Adenylyl Cyclase Plays a Regulatory Role in Development, Stress Resistance and Secondary Metabolism in Fusarium fujikuroi

The ascomycete fungus Fusarium fujikuroi (Gibberella fujikuroi MP-C) produces secondary metabolites of biotechnological interest, such as gibberellins, bikaverin, and carotenoids. Production of these metabolites is regulated by nitrogen availability and, in a specific manner, by other environmental signals, such as light in the case of the carotenoid pathway. A complex regulatory network controlling these processes is recently emerging from the alterations of metabolite production found through the mutation of different regulatory genes. Here we show the effect of the targeted mutation of the acyA gene of F. fujikuroi, coding for adenylyl cyclase. Mutants lacking the catalytic domain of the AcyA protein showed different phenotypic alterations, including reduced growth, enhanced production of unidentified red pigments, reduced production of gibberellins and partially derepressed carotenoid biosynthesis in the dark. The phenotype differs in some aspects from that of similar mutants of the close relatives F. proliferatum and F. verticillioides: contrary to what was observed in these species, ΔacyA mutants of F. fujikuroi showed enhanced sensitivity to oxidative stress (H2O2), but no change in heavy metal resistance or in the ability to colonize tomato tissue, indicating a high versatility in the regulatory roles played by cAMP in this fungal group

Production of dust by massive stars at high redshift

The large amounts of dust detected in sub-millimeter galaxies and quasars at high redshift pose a challenge to galaxy formation models and theories of cosmic dust formation. At z > 6 only stars of relatively high mass (> 3 Msun) are sufficiently short-lived to be potential stellar sources of dust. This review is devoted to identifying and quantifying the most important stellar channels of rapid dust formation. We ascertain the dust production efficiency of stars in the mass range 3-40 Msun using both observed and theoretical dust yields of evolved massive stars and supernovae (SNe) and provide analytical expressions for the dust production efficiencies in various scenarios. We also address the strong sensitivity of the total dust productivity to the initial mass function. From simple considerations, we find that, in the early Universe, high-mass (> 3 Msun) asymptotic giant branch stars can only be dominant dust producers if SNe generate <~ 3 x 10^-3 Msun of dust whereas SNe prevail if they are more efficient. We address the challenges in inferring dust masses and star-formation rates from observations of high-redshift galaxies. We conclude that significant SN dust production at high redshift is likely required to reproduce current dust mass estimates, possibly coupled with rapid dust grain growth in the interstellar medium.Comment: 72 pages, 9 figures, 5 tables; to be published in The Astronomy and Astrophysics Revie

Cluster tendency assessment in neuronal spike data.

Sorting spikes from extracellular recording into clusters associated with distinct single units (putative neurons) is a fundamental step in analyzing neuronal populations. Such spike sorting is intrinsically unsupervised, as the number of neurons are not known a priori. Therefor, any spike sorting is an unsupervised learning problem that requires either of the two approaches: specification of a fixed value k for the number of clusters to seek, or generation of candidate partitions for several possible values of c, followed by selection of a best candidate based on various post-clustering validation criteria. In this paper, we investigate the first approach and evaluate the utility of several methods for providing lower dimensional visualization of the cluster structure and on subsequent spike clustering. We also introduce a visualization technique called improved visual assessment of cluster tendency (iVAT) to estimate possible cluster structures in data without the need for dimensionality reduction. Experimental results are conducted on two datasets with ground truth labels. In data with a relatively small number of clusters, iVAT is beneficial in estimating the number of clusters to inform the initialization of clustering algorithms. With larger numbers of clusters, iVAT gives a useful estimate of the coarse cluster structure but sometimes fails to indicate the presumptive number of clusters. We show that noise associated with recording extracellular neuronal potentials can disrupt computational clustering schemes, highlighting the benefit of probabilistic clustering models. Our results show that t-Distributed Stochastic Neighbor Embedding (t-SNE) provides representations of the data that yield more accurate visualization of potential cluster structure to inform the clustering stage. Moreover, The clusters obtained using t-SNE features were more reliable than the clusters obtained using the other methods, which indicates that t-SNE can potentially be used for both visualization and to extract features to be used by any clustering algorithm

Electrical coupling underlies high-frequency oscillations in the hippocampus in vitro

Coherent oscillations, in which ensembles of neurons fire in a repeated and synchronous manner, are thought to be important in higher brain functions. In the hippocampus, these discharges are categorized according to their frequency as theta (4-10Hz), {gamma} (20-80 Hz) and high-frequency (approximately 200 Hz) discharges, and they occur in relation to different behavioural states. The synaptic bases of theta and {gamma} rhythms have been extensively studied but the cellular bases for high-frequency oscillations are not understood. Here we report that high-frequency network oscillations are present in rat brain slices in vitro, occurring as a brief series of repetitive population spikes at 150-200 Hz in all hippocampal principal cell layers. Moreover, this synchronous activity is not mediated through the more commonly studied modes of chemical synaptic transmission, but is in fact a result of direct electrotonic coupling of neurons, most likely through gap-junctional connections. Thus high-frequency oscillations synchronize the activity of electrically coupled subsets of principal neurons within the well-documented synaptic network of the hippocampus

Calcium-activated potassium currents in mammalian neurons

1. Influx of calcium via voltage-dependent calcium channels during the action potential lends to increases in cytosolic calcium that can initiate a number of physiological processes. One of these is the activation of potassium currents on the plasmalemma. These calcium-activated potassium currents contribute to action potential repolarization and are largely responsible for the phenomenon of spike frequency adaptation. This refers to the progressive slowing of the frequency of discharge of action potentials during sustained injection of depolarizing current. In some cell types, this adaptation is so marked that despite the presence of depolarizing current, only a single spike (or a few spikes) is initiated, Following cessation of current injection, slow deactivation of calcium-activated potassium currents is also responsible for the prolonged hyperpolarization that often follows, 2. A number of macroscopic calcium-activated potassium currents that can be separated on the basis of kinetic and pharmacological criteria have been described in mammalian neurons. At the single channel level, several types of calcium-activated potassium channels also have been characterized. While for some macroscopic currents the underlying:single channels have been unambiguously defined, for other currents the identity of the underlying channels is not clear. 3. In the present review we describe the properties of the known types of calcium-activated potassium currents in mammalian neurons and indicate the relationship between macroscopic currents and particular single channels