by Theresa Pepin
In the long list of worries that life entails, water—especially fresh water, our most precious resource—should be right up there. And yet, although we may vaguely suspect that our waters are “troubled” from time to time, it seems to be natural for us to assume that nature will somehow take care of them for us, no matter what. Wrong.
Many microorganisms are involved in the natural processes that “purify” our waters, but some cause unintended consequences in certain conditions. In recent decades, degradation of fresh waters by microbial activity has increased globally at alarming rates. We are aware of the organisms involved but we don’t really know much about the direct causes, nor how to predict or prevent the damage.
By the time toxic cyanobacterial “blooms” make the evening news, many have already been put at risk from exposure to their harmful effects. With such events increasing in frequency and intensity, resource managers responsible to the millions of people and animals who live near such “troubled waters” are desperate to learn how to deal with them. It is critical to identify specific environmental factors driving these blooms and develop predictive capabilities to support technical monitoring and decision-making at local levels.
To tackle this problem, the JDRD team led by Steven Wilhelm will adapt High-Throughput Transcriptomics (RNAseq) developed for microbial bioforensics to create transcriptome profiles for healthy, unhealthy, and transitional waterways as well as the major microbial agent Microcystis aeruginosa. A transcriptome is the complete set of messenger RNA (mRNA) molecules (the transcript) produced in a cell or a population of cells.
The LDRD project led by Bioinformatics Staff Scientist Loren Hauser at ORNL has developed a new approach for bio-threat and bioforensic analysis of laboratory-grown bacterial strains that is superior in specificity and sensitivity. A robust automated analysis pipeline identifies all significant differences between any two transcriptional profiles and links these profiles to candidate pathogenic bacteria, just as human fingerprints or DNA are used today.
The first phase of the JDRD project involves laboratory-based culture, experiments and “fingerprinting” of the organisms during rapid growth associated with blooms. In the second phase, Wilhelm and his team members, PhD student Morgan Steffen and graduate student Shafer Belisle, “get their feet wet” in a field expedition aboard a Canadian Coast Guard research vessel examining a part of Lake Erie where blooms have recurred annually for fourteen years. There they will collect samples and metadata regarding environmental conditions—such as nutrients, temperature, light, turbidity—to bring back for validation testing of the biological signatures.
The JDRD project effectively extends the LDRD analytic technique to environmentally collected samples to help determine how the environment influences the expression of genes involved in creating dangerous cyanobacteria blooms. Establishing this ability to complete metatranscriptomic analysis and data pipelining will put the collaboration in the forefront of microbial ecologists working globally with environmental samples, especially in fresh waters.
The JDRD puts the LDRD technique to the very challenging test posed by highly complex environmental samples—made complex by the natural diversity of the tens of thousands of microorganisms found in fresh waters. In effect, the work is developing an approach to study a microbial “needle” in a microbial “haystack,” forcing the LDRD pipeline to sort through an immense number of bits of “distracting” data to find the real “culprits” in the field samples.
The success of the JDRD-LDRD collaboration will improve ecological models and allow for an “early warning system,” giving resource managers the information they need to find ways to either inhibit or rapidly recover from toxic blooms affecting millions of people and animals.
High-throughput transcriptomics to secure ecosystem health in freshwater systems
Steven Wilhelm, UT Department of Microbiology
High-Throughput Transcriptomics for Microbial Bioforensic Analysis
Loren Hauser, ORNL Biosciences Division