SEARCH · Search bioRxiv

Results for “Biophysics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources

bioRxiv2018

Characterization and automatic classification of preterm and term uterine records

Predicting preterm birth is uncertain, and numerous scientists are searching for non-invasive methods to improve its predictability. Current researches are based on the analysis of ElectroHysteroGram (EHG) records, which contain information about the electrophysiological properties of the uterine muscle and uterine contractions. Since pregnancy is a long process, we decided to also characterize, for the first time, non-contraction intervals (dummy intervals) of the uterine records, i.e., EHG signals accompanied by a simultaneously recorded external tocogram measuring mechanical uterine activity (TOCO signal). For this purpose, we developed a new set of uterine records, TPEHGT DS, containing preterm and term uterine records of pregnant women, and uterine records of non-pregnant women. We quantitatively characterized contraction intervals (contractions) and dummy intervals of the uterine records of the TPEHGT DS in terms of the normalized power spectra of the EHG and TOCO signals, and developed a new method for predicting preterm birth. The results on the characterization revealed that the peak amplitudes of the normalized power spectra of the EHG and TOCO signals of the contraction and dummy intervals in the frequency band 1.0-2.2 Hz, describing the electrical and mechanical activity of the uterus due to the maternal heart (maternal heart rate), are high only during term pregnancies, when the delivery is still far away; and they are low when the delivery is close. However, these peak amplitudes are also low during preterm pregnancies, when the delivery is still supposed to be far away (thus suggesting the danger of preterm birth); and they are also low or barely present for non-pregnant women. We propose the values of the peak amplitudes of the normalized power spectra due to the influence of the maternal heart, in an electro-mechanical sense, in the frequency band 1.0-2.2 Hz as a new biophysical marker for the preliminary, or early, assessment of the danger of preterm birth. The classification of preterm and term, contraction and dummy intervals of the TPEHGT DS, for the task of the automatic prediction of preterm birth, using sample entropy, the median frequency of the power spectra, and the peak amplitude of the normalized power spectra, revealed that the dummy intervals provide quite comparable and slightly higher classification performances than these features obtained from the contraction intervals. This result suggests a novel and simple clinical technique, not necessarily to seek contraction intervals but using the dummy intervals, for the early assessment of the danger of preterm birth. Using the publicly available TPEHG DB database to predict preterm birth in terms of classifying between preterm and term EHG records, the proposed method outperformed all currently existing methods. The achieved classification accuracy was 100% for early records, recorded around the 23rd week of pregnancy; and 96.33%, the area under the curve of 99.44%, for all records of the database. Since the proposed method is capable of using the dummy intervals with high classification accuracy, it is also suitable for clinical use very early during pregnancy, around the 23rd week of pregnancy, when contractions may or may not be present.

bioinformatics↗

bioRxiv2018

EECoG-Comp: An Open Source Platform for Concurrent EEG/ECoG Comparisons

Electrophysiological Source Imaging (ESI) methods are hampered by the lack of "gold standards" for model comparison. Concurrent electroencephalography (EEG) and electrocorticography (ECoG) recordings (namely EECoG) are considered gold standard to validating EEG generative models with primate models have the unique advantages of both flexibility and translational value in human research. However the severe EEG artifacts during such invasive experiments, the complexity of providing sufficiently detailed biophysical models, as well as lacking sound statistical connectivity comparison methods have hampered the availability and analysis of such datasets. In this paper, 1) we provide EECoG-Comp: an open source platform (https://github.com/Vincent-wq/EECoG-Comp) which encompasses the preprocessing, forward modeling, simulation and comparison module; 2) we take the simultaneous EECoG dataset from www.neurotycho.org as an example to illustrate the use of this platform and compare the source connectivity estimation performance of 4 popular ESI methods named MNE, LCMV, eLORETA and SSBL. The conclusion shows the limits of performance of these ESI connectivity estimators using both simulations and real data analysis. In fact, the use of this platform also suggests the need for both improved simultaneous EEG and ECoG experiments and ESI connectivity estimators.

bioinformatics↗

bioRxiv2018

Mutation rate variability as a driving force in adaptive evolution

Mutation rate is a key determinant of the pace as well as outcome of evolution, and variability in this rate has been shown in different scenarios to play a key role in evolutionary adaptation and resistance evolution under stress. Here we investigate the dynamics of resistance fixation in a bacterial population with variable mutation rates and show that evolutionary outcomes are most sensitive to mutation rate variations when the population is subject to environmental and demographic conditions that suppress the evolutionary advantage of high-fitness subpopulations. By directly mapping a molecular-level biophysical fitness function to the system-level dynamics of the population we show that both low and very high, but not intermediate, levels of stress result in a disproportionate effect of hypermutation on resistance fixation and that traditional definitions of the selection coefficient are insufficient to account for this effect. We demonstrate how this behavior is directly tied to the extent of genetic hitchhiking in the system, the propagation of high-mutation rate cells through association with high-fitness mutations. Our results indicate a substantial role for mutation rate flexibility in the evolution of antibiotic resistance under conditions that present a weak advantage over wildtype to resistant cells.

evolutionary biology↗

bioRxiv2018

Stoichiometry and Mobility Switching of a Morphogenetic Protein in Live Differentiating Cells

Spore formation following asymmetric cell division in Bacillus subtilis offers a model system to study development, morphogenesis and signal transduction in more complex organisms. Extensive biochemical and genetic details of its sporulation factors are known, however, the molecular mechanisms by which asymmetry is generated remain unclear. A crucial membrane phosphatase, SpoIIE, couples gene regulation to morphology changes, but how it performs different functions dependent on cell stage is unknown. We addressed this puzzle using high-speed single-molecule fluorescence microscopy on live B. subtilis expressing genomically encoded SpoIIE fluorescent protein fusions during sporulation. Copy number analysis indicated a few tens of SpoIIE at sporulation onset increasing to 400-600 molecules per cell following asymmetric cell division with up to 30% greater proportion in the forespore, corresponding to a concentration enhancement in the smaller forespore sufficient for differential dephosphorylation of an anti-sigma factor antagonist and activation of the forespore specific transcription factor, {sigma}F. Step-wise photobleach analysis indicates that SpoIIE forms tetramers capable of reversible oligomerisation to form clusters correlated with stage-specific functions. Specifically, low mobility SpoIIE clusters which initially localize to the asymmetric septum are released as mobile SpoIIE clusters around the forespore when phosphatase activity is manifested. SpoIIE is subsequently recaptured at the septum in a SpoIIQ-dependent manner. After mother cell engulfment of the forespore, SpoIIE is released as a mix of higher mobility clusters and tetramers. Our findings suggest that additional information captured in the changing state of multimerization and mobility enable one protein to perform different roles at different cell stages.\n\nSignificance/impactCertain bacteria undergo sporulation involving cells dividing asymmetrically. A crucial protein SpoIIE facilitates this morphological asymmetry and directly links it to asymmetry in gene expression. Here, we used specialized light microscopy, capable of observing single molecules, plus biophysics, genetics and biochemical tools, to monitor SpoIIE in single living bacteria in real time, allowing us to count how many molecules are present in different cell regions, and how mobile they are. We find that SpoIIE clusters and moves depending on development stages, indicating that it has different roles depending on other binding proteins and their cellular locations. Our results suggest that changes in molecular stoichiometry and mobility may be used as switches in more complex cell processes.

microbiology↗

bioRxiv2018

The Therapeutic Antibody Profiler (TAP): Five Computational Developability Guidelines

Therapeutic monoclonal antibodies (mAbs) must not only bind to their target but must also be free from 'developability issues', such as poor stability or high levels of aggregation. While small molecule drug discovery benefits from Lipinski's rule of five to guide the selection of molecules with appropriate biophysical properties, there is currently no in silico analog for antibody design. Here, we model the variable domain structures of a large set of post-Phase I clinical-stage antibody therapeutics (CSTs), and calculate an array of metrics to estimate their typical properties. In each case, we contextualize the CST distribution against a snapshot of the human antibody gene repertoire. We describe guideline values for five metrics thought to be implicated in poor developability: the total length of the Complementarity-Determining Regions (CDRs), the extent and magnitude of surface hydrophobicity, positive charge and negative charge in the CDRs, and asymmetry in the net heavy and light chain surface charges. The guideline cut-offs for each property were derived from the values seen in CSTs, and a flagging system is proposed to identify nonconforming candidates. On two mAb drug discovery sets, we were able to selectively highlight sequences with developability issues. We make available the Therapeutic Antibody Profiler (TAP), an open-source computational tool that builds downloadable homology models of variable domain sequences, tests them against our five developability guidelines, and reports potential sequence liabilities and canonical forms. TAP is freely available at http://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/TAP.php.

immunology↗

bioRxiv2018

Short-term radiofrequency exposure from new generation mobile phones reduces EEG alpha power with no effects on cognitive performance

Although mobile phone (MP) use has been steadily increasing in the last decades and similar positive trends are expected for the near future, systematic investigations on neurophysiological and cognitive effects caused by recently developed technological standards for MPs are scarcely available. Here, we investigated the effects of radiofrequency (RF) fields emitted by new-generation mobile technologies, specifically, Universal Mobile Telecommunications System (UMTS) and Long-Term Evolution (LTE), on intrinsic scalp EEG activity in the alpha band (8-12 Hz) and cognitive performance in the Stroop test. The study involved 60 healthy, young-adult university students (34 for UMTS and 26 for LTE) with double-blind administration of Real and Sham exposure in separate sessions. EEG was recorded before, during and after RF exposure, and Stroop performance was assessed before and after EEG recording. Both RF exposure types caused a notable decrease in the alpha power over the whole scalp that persisted even after the cessation of the exposure, whereas no effects were found on any aspects of performance in the Stroop test. The results imply that the brain networks underlying global alpha oscillations might require minor reconfiguration to adapt to the local biophysical changes caused by focal RF exposure mimicking MP use.

neuroscience↗

bioRxiv2018

Flexible resonance in prefrontal networks with strong feedback inhibition

Oscillations are ubiquitous features of brain dynamics that undergo task-related changes in synchrony, power, and frequency. The impact of those changes on target networks is poorly understood. In this work, we used a biophysically detailed model of prefrontal cortex (PFC) to explore the effects of varying the spike rate, synchrony, and waveform of strong oscillatory inputs on the behavior of cortical networks driven by them. Interacting populations of excitatory and inhibitory neurons with strong feedback inhibition are inhibition-based network oscillators that exhibit resonance (i.e., larger responses to preferred input frequencies). We quantified network responses in terms of mean firing rates and the population frequency of network oscillation; and characterized their behavior in terms of the natural response to asynchronous input and the resonant response to oscillatory inputs. We show that strong feedback inhibition causes the PFC to generate internal (natural) oscillations in the beta/gamma frequency range (>15 Hz) and to maximize principal cell spiking in response to external oscillations at slightly higher frequencies. Importantly, we found that the fastest oscillation frequency that can be relayed by the network maximizes local inhibition and is equal to a frequency even higher than that which maximizes the firing rate of excitatory cells; we call this phenomenon population frequency resonance. This form of resonance is shown to determine the optimal driving frequency for suppressing responses to asynchronous activity. Lastly, we demonstrate that the natural and resonant frequencies can be tuned by changes in neuronal excitability, the duration of feedback inhibition, and dynamic properties of the input. Our results predict that PFC networks are tuned for generating and selectively responding to beta- and gamma-rhythmic signals due to the natural and resonant properties of inhibition-based oscillators. They also suggest strategies for optimizing transcranial stimulation and using oscillatory networks in neuromorphic engineering.\n\nAuthor SummaryThe prefrontal cortex (PFC) flexibly encodes task-relevant representations and outputs biases to mediate higher cognitive functions. The relevant neural ensembles undergo task-related changes in oscillatory dynamics at beta- and gamma frequencies. Using a computational model of the PFC network, we show that strong feedback inhibition causes the PFC to generate internal oscillations and to prefer external oscillations at similar frequencies. The precise frequencies that are generated and preferred can be flexibly tuned by varying the synchrony and strength of input network activity, the level of background excitation, and neuromodulation of intrinsic ion currents. We also show that the peak output frequency in response to external oscillations, which depends on the synchrony and strength of the input as well as the strong inhibitory feedback, is faster than the internally generated frequency, and that this difference enables exclusive response to oscillatory inputs. These properties enable changes in oscillatory dynamics to govern the selective processing and gating of task-relevant signals in service of cognitive control.

neuroscience↗

bioRxiv2018

Basal forebrain and brainstem cholinergic neurons differentially impact amygdala circuits and learning-related behavior

The central cholinergic system and the amygdala are important for motivation and mnemonic processes. Different cholinergic populations innervate the amygdala but it is unclear how these projections impact amygdala processes. Using optogenetic circuit-mapping strategies in ChAT-cre mice we demonstrate that amygdala-projecting basal forebrain and brainstem ChAT-containing neurons can differentially affect amygdala circuits and behavior. Photo-activating ChAT terminals in vitro revealed the underlying synaptic impact of brainstem inputs to the central lateral division to be excitatory, mediated via the synergistic glutamatergic activation of AMPA and NMDA receptors. In contrast, stimulating basal forebrain inputs to the basal nucleus resulted in endogenous ACh release resulting in biphasic inhibition-excitation responses onto principal neurons. Such response profiles are physiological hallmarks of neural oscillations and could thus form the basis of acetylcholine-mediated rhythmicity in amygdala networks. Consistent with this, in vivo NBm activation strengthened amygdala basal nucleus theta and gamma frequency rhythmicity, both of which continued for seconds after stimulation and were dependent on local muscarinic or nicotinic receptor activation, respectively. Activation of brainstem ChAT-containing neurons however resulted in a transient increase in central lateral amygdala activity that was independent of cholinergic receptors. In addition, driving these respective inputs in behaving animals induced opposing appetitive and defensive learning-related behavioral changes. Since learning and memory is supported by both cellular and network-level processes in central cholinergic and amygdala networks, these results provide a route by which distinct cholinergic inputs can convey salient information to the amygdala and promote associative biophysical changes that underlie emotional memories.

neuroscience↗

bioRxiv2018

Individual variations of the human corticospinal tract and its hand-related motor fibers using diffusion MRI tractography

The corticospinal tract (CST) is one of the most well-studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many notable traumatic conditions and diseases such as stroke, spinal cord injury (SCI) or amyotrophic lateral sclerosis (ALS). With the advent of diffusion MRI and tractography the computational representation of the human CST in a 3D model became available. However, the representation of the entire CST and, specifically, the hand motor area has remained elusive. In this paper we proposed a novel method, using manually-drawn ROIs based on robustly identifiable neuroanatomic structures to delineate the entire CST and isolate its hand motor representation as well as to estimate their variability and generate a database of their volume, length and biophysical parameters. Using 37 healthy human subjects we performed a qualitative and quantitative analysis of the CST and the hand-related motor fiber tracts (HMFTs). Finally, we have created variability heatmaps from 37 subjects for both the aforementioned tracts, which could be utilized as reference for clinicians to explore neuropathology in both trauma and disease states.

neuroscience↗

bioRxiv2018

Nematode germ granule assembly is linked to mRNA repression

Cytoplasmic RNA-protein (RNP) granules have diverse biophysical properties, from liquid to solid, and play enigmatic roles in RNA metabolism. Nematode P-granules are paradigmatic liquid droplet granules and central to germ cell development. Here we analyze a key P-granule scaffolding protein, called PGL, to investigate the functional relationship between P-granule assembly and function. Using a protein-RNA tethering assay, we find that reporter mRNA expression is repressed when recruited to PGL granules. We determine the crystal structure of the PGL N-terminal region to 1.5 [A], discover its dimerization and identify key residues at the dimer interface. In vivo mutations of those interface residues prevent P-granule assembly, de-repress PGL-tethered mRNA and reduce fertility. Therefore, PGL dimerization lies at the heart of both P-granule assembly and function. Finally, we identify the P-granule-associated Argonaute WAGO-1 as crucial for repression of PGL-tethered mRNA. We conclude that P-granule function requires both assembly and localized regulators.

developmental biology↗

bioRxiv2018

Unjamming overcomes kinetic and proliferation arrest in terminally differentiated cells and promotes collective motility of carcinoma.

During wound repair, branching morphogenesis and carcinoma dissemination, cellular rearrangements are fostered by a solid-to-liquid transition known as unjamming. The biomolecular machinery behind unjamming, its physiological and clinical relevance remain, however, a mystery. Here, we combine biophysical and biochemical analysis to study unjamming in a variety of epithelial 2D and 3D collectives: monolayers, differentiated normal mammary cysts, spheroid models of breast ductal carcinoma in situ (DCIS), and ex vivo slices of orthotopically-implanted DCIS. In all cases, elevation of the small GTPase RAB5A sparks unjamming by promoting non-clathrin-dependent internalization of epidermal growth factor receptor that leads to hyper-activation of endosomally-confined ERK1/2 and phosphorylation of the actin nucleator WAVE2. Physically, activation of this pathway causes highly coordinated flocking of the cells, with striking rotational motion in 3D that eventually leads to matrix remodelling and collective invasiveness of otherwise jammed carcinoma. The identified endo-ERK1/2 pathway provides an effective switch for unjamming through flocking to promote epithelial tissues morphogenesis and carcinoma invasion and dissemination.

cancer biology↗

bioRxiv2018

Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

Hyperspectral reflectance phenotyping and genomic selection are two emerging technologies that have the potential to increase plant breeding efficiency by improving prediction accuracy for grain yield. Hyperspectral cameras quantify canopy reflectance across a wide range of wavelengths that are associated with numerous biophysical and biochemical processes in plants. Genomic selection models utilize genome-wide marker or pedigree information to predict the genetic values of breeding lines. In this study, we propose a multi-kernel GBLUP approach to genomic selection that uses genomic marker-, pedigree-, and hyperspectral reflectance-derived relationship matrices to model the genetic main effects and genotype x environment (G x E) interactions across environments within a bread wheat (Triticum aestivum L.) breeding program. We utilized an airplane equipped with a hyperspectral camera to phenotype five differentially managed treatments of the yield trials conducted by the Bread Wheat Improvement Program, International Maize and Wheat Improvement Center (CIMMYT) at Ciudad Obregon, Mexico over four breeding cycles. We observed that single-kernel models using hyperspectral reflectance-derived relationship matrices performed similarly or superior to marker-and pedigree-based genomic selection models when predicting within and across environments. Multi-kernel models combining marker/pedigree information with hyperspectral reflectance phentoypes had the highest prediction accuracies; however, improvements in accuracy over marker-and pedigree-based models were marginal when correcting for days to heading. Our results demonstrates the potential of hyperspectral imaging in predicting grain yield within a multi-environment context, it also supports further studies on integration of hyperspectral reflectance phenotyping in breeding programs.

genomics↗

bioRxiv2018

Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative

A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials (LFP), electrocorticography (ECoG), and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources (\"dipoles\") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources--magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low passes filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.

neuroscience↗

bioRxiv2018

Balancing dynamic tradeoffs to drive cellular reprogramming

Although cellular reprogramming continues to generate new cell types, reprogramming remains a rare cellular event. The molecular mechanisms that limit reprogramming, particularly to somatic lineages, remain unclear. By examining fibroblast-to-motor neuron conversion, we identify a previously unappreciated dynamic between transcription and replication that determines reprogramming competency. Transcription factor overexpression forces most cells into states that are refractory to reprogramming and are characterized by either hypertranscription with little cell division, or hyperproliferation with low transcription. We identify genetic and chemical factors that dramatically increase the number of cells capable of both hypertranscription and hyperproliferation. Hypertranscribing, hyperproliferating cells reprogram at 100-fold higher, near-deterministic rates. We demonstrate that elevated topoisomerase expression endows cells with privileged reprogramming capacity, suggesting that biophysical constraints limit cellular reprogramming to rare events.

cell biology↗

bioRxiv2018

Molecular structure and function of myelin protein P0 in membrane stacking

Compact myelin forms the basis of nerve insulation essential for higher vertebrates. Dozens of myelin membrane bilayers undergo tight stacking, and in the peripheral nervous system, this is partially enabled by myelin protein zero (P0). Consisting of an immunoglobulin (Ig)-like extracellular domain, a single transmembrane helix, and a cytoplasmic extension (P0ct), P0 harbours an important task in ensuring the integrity of compact myelin in the extracellular compartment, referred to as the intraperiod line. Several disease mutations resulting in peripheral neuropathies have been identified for P0, reflecting its physiological importance, but the arrangement of P0 within the myelin ultrastructure remains obscure. We performed a biophysical characterization of recombinant P0ct. P0ct contributes to the binding affinity between apposed cytoplasmic myelin membrane leaflets, which not only results in fluidity changes of the bilayers themselves, but also potentially involves the rearrangement of the Ig-like domains in a manner that stabilizes the intraperiod line. Transmission electron cryomicroscopy of native full-length P0 showed that P0 stacks lipid membranes by forming antiparallel dimers between the extracellular Ig-like domains. The zipper-like arrangement of the P0 extracellular domains between two membranes explains the double structure of the myelin intraperiod line. Our results contribute to the understanding of PNS myelin, the role of P0 therein, and the underlying molecular foundation of compact myelin stability in health and disease.

biochemistry↗

bioRxiv2018

A neuromechanistic model for rhythmic beat generation

When listening to music, humans can easily identify and move to the beat. Numerous experimental studies have identified brain regions that may be involved with beat perception and representation. Several theoretical and algorithmic approaches have been proposed to account for this ability. Related to, but different from the issue of how we perceive a beat, is the question of how we learn to generate and hold a beat. In this paper, we introduce a neuronal framework for a beat generator that is capable of learning isochronous rhythms over a range of frequencies that are relevant to music and speech. Our approach combines ideas from error-correction and entrainment models to investigate the dynamics of how a biophysically-based neuronal network model synchronizes its period and phase to match that of an external stimulus. The model makes novel use of on-going faster gamma rhythms to form a set of discrete clocks that provide estimates, but not exact information, of how well the beat generator spike times match those of a stimulus sequence. The beat generator is endowed with plasticity allowing it to quickly learn and thereby adjust its spike times to achieve synchronization. Our model makes generalizable predictions about the existence of asymmetries in the synchronization process, as well as specific predictions about resynchronization times after changes in stimulus tempo or phase. Analysis of the model demonstrates that accurate rhythmic time keeping can be achieved over a range of frequencies relevant to music, in a manner that is robust to changes in parameters and to the presence of noise. Author summaryMusic is integral to human experience and is appreciated across a wide range of cultures. Although many features distinguish different musical traditions, rhythm is central to nearly all. Most humans can detect and move along to the beat through finger or foot tapping, hand clapping or other bodily movements. But many people have a hard time "keeping a beat", or say they have "no sense of rhythm". There appears to be a disconnect between our ability to perceive a beat versus our ability to produce a beat, as a drummer would do as part of a musical group. Producing a beat requires beat generation, the process by which we learn how to keep track of the specific time intervals between beats, as well as executing the motor movement needed to produce the sound associated with a beat. In this paper, we begin to explore neural mechanisms that may be responsible for our ability to generate and keep a beat. We develop a computational model that includes different neurons and shows how they cooperate to learn a beat and keep it, even after the stimulus is removed, across a range of frequencies relevant to music. Our dynamical systems model leads to predictions for how the brain may react when learning a beat. Our findings and techniques should be widely applicable to those interested in understanding how the brain processes time, particularly in the context of music.

neuroscience↗

bioRxiv2018

LION/web: a web-based ontology enrichment tool for lipidomic data analysis

A major challenge for lipidomic analyses is the handling of the large amounts of data and the translation of results to interpret the involvement of lipids in biological systems. We built a new lipid ontology (LION) that associates over 50,000 lipid species to biophysical, chemical and cell biological features. By making use of enrichment algorithms, we used LION to develop a web-based interface (LION/web, www.lipidontology.com) that allows identification of lipid-associated terms in lipidomes. LION/web was validated by analyzing a lipidomic dataset derived from well-characterized sub-cellular fractions of RAW 264.7 macrophages. Comparison of isolated plasma membranes with the microsomal fraction showed a significant enrichment of relevant LION-terms including plasma membrane, headgroup with negative charge, glycerophosphoserines, above average bilayer thickness, and below average lateral diffusion. A second validation was performed by analyzing the membrane fluidity of CHO cells incubated with arachidonic acid. An increase in membrane fluidity was observed both experimentally by using pyrene decanoic acid and by using LION/web, showing significant enrichment of terms associated with high membrane fluidity ('above average, 'very high and 'high lateral diffusion, and 'below average transition temperature). The results demonstrate the functionality of LION/web, which is freely accessible in a platform-independent way.

biochemistry↗

bioRxiv2018

A model for physiological transmembrane transport derived from thermodynamical principles

A generic formulation for both passive and active transmembrane transport is derived from basic thermodynamical principles. The derivation takes into account the energy required for the motion of molecules across membranes, and includes the possibility of modeling asymmetric flow. Transmembrane currents can then be described by the generic model in the case of electrogenic flow. As it is desirable in new models, it is possible to derive other well known expressions for transmembrane currents as particular cases of the generic formulation. For instance, the conductance-based formulation for current turns out to be a linear approximation of the generic current. Also, under suitable assumptions, other formulas for current based on electrodiffusion, like the constant field approximation by Goldman, can also be recovered from the generic formulation. The applicability of the generic formulations is illustrated first with fits to existing data, and after, with models of transmembrane potential dynamics for pacemaking cardiocytes and neurons. The generic formulations presented here provide a common ground for the biophysical study of physiological phenomena that depend on transmembrane transport.

physiology↗