Uptake of contaminants of emerging concern by the bivalves Anodonta californiensis and Corbicula fluminea.

Uptake of seven contaminants regularly detected in surface waters and spanning a range of hydrophobicities (log D(ow) -1 to 5) was studied for two species of freshwater bivalves, the native mussel Anodonta californiensis and the invasive clam Corbicula fluminea. Batch systems were utilized to determine compound partitioning, and flow-through systems, comparable to environmental conditions in effluent dominated surface waters, were used to determine uptake and depuration kinetics. Uptake of compounds was independent of bivalve type. Log bioconcentration factor (BCF) values were correlated with log D(ow) for nonionized compounds with the highest BCF value obtained for triclocarban (TCC). TCC concentrations were reduced in the water column due to bivalve activity. Anionic compounds with low D(ow) values, i.e., clofibric acid and ibuprofen, were not removed from water, while the organic cation propranolol showed biouptake similar to that of TCC. Batch experiments supported compound uptake patterns observed in flow-through experiments. Contaminant removal from water was observed through accumulation in tissue or settling as excreted pseudofeces or feces. The outcomes of this study indicate the potential utility of bivalve augmentation to improve water quality by removing hydrophobic trace organic compounds found in natural systems.

OrbId: Origin-based identification of microRNA targets.

MicroRNAs coordinate networks of mRNAs, but predicting specific sites of interactions is complicated by the very few bases of complementarity needed for regulation. Although efforts to characterize the specific requirements for microRNA (miR) regulation have made some advances, no general model of target recognition has been widely accepted. In this work, we describe an entirely novel approach to miR target identification. The genomic events responsible for the creation of individual miR loci have now been described with many miRs now known to have been initially formed from transposable element (TE) sequences. In light of this, we propose that limiting miR target searches to transcripts containing a miR's progenitor TE can facilitate accurate target identification. In this report we outline the methodology behind OrbId (Origin-based identification of microRNA targets). In stark contrast to the principal miR target algorithms (which rely heavily on target site conservation across species and are therefore most effective at predicting targets for older miRs), we find OrbId is particularly efficacious at predicting the mRNA targets of miRs formed more recently in evolutionary time. After defining the TE origins of > 200 human miRs, OrbId successfully generated likely target sets for 191 predominately primate-specific human miR loci. While only a handful of the loci examined were well enough conserved to have been previously evaluated by existing algorithms, we find ~80% of the targets for the oldest miR (miR-28) in our analysis contained within the principal Diana and TargetScan prediction sets. More importantly, four of the 15 OrbId miR-28 putative targets have been previously verified experimentally. In light of OrbId proving best-suited for predicting targets for more recently formed miRs, we suggest OrbId makes a logical complement to existing, conservation based, miR target algorithms.