Identification of proteins capable of metal reduction from the proteome of the Gram‐positive bacterium Desulfotomaculum reducens MI‐1 using an NADH‐based activity assay

Understanding of microbial metal reduction is based almost solely on studies of Gram‐negative organisms. In this study, we focus on Desulfotomaculum reducens MI‐1, a Gram‐positive metal reducer whose genome lacks genes with similarity to any characterized metal reductase. Using non‐denaturing separations and mass spectrometry identification, in combination with a colorimetric screen for chelated Fe(III)‐NTA reduction with NADH as electron donor, we have identified proteins from the D. reducens proteome not previously characterized as iron reductases. Their function was confirmed by heterologous expression in Escherichia coli. Furthermore, we show that these proteins have the capability to reduce soluble Cr(VI) and U(VI) with NADH as electron donor. The proteins identified are NADH : flavin oxidoreductase (Dred_2421) and a protein complex composed of oxidoreductase flavin adenine dinucleotide/NAD(P)‐binding subunit (Dred_1685) and dihydroorotate dehydrogenase 1B (Dred_1686). Dred_2421 was identified in the soluble proteome and is predicted to be a cytoplasmic protein. Dred_1685 and Dred_1686 were identified in both the soluble as well as the insoluble protein fraction, suggesting a type of membrane association, although PSORTb predicts both proteins are cytoplasmic. This study is the first functional proteomic analysis of D. reducens and one of the first analyses of metal and radionuclide reduction in an environmentally relevant Gram‐positive bacterium.     

On-Going Frontal Alpha Rhythms Are Dominant in Passive State and Desynchronize in Active State in Adult Gray Mouse Lemurs

The gray mouse lemur (Microcebus murinus) is considered a useful primate model for translational research. In the framework of IMI PharmaCog project (Grant Agreement n°115009, www.pharmacog.org), we tested the hypothesis that spectral electroencephalographic (EEG) markers of motor and locomotor activity in gray mouse lemurs reflect typical movement-related desynchronization of alpha rhythms (about 8–12 Hz) in humans. To this aim, EEG (bipolar electrodes in frontal cortex) and electromyographic (EMG; bipolar electrodes sutured in neck muscles) data were recorded in 13 male adult (about 3 years) lemurs. Artifact-free EEG segments during active state (gross movements, exploratory movements or locomotor activity) and awake passive state (no sleep) were selected on the basis of instrumental measures of animal behavior, and were used as an input for EEG power density analysis. Results showed a clear peak of EEG power density at alpha range (7–9 Hz) during passive state. During active state, there was a reduction in alpha power density (8–12 Hz) and an increase of power density at slow frequencies (1–4 Hz). Relative EMG activity was related to EEG power density at 2–4 Hz (positive correlation) and at 8–12 Hz (negative correlation). These results suggest for the first time that the primate gray mouse lemurs and humans may share basic neurophysiologic mechanisms of synchronization of frontal alpha rhythms in awake passive state and their desynchronization during motor and locomotor activity. These EEG markers may be an ideal experimental model for translational basic (motor science) and applied (pharmacological and non-pharmacological interventions) research in Neurophysiology.     

Ensemble multivariate analysis to improve identification of articular cartilage disease in noisy Raman spectra

The development of new methods for the early diagnosis of cartilage disease could offer significant improvement in patient care. Raman spectroscopy is an emerging biomedical technology with unique potential to recognize disease tissues, though difficulty in obtaining the samples needed to train a diagnostic and excessive signal noise could slow its development into a clinical tool. In the current report we detail the use of principal component analysis – linear discriminant analysis (PCA‐LDA) on spectra from pairs of materials modeling cartilage disease to create multiple spectral scoring metrics, which could limit the reliance on primary training data for identifying disease in low signal‐to‐noise‐ratio (SNR) Raman spectra. Our proof‐of‐concept experiments show that combinations of these model‐metrics has the potential to improve the classification of low‐SNR Raman spectra from human normal and osteoarthritic (OA) cartilage over a single metric trained with spectra from the same healthy and OA tissues.

Scatter plot showing the PCA‐LDA derived human‐disease‐metric scores versus rat‐model‐metric scores for 7656 low signal‐to‐noise spectra from healthy (blue) and osteoarthritic (red) cartilage. Light vertical and horizontal lines represent the optimized single metric classification boundary. Dark diagonal line represents the classification of boundary resulting from the optimized combination of the two metrics. Abbreviations: er (error rate), PCA‐LDA (principal component analysis – linear discriminant analysis), HOA (human osteoarthritis), HAC (human articular cartilage), RIF (rat injury fibrocartilage), RAC (rat articular cartilage).     

