Merino, N. | Search bioRxiv

bioRxiv2019

Structure of the processive human Pol δ holoenzyme

In eukaryotes, DNA polymerase {delta} (Pol {delta}) bound to the proliferating cell nuclear antigen (PCNA) replicates the lagging strand and cooperates with flap endonuclease 1 (FEN1) to process the Okazaki fragments for their ligation. We present the high-resolution cryo-EM structure of the human processive Pol {delta}-DNA-PCNA complex in the absence and presence of FEN1. Pol {delta} is anchored to one of the three PCNA monomers through the C-terminal domain of the catalytic subunit. The catalytic core sits on top of PCNA in an open configuration while the regulatory subunits project laterally. This arrangement allows PCNA to thread and stabilize the DNA exiting the catalytic cleft and recruit FEN1 to one unoccupied monomer in a toolbelt fashion. Alternative holoenzyme conformations reveal important functional interactions that maintain PCNA orientation during synthesis. This work sheds light on the structural basis of Pol {delta}s activity in replicating the human genome.

biochemistry↗

bioRxiv2019

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms, and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earths crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and the associated surge in publicly-available sequence data has now made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition and utilization in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) that is based on genes related to iron acquisition, storage, and reduction/oxidation. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate the provided datasets with respect to iron-related genes and gene clusters. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenies database will be maintained and continually-updated as new genetic markers are discovered. FeGenie is freely available: https://github.com/Arkadiy-Garber/FeGenie.

bioinformatics↗