Design and calibration of microarrays as universal transcriptomic environmental biosensors

Towards early-warning gene signature of Chlamydomonas reinhardtii exposed to Hg-containing complex media

The potential of using gene expression signature as a biomarker of toxicants exposure was explored in the microalga Chlamydomonas reinhardtii exposed 2 h to mercury (Hg) as inorganic mercury (IHg) and methyl mercury (MeHg) in presence of copper (Cu) and Suwannee River Humic Acid (SRHA). Total cellular Hg (THg = IHg + MeHg) decreased in presence of SRHA for 0.7 nM IHg and 0.4 nM MeHg, but increased for 70 nM IHg exposure. In mixtures of IHg + MeHg and (IHg or MeHg) + Cu, SRHA decreased THg uptake, except for 0.7 nM IHg + 0.4 nM MeHg which was unchanged (p-value>0.05). In the absence of SRHA, 0.5 μM Cu strongly decreased intracellular THg concentration for 70 nM IHg, while it had no effect for 0.7 nM IHg and 0.4 nM MeHg. The expression of single transcripts was not correlated with measured THg uptake, but a subset of 60 transcripts showed signatures specific to the exposed metal(s) and was congruent with exposure concentration. Notably, the range of fold change values of this subset correlated with THg bioaccumulation with a two-slope pattern in line with [THg]_intra/[THg]_med ratios. Gene expression signature seems a promising approach to complement chemical analyses to assess bioavailability of toxicants in presence of other metals and organic matter.

Molecular Effects, Speciation, and Competition of Inorganic and Methyl Mercury in the Aquatic Plant Elodea nuttallii

Mercury (Hg) remains hazardous in aquatic environments because of its biomagnification in food webs. Nonetheless, Hg uptake and impact in primary producers is still poorly understood. Here, we compared the cellular toxicity of inorganic and methyl Hg (IHg and MeHg, respectively) in the aquatic plant Elodea nuttallii. IHg and MeHg regulated contigs involved in similar categories (e.g., energy metabolism, development, transport, secondary metabolism), but MeHg regulated more contigs, supporting a higher molecular impact than IHg. At the organism level, MeHg induced antioxidants, while IHg decreased chlorophyll content. The uptake of Hg and expression of a subset of contigs was subsequently studied in complex media. Measured uptake pointed to a contrasted impact of cell walls and copper (Cu) on IHg and MeHg. Using a speciation modeling, differences in uptake were attributed to the differences in affinities of IHg and MeHg to organic matter in relation to Cu speciation. We also identified a distinct gene expression signature for IHg, MeHg, and Cu, further supporting different molecular toxicity of these trace elements. Our data provided fundamental knowledge on IHg and MeHg uptake in a key aquatic primary producer and confirmed the potential of transcriptomics to assess Hg exposure in environmentally realistic systems.

Machine learning approaches to investigate the impact of PCBs on the transcriptome of the common bottlenose dolphin (Tursiops truncatus)

As top-level predators, common bottlenose dolphins (Tursiops truncatus) are particularly sensitive to chemical and biological contaminants that accumulate and biomagnify in the marine food chain. This work investigates the potential use of microarray technology and gene expression profile analysis to screen common bottlenose dolphins for exposure to environmental contaminants through the immunological and/or endocrine perturbations associated with these agents. A dolphin microarray representing 24,418 unigene sequences was used to analyze blood samples collected from 47 dolphins during capture-release health assessments from five different US coastal locations (Beaufort, NC, Sarasota Bay, FL, Saint Joseph Bay, FL, Sapelo Island, GA and Brunswick, GA). Organohalogen contaminants including pesticides, polychlorinated biphenyl congeners (PCBs) and polybrominated diphenyl ether congeners were determined in blubber biopsy samples from the same animals. A subset of samples (n = 10, males; n = 8, females) with the highest and the lowest measured values of PCBs in their blubber was used as strata to determine the differential gene expression of the exposure extremes through machine learning classification algorithms. A set of genes associated primarily with nuclear and DNA stability, cell division and apoptosis regulation, intra- and extra-cellular traffic, and immune response activation was selected by the algorithm for identifying the two exposure extremes. In order to test the hypothesis that these gene expression patterns reflect PCB exposure, we next investigated the blood transcriptomes of the remaining dolphin samples using machine-learning approaches, including K-nn and Support Vector Machines classifiers. Using the derived gene sets, the algorithms worked very well (100% success rate) at classifying dolphins according to the contaminant load accumulated in their blubber. These results suggest that gene expression profile analysis may provide a valuable means to screen for indicators of chemical exposure.

A dolphin peripheral blood leukocyte cDNA microarray for studies of immune function and stress reactions

A microarray focused on stress response and immune function genes of the bottlenosed dolphin has been developed. Random expressed sequence tags (ESTs) were isolated and sequenced from two dolphin peripheral blood leukocyte (PBL) cDNA libraries biased towards T- and B-cell gene expression by stimulation with IL-2 and LPS, respectively. A total of 2784 clones were sequenced and contig analysis yielded 1343 unigenes (archived and annotated at ). In addition, 52 dolphin genes known to be important in innate and adaptive immune function and stress responses of terrestrial mammals were specifically targeted, cloned and added to the unigene collection. The set of dolphin sequences printed on a cDNA microarray comprised the 1343 unigenes, the 52 targeted genes and 2305 randomly selected (but unsequenced) EST clones. This set was printed in duplicate spots, side by side, and in two replicates per slide, such that the total number of features per microarray slide was 19,200, including controls. The dolphin arrays were validated and transcriptomic profiles were generated using PBL from a wild dolphin, a captive dolphin and dolphin skin cells. The results demonstrate that the array is a reproducible and informative tool for assessing differential gene expression in dolphin PBL and in other tissues.

Insights into the immune transcriptome of the shrimp Litopenaeus vannamei: tissue-specific expression profiles and transcriptomic responses to immune challenge

Infectious disease constitutes a major obstacle to the sustainability of shrimp aquaculture worldwide and a significant threat to natural populations of shrimp and other crustacea. The study of the shrimp immune system, including the response to viral infection, has been hampered by a relative lack of molecular genetic information and of tools suitable for high-throughput assessment of gene expression. In this report, the generation of a cDNA microarray encompassing 2,469 putative unigenes expressed in gills, circulating hemocytes, and hepatopancreas of Litopenaeus vannamei is described. The unigenes printed on the microarray were derived from the analyses of 7,021 expressed sequence tags obtained from standard cDNA libraries as well as from libraries generated by suppression subtractive hybridization, after challenging shrimp with a variety of immune stimuli. The general utility of the cDNA microarray was demonstrated by interrogating the array with labeled RNA from four different shrimp tissues (gills, hemocytes, hepatopancreas, and muscle) and by analyzing the transcriptomic response of shrimp to a lethal challenge with white spot syndrome virus. Our results indicate that white spot syndrome virus infection upregulates (in the hepatopancreas) genes encoding known and potential antimicrobial effectors, while some genes involved in protection from oxidative stress were found to be downregulated by the virus.