As key regulators of gene expression and cellular machinery, microRNAs may be the most significant discovery in molecular biology in the last decade. Because of their enormous potential, Frost & Sullivan projects that current U.S. microRNA revenues of about $20 million in 2008 will increase to more than $98 million in 2015.
The buzz in the industry stems in part from the global presence of microRNAs. These 18- to 25-nucleotide noncoding RNAs operate in organisms ranging from roundworms to mosses and even viruses. The roughly 1,000 human microRNAs discovered so far regulate nearly half of all genes. Dysfunctions are associated with disease processes that range from dementia to cancer. New insights are emerging into the biology of how they work, what happens when they don’t, and their potential use in targeted therapies.
Caenorhabditis elegans provides an ideal model system to study microRNA functions in eukaryotes, according to Alison L. Abbott, Ph.D., assistant professor at Marquette University. “C. elegans has many microRNAs that show nearly complete conservation between worms and humans. Earlier studies in C. elegans demonstrated that microRNAs are critical regulators of developmental timing genes.”
To characterize how individual microRNAs control such genes is no easy task. “There is a cooperativity of microRNA families and on some level they will function together,” Dr. Abbott notes. “So, we decided to begin studying individual microRNAs with a subset of 20–30 that show some sequence conservation with other organisms such as mammals, flies, and fish.”
Dr. Abbott developed a model system in C. elegans to lower the genetic background sufficiently to test if deletion or mutation of the specific microRNAs made a difference in the worm’s development. Her team targeted the genes for Argonaute proteins, which are the catalytic subunits of the RNA-induced silencing complex (RISC). The latter protein complex mediates gene silencing or RNA interference.
“Mutations in two Argonaute-encoding genes, alg-1 and alg-2, result in lower microRNA levels and lethality in C. elegans,” Dr. Abbott reports. “However, knockdown of just alg-1 results in lower microRNA levels but sufficient levels for the worms to progress through embryonic and larval development. This creates an optimal sensitized background that allows us to test the effects of losing an additional single microRNA or a single cluster of microRNAs.”
According to Dr. Abbott, not only can microRNAs regulate a common target, but they also may function through different targets while still regulating the same pathway. For the future, Dr. Abbott hopes “that the combination of bioinformatic approaches and genetics will help us identify key biologically relevant targets.”
Validating microRNA Targets
Although microRNAs control many aspects of an organism’s development, the specifics of microRNA-mRNA regulatory interactions is largely unknown. Liang Zhang, Ph.D., who is currently working at The Rockefeller University, also developed an approach using a C. elegans model while in the laboratory of Min Han, Ph.D., at Howard Hughes Medical Institute and the University of Colorado at Boulder. Dr. Zhang creates and expresses a fusion protein in which green fluorescent protein (GFP) is tagged to AIN-2, an essential member of miRISC (microRNA associated RISC).
“This model can be used to generate a more global look at the dynamics of microRNA-mediated regulation of gene expression during the worm’s development,” Dr. Zhang says. “We prepare lysates during five developmental stages and immunoprecipitate the AIN-2:GFP containing miRISC with an antibody to GFP. Then, we analyze the microRNAs and mRNAs in the immunoprecipitated complexes using deep sequencing and microarrays, which allows us to access the profiles of microRNAs, microRNA targets, and interactions. We found that more than 2,000 mRNAs associate with the AIN-2 family during worm development.”
Using that data, Dr. Zhang then identified thousands of microRNA targets related to each developmental stage. “We used this data to predict more than 1,500 microRNA family-mRNA interactions. Our data indicates that microRNAs have a high degree of specificity and preferentially target genes involved in signaling and do not regulate genes involved in housekeeping functions.
“Further, although perfect complementarity between bases 2–8 of the microRNA and its targets is a highly enriched feature of these microRNA family-mRNA interactions, additional matching between bases 9–10 of the miRNA and its targets are depleted, suggesting that perfect target matchings in the center region of the microRNA are avoided by functional interaction in vivo.”
Dr. Zhang reports that his studies indicate that microRNAs target and have preferences for different stages of development. “MicroRNAs are trying to temporally coordinate processes in different stages of development. Our future studies will begin to analyze spatial patterns of microRNA regulations in specific tissues of the worm, since our current studies used lysates of the whole worm.”
Dissecting how microRNAs work, individually as well as with other regulatory molecules in the complex network within the cell, is a significant hurdle. Bioinformatic modeling can help unravel the intricate workings, says Jiang Qian, Ph.D., assistant professor at Wilmer Institute, Johns Hopkins University School of Medicine.
“Many researchers study only one or a few microRNAs to better understand and profile their activity. It is also important, however, to view the global picture of interactions within such regulatory networks. We use a bioinformatics approach to understand network interactions and gene regulation. Our goal has been to examine a broader scope of network motifs that are the basic building blocks of the regulatory networks."
Dr. Qian’s group studies not only the interactions of transcription factors with microRNAs, but also other types of network motifs where there could be regulatory targets. “In a recent study, we examined 46 network motifs in order to examine the biological roles they play. We found that transcription factors and microRNAs work together and tend to regulate each other as well as coregulate genes. By looking at global signatures, we found a highly represented pattern showing there is a feedback loop in which two transcription factors regulate each other and one microRNA regulates both of the factors. This is important because it helps explain how microRNAs contribute to development.”
Another finding was that there are two overall classes of microRNAs. “It is clear that specific microRNAs show distinct preference for either functioning in embryonic conditions (class I) or for functioning in adult tissues (class II). We feel that this is a valid finding since these expression patterns are conserved across species including humans, mice, and zebrafish. Also, we used several platforms to come to the same conclusion.”