Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.     

Clostridium scindens: a human gut microbe with a high potential to convert glucocorticoids into androgens

Clostridium scindens American Type Culture Collection 35704 is capable of converting primary bile acids to toxic secondary bile acids, as well as converting glucocorticoids to androgens by side-chain cleavage. The molecular structure of the side-chain cleavage product of cortisol produced by C. scindens was determined to be 11β-hydroxyandrost-4-ene-3,17-dione (11β-OHA) by high-resolution mass spectrometry, ¹H and ¹³C NMR spectroscopy, and X-ray crystallography. Using RNA-Seq technology, we identified a cortisol-inducible (∼1,000-fold) operon (desABCD) encoding at least one enzyme involved in anaerobic side-chain cleavage. The desC gene was cloned, overexpressed, purified, and found to encode a 20α-hydroxysteroid dehydrogenase (HSDH). This operon also encodes a putative “transketolase” (desAB) hypothesized to have steroid-17,20-desmolase/oxidase activity, and a possible corticosteroid transporter (desD). RNA-Seq data suggests that the two-carbon side chain of glucocorticords may feed into the pentose-phosphate pathway and are used as a carbon source. The 20α-HSDH is hypothesized to function as a metabolic “rheostat” controlling rates of side-chain cleavage. Phylogenetic analysis suggests this operon is rare in nature and the desC gene evolved from a gene encoding threonine dehydrogenase. The physiological effect of 11β-OHAD on the host or other gut microbes is currently unknown.     

Proteases of Sporothrix schenckii: Cytopathological effects on a host-cell model

Background

Sporotrichosis is a fungal infection caused by the Sporothrix schenckii complex. The adhesion of the fungus to the host tissue has been considered the key step in the colonization and invasion, but little is known about the early events in the host–parasite interaction.

Repertoire, genealogy and genomic organization of cruzipain and homologous genes in Trypanosoma cruzi, T. cruzi-like and other trypanosome species

Trypanosoma cruzi, the agent of Chagas disease, is a complex of genetically diverse isolates highly phylogenetically related to T. cruzi-like species, Trypanosoma cruzi marinkellei and Trypanosoma dionisii, all sharing morphology of blood and culture forms and development within cells. However, they differ in hosts, vectors and pathogenicity: T. cruzi is a human pathogen infective to virtually all mammals whilst the other two species are non-pathogenic and bat restricted. Previous studies suggest that variations in expression levels and genetic diversity of cruzipain, the major isoform of cathepsin L-like (CATL) enzymes of T. cruzi, correlate with levels of cellular invasion, differentiation, virulence and pathogenicity of distinct strains. In this study, we compared 80 sequences of genes encoding cruzipain from 25 T. cruzi isolates representative of all discrete typing units (DTUs TcI-TcVI) and the new genotype Tcbat and 10 sequences of homologous genes from other species. The catalytic domain repertoires diverged according to DTUs and trypanosome species. Relatively homogeneous sequences are found within and among isolates of the same DTU except TcV and TcVI, which displayed sequences unique or identical to those of TcII and TcIII, supporting their origin from the hybridization between these two DTUs. In network genealogies, sequences from T. cruzi clustered tightly together and closer to T. c. marinkellei than to T. dionisii and largely differed from homologues of T. rangeli and T. b. brucei. Here, analysis of isolates representative of the overall biological and genetic diversity of T. cruzi and closest T. cruzi-like species evidenced DTU- and species-specific polymorphisms corroborating phylogenetic relationships inferred with other genes. Comparison of both phylogenetically close and distant trypanosomes is valuable to understand host-parasite interactions, virulence and pathogenicity. Our findings corroborate cruzipain as valuable target for drugs, vaccine, diagnostic and genotyping approaches.     

Extracellular Enzyme Activity and Microbial Diversity Measured on Seafloor Exposed Basalts from Loihi Seamount Indicate the Importance of Basalts to Global Biogeochemical Cycling

Seafloor basalts are widely distributed and host diverse prokaryotic communities, but no data exist concerning the metabolic rates of the resident microbial communities. We present here potential extracellular enzyme activities of leucine aminopeptidase (LAP) and alkaline phosphatase (AP) measured on basalt samples from different locations on Loihi Seamount, HI, coupled with analysis of prokaryotic biomass and pyrosequencing of the bacterial 16S rRNA gene. The community maximum potential enzyme activity (V_max) of LAP ranged from 0.47 to 0.90 nmol (g rock)⁻¹ h⁻¹; the V_max for AP was 28 to 60 nmol (g rock)⁻¹ h⁻¹. The K_m of LAP ranged from 26 to 33 μM, while the K_m for AP was 2 to 7 μM. Bacterial communities on Loihi basalts were comprised primarily of Alpha-, Delta-, andGammaproteobacteria, Bacteroidetes, and Planctomycetes. The putative ability to produce LAP is evenly distributed across the most commonly detected bacterial orders, but the ability to produce AP is likely dominated by bacteria in the orders Xanthomonadales, Flavobacteriales, and Planctomycetales. The enzyme activities on Loihi basalts were compared to those of other marine environments that have been studied and were found to be similar in magnitude to those from continental shelf sediments and orders of magnitude higher than any measured in the water column, demonstrating that the potential for exposed basalts to transform organic matter is substantial. We propose that microbial communities on basaltic rock play a significant, quantifiable role in benthic biogeochemical processes.     

Chronic hypoxia promotes an aggressive phenotype in rat prostate cancer cells

In general, tumors cells that are resistant to apoptosis and increase angiogenesis are a result of the hypoxic responses contributing to the malignant phenotype. In this study, we developed a chronic hypoxic cell model (HMLL), by incubating the prostate cancer MatLyLu cells in a hypoxic chamber (1% O(2)) over 3 weeks. Surviving cells were selected through each cell passage and were grown in the hypoxic condition up to 8 weeks. This strategy resulted in survival of only 5% of the cells. The surviving hypoxic cells displayed a greater stimulation on hypoxic adaptive response, including a greater expression of glucose transporter1 (Glut1) and VEGF secretion. In addition, higher invasion activity was observed in the chronic hypoxic HMLL cells as compared to MatLyLu cells exposed to acute hypoxia (1% O(2), 5 h) using the matrigel assay. To further examine the role of HIF-1alpha in tumor progression, both MatLyLu and HMLL cells were transfected with dominant-negative form of HIF-1alpha (DNHIF-1alpha). The Matrigel invasion activity induced by chronic hypoxia was significantly attenuated by DNHIF-1alpha. These results suggest that signaling pathways leading to hypoxic response may be differentially regulated in chronic hypoxic cells and acute hypoxic cells. Chronic hypoxia may play a greater role than acute hypoxia in promoting the aggressive phenotype of tumor cells. This observation mimics the clinical scenario where tumor cells following treatment with radiation are subjected to hypoxic conditions. The reemergence of tumor following treatment usually results in tumor cells that are more aggressive and metastatic.     

Mineral stabilization of soil carbon is suppressed by live roots,outweighing influences from litter quality or quantity

Biogeochemistry - Conserving soil carbon (C) and harnessing the potential for soil C sequestration requires an improved understanding of the processes through which organic material accumulates in...     

Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia,Bipolar Disorder,and Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.