Untangling taxonomy: a DNA barcode reference library for Canadian spiders

Approximately 1460 species of spiders have been reported from Canada, 3% of the global fauna. This study provides a DNA barcode reference library for 1018 of these species based upon the analysis of more than 30 000 specimens. The sequence results show a clear barcode gap in most cases with a mean intraspecific divergence of 0.78% vs. a minimum nearest‐neighbour (NN) distance averaging 7.85%. The sequences were assigned to 1359 Barcode index numbers (BINs) with 1344 of these BINs composed of specimens belonging to a single currently recognized species. There was a perfect correspondence between BIN membership and a known species in 795 cases, while another 197 species were assigned to two or more BINs (556 in total). A few other species (26) were involved in BIN merges or in a combination of merges and splits. There was only a weak relationship between the number of specimens analysed for a species and its BIN count. However, three species were clear outliers with their specimens being placed in 11–22 BINs. Although all BIN splits need further study to clarify the taxonomic status of the entities involved, DNA barcodes discriminated 98% of the 1018 species. The present survey conservatively revealed 16 species new to science, 52 species new to Canada and major range extensions for 426 species. However, if most BIN splits detected in this study reflect cryptic taxa, the true species count for Canadian spiders could be 30–50% higher than currently recognized.     

<Superscript>1</Superscript>H, <Superscript>13</Superscript>C and <Superscript>15</Superscript>N resonance assignments and secondary structure analysis of translation initiation factor 1 from <Emphasis Type="Italic">Pseudomonas aeruginosa</Emphasis>

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen and a primary cause of infection in humans. P. aeruginosa can acquire resistance against multiple groups of antimicrobial agents, including β-lactams, aminoglycosides and fluoroquinolones, and multidrug resistance is increasing in this organism which makes treatment of the infections difficult and expensive. This has led to the unmet need for discovery of new compounds distinctly different from present antimicrobials. Protein synthesis is an essential metabolic process and a validated target for the development of new antibiotics. Translation initiation factor 1 from P. aeruginosa (Pa-IF1) is the smallest of the three initiation factors that acts to establish the 30S initiation complex to initiate translation during protein biosynthesis, and its structure is unknown. Here we report the ¹H, ¹³C and ¹⁵N chemical shift assignments of Pa-IF1 as the basis for NMR structure determination and interaction studies. Secondary structure analyses deduced from the NMR chemical shift data have identified five β-strands with an unusually extended β-strand at the C-terminal end of the protein and one short α-helix arranged in the sequential order β1–β2–β3–α1–β4–β5. This is further supported by ¹⁵N–{¹H} hetero NOEs. These secondary structure elements suggest the Pa-IF1 adopts the typical β-barrel structure and is composed of an oligomer-binding motif.     

The dynamics of coupled populations subject to control

The dynamics of coupled populations have mostly been studied in the context of metapopulation viability with application to, for example, species at risk. However, when considering pests and pathogens, eradication, not persistence, is often the end goal. Humans may intervene to control nuisance populations, resulting in reciprocal interactions between the human and natural systems that can lead to unexpected dynamics. The incidence of these human-natural couplings has been increasing, hastening the need to better understand the emergent properties of such systems in order to predict and manage outbreaks of pests and pathogens. For example, the success of the growing aquaculture industry depends on our ability to manage pathogens and maintain a healthy environment for farmed and wild fish. We developed a model for the dynamics of connected populations subject to control, motivated by sea louse parasites that can disperse among salmon farms. The model includes exponential population growth with a forced decline when populations reach a threshold, representing control interventions. Coupling two populations with equal growth rates resulted in phase locking or synchrony in their dynamics. Populations with different growth rates had different periods of oscillation, leading to quasiperiodic dynamics when coupled. Adding small amounts of stochasticity destabilized quasiperiodic cycles to chaos, while stochasticity was damped for periodic or stable dynamics. Our analysis suggests that strict treatment thresholds, although well intended, can complicate parasite dynamics and hinder control efforts. Synchronizing populations via coordinated management among farms leads to more effective control that is required less frequently. Our model is simple and generally applicable to other systems where dispersal affects the management of pests and pathogens.     

The DNA methylation profile of activated human natural killer cells

Natural killer (NK) cells are now recognized to exhibit characteristics akin to cells of the adaptive immune system. The generation of adaptive memory is linked to epigenetic reprogramming including alterations in DNA methylation. The study herein found reproducible genome wide DNA methylation changes associated with human NK cell activation. Activation led predominately to CpG hypomethylation (81% of significant loci). Bioinformatics analysis confirmed that non-coding and gene-associated differentially methylated sites (DMS) are enriched for immune related functions (i.e., immune cell activation). Known DNA methylation-regulated immune loci were also identified in activated NK cells (e.g., TNFA, LTA, IL13, CSF2). Twenty-one loci were designated high priority and further investigated as potential markers of NK activation. BHLHE40 was identified as a viable candidate for which a droplet digital PCR assay for demethylation was developed. The assay revealed high demethylation in activated NK cells and low demethylation in naïve NK, T- and B-cells. We conclude the NK cell methylome is plastic with potential for remodeling. The differentially methylated region signature of activated NKs revealed similarities with T cell activation, but also provided unique biomarker candidates of NK activation, which could be useful in epigenome-wide association studies to interrogate the role of NK subtypes in global methylation changes associated with exposures and/or disease states.     

SETD7 Regulates the Differentiation of Human Embryonic Stem Cells

The successful use of specialized cells in regenerative medicine requires an optimization in the differentiation protocols that are currently used. Understanding the molecular events that take place during the differentiation of human pluripotent cells is essential for the improvement of these protocols and the generation of high quality differentiated cells. In an effort to understand the molecular mechanisms that govern differentiation we identify the methyltransferase SETD7 as highly induced during the differentiation of human embryonic stem cells and differentially expressed between induced pluripotent cells and somatic cells. Knock-down of SETD7 causes differentiation defects in human embryonic stem cell including delay in both the silencing of pluripotency-related genes and the induction of differentiation genes. We show that SETD7 methylates linker histone H1 in vitro causing conformational changes in H1. These effects correlate with a decrease in the recruitment of H1 to the pluripotency genes OCT4 and NANOG during differentiation in the SETD7 knock down that might affect the proper silencing of these genes during differentiation.     

Regulating Emotions during Difficult Multiattribute Decision Making: The Role of Pre-Decisional Coherence Shifting

Almost all real-life decisions entail attribute conflict; every serious choice alternative is better than its competitors on some attribute dimensions but worse on others. In pre-decisional “coherence shifting,” the decision maker gradually softens that conflict psychologically to the point where one alternative is seen as dominant over its competitors, or nearly so. Specifically, weaknesses of the eventually chosen alternative come to be perceived as less severe and less important while its strengths seem more desirable and significant. The research described here demonstrates that difficult multiattribute decision problems are aversive and that pre-decisional coherence shifting aids individuals in regulating that emotional discomfort. Across three studies, attribute conflict was confirmed to be aversive (Study 1), and skin conductance responses and ratings of decision difficulty both decreased in participants who coherence shifted (Study 2). Coherence shifting was also diminished among decision makers who were depleted of regulatory resources, known to be required for common emotion regulation mechanisms. Further, coherence shifting was shown to be relatively common among people who reported strong suppression tendencies in everyday emotion regulation (Study 3). Overall, the data suggest that, at least in part, coherence shifting serves as a tool that helps decision makers manage the pre-decisional discomfort generated by attribute conflict. Theoretical and practical implications are discussed.     

An Age-Associated Decline in Thymic Output Differs in Dog Breeds According to Their Longevity

The age associated decline in immune function is preceded in mammals by a reduction in thymic output. Furthermore, there is increasing evidence of a link between immune competence and lifespan. One approach to determining thymic output is to quantify signal joint T cell receptor excision circles (sj-TRECs), a method which has been developed and used in several mammalian species. Life expectancy and the rate of aging vary in dogs depending upon their breed. In this study, we quantified sj-TRECs in blood samples from dogs of selected breeds to determine whether there was a relationship between longevity and thymic output. In Labrador retrievers, a breed with a median expected lifespan of 11 years, there was an age-associated decline in sj-TREC values, with the greatest decline occurring before 5 years of age, but with sj-TREC still detectable in some geriatric animals, over 13 years of age. In large short-lived breeds (Burnese mountain dogs, Great Danes and Dogue de Bordeaux), the decline in sj-TREC values began earlier in life, compared with small long-lived breeds (Jack Russell terriers and Yorkshire terriers), and the presence of animals with undetectable sj-TRECs occurred at a younger age in the short-lived breeds. The study findings suggest that age-associated changes in canine sj-TRECs are related to breed differences in longevity, and this research highlights the use of dogs as a potential model of immunosenescence.     

Kinetic Characterization of 100 Glycoside Hydrolase Mutants Enables the Discovery of Structural Features Correlated with Kinetic Constants

The use of computational modeling algorithms to guide the design of novel enzyme catalysts is a rapidly growing field. Force-field based methods have now been used to engineer both enzyme specificity and activity. However, the proportion of designed mutants with the intended function is often less than ten percent. One potential reason for this is that current force-field based approaches are trained on indirect measures of function rather than direct correlation to experimentally-determined functional effects of mutations. We hypothesize that this is partially due to the lack of data sets for which a large panel of enzyme variants has been produced, purified, and kinetically characterized. Here we report the k_cat and K_M values of 100 purified mutants of a glycoside hydrolase enzyme. We demonstrate the utility of this data set by using machine learning to train a new algorithm that enables prediction of each kinetic parameter based on readily-modeled structural features. The generated dataset and analyses carried out in this study not only provide insight into how this enzyme functions, they also provide a clear path forward for the improvement of computational enzyme redesign algorithms.