bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data
Authors: Rasero Javier , Aerts Hannelore , Cortes Jesus M. , Stramaglia Sebastiano , Marinazzo Daniele
Published: February 2018

Intrinsic Connectivity Networks, patterns of correlated activity emerging from "resting-state" Blood Oxygenation Level Dependent time series, are increasingly being associated to cognitive, clinical, and behavioral aspects, and compared with the pattern of activity elicited by specific tasks. We study the reconfiguration of the brain networks between task and resting-state conditions by a machine learning approach, to highlight the Intrinsic Connectivity Networks (ICNs) which are more affected by the change of network configurations in task vs. rest. We use a large cohort of publicly available data in both resting and task-based fMRI paradigms; by trying a battery of different supervised classifiers relying only on task-based measurements, we show that the highest accuracy is reached with a simple neural network of one hidden layer. In addition, when testing the fitted model on resting state measurements, such architecture yields a performance close to 90\% for areas connected to the task performed, which mainly involve the visual and sensorimotor cortex, whilst a relevant decrease of the performance is observed in the other ICNs. On one hand, our results confirm the correspondence of ICNs in both paradigms (task and resting) thus opening a window for future clinical applications to subjects whose participation in a required task cannot be guaranteed. On the other hand it is shown that brain areas not involved in the task display different connectivity patterns in the two paradigms.
Integrated transcriptomics and metabolomics reveal signatures of lipid metabolism dysregulation in HepaRG liver cells exposed to PCB 126
Authors: Mesnage Robin , Biserni Martina , Balu Sucharitha , Frainay Clément , Poupin Nathalie , Jourdan Fabien , Wozniak Eva , Xenakis Theodoros , Mein Charles A , Antoniou Michael N
Published: February 2018

Chemical pollutant exposure is a risk factor contributing to the growing epidemic of nonalcoholic fatty liver disease (NAFLD) affecting human populations that consume a Western diet. Although it is recognized that intoxication by chemical pollutants can lead to NAFLD, there is limited information available regarding the mechanism by which typical environmental levels of exposure can contribute to the onset of this disease. Here we describe the alterations in gene expression profiles and metabolite levels in the human hepatocyte HepaRG cell line, a validated model for cellular steatosis, exposed to the polychlorinated biphenyl (PCB) 126, one of the most potent chemical pollutants that can induce NAFLD. Sparse partial least squares classification of the molecular profiles revealed that exposure to PCB 126 provoked a decrease in polyunsaturated fatty acids as well as an increase in sphingolipid levels, concomitant with a decrease in the activity of genes involved in lipid metabolism. This was associated with an increased oxidative stress reflected by marked disturbances in taurine metabolism. A gene ontology analysis showed hallmarks of an activation of the AhR receptor by dioxin-like compounds. These changes in metabolome and transcriptome profiles were observed even at the lowest concentration (100 pM) of PCB 126 tested. A decrease in docosatrienoate levels was the most sensitive biomarker. Overall, our integrated multi-omics analysis provides mechanistic insight into how this class of chemical pollutant can cause NAFLD. Our study lays the foundation for the development of molecular signatures of toxic effects of chemicals causing fatty liver diseases to move away from a chemical risk assessment based on in vivo animal experiments.
A neural circuit arbitrates between perseverance and withdrawal in hungry Drosophila
Authors: Sayin Sercan , De Backer Jean-Francois , Wosniack Marina E , Lewis Laurence , Siju K.P. , Frisch Lisa-Marie , Schlegel Philipp , Edmondson-Stait A. , Sharifi N. , Fisher C.B. , Calle-Schuler S. , Lauritzen Scott , Bock Davi , Costa Marta , Jefferis Gregory S.X.E. , Gjorgjieva Julijana , Grunwald Kadow Ilona
Published: February 2018

In pursuit of palatable food, hungry animals mobilize significant energy resources and overcome obstacles, exhaustion and fear. Their perseverance depends on metabolic state, internal motivation and the expected benefit. Sustained commitment to a trying task is crucial, however, disengagement from one behavior to engage into another can be essential for optimal adaptation and survival. How neural circuits allow prioritizing perseverance over withdrawal based on the animal's need, however, is not understood. Using a single fly spherical treadmill, we show that hungry flies display increasing perseverance to track a food odor in the repeated absence of the predicted food reward. While this perseverance is mediated by a group of dopaminergic neurons, a subset of neurons expressing octopamine, the invertebrate noradrenaline, provide reward feedback and counteract dopamine-motivated food seeking. Our data and modeling suggest that two important neuromodulators tally internal and external signals to ultimately coordinate motivation-dependent antagonistic behavioral drives: perseverance vs. change of behavior.
INKA, an integrative data analysis pipeline for phosphoproteomic inference of active phosphokinases
Authors: Pham Thang V. , Beekhof Robin , van Alphen Carolien , Knol Jaco C. , Henneman Alex A. , Rolfs Frank , Labots Mariette , Henneberry Evan , Le Large Tessa Y.S. , de Haas Richard R. , Piersma Sander R. , Verheul Henk M.W. , Jimenez Connie R.
Published: February 2018

