Phylogenetic relationships within Echinococcus and Taenia tapeworms (Cestoda: Taeniidae): an inference from nuclear protein-coding genes

The family Taeniidae of tapeworms is composed of two genera, Echinococcus and Taenia, which obligately parasitize mammals including humans. Inferring phylogeny via molecular markers is the only way to trace back their evolutionary histories. However, molecular dating approaches are lacking so far. Here we established new markers from nuclear protein-coding genes for RNA polymerase II second largest subunit (rpb2), phosphoenolpyruvate carboxykinase (pepck) and DNA polymerase delta (pold). Bayesian inference and maximum likelihood analyses of the concatenated gene sequences allowed us to reconstruct phylogenetic trees for taeniid parasites. The tree topologies clearly demonstrated that Taenia is paraphyletic and that the clade of Echinococcus oligarthrus and Echinococcusvogeli is sister to all other members of Echinococcus. Both species are endemic in Central and South America, and their definitive hosts originated from carnivores that immigrated from North America after the formation of the Panamanian land bridge about 3 million years ago (Ma). A time-calibrated phylogeny was estimated by a Bayesian relaxed-clock method based on the assumption that the most recent common ancestor of E. oligarthrus and E. vogeli existed during the late Pliocene (3.0 Ma). The results suggest that a clade of Taenia including human-pathogenic species diversified primarily in the late Miocene (11.2 Ma), whereas Echinococcus started to diversify later, in the end of the Miocene (5.8 Ma). Close genetic relationships among the members of Echinococcus imply that the genus is a young group in which speciation and global radiation occurred rapidly.     

Autism and intellectual disability are differentially related to sociodemographic background at birth

Background

Research findings investigating the sociodemographics of autism spectrum disorder (ASD) have been inconsistent and rarely considered the presence of intellectual disability (ID).

Methods

We used population data on Western Australian singletons born from 1984 to 1999 (n = 398,353) to examine the sociodemographic characteristics of children diagnosed with ASD with or without ID, or ID without ASD compared with non-affected children.

Results

The profiles for the four categories examined, mild-moderate ID, severe ID, ASD without ID and ASD with ID varied considerably and we often identified a gradient effect where the risk factors for mild-moderate ID and ASD without ID were at opposite extremes while those for ASD with ID were intermediary. This was demonstrated clearly with increased odds of ASD without ID amongst older mothers aged 35 years and over (odds ratio (OR) = 1.69 [CI: 1.18, 2.43]), first born infants (OR = 2.78; [CI: 1.67, 4.54]), male infants (OR = 6.57 [CI: 4.87, 8.87]) and increasing socioeconomic advantage. In contrast, mild-moderate ID was associated with younger mothers aged less than 20 years (OR = 1.88 [CI: 1.57, 2.25]), paternal age greater than 40 years (OR = 1.59 [CI: 1.36, 1.86]), Australian-born and Aboriginal mothers (OR = 1.60 [CI: 1.41, 1.82]), increasing birth order and increasing social disadvantage (OR = 2.56 [CI: 2.27, 2.97]). Mothers of infants residing in regional or remote areas had consistently lower risk of ASD or ID and may be linked to reduced access to services or under-ascertainment rather than a protective effect of location.

Conclusions

The different risk profiles observed between groups may be related to aetiological differences or ascertainment factors or both. Untangling these pathways is challenging but an urgent public health priority in view of the supposed autism epidemic.     

Accuracy and precision of gait events derived from motion capture in horses during walk and trot

This study aimed to create an evidence base for detection of stance-phase timings from motion capture in horses. The objective was to compare the accuracy (bias) and precision (SD) for five published algorithms for the detection of hoof-on and hoof-off using force plates as the reference standard.     

