There is a lot of interesting science to write about this season, but unfortunately I have been kept mute by a number of obligations. It has been a busy semester teaching (and grading), and the holiday seasons means time with family and/or searching for gifts. More importantly, my pending nuptials have demanded time for preparation; finding the venue, getting the tux, and so forth. Although my loving fiancee handled a majority of the details, much of it was happily done together. Even happier will be the time we spend on our honeymoon in the coming few weeks, but of course blogging will not be part of my agenda on that trip.
As a teaser for the content when I return in 2015, here are some of the articles for which I had planned summary and commentary.
Ovchinnikov, S., Kamisetty, H., Baker, D. (2014) Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information eLife, 02030
This paper uses a bioinformatic approach to determine co-evolution between bacterial proteins on a large scale. This type of analysis had been done previously, but usually only with a handful of proteins at a time. Here, Baker and colleagues analyze protein-protein residue pairs that display co-evolution across all proteins in the ribosome, among other bacterial complexes, and then map these predicted interacting pairs back onto the known structures of the proteins.
A companion site to this work, gremlin.bakerlab.org, allows you to download the sequences and alignments used in the study, view the results for any two proteins analyzes, and also perform your own comparisons by inputting sequences to their server.
Gardin, J., et al (2014) Measurement of average decoding rates of the 61 sense codons in vivo. eLife 03735
During my time at Stony Brook I learnt of the work by Professors Skiena, Wimmer, and Futcher into analyzing codon bias and codon pair bias (indeed, I even took a computer science class offered by Skiena). This research was interesting, and I have since kept an eye out for further developments from this group. In this paper, they use ribosome profiling data to determine the average decoding rate at each codon, to provide some evidence for a mechanism of codon bias. Previously, slower decoding at rare codons had only been inferred based on low tRNA abundance and observations of ribosome stalling.
Venkataraman, K., Zafar, H., Karzai, W. (2014) Distinct tmRNA sequence elements facilitate RNase R engagement on rescued ribosomes for selective nonstop mRNA decay. Nulceic Acids Research, 42 (17): 11192-11202
Venkataraman, K., Guja, KE., Garcia-Diaz, M., Karzai, W. (2014) Non-stop mRNA decay: a special attribute of trans-translation mediated ribosome rescue. Front. Microbiol. 11, 5:93
These two articles are from my former colleagues at the Karzai lab, and help add insight into a complex between the ribosome and RNase-R, important during trans-translation.