bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues
Authors: Terry Erin E , Zhang Xiping , Hoffmann Christy , Hughes Laura D , Lewis Scott A , Li Jiajia , Riley Lance , Lahens Nicholas F , Gong Ming , Andrade Francisco , Esser Karyn A , Hughes Michael E.
Published: November 2017

Skeletal muscle comprises a family of diverse tissues with highly specialized morphology, function, and metabolism. Many acquired diseases – including HIV, COPD, cancer cachexia, critical illness myopathy, and sepsis – affect specific muscles while sparing others. Even monogenic muscular dystrophies tend to selectively affect certain muscle groups, despite their causative genetic mutations being present in all tissues. These observations suggest that factors intrinsic to muscle tissues influence their susceptibility to various disease mechanisms. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNA sequencing (RNA-seq) to profile global mRNA expression in a wide array of skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. This diversity is only partly explained by fiber type composition and developmental history, suggesting that specialized transcriptional profiles establish the functional identity of muscle tissues. We find conservation in the transcriptional profiles across species as well as between males and females, indicating that these data may be useful in predicting gene expression in related species. Notably, thousands of differentially expressed genes in skeletal muscle are associated with human disease, and hundreds of these genes encode targets of drugs on the market today. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. In addition to demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for generating testable hypotheses regarding the mechanisms that establish differential disease susceptibility in muscle.

Significance Statement

Skeletal muscles are a diverse family of tissues with a common contractile function but divergent morphology, development, and metabolism. One need only reflect on the different functions of limb muscles and the diaphragm to realize the highly specialized nature of these tissues. Nevertheless, every study of global gene expression has analyzed at most one representative skeletal muscle. Here we measure gene expression from 11 different skeletal muscles in mice and rats. We show that there is no such thing as a representative skeletal muscle, as gene expression profiles vary widely among the tissues analyzed. These data are an important resource for pharmacologists, tissue engineers, and investigators studying the mechanisms of cellular specialization.
Biophysics of object segmentation in a collision-detecting neuron
Authors: Dewell Richard B. , Gabbiani Fabrizio
Published: November 2017

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. The most studied such collision-detecting neuron within the optic lobe of grasshoppers has long served as a model for understanding collision avoidance behaviors and their underlying neural computations. Here, we demonstrate that this neuron detects the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation as its pharmacological block abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Our results elucidate how active dendritic channels produce neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.
AptaBlocks: Accelerating the Design of RNA-based Drug Delivery Systems
Authors: Wang Yijie , Hoinka Jan , Swiderski Piotr , Przytycka Teresa M
Published: November 2017

Synthetic RNA molecules are increasingly used to alter cellular functions. These successful applications indicate that RNA-based therapeutics might be able to target currently undruggable genes. However, to achieve this promise, an effective method for delivering therapeutic RNAs into specific cells is required. Recently, RNA aptamers emerged as promising delivery agents due to their ability of binding specific cell receptors. Crucially, these aptamers can frequently be internalized into the cells expressing these receptors on their surfaces. This property is leveraged in aptamer based drug delivery systems by combining such receptor-specific aptamers with a therapeutic “cargo” such that the aptamer facilitates the internalization of the cargo into the cell. The advancement of this technology however is contingent on an efficient method to produce stable molecular complexes that include specific aptamers and cargoes. A recently proposed experimental procedure for obtaining such complexes relies on conjugating the aptamer and the cargo with complementary RNA strands so that when such modified molecules are incubated together, the complementary RNA strands hybridize to form a double-stranded “sticky bridge” connecting the aptamer with its cargo. However, designing appropriate sticky bridge sequences guaranteeing the formation and stability of the complex while simultaneously not interfering with the aptamer or the cargo as well as not causing spurious aggregation of the molecules during incubation has proven highly challenging. To fill this gap, we developed AptaBlocks, a computational method to design sticky bridges to connect RNA-based molecules (blocks). AptaBlocks relies on a biophysically inspired theoretical model capturing the complex objectives of the design and yet is simple enough to allow for efficient parameter estimation. Given this model, the sticky bridge sequence is optimized using a Monte Carlo algorithm based on heat-bath transitions. The effectiveness of the algorithm has been verified computationally and experimentally. AptaBlocks can be used in variety of experimental settings and its preliminary version has already been leveraged to design an aptamer based delivery system for a cytotoxic drug targeting Pancreatic ductal adenocarcinoma cells. It is thus expected that AptaBlocks will play a substantial role in accelerating RNA-based drug delivery design.

AptaBlocks is available at https://github.com/wyjhxq/AptaBlocks.
Is whole-brain functional connectivity a neuromarker of sustained attention? Comment on Rosenberg & al. (2016)
Authors: Kristensen Simon Bang , Sandberg Kristian
Published: November 2017

Identification of neuromarkers accurately predicting cognitive characteristics from a single, standardised MRI scan could be tremendously useful in basic psychology and clinical practise. In a recent article, Rosenberg et al. (Nat Neurosci, 19, 165-171, 2016) argue that whole-brain functional network strength is a broadly applicable neuromarker of sustained attention. They claim that this marker accurately predicts performance from task related as well as resting state activity. Here, we discuss the applicability and generalizability in the context of three methodological concerns: Simulations show that the statistical methods for the 1) initial validation analyses as well as 2) internal validation using leave-one-out cross validation, are biased towards significance; 3) simple and complex models are compared suboptimally. Overall, we find that the article of Rosenberg et al. provides sufficient proof that network strength is associated with attentional capacity that it is not possible to say to which extent, and for this reason we argue that it cannot be concluded that the network is a broadly applicable neuromarker.
Structure of the eukaryotic cytoplasmic pre-40S ribosomal subunit
Authors: Scaiola Alain , Peña Cohue , Weisser Melanie , Böhringer Daniel , Leibundgut Marc , Klingauf-Nerurkar Purnima , Gerhardy Stefan , Panse Vikram Govind , Ban Nenad
Published: November 2017

Final maturation of eukaryotic ribosomes occurs in the cytoplasm and requires the sequential removal of associated assembly factors and processing of the immature 20S pre-RNA. Using cryo-electron microscopy (cryo-EM), we have determined the structure of a cytoplasmic pre-40S particle poised to initiate final maturation at a resolution of 3.4 Å. The structure reveals the extent of conformational rearrangements of the 3’ major and 3’ minor domains of the ribosomal RNA that take place during maturation, as well as the roles of the assembly factors Enp1, Ltv1, Rio2, Tsr1, and Pno1 in the process. Altogether, we provide a structural framework for the coordination of the final maturation events that drive a pre-40S particle towards the mature form capable of engaging in translation.
Structural centrosome aberrations promote non-cell-autonomous invasiveness
Authors: Ganier Olivier , Schnerch Dominik , Oertle Philipp , Lim Roderick Y. H. , Plodinec Marija , Nigg Erich A.
Published: November 2017

Centrosomes are the main microtubules organizing centers of animal cells. Although centrosome aberrations are common in tumors, their consequences remain subject to debate. Here, we studied the impact of structural centrosome aberrations, induced by deregulated expression of Ninein-like protein (NLP), on epithelial spheres grown in Matrigel matrices. We demonstrate that NLP-induced structural centrosome aberrations trigger the escape (’budding’) of living cells from epithelia. Remarkably, all cells disseminating into the matrix were undergoing mitosis. This invasive behavior reflects a novel mechanism that depends on the acquisition of two distinct properties. First, NLP-induced centrosome aberrations trigger a re-organization of the cytoskeleton, which stabilizes microtubules and weakens E-cadherin junctions during mitosis. Second, atomic force microscopy reveals that cells harboring these centrosome aberrations display increased stiffness. As a consequence, mitotic cells are pushed out of mosaic epithelia, particularly if they lack centrosome aberrations. We conclude that centrosome aberrations can trigger cell dissemination through a novel, non-cell autonomous mechanism, raising the prospect that centrosome aberrations contribute to the dissemination of metastatic cells harboring normal centrosomes.
The unconventional kinetoplastid kinetochore protein KKT4 tracks with dynamic microtubule tips
Authors: Llauró Aida , Hayashi Hanako , Bailey Megan E. , Wilson Alex , Ludzia Patryk , Asbury Charles L. , Akiyoshi Bungo
Published: November 2017

Kinetochores are multiprotein machines that drive chromosome segregation in all eukaryotes by maintaining persistent, load-bearing linkages between the chromosomes and the tips of dynamic spindle microtubules. Kinetochores in commonly studied eukaryotes are assembled from widely conserved components like the Ndc80 complex that directly binds microtubules. However, in evolutionarily-divergent kinetoplastid species such as Trypanosoma brucei, which causes sleeping sickness, the kinetochores assemble from a unique set of proteins lacking homology to any known microtubule-binding domains. Here we show that a kinetochore protein from T. brucei called KKT4 binds directly to microtubules, diffuses along the microtubule lattice, and tracks with disassembling microtubule tips. The protein localizes both to kinetochores and to spindle microtubules in vivo, and its depletion causes defects in chromosome segregation. We define a minimal microtubule-binding domain within KKT4 and identify several charged residues important for its microtubule-binding activity. Laser trapping experiments show that KKT4 can maintain load-bearing attachments to both growing and shortening microtubule tips. Thus, despite its lack of similarity to other known microtubule-binding proteins, KKT4 has key functions required for harnessing microtubule dynamics to drive chromosome segregation. We propose that it represents a primary element of the kinetochore-microtubule interface in kinetoplastids.
Cyclic-di-adenosine monophosphate (c-di-AMP) is required for osmotic regulation inStaphylococcus aureusbut dispensable for viability in anaerobic conditions
Authors: Zeden Merve S. , Schuster Christopher F. , Bowman Lisa , Zhong Qiyun , Williams Huw D. , Gründling Angelika
Published: November 2017

Cyclic di-adenosine monophosphate (c-di-AMP) is a recently discovered signaling molecule important for the survival of Firmicutes, a large bacterial group that includes notable pathogens such asStaphylococcus aureus. However, the exact role of this molecule has not been identified.dacA, theS. aureusgene encoding the diadenylate cyclase enzyme required for c-di-AMP production, cannot be deleted when bacterial cells are grown in rich medium, indicating that c-di-AMP is required for growth in this condition. Here, we report that anS. aureus dacAmutant can be generated in chemically defined medium. Consistent with previous findings, this mutant had a severe growth defect when cultured in rich medium. Using this growth defect in rich medium, we selected for suppressor strains with improved growth to identify c-di-AMP-requiring pathways. Mutations bypassing the essentiality ofdacAwere identified inalsTandopuD, encoding a predicted amino acid and osmolyte transporter, the latter of which we show here to be the main glycine betaine-uptake system inS. aureus. Inactivation of these transporters likely prevents the excessive osmolyte and amino acid accumulation in the cell, providing further evidence for a key role of c-di-AMP in osmotic regulation. Suppressor mutations were also obtained inhepS, hemB, ctaAandqoxB, coding for proteins required for respiration. Furthermore, we show thatdacAis dispensable for growth in anaerobic conditions. Together, these finding reveal an essential role for the c-di-AMP signaling network in aerobic, but not anaerobic, respiration inS. aureus.
A hyperthermophilic phage decoration protein suggests common evolutionary origin with Herpesvirus Triplex proteins and an anti-CRISPR protein
Authors: Stone Nicholas P. , Hilbert Brendan J. , Hidalgo Daniel , Halloran Kevin T. , Kelch Brian A.
Published: November 2017

Virus capsid proteins reproducibly self-assemble into regularly-shaped, stable shells that protect the viral genome from external environmental assaults, while maintaining the high internal pressure of the tightly packaged viral genome. To elucidate how capsids maintain stability under harsh conditions, we investigated the capsid components of a hyperthermophilic virus, phage P74-26. We determined the structure of a capsid protein gp87 and show that it has the same fold as trimeric decoration proteins that enhance the structural stability of capsids in many other phage, despite lacking significant sequence homology. We also find that gp87 is significantly more stable than its mesophilic homologs, reflecting the high temperature environment in which phage P74-26 thrives. Our analysis of the gp87 structure reveals that the core domain of the decoration protein is conserved in trimeric capsid components across numerous dsDNA viruses, including human pathogens such as Herpesviruses. Moreover, this core β-barrel domain is found in the anti-CRISPR protein AcrIIC1, which suggests a mechanism for the evolution of this broad spectrum Cas9 inhibitor. Our work illustrates the principles for increased stability of a thermophilic decoration protein, and extends the evolutionary reach of the core trimeric decoration protein fold.
The distance decay of similarity in tropical rainforests. A spatial point processes analytical formulation
Authors: Tovo Anna , Favretti Marco
Published: November 2017

In this paper we are concerned with the analytical description of the change in floristic composition (species turnover) with the distance between two plots of a tropical rainforest due to the clustering of the individuals of the different species. We describe the plant arrangement by a superposition of spatial point processes and in this framework we introduce an analytical function which represents the average spatial density of the Sørensen similarity between two infinitesimal plots at distancer. We see that the decay in similarity with the distance is essentially described by the pair correlation function of the superposed process and that it is governed by the most abundant species. We test our analytical model with empirical data obtained for the Barro Colorado Island and Pasoh rainforests. To this end we adopt the statistical estimator for the pair correlation function in [1] and we design a novel one for the Sørensen similarity. Furthermore, we test our analytical formula by modelling the forest study area with Neyman-Scott point processes. We conclude comparing the advantages of our approach with other ones existing in literature.
Muscarinic Lateral Excitation Contributes to Visual Object Segmentation during Collision Avoidance
Authors: Zhu Ying , Dewell Richard B. , Wang Hongxia , Gabbiani Fabrizio
Published: November 2017

Visual neurons specialized in tracking objects on a collision course are often finely tuned to their target stimuli as this is critical for survival. The presynaptic neural networks converging on these neurons and their role in tuning them remains poorly understood. We took advantage of well-known characteristics of one such neuron to investigate the properties of its presynaptic input network. We find a structure more complex than hitherto realized. In addition to dynamic lateral inhibition used to filter out background motion, presynaptic circuits include normalizing inhibition and short-range lateral excitatory interactions mediated by muscarinic acetylcholine receptors. These interactions preferentially boost responses to coherently expanding visual stimuli generated by colliding objects, as opposed to spatially incoherent controls, helping implement object segmentation. Hence, in addition to active dendritic conductances within collision detecting neurons, multiple layers of both inhibitory and excitatory presynaptic connections are needed to finely tune neural circuits for collision detection.
Which line to follow? The utility of different line-fitting methods to capture the mechanism of morphological scaling
Authors: Shingleton Alexander W.
Published: November 2017

Bivariate morphological scaling relationships describe how the size of two traits co-varies among adults in a population. In as much as body shape is reflected by the relative size of various traits within the body, morphological scaling relationships capture how body shape varies with size, and therefore have been used widely as descriptors of morphological variation within and among species. Despite their extensive use, there is continuing discussion over which line-fitting method should be used to describe linear morphological scaling relationships. Here I argue that the ‘best’ line-fitting method is the one that most accurately captures the proximate developmental mechanisms that generate scaling relationships. Using mathematical modeling, I show that the ‘best’ line-fitting method depends on the pattern of variation among individuals in the developmental mechanisms that regulate trait size, and the morphological variation this pattern of developmental variation produces. For Drosophila traits, this pattern of variation indicates that major axis regression is the best line-fitting method. For morphological traits in other animals, however, other line-fitting methods may be more accurate. I provide a simple web-based application for researchers to explore how different line-fitting methods perform on their own morphological data.
Leveraging multiple transcriptome assembly methods for improved gene structure annotation
Authors: Venturini Luca , Caim Shabhonam , Kaithakottil Gemy G , Mapleson Daniel L , Swarbreck David
Published: November 2017

The performance of RNA-Seq aligners and assemblers varies greatly across different organisms and experiments, and often the optimal approach is not known beforehand. Here we show that the accuracy of transcript reconstruction can be boosted by combining multiple methods, and we present a novel algorithm to integrate multiple RNA-Seq assemblies into a coherent transcript annotation. Our algorithm can remove redundancies and select the best transcript models according to user-specified metrics, while solving common artefacts such as erroneous transcript chimerisms. We have implemented this method in an open-source Python3 and Cython program, Mikado, available at https://github.com/lucventurini/Mikado.
The affinity of the S9.6 antibody for double-stranded RNAs impacts the mapping of R-loops in fission yeast
Authors: Hartono Stella R. , Malapert Amélie , Legros Pénélope , Bernard Pascal , Chédin Frédéric , Vanoosthuyse Vincent
Published: November 2017

R-loops, which result from the formation of stable DNA:RNA hybrids, can both threaten genome integrity and act as physiological regulators of gene expression and chromatin patterning. To characterize R-loops in fission yeast, we used the S9.6 antibody-based DRIPc-seq method to sequence the RNA strand of R-loops and obtain strand-specific R-loop maps at near nucleotide resolution. Surprisingly, preliminary DRIPc-seq experiments identified mostly RNase H-resistant but exosome-sensitive RNAs that mapped to both DNA strands and resembled RNA:RNA hybrids (dsRNAs), suggesting that dsRNAs form widely in fission yeast. We confirmed in vitro that S9.6 can immuno-precipitate dsRNAs and provide evidence that dsRNAs can interfere with its binding to R-loops. dsRNA elimination by RNase III treatment prior to DRIPc-seq allowed the genome-wide and strand-specific identification of genuine R-loops that responded in vivo to RNase H levels and displayed classical features associated with R-loop formation. We also found that most transcripts whose levels were altered by in vivo manipulation of RNase H levels did not form detectable R-loops, suggesting that prolonged manipulation of R-loop levels could indirectly alter the transcriptome. We discuss the implications of our work in the design of experimental strategies to probe R-loop functions.
Glutathione levels influence chronological life span ofSaccharomyces cerevisiaein a glucose-dependent manner
Authors: Tello-Padilla Mayra Fabiola , Perez-Gonzalez Alejandra Yudid , Canizal-García Melina , González-Hernández Juan Carlos , Cortes-Rojo Christian , Olivares-Marin Ivanna Karina , Madrigal-Perez Luis Alberto
Published: November 2017

Diet plays a key role in determining the longevity of the organisms since it has been demonstrated that glucose restriction increases lifespan whereas a high-glucose diet decreases it. However, the molecular basis of how diet leads to the aging process is currently unknown. We propose that the quantity of glucose that fuels respiration influences ROS generation and glutathione levels, and both chemical species impact in the aging process. Herein, we provide evidence that mutation of the geneGSH1diminishes glutathione levels. Moreover, glutathione levels were higher with 0.5% than in 10% glucose in thegsh1Δand WT strains. Interestingly, the chronological life span (CLS) was lowered in thegsh1Δstrain cultured with 10% glucose but not under dietary restriction. Thegsh1Δstrain also showed an inhibition of the mitochondrial respiration in 0.5 and 10% of glucose but only increased the H2O2levels under dietary restriction. These results correlate well with the GSH/GSSG ratio, which showed a decrease ingsh1Δstrain cultured with 0.5% glucose. Altogether these data indicate that glutathione has a major role in the function of electron transport chain (ETC) and is essential to maintain life span ofSaccharomyces cerevisiaein 10% glucose.
Deep2Full: Predictive model for complementing phenotypic outcomes in a deep mutational scan using protein sequence and structure information
Authors: Sruthi C. K. , Prakash Meher K.
Published: November 2017

Large scale mutagenesis experiments are becoming possible owing to the advancement in the sequencing technologies and high throughput screening. Deep mutational scans perform exhaustive single-point muta-tions on a protein and probe their phenotypic effects. Performing a full scan with site-directed mutations of all the amino acid residues in a protein may not be practical, and may not even be required, especially if predictive computational models can be developed. Computational models are however naive to cellular response in the myriads of assay-conditions. In order to develop the realistic paradigm of assay context-aware predictive hybrid models, we combine minimal deep mutational studies with computational models and pre-dict the phenotypic outcomes quantitatively. Structural, sequence and co-evolutionary information along with partial deep mutational scan data was included to capture the phenotypic relevance of the mutations to the specific screening criterion. The model reliably predicts the fitness outcomes of hundreds of randomly selected amino acid mutations in β-lactamase, when the phenotypic fitness data from as few as 15% of the full mutation is available. Interestingly, the predictive capabilities are better with a random set of mutations rather than with a systematic substitution of all amino acids to alanine, asparagine and histidine (ANH). The model can potentially be extended for predicting the phenotypic outcomes at other concentrations of the stressor by carefully analyzing the dose-response curves of a representative set of mutations.

Author Summary

Mutations are the minor changes in protein sequences, with incommensurately high consequences for their function. Many severe diseases can occur with simple single point mutations. An interesting way of studying these mutations is not to isolate the protein from its natural conditions, but rather study how the fitness of the cell improves or decreases in response to these mutations. Whether it is for understanding disease biology or for bio-engineering applications it is important to quantify the impact of mutations on the cellular fitness. An experimental paradigm has evolved which has improved the ability to sample several hundred thousands of mutation-fitness relations using high throughput screening. However, since these are very specialized experiments, the question is if the number of such experiments required can be minimized, by using computer models to complement the rest of the fitness predictions. In this work we introduce this new paradigm which uses computer model trained on a partial deep mutation scan data, to predict the fitness variations in a full mutations scan that could also be repeated under multiple experimental conditions like drug concentrations.
Deciphering the histone code to build the genome structure
Authors: Prakash Kirti , Fournier David
Published: November 2017

Histones are punctuated with small chemical modifications that alter their interaction with DNA. One attractive hypothesis stipulates that certain combinations of these histone modifications may function, alone or together, as a part of a predictive histone code to provide ground rules for chromatin folding. We consider four features that relate histone modifications to chromatin folding: charge neutralisation, molecular specificity, robustness and evolvability. Next, we present evidence for the association among different histone modifications at various levels of chromatin organisation and show how these relationships relate to function such as transcription, replication and cell division. Finally, we propose a model where the histone code can set critical checkpoints for chromatin to fold reversibly between different orders of the organisation in response to a biological stimulus.
Within-host dynamics explain patterns of antibiotic resistance in commensal bacteria
Authors: Davies Nicholas G. , Flasche Stefan , Jit Mark , Atkins Katherine E.
Published: November 2017

The spread of antibiotic resistance, a major threat to human health, is poorly understood. Empirically, resistant strains gradually increase in prevalence as antibiotic consumption increases, but current mathematical models predict a sharp transition between full sensitivity and full resistance. In other words, we do not understand what drives persistent coexistence between resistant and sensitive strains of disease-causing bacteria in host populations. Without knowing what drives patterns of resistance, we cannot accurately predict the impact of potential strategies for managing resistance. Here, we show that within-host dynamics—bacterial growth, strain competition, and host immune responses—promote frequency-dependent selection for resistant strains, explaining patterns of resistance at the population level. By capturing these processes in a parsimonious mathematical framework, we resolve a long-standing conflict between theory and observation. Our models capture widespread coexistence for multiple bacteria-drug combinations across 30 European countries and explain associations between carriage prevalence and resistance prevalence among bacterial subtypes. A mechanistic understanding of resistance evolution is needed to accurately forecast the impact and effectiveness of resistance-management strategies.
Chronic ethanol ingestion impairs Drosophila melanogaster health in a microbiome-dependent manner
Authors: Chandler James Angus , Innocent Lina Victoria , Huang Isaac L. , Yang Jane L. , Eisen Michael B. , Ludington William B.
Published: November 2017

Ethanol is one of the worlds most abused drugs yet the impacts of chronic ethanol consumption are debated. Ethanol is a prevalent component in the diets of diverse animals and can act as a nutritional source, behavior modulator, and a toxin. The source of ethanol is microbes, which can both produce and degrade ethanol, and the gut microbiome has been associated with differential health outcomes in chronic alcoholism. To disentangle the various and potentially interacting roles of bacteria and ethanol on host health, we developed a model for chronic ethanol ingestion in the adult fruit fly, Drosophila melanogaster, which naturally consumes a diet between 0 and 5% ethanol. We took advantage of the tractability of the fly microbiome, which can be experimentally removed to separate the direct and indirect effects of commensal microbes. We found that moderate to heavy ethanol ingestion decreased lifespan and reproduction, without causing inebriation. These effects were more pronounced in flies lacking a microbiome, but could not be explained by simple bacterial degradation of ethanol. However, moderate ethanol ingestion increased reproduction in bacterially-colonized flies, relative to bacteria-free flies. Ethanol decreased intestinal stem cell turnover in bacterially-colonized flies and decreased intestinal barrier failure and increased fat content in all flies, regardless of microbiome status. Analysis of host gene expression finds that ethanol triggers the innate immune response, but only in flies colonized with bacteria. Taken together we show that, chronic ethanol ingestion negatively impacts fly health in a microbiome-dependent manner.
Realistic vOlumetric-Approach to Simulate Transcranial Electric Stimulation – ROAST – a fully automated open-source pipeline
Authors: Huang Yu , Datta Abhishek , Bikson Marom , Parra Lucas C.
Published: November 2017

Objective

Research in the area of transcranial electrical stimulation (TES) often relies on computational models of current flow in the brain. Models are built based on magnetic resonance images (MRI) of the human head to capture detailed individual anatomy. To simulate current flow on an individual, the subject’s MRI is segmented, virtual electrodes are placed on this anatomical model, the volume is tessellated into a mesh, and a finite element model (FEM) is solved numerically to estimate the current flow. Various software tools are available for each of these steps, as well as processing pipelines that connect these tools for automated or semi-automated processing. The goal of the present tool – ROAST – is to provide an end-to-end pipeline that can automatically process individual heads with realistic volumetric anatomy leveraging open-source software and custom scripts to improve segmentation and execute electrode placement.

Approach

ROAST combines the segmentation algorithm of SPM8, a Matlab script for touch-up and automatic electrode placement, the finite element mesher iso2mesh and the solver getDP. We compared its performance with commercial FEM software, and SimNIBS, a well-established open-source modeling pipeline.

Main Results

The electric fields estimated with ROAST differ little from the results obtained with commercial meshing and FEM solving software. We also do not find large differences between the various automated segmentation methods used by ROAST and SimNIBS. We do find bigger differences when volumetric segmentation are converted into surfaces in SimNIBS. However, evaluation on intracranial recordings from human subjects suggests that ROAST and SimNIBS are not significantly different in predicting field distribution, provided that users have detailed knowledge of SimNIBS.

Significance

We hope that the detailed comparisons presented here of various choices in this modeling pipeline can provide guidance for future tool development. We released ROAST as an open-source, easy-to-install and fully-automated pipeline for individualized TES modeling.
MODE-TASK: Large-scale protein motion tools
Authors: Ross Caroline , Nizami Bilal , Glenister Michael , Amamuddy Olivier Sheik , Atilgan Ali Rana , Atilgan Canan , Tastan Bishop Özlem
Published: November 2017

MODE-TASK, a novel software suite, comprises Principle Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using molecular dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive.

Availability and Implementation

MODE-TASK has been open-sourced, and is available for download from https://github.com/RUBi-ZA/MODE-TASK, implemented in Python and C++.

Supplementary information

Documentation available at http://mode-task.readthedocs.io.
EpiGraph: an open-source platform to quantify epithelial organization
Authors: Vicente-Munuera Pablo , Gómez-Gálvez Pedro , Tetley Robert J. , Forja Cristina , Tagua Antonio , Letrán Marta , Tozluoglu Melda , Mao Yanlan , Escudero Luis M.
Published: November 2017

During development, cells must coordinate their differentiation with their growth and organization to form complex multicellular structures such as tissues and organs. Healthy tissues must maintain these structures during homeostasis. Epithelia are packed ensembles of cells from which the different tissues of the organism will originate during embryogenesis. A large barrier to the analysis of the morphogenetic changes in epithelia is the lack of simple tools that enable the quantification of cell arrangements. Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform FIJI. This makes EpiGraph very user friendly, with no programming skills required.
Programming of macrophages by apoptotic cancer cells inhibits cancer progression through exosomal PTEN and PPARγ ligands
Authors: Kim Yong-Bae , Ahn Young-Ho , Lee Jin-Hwa , Kang Jihee Lee
Published: November 2017

Apoptotic cell clearance by phagocytes is essential in tissue homeostasis. We demonstrated that conditioned medium (CM) from macrophages exposed to apoptotic cancer cells inhibits epithelial-mesenchymal transition (EMT), migration, and invasion of cancer cells with the acquisition of cancer-stem–like traits. Apoptotic 344SQ (ApoSQ) cell-induced PPARγ activity in macrophages caused increased PTEN levels, secreted in exosomes. ApoSQ-exposed CM from PTEN knockdown cells failed to enhance PTEN in recipient 344SQ cells, restore cellular polarity, and exert anti-EMT and anti-invasive effects. The CM which deficient of PPARγ ligands could not reverse the suppression of PPARγ activity and PTEN and consequently failed to the prevent EMT process. Moreover, single injection of ApoSQ cells inhibited lung metastasis in syngeneic mice with enhanced PPARγ/PTEN signaling both in tumor-associated macrophages and tumor cells. PPARγ antagonist GW9662 reversed PTEN signaling and anti-metastatic effect. Thus, apoptotic cancer cell therapy may offer a new strategy for the prevention of metastasis.
Eco-evolutionary dynamics in metacommunities: ecological inheritance, helping within- and harming between-species
Authors: Mullon Charles , Lehmann Laurent
Published: November 2017

Understanding selection on intra- and inter-specific interactions that take place in dispersal-limited communities is a challenge for ecology and evolutionary biology. The problem is that local demographic stochasticity generates eco-evolutionary dynamics that are generally too complicated to make tractable analytical investigations. Here, we circumvent this problem by approximating the selection gradient on a quantitative trait that influences local community dynamics, assuming that such dynamics are deterministic with a stable fixed point. We nonetheless incorporate unavoidable kin selection effects arising from demographic stochasticity. Our approximation reveals that selection depends on how an individual expressing a trait-change influences: (1) its own fitness and the fitness of its current relatives; and (2) the fitness of its downstream relatives through modifications of local ecological conditions (i.e., through ecological inheritance). Mathematically, the effects of ecological inheritance on selection are captured by dispersal-limited versions of press-perturbations of community ecology. We use our approximation to investigate the evolution of helping within- and harming between-species when these behaviours influence demography. We find that individually costly helping evolves more readily when intra-specific competition is for material resources rather than for space because in this case, the costs of kin competition are paid by downstream relatives. Similarly, individually costly harming between species evolves when it alleviates downstream relatives from inter-specific competition. Beyond these examples, our approximation can help better understand the influence of ecological inheritance on a variety of eco-evolutionary dynamics in metacommunities, from consumer-resource and predator-prey coevolution to selection on mating systems with demographic feedbacks.
Diversification of heart progenitor cells by EGF signaling and differential modulation of ETS protein activity
Authors: Schwarz Benjamin , Hollfelder Dominik , Scharf Katharina , Hartmann Leonie , Reim Ingolf
Published: November 2017

For coordinated circulation, vertebrate and invertebrate hearts require stereotyped arrangements of diverse cell populations. This study explores the process of cardiac cell diversification in theDrosophilaheart, focusing on the two major cardioblast subpopulations: generic working myocardial cells and inflow valve-forming ostial cardioblasts. By screening a large collection of randomly induced mutants we identified several genes involved in cardiac patterning. Further analysis revealed an unexpected, specific requirement of EGF signaling for the specification of generic cardioblasts and a subset of pericardial cells. We demonstrate that the Tbx20 ortholog Midline acts as a direct target of the EGFR effector Pointed to repress ostial fates. Furthermore, we identified Edl/Mae, an antagonist of the ETS factor Pointed, as a novel cardiac regulator crucial for ostial cardioblast specification. Combining these findings we propose a regulatory model in which the balance between activation of Pointed and its inhibition by Edl controls cardioblast subtype-specific gene expression.
A repetitive mutation and selection system for bacterial evolution to increase the specific affinity to pancreatic cancer cells
Authors: Osawa Masaki
Published: November 2017

It is difficult to target and kill cancer cells. One possible approach is to mutate bacteria to enhance their binding to cancer cells. In this study, Gram-negative bacteria Escherichia coli and Gram-positive bacteria Bacillus subtilis were randomly mutated, and then were positively and negatively selected for binding cancer and normal cells. With repetitive mutation and selection both bacteria successfully evolved to increase affinity to the pancreatic cancer cell line (Mia PaCa-2) but not normal cells (HPDE: immortalized human pancreatic ductal epithelial cell line). The mutant E. coli and B. subtilis strains could bind to Mia PaCa-2 cells about 10 and 25 times more than to HPDE cells. The selected E. coli, strain had mutations in biofilm-related genes and the regulatory region for a type I pilus gene. Consistent with type I pili involvement, mannose could inhibit the binding to cells. However, the results suggest that weak but specific binding is involved in the initial step of adhesion. To kill Mia PaCa-2 cells, hemolysin was expressed in the mutant strain. The hemolysin that was released from the mutant strain could kill Mia PaCa-2 cells. This type of mutation/selection strategy may be applicable to other combinations of cancer cells and bacterial species.
L-tyrosine supplementation is not therapeutic for skeletal muscle dysfunction in zebrafish and mouse models of dominant skeletal muscle α-actin nemaline myopathy
Authors: Messineo Adriana M. , Gineste Charlotte , Sztal Tamar E. , McNamara Elyshia L. , Vilmen Christophe , Ogier Augustin C. , Hahne Dorothee , Bendahan David , Laing Nigel G. , Bryson-Richardson Robert J. , Gondin Julien , Nowak Kristen J.
Published: November 2017

Nemaline myopathy (NM) is a skeletal muscle disorder with no curative treatment. Although L-tyrosine administration has been indicated to provide benefit to patients, previous studies have been limited due to sample size or not testing for raised L-tyrosine levels. We evaluated the efficacy of L-tyrosine treatment to improve skeletal muscle function in three animal models of NM caused by skeletal muscle α-actin (ACTA1) mutations. Firstly we determined the maximum safest L-tyrosine concentration for inclusion in the water of wildtype zebrafish. We then treated NM TgACTA1D286G-eGFPzebrafish from 24 hours post fertilization with the highest safe L-tyrosine dose (10 µM). At 6 days post fertilization, no significant improvement was detected in skeletal muscle function (swimming distance). We also determined the highest safe L-tyrosine dose for dietary L-tyrosine supplementation to wildtype mice. Next we treated the NM TgACTA1D286Gmouse model continuously from preconception with 2% L-tyrosine supplemented to regular feed. We examined skeletal muscles at 6–7 weeks using indicators of skeletal muscle integrity: bodyweight, voluntary running wheel and rotarod performance, all parameters previously shown to be reduced in TgACTA1D286Gmice. The L-tyrosine treatment regime did not result in any improvement of these parameters, despite significant elevation of free L-tyrosine levels in sera (57%) and quadriceps muscle (45%) of treated TgACTA1D286Gmice. Additionally, we assessed the effects of 4 weeks of 2% L-tyrosine dietary supplementation on skeletal muscle function of older (6-7 month old) NM TgACTA1D286Gand KIActa1H40Ymice. This dosing regime did not improve decreased bodyweight, nor the mechanical properties, energy metabolism, or atrophy of skeletal muscles in these NM models. Together these findings demonstrate that with the treatment regimes and doses evaluated, L-tyrosine does not therapeutically modulate dysfunctional skeletal muscles in NM animal models with dominantACTA1mutations. Therefore this study yields important information on aspects of the clinical utility of L-tyrosine forACTA1NM.

Summary statement

Despite previous encouraging reports, this study utilising zebrafish and mouse models of nemaline myopathy shows no therapeutic benefit on skeletal muscle functionality in response to L-tyrosine supplementation.
A synergistic transcriptional regulation of olfactory genes derives complex behavioral responses in the mosquito Anopheles culicifacies
Authors: De Tanwee Das , Thomas Tina , Verma Sonia , Singla Deepak , Rawal Charu , Srivastava Vartika , Sharma Punita , Kumari Seena , Tevatiya Sanjay , Rani Jyoti , Hasija Yasha , Pandey Kailash C , Dixit Rajnikant
Published: November 2017

Decoding the molecular basis of host seeking and blood feeding behavioral evolution/adaptation in the adult female mosquito may provide an opportunity to design new molecular strategy to disrupt human-mosquito interactions. However, despite the great progress in the field of mosquito olfaction and chemo-detection, little is known that how the sex-specific specialization of the olfactory system enables adult female mosquitoes to derive and manage complex blood feeding associated behavioral responses. A comprehensive RNAseq analysis of prior and post blood meal olfactory system of An. culicifacies mosquito revealed that a minor but unique change in the nature and regulation of key olfactory genes play a pivotal role in managing diverse behavioral responses. Age dependent transcriptional profiling demonstrated that adult female mosquito’s chemosensory system gradually learned and matured to drive the host-seeking and blood feeding behavior at the age of 5-6 days. A zeitgeber time scale expression analysis of Odorant Binding Proteins (OBPs) unravels unique association with a late evening to midnight peak biting time. Blood meal-induced switching of unique sets of OBP genes and Odorant Receptors (ORs) expression coincides with the change in the innate physiological status of the mosquitoes. Blood meal follows up experiments provide enough evidence that how a synergistic and concurrent action of OBPs-ORs may drive ‘prior and post blood meal’ complex behavioral events. Finally, tissue-specific gene expression analysis and molecular modelling predicted two uncharacterized novel sensory appendages proteins (SAP-1 & SAP2) unique to An. culicifacies mosquito and may play a central role in the host-seeking behavior.

Significance

Evolution and adaptation of blood feeding behavior not only favored the reproductive success of adult female mosquito but also make them an important disease vectors. Immediately after emergence, an environmental exposure may favor the broadly tuned olfactory system of mosquitoes to derive complex behavioral responses. But, how these olfactory derived genetic factors manage female specific ‘pre and post’ blood meal associated complex behavioral responses are not well known. We unraveled synergistic actions of olfactory factors governs an innate to prime learning strategy to facilitate rapid blood meal acquisition and downstream behavioral activities. A species-specific transcriptional profiling and an in-silico analysis predict novel ‘sensory appendages protein’, as a unique target to design disorientation strategy against the mosquito Anopheles culicifacies.