Disentangling the drivers of continental mammalian endemism

Endemic species and species with small ranges are ecologically and evolutionarily distinct and are vulnerable to extinction. Determining which abiotic and biotic factors structure patterns of endemism on continents can advance our understanding of global biogeographic processes, but spatial patterns of mammalian endemism have not yet been effectively predicted and reconstructed. Using novel null model techniques, we reconstruct trends in mammalian endemism and describe the isolated and combined effects of physiographic, ecological, and evolutionary factors on endemism. We calculated weighted endemism for global continental ecoregions and compared the spatial distribution of endemism to niche-based, geographic null models of endemism. These null models distribute species randomly across continents, simulating their range sizes from their degree of climatic specialization. They isolate the effects of physiography (topography and climate) and species richness on endemism. We then ran linear and structural models to determine how topography and historical climate stability influence endemism. The highest rates of mammalian endemism were found in topographically rough, climatically stable ecoregions with many species. The null model that isolated physiography did not closely approximate the observed distribution of endemism (r² = .09), whereas the null model that incorporated both physiography and species richness did (r² = .59). The linear models demonstrate that topography and climatic stability both influenced endemism values, but that average climatic niche breadth was not highly correlated with endemism. Climate stability and topography both influence weighted endemism in mammals, but the spatial distribution of mammalian endemism is driven by a combination of physiography and species richness. Despite its relationship to individual range size, average climate niche breadth has only a weak influence on endemism. The results highlight the importance of historical biogeographic processes (e.g. centers of speciation) and geography in driving endemism patterns, and disentangle the mechanisms structuring species ranges worldwide.     

Dasatinib, imatinib and staurosporine capture compounds - Complementary tools for the profiling of kinases by Capture Compound Mass Spectrometry (CCMS)

Capture Compound Mass Spectrometry (CCMS) is a platform technology for the functional isolation of subproteomes. Here we report the synthesis of two new kinase Capture Compounds (CCs) based on the tyrosine-kinase specific inhibitors dasatinib and imatinib and compare their interaction profiles to that of our previously reported staurosporine-CCs. CCs are tri-functional molecules: they comprise a sorting function (e.g. the small molecule or drug of interest) which interacts with target proteins, a photo-activatable reactivity function to covalently trap the interacting proteins, and a sorting function to isolate the CC-protein conjugates from complex biological samples for protein identification by liquid chromatography/mass spectrometry (LC-MS/MS). We present data of CCMS experiments from human HepG2 cells and compare the profiles of the kinases isolated with dasatinib, imatinib and staurosporine CC, respectively. Dasatinib and imatinib have a more selective kinase binding profile than staurosporine. Moreover, the new CCs allow isolation and identification of additional kinases, complementing the staurosporine CC. The family of kinase CCs will be a valuable tool for the proteomic profiling of this important protein class. Besides sets of expected kinases we identified additional specific interactors; these off-targets may be of relevance in the view of the pharmacological profile of dasatinib and imatinib.     

A Label-free Selected Reaction Monitoring Workflow Identifies a Subset of Pregnancy Specific Glycoproteins as Potential Predictive Markers of Early-onset Pre-eclampsia