Combinations of PARP Inhibitors with Temozolomide Drive PARP1 Trapping and Apoptosis in Ewing’s Sarcoma

Ewing’s sarcoma is a malignant pediatric bone tumor with a poor prognosis for patients with metastatic or recurrent disease. Ewing’s sarcoma cells are acutely hypersensitive to poly (ADP-ribose) polymerase (PARP) inhibition and this is being evaluated in clinical trials, although the mechanism of hypersensitivity has not been directly addressed. PARP inhibitors have efficacy in tumors with BRCA1/2 mutations, which confer deficiency in DNA double-strand break (DSB) repair by homologous recombination (HR). This drives dependence on PARP1/2 due to their function in DNA single-strand break (SSB) repair. PARP inhibitors are also cytotoxic through inhibiting PARP1/2 auto-PARylation, blocking PARP1/2 release from substrate DNA. Here, we show that PARP inhibitor sensitivity in Ewing’s sarcoma cells is not through an apparent defect in DNA repair by HR, but through hypersensitivity to trapped PARP1-DNA complexes. This drives accumulation of DNA damage during replication, ultimately leading to apoptosis. We also show that the activity of PARP inhibitors is potentiated by temozolomide in Ewing’s sarcoma cells and is associated with enhanced trapping of PARP1-DNA complexes. Furthermore, through mining of large-scale drug sensitivity datasets, we identify a subset of glioma, neuroblastoma and melanoma cell lines as hypersensitive to the combination of temozolomide and PARP inhibition, potentially identifying new avenues for therapeutic intervention. These data provide insights into the anti-cancer activity of PARP inhibitors with implications for the design of treatment for Ewing’s sarcoma patients with PARP inhibitors.     

Selected anthropometric variables and aerobic fitness as predictors of cardiovascular disease risk in children

The aim of this study was to assess the suitability of body mass index, waist circumference, waist-to-height ratio and aerobic fitness as predictors of cardiovascular risk factor clustering in children. A cross-sectional study was conducted with 290 school boys and girls from 6 to 10 years old, randomly selected. Blood was collected after a 12-hour fasting period. Blood pressure, waist circumference (WC), height and weight were evaluated according to international standards. Aerobic fitness (AF) was assessed by the 20-metre shuttle-run test. Clustering was considered when three of these factors were present: high systolic or diastolic blood pressure, high low-density lipoprotein (LDL) cholesterol, high triglycerides, high plasma glucose, high insulin concentrations and low high-density lipoprotein (HDL) cholesterol. A ROC curve identified the cut-off points of body mass index (BMI), WC, waist-to-height ratio (WHtR) and AF as predictors of risk factor clustering. BMI, WC and WHR resulted in significant areas under the ROC curves, which was not observed for AF. The anthropometric variables were good predictors of cardiovascular risk factor clustering in both sexes, whereas aerobic fitness should not be used to identify cardiovascular risk factor clustering in these children.     

Population history,gene flow,and bottlenecks in island populations of a secondary seed disperser,the southern grey shrike (Lanius meridionalis koenigi)

Studying the population history and demography of organisms with important ecological roles can aid understanding of evolutionary processes at the community level and inform conservation. We screened genetic variation (mtDNA and microsatellite) across the populations of the southern grey shrike (Lanius meridionalis koenigi) in the Canary Islands, where it is an endemic subspecies and an important secondary seed disperser. We show that the Canarian subspecies is polyphyletic with L. meridionalis elegans from North Africa and that shrikes have colonized the Canary Islands from North Africa multiple times. Substantial differences in genetic diversity exist across islands, which are most likely the product of a combination of historical colonization events and recent bottlenecks. The Eastern Canary Islands had the highest overall levels of genetic diversity and have probably been most recently and/or frequently colonized from Africa. Recent or ongoing bottlenecks were detected in three of the islands and are consistent with anecdotal evidence of population declines due to human disturbance. These findings are troubling given the shrike's key ecological role in the Canary Islands, and further research is needed to understand the community‐level consequences of declines in shrike populations. Finally, we found moderate genetic differentiation among populations, which largely reflected the shrike's bottleneck history; however, a significant pattern of isolation‐by‐distance indicated that some gene flow occurs between islands. This study is a useful first step toward understanding how secondary seed dispersal operates over broad spatial scales.