The novel flightless-I gene brings together two gene families, actin- binding proteins related to gelsolin and leucine-rich-repeat proteins involved in Ras signal transduction

The Drosophila melanogaster gene flightless-I, involved in gastrulation and muscle degeneration, has Caenorhabditis elegans and human homologues. In these highly conserved genes, two previously known gene families have been brought together, families encoding the actin- binding proteins related to gelsolin and the leucine-rich-repeat (LRR) group of proteins involved in protein-protein interactions. Both these gene families exhibit characteristics of molecular changes involving replication slippage and exon shuffling. Phylogenetic analyses of 19 amino acid sequences of 6 related protein types indicate that actin- associated proteins related to gelsolin are monophyletic to a common ancestor and include flightless proteins. Conversely, comparison of 24 amino acid sequences of LRR proteins including the flightless proteins indicates that flightless proteins are members of a structurally related subgroup. Included in the flightless cluster are human and mouse rsp-1 proteins involved in suppressing v-Ras transformation of cells and the membrane-associated yeast (Saccharomyces cerevisae) adenylate cyclase whose analogous LRRs are required for interaction with Ras proteins. There is a strong possibility that ligands for this group could be related and that flightless may have a similar role in Ras signal transduction. It is hypothesized that an ancestral monomeric gelsolin precursor protein has undergone at least four independent gene reorganization events to account for the structural diversity of the extant family of gelsolin-related proteins and that gene duplication and exon shuffling events occurred prior to or at the beginning of multicellular life, resulting in the evolution of some members of the family soon after the appearance of actin-type proteins.      

Magnesium-induced inner membrane aggregation in heart mitochondria: prevention and reversal by carboxyatractyloside and bongkrekic acid

Mg(2+) at an optimal concentration of 2mM (ph 6.5) induces large increases (up to 30 percent) in the optical density of bovine heart mitochondria incubated under conditions of low ionic strength (< approx. 0.01). The increases are associated with aggregation (sticking together) of the inner membranes and are little affected by changes in the energy status of the mitochondria. Virtually all of a number of other polyvalent cations tested and Ag(+) induce increases in mitochondrial optical density similar to those induced by Mg(2+), their approximate order of concentration effectiveness in respect to Mg(2+) being: La(3+) > Pb(2+) = Cu(2+) > Cd(2+) > Zn(2+) > Ag(+) > Mn(2+) > Ca(2+) > Mg(2+). With the exception of Mg(2+), all of these cations appear to induce swelling of the mitochondria concomitant with inner membrane aggregation. The inhibitors of the adenine nucleotide transport reaction carboxyatratyloside and bongkrekic acid are capable of preventing and reversing Mg(2+)-induced aggregation at the same low concentration required for complete inhibition of phosphorylating respiration, suggesting that they inhibit the aggregation by binding to the adenine nucleotide carrier. The findings are interpreted to indicate (a) that the inner mitochondrial membrane is normally prevented from aggregating by virtue of its net negative outer surface change, (b) that the cations induce the membrane to aggregate by binding at its outer surface, decreasing the net negative charge, and (c) that carboxyatractyloside and bongkrekic acid inhibit the aggregation by binding to the outer surface of the membrane, increasing the net negative charge.     

Inter-Network Interactions: Impact of Connections between Oscillatory Neuronal Networks on Oscillation Frequency and Pattern

Oscillations in electrical activity are a characteristic feature of many brain networks and display a wide variety of temporal patterns. A network may express a single oscillation frequency, alternate between two or more distinct frequencies, or continually express multiple frequencies. In addition, oscillation amplitude may fluctuate over time. The origin of this complex repertoire of activity remains unclear. Different cortical layers often produce distinct oscillation frequencies. To investigate whether interactions between different networks could contribute to the variety of oscillation patterns, we created two model networks, one generating on its own a relatively slow frequency (20 Hz; slow network) and one generating a fast frequency (32 Hz; fast network). Taking either the slow or the fast network as source network projecting connections to the other, or target, network, we systematically investigated how type and strength of inter-network connections affected target network activity. For high inter-network connection strengths, we found that the slow network was more effective at completely imposing its rhythm on the fast network than the other way around. The strongest entrainment occurred when excitatory cells of the slow network projected to excitatory or inhibitory cells of the fast network. The fast network most strongly imposed its rhythm on the slow network when its excitatory cells projected to excitatory cells of the slow network. Interestingly, for lower inter-network connection strengths, multiple frequencies coexisted in the target network. Just as observed in rat prefrontal cortex, the target network could express multiple frequencies at the same time, alternate between two distinct oscillation frequencies, or express a single frequency with alternating episodes of high and low amplitude. Together, our results suggest that input from other oscillating networks may markedly alter a network''s frequency spectrum and may partly be responsible for the rich repertoire of temporal oscillation patterns observed in the brain.     

