Degradation of newly synthesized polypeptides by ribosome-associated RACK1/c-Jun N-terminal kinase/eukaryotic elongation factor 1A2 complex.

Folding of newly synthesized polypeptides (NSPs) into functional proteins is a highly regulated process. Rigorous quality control ensures that NSPs attain their native fold during or shortly after completion of translation. Nonetheless, signaling pathways that govern the degradation of NSPs in mammals remain elusive. We demonstrate that the stress-induced c-Jun N-terminal kinase (JNK) is recruited to ribosomes by the receptor for activated protein C kinase 1 (RACK1). RACK1 is an integral component of the 40S ribosome and an adaptor for protein kinases. Ribosome-associated JNK phosphorylates the eukaryotic translation elongation factor 1A isoform 2 (eEF1A2) on serines 205 and 358 to promote degradation of NSPs by the proteasome. These findings establish a role for a RACK1/JNK/eEF1A2 complex in the quality control of NSPs in response to stress.

An entropy-based approach for the identification of phylogenetically informative genomic regions of Papillomavirus.

The papillomaviruses form a highly diverse group that infect mammals, birds and reptiles. We know little about their genetic diversity and therefore the evolutionary mechanisms that drive the diversity of these viruses. Genomic sequences of papillomaviruses are highly divergent and so it is important to develop methods that select the most phylogenetic informative sites. This study aimed at making use of a novel approach based on entropy to select suitable genomic regions from which to infer the phylogeny of papillomavirus. Comparative genomic analyzes were performed to assess the genetic variability of each gene of Papillomaviridae family members. Regions with low entropy were selected to reconstruct papillomavirus phylogenetic trees based on four different methods. This methodology allowed us to identify regions that are conserved among papillomaviruses that infect different hosts. This is important because, despite the huge variation among all papillomaviruses genomes, we were able to find regions that are clearly shared among them, presenting low complexity levels of information from which phylogenetic predictions can be made. This approach allowed us to obtain robust topologies from relatively small datasets. The results indicate that the entropy approach can successfully select regions of the genome that are good markers from which to infer phylogenetic relationships, using less computational time, making the estimation of large phylogenies more accessible.