Veillonella,Firmicutes: Microbes disguised as Gram negatives

The Firmicutes represent a major component of the intestinal microflora. The intestinal Firmicutes are a large, diverse group of organisms, many of which are poorly characterized due to their anaerobic growth requirements. Although most Firmicutes are Gram positive, members of the class Negativicutes, including the genus Veillonella, stain Gram negative. Veillonella are among the most abundant organisms of the oral and intestinal microflora of animals and humans, in spite of being strict anaerobes. In this work, the genomes of 24 Negativicutes, including eight Veillonella spp., are compared to 20 other Firmicutes genomes; a further 101 prokaryotic genomes were included, covering 26 phyla. Thus a total of 145 prokaryotic genomes were analyzed by various methods to investigate the apparent conflict of the Veillonella Gram stain and their taxonomic position within the Firmicutes. Comparison of the genome sequences confirms that the Negativicutes are distantly related to Clostridium spp., based on 16S rRNA, complete genomic DNA sequences, and a consensus tree based on conserved proteins. The genus Veillonella is relatively homogeneous: inter-genus pair-wise comparison identifies at least 1,350 shared proteins, although less than half of these are found in any given Clostridium genome. Only 27 proteins are found conserved in all analyzed prokaryote genomes. Veillonella has distinct metabolic properties, and significant similarities to genomes of Proteobacteria are not detected, with the exception of a shared LPS biosynthesis pathway. The clade within the class Negativicutes to which the genus Veillonella belongs exhibits unique properties, most of which are in common with Gram-positives and some with Gram negatives. They are only distantly related to Clostridia, but are even less closely related to Gram-negative species. Though the Negativicutes stain Gram-negative and possess two membranes, the genome and proteome analysis presented here confirm their place within the (mainly) Gram positive phylum of the Firmicutes. Further studies are required to unveil the evolutionary history of the Veillonella and other Negativicutes.     

Membrane protein shaving with thermolysin can be used to evaluate topology predictors

Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large‐scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over‐expressed proteins. Second, we analyzed the peptides from non‐over‐expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors. At the end we suggest that the usage of thermolysin, an enzyme working at the natural pH of the cell for membrane shaving, is superior because: (i) we detect a similar number of peptides and proteins using thermolysin and trypsin; (ii) thermolysin shaving can be run at a natural pH and (iii) the incubation time is quite short. (iv) Fewer detected peptides from thermolysin shaving originate from the transmembrane regions. Using thermolysin shaving we can also provide a clear separation between the best and the less accurate topology predictors, indicating that using data from shaving can provide valuable information when developing new topology predictors.     

Transcriptional Cofactor TBLR1 Controls Lipid Mobilization in White Adipose Tissue

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Highlights? TBLR1 controls cAMP-dependent lipolysis in adipocytes ? Adipocyte-specific deletion of TBLR1 in mice impairs fasting-induced lipolysis ? Lack of TBLR1 in adipocytes aggravates diet-induced obesity and metabolic dysfunction ? TBLR1 mRNA levels in WAT are elevated under lipolytic conditions in mice and humans     

Seminal roots of wild and cultivated barley differentially respond to osmotic stress in gene expression,suberization, and hydraulic conductivity

Wild barley, Hordeum vulgare spp. spontaneum, has a wider genetic diversity than its cultivated progeny, Hordeum vulgare spp. vulgare. Osmotic stress leads to a series of different responses in wild barley seminal roots, ranging from no changes in suberization to enhanced endodermal suberization of certain zones and the formation of a suberized exodermis, which was not observed in the modern cultivars studied so far. Further, as a response to osmotic stress, the hydraulic conductivity of roots was not affected in wild barley, but it was 2.5-fold reduced in cultivated barley. In both subspecies, osmotic adjustment by increasing proline concentration and decreasing osmotic potential in roots was observed. RNA-sequencing indicated that the regulation of suberin biosynthesis and water transport via aquaporins were different between wild and cultivated barley. These results indicate that wild barley uses different strategies to cope with osmotic stress compared with cultivated barley. Thus, it seems that wild barley is better adapted to cope with osmotic stress by maintaining a significantly higher hydraulic conductivity of roots during water deficit.     