Identifying (hyper)active kinases in cancer patient tumors is crucial to enable individualized treatment with specific inhibitors. Conceptually, kinase activity can be gleaned from global protein phosphorylation profiles obtained with mass spectrometry-based phosphoproteomics. A major challenge is to relate such profiles to specific kinases to identify (hyper)active kinases that may fuel growth/progression of individual tumors. Approaches have hitherto focused on phosphorylation of either kinases or their substrates. Here, we combine kinase-centric and substrate-centric information in an Integrative Inferred Kinase Activity (INKA) analysis. INKA utilizes label-free quantification of phosphopeptides derived from kinases, kinase activation loops, kinase substrates deduced from prior experimental knowledge, and kinase substrates predicted from sequence motifs, yielding a single score. This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase-substrate relation networks in a biological sample. As a proof of concept, INKA scoring of phosphoproteomic data for different oncogene-driven cancer cell lines inferred top activity of implicated driver kinases, and relevant quantitative changes upon perturbation. These analyses show the ability of INKA scoring to identify (hyper)active kinases, with potential clinical significance.
Xist Intron 1 Repression by TALE Transcriptional Factor Improves Somatic Cell Reprogamming in Mice
Authors: Zhang Jindun , Gao Xuefei , Yang Jian , Fan Xiaoying , Wang Wei , Liang Yanfeng , Fan Lihong , Han Hongmei , Xu Xiaorong , Tang Fuchou , Bao Siqin , Liu Pentao , Li Xihe
Published: February 2018

Xist is the master regulator of X chromosome inactivation (XCI). In order to further understand the Xist locus in reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) and in somatic cell nuclear transfer (SCNT), we tested transcription-factor-like effectors (TALE)-based designer transcriptional factors (dTFs), which were specific to numerous regions at the Xist locus. We report that the selected dTF repressor 6 (R6) binding the intron 1 of Xist, which did not affect Xist expression in mouse embryonic fibroblasts (MEFs), substantially improved the iPSC generation and the SCNT preimplantation embryo development. Conversely, the dTF activator targeting the same genomic region of R6 decreased iPSC formation, and blocked SCNT-embryo development. These results thus uncover the critical requirement for the Xist locus in epigenetic resetting, which is not directly related to Xist transcription. This may provide a unique route to improving the reprogramming.
Doxorubicin induces caspase-mediated proteolysis of KV7.1
Authors: Strigli Anne , Raab Christian , Hessler Sabine , Huth Tobias , Schuldt Adam J. T. , Alzheimer Christian , Friedrich Thomas , Burridge Paul W. , Luedde Mark , Schwake Michael
Published: February 2018

The voltage-gated potassium channel Kv7.1 (KCNQ1) co-assembles with KCNE1 to generate the cardiac potassium current IKs. Gain- and loss-of-function mutations in KCNQ1 are associated with atrial fibrillation and long-QT (LQT) syndrome, respectively, highlighting the importance of modulating IKS activity for proper cardiac function. On a post-translational level, IKS can be regulated by phosphorylation, ubiquitination and sumoylation. Here, we report proteolysis of Kv7.1 as a novel, irreversible posttranslational modification. The identification of two C-terminal fragments (CTF1 and CTF2) of Kv7.1 led us to identify an aspartate critical for the generation of CTF2 and caspases as responsible for mediating Kv7.1 proteolysis. Activating caspases by apoptotic stimuli significantly reduced Kv7.1/KCNE1 currents, which was abrogated in cells expressing caspase-resistant Kv7.1 D459A/KCNE1 channels. An increase in cleavage of Kv7.1 could be detected in the case of LQT mutation G460S, which is located adjacent to the cleavage site. Application of apoptotic stimuli or doxorubicin-induced cardiotoxicity provoked caspase-mediated cleavage of endogenous Kv7.1 in human cardiomyocytes. In summary, our findings establish caspases as novel regulatory components for modulating Kv7.1 activity which may have important implications for the molecular mechanism of doxorubicin-induced cardiotoxicity.

Non-standard Abbreviations and Acronyms

Cam

calmodulin

EBC

equilibrium buffer content

LQT syndrome

long QT syndrome

NRVM

Neonatal rat ventricular cardiomyocytes

hiPSC-CMs

human induced pluripotent stem cell-derived cardiomyocytes
Predicting CTCF-mediated chromatin loops using CTCF-MP
Authors: Zhang Ruochi , Wang Yuchuan , Yang Yang , Zhang Yang , Ma Jian
Published: February 2018

The three dimensional organization of chromosomes within the cell nucleus is highly regulated. It is known that CTCF is an important architectural protein to mediate long-range chromatin loops. Recent studies have shown that the majority of CTCF binding motif pairs at chromatin loop anchor regions are in convergent orientation. However, it remains unknown whether the genomic context at the sequence level can determine if a convergent CTCF motif pair is able to form chromatin loop. In this paper, we directly ask whether and what sequence-based features (other than the motif itself) may be important to establish CTCF-mediated chromatin loops. We found that motif conservation measured by “branch-of-origin” that accounts for motif turn-over in evolution is an important feature. We developed a new machine learning algorithm called CTCF-MP based on word2vec to demonstrate that sequence-based features alone have the capability to predict if a pair of convergent CTCF motifs would form a loop. Together with functional genomic signals from CTCF ChIP-seq and DNase-seq, CTCF-MP is able to make highly accurate predictions on whether a convergent CTCF motif pair would form a loop in a single cell type and also across different cell types. Our work represents an important step further to understand the sequence determinants that may guide the formation of complex chromatin architectures.
Atomic Resolution Mechanism of Ligand Binding to a Solvent Inaccessible Cavity in T4 Lysozyme
Authors: Mondal Jagannath , Ahalawat Navjeet , Pandit Subhendu , Kay Lewis E , Vallurupalli Pramodh
Published: February 2018

