Cell: Publishing innovative protein research technology

Like a small, well functioning machine, an enzyme is a kind of protein composed of multiple interlocking molecular elements, which performs various tasks in each cell However, how exactly do these components work together to accomplish the task? This problem has been plaguing scientists for a long time Now, a team of researchers has found a new way to map the potential molecular machinery of an enzyme Based on the patterns it reveals, researchers can predict how an enzyme behaves and what happens when the process is disrupted In the August 8 issue of cell, a team of scientists led by Dr Nevan krogan, a researcher at Gladstone Institute and the University of California, San Francisco, Dr Craig Kaplan at Texas A & M University, and Christine Guthrie, a professor at the University of California, San Francisco, described what they call a "point mutant With the help of E-map, researchers can accurately find and map thousands of interactions among many moving parts of an enzyme The researchers focused on the well-known RNA polymerase II (RNAPII) and used S cerevisiae as a model In the past, researchers have mapped out the physical structure of RNAPII, but it is not clear how the various parts of the enzyme work together with other proteins in the cell to complete important functions "Scientists know the physical structure of RNAPII, but this large enzyme has many different regions, each of which performs different functions," Dr Kaplan said We want to connect the points between these areas and functions " The team used a genetic approach to generate 53 "mutants" of RNAPII, each of which changed a specific element of RNAPII They want to test specific functions for each mutation In this way, they are able to associate specific areas of the enzyme with a specific function But in doing so, they have to compare each mutant with thousands of functions related to RNAPII in cells, which is a huge task that cannot be completed by traditional methods Therefore, the team developed this PE map method "Instead of cross comparing a single point mutation with one or two different mutants, PE map enables us to cross compare a single point mutation with more than 1000 mutants," Dr krogan said This provided us with 1000 data points of each mutant, and then we used these data points to build a high-resolution map " "Until now, the only way to get similar information is to inactivate or 'knock out' specific genes in the enzyme and observe their effects," said Hannes braberg, a graduate student at krogan laboratory and the lead author of the paper RNAPII is so crucial that even inactivating a gene often kills cells So instead of knocking out these genes, we have mutated them The researchers then linked the newly generated map to how each RNAPII mutant can transcribe DNA into RNA, the most important function of RNAPII The team found that some of the RNAPII mutants transcribed slower than others, while others transcribed faster Further analysis revealed that there are some important similarities between slow transcribers and fast transcribers This pattern allows researchers to predict the transcription rate of each mutant Later, the team found another phenomenon related to transcription, which involves splicing Splicing refers to the process of removing specific non coding RNA segments and connecting the remaining segments together Once upon a time, scientists speculated that transcription speed was related to splicing - fast transcribers were less precise splicers, and vice versa But no one can see its behavior Therefore, Dr Guthrie used the map generated by PE map method to observe the different effects of transcription speed on splicing accuracy in real time "When transcription slows down, splicing is more efficient," Guthrie said We have seen the reverse effect of fast transcribers, which has been predicted for a long time, but has never been observed This proves once again the effectiveness of the PE map method " The method could also be used to study other enzymes, the researchers said And researchers can also apply the knowledge they have learned to understand the mechanism of mutations in proteins such as RNAPII that lead to specific disease states, and ultimately may give us the ability to correct these diseases.