Characterization of an Oct1 orthologue in the channel catfish, Ictalurus punctatus: A negative regulator of immunoglobulin gene transcription?

BACKGROUND: The enhancer (Eμ3') of the immunoglobulin heavy chain locus (IGH) of the channel catfish (Ictalurus punctatus) has been well characterized. The functional core region consists of two variant Oct transcription factor binding octamer motifs and one E-protein binding μE5 site. An orthologue to the Oct2 transcription factor has previously been cloned in catfish and is a functionally active transcription factor. This study was undertaken to clone and characterize the Oct1 transcription factor, which has also been shown to be important in driving immunoglobulin gene transcription in mammals. RESULTS: An orthologue of Oct1, a POU family transcription factor, was cloned from a catfish macrophage cDNA library. The inferred amino acid sequence of the catfish Oct1, when aligned with other vertebrate Oct1 sequences, revealed clear conservation of structure, with the POU specific subdomain of catfish Oct1 showing 96% identity to that of mouse Oct1. Expression of Oct1 was observed in clonal T and B cell lines and in all tissues examined. Catfish Oct1, when transfected into both mammalian (mouse) and catfish B cell lines, unexpectedly failed to drive transcription from three different octamer-containing reporter constructs. These contained a trimer of octamer motifs, a fish V(H )promoter, and the core region of the catfish Eμ3' IGH enhancer, respectively. This failure of catfish Oct1 to drive transcription was not rescued by human BOB.1, a co-activator of Oct transcription factors that stimulates transcription driven by catfish Oct2. When co-transfected with catfish Oct2, Oct1 reduced Oct2 driven transcriptional activation. Electrophoretic mobility shift assays showed that catfish Oct1 (native or expressed in vitro) bound both consensus and variant octamer motifs. Putative N- and C-terminal activation domains of Oct1, when fused to a Gal4 DNA binding domain and co-transfected with Gal4-dependent reporter constructs were transcriptionally inactive, which may be due in part to a lack of residues associated with activation domain function. CONCLUSION: An orthologue to mammalian Oct1 has been found in the catfish. It is similar to mammalian Oct1 in structure and expression. However, these results indicate that the physiological functions of catfish Oct1 differ from those of mammalian Oct1 and include negative regulation of transcription

Optimal cDNA microarray design using expressed sequence tags for organisms with limited genomic information

BACKGROUND: Expression microarrays are increasingly used to characterize environmental responses and host-parasite interactions for many different organisms. Probe selection for cDNA microarrays using expressed sequence tags (ESTs) is challenging due to high sequence redundancy and potential cross-hybridization between paralogous genes. In organisms with limited genomic information, like marine organisms, this challenge is even greater due to annotation uncertainty. No general tool is available for cDNA microarray probe selection for these organisms. Therefore, the goal of the design procedure described here is to select a subset of ESTs that will minimize sequence redundancy and characterize potential cross-hybridization while providing functionally representative probes. RESULTS: Sequence similarity between ESTs, quantified by the E-value of pair-wise alignment, was used as a surrogate for expected hybridization between corresponding sequences. Using this value as a measure of dissimilarity, sequence redundancy reduction was performed by hierarchical cluster analyses. The choice of how many microarray probes to retain was made based on an index developed for this research: a sequence diversity index (SDI) within a sequence diversity plot (SDP). This index tracked the decreasing within-cluster sequence diversity as the number of clusters increased. For a given stage in the agglomeration procedure, the EST having the highest similarity to all the other sequences within each cluster, the centroid EST, was selected as a microarray probe. A small dataset of ESTs from Atlantic white shrimp (Litopenaeus setiferus) was used to test this algorithm so that the detailed results could be examined. The functional representative level of the selected probes was quantified using Gene Ontology (GO) annotations. CONCLUSIONS: For organisms with limited genomic information, combining hierarchical clustering methods to analyze ESTs can yield an optimal cDNA microarray design. If biomarker discovery is the goal of the microarray experiments, the average linkage method is more effective, while single linkage is more suitable if identification of physiological mechanisms is more of interest. This general design procedure is not limited to designing single-species cDNA microarrays for marine organisms, and it can equally be applied to multiple-species microarrays of any organisms with limited genomic information

Marine Genomics: A clearing-house for genomic and transcriptomic data of marine organisms

