Ten simple rules for managing laboratory information.

Information is the cornerstone of research, from experimental (meta)data and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems to transform this large information load into useful scientific findings.

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments.

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise.

Introduction: Despite continued technological improvements, measurement errors always reduce or distort the information that any real experiment can provide to quantify cellular dynamics. This problem is particularly serious for cell signaling studies to quantify heterogeneity in single-cell gene regulation, where important RNA and protein copy numbers are themselves subject to the inherently random fluctuations of biochemical reactions. Until now, it has not been clear how measurement noise should be managed in addition to other experiment design variables (e.g., sampling size, measurement times, or perturbation levels) to ensure that collected data will provide useful insights on signaling or gene expression mechanisms of interest. Methods: We propose a computational framework that takes explicit consideration of measurement errors to analyze single-cell observations, and we derive Fisher Information Matrix (FIM)-based criteria to quantify the information value of distorted experiments. Results and Discussion: We apply this framework to analyze multiple models in the context of simulated and experimental single-cell data for a reporter gene controlled by an HIV promoter. We show that the proposed approach quantitatively predicts how different types of measurement distortions affect the accuracy and precision of model identification, and we demonstrate that the effects of these distortions can be mitigated through explicit consideration during model inference. We conclude that this reformulation of the FIM could be used effectively to design single-cell experiments to optimally harvest fluctuation information while mitigating the effects of image distortion.

Using Mechanistic Models and Machine Learning to Design Single-Color Multiplexed Nascent Chain Tracking Experiments.

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Through simulation, we show that with careful application, this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. The proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell signalling applications requiring simultaneous study of multiple mRNAs.

Non-equilibrium view of the amorphous solidification of liquids with competing interactions.

The interplay between short-range attractions and long-range repulsions (SALR) characterizes the so-called liquids with competing interactions, which are known to exhibit a variety of equilibrium and non-equilibrium phases. The theoretical description of the phenomenology associated with glassy or gel states in these systems has to take into account both the presence of thermodynamic instabilities (such as those defining the spinodal line and the so called λ line) and the limited capability to describe genuine non-equilibrium processes from first principles. Here, we report the first application of the non-equilibrium self-consistent generalized Langevin equation theory to the description of the dynamical arrest processes that occur in SALR systems after being instantaneously quenched into a state point in the regions of thermodynamic instability. The physical scenario predicted by this theory reveals an amazing interplay between the thermodynamically driven instabilities, favoring equilibrium macro- and micro-phase separation, and the kinetic arrest mechanisms, favoring non-equilibrium amorphous solidification of the liquid into an unexpected variety of glass and gel states.

From Subaging to Hyperaging in Structural Glasses.

We demonstrate nonequilibrium scaling laws for the aging and equilibration dynamics in glass formers that emerge from combining a relaxation equation for the static structure with the equilibrium scaling laws of glassy dynamics. Different scaling regimes are predicted for the evolution of the structural relaxation time τ with age (waiting time t_{w}), depending on the depth of the quench from the liquid into the glass: "simple" aging (τ∼t_{w}) applies for quenches close to the critical point of mode-coupling theory (MCT) and implies "subaging" (τ≈t_{w}^{δ} with δ<1) as a broad equilibration crossover for quenches to nearly arrested equilibrium states; "hyperaging" (or superaging, τ∼t_{w}^{δ^{'}} with δ^{'}>1) emerges for quenches deep into the glass. The latter is cut off by non-mean-field fluctuations that we account for within a recent extension of MCT, the stochastic ß-relaxation theory (SBR). We exemplify the scaling laws with a schematic model that quantitatively fits simulation data.

Stochastic dynamics of Type-I interferon responses.

Interferon (IFN) activates the transcription of several hundred of IFN stimulated genes (ISGs) that constitute a highly effective antiviral defense program. Cell-to-cell variability in the induction of ISGs is well documented, but its source and effects are not completely understood. The molecular mechanisms behind this heterogeneity have been related to randomness in molecular events taking place during the JAK-STAT signaling pathway. Here, we study the sources of variability in the induction of the IFN-alpha response by using MxA and IFIT1 activation as read-out. To this end, we integrate time-resolved flow cytometry data and stochastic modeling of the JAK-STAT signaling pathway. The complexity of the IFN response was matched by fitting probability distributions to time-course flow cytometry snapshots. Both, experimental data and simulations confirmed that the MxA and IFIT1 induction circuits generate graded responses rather than all-or-none responses. Subsequently, we quantify the size of the intrinsic variability at different steps in the pathway. We found that stochastic effects are transiently strong during the ligand-receptor activation steps and the formation of the ISGF3 complex, but negligible for the final induction of the studied ISGs. We conclude that the JAK-STAT signaling pathway is a robust biological circuit that efficiently transmits information under stochastic environments.

"Inner clocks" of glass-forming liquids.

Providing a physically sound explanation of aging phenomena in non-equilibrium amorphous materials is a challenging problem in modern statistical thermodynamics. The slow evolution of physical properties after quenches of control parameters is empirically well interpreted via the concept of material time (or internal clock) based on the Tool-Narayanaswamy-Moynihan model. Yet, the fundamental reasons of its striking success remain unclear. We propose a microscopic rationale behind the material time on the basis of the linear laws of irreversible thermodynamics and its extension that treats the corresponding kinetic coefficients as state functions of a slowly evolving material state. Our interpretation is based on the recognition that the same mathematical structure governs both the Tool model and the recently developed non-equilibrium extension of the self-consistent generalized Langevin equation theory, guided by the universal principles of Onsager's theory of irreversible processes. This identification opens the way for a generalization of the material-time concept to aging systems where several relaxation modes with very different equilibration processes must be considered, and partially frozen glasses manifest the appearance of partial ergodicity breaking and, hence, materials with multiple very distinct inner clocks.

Non-equilibrium relaxation and aging in the dynamics of a dipolar fluid quenched towards the glass transition.

The recently developed non-equilibrium self-consistent generalized Langevin equation theory of the dynamics of liquids of non-spherically interacting particles [2016J. Phys. Chem. B1207975] is applied to the description of the irreversible relaxation of a thermally and mechanically quenched dipolar fluid. Specifically, we consider a dipolar hard-sphere liquid quenched (attw= 0) from full equilibrium conditions towards different ergodic-non-ergodic transitions. Qualitatively different scenarios are predicted by the theory for the time evolution of the system after the quench (tw> 0), that depend on both the kind of transition approached and the specific features of the protocol of preparation. Each of these scenarios is characterized by the kinetics displayed by a set of structural correlations, and also by the development of two characteristic times describing the relaxation of the translational and rotational dynamics, allowing us to highlight the crossover from equilibration to aging in the system and leading to the prediction of different underlying mechanisms and relaxation laws for the dynamics at each of the glass transitions explored.

Structure and dynamics of highly concentrated LiTFSI/acetonitrile electrolytes.

High salt concentration has been shown to induce increased electrochemical stability in organic solvent-based electrolytes. Accompanying the change in bulk properties is a structural ordering on mesoscopic length scales and changes in the ion transport mechanism have also been suggested. Here we investigate the local structure and dynamics in highly concentrated acetonitrile electrolytes as a function of salt concentration. Already at low concentrations ordering on microscopic length scales in the electrolytes is revealed by small angle X-ray scattering, as a result of correlations of Li+ coordinating clusters. For higher salt concentrations a charge alternation-like ordering is found as anions start to take part in the solvation. Results from quasi-elastic neutron spectroscopy reveal a jump diffusion dynamical process with jump lengths virtually independent of both temperature and Li-salt concentration. The jump can be envisaged as dissociation of a solvent molecule or anion from a particular Li+ solvation structure. The residence time, 50-800 ps, between the jumps is found to be highly temperature and Li-salt concentration dependent, with shorter residence times for higher temperature and lower concentrations. The increased residence time at high Li-salt concentration can be attributed to changes in the interaction of the solvation shell as a larger fraction of TFSI anions take part in the solvation, forming more stable solvation shells.

Design, Implementation, and Configuration of Laser Systems for Vehicle Detection and Classification in Real Time.

The use of real-time vehicle detection and classification systems is essential for the accurate management of traffic and road infrastructure. Over time, diverse systems have been proposed for it, such as the widely known magnetic loops or microwave radars. However, these types of sensors do not offer all the information currently required for exhaustive and comprehensive traffic control. Thus, this paper presents the design, implementation, and configuration of laser systems to obtain 3D profiles of vehicles, which collect more precise information about the state of the roads. Nevertheless, to obtain reliable information on vehicle traffic by means of these systems, it is fundamental to correctly carry out a series of preliminary steps: choose the most suitable type of laser, select its configuration properly, determine the optimal location, and process the information provided accurately. Therefore, this paper details a series of criteria to help make these crucial and difficult decisions. Furthermore, following these guidelines, a complete laser system implemented for vehicle detection and classification is presented as result, which is characterized by its versatility and the ability to control up to four lanes in real time.

Modeling the intracellular dynamics of the dengue viral infection and the innate immune response.

The interplay between the dengue virus and the innate immune response is not fully understood. Here, we use deterministic and stochastic approaches to investigate the dynamics of the interaction between the interferon-mediated innate immune response and the dengue virus. We aim to develop a quantitative representation of these complex interactions and predict their system-level dynamics. Our simulation results predict bimodal and bistable dynamics that represent viral clearance and virus-producing states. Under normal conditions, we determined that the viral infection outcome is modulated by the innate immune response and the positive-strand viral RNA concentration. Additionally, we tested system perturbations by external stimulation, such as the direct induction of the innate immune response by interferon, and a therapeutic intervention consisting of the direct application of mRNA encoding for several interferon-stimulated genes. Our simulation results suggest optimal regimes for the studied intervention approaches.

Author Correction: Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells.

Viruses use internal ribosome entry sites (IRES) to hijack host ribosomes and promote cap-independent translation. Although they are well-studied in bulk, the dynamics of IRES-mediated translation remain unexplored at the single-molecule level. Here, we developed a bicistronic biosensor encoding distinct repeat epitopes in two open reading frames (ORFs), one translated from the 5' cap, and the other from the encephalomyocarditis virus IRES. When combined with a pair of complementary probes that bind the epitopes cotranslationally, the biosensor lights up in different colors depending on which ORF is translated. Using the sensor together with single-molecule tracking and computational modeling, we measured the kinetics of cap-dependent versus IRES-mediated translation in living human cells. We show that bursts of IRES translation are shorter and rarer than bursts of cap translation, although the situation reverses upon stress. Collectively, our data support a model for translational regulation primarily driven by transitions between translationally active and inactive RNA states.

Spherical harmonic projections of the static structure factor of the dipolar hard sphere model: Theory vs simulations.

We investigate the static correlations of a dipolar fluid in terms of the irreducible coefficients of the spherical harmonic expansion of the static structure factor. To this end, we develop a theoretical framework based on a soft-core version of Wertheim's solution of the mean spherical approximation (MSA), which renders the analytical determination of such coefficients possible. The accuracy of this approximation is tested by a comparison against the results obtained with the assistance of extensive molecular dynamics simulations at different regimes of concentration and temperature. Crucial aspects for the comparison of the results provided by the two methods are carefully discussed, concerning the different reference frames used in theory and simulations to describe rotations and orientations, and leading to important differences in the behavior of correlation functions with the same combination of spherical harmonic indices. We find a remarkable agreement between the two approaches in the fluid regime, thus providing a first stringent comparison of the irreducible coefficients of the spherical harmonic expansion of the dipolar fluid's static structure factor, provided by the MSA theory and molecular dynamics simulations.

Arrested dynamics of the dipolar hard sphere model.

We report the combined results of molecular dynamics simulations and theoretical calculations concerning various dynamical arrest transitions in a model system representing a dipolar fluid, namely, N (soft core) rigid spheres interacting through a truncated dipole-dipole potential. By exploring different regimes of concentration and temperature, we find three distinct scenarios for the slowing down of the dynamics of the translational and orientational degrees of freedom: at low (η = 0.2) and intermediate (η = 0.4) volume fractions, both dynamics are strongly coupled and become simultaneously arrested upon cooling. At high concentrations (η≥ 0.6), the translational dynamics shows the features of an ordinary glass transition, either by compressing or cooling down the system, but with the orientations remaining ergodic, thus indicating the existence of partially arrested states. In this density regime, but at lower temperatures, the relaxation of the orientational dynamics also freezes. The physical scenario provided by the simulations is discussed and compared against results obtained with the self-consistent generalized Langevin equation theory, and both provide a consistent description of the dynamical arrest transitions in the system. Our results are summarized in an arrested states diagram which qualitatively organizes the simulation data and provides a generic picture of the glass transitions of a dipolar fluid.

Computational design and interpretation of single-RNA translation experiments.

Advances in fluorescence microscopy have introduced new assays to quantify live-cell translation dynamics at single-RNA resolution. We introduce a detailed, yet efficient sequence-based stochastic model that generates realistic synthetic data for several such assays, including Fluorescence Correlation Spectroscopy (FCS), ribosome Run-Off Assays (ROA) after Harringtonine application, and Fluorescence Recovery After Photobleaching (FRAP). We simulate these experiments under multiple imaging conditions and for thousands of human genes, and we evaluate through simulations which experiments are most likely to provide accurate estimates of elongation kinetics. Finding that FCS analyses are optimal for both short and long length genes, we integrate our model with experimental FCS data to capture the nascent protein statistics and temporal dynamics for three human genes: KDM5B, ß-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (rSNAPsim), to easily simulate the single-molecule translation dynamics of any gene sequence for any of these assays and for different assumptions regarding synonymous codon usage, tRNA level modifications, or ribosome pauses. rSNAPsim is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git.

Efecto de un entrenamiento corto en habilidades de comunicación con el método CICAA (conectar, identificar, comprender, acordar y ayudar), en médicos residentes de una universidad peruana / Effect of a short training in communication abilities with the CICAA method in an university in Lima, Peru

Objetivo: Evaluar la eficacia de un entrenamiento corto en habilidades de comunicación con el método CICAA (conectar, identificar, comprender, acordar y ayudar) en una universidad de Lima-Perú. Material y métodos: Estudio de intervención antes y después, donde cada médico residente fue su propio control. Participantes: 25 médicos residentes del primer año académico de los programas de especialización en medicina familiar, medicina interna y pediatría de la Universidad Peruana Cayetano Heredia (UPCH). Intervención: Entrenamiento en entrevista clínica basado en el método CICAA. El método CICAA incluye cuatro tareas agrupadas en tres dominios: Conectar (dominio 1), Identificar y comprender (dominio 2), Acordar y Ayudar (dominio 3). Se realizó un entrenamiento de 26 horas de duración, el cual consistió en clases teóricas, talleres, role-play de escenarios diseñados por los docentes y alumnos. Se diseñó una evaluación clínica objetiva estructurada (ECOE) con la participación de dos pacientes estandarizados. Se utilizó el score CICAA para calificar la entrevista clínica tanto antes como una semana después del entrenamiento. Resultados: La media de la calificación total antes del entrenamiento fue de 29,84 ± 1,44; 8,72 ± 0,33, 12,8 ± 1,02 y 8,32 ± 0,67 para los dominios 1, 2 y 3, respectivamente. Después del entrenamiento, la calificación total fue de 40,84 ± 1,32; 11 ± 0,26, 16,04 ± 1,01 y 13,44 ± 0,51, para los dominios 1,2 y 3, respectivamente. Conclusiones: La implementación de un entrenamiento corto sobre habilidades de comunicación basado en teoría y juego de roles tiene un impacto positivo en una evaluación temprana.

Objective: To evaluate the efficacy of a short training in communication abilities with the CICAA method in a university in Lina, Peru. Methods: A before-after study design was undertaken where each resident was a control. Participants: 25 first year residents of family medicine, internal medicine and pediatrics of Universidad Peruana Cayetano Heredia. Intervention: training in the CICAA method which includes four areas grouped in three domains; connecting (domain 1), identifying and learning (domain 2); and remembering and helping (domain 3). A short training of 26 hours was conducted including lectures, workshops, and play-role activities for students and teachers. A structure objective assessment with the participation of two standardized patients was carried-out. CICAA score was used to evaluate the clinical interview one week before and after the training. Results: The mean value of the overall evaluation was 29.84 ± 1.44; 8.72 ± 0.33, 12.8 ± 1.02 and 8.32 ± 0.67 for domains 1-3, respectively. Values after the training were 40.84 ± 1.32; 11 ± 0.26, 16.04 ± 1.01 and 13.44 ± 0.51, for domains 1-3, respectively. Conclusion: The implementation of a short training in communication abilities based on lectures and play-role has a positive impact on an early evaluation.

Live-Cell Single RNA Imaging Reveals Bursts of Translational Frameshifting.

Ribosomal frameshifting during the translation of RNA is implicated in human disease and viral infection. While previous work has uncovered many details about single RNA frameshifting kinetics in vitro, little is known about how single RNA frameshift in living systems. To confront this problem, we have developed technology to quantify live-cell single RNA translation dynamics in frameshifted open reading frames. Applying this technology to RNA encoding the HIV-1 frameshift sequence reveals a small subset (∼8%) of the translating pool robustly frameshift. Frameshifting RNA are translated at similar rates as non-frameshifting RNA (∼3 aa/s) and can continuously frameshift for more than four rounds of translation. Fits to a bursty model of frameshifting constrain frameshifting kinetic rates and demonstrate how ribosomal traffic jams contribute to the persistence of the frameshifting state. These data provide insight into retroviral frameshifting and could lead to alternative strategies to perturb the process in living cells.

Glassy dynamics in asymmetric binary mixtures of hard spheres.

We perform a systematic and detailed study of the glass transition in highly asymmetric binary mixtures of colloidal hard spheres, combining differential dynamic microscopy experiments, event-driven molecular dynamics simulations, and theoretical calculations, exploring the whole state diagram and determining the self-dynamics and collective dynamics of both species. Two distinct glassy states involving different dynamical arrest transitions are consistently described, namely, a double glass with the simultaneous arrest of the self-dynamics and collective dynamics of both species, and a single glass of large particles in which the self-dynamics of the small species remains ergodic. In the single-glass scenario, spatial modulations in the collective dynamics of both species occur due to the structure of the large spheres, a feature not observed in the double-glass domain. The theoretical results, obtained within the self-consistent generalized Langevin equation formalism, are in agreement with both simulations and experimental data, thus providing a stringent validation of this theoretical framework in the description of dynamical arrest in highly asymmetric mixtures. Our findings are summarized in a state diagram that classifies the various amorphous states of highly asymmetric mixtures by their dynamical arrest mechanisms.