Phylogenetic trees are an important analytical tool for evaluating community diversity and evolutionary history. In the case of microorganisms, the decreasing cost of sequencing has enabled researchers to generate ever-larger sequence datasets, which in turn have begun to fill gaps in the evolutionary history of microbial groups. However, phylogenetic analyses of these types of datasets create complex trees that can be challenging to interpret. Scientific inferences made by visual inspection of phylogenetic trees can be simplified and enhanced by customizing various parts of the tree. Yet, manual customization is time-consuming and error prone, and programs designed to assist in batch tree customization often require programming experience or complicated file formats for annotation. Iroki, a user-friendly web interface for tree visualization, addresses these issues by providing automatic customization of large trees based on metadata contained in tab-separated text files. Iroki’s utility for exploring biological and ecological trends in sequencing data was demonstrated through a variety of microbial ecology applications in which trees with hundreds to thousands of leaf nodes were customized according to extensive collections of metadata. The Iroki web application and documentation are available at https://www.iroki.net or through the VIROME portal http://virome.dbi.udel.edu. Iroki’s source code is released under the MIT license and is available at https://github.com/mooreryan/iroki.

Phylogenetic trees are an important analytical tool for evaluating community diversity and evolutionary history. In the case of microorganisms, the decreasing cost of sequencing has enabled researchers to generate ever-larger sequence datasets, which in turn have begun to fill gaps in the evolutionary history of microbial groups. However, phylogenetic analyses of these types of datasets create complex trees that can be challenging to interpret. Scientific inferences made by visual inspection of phylogenetic trees can be simplified and enhanced by customizing various parts of the tree. Yet, manual customization is time-consuming and error prone, and programs designed to assist in batch tree customization often require programming experience or complicated file formats for annotation. Iroki, a user-friendly web interface for tree visualization, addresses these issues by providing automatic customization of large trees based on metadata contained in tab-separated text files. Iroki’s utility for exploring biological and ecological trends in sequencing data was demonstrated through a variety of microbial ecology applications in which trees with hundreds to thousands of leaf nodes were customized according to extensive collections of metadata. The Iroki web application and documentation are available at https://www.iroki.net or through the VIROME portal (http://virome.dbi.udel.edu). Iroki’s source code is released under the MIT license and is available at https://github.com/mooreryan/iroki.

No abstract

Ribonucleotide reductases (RNRs) are ancient enzymes that catalyze the reduction of ribonucleotides to deoxyribonucleotides. They are required for virtually all cellular life and are prominent within viral genomes. RNRs share a common ancestor and must generate a protein radical for direct ribonucleotide reduction. The mechanisms by which RNRs produce radicals are diverse and divide RNRs into three major classes and several subclasses. The diversity of radical generation methods means that cellular organisms and viruses typically contain the RNR best-suited to the environmental conditions surrounding DNA replication. However, such diversity has also fostered high rates of RNR misannotation within subject sequence databases. These misannotations have resulted in incorrect translative presumptions of RNR biochemistry and have diminished the utility of this marker gene for ecological studies of viruses. We discovered a misannotation of the RNR gene within the Prochlorococcus phage P-SSP7 genome, which caused a chain of misannotations within commonly observed RNR genes from marine virioplankton communities. These RNRs are found in marine cyanopodo- and cyanosiphoviruses and are currently misannotated as Class II RNRs, which are O2-independent and require cofactor B12. In fact, these cyanoviral RNRs are Class I enzymes that are O2-dependent and may require a di-metal cofactor made of Fe, Mn, or a combination of the two metals. The discovery of an overlooked Class I β subunit in the P-SSP7 genome, together with phylogenetic analysis of the α and β subunits confirms that the RNR from P-SSP7 is a Class I RNR. Phylogenetic and conserved residue analyses also suggest that the P-SSP7 RNR may constitute a novel Class I subclass. The reannotation of the RNR clade represented by P-SSP7 means that most lytic cyanophage contain Class I RNRs, while their hosts, B12-producing Synechococcus and Prochlorococcus, contain Class II RNRs. By using a Class I RNR, cyanophage avoid a dependence on host-produced B12, a more effective strategy for a lytic virus. The discovery of a novel RNR β subunit within cyanopodoviruses also implies that some unknown viral genes may be familiar cellular genes that are too divergent for homology-based annotation methods to identify.