BACKGROUND: The Marine Genomics project is a functional genomics initiative developed to provide a pipeline for the curation of Expressed Sequence Tags (ESTs) and gene expression microarray data for marine organisms. It provides a unique clearing-house for marine specific EST and microarray data and is currently available at . DESCRIPTION: The Marine Genomics pipeline automates the processing, maintenance, storage and analysis of EST and microarray data for an increasing number of marine species. It currently contains 19 species databases (over 46,000 EST sequences) that are maintained by registered users from local and remote locations in Europe and South America in addition to the USA. A collection of analysis tools are implemented. These include a pipeline upload tool for EST FASTA file, sequence trace file and microarray data, an annotative text search, automated sequence trimming, sequence quality control (QA/QC) editing, sequence BLAST capabilities and a tool for interactive submission to GenBank. Another feature of this resource is the integration with a scientific computing analysis environment implemented by MATLAB. CONCLUSION: The conglomeration of multiple marine organisms with integrated analysis tools enables users to focus on the comprehensive descriptions of transcriptomic responses to typical marine stresses. This cross species data comparison and integration enables users to contain their research within a marine-oriented data management and analysis environment

Modelling interactions of acid–base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology 155 (2010): 341-349, doi:10.1016/j.cbpa.2009.11.019.Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001 – 0.400 μM), Zn (0.001 – 3.059 μM) or Cu (0.002 – 0.787 μM), either alone or in combination for 1 to 27 days. We measured indicators of acid-base balance (hemolymph pH and total CO2), gas exchange (Po2), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid-base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.This study was supported by NOAA’s Center of Excellence in Oceans and Human Health at HML and the National Science Foundation

Selective and Irreversible Inhibitors of Mosquito Acetylcholinesterases for Controlling Malaria and Other Mosquito-Borne Diseases

New insecticides are urgently needed because resistance to current insecticides allows resurgence of disease-transmitting mosquitoes while concerns for human toxicity from current compounds are growing. We previously reported the finding of a free cysteine (Cys) residue at the entrance of the active site of acetylcholinesterase (AChE) in some insects but not in mammals, birds, and fish. These insects have two AChE genes (AP and AO), and only AP-AChE carries the Cys residue. Most of these insects are disease vectors such as the African malaria mosquito (Anopheles gambiae sensu stricto) or crop pests such as aphids. Recently we reported a Cys-targeting small molecule that irreversibly inhibited all AChE activity extracted from aphids while an identical exposure caused no effect on the human AChE. Full inhibition of AChE in aphids indicates that AP-AChE contributes most of the enzymatic activity and suggests that the Cys residue might serve as a target for developing better aphicides. It is therefore worth investigating whether the Cys-targeting strategy is applicable to mosquitocides. Herein, we report that, under conditions that spare the human AChE, a methanethiosulfonate-containing molecule at 6 µM irreversibly inhibited 95% of the AChE activity extracted from An. gambiae s. str. and >80% of the activity from the yellow fever mosquito (Aedes aegypti L.) or the northern house mosquito (Culex pipiens L.) that is a vector of St. Louis encephalitis. This type of inhibition is fast (∼30 min) and due to conjugation of the inhibitor to the active-site Cys of mosquito AP-AChE, according to our observed reactivation of the methanethiosulfonate-inhibited AChE by 2-mercaptoethanol. We also note that our sulfhydryl agents partially and irreversibly inhibited the human AChE after prolonged exposure (>4 hr). This slow inhibition is due to partial enzyme denaturation by the inhibitor and/or micelles of the inhibitor, according to our studies using atomic force microscopy, circular dichroism spectroscopy, X-ray crystallography, time-resolved fluorescence spectroscopy, and liquid chromatography triple quadrupole mass spectrometry. These results support our view that the mosquito-specific Cys is a viable target for developing new mosquitocides to control disease vectors and to alleviate resistance problems with reduced toxicity toward non-target species

Health status, infection and disease in California sea lions (\u3ci\u3eZalophus californianus\u3c/i\u3e) studied using a canine microarray platform and machine-learning approaches

Conservation biologists face many challenges in assessing health, immune status and infectious diseases in protected species. These challenges include unpredictable sample populations, diverse genetic and environmental backgrounds of the animals, as well as the practical, legal and ethical issues involved in experimentation. The use of whole genome scale transcriptomics with animal samples obtained in a minimally invasive manner is an approach that shows promise for health assessment. In this study we assessed the utility of a microarray to identify changes in gene expression predictive of health status by interrogating blood samples from California sea lions (Zalophus californianus) in rehabilitation. A custom microarray was developed from the commercially available dog microarray (Canis familiaris) by selecting probes that demonstrated reliable cross-hybridization with RNA in sea lion blood. This custom microarray was used for the analysis of RNA from 73 sea lion blood samples, from animals with a broad spectrum of health changes. Both traditional classifying techniques and newer artificial neural network approaches correctly classified sea lions with respect to health status, primarily distinguishing between leptospirosis infection and domoic acid exposure. Real time PCR validation for a small set of genes, followed by sequencing, showed good correlation with array results and high identity (96–98%) between the dog and sea lion sequences. This approach to health status classification shows promise for disease identification in a clinical setting, and assessment of health status of wildlife