Ligand binding sites in proteins are often localized to deeply buried cavities, inaccessible to bulk solvent. Yet, in many cases binding of cognate ligands occurs rapidly. An intriguing system is presented by the L99A cavity mutant of T4 Lysozyme (L99A T4L) that rapidly binds benzene (~106 M−1 s−1). Although the protein has long served as a model system for protein thermodynamics and crystal structures of both free and benzene-bound L99A T4L are available, the kinetic pathways by which benzene reaches its solvent-inaccessible binding cavity remain elusive. The current work, using extensive molecular dynamics simulation, achieves this by capturing the complete process of spontaneous recognition of benzene by L99A T4L at atomistic resolution. A series of multi-microsecond unbiased molecular dynamics simulation trajectories unequivocally reveal how benzene, starting in bulk solvent, diffuses to the protein and spontaneously reaches the solvent inaccessible cavity of L99A T4L. The simulated and high-resolution X-ray derived bound structures are in excellent agreement. A robust four-state Markov model, developed using cumulative 60 µs trajectories, identifies and quantifies multiple ligand binding pathways with low activation barriers. Interestingly, none of these identified binding pathways required large conformational changes for ligand access to the buried cavity. Rather, these involve transient but crucial opening of a channel to the cavity via subtle displacements in the positions of key helices (helix4/helix6, helix7/helix9) leading to rapid binding. Free energy simulations further elucidate that these channel-opening events would have been unfavorable in otherwise ligand-inactive wild type T4L. Taken together, by integrating experiments, these simulations provide unprecedented mechanistic insights into complete ligand recognition process in a buried cavity. By illustrating the power of subtle helix movements in opening up multiple pathways for ligand access, this work offers an alternate view of ligand recognition mechanism in a solvent-inaccessible cavity, contrary to common perception of single dominant pathway for ligand binding.
Template switching causes artificial junction formation and false identification of circular RNAs
Authors: Tang Chong , Yu Tian , Xie Yeming , Wang Zhuqing , McSwiggin Hayden , Zhang Ying , Zheng Huili , Yan Wei
Published: February 2018

Hundreds of thousands of putative circular RNAs have been identified through deep sequencing and bioinformatic analyses. However, the circularity of these putative RNA circles has not been experimentally validated due to limited methodologies currently available. We reported here that the template-switching capability of commonly used reverse transcriptases (e.g., SuperScript II) leads to the formation of artificial junction sequences, and consequently misclassification of large linear RNAs as RNA circles. Use of reverse transcriptases without terminal transferase activity (e.g., MonsterScript) for cDNA synthesis is critical for the identification of physiological circular RNAs. We also report two methods, MonsterScript junction PCR and high-resolution melting curve analyses, which can reliably distinguish circular RNAs from their linear forms and thus, can be used to discover and validate true circular RNAs.

Significance Statement

The vast majority of circular RNAs were identified through computational detection of junction sequences in the deep sequencing reads because these unique fusion sequences represent back-splicing events. We found that artificial junction sequences could be formed through template switching (TS) when MMLV-derived reverse transcriptases, e.g., SuperScript II, are used to synthesize cDNAs. Thus, many of the reported circular RNAs may not be RNA circles, but rather experimental artifacts. Fake circular RNAs can be avoided by using reverse transcriptases without terminal transferase activity (e.g., MonsterScript) for cDNA synthesis. We developed two novel methods, MonsterScript junction PCR and high-resolution melting curve analyses, for distinguishing circular RNAs from their linear form.
LonGP: an additive Gaussian process regression model for longitudinal study designs
Authors: Cheng Lu , Ramchandran Siddharth , Vatanen Tommi , Lietzen Niina , Lahesmaa Riitta , Vehtari Aki , Lähdesmäki Harri
Published: February 2018

Motivation

Biomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models have become the standard workhorse for statistical analysis of data from longitudinal study designs. However, analysis of longitudinal data can be complicated for both practical and theoretical reasons, including difficulties in modelling, correlated outcome values, functional (time-varying) covariates, nonlinear effects, and model inference.

Results

We present LonGP, an additive Gaussian process regression model for analysis of experimental data from longitudinal study designs. LonGP implements a flexible, non-parametric modelling framework that solves commonly faced challenges in longitudinal data analysis. In addition to inheriting all standard features of Gaussian processes, LonGP can model time-varying random effects and non-stationary signals, incorporate multiple kernel learning, and provide interpretable results for the effects of individual covariates and their interactions. We develop an accurate Bayesian inference and model selection method, and implement an efficient model search algorithm for our additive Gaussian process model. We demonstrate LonGP’s performance and accuracy by analysing various simulated and real longitudinal -omics datasets. Our work is accompanied by a versatile software implementation.

