A computational model of the hypothalamic - pituitary - gonadal axis in female fathead minnows (Pimephales promelas) exposed to 17α-ethynylestradiol and 17β-trenbolone

© 2011 Li et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Endocrine disrupting chemicals (e.g., estrogens, androgens and their mimics) are known to affect reproduction in fish. 17α-ethynylestradiol is a synthetic estrogen used in birth control pills. 17β-trenbolone is a relatively stable metabolite of trenbolone acetate, a synthetic androgen used as a growth promoter in livestock. Both 17α-ethynylestradiol and 17β-trenbolone have been found in the aquatic environment and affect fish reproduction. In this study, we developed a physiologically-based computational model for female fathead minnows (FHM, Pimephales promelas), a small fish species used in ecotoxicology, to simulate how estrogens (i.e., 17α-ethynylestradiol) or androgens (i.e., 17β-trenbolone) affect reproductive endpoints such as plasma concentrations of steroid hormones (e.g., 17β-estradiol and testosterone) and vitellogenin (a precursor to egg yolk proteins). Results - Using Markov Chain Monte Carlo simulations, the model was calibrated with data from unexposed, 17α-ethynylestradiol-exposed, and 17β-trenbolone-exposed FHMs. Four Markov chains were simulated, and the chains for each calibrated model parameter (26 in total) converged within 20,000 iterations. With the converged parameter values, we evaluated the model's predictive ability by simulating a variety of independent experimental data. The model predictions agreed with the experimental data well. Conclusions - The physiologically-based computational model represents the hypothalamic-pituitary-gonadal axis in adult female FHM robustly. The model is useful to estimate how estrogens (e.g., 17α-ethynylestradiol) or androgens (e.g., 17β-trenbolone) affect plasma concentrations of 17β-estradiol, testosterone and vitellogenin, which are important determinants of fecundity in fish.The Medical Research Foundation of Oregon, U.S. Environmental Protection Agency, and the National Center for Computational Toxicology of the EPA Office of Research and Development

Risk-based prioritization of pharmaceuticals in the natural environment in Iraq

Numerous studies have demonstrated the occurrence of pharmaceuticals in the natural environment, raising concerns about their impact on non-target organisms or human health. One region where little is known about the exposure and effects of pharmaceuticals in the environment is Iraq. Due to the high number of pharmaceuticals used by the public health sector in Iraq (hospitals and care centres) and distributed over the counter, there is a need for a systematic approach for identifying substances that should be monitored in the environment in Iraq and assessed in terms of environmental risk. In this study, a risk-based prioritization approach was applied to 99 of the most dispensed pharmaceuticals in three Iraqi cities, Baghdad, Mosul and Basrah. Initially, information on the amounts of pharmaceuticals used in Iraq was obtained. The top used medicines were found to be paracetamol, amoxicillin and metformin with total annual consumption exceeding 1000 tonnes per year. Predicted environmental concentrations (PECs) and predicted no-effect concentrations (PNECs), derived from ecotoxicological end-points and effects related to the therapeutic mode of action, were then used to rank the pharmaceuticals in terms of risks to different environmental compartments. Active pharmaceutical ingredients used as antibiotics, antidepressants and analgesics were identified as the highest priority in surface water, sediment and the terrestrial environment. Antibiotics were also prioritized according to their susceptibility to kill or inhibit the growth of bacteria or to accelerate the evolution and dissemination of antibiotic-resistant genes in water. Future work will focus on understanding the occurrence, fate and effects of some of highly prioritized substances in the environment

Identifying and Characterizing a Novel Protein Kinase STK35L1 and Deciphering Its Orthologs and Close-Homologs in Vertebrates

The human kinome containing 478 eukaryotic protein kinases has over 100 uncharacterized kinases with unknown substrates and biological functions. The Ser/Thr kinase 35 (STK35, Clik1) is a member of the NKF 4 (New Kinase Family 4) in the kinome with unknown substrates and biological functions. Various high throughput studies indicate that STK35 could be involved in various human diseases such as colorectal cancer and malaria. In this study, we found that the previously published coding sequence of the STK35 gene is incomplete. The newly identified sequence of the STK35 gene codes for a protein of 534 amino acids with a N-terminal elongation of 133 amino acids. It has been designated as STK35L (STK35 long). Since it is the first of further homologous kinases we termed it as STK35L1. The STK35L1 protein (58 kDa on SDS-PAGE), but not STK35 (44 kDa), was found to be expressed in all human cells studied (endothelial cells, HeLa, and HEK cells) and was down-regulated after silencing with specific siRNA. EGFP-STK35L1 was localized in the nucleus and the nucleolus. By combining syntenic and gene structure pattern data and homology searches, two further STK35L1 homologs, STK35L2 (previously known as PDIK1L) and STK35L3, were found. All these protein kinase homologs were conserved throughout the vertebrates. The STK35L3 gene was specifically lost during placental mammalian evolution. Using comparative genomics, we have identified orthologous sets of these three protein kinases genes and their possible ancestor gene in two sea squirt genomes. We found the full-length coding sequence of the STK35 gene and termed it as STK35L1. We identified a new third STK35-like gene, STK35L3, in vertebrates and a possible ancestor gene in sea squirt genome. This study will provide a comprehensive platform to explore the role of STK35L kinases in cell functions and human diseases

Pharmaceutical Formulation Facilities as Sources of Opioids and Other Pharmaceuticals to Wastewater Treatment Plant Effluents

Facilities involved in the manufacture of pharmaceutical products are an under-investigated source of pharmaceuticals to the environment. Between 2004 and 2009, 35 to 38 effluent samples were collected from each of three wastewater treatment plants (WWTPs) in New York and analyzed for seven pharmaceuticals including opioids and muscle relaxants. Two WWTPs (NY2 and NY3) receive substantial flows (>20% of plant flow) from pharmaceutical formulation facilities (PFF) and one (NY1) receives no PFF flow. Samples of effluents from 23 WWTPs across the United States were analyzed once for these pharmaceuticals as part of a national survey. Maximum pharmaceutical effluent concentrations for the national survey and NY1 effluent samples were generally <1 μg/L. Four pharmaceuticals (methadone, oxycodone, butalbital, and metaxalone) in samples of NY3 effluent had median concentrations ranging from 3.4 to >400 μg/L. Maximum concentrations of oxycodone (1700 μg/L) and metaxalone (3800 μg/L) in samples from NY3 effluent exceeded 1000 μg/L. Three pharmaceuticals (butalbital, carisoprodol, and oxycodone) in samples of NY2 effluent had median concentrations ranging from 2 to 11 μg/L. These findings suggest that current manufacturing practices at these PFFs can result in pharmaceuticals concentrations from 10 to 1000 times higher than those typically found in WWTP effluents

Microarray-Based Analysis of Differential Gene Expression between Infective and Noninfective Larvae of Strongyloides stercoralis

Strongyloides stercoralis is a soil-transmitted helminth that affects an estimated 30–100 million people worldwide. Chronically infected persons who are exposed to corticosteroids can develop disseminated disease, which carries a high mortality (87–100%) if untreated. Despite this, little is known about the fundamental biology of this parasite, including the features that enable infection. We developed the first DNA microarray for this parasite and used it to compare infective third-stage larvae (L3i) with non-infective first stage larvae (L1). Using this method, we identified 935 differentially expressed genes. Functional characterization of these genes revealed L3i biased expression of heat shock proteins and genes with products that have previously been shown to be immunoreactive in infected humans. Genes putatively involved in transcription were found to have L1 biased expression. Potential chemotherapeutic and vaccine targets such as far-1, ucr 2.1 and hsp-90 were identified for further study

Environmental Emission of Pharmaceuticals from Wastewater Treatment Plants in the USA

The residual drugs, drug bioconjugates, and their metabolites, mostly from human and veterinary usage, are routinely flushed down the drain, and enter wastewater treatment plants (WWTP). Increasing population, excessive use of allopathic medicine, continual introduction of novel drugs, and existing inefficient wastewater treatment processes result in the discharge of large volumes of pharmaceuticals and their metabolites from the WWTPs into the environment. The effluent from the WWTPs globally contaminate ~25% of rivers and the lakes. Pharmaceuticals in the environment, as contaminants of emerging concerns, behave as pseudo-persistent despite their relatively short environmental half-lives in the environment. Therefore, residual levels of pharmaceuticals in the environment not only pose a threat to the wildlife but also affect human health through contaminated food and drinking water. This chapter highlights WWTPs as point-sources of their environmental emissions and various effects on the aquatic and terrestrial ecosystem

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

BACKGROUND: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multi-domain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. METHODOLOGY: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. CONCLUSIONS: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multi-domain architecture

A batch correction method for liquid chromatography–mass spectrometry data that does not depend on quality control samples

The need for reproducible and comparable results is of increasing importance in non-targeted metabolomic studies, especially when differences between experimental groups are small. Liquid chromatography– mass spectrometry spectra are often acquired batch-wise so that necessary calibrations and cleaning of the instrument can take place. However this may introduce further sources of variation, such as differences in the conditions under which the acquisition of individual batches is performed. Quality control (QC) samples are frequently employed as a means of both judging and correcting this variation. Here we show that the use of QC samples can lead to problems. The non-linearity of the response can result in substantial differences between the recorded intensities of the QCs and experimental samples, making the required adjustment difficult to predict. Furthermore, changes in the response profile between one QC interspersion and the next cannot be accounted for and QC based correction can actually exacerbate the problems by introducing artificial differences. ‘‘Background correction’’ methods utilise all experimental samples to estimate the variation over time rather than relying on the QC samples alone. We compare non-QC correction methods with standard QC correction and demonstrate their success in reducing differences between replicate samples and their potential to highlight differences between experimental groups previously hidden by instrumental variation