Visual perception of texture regularity: Conjoint measurements and a wavelet response-distribution model
by Hua-Chun Sun, David St-Amand, Curtis L. Baker Jr., Frederick A. A. Kingdom Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements’ positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) for the first time to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in additio...
Source: PLoS Computational Biology - October 15, 2021 Category: Biology Authors: Hua-Chun Sun Source Type: research

State transitions through inhibitory interneurons in a cortical network model
by Alexander Bryson, Samuel F. Berkovic, Steven Petrou, David B. Grayden Inhibitory interneurons shape the spiking characteristics and computational properties of cortical networks. Interneuron subtypes can precisely regulate cortical function but the roles of interneuron subtypes for promoting different regimes of cortical activity remains unclear. Therefore, we inves tigated the impact of fast spiking and non-fast spiking interneuron subtypes on cortical activity using a network model with connectivity and synaptic properties constrained by experimental data. We found that network properties were more sensitive to modul...
Source: PLoS Computational Biology - October 15, 2021 Category: Biology Authors: Alexander Bryson Source Type: research

On testing structural identifiability by a simple scaling method: Relying on scaling symmetries can be misleading
by Alejandro F. Villaverde, Gemma Massonis A recent paper published inPLOS Computational Biology [1] introduces the Scaling Invariance Method (SIM) for analysing structural local identifiability and observability. These two properties define mathematically the possibility of determining the values of the parameters (identifiability) and states (observability) of a dynamic model by observing its output. In this note we warn that SIM considers scaling symmetries as the only possible cause of non-identifiability and non-observability. We show that other types of symmetries can cause the same problems without being detected b...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Alejandro F. Villaverde Source Type: research

Interplay between mobility, multi-seeding and lockdowns shapes COVID-19 local impact
by Mattia Mazzoli, Emanuele Pepe, David Mateo, Ciro Cattuto, Laetitia Gauvin, Paolo Bajardi, Michele Tizzoni, Alberto Hernando, Sandro Meloni, Jos é J. Ramasco Assessing the impact of mobility on epidemic spreading is of crucial importance for understanding the effect of policies like mass quarantines and selective re-openings. While many factors affect disease incidence at a local level, making it more or less homogeneous with respect to other areas, th e importance of multi-seeding has often been overlooked. Multi-seeding occurs when several independent (non-clustered) infected individuals arrive at a susceptible...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Mattia Mazzoli Source Type: research

Universal risk phenotype of US counties for flu-like transmission to improve county-specific COVID-19 incidence forecasts
This study demonstrates that knowledge of past epidemics may be used to chart the course of future ones, if transmission mechanisms are broad ly similar, despite distinct disease processes and causative pathogens. (Source: PLoS Computational Biology)
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Yi Huang Source Type: research

Segmentation and genome annotation algorithms for identifying chromatin state and other genomic patterns
by Maxwell W. Libbrecht, Rachel C. W. Chan, Michael M. Hoffman Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These algorithms take as input epigenomic datasets, such as chromatin immunoprecipitation-sequencing (ChIP-seq) measurements of histone modifications or transcription factor bind ing. They partition the genome and assign a label to each segment such that positions with the same label exhibit similar patterns of input data. SAGA algorithms discover categories of activity such as promoters, enhancers, or parts of genes without prior knowledge o...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Maxwell W. Libbrecht Source Type: research

The limitations, dangers, and benefits of simple methods for testing identifiability
by Mario Castro, Rob J. de Boer In their Commentary paper, Villaverde and Massonis (On testing structural identifiability by a simple scaling method: relying on scaling symmetries can be misleading) have commented on our paper in which we proposed a simple scaling method to test structural identifiability. Our scaling invariance method (SIM) tests for scaling symmetries only, and Villaverde and Massonis correctly show the SIM may fail to detect identifiability problems when a model has other types of symmetries. We agree with the limitations raised by these authors but, also, we emphasize that the method is still valuable...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Mario Castro Source Type: research

Dynamics and turnover of memory CD8 T cell responses following yellow fever vaccination
by Veronika I. Zarnitsyna, Rama S. Akondy, Hasan Ahmed, Donald J. McGuire, Vladimir G. Zarnitsyn, Mia Moore, Philip L. F. Johnson, Rafi Ahmed, Kelvin W. Li, Marc K. Hellerstein, Rustom Antia Understanding how immunological memory lasts a lifetime requires quantifying changes in the number of memory cells as well as how their division and death rates change over time. We address these questions by using a statistically powerful mixed-effects differential equations framework to analyze data from two human studies that follow CD8 T cell responses to the yellow fever vaccine (YFV-17D). Models were first fit to the frequency o...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Veronika I. Zarnitsyna Source Type: research

Slipknotted and unknotted monovalent cation-proton antiporters evolved from a common ancestor
by Vasilina Zayats, Agata P. Perlinska, Aleksandra I. Jarmolinska, Borys Jastrzebski, Stanislaw Dunin-Horkawicz, Joanna I. Sulkowska While the slipknot topology in proteins has been known for over a decade, its evolutionary origin is still a mystery. We have identified a previously overlooked slipknot motif in a family of two-domain membrane transporters. Moreover, we found that these proteins are homologous to several families of unknotted membrane proteins. This allows us to directly investigate the evolution of the slipknot motif. Based on our comprehensive analysis of 17 distantly related protein families, we have fou...
Source: PLoS Computational Biology - October 14, 2021 Category: Biology Authors: Vasilina Zayats Source Type: research

Steady-state measures of visual suppression
by Daniel H. Baker, Greta Vilidaite, Alex R. Wade In the early visual system, suppression occurs between neurons representing different stimulus properties. This includes features such as orientation (cross-orientation suppression), eye-of-origin (interocular suppression) and spatial location (surround suppression), which are thought to involve d istinct anatomical pathways. We asked if these separate routes to suppression can be differentiated by their pattern of gain control on the contrast response function measured in human participants using steady-state electroencephalography. Changes in contrast gain shift the cont...
Source: PLoS Computational Biology - October 13, 2021 Category: Biology Authors: Daniel H. Baker Source Type: research

Modular assembly of dynamic models in systems biology
by Michael Pan, Peter J. Gawthrop, Joseph Cursons, Edmund J. Crampin It is widely acknowledged that the construction of large-scale dynamic models in systems biology requires complex modelling problems to be broken up into more manageable pieces. To this end, both modelling and software frameworks are required to enable modular modelling. While there has been consi stent progress in the development of software tools to enhance model reusability, there has been a relative lack of consideration for how underlying biophysical principles can be applied to this space. Bond graphs combine the aspects of both modularity and phys...
Source: PLoS Computational Biology - October 13, 2021 Category: Biology Authors: Michael Pan Source Type: research

qc3C: Reference-free quality control for Hi-C sequencing data
by Matthew Z. DeMaere, Aaron E. Darling Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assembli es and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, preparing a Hi-C library remains a complex laboratory protocol. To avoid costly failures and maximise the odds of successful outcomes, diligent quality management is...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Matthew Z. DeMaere Source Type: research

Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers
by Yao-zhong Zhang, Seiya Imoto, Satoru Miyano, Rui Yamaguchi Read-depths (RDs) are frequently used in identifying structural variants (SVs) from sequencing data. For existing RD-based SV callers, it is difficult for them to determine breakpoints in single-nucleotide resolution due to the noisiness of RD data and the bin-based calculation. In this paper, we propose to use the deep segmentation model UNet to learn base-wise RD patterns surrounding breakpoints of known SVs. We integrate model predictions with an RD-based SV caller to enhance breakpoints in single-nucleotide resolution. We show that UNet can be trained with ...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Yao-zhong Zhang Source Type: research

Improved prediction of smoking status via isoform-aware RNA-seq deep learning models
by Zifeng Wang, Aria Masoomi, Zhonghui Xu, Adel Boueiz, Sool Lee, Tingting Zhao, Russell Bowler, Michael Cho, Edwin K. Silverman, Craig Hersh, Jennifer Dy, Peter J. Castaldi Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effec ts on gene expression. Using smoking status as a prediction target, we developed deep neural network predictive models using gene, exon, and isoform level q...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Zifeng Wang Source Type: research

The information theory of developmental pruning: Optimizing global network architectures using local synaptic rules
by Carolin Scholl, Michael E. Rule, Matthias H. Hennig During development, biological neural networks produce more synapses and neurons than needed. Many of these synapses and neurons are later removed in a process known as neural pruning. Why networks should initially be over-populated, and the processes that determine which synapses and neurons are ultimately pruned, remains unclear. We study the mechanisms and significance of neural pruning in model neural networks. In a deep Boltzmann machine model of sensory encoding, we find that (1) synaptic pruning is necessary to learn efficient network architectures that retain ...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Carolin Scholl Source Type: research

Frank-Starling mechanism, fluid responsiveness, and length-dependent activation: Unravelling the multiscale behaviors with an in silico analysis
In this study, we use a multiscale model of the cardiovascular system to untangle the three concepts (length-dependent activation, Frank -Starling, and vascular filling). We first show that length-dependent activation is required to observe both the Frank-Starling mechanism and a positive response to high vascular fillings. Our results reveal a dynamical length dependent activation-driven response to changes in preload, which involve s interactions between the cellular, ventricular and cardiovascular levels and thus highlights fundamentally multiscale behaviors. We show however that the cellular force increase is not enoug...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Sarah Kosta Source Type: research

Cortical feedback and gating in odor discrimination and generalization
by Gaia Tavoni, David E. Chen Kersen, Vijay Balasubramanian A central question in neuroscience is how context changes perception. In the olfactory system, for example, experiments show that task demands can drive divergence and convergence of cortical odor responses, likely underpinning olfactory discrimination and generalization. Here, we propose a simple statistical mechanism for this effect based on unstructured feedback from the central brain to the olfactory bulb, which represents the context associated with an odor, and sufficiently selective cortical gating of sensory inputs. Strikingly, the model predicts that bot...
Source: PLoS Computational Biology - October 11, 2021 Category: Biology Authors: Gaia Tavoni Source Type: research

Tracking calcium dynamics from individual neurons in behaving animals
We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC2) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from two-photon volumetric microscopy in visual cortex of awake mice, and from confocal microscopy in behavingHydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth ...
Source: PLoS Computational Biology - October 8, 2021 Category: Biology Authors: Thibault Lagache Source Type: research

Segmentation-Less, Automated, Vascular Vectorization
by Samuel A. Mihelic, William A. Sikora, Ahmed M. Hassan, Michael R. Williamson, Theresa A. Jones, Andrew K. Dunn Recent advances in two-photon fluorescence microscopy (2PM) have allowed large scale imaging and analysis of blood vessel networks in living mice. However, extracting network graphs and vector representations for the dense capillary bed remains a bottleneck in many applications. Vascular vectoriza tion is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art...
Source: PLoS Computational Biology - October 8, 2021 Category: Biology Authors: Samuel A. Mihelic Source Type: research

Engineering gene overlaps to sustain genetic constructs < i > in vivo < /i >
by Antoine L. Decrulle, Antoine Fr énoy, Thomas A. Meiller-Legrand, Aude Bernheim, Chantal Lotton, Arnaud Gutierrez, Ariel B. Lindner Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential ge...
Source: PLoS Computational Biology - October 8, 2021 Category: Biology Authors: Antoine L. Decrulle Source Type: research

Pulsed low-energy stimulation initiates electric turbulence in cardiac tissue
by Rupamanjari Majumder, Sayedeh Hussaini, Vladimir S. Zykov, Stefan Luther, Eberhard Bodenschatz Interruptions in nonlinear wave propagation, commonly referred to as wave breaks, are typical of many complex excitable systems. In the heart they lead to lethal rhythm disorders, the so-called arrhythmias, which are one of the main causes of sudden death in the industrialized world. Progress in t he treatment and therapy of cardiac arrhythmias requires a detailed understanding of the triggers and dynamics of these wave breaks. In particular, two very important questions are: 1) What determines the potential of a wave break t...
Source: PLoS Computational Biology - October 8, 2021 Category: Biology Authors: Rupamanjari Majumder Source Type: research

Narrative event segmentation in the cortical reservoir
by Peter Ford Dominey Recent research has revealed that during continuous perception of movies or stories, humans display cortical activity patterns that reveal hierarchical segmentation of event structure. Thus, sensory areas like auditory cortex display high frequency segmentation related to the stimulus, while seman tic areas like posterior middle cortex display a lower frequency segmentation related to transitions between events. These hierarchical levels of segmentation are associated with different time constants for processing. Likewise, when two groups of participants heard the same sentence in a narrative , prece...
Source: PLoS Computational Biology - October 7, 2021 Category: Biology Authors: Peter Ford Dominey Source Type: research

Paranoia, self-deception and overconfidence
by Rosa A. Rossi-Goldthorpe, Yuan Chang Leong, Pantelis Leptourgos, Philip R. Corlett Self-deception, paranoia, and overconfidence involve misbeliefs about the self, others, and world. They are often considered mistaken. Here we explore whether they might be adaptive, and further, whether they might be explicable in Bayesian terms. We administered a difficult perceptual judgment ta sk with and without social influence (suggestions from a cooperating or competing partner). Crucially, the social influence was uninformative. We found that participants heeded the suggestions most under the most uncertain conditions and that t...
Source: PLoS Computational Biology - October 7, 2021 Category: Biology Authors: Rosa A. Rossi-Goldthorpe Source Type: research

Molecular mechanism of proton-coupled ligand translocation by the bacterial efflux pump EmrE
by Jakub Jurasz, Maciej Bagi ński, Jacek Czub, Miłosz Wieczór The current surge in bacterial multi-drug resistance (MDR) is one of the largest challenges to public health, threatening to render ineffective many therapies we rely on for treatment of serious infections. Understanding different factors that contribute to MDR is hence crucial from the global “ one health” perspective. In this contribution, we focus on the prototypical broad-selectivity proton-coupled antiporter EmrE, one of the smallest known ligand transporters that confers resistance to aromatic cations in a number of clinically relevan...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Jakub Jurasz Source Type: research

Recursive MAGUS: Scalable and accurate multiple sequence alignment
by Vladimir Smirnov Multiple sequence alignment tools struggle to keep pace with rapidly growing sequence data, as few methods can handle large datasets while maintaining alignment accuracy. We recently introduced MAGUS, a new state-of-the-art method for aligning large numbers of sequences. In this paper, we present a comprehensive set of enhancements that allow MAGUS to align vastly larger datasets with greater speed. We compare MAGUS to other leading alignment methods on datasets of up to one million sequences. Our results demonstrate the advantages of MAGUS over other alignment software in both accuracy and speed. MAGU...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Vladimir Smirnov Source Type: research

Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans
by Yashika Arora, Pushpinder Walia, Mitsuhiro Hayashibe, Makii Muthalib, Shubhajit Roy Chowdhury, Stephane Perrey, Anirban Dutta Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-comp artmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Yashika Arora Source Type: research

Sarc-Graph: Automated segmentation, tracking, and analysis of sarcomeres in hiPSC-derived cardiomyocytes
by Bill Zhao, Kehan Zhang, Christopher S. Chen, Emma Lejeune A better fundamental understanding of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) has the potential to advance applications ranging from drug discovery to cardiac repair. Automated quantitative analysis of beating hiPSC-CMs is an important and fast developing component o f the hiPSC-CM research pipeline. Here we introduce “Sarc-Graph,” a computational framework to segment, track, and analyze sarcomeres in fluorescently tagged hiPSC-CMs. Our framework includes functions to segment z-discs and sarcomeres, track z-discs and sa...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Bill Zhao Source Type: research

A metric for evaluating biological information in gene sets and its application to identify co-expressed gene clusters in PBMC
by Jason Bennett, Mikhail Pomaznoy, Akul Singhania, Bjoern Peters Recent technological advances have made the gathering of comprehensive gene expression datasets a commodity. This has shifted the limiting step of transcriptomic studies from the accumulation of data to their analyses and interpretation. The main problem in analyzing transcriptomics data is that t he number of independent samples is typically much lower (14,000). To address this, it would be desirable to reduce the gathered data ’s dimensionality without losing information. Clustering genes into discrete modules is one of the most commonly used tools ...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Jason Bennett Source Type: research

Comprehensive analysis of lectin-glycan interactions reveals determinants of lectin specificity
by Daniel E. Mattox, Chris Bailey-Kellogg Lectin-glycan interactions facilitate inter- and intracellular communication in many processes including protein trafficking, host-pathogen recognition, and tumorigenesis promotion. Specific recognition of glycans by lectins is also the basis for a wide range of applications in areas including gly cobiology research, cancer screening, and antiviral therapeutics. To provide a better understanding of the determinants of lectin-glycan interaction specificity and support such applications, this study comprehensively investigates specificity-conferring features of all available lectin-...
Source: PLoS Computational Biology - October 6, 2021 Category: Biology Authors: Daniel E. Mattox Source Type: research

Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites
by Bikash K. Bhandari, Chun Shen Lim, Daniela M. Remus, Augustine Chen, Craig van Dolleweerd, Paul P. Gardner Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann’s ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which ut...
Source: PLoS Computational Biology - October 5, 2021 Category: Biology Authors: Bikash K. Bhandari Source Type: research

DeepCellState: An autoencoder-based framework for predicting cell type specific transcriptional states induced by drug treatment
by Ramzan Umarov, Yu Li, Erik Arner Drug treatment induces cell type specific transcriptional programs, and as the number of combinations of drugs and cell types grows, the cost for exhaustive screens measuring the transcriptional drug response becomes intractable. We developed DeepCellState, a deep learning autoencoder-based framew ork, for predicting the induced transcriptional state in a cell type after drug treatment, based on the drug response in another cell type. Training the method on a large collection of transcriptional drug perturbation profiles, prediction accuracy improves significantly over baseline and alte...
Source: PLoS Computational Biology - October 5, 2021 Category: Biology Authors: Ramzan Umarov Source Type: research

Regulation of transcription reactivation dynamics exiting mitosis
by Sergio Sarnataro, Andrea Riba, Nacho Molina Proliferating cells experience a global reduction of transcription during mitosis, yet their cell identity is maintained and regulatory information is propagated from mother to daughter cells. Mitotic bookmarking by transcription factors has been proposed as a potential mechanism to ensure the rea ctivation of transcription at the proper set of genes exiting mitosis. Recently, mitotic transcription and waves of transcription reactivation have been observed in synchronized populations of human hepatoma cells. However, the study did not consider that mitotic-arrested cell popul...
Source: PLoS Computational Biology - October 4, 2021 Category: Biology Authors: Sergio Sarnataro Source Type: research

Choice history effects in mice and humans improve reward harvesting efficiency
by Samuel L ópez-Yépez Junior, Juliane Martin, Oliver Hulme, Duda Kvitsiani Choice history effects describe how future choices depend on the history of past choices. In experimental tasks this is typically framed as a bias because it often diminishes the experienced reward rates. However, in natural habitats, choices made in the past constrain choices that can be made in the future. For foraging animals, the probability of earning a reward in a given patch depends on the degree to which the animals have exploited the patch in the past. One problem with many experimental tasks that show choice history effects...
Source: PLoS Computational Biology - October 4, 2021 Category: Biology Authors: Samuel L ópez-Yépez Junior Source Type: research

The importance of urgency in decision making based on dynamic information
by Lorenzo Ferrucci, Aldo Genovesio, Encarni Marcos A standard view in the literature is that decisions are the result of a process that accumulates evidence in favor of each alternative until such accumulation reaches a threshold and a decision is made. However, this view has been recently questioned by an alternative proposal that suggests that, instead of accumulated, evidence is combined with an urgency signal. Both theories have been mathematically formalized and supported by a variety of decision-making tasks with constant information. However, recently, tasks with changing information have shown to be more effectiv...
Source: PLoS Computational Biology - October 4, 2021 Category: Biology Authors: Lorenzo Ferrucci Source Type: research

Action planning and control under uncertainty emerge through a desirability-driven competition between parallel encoding motor plans
by Vince Enachescu, Paul Schrater, Stefan Schaal, Vassilios Christopoulos Living in an uncertain world, nearly all of our decisions are made with some degree of uncertainty about the consequences of actions selected. Although a significant progress has been made in understanding how the sensorimotor system incorporates uncertainty into the decision-making process, the p reponderance of studies focus on tasks in which selection and action are two separate processes. First people select among alternative options and then initiate an action to implement the choice. However, we often make decisions during ongoing actions in w...
Source: PLoS Computational Biology - October 1, 2021 Category: Biology Authors: Vince Enachescu Source Type: research

Memory shapes microbial populations
We describe the population-wide consequences of phenot ypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individua l cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, ...
Source: PLoS Computational Biology - October 1, 2021 Category: Biology Authors: Chaitanya S. Gokhale Source Type: research

Separable actions of acetylcholine and noradrenaline on neuronal ensemble formation in hippocampal CA3 circuits
by Luke Y. Prince, Travis Bacon, Rachel Humphries, Krasimira Tsaneva-Atanasova, Claudia Clopath, Jack R. Mellor In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. The neuromodulators acetylcholine and noradrenaline are separately proposed a s saliency signals that dictate memory encoding but it is not known if they represent distinct signals with separate mechanisms. Here, we show experimentally that acetylcholine, and to a lesser extent noradrenaline, su...
Source: PLoS Computational Biology - October 1, 2021 Category: Biology Authors: Luke Y. Prince Source Type: research

Ten simple rules for choosing a PhD supervisor
by Loay Jabre, Catherine Bannon, J. Scott P. McCain, Yana Eglit (Source: PLoS Computational Biology)
Source: PLoS Computational Biology - September 30, 2021 Category: Biology Authors: Loay Jabre Source Type: research

The critical balance between dopamine D2 receptor and RGS for the sensitive detection of a transient decay in dopamine signal
by Hidetoshi Urakubo, Sho Yagishita, Haruo Kasai, Yoshiyuki Kubota, Shin Ishii In behavioral learning, reward-related events are encoded into phasic dopamine (DA) signals in the brain. In particular, unexpected reward omission leads to a phasic decrease in DA (DA dip) in the striatum, which triggers long-term potentiation (LTP) in DA D2 receptor (D2R)-expressing spiny-projec tion neurons (D2 SPNs). While this LTP is required for reward discrimination, it is unclear how such a short DA-dip signal (0.5–2 s) is transferred through intracellular signaling to the coincidence detector, adenylate cyclase (AC). In the prese...
Source: PLoS Computational Biology - September 30, 2021 Category: Biology Authors: Hidetoshi Urakubo Source Type: research

Ten simple rules for being a faculty advocate of first-year graduate students
by Kevin A. Janes (Source: PLoS Computational Biology)
Source: PLoS Computational Biology - September 30, 2021 Category: Biology Authors: Kevin A. Janes Source Type: research

Heterodimer-heterotetramer formation mediates enhanced sensor activity in a biophysical model for BMP signaling
by M. Shahriar Karim, Aasakiran Madamanchi, James A. Dutko, Mary C. Mullins, David M. Umulis Numerous stages of organismal development rely on the cellular interpretation of gradients of secreted morphogens including members of the Bone Morphogenetic Protein (BMP) family through transmembrane receptors. Early gradients of BMPs drive dorsal/ventral patterning throughout the animal kingdom in both vertebrates and invertebrates. Growing evidence in Drosophila, zebrafish, murine and other systems suggests that BMP ligand heterodimers are the primary BMP signaling ligand, even in systems in which mixtures of BMP homodimers and...
Source: PLoS Computational Biology - September 30, 2021 Category: Biology Authors: M. Shahriar Karim Source Type: research

High-integrity human intervention in ecosystems: Tracking self-organization modes
by Yuval R. Zelnik, Yair Mau, Moshe Shachak, Ehud Meron Humans play major roles in shaping and transforming the ecology of Earth. Unlike natural drivers of ecosystem change, which are erratic and unpredictable, human intervention in ecosystems generally involves planning and management, but often results in detrimental outcomes. Using model studies and aerial-image analysis, we argue that the design of a successful human intervention form calls for the identification of the self-organization modes that drive ecosystem change, and for studying their dynamics. We demonstrate this approach with two examples: grazing manageme...
Source: PLoS Computational Biology - September 29, 2021 Category: Biology Authors: Yuval R. Zelnik Source Type: research

Computational analysis of GAL pathway pinpoints mechanisms underlying natural variation
by Jiayin Hong, Julius Palme, Bo Hua, Michael Springer Quantitative traits are measurable phenotypes that show continuous variation over a wide phenotypic range. Enormous effort has recently been put into determining the genetic influences on a variety of quantitative traits with mixed success. We identified a quantitative trait in a tractable model s ystem, the GAL pathway in yeast, which controls the uptake and metabolism of the sugar galactose. GAL pathway activation depends both on galactose concentration and on the concentrations of competing, preferred sugars such as glucose. Natural yeast isolates show substantial ...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Jiayin Hong Source Type: research

Memes: A motif analysis environment in R using tools from the MEME Suite
by Spencer L. Nystrom, Daniel J. McKay Identification of biopolymer motifs represents a key step in the analysis of biological sequences. The MEME Suite is a widely used toolkit for comprehensive analysis of biopolymer motifs; however, these tools are poorly integrated within popular analysis frameworks like the R/Bioconductor project, creating barriers to their use. Here we present memes, an R package that provides a seamless R interface to a selection of popular MEME Suite tools. memes provides a novel “data aware” interface to these tools, enabling rapid and complex discriminative motif analysis workflows. ...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Spencer L. Nystrom Source Type: research

XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers
by Jack B. Maguire, Daniele Grattarola, Vikram Khipple Mulligan, Eugene Klyshko, Hans Melo Graph representations are traditionally used to represent protein structures in sequence design protocols in which the protein backbone conformation is known. This infrequently extends to machine learning projects: existing graph convolution algorithms have shortcomings when representing protein e nvironments. One reason for this is the lack of emphasis on edge attributes during massage-passing operations. Another reason is the traditionally shallow nature of graph neural network architectures. Here we introduce an improved message-...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Jack B. Maguire Source Type: research

Optima TB: A tool to help optimally allocate tuberculosis spending
by Lara Gosc é, Gerard J. Abou Jaoude, David J. Kedziora, Clemens Benedikt, Azfar Hussain, Sarah Jarvis, Alena Skrahina, Dzmitry Klimuk, Henadz Hurevich, Feng Zhao, Nicole Fraser-Hurt, Nejma Cheikh, Marelize Gorgens, David J. Wilson, Romesh Abeysuriya, Rowan Martin-Hughes, Sherrie L. Kelly, Anna Roberts, Robyn M. Stuart, Tom Palmer, Jasmina Panovska-Griffiths, Cliff C. Kerr, David P. Wilson, Hassan Haghparast-Bidgoli, Jolene Skordis, Ibrahim Abubakar Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is requir...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Lara Gosc é Source Type: research

Meta-analysis of transcriptomic data reveals clusters of consistently deregulated gene and disease ontologies in Down syndrome
by Ilario De Toma, Cesar Sierra, Mara Dierssen Trisomy of human chromosome 21 (HSA21) causes Down syndrome (DS). The trisomy does not simply result in the upregulation of HSA21--encoded genes but also leads to a genome-wide transcriptomic deregulation, which may differently affect each tissue and cell type as results of epigenetic mechanisms a nd protein-protein interactions. We performed a meta-analysis integrating the differential expression (DE) analyses of all publicly available transcriptomic datasets, both in human and mouse, comparing trisomic and euploid transcriptomes from different sources. We integrated all the...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Ilario De Toma Source Type: research

FunOrder: A robust and semi-automated method for the identification of essential biosynthetic genes through computational molecular co-evolution
In this study, we developed a method that allows semi-automated identification of essential genes in a BGC based on co-evolution analysis. To this end, the protein sequences of a BGC are blasted agai nst a suitable proteome database. For each protein, a phylogenetic tree is created. The trees are compared by treeKO to detect co-evolution. The results of this comparison are visualized in different output formats, which are compared visually. Our results suggest that co-evolution is commonly occur ring within BGCs, albeit not all, and that especially those genes that encode for enzymes of the biosynthetic pathway are co-evol...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Gabriel A. Vignolle Source Type: research

Hybrid computational modeling demonstrates the utility of simulating complex cellular networks in type 1 diabetes
by Zhenzhen Shi, Yang Li, Majid Jaberi-Douraki Persistent destruction of pancreatic β-cells in type 1 diabetes (T1D) results from multifaceted pancreatic cellular interactions in various phase progressions. Owing to the inherent heterogeneity of coupled nonlinear systems, computational modeling based on T1D etiology help achieve a systematic understanding of biological processes and T1D health outcomes. The main challenge is to design such a reliable framework to analyze the highly orchestrated biology of T1D based on the knowledge of cellular networks and biological parameters. We constructed a novel hybrid in-silic...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Zhenzhen Shi Source Type: research

A model of head direction and landmark coding in complex environments
We present a computational model of how visual feedback can stabilize HD information in envi ronments that contain multiple cues of varying stability and directional specificity. We show how combinations of feature-specific visual inputs can generate a stable unimodal landmark bearing signal, even in the presence of multiple cues and ambiguous directional specificity. This signal is associa ted with the retrosplenial HD signal (inherited from thalamic HD cells) and conveys feedback to the subcortical HD circuitry. The model predicts neurons with a unimodal encoding of the egocentric orientation of the array of landmarks, r...
Source: PLoS Computational Biology - September 27, 2021 Category: Biology Authors: Yijia Yan Source Type: research