Availability

LonGP software tool is available athttp://research.cs.aalto.fi/csb/software/longp/.

Contact

lu.cheng.ac@gmail.com,harri.lahdesmaki@aalto.fi
Crystallizing the Parkinson’s Disease Protein LRRK2 Under Microgravity Conditions
Authors: Mathea Sebastian , Baptista Marco , Reichert Paul , Spinale April , Wu Jian , Allaire Marc , Fiske Brian , Knapp Stefan
Published: February 2018

Mutations in the gene coding for leucine-rich repeat kinase 2 (LRRK2) are a considerable cause for Parkinson’s disease (PD). However, the high- resolution 3D structure of the protein is still lacking. This structure will not only help to understand PD etiology but will also enable rational drug design. We have established a reliable method to produce LRRK2 crystals for the first time. However, the limited resolution of the diffraction data prevented structure determination using crystallographic methods. Herein we describe our efforts to improve the crystal quality by crystallizing under microgravity conditions aboard the International Space Station (ISS). Our method features diffusive sample mixing in capillaries and controlled crystal formation by transporting the samples in a frozen state. The crystallisation was successfully repeated under microgravity conditions. However, comparison of earth-grown and microgravity-grown LRRK2 crystals did not reveal any differences in diffraction quality. Here we present the established protocol and our experience adapting crystallization condition to the requirements necessary for successful crystallization of large and sensitive biomolecules under microgravity.
Two case studies detailing Bayesian parameter inference for dynamic energy budget models
Authors: Boersch-Supan Philipp H. , Johnson Leah R.
Published: February 2018

Mechanistic representations of individual life-history trajectories are powerful tools for the prediction of organismal growth, reproduction and survival under novel environmental conditions. Dynamic energy budget (DEB) theory provides compact models to describe the acquisition and allocation of energy by organisms over their full life cycle. However, estimating DEB model parameters, and their associated uncertainties and covariances, is not trivial. Bayesian inference provides a coherent way to estimate parameter uncertainty, and propagate it through the model, while also making use of prior information to constrain the parameter space. We outline a Bayesian inference approach for energy budget models and provide two case studies – based on a simplified DEBkiss model, and the standard DEB model – detailing the implementation of such inference procedures using the open-source software package deBInfer. We demonstrate how DEB and DEBkiss parameters can be estimated in a Bayesian framework, but our results also highlight the difficulty of identifying DEB model parameters which serves as a reminder that fitting these models requires statistical caution.
Adaptive and Wireless Recordings of Electrophysiological Signals during Concurrent Magnetic Resonance Imaging
Authors: Mandal Ranajay , Babaria Nishant , Cao Jiayue , Liu Zhongming ,   Senior Member IEEE
Published: February 2018

Strong electromagnetic fields that occur during functional magnetic resonance imaging (fMRI) presents a challenging environment for concurrent electrophysiological recordings. Here, we present a miniaturized, wireless platform – “MR-Link” (Multimodal Recording Link) that provides a hardware solution for simultaneous electrophysiological and fMRI signal acquisition. The device detects the changes in the electromagnetic field during fMRI to synchronize amplification and sampling of electrophysiological signals with minimal artifacts. It wirelessly transmits the recorded data at a frequency detectable by the MR-receiver coil. The transmitted data is readily separable from MRI in the frequency domain. To demonstrate its efficacy, we used this device to record electrocardiograms and somatosensory evoked potential during concurrent fMRI scans. The device minimized the fMRI-induced artifacts in electrophysiological data and wirelessly transmitted the data back to the receiver coil without compromising fMRI signal quality. The device is compact (22 mm dia., 2gms) and can be placed within the MR-bore to precisely synchronize with fMRI. Therefore, MR-Link offers an inexpensive system by eliminating the need for amplifiers with a high dynamic range, high-speed sampling, additional storage or synchronization hardware for electrophysiological signal acquisition. It is expected to enable a broader range of applications of simultaneous fMRI and electrophysiology in animals and humans.
No Evidence for Systematic White Matter Correlates of Dyslexia and Dyscalculia
Authors: Moreau David , Wilson Anna J. , McKay Nicole S. , Nihill Kasey , Waldie Karen E.
Published: February 2018

Learning disabilities such as dyslexia, dyscalculia and their comorbid manifestation are prevalent, affecting as much as fifteen percent of the population. Structural neuroimaging studies have indicated that these disorders can be related to differences in white matter integrity, although findings remain disparate. In this study, we used a unique design composed of individuals with dyslexia, dyscalculia, both disorders and controls, to systematically explore differences in fractional anisotropy across groups using diffusion tensor imaging. Specifically, we focused on the corona radiata and the arcuate fasciculus, two tracts associated with reading and mathematics in a number of previous studies. Using Bayesian hypothesis testing, we show that the present data favor the null model of no differences between groups for these particular tracts—a finding that seems to go against the current view but might be representative of the disparities within this field of research. Together, these findings suggest that structural differences associated with dyslexia and dyscalculia might not be as reliable as previously thought, with potential ramifications in terms of remediation.
Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: meta-analysis of data from genome-wide association studies
Authors: Fabbri Chiara , Tansey Katherine E. , Perlis Roy H. , Hauser Joanna , Henigsberg Neven , Maier Wolfgang , Mors Ole , Placentino Anna , Rietschel Marcella , Souery Daniel , Breen Gerome , Curtis Charles , Lee Sang-Hyuk , Newhouse Stephen , Patel Hamel , O’Donovan Michael , Lewis Glyn , Jenkins Gregory , Weinshilboum Richard M. , Farmer Anne , Aitchison Katherine J. , Craig Ian , McGuffin Peter , Schruers Koen , Biernacka Joanna M. , Uher Rudolf , Lewis Cathryn M.
Published: February 2018