Field evaluation of abundance estimates under binomial and multinomial N-mixture models

Assessing and modelling abundance from animal count data is a very common task in ecology and management. Detection is arguably never perfect, but modern hierarchical models can incorporate detection probability and yield abundance estimates that are corrected for imperfect detection. Two variants of these models rely on counts of unmarked individuals, or territories (binomial N-mixture models, or binmix), and on detection histories based on territory-mapping data (multinomial N-mixture models or multimix). However, calibration studies which evaluate these two N-mixture model approaches are needed. We analysed conventional territory-mapping data (three surveys in 2014 and four in 2015) using both binmix and multimix models to estimate abundance for two common avian cavity-nesting forest species (Great Tit Parus major and Eurasian Blue Tit Cyanistes caeruleus). In the same study area, we used two benchmarks: occupancy data from a dense nestbox scheme and total number of detected territories. To investigate variance in estimates due to the territory assignment, three independent ornithologists conducted territory assignments. Nestbox occupancy yields a minimum number of territories, as some natural cavities may have been used, and binmix model estimates were generally higher than this benchmark. Estimates using the multimix model were slightly more precise than binmix model estimates. Depending on the person assigning the territories, the multimix model estimates became quite different, either overestimating or underestimating the ‘truth’. We conclude that N-mixture models estimated abundance reliably, even for our very small sample sizes. Territory-mapping counts depended on territory assignment and this carried over to estimates under the multimix model. This limitation has to be taken into account when abundance estimates are compared between sites or years. Whenever possible, accounting for such hidden heterogeneity in the raw data of bird surveys, via including a ‘territory editor’ factor, is recommended. Distributing the surveys randomly (in time and space) to editors may also alleviate this problem.     

Polymerase manager protein UmuD directly regulates Escherichia coli DNA polymerase III α binding to ssDNA

Replication by Escherichia coli DNA polymerase III is disrupted on encountering DNA damage. Consequently, specialized Y-family DNA polymerases are used to bypass DNA damage. The protein UmuD is extensively involved in modulating cellular responses to DNA damage and may play a role in DNA polymerase exchange for damage tolerance. In the absence of DNA, UmuD interacts with the α subunit of DNA polymerase III at two distinct binding sites, one of which is adjacent to the single-stranded DNA-binding site of α. Here, we use single molecule DNA stretching experiments to demonstrate that UmuD specifically inhibits binding of α to ssDNA. We predict using molecular modeling that UmuD residues D91 and G92 are involved in this interaction and demonstrate that mutation of these residues disrupts the interaction. Our results suggest that competition between UmuD and ssDNA for α binding is a new mechanism for polymerase exchange.     

Noise-Induced Inner Hair Cell Ribbon Loss Disturbs Central Arc Mobilization: A Novel Molecular Paradigm for Understanding Tinnitus

Increasing evidence shows that hearing loss is a risk factor for tinnitus and hyperacusis. Although both often coincide, a causal relationship between tinnitus and hyperacusis has not been shown. Currently, tinnitus and hyperacusis are assumed to be caused by elevated responsiveness in subcortical circuits. We examined both the impact of different degrees of cochlear damage and the influence of stress priming on tinnitus induction. We used (1) a behavioral animal model for tinnitus designed to minimize stress, (2) ribbon synapses in inner hair cells (IHCs) as a measure for deafferentation, (3) the integrity of auditory brainstem responses (ABR) to detect differences in stimulus-evoked neuronal activity, (4) the expression of the activity-regulated cytoskeletal protein, Arc, to identify long-lasting changes in network activity within the basolateral amygdala (BLA), hippocampal CA1, and auditory cortex (AC), and (5) stress priming to investigate the influence of corticosteroid on trauma-induced brain responses. We observed that IHC ribbon loss (deafferentation) leads to tinnitus when ABR functions remain reduced and Arc is not mobilized in the hippocampal CA1 and AC. If, however, ABR waves are functionally restored and Arc is mobilized, tinnitus does not occur. Both central response patterns were found to be independent of a profound threshold loss and could be shifted by the corticosterone level at the time of trauma. We, therefore, discuss the findings in the context of a history of stress that can trigger either an adaptive or nonadaptive brain response following injury.