Lisa R. Moore

Physiology and molecular phylogeny of coexisting Prochlorococcus ecotypes.

The cyanobacterium Prochlorococcus, is the dominant oxygenic phototroph in the tropical and subtropical regions of the worlds oceans,,. It can grow at a range of depths over which light intensities can vary by up to 4 orders of magnitude. This broad depth distribution has been hypothesized to stem from the coexistence of genetically different populations adapted for growth at high- and low-light intensities. Here we report direct evidence supporting this hypothesis, which has been generated by isolating and analysing distinct co-occurring populations of Prochlorococcus at two locations in the North Atlantic. Co-isolates from the same water sample have very different light-dependent physiologies, one growing maximally at light intensities at which the other is completely photoinhibited. Despite this ecotypic differentiation, the co-isolates have 97% similarity in their 16S ribosomal RNA sequences, demonstrating that molecular microdiversity, commonly observed in microbial systems can be due to the coexistence of closely related, physiologically distinct populations. The coexistence and distribution of multiple ecotypes permits the survival of the population as a whole over a broader range of environmental conditions than would be possible for a homogeneous population.

Physiology and evolution of nitrate acquisition in Prochlorococcus.

Prochlorococcus is the numerically dominant phototroph in the oligotrophic subtropical ocean and carries out a significant fraction of marine primary productivity. Although field studies have provided evidence for nitrate uptake by Prochlorococcus, little is known about this trait because axenic cultures capable of growth on nitrate have not been available. Additionally, all previously sequenced genomes lacked the genes necessary for nitrate assimilation. Here we introduce three Prochlorococcus strains capable of growth on nitrate and analyze their physiology and genome architecture. We show that the growth of high-light (HL) adapted strains on nitrate is ∼17% slower than their growth on ammonium. By analyzing 41 Prochlorococcus genomes, we find that genes for nitrate assimilation have been gained multiple times during the evolution of this group, and can be found in at least three lineages. In low-light adapted strains, nitrate assimilation genes are located in the same genomic context as in marine Synechococcus. These genes are located elsewhere in HL adapted strains and may often exist as a stable genetic acquisition as suggested by the striking degree of similarity in the order, phylogeny and location of these genes in one HL adapted strain and a consensus assembly of environmental Prochlorococcus metagenome sequences. In another HL adapted strain, nitrate utilization genes may have been independently acquired as indicated by adjacent phage mobility elements; these genes are also duplicated with each copy detected in separate genomic islands. These results provide direct evidence for nitrate utilization by Prochlorococcus and illuminate the complex evolutionary history of this trait.

Genomes of diverse isolates of the marine cyanobacterium Prochlorococcus

The marine cyanobacterium Prochlorococcus is the numerically dominant photosynthetic organism in the oligotrophic oceans, and a model system in marine microbial ecology. Here we report 27 new whole genome sequences (2 complete and closed; 25 of draft quality) of cultured isolates, representing five major phylogenetic clades of Prochlorococcus. The sequenced strains were isolated from diverse regions of the oceans, facilitating studies of the drivers of microbial diversity—both in the lab and in the field. To improve the utility of these genomes for comparative genomics, we also define pre-computed clusters of orthologous groups of proteins (COGs), indicating how genes are distributed among these and other publicly available Prochlorococcus genomes. These data represent a significant expansion of Prochlorococcus reference genomes that are useful for numerous applications in microbial ecology, evolution and oceanography.

Next-generation phenomics for the Tree of Life

The phenotype represents a critical interface between the genome and the environment in which organisms live and evolve. Phenotypic characters also are a rich source of biodiversity data for tree building, and they enable scientists to reconstruct the evolutionary history of organisms, including most fossil taxa, for which genetic data are unavailable. Therefore, phenotypic data are necessary for building a comprehensive Tree of Life. In contrast to recent advances in molecular sequencing, which has become faster and cheaper through recent technological advances, phenotypic data collection remains often prohibitively slow and expensive. The next-generation phenomics project is a collaborative, multidisciplinary effort to leverage advances in image analysis, crowdsourcing, and natural language processing to develop and implement novel approaches for discovering and scoring the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and to enable rapid advances in constructing the Tree of Life. Our goal is to assemble large phenomic datasets built using new methods and to provide the public and scientific community with tools for phenomic data assembly that will enable rapid and automated study of phenotypes across the Tree of Life.

Effects of phosphorus starvation versus limitation on the marine cyanobacterium Prochlorococcus MED4 II: gene expression

Phosphorus (P) availability drives niche differentiation in the most abundant phytoplankter in the oceans, the marine cyanobacterium Prochlorococcus. We compared the molecular response of Prochlorococcus strain MED4 to P starvation in batch culture to P-limited growth in chemostat culture. We also identified an outer membrane porin, PMM0709, which may allow transport of organic phosphorous compounds, rather than phosphate as previously suggested. The expression of three P uptake genes, pstS, the high-affinity phosphate-binding component of the phosphate transporter, phoA, an alkaline phosphatase, and porin PMM0709, were strongly upregulated (between 10- and 700-fold) under both P starvation and limitation. pstS exhibits high basal expression under P-replete conditions and is likely necessary for P uptake regardless of P availability. A P-stress regulatory gene, ptrA, was upregulated in response to both P starvation and limitation although a second regulatory gene, phoB, was not. Elevated expression levels (> 10-fold) of phoR, a P-sensing histidine kinase, were only observed under conditions of P limitation. We suggest Prochlorococcus in P-limited systems are physiologically distinct from cells subjected to abrupt P depletion. Detection of expression of both pstS and phoR in field populations will enable discernment of the present P status of Prochlorococcus in the oligotrophic oceans.

More mixotrophy in the marine microbial mix

Since the turn of the century, the paradigm of the marine microbial assemblage being composed primarily of photoautotrophs and chemoheterotrophs is shifting and challenging our understanding of how the microbial diversity contributes to the flow of energy, carbon, and other nutrients in the oceans. In PNAS, Munoz-Marin et al. (1) add another piece to the puzzle by demonstrating that natural populations of Prochlorococcus, the smallest and most abundant oxygenic phototroph in the oceans, can take up glucose in nanomolar amounts and has a gene (Pro1404) that codes for a sugar transporter.

MicrO: An ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions

BackgroundMicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature.ResultsMicrO currently has ~14550 classes (~2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by ~24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO’s Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology.ConclusionsBy connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we intend MicrO to be a powerful new tool to increase the computing power of bioinformatics tools such as the automated text mining of prokaryotic taxonomic descriptions using natural language processing. We also intend MicrO to support the development of new bioinformatics tools that aim to develop new connections between microbial phenotypes and genotypes (i.e., the gene content in genomes). Future ontology development will include incorporation of pathogenic phenotypes and prokaryotic habitats.

Microbial phenomics information extractor (MicroPIE): a natural language processing tool for the automated acquisition of prokaryotic phenotypic characters from text sources

BackgroundThe large-scale analysis of phenomic data (i.e., full phenotypic traits of an organism, such as shape, metabolic substrates, and growth conditions) in microbial bioinformatics has been hampered by the lack of tools to rapidly and accurately extract phenotypic data from existing legacy text in the field of microbiology. To quickly obtain knowledge on the distribution and evolution of microbial traits, an information extraction system needed to be developed to extract phenotypic characters from large numbers of taxonomic descriptions so they can be used as input to existing phylogenetic analysis software packages.ResultsWe report the development and evaluation of Microbial Phenomics Information Extractor (MicroPIE, version 0.1.0). MicroPIE is a natural language processing application that uses a robust supervised classification algorithm (Support Vector Machine) to identify characters from sentences in prokaryotic taxonomic descriptions, followed by a combination of algorithms applying linguistic rules with groups of known terms to extract characters as well as character states. The input to MicroPIE is a set of taxonomic descriptions (clean text). The output is a taxon-by-character matrix—with taxa in the rows and a set of 42 pre-defined characters (e.g., optimum growth temperature) in the columns. The performance of MicroPIE was evaluated against a gold standard matrix and another student-made matrix. Results show that, compared to the gold standard, MicroPIE extracted 21 characters (50%) with a Relaxed F1 score > 0.80 and 16 characters (38%) with Relaxed F1 scores ranging between 0.50 and 0.80. Inclusion of a character prediction component (SVM) improved the overall performance of MicroPIE, notably the precision. Evaluated against the same gold standard, MicroPIE performed significantly better than the undergraduate students.ConclusionMicroPIE is a promising new tool for the rapid and efficient extraction of phenotypic character information from prokaryotic taxonomic descriptions. However, further development, including incorporation of ontologies, will be necessary to improve the performance of the extraction for some character types.