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE.To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of “candidate” biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.The identification of clinically relevant plasma biomarkers with diagnostic and/or predictive value continues to challenge the proteomics field. Whereas once the biomarker pipeline was described as a two part discovery and validation process, there is increasing consensus that an intermediate step is required in which the proteins identified in the discovery phase are technically verified in 50 to 200 samples. This verification step identifies false positives from the discovery phase and allows prioritization of proteins to be taken into large-scale clinical validation studies (1). Although commercial ELISA kits may be used in this phase, these are unavailable for many proteins, are expensive, and may lack specificity. In addition, sample requirements may be too high to perform ELISA on all candidates, especially if many proteins are identified as potential markers by low powered, high penetration discovery workflows.Selected reaction monitoring (SRM)¹ mass spectrometry has great potential as an alternative verification method (2–6) as it can be multiplexed, customized, and is highly specific. This potential has not been exploited to date, largely because of technical issues developing a low-cost, reproducible workflow encompassing plasma and serum preparation and LC/MS analysis with the capability to measure protein levels reproducible in hundreds of samples. With traditional stable isotope dilution SRM (SID-SRM), the high cost of accurately quantified, purified stable isotope encoded peptides or proteins may be prohibitive for the verification of multiple peptides from many proteins. Label-free relatively quantitative methods are increasingly popular in discovery proteomics but to a much lesser extent in targeted SRM studies (7, 8).For any SRM method, sample preparation workflows must balance the extent of enrichment and fractionation to enable quantification of lower abundance proteins, against increased technical variability (which is influenced by the number of sample handling steps) and reduced multiplexed potential as a consequence of fractionating peptides from the protein of interest into several distinct fractions. It is also essential that the true technical variation in the workflow is quantitatively evaluated from freezer to MS analysis, rather than just the variation within the LC-SRM part of the experiment. As a paradigm for a label-free SRM assay, we developed our workflow and applied it to the verification of candidate biomarkers that indicate the risk of pre-eclampsia (PE).PE affects 2–8% of pregnancies, and is characterized by hypertension and proteinuria, which may progress to severe maternal complications or death (9). Because delivery of the infant is the only effective intervention, a third of babies are born premature and fetal or newborn mortality is increased three- to 10-fold (10). Its complex etiology involves abnormal placentation, an altered immune response and a sensitized maternal vascular endothelium (11). Prediction of the condition in early pregnancy would allow prevention strategies, such as low dose aspirin, to be targeted to high risk women. In first-time pregnant women, a group particularly at risk, biomarkers continue to fall short of a test that would be useful or cost effective in clinical practice (12–14). Better-performing novel biomarkers are required.The aim of this study was to identify candidate predictive biomarkers for PE and then develop a verification assay using mass spectrometry to determine whether these should be taken forward into more extensive and expensive validation studies. Initial discovery experiments were employed using a pooled sample iTRAQ approach using two different MS platforms to increase plasma proteome coverage. Among the set of proteins discovered, we then developed a label-free SRM assay for relative quantification of CXCL7 (Platelet basic protein; PBP) and members of the Pregnancy specific glycoprotein (PSG) family in a 100-sample set from the international SCreeningfOr Pregnancy Endpoints (SCOPE) study (www.scopestudy.net). Our workflow allowed the specificity and linearity of response for each peptide to be determined, along with true technical variability. Although absolute concentration and LOD/LOQ cannot be calculated using this approach, we aimed to test the hypothesis that a label-free SRM approach could provide a rapid, robust, and efficient screen of candidate plasma biomarkers.     

Glutathione in plants: an integrated overview

Plants cannot survive without glutathione (γ-glutamylcysteinylglycine) or γ-glutamylcysteine-containing homologues. The reasons why this small molecule is indispensable are not fully understood, but it can be inferred that glutathione has functions in plant development that cannot be performed by other thiols or antioxidants. The known functions of glutathione include roles in biosynthetic pathways, detoxification, antioxidant biochemistry and redox homeostasis. Glutathione can interact in multiple ways with proteins through thiol-disulphide exchange and related processes. Its strategic position between oxidants such as reactive oxygen species and cellular reductants makes the glutathione system perfectly configured for signalling functions. Recent years have witnessed considerable progress in understanding glutathione synthesis, degradation and transport, particularly in relation to cellular redox homeostasis and related signalling under optimal and stress conditions. Here we outline the key recent advances and discuss how alterations in glutathione status, such as those observed during stress, may participate in signal transduction cascades. The discussion highlights some of the issues surrounding the regulation of glutathione contents, the control of glutathione redox potential, and how the functions of glutathione and other thiols are integrated to fine-tune photorespiratory and respiratory metabolism and to modulate phytohormone signalling pathways through appropriate modification of sensitive protein cysteine residues.     

Synthesis and anti-tumor evaluation of new trisulfide derivatives

New bis-aromatic and heterocyclic trisulfide derivatives 5, 7-10 were synthesized by optimizing lead dibenzyl trisulfide natural product (4) to evaluate their anti-tumor activities. Five compounds 5-7, 9, and 10 exhibited potent anti-tumor activities against eight different tumor cell lines with low cytotoxicity against HepG2. Initial SAR was discussed, and MOA of these anti-microtubule agents was suggested based on cell kinetic response patterns observed on RT-CES system.