Translation, the process of protein synthesis by ribosome decoding of the genetic codes on messenger RNA, is one of the most fundamental biological processes in all three kingdoms of life. Translation is closely regulated in the cell to coordinate with other cellular events and to adapt to environmental stress. Abnormality in translational control of gene expression in humans has been implicated in many diseases, such as cancer, metabolic diseases (for example, obesity and diabetes), and viral infection. Drugs have been developed to: (i) treat tumors by down-regulating translation; (ii) treat viral infection by altering frame-shifting efficiency; (iii) treat genetic disorders by promoting read-through of nonsense mutations; and (iv) treat microbial infection by inhibiting the prokaryotic ribosome function. Understanding the mechanism of translational control of gene expression is of great significance for developing better drugs and fighting human diseases.
Diverse mechanisms have been discovered for translational control of gene expression, but our understanding is still greatly lacking in many areas as a result of the inherent complexity of the translation system. Specifically, translational control is a very fast, dynamic process involving many protein and RNA factors. This imposes great technical challenges for monitoring translational control in real time on the molecular level, which has a minimal requirement of simultaneous millisecond time resolution and nanometer spatial resolution. Such requirement is out of the range of traditional biochemical and biophysical techniques. The recent developments in single-molecule techniques filled the gap and opened the door to elevate our understanding of translational control to a new level. Examples of two types of single-molecule techniques are shown below. The goal of our lab is to unravel the fundamental molecular mechanisms of translational control of gene expression by integrating advanced single-molecule optical microscopy, biophysical and biochemical techniques, and quantitative modeling.