Detection of silent cells,synchronization and modulatory activity in developing cellular networks

Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature “silent” cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity‐based pixel correlations to identify cellular‐based regions of interest (ROIs) and coincident cell activity. However, using activity‐based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell‐dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi‐automatically detect cells within developing neuronal networks that were imaged using calcium‐sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 76: 357–374, 2016     

Rates and patterns of mitochondrial DNA sequence evolution in fringilline finches (fringilla spp.) and the greenfinch (Carduelis chloris)

Rates and patterns of evolution in partial sequences of five mitochondrial genes (cytochrome b, ATPase 6, NADH dehydrogenase subunit 5, tRNA(Glu), and the control region) were compared among taxa in the passerine bird genera Fringilla and Carduelis. Rates of divergence do not vary significantly among genes, even in comparisons with the control region. Rate variation among lineages is significant only for the control region and NADH dehydrogenase subunit 5, and patterns of variation are consistent with the expectations of neutral theory. Base composition is biased in all genes but is stationary among lineages, and there is evidence for directional mutation pressure only in the control region. Despite these similarities, patterns of substitution differ among genes, consistent with alternative regimes of selective constraint. Rates of nonsynonymous substitution are higher in NADH dehydrogenase subunit 5 than in other protein-coding genes, and transitions exist in elevated proportions relative to transversions. Transitions appear to accumulate linearly with time in tRNA(Glu), and despite exhibiting the highest overall rate of divergence among species, there are no transversional changes in this gene. Finally, for resolving phylogenetic relationships among Fringilla taxa, the combined protein-coding data are broadly similar to those of the control region in terms of phylogenetic informativeness and statistical support.      

Comparison of linkage disequilibrium and haplotype diversity on macro- and microchromosomes in chicken

Background

Toll like receptors (TLR) play the central role in the recognition of pathogen associated molecular patterns (PAMPs). Mutations in the TLR1, TLR2 and TLR4 genes may change the ability to recognize PAMPs and cause altered responsiveness to the bacterial pathogens.

Results

The study presents association between TLR gene mutations and increased susceptibility to Mycobacterium avium subsp. paratuberculosis (MAP) infection. Novel mutations in TLR genes (TLR1- Ser150Gly and Val220Met; TLR2 – Phe670Leu) were statistically correlated with the hindrance in recognition of MAP legends. This correlation was confirmed subsequently by measuring the expression levels of cytokines (IL-4, IL-8, IL-10, IL-12 and IFN-γ) in the mutant and wild type moDCs (mocyte derived dendritic cells) after challenge with MAP cell lysate or LPS. Further in silico analysis of the TLR1 and TLR4 ectodomains (ECD) revealed the polymorphic nature of the central ECD and irregularities in the central LRR (leucine rich repeat) motifs.

Conclusion

The most critical positions that may alter the pathogen recognition ability of TLR were: the 9^th amino acid position in LRR motif (TLR1–LRR10) and 4^th residue downstream to LRR domain (exta-LRR region of TLR4). The study describes novel mutations in the TLRs and presents their association with the MAP infection.     

Presynaptic inhibition upon CB1 or mGlu2/3 receptor activation requires ERK/MAPK phosphorylation of Munc18‐1

Presynaptic cannabinoid (CB1R) and metabotropic glutamate receptors (mGluR2/3) regulate synaptic strength by inhibiting secretion. Here, we reveal a presynaptic inhibitory pathway activated by extracellular signal‐regulated kinase (ERK) that mediates CB1R‐ and mGluR2/3‐induced secretion inhibition. This pathway is triggered by a variety of events, from foot shock‐induced stress to intense neuronal activity, and induces phosphorylation of the presynaptic protein Munc18‐1. Mimicking constitutive phosphorylation of Munc18‐1 results in a drastic decrease in synaptic transmission. ERK‐mediated phosphorylation of Munc18‐1 ultimately leads to degradation by the ubiquitin–proteasome system. Conversely, preventing ERK‐dependent Munc18‐1 phosphorylation increases synaptic strength. CB1R‐ and mGluR2/3‐induced synaptic inhibition and depolarization‐induced suppression of excitation (DSE) are reduced upon ERK/MEK pathway inhibition and further reduced when ERK‐dependent Munc18‐1 phosphorylation is blocked. Thus, ERK‐dependent Munc18‐1 phosphorylation provides a major negative feedback loop to control synaptic strength upon activation of presynaptic receptors and during intense neuronal activity.     

Nicotinic modulation of synaptic transmission and plasticity in cortico-limbic circuits

Nicotine is the principle addictive agent delivered via cigarette smoking. The addictive activity of nicotine is due to potent interactions with nicotinic acetylcholine receptors (nAChRs) on neurons in the reinforcement and reward circuits of the brain. Beyond its addictive actions, nicotine is thought to have positive effects on performance in working memory and short-term attention-related tasks. The brain areas involved in such behaviors are part of an extensive cortico-limbic network that includes relays between prefrontal cortex (PFC) and cingulate cortex (CC), hippocampus, amygdala, ventral tegmental area (VTA) and the nucleus accumbens (nAcc). Nicotine activates a broad array of nAChRs subtypes that can be targeted to pre- as well as peri- and post-synaptic locations in these areas. Thereby, nicotine not only excites different types of neurons, but it also perturbs baseline neuronal communication, alters synaptic properties and modulates synaptic plasticity.In this review we focus on recent findings on nicotinic modulation of cortical circuits and their targets fields, which show that acute and transient activation of nicotinic receptors in cortico-limbic circuits triggers a series of events that affects cognitive performance in a long lasting manner. Understanding how nicotine induces long-term changes in synapses and alters plasticity in the cortico-limbic circuits is essential to determining how these areas interact in decoding fundamental aspects of cognition and reward.