Complete genome sequence of Desulfocapsa sulfexigens,a marine deltaproteobacterium specialized in disproportionating inorganic sulfur compounds

Desulfocapsa sulfexigens SB164P1 (DSM 10523) belongs to the deltaproteobacterial family Desulfobulbaceae and is one of two validly described members of its genus. This strain was selected for genome sequencing, because it is the first marine bacterium reported to thrive on the disproportionation of elemental sulfur, a process with a unresolved enzymatic pathway in which elemental sulfur serves both as electron donor and electron acceptor. Furthermore, in contrast to its phylogenetically closest relatives, which are dissimilatory sulfate-reducers, D. sulfexigens is unable to grow by sulfate reduction and appears metabolically specialized in growing by disproportionating elemental sulfur, sulfite or thiosulfate with CO₂ as the sole carbon source. The genome of D. sulfexigens contains the set of genes that is required for nitrogen fixation. In an acetylene assay it could be shown that the strain reduces acetylene to ethylene, which is indicative for N-fixation. The circular chromosome of D. sulfexigens SB164P1 comprises 3,986,761 bp and harbors 3,551 protein-coding genes of which 78% have a predicted function based on auto-annotation. The chromosome furthermore encodes 46 tRNA genes and 3 rRNA operons.     

A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees'' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments.     

Serum Iron Levels and the Risk of Parkinson Disease: A Mendelian Randomization Study

Background

Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date.

Methods and Findings

We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 µg/dl increase in serum iron.

Conclusions

Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made. Please see later in the article for the Editors'' Summary     

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex.     

Recombinant HIV Envelope Proteins Fail to Engage Germline Versions of Anti-CD4bs bNAbs

Vaccine candidates for HIV-1 so far have not been able to elicit broadly neutralizing antibodies (bNAbs) although they express the epitopes recognized by bNAbs to the HIV envelope glycoprotein (Env). To understand whether and how Env immunogens interact with the predicted germline versions of known bNAbs, we screened a large panel (N:56) of recombinant Envs (from clades A, B and C) for binding to the germline predecessors of the broadly neutralizing anti-CD4 binding site antibodies b12, NIH45-46 and 3BNC60. Although the mature antibodies reacted with diverse Envs, the corresponding germline antibodies did not display Env-reactivity. Experiments conducted with engineered chimeric antibodies combining the mature and germline heavy and light chains, respectively and vice-versa, revealed that both antibody chains are important for the known cross-reactivity of these antibodies. Our results also indicate that in order for b12 to display its broad cross-reactivity, multiple somatic mutations within its VH region are required. A consequence of the failure of the germline b12 to bind recombinant soluble Env is that Env-induced B-cell activation through the germline b12 BCR does not take place. Our study provides a new explanation for the difficulties in eliciting bNAbs with recombinant soluble Env immunogens. Our study also highlights the need for intense efforts to identify rare naturally occurring or engineered Envs that may engage the germline BCR versions of bNAbs.     

Replication Vesicles are Load- and Choke-Points in the Hepatitis C Virus Lifecycle

Hepatitis C virus (HCV) infection develops into chronicity in 80% of all patients, characterized by persistent low-level replication. To understand how the virus establishes its tightly controlled intracellular RNA replication cycle, we developed the first detailed mathematical model of the initial dynamic phase of the intracellular HCV RNA replication. We therefore quantitatively measured viral RNA and protein translation upon synchronous delivery of viral genomes to host cells, and thoroughly validated the model using additional, independent experiments. Model analysis was used to predict the efficacy of different classes of inhibitors and identified sensitive substeps of replication that could be targeted by current and future therapeutics. A protective replication compartment proved to be essential for sustained RNA replication, balancing translation versus replication and thus effectively limiting RNA amplification. The model predicts that host factors involved in the formation of this compartment determine cellular permissiveness to HCV replication. In gene expression profiling, we identified several key processes potentially determining cellular HCV replication efficiency.     

Increased Maternal Genome Dosage Bypasses the Requirement of the FIS Polycomb Repressive Complex 2 in Arabidopsis Seed Development

Seed development in flowering plants is initiated after a double fertilization event with two sperm cells fertilizing two female gametes, the egg cell and the central cell, leading to the formation of embryo and endosperm, respectively. In most species the endosperm is a polyploid tissue inheriting two maternal genomes and one paternal genome. As a consequence of this particular genomic configuration the endosperm is a dosage sensitive tissue, and changes in the ratio of maternal to paternal contributions strongly impact on endosperm development. The FERTILIZATION INDEPENDENT SEED (FIS) Polycomb Repressive Complex 2 (PRC2) is essential for endosperm development; however, the underlying forces that led to the evolution of the FIS-PRC2 remained unknown. Here, we show that the functional requirement of the FIS-PRC2 can be bypassed by increasing the ratio of maternal to paternal genomes in the endosperm, suggesting that the main functional requirement of the FIS-PRC2 is to balance parental genome contributions and to reduce genetic conflict. We furthermore reveal that the AGAMOUS LIKE (AGL) gene AGL62 acts as a dosage-sensitive seed size regulator and that reduced expression of AGL62 might be responsible for reduced size of seeds with increased maternal genome dosage.