Toxin Dynamics among Populations of the Bioluminescent HAB Species Pyrodinium bahamense from the Indian River Lagoon, FL.

Dinoflagellate species that form some of the most frequent toxic blooms are also bioluminescent, yet the two traits are rarely linked when studying bloom development and persistence. P. bahamense is a toxic, bioluminescent dinoflagellate that previously bloomed in Florida with no known record of saxitoxin (STX) production. Over the past 20 years, STX was identified in P. bahamense populations. The goal of this study was to examine toxin dynamics and associated molecular mechanisms in spatially and temporally distinct P. bahamense populations from the Indian River Lagoon, FL. SxtA4 is a key gene required for toxin biosynthesis. SxtA4 genotype analysis was performed on individual cells from multiple sites. Cell abundance, toxin quota cell-1, and sxtA4 and RubisCo (rbcL) transcript abundance were also measured. There was a significant negative correlation between cell abundance and toxin quota cell-1. While the sxtA4+ genotype was dominant at all sites, its frequency varied, but it occurred at 90-100% in many samples. The underlying mechanism for toxin decrease with increased cell abundance remains unknown. However, a strong, statistically significant negative correlation was found between stxA4 transcripts and the sxtA4/rbcL ratio, suggesting cells make fewer sxtA4 transcripts as a bloom progresses. However, the influence of sxtA4- cells must also be considered. Future plans include bioluminescence measurements, normalized to a per cell basis, at sites when toxicity is measured along with concomitant quantification of sxtA4 gene and transcript copy numbers as a means to elucidate whether changes in bloom toxicity are driven more at the genetic (emergence of sxtA4- cells) or transcriptional (repression of sxtA4 in sxtA4+ cells) level. Based on the results of this study, a model is proposed that links the combined traits of toxicity and bioluminescence in P. bahamense bloom development.

DDLm: a new dictionary definition language.

A previous paper [Spadaccini and Hall J. Chem. Inf. Model. doi:10.1021/ci300074v] details extensions to the STAR File [Hall J. Chem. Inf. Comput. Sci. 1991, 31, 326-333] syntax that will improve the exchange and archiving of electronic data. This paper describes a dictionary definition language (DDLm) for defining STAR File data items in a domain dictionary. A dictionary that defines the ontology and vocabulary of a discipline is built with DDLm, which is itself implemented in STAR, and is extensible and machine parsable. The DDLm is semantically rich and highly specific; provides strong data typing, data enumerations, and ranges; enables relationship keys between data items; and uses imbedded methods written in dREL [Spadaccini et al. J. Chem. Inf. Model. doi:10.1021/ci300076w] for data validation and evaluation and for refining data definitions. It promotes the modular definition of the discipline ontology and reuse through the ability to import definitions from other local and remote dictionaries, thus encouraging the sharing of data dictionaries within and across domains.

Extensions to the STAR File syntax.

The STAR File [Hall J. Chem. Inf. Comput. Sci. 1991, 31, 326-333; Hall and Spadaccini J. Chem. Inf. Comput. Sci. 1994, 34, 505-508] format represents a universal language adopted for electronic data and metadata exchange in the molecular-structure sciences [Hall et al. Acta Crystallogr. Sect. A 1991, 47, 655-685; International Tables for International Tables for Crystallography. Vol. G: Definition and exchange of crystallographic data; Springer: Dordrecht, The Netherlands, 2005; Allen et al. J. Chem. Inf. Comput. Sci. 1995, 35, 412-427] and used by the International Union for Crystallography for publication submissions and database depositions. This paper describes an extended STAR syntax that facilitates richer and more specific data definition and typing and a commensurate improvement in precise data description.

dREL: a relational expression language for dictionary methods.

The provision of precise metadata is an important but a largely underrated challenge for modern science [Nature 2009, 461, 145]. We describe here a dictionary methods language dREL that has been designed to enable complex data relationships to be expressed as formulaic scripts in data dictionaries written in DDLm [Spadaccini and Hall J. Chem. Inf. Model.2012 doi:10.1021/ci300075z]. dREL describes data relationships in a simple but powerful canonical form that is easy to read and understand and can be executed computationally to evaluate or validate data. The execution of dREL expressions is not a substitute for traditional scientific computation; it is to provide precise data dependency information to domain-specific definitions and a means for cross-validating data. Some scientific fields apply conventional programming languages to methods scripts but these tend to inhibit both dictionary development and accessibility. dREL removes the programming barrier and encourages the production of the metadata needed for seamless data archiving and exchange in science.