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects.

CYP2C19 phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was percentage symptom improvement and remission. Side effect data were available at weeks 2–4, 6 and 9 in three of the investigated samples. A fixed-effects meta-analysis was performed using EM as the reference group.

Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD=0.43, CI=0.19–0.66) and higher remission rates (OR=1.55, CI=1.23–1.96) compared to EMs. At weeks 2–4, PMs showed higher risk of gastro-intestinal (OR=1.26, CI=1.08–1.47), neurological (OR=1.28, CI=1.07–1.53) and sexual side effects (OR=1.52, CI=1.23–1.87; week 6 values similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups.

CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs are relatively rare among Caucasians (~2%).
Decoding of selective attention to continuous speech from the human auditory brainstem response
Authors: Etard Octave , Kegler Mikolaj , Braiman Chananel , Forte Antonio Elia , Reichenbach Tobias
Published: February 2018

Humans are highly skilled at analysing complex acoustic scenes. The segregation of different acoustic streams and the formation of corresponding neural representations is mostly attributed to the auditory cortex. Decoding of selective attention from neuroimaging has therefore focussed on cortical responses to sound. However, the auditory brainstem response to speech is modulated by selective attention as well, as recently shown through measuring the brainstem’s response to running speech. Although the response of the auditory brainstem has a smaller magnitude than that of the auditory cortex, it occurs at much higher frequencies and therefore has a higher information rate. Here we develop statistical models for extracting the brainstem response from multi-channel scalp recordings and for analysing the attentional modulation according to the focus of attention. We demonstrate that the attentional modulation of the brainstem response to speech can be employed to decode the attentional focus of a listener from short measurements of ten seconds or less in duration. The decoding remains accurate when obtained from three EEG channels only. We further show how out-of-the-box decoding that employs subject-independent models, as well as decoding that is independent of the specific attended speaker is capable of achieving similar accuracy. These results open up new avenues for investigating the neural mechanisms for selective attention in the brainstem and for developing efficient auditory brain-computer interfaces.
Mosaic representations of odors in the input and output layers of the mouse olfactory bulb
Authors: Chae Honggoo , Kepple Daniel , Bast Walter G. , Murthy Venkatesh N. , Koulakov Alexei , Albeanu Dinu F.
Published: February 2018

The elementary stimulus features encoded by the olfactory system remain poorly understood. We examined the relationship between 1,666 physical-chemical descriptors of odors and the activity of olfactory bulb inputs as well as outputs in awake mice. Glomerular and M/T cell responses were sparse and locally heterogeneous, with only a coarse dependence of glomerular positions on physical-chemical properties. Odor features represented by ensembles of M/T cells were overlapping, but distinct from those represented in glomeruli, consistent with extensive interplay between feedforward and feedback inputs to the bulb. This reformatting was well-described as a rotation in odor space. The descriptors accounted for a small fraction in response variance, and the similarity of odors in physical-chemical space was a poor predictor of similarity in neuronal representations. Our results suggest that commonly used physical-chemical properties are not systematically represented in bulbar activity and encourage further search for better descriptors of odor space.
Design and Simulation of Microfluidic Device for Metabolite Screening and Quantitative Monitoring of Drug Uptake in Cancer Cells
Authors: Asif Afia , Khawaldeh Saed , Khan Muhammad Salman , Tekin Ahmet
Published: February 2018

Although liquid-liquid extraction methods are currently being applied in many areas such as analytical chemistry, biochemical engineering, biochemistry, and biological applications, however, accessibility and usability of microfluidics in practical daily life fields are still bounded. Suspended microfluidic devices have strength to lessen the obstacles, but the absence of robust design rules have hampered their usage. The primary objective of this work is to design and fabricate a microfluidic device to quantitatively monitor the drug uptake of cancer cells. Liquid-liquid extraction is used to quantify the drug uptake. In this research work, designs and simulations of two different microfluidic devices for carrying out multiplex solution experiments are proposed to test their efficiency. These simplified miniaturized chips would serve as suspended microfluidic metabolites extraction platform as it allows extracting the metabolites produced from the cancer cells as a result of applying a specific drug type for a certain period of time. These devices would be fabricated by making Polydimethylesiloxane (PDMS) molds from the negative master mold using soft lithography. Furthermore, it can leverage to provide versatile functionalities like high throughput screening, cancer cell invasions, protein purification, and small molecules extractions. As per previous studies, PDMS has been depicting better stability with various solvents and has proved to be reliable and cost effective material to be used for fabrication, though the sensitivity of the chip would be analyzed by cross contamination and of solvents within the channels of device.
Genome-wide epigenetic profiling of 5-hydroxymethylcytosine by long-read optical mapping
Authors: Gabrieli Tslil , Sharim Hila , Nifker Gil , Jeffet Jonathan , Shahal Tamar , Arielly Rani , Levi-Sakin Michal , Hoch Lily , Arbib Nissim , Michaeli Yael , Ebenstein Yuval
Published: February 2018

