researchers are having to analyze is so overwhelmingly greater that it was even five years ago that bioinformatics experts like Lefkowitz, even with leaps in computing technology, are having to create new computational techniques for using that computing power to get the job done.

8:20 For years, bioinformatics experts, including some at UAB, having been experimenting with concepts like cloud computing and Web 3.0, techie terms for massive stores of patient data and a unified system to analyze it. Lefkowitz and his colleagues work closely with the UAB Information Technology's Research Computing group (UAB ITRC), which makes available to research groups many resources, including the Cheaha cluster. It's a private network of individual data processors networked together to act like a supercomputer. When they need even more computing power, they turn to the cloud, in some ways like the networks that make Google searches so powerful.

10:00 To understand the impact of any individual's microbiome on that person's health, researchers need to know its make-up, the number of each kind of bug in comparison with others present, and what those ratios look like in a healthy person. A healthy microbiome is likely to vary by where you live, but there are some constants that could then be compared against those who have any particular disease.

10:58 Bioinformatics tools make it possible for researcher to compare the numbers and types of microbes in people who are healthy against those with each disease to see if different bugs dominate in people with a disease. Statistical associations promise to yield give clues that may lead researchers to create treatments that change microbes, rather than human cell signalling pathways, to treat human diseases.

13:00 Proteins, the workhorse molecules of human tissue, are made up of functional building blocks, many of which are used again and again by many different proteins. So when researchers see one of the known blocks in a protein of unknown function, it gives them some clues about what it does, especially when combined with bioinformatic analysis. Discovery of such repeating pattern often provides clues to overall biology.

14:20  In analyzing microbial communities, finding repeating patterns, like distribution of each bacterial types, and the ratios of one to the others represent patterns that can be compared between a person who is healthy and another with diabetes, for example. Lefkowitz can go even deeper and look at how at patterns in the proteins created by each set of microbes to see which are associated with disease or health.

No comments:

Post a Comment

We encourage and look forward to your comments on The Mix (and in its related social networking outposts).

Comments will be reviewed before they're posted. Those that are not related to the topic under discussion, promote products or use profanity or abusive language will not be included.