Translational sensitivity of the Escherichia coli genome to fluctuating tRNA availability

The synthesis of protein from messenger RNA during translation is a highly dynamic process that plays a key role in controlling the efficiency and fidelity of genome-wide protein expression. The availability of aminoacylated transfer RNA (tRNA) is a major factor influencing the speed of ribosomal movement, which depending on codon choices, varies considerably along a transcript. Furthermore, it has been shown experimentally that tRNA availability can vary signifi-cantly under different growth and stress conditions, offering the cell a way to adapt translational dynamics across the genome. Existing models of translation have neglected fluctuations of tRNA pools, instead assuming fixed tRNA availabilities over time. This has lead to an incomplete under-standing of this process. Here, we show for the entire Escherichia coli genome how and to what extent translational speed profiles, which capture local aspects of translational elongation, respond to measured shifts in tRNA availability. We find that translational profiles across the genome are affected to differing degrees, with genes that are essential or related to fundamental processes such as transla-tion, being more robust than those linked to regula-tion. Furthermore, we reveal how fluctuating tRNA availability influences profiles of specific sequences known to play a significant role in translational control of gene expression

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

A LEED structural analysis of the Co(100) surface

The structure of the clean Co(1010) surface has been analysed by LEED. Application of a recently developed computational scheme reveals the prevalence of the termination A in which the two topmost layers exhibit a narrow spacing of 0.62 Å, corresponding to a 12.8(±0.5)% contraction with respect to the bulk value, while the spacing between the second and third layer is slightly expanded by 0.8(±0.2)%

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax

The future of metabolomics in ELIXIR.

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases

Sigmund Exner's (1887) einige beobachtungen über bewegungsnachbilder (some observations on movement aftereffects):an illustrated translation with commentary

In his original contribution, Exner’s principal concern was a comparison between the properties of different aftereffects, and particularly to determine whether aftereffects of motion were similar to those of color and whether they could be encompassed within a unified physiological framework. Despite the fact that he was unable to answer his main question, there are some excellent—so far unknown—contributions in Exner’s paper. For example, he describes observations that can be related to binocular interaction, not only in motion aftereffects but also in rivalry. To the best of our knowledge, Exner provides the first description of binocular rivalry induced by differently moving patterns in each eye, for motion as well as for their aftereffects. Moreover, apart from several known, but beautifully addressed, phenomena he makes a clear distinction between motion in depth based on stimulus properties and motion in depth based on the interpretation of motion. That is, the experience of movement, as distinct from the perception of movement. The experience, unlike the perception, did not result in a motion aftereffect in depth

The Chemical Translation Service—a web-based tool to improve standardization of metabolomic reports

Summary: Metabolomic publications and databases use different database identifiers or even trivial names which disable queries across databases or between studies. The best way to annotate metabolites is by chemical structures, encoded by the International Chemical Identifier code (InChI) or InChIKey. We have implemented a web-based Chemical Translation Service that performs batch conversions of the most common compound identifiers, including CAS, CHEBI, compound formulas, Human Metabolome Database HMDB, InChI, InChIKey, IUPAC name, KEGG, LipidMaps, PubChem CID+SID, SMILES and chemical synonym names. Batch conversion downloads of 1410 CIDs are performed in 2.5 min. Structures are automatically displayed

Strain-dependent dynamic re-alignment of collagen fibers in skeletal muscle extracellular matrix

Collagen fiber architecture within the skeletal muscle extracellular matrix (ECM) is significant to passive muscle mechanics. While it is thought that collagen fibers re-orient themselves in response to changes in muscle length, this has not been dynamically visualized and quantified within a muscle. The goal of this study was to measure changes in collagen alignment across a range of muscle lengths and compare the corresponding alignment to muscle mechanics. We hypothesized that collagen fibers dynamically increase alignment in response to muscle stretching, and this change in alignment is related to passive muscle stiffness. Further, we hypothesized that digesting collagen fibers with collagenase would reduce the re-alignment response to muscle stretching. Using DBA/2J and D2.mdx mice, we isolated extensor digitorum longus (EDL), soleus, and diaphragm muscles for collagenase or sham treatment and decellularization to isolate intact or collagenase-digested decellularized muscles (DCMs). These DCMs were mechanically tested and imaged using second harmonic generation microscopy to measure collagen alignment across a range of strains. We found that collagen alignment increased in a strain-dependent fashion, but collagenase did not significantly affect the strain-dependent change in alignment. We also saw that the collagen fibers in the diaphragm epimysium (surface ECM) and perimysium (deep ECM) started at different angles, but still re-oriented in the same direction in response to stretching. These robust changes in collagen alignment were weakly related to passive DCM stiffness. Overall, we demonstrated that the architecture of muscle ECM is dynamic in response to strain and is related to passive muscle mechanics. STATEMENT OF SIGNIFICANCE: Our study presents a unique visualization and quantification of strain-induced changes in muscle collagen fiber alignment as they relate to passive mechanics. Using dynamic imaging of collagen in skeletal muscle we demonstrate that as skeletal muscle is stretched, collagen fibers re-orient themselves along the axis of stretch and increase their alignment. The degree of alignment and the increase in alignment are each weakly related to passive muscle stiffness. Collagenase treatments further demonstrate that the basis for muscle Extracellular matrix stiffness is dependent on factors beyond collagen crosslinking and alignment. Together the study contributes to the knowledge of the structure-function relationships of muscle extracellular matrix to tissue stiffness relevant to conditions of fibrosis and aberrant stiffness

Translation error clusters induced by aminoglycoside antibiotics

Aminoglycoside antibiotics target the ribosome and induce mistranslation, yet which translation errors induce bacterial cell death is unclear. The analysis of cellular proteins by quantitative mass spectrometry shows that bactericidal aminoglycosides induce not only single translation errors, but also clusters of errors in full-length proteins in vivo with as many as four amino acid substitutions in a row. The downstream errors in a cluster are up to 10,000-fold more frequent than the first error and independent of the intracellular aminoglycoside concentration. The prevalence, length, and composition of error clusters depends not only on the misreading propensity of a given aminoglycoside, but also on its ability to inhibit ribosome translocation along the mRNA. Error clusters constitute a distinct class of misreading events in vivo that may provide the predominant source of proteotoxic stress at low aminoglycoside concentration, which is particularly important for the autocatalytic uptake of the drugs