| 1. |
- A, Teschendorff, et al.
(författare)
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The dynamics of DNA methylation covariation patterns in carcinogenesis
- 2014
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Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 10:7
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Tidskriftsartikel (refereegranskat)abstract
- Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified.
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| 2. |
- Albantakis, L., et al.
(författare)
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Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity
- 2014
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Ingår i: PloS Computational Biology. - : Public Library of Science. - 1553-734X .- 1553-7358. ; 10:12
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Tidskriftsartikel (refereegranskat)abstract
- Natural selection favors the evolution of brains that can capture fitness-relevant features of the environment's causal structure. We investigated the evolution of small, adaptive logic-gate networks (“animats”) in task environments where falling blocks of different sizes have to be caught or avoided in a ‘Tetris-like’ game. Solving these tasks requires the integration of sensor inputs and memory. Evolved networks were evaluated using measures of information integration, including the number of evolved concepts and the total amount of integrated conceptual information. The results show that, over the course of the animats' adaptation, i) the number of concepts grows; ii) integrated conceptual information increases; iii) this increase depends on the complexity of the environment, especially on the requirement for sequential memory. These results suggest that the need to capture the causal structure of a rich environment, given limited sensors and internal mechanisms, is an important driving force for organisms to develop highly integrated networks (“brains”) with many concepts, leading to an increase in their internal complexity. © 2014 Albantakis et al.
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| 3. |
- Altafini, Claudio, et al.
(författare)
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Metabolic Adaptation Processes That Converge to Optimal Biomass Flux Distributions
- 2015
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Ingår i: PloS Computational Biology. - : PUBLIC LIBRARY SCIENCE. - 1553-734X .- 1553-7358. ; 11:9
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Tidskriftsartikel (refereegranskat)abstract
- In simple organisms like E. coli, the metabolic response to an external perturbation passes through a transient phase in which the activation of a number of latent pathways can guarantee survival at the expenses of growth. Growth is gradