bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time analysis of nanopore-based metagenomic sequencing from orthopaedic device infection
Authors: Sanderson Nicholas D , Street Teresa L , Foster Dona , Swann Jeremy , Atkins Bridget L. , Brent Andrew J. , McNally Martin A. , Oakley Sarah , Taylor Adrian , Peto Tim E A , Crook Derrick , Eyre David W 
Published: November 2017

AbstractProsthetic joint infections are clinically difficult to diagnose and treat. Previously, we demonstrated metagenomic sequencing on an Illumina MiSeq replicates the findings of current gold standard microbiological diagnostic techniques. Nanopore sequencing offers advantages in speed of detection over MiSeq. Here, we compare direct-from-clinical-sample metagenomic Illumina sequencing with Nanopore sequencing, and report a real-time analytical pathway for Nanopore sequence data, designed for detecting bacterial composition of prosthetic joint infections.DNA was extracted from the sonication fluids of seven explanted orthopaedic devices, and additionally from two culture negative controls, and was sequenced on the Oxford Nanopore Technologies MinION platform. A specific analysis pipeline was assembled to overcome the challenges of identifying the true infecting pathogen, given high levels of host contamination and unavoidable background lab and kit contamination.The majority of DNA classified (>90%) was host contamination and discarded. Using negative control filtering thresholds, the species identified corresponded with both routine microbiological diagnosis and MiSeq results. By analysing sequences in real time, causes of infection were robustly detected within minutes from initiation of sequencing.We demonstrate initial proof of concept that metagenomic MinION sequencing can provide rapid, accurate diagnosis for prosthetic joint infections. We demonstrate a novel, scalable pipeline for real-time analysis of MinION sequence data. The high proportion of human DNA in extracts prevents full genome analysis from complete coverage, and methods to reduce this could increase genome depth and allow antimicrobial resistance profiling.
Neurotransmitter imbalance in the brain and Alzheimer’s pathology
Authors: Snowden Stuart G. , Ebshiana Amera A. , Hye Abdul , Pletnikova Olga , O’Brien Richard , Yang An , Troncoso John , Legido-Quigley Cristina , Thambisetty Madhav 
Published: November 2017

ABSTRACTINTRODUCTIONThree of the four treatments for Alzheimer’s disease are cholinesterase inhibitors targeting the pathological reduction of acetylcholine levels. Here we aimed to determine the role of other neurotransmitter pathways in AD pathology.METHODSTissue samples were obtained from three groups, controls, AD and ‘asymptomatic AD’ i.e. cognitively normal individuals that had significant AD neuropathology. Three brain areas were studied, the middle frontal gyrus (MFG) the inferior temporal gyrus (ITG) and the cerebellum.RESULTS11 of 15 measured metabolites were shown to be associated with disease. Decreases in dopamine were seen in the ASYMAD group in the MFG when compared to control and AD patients (FC=0.78, p=4.1×10-3). In AD patients changes were mainly seen in the ITG’s inhibitory GABAergic system.DISCUSSIONThese results indicate that dopamine could be depleted in brains with Alzheimer’s pathology but intact cognition, while and imbalance of several neurotransmitters is evident in the brain of AD patients.
Atypical domain communication and domain functions of a Hsp110 chaperone
Authors: Kumar Vignesh , Peter Joshua Jebakumar , Sagar Amin , Ray Arjun , Ashish  , mapa koyeli 
Published: November 2017

AbstractHsp110s are well recognized nucleotide exchange factors (NEFs) of Hsp70s, in addition they are implicated in various aspects of cellular proteostasis as discrete chaperones with yet enigmatic molecular mechanism. Stark similarity in domain organization and structure between Hsp110s and Hsp70s, is easily discernible although the nature of domain communication and domain functions of Hsp110s are still puzzling. Here, we report atypical domain communication of yeast Hsp110, Sse1 using single molecule FRET, small angle X-ray scattering measurements (SAXS) and Molecular Dynamic simulations. Our data show that Sse1 lacks typical domain movements as exhibited by Hsp70s, albeit it undergoes unique structural alteration upon nucleotide and substrate binding. Hsp70-like domain-movements can be artificially salvaged in chimeric constructs of Hsp110-Hsp70 although such salvaging proves detrimental for the NEF activity of the protein. Furthermore, we show that substrate binding domain (SBD) of Hsp110, chaperones self, as well as foreign nucleotide binding domains (NBD). Interestingly, the substrate binding specificity of Hsp110 is largely determined by its NBD rather than SBD, the latter being the foremost substrate binding region for Hsp70s.
Newly identified relatives of botulinum neurotoxins shed light on their molecular evolution
Authors: Mansfield MJ , Wentz TG , Zhang S , Lee EJ , Dong M , Sharma SK , Doxey AC 
Published: November 2017

AbstractThe evolution of bacterial toxins is a central question to understanding the origins of human pathogens and infectious disease. Through genomic data mining, we traced the evolution of the deadliest known toxin family, clostridial neurotoxins, comprised of tetanus and botulinum neurotoxins (BoNT). We identified numerous uncharacterized lineages of BoNT-related genes in environmental species outside ofClostridium, revealing insights into their molecular ancestry. Phylogenetic analysis pinpointed a sister lineage of BoNT-like toxins in the gram-negative organism,Chryseobacterium piperi, that exhibit distant homology at the sequence level but preserve overall domain architecture. Resequencing and assembly of theC. piperigenome confirmed the presence of BoNT-like proteins encoded within two toxin-rich gene clusters. AC. piperiBoNT-like protein was validated as a novel toxin that induced necrotic cell death in human kidney cells. Mutagenesis of the putative active site abolished toxicity and indicated a zinc metalloprotease-dependent mechanism. TheC. piperitoxin did not cleave common SNARE substrates of BoNTs, indicating that BoNTs have diverged from related families in substrate specificity. The new lineages of BoNT-like toxins identified by computational methods represent evolutionary missing links, and suggest an origin of clostridial neurotoxins from ancestral toxins present in environmental bacteria.Significance statementThe origins of bacterial toxins that cause human disease is a key question in our understanding of pathogen evolution. To explore this question, we searched genomes for evolutionary relatives of the deadliest biological toxins known to science, botulinum neurotoxins. Genomic and phylogenetic analysis revealed a group of toxins in theChryseobacterium piperigenome that are a sister lineage to botulinum toxins. Genome sequencing of this organism confirmed the presence of toxin-rich gene clusters, and a predictedC. piperitoxin was shown to induce necrotic cell death in human cells. These newly predicted toxins are missing links in our understanding of botulinum neurotoxin evolution, revealing its origins from an ancestral family of toxins that may be widespread in the environment.
Ethology as a physical science
Authors: Brown André EX , de Bivort Benjamin 
Published: November 2017

AbstractBehaviour is the ultimate output of an animal’s nervous system and choosing the right action at the right time can be critical for survival. The study of the organisation of behaviour in its natural context, ethology, has historically been a primarily qualitative science. A quantitative theory of behaviour would advance research in neuroscience as well as ecology and evolution. However, animal posture typically has many degrees of freedom and behavioural dynamics vary on timescales ranging from milliseconds to years, presenting both technical and conceptual challenges. Here we review 1) advances in imaging and computer vision that are making it possible to capture increasingly complete records of animal motion and 2) new approaches to understanding the resulting behavioural data sets. With the right analytical approaches, these data are allowing researchers to revisit longstanding questions about the structure and organisation of animal behaviour and to put unifying principles on a quantitative footing. Contributions from both experimentalists and theorists are leading to the emergence of a physics of behaviour and the prospect of discovering laws and developing theories with broad applicability. We believe that there now exists an opportunity to develop theories of behaviour which can be tested using these data sets leading to a deeper understanding of how and why animals behave.
Efficient online-group-screening designs for agent identification
Authors: Gao Tianxiang , Finkel Omri , Dangl Jeff , Jojic Vladimir 
Published: November 2017

AbstractIdentifying significant causal agents among a large number of candidates is challenging. When experimental resources are limited, exhaustively screening a large number of agents for the desired effect could incur a large cost and take a substantial amount of time. However, in many large scale experiments, such as high-throughput screening (HTS), the ratio of causal to non-causal agents is usually very low.In this paper, we introduce a group-screening strategy to efficiently screen causal agents by grouping them into treatments. Our analysis shows that when a large number of candidates factors are screened and true agent percentage is very low (less than 1%), even in the worst case we could save up to 80% of the experiment runs. In the case where experiments span many rounds, we provide an online version of the group-screening that can determine the best strategy automatically based on the existing results. We applied this method to a real HTS experiment with 50,000 candidates that would require 9 rounds to finish in an exhaustive case. Our analysis showed that by applying the online-group-screening method, in the worst case, we can use 3 rounds and 19.7% (9828/50000) total tests to identify all the agents.Finally, we show that with minor modifications, this framework extends to more complex agent discovery problems.
Fast ordered sampling of DNA sequence variants
Authors: Greenberg Anthony J. 
Published: November 2017

AbstractExplosive growth in the amount of genomic data is matched by increasing power of consumer-grade computers. Even applications that require powerful servers can be quickly tested on desktop or laptop machines if we can generate representative samples from large data sets. I describe a fast and memory-efficient implementation of an on-line sampling method developed for tape drives 30 years ago. Focusing on genotype files, I test the performance of this technique on modern solid-state and spinning hard drives, and show that it performs well compared to a simple sampling scheme. I illustrate its utility by developing a method to quickly estimate genome-wide patterns of linkage disequilibrium (LD) decay with distance. I provide open-source software that samples loci from several variant format files, a separate program that performs LD decay estimates, and a C++ library that lets developers incorporate these methods into their own projects.
A Multilevel Computational Characterization of Endophenotypes in Addiction
Authors: Fiore Vincenzo G. , Ognibene Dimitri , Adinoff Bryon , Gu Xiaosi 
Published: November 2017

AbstractSubstance use disorders are characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction, and have not yet been able to identify mechanisms that can account for the multifaceted phenotypic behaviors reported in literature. To investigate this knowledge gap theoretically, here we simulated phenotypic variations in addiction symptomology and responses to putative treatments, using both a neural model based on cortico-striatal circuit dynamics, and an algorithmic model of reinforcement learning. These simulations rely on the widely accepted assumption that both the ventral, model-based, goal-directed system and the dorsal, model-free, habitual system are vulnerable to extra-physiologic dopamine reinforcements triggered by drug consumption. We found that endophenotypic differences in the balance between the two circuit or control systems resulted in an inverted U-shape in optimal choice behavior. Specifically, greater unbalance led to a higher likelihood of developing addiction and more severe drug-taking behaviors. Furthermore, endophenotypes with opposite asymmetrical biases among cortico-striatal circuits expressed similar addiction behaviors, but responded differently to simulated treatments, suggesting personalized treatment development could rely on endophenotypic rather than phenotypic differentiations. We propose our simulated results, confirmed across neural and algorithmic levels of analysis, inform on a fundamental and, to date, neglected quantitative method to characterize clinical heterogeneity in addiction.
The global distribution and spread of the mobilized colistin resistance gene mcr-1
Authors: Wang Ruobing , van Dorp Lucy , Shaw Liam , Bradley Phelim , Wang Qi , Wang Xiaojuan , Jin Longyang , Zhang Qing , Liu Yuqing , Rieux Adrien , Dorai-Schneiders Thamarai , Weinert Lucy Anne , Iqbal Zamin , Didelot Xavier , Wang Hui , Balloux Francois 
Published: November 2017

AbstractColistin represents one of the very few available drugs for treating infections caused by carbapenem resistant Enterobacteriaceae (CRE). As such, the recent plasmid-mediated spread of the mobilized colistin resistance gene mcr-1 poses a significant public health threat requiring global monitoring and surveillance. In this work, we characterize the global distribution of mcr-1 using a dataset of 457 mcr-1 positive sequenced isolates consisting of currently publicly available mcr-1 carrying sequences combined with an additional 110 newly sequenced mcr-1 positive isolates from China. We find mcr-1 in a diversity of plasmid backgrounds but identify an immediate background common to all mcr-1 sequences. Our analyses establish that all mcr-1 elements in circulation descend from the same initial mobilization of mcr-1 by an ISApl1 transposon in the mid 2000s (2002-2008; 95% higher posterior density), followed by a dramatic demographic expansion, which led to its current global distribution. Our results provide the first systematic phylogenetic analysis of the origin and spread of mcr-1, and emphasize the importance of understanding the movement of mobile elements carrying antibiotic resistance genes across multiple levels of genomic organization.
Wide-field dynamic monitoring of immune cell trafficking in murine models of glioblastoma
Authors: SoRelle Elliott D. , Yecies Derek , Liba Orly , Bennett F. Chris , Graef Claus Moritz , Dutta Rebecca , Mitra Siddhartha S. , Joubert Lydia-Marie , Cheshier Samuel H. , Grant Gerald A. , de la Zerda Adam 
Published: November 2017

AbstractLeukocyte populations, especially tumor-associated macrophages (TAMs), are capable of mediating both anti- and pro-tumor processes and play significant roles in the tumor microenvironment. Moreover, TAMs have been shown to exert substantial influence on the efficacy of various cancer immunotherapy treatment strategies. Laboratory investigation into the behavior of TAMs has been limited by a lack of methods capable of resolving thein vivodistribution and dynamics of this cell population across wide fields of view. Recent studies have employed magnetic resonance imaging and intravital microscopy in conjunction with nanoparticle labeling methods to detect TAMs and observe their responses to therapeutic agents. Here we describe a novel method to enable high-resolution, wide-field, longitudinal imaging of leukocytes based on contrast-enhanced Speckle-Modulating Optical Coherence Tomography (SM-OCT), which substantially reduces imaging noise. We were able to specifically label TAMs and activated microgliain vivowith large gold nanorod contrast agents (LGNRs) in an orthotopic murine glioblastoma model. After labeling, we demonstrated near real-time tracking of leukocyte migration and distribution within the tumors. The intrinsic resolution, imaging depth, and sensitivity of this method may facilitate detailed studies of the fundamental behaviors of TAMsin vivo, including their intratumoral distribution heterogeneity and the roles they play in modulating cancer proliferation. In future studies, the method described herein may also provide the necessary means to characterize TAM responses to immunotherapeutic regimens in a range of solid tumors.
Closed-loop feedback control for microfluidic systems through automated capacitive fluid height sensing
Authors: Soenksen L. R. , Kassis T. , Noh M. , Griffith L.G. , Trumper D.L. 
Published: November 2017

AbstractPrecise fluid height sensing in open-channel microfluidics has long been a desirable feature for a wide range of applications. However, performing accurate measurements of the fluid level in small-scale reservoirs (<1mL) has proven to be an elusive goal, especially if direct fluid-sensor contact needs to be avoided. In particular, gravity-driven systems used in several microfluidic applications to establish pressure gradients and impose flow remain open-loop and largely unmonitored due to these sensing limitations. Here we present an optimized self-shielded coplanar capacitive sensor design and automated control system to provide submillimeter fluid-height resolution (~250 μm) and control of small-scale open reservoirs without the need for direct fluid contact. Results from testing and validation of our optimized sensor and system also suggest that accurate fluid height information can be used to robustly characterize, calibrate and dynamically control a range of microfluidic systems with complex pumping mechanisms, even in cell culture conditions. Capacitive sensing technology provides a scalable and cost-effective way to enable continuous monitoring and closed-loop feedback control of fluid volumes in small-scale gravity-dominated wells in a variety of microfluidic applications.
Discovery of a new song mode in Drosophila reveals hidden structure in the sensory and neural drivers of behavior
Authors: Clemens Jan , Coen Philip , Roemschied Frederic A. , Pereira Talmo , Mazumder David , Pacheco Diego , Murthy Mala 
Published: November 2017

SummaryDeciphering how brains generate behavior depends critically on an accurate description of behavior. If distinct behaviors are lumped together, separate modes of brain activity can be wrongly attributed to the same behavior. Alternatively, if a single behavior is split into two, the same neural activity can appear to produce different behaviors [1]. Here, we address this issue in the context of acoustic communication in Drosophila. During courtship, males utilize wing vibration to generate time-varying songs, and females evaluate songs to inform mating decisions [2-4]. Drosophila melanogaster song was thought for 50 years to consist of only two modes, sine and pulse, but using new unsupervised classification methods on large datasets of song recordings, we now establish the existence of at least three song modes: two distinct, evolutionary conserved pulse types, along with a single sine mode. We show how this seemingly subtle distinction profoundly affects our interpretation of the mechanisms underlying song production, perception and evolution. Specifically, we show that sensory feedback from the female influences the probability of producing each song mode and that male song mode choice affects female responses and contributes to modulating his song amplitude with distance [5]. At the neural level, we demonstrate how the activity of three separate neuron types within the fly’s song pathway differentially affect the probability of producing each song mode. Our results highlight the importance of carefully segmenting behavior to accurately map the underlying sensory, neural, and genetic mechanisms.
Reconstruction of resting-state networks from macaque electrocorticographic data
Authors: Hindriks R. , Micheli C. , Bosman C.A. , Oostenveld R. , Lewis C. , Mantini D. , Fries P. , Deco G. 
Published: November 2017

AbstractThe discovery of haemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electrophysiological cortical rhythms are organized into RSNs. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or electroencephalography (EEG), which limits the spatial scale on which RSNs can be investigated. Due to their close proximity to the cortical surface, electroencephalographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms. In this study we propose using source-space independent component analysis for identifying generators of resting-state cortical rhythms as recorded with ECoG and reconstructing their network structure. Their network structure is characterized by two kinds of connectivity: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. Using simulated data, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated as a consequence of first-order and higher-order volume-conduction effects, which troubles the interpretation of interaction measures based on imaginary phase-locking or coherence. The methodology is applied to resting-state beta (15-30 Hz) rhythms within the motor system of a macaque monkey and leads to the identification of a functional network of seven cortical generators that are distributed across the sensorimotor system. The spatial extent of the identified generators, together with consistent phase-lags, suggests that these rhythms can be viewed as being spatially continuous with complex dynamics including traveling waves. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human.
Mechanical variations in proteins with large-scale motions highlight the formation of structural locks
Authors: Sacquin-Mora Sophie 
Published: November 2017

AbstractProtein function depends just as much on flexibility as on structure, and in numerous cases, a protein’s biological activity involves transitions that will impact both its conformation and its mechanical properties. Here, we use a coarse-grain approach to investigate the impact of structural changes on protein flexibility. More particularly, we focus our study on proteins presenting large-scale motions. We show how calculating directional force constants within residue pairs, and investigating their variation upon protein closure, can lead to the detection of a limited set of residues that form astructural lockin the protein’s closed conformation. This lock, which is composed of residues whose side-chains are tightly interacting, highlights a new class of residues that are important for protein function by stabilizing the closed structure, and that cannot be detected using earlier tools like local rigidity profiles or distance variations maps, or alternative bioinformatics approaches, such as coevolution scores.