The epigenetic mark 5-hydroxymethylcytosine (5-hmC) is a distinct product of active enzymatic demethylation that is linked to gene regulation, development and disease. Genome-wide 5-hmC profiles generated by short-read next-generation sequencing are limited in providing long-range epigenetic information relevant to highly variable genomic regions, such as the 3.7 Mbp disease-related Human Leukocyte Antigen (HLA) region. We present a long-read, single-molecule mapping technology that generates hybrid genetic/epigenetic profiles of native chromosomal DNA. The genome-wide distribution of 5- hmC in human peripheral blood cells correlates well with 5-hmC DNA immunoprecipitation (hMeDIP) sequencing. However, the long read length of 100 kbp-1Mbp produces 5-hmC profiles across variable genomic regions that failed to showup in the sequencing data. In addition, optical 5-hmC mapping shows strong correlation between the 5-hmC density in gene bodies and the corresponding level of gene expression. The single molecule concept provides information on the distribution and coexistence of 5-hmC signals at multiple genomic loci on the same genomic DNA molecule, revealing long-range correlations and cell-to-cell epigenetic variation.
Conservation of conformational dynamics across prokaryotic actins
Authors: Ng Natalie , Shi Handuo , Colavin Alexandre , Casey Huang Kerwyn
Published: February 2018

The actin family of cytoskeletal proteins is essential to the physiology of virtually all archaea, bacteria, and eukaryotes. While X-ray crystallography and electron microscopy have revealed structural homologies among actin-family proteins, these techniques cannot probe molecular-scale conformational dynamics. Here, we use all-atom molecular dynamic simulations to reveal conserved dynamical behaviors in four prokaryotic actin homologs: MreB, FtsA, ParM, and crenactin. We demonstrate that the majority of the conformational dynamics of prokaryotic actins can be explained by treating the four subdomains as rigid bodies. MreB, ParM, and FtsA monomers exhibited nucleotide-dependent dihedral and opening angles, while crenactin monomer dynamics were nucleotide-independent. We further determine that the opening angle of ParM is sensitive to a specific interaction between subdomains. Steered molecular dynamics simulations of MreB, FtsA, and crenactin dimers revealed that changes in subunit dihedral angle lead to intersubunit bending or twist, suggesting a conserved mechanism for regulating filament structure. Taken together, our results provide molecular-scale insights into the nucleotide and polymerization dependencies of the structure of prokaryotic actins, suggesting mechanisms for how these structural features are linked to their diverse functions.

Significance Statement

Simulations are a critical tool for uncovering the molecular mechanisms underlying biological form and function. Here, we use molecular-dynamics simulations to identify common and specific dynamical behaviors in four prokaryotic homologs of actin, a cytoskeletal protein that plays important roles in cellular structure and division in eukaryotes. Dihedral angles and opening angles in monomers of bacterial MreB, FtsA, and ParM were all sensitive to whether the subunit was bound to ATP or ADP, unlike in the archaeal homolog crenactin. In simulations of MreB, FtsA, and crenactin dimers, changes in subunit dihedral angle led to bending or twisting in filaments of these proteins, suggesting a mechanism for regulating the properties of large filaments. Taken together, our simulations set the stage for understanding and exploiting structure- function relationships of bacterial cytoskeletons.
New insights on human essential genes based on integrated analysis
Authors: Chen Hebing , Zhang Zhuo , Jiang Shuai , Li Ruijiang , Li Wanying , Zhao Chenghui , Hong Hao , Huang Xin , Li Hao , Bo Xiaochen
Published: February 2018

Essential genes are those whose functions govern critical processes that sustain life in the organism. Recent gene-editing technologies have provided new opportunities to characterize essential genes. Here, we present an integrated analysis for comprehensively and systematically elucidating the genetic and regulatory characteristics of human essential genes. First, essential genes act as “hubs” in protein-protein interactions networks, in chromatin structure, and in epigenetic modifications, thus are essential for cell growth. Second, essential genes represent the conserved biological processes across species although gene essentiality changes itself. Third, essential genes are import for cell development due to its discriminate transcription activity in both embryo development and oncogenesis. In addition, we develop an interactive web server, the Human Essential Genes Interactive Analysis Platform (HEGIAP) (http://sysomics.com/HEGIAP/), which integrates abundant analytical tools to give a global, multidimensional interpretation of gene essentiality. Our study provides a new view for understanding human essential genes.
Development of photoactivatable drugs enables nicotinic optopharmacology
Authors: Banala Sambashiva , Arvin Matthew C. , Bannon Nicolas M. , Jin Xiao-Tao , Wang Yong , Zhao Guiqing , Marshall John J. , Gee Kyle R. , Wokosin David L. , Contractor Anis , Lester Henry A. , Kozorovitskiy Yevgenia , Drenan Ryan M. , Lavis Luke D.
Published: February 2018

Photoactivatable (‘caged’) pharmacological agents have revolutionized neuroscience but the palette of available ligands is limited. We describe a general method for caging tertiary amines using an unconventional quaternary ammonium linkage that is chemically stable and elicits a desirable red-shift in activation wavelength. A photoactivatable nicotine (PA-Nic) prepared using this strategy could be uncaged via 1- or 2-photon excitation, making it useful for optopharmacology experiments to study nicotinic acetylcholine receptors (nAChRs) in different experimental preparations and spatiotemporal scales.
The TRIM-NHL protein NHL-2 is a Novel Co-Factor of the CSR-1 and HRDE-1 22G-RNA Pathways
Authors: Davis Gregory M. , Tu Shikui , Colson Rhys N. , Anderson Joshua W. T. , Gunzburg Menachem J. , Francisco Michelle A. , Ray Debashish , Maity Tuhin , Wu Monica Z. , Morris Quaid D. , Hughes Timothy R. , Wilce Jacqueline A. , Claycomb Julie M. , Weng Zhiping , Boag Peter R.
Published: February 2018

Proper regulation of germline gene expression is essential for fertility and maintaining species integrity. In theC. elegansgermline, a diverse repertoire of regulatory pathways promote the expression of endogenous germline genes and limit the expression of deleterious transcripts to maintain genome homeostasis. Here we show that the conserved TRIM-NHL protein, NHL-2, plays an essential role in theC. elegansgermline, modulating germline chromatin and meiotic chromosome organization. We uncover a role for NHL-2 as a co-factor in both positively (CSR-1) and negatively (HRDE-1) acting germline 22G-small RNA pathways and the somatic nuclear RNAi pathway. Furthermore, we demonstrate that NHL-2 is a bona fide RNA binding protein and, along with RNA-seq data point to a small RNA independent role for NHL-2 in regulating transcripts at the level of RNA stability. Collectively, our data implicate NHL-2 as an essential hub of gene regulatory activity in both the germline and soma.
Beyond the vestibulo-ocular reflex: Vestibular input is processed centrally to achieve visual stability
Authors: Dalmaijer Edwin S.
Published: February 2018

The current study presents a re-analysis of data from Zink et al. (1998, Electroencephalography and Clinical Neurophysiology, 107), who administered galvanic vestibular stimulation through unipolar direct current. They placed electrodes on each mastoid, and applied both right and left anodal stimulation. Ocular torsion and visual tilt were measured under different stimulation intensities. New modelling introduced here demonstrates that directly proportional linear models fit reasonably well to the relationship between vestibular input and visual tilt, but not to that between vestibular input and ocular torsion. Instead, an exponential model characterised by a decreasing slope and an asymptote fitted best. These results demonstrate that in the results presented by Zink et al., ocular torsion could not completely account for visual tilt. This suggests that vestibular input is processed centrally to stabilise vision when ocular torsion is insufficient. Potential mechanisms and seemingly conflicting literature are discussed.
Interconnected feedback loops among ESRP1, HAS2, and CD44 regulate epithelial-mesenchymal plasticity in cancer
Authors: Jolly Mohit Kumar , Preca Bogdan-Tiberius , Tripathi Satyendra C , jia Dongya , Hanash Samir M , Brabletz Thomas , Stemmler Marc P , Maurer Jochen , Levine Herbert
Published: February 2018

Aberrant activation of epithelial-mesenchymal transition (EMT) in carcinoma cells contributes to increased migration and invasion, metastasis, drug resistance, and tumor-initiating capacity. EMT is not always a binary process, rather cells may exhibit a hybrid epithelial/mesenchymal (E/M) phenotype. ZEB1 - a key transcription factor driving EMT - can both induce and maintain a mesenchymal phenotype. Recent studies have identified two novel autocrine feedback loops utilizing ESRP1, HAS2, and CD44 that maintain high levels of ZEB1. However, how the crosstalk between these feedback loops alters the dynamics of epithelial-hybrid-mesenchymal transition remains elusive. Here, using an integrated theoretical-experimental framework, we identify that these feedback loops can enable cells to stably maintain a hybrid E/M phenotype. Moreover, computational analysis identifies the regulation of ESRP1 as a crucial node, a prediction that is validated by two complementary experiments showing that (a) overexpression of ESRP1 reverts EMT in MCF10A cells treated with TGFβ for 21 days, and (b) knockdown of ESRP1 in stable hybrid E/M H1975 cells drives EMT. Finally, in multiple breast cancer datasets, high levels of ESRP1, ESRP1/HAS2, and ESRP1/ZEB1 correlates with poor prognosis, supporting the relevance of ZEB1/ESRP1 and ZEB1/HAS2 axes in tumor progression. Together, our results unravel how these interconnected feedback loops act in concert to regulate ZEB1 levels and to drive the dynamics of epithelial-hybrid-mesenchymal transition.
ASGAL: Aligning RNA-Seq Data to a Splicing Graph to Detect Novel Alternative Splicing Events
Authors: Denti Luca , Rizzi Raffaella , Beretta Stefano , Della Vedova Gianluca , Previtali Marco , Bonizzoni Paola
Published: February 2018

Background: While the reconstruction of transcripts from a sample of RNA-Seq data is a computationally expensive and complicated task, the detection of splicing events from RNA-Seq data and a gene annotation is computationally feasible. The latter task, which is adequate for many transcriptome analyses, is usually achieved by aligning the reads to a reference genome, followed by comparing the alignments with a gene annotation, often implicitly represented by a graph: the splicing graph.

Results: We present ASGAL (Alternative Splicing Graph ALigner): a tool for mapping RNA-Seq data to the splicing graph, with the main goal of detecting novel alternative splicing events. ASGAL receives in input the annotated transcripts of a gene and an RNA-Seq sample, and it computes (1) the spliced alignments of each read, and (2) a list of novel events with respect to the gene annotation.

Conclusions: An experimental analysis shows that, by aligning reads directly to the splicing graph, ASGAL better predicts alternative splicing events when compared to tools requiring spliced alignments of the RNA-Seq data to a reference genome. To the best of our knowledge, ASGAL is the first tool that detects novel alternative splicing events by directly aligning reads to a splicing graph.

Availability: Source code, documentation, and data are available for download at http://asgal.algolab.eu.
Chromosome-scale comparative sequence analysis unravels molecular mechanisms of genome evolution between two wheat cultivars
Authors: Thind Anupriya Kaur , Wicker Thomas , Müller Thomas , Ackermann Patrick M. , Steuernagel Burkhard , Wulff Brande B.H. , Spannagl Manuel , Twardziok Sven O. , Felder Marius , Lux Thomas , Mayer Klaus F.X. ,   International Wheat Genome Sequencing Consortium, Keller Beat , Krattinger Simon G.
Published: February 2018

Background

Recent improvements in DNA sequencing and genome scaffolding have paved the way to generate high-qualityde novoassemblies of pseudomolecules representing complete chromosomes of wheat and its wild relatives. These assemblies form the basis to compare the evolutionary dynamics of wheat genomes on a megabase-scale.

Results

Here, we provide a comparative sequence analysis of the ~700-megabase chromosome 2D between two bread wheat genotypes – the old landrace Chinese Spring and the elite Swiss spring wheat line ‘CH CampalaLr22a’. There was a high degree of sequence conservation between the two chromosomes. Analysis of large structural variations revealed four large insertions/deletions (InDels) of >100 kb. Based on the molecular signatures at the breakpoints, unequal crossing over and double-strand break repair were identified as the evolutionary mechanisms that caused these InDels. Three of the large InDels affected copy number of NLRs, a gene family involved in plant immunity. Analysis of single nucleotide polymorphism (SNP) density revealed three haploblocks of ~8 Mb, ~9 Mb and ~48 Mb with a 35-fold increased SNP density compared to the rest of the chromosome.

Conclusions

This comparative analysis of two high-quality chromosome assemblies enabled a comprehensive assessment of large structural variations. The insight obtained from this analysis will form the basis of future wheat pan-genome studies.
Modeling driver cells in developing neuronal networks
Authors: Luccioli Stefano , Angulo-Garcia David , Cossart Rosa , Malvache Arnaud , Módol Laura , Sousa Vitor Hugo , Bonifazi Paolo , Torcini Alessandro
Published: February 2018

Spontaneous emergence of synchronized population activity is a characteristic feature of developing brain circuits. Recent experiments in the developing neo-cortex showed the existence of driver cells able to impact the synchronization dynamics when single-handedly stimulated. We have developed a spiking network model capable to reproduce the experimental results, thus identifying two classes of driver cells: functional hubs and low functionally connected (LC) neurons. The functional hubs arranged in a clique orchestrated the synchronization build-up, while the LC drivers were lately or not at all recruited in the synchronization process. Notwithstanding, they were able to alter the network state when stimulated by modifying the temporal activation of the functional clique or even its composition. LC drivers can lead either to higher population synchrony or even to the arrest of population dynamics, upon stimulation. Noticeably, some LC driver can display both effects depending on the received stimulus. We show that in the model the presence of inhibitory neurons together with the assumption that younger cells are more excitable and less connected is crucial for the emergence of LC drivers. These results provide a further understanding of the structural-functional mechanisms underlying synchronized firings in developing circuits possibly related to the coordinated activity of cell assemblies in the adult brain.

Author Summary

There is timely interest on the impact of peculiar neurons (driver cells) and of small neuronal sub-networks (cliques) on operational brain dynamics. We first provide experimental data concerning the effect of stimulated driver cells on the bursting activity observable in the developing entorhinal cortex. Secondly, we develop a network model able to fully reproduce the experimental observations. Analogously to the experiments two types of driver cells can be identified: functional hubs and low functionally connected (LC) drivers. We explain the role of hub neurons, arranged in a clique, for the orchestration of the bursting activity in control conditions. Furthermore, we report a new mechanism, which can explain why and how LC drivers emerge in the structural-functional organization of the enthorinal cortex.