Carrine E. Blank

Not so old Archaea – the antiquity of biogeochemical processes in the archaeal domain of life

Since the archaeal domain of life was first recognized, it has often been assumed that Archaea are ancient, and harbor primitive traits. In fact, the names of the major archaeal lineages reflect our assumptions regarding the antiquity of their traits. Ancestral state reconstruction and relaxed molecular clock analyses using newly articulated oxygen age constraints show that although the archaeal domain itself is old, tracing back to the Archean eon, many clades and traits within the domain are not ancient or primitive. Indeed many clades and traits, particularly in the Euryarchaeota, were inferred to be Neoproterozoic or Phanerozoic in age. Both Eury- and Crenarchaeota show increasing metabolic and physiological diversity through time. Early archaeal microbial communities were likely limited to sulfur reduction and hydrogenotrophic methanogenesis, and were confined to high-temperature geothermal environments. However, after the appearance of atmospheric oxygen, nodes containing a wide variety of traits (sulfate and thiosulfate reduction, sulfur oxidation, sulfide oxidation, aerobic respiration, nitrate reduction, mesophilic methanogenesis in sedimentary environments) appear, first in environments containing terrestrial Crenarchaeota in the Meso/Neoproterozoic followed by environments containing marine Euryarchaeota in the Neoproterozoic and Phanerozoic. This provides phylogenetic evidence for increasing complexity in the biogeochemical cycling of C, N, and S through geologic time, likely as a consequence of microbial evolution and the gradual oxygenation of various compartments within the biosphere. This work has implications not only for the large-scale evolution of microbial communities and biogeochemical processes, but also for the interpretation of microbial biosignatures in the ancient rock record.

Origin and early evolution of photosynthetic eukaryotes in freshwater environments: reinterpreting proterozoic paleobiology and biogeochemical processes in light of trait evolution.

Phylogenetic analyses were performed on concatenated data sets of 31 genes and 11,789 unambiguously alignable characters from 37 cyanobacterial and 35 chloroplast genomes. The plastid lineage emerged somewhat early in the cyanobacterial tree, at a time when Cyanobacteria were likely unicellular and restricted to freshwater ecosystems. Using relaxed molecular clocks and 22 age constraints spanning cyanobacterial and eukaryote nodes, the common ancestor to the photosynthetic eukaryotes was predicted to have also inhabited freshwater environments around the time that oxygen appeared in the atmosphere (2.0–2.3 Ga). Early diversifications within each of the three major plastid clades were also inferred to have occurred in freshwater environments, through the late Paleoproterozoic and into the middle Mesoproterozoic. The colonization of marine environments by photosynthetic eukaryotes may not have occurred until after the middle Mesoproterozoic (1.2–1.5 Ga). The evolutionary hypotheses proposed here predict that early photosynthetic eukaryotes may have never experienced the widespread anoxia or euxinia suggested to have characterized marine environments in the Paleoproterozoic to early Mesoproterozoic. It also proposes that earliest acritarchs (1.5–1.7 Ga) may have been produced by freshwater taxa. This study highlights how the early evolution of habitat preference in photosynthetic eukaryotes, along with Cyanobacteria, could have contributed to changing biogeochemical conditions on the early Earth.

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.

Phylogenetic distribution of compatible solute synthesis genes support a freshwater origin for cyanobacteria

Previous work using ancestral state reconstruction of habitat salinity preference proposed that the early cyanobacteria likely lived in a freshwater environment. The aim of this study was to test that hypothesis by performing phylogenetic analyses of the genes underlying salinity preferences in the cyanobacteria. Phylogenetic analysis of compatible solute genes shows that sucrose synthesis genes were likely ancestral in the cyanobacteria, and were also likely inherited during the cyanobacterial endosymbiosis and into the photosynthetic algae and land plants. In addition, the genes for the synthesis of compatible solutes that are necessary for survival in marine and hypersaline environments (such as glucosylglycerol, glucosylglycerate, and glycine betaine) were likely acquired independently high up (i.e., more recently) in the cyanobacterial tree. Because sucrose synthesis is strongly associated with growth in a low salinity environment, this independently supports a freshwater origin for the cyanobacteria. It is also consistent with geologic evidence showing that the early oceans were much warmer and saltier than modern oceans—sucrose synthesis alone would have been insufficient for early cyanobacteria to have colonized early Precambrian oceans that had a higher ionic strength. Indeed, the acquisition of an expanded set of new compatible solute genes may have enabled the historical colonization of marine and hypersaline environments by cyanobacteria, midway through their evolutionary history.

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.

Chitin: a potential new alternative nitrogen source for the tertiary, algal-based treatment of pulp and paper mill wastewater

Every day, pulp and paper mills in the USA discharge millions of liters of wastewater. Primary and secondary treatment of this wastewater often enriches it with phosphorus, resulting in uncontrolled eutrophication of receiving water bodies. A new method of tertiary wastewater treatment uses controlled growth of algae in a photobioreactor to sequester phosphorus into algal biomass, which is then harvested. This typically requires addition of a nitrogen fertilizer (nitrate, ammonium, or urea) to the water. We show on the laboratory scale that chitin can be used as an alternative source of nitrogen for the tertiary treatment of pulp mill wastewater using algae. We demonstrate that phosphorus can be efficiently removed from pulp wastewater using algae and chitin. Furthermore, phosphorus removal with chitin did not result in an increase in dissolved nitrogen in the wastewater because it is insoluble, unlike conventional nitrogen fertilizers. Despite its insolubility, it has recently been found that many diverse algae and cyanobacteria can use it as a source of nitrogen. Chitin has many advantages over conventional nitrogen fertilizers for use in wastewater treatment technologies. It is the second-most abundant natural polymer and is a waste product of the shellfish industry. Chitin is sustainable, inexpensive, and carbon neutral. Thus, chitin improves the sustainability and carbon footprints associated with water treatment, while the production of commercially attractive algal biomass helps to offset costs associated with the water treatment system itself.