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Leonard, Guy

Publications and source records attributed to Leonard, Guy.

A distinct lineage of giant viruses brings a rhodopsin photosystem to unicellular marine predators

Giant viruses are remarkable for their large genomes, often rivaling those of small bacteria, and for having genes thought exclusive to cellular life. Most isolated to date infect nonmarine protists, leaving their strategies and prevalence in marine environments largely unknown. Using eukaryotic single-cell metagenomics in the Pacific, we discovered a Mimiviridae lineage of giant viruses, which infects choanoflagellates, widespread protistan predators related to metazoans. The ChoanoVirus genomes are the largest yet from pelagic ecosystems, with 442 of 862 predicted proteins lacking known homologs. They are enriched in enzymes for modifying organic compounds, including degradation of chitin, an abundant polysaccharide in oceans, and they encode 3 divergent type-1 rhodopsins (VirR) with distinct evolutionary histories from those that capture sunlight in cellular organisms. One (VirR DTS ) is similar to the only other putative rhodopsin from a virus (PgV) with a known host (a marine alga). Unlike the algal virus, ChoanoViruses encode the entire pigment biosynthesis pathway and cleavage enzyme for producing the required chromophore, retinal. We demonstrate that the rhodopsin shared by ChoanoViruses and PgV binds retinal and pumps protons. Moreover, our 1.65-Å resolved VirR DTS crystal structure and mutational analyses exposed differences from previously characterized type-1 rhodopsins, all of which come from cellular organisms. Multiple VirR types are present in metagenomes from across surface oceans, where they are correlated with and nearly as abundant as a canonical marker gene from Mimiviridae . Our findings indicate that light-dependent energy transfer systems are likely common components of giant viruses of photosynthetic and phagotrophic unicellular marine eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

59 BASIC BIOLOGICAL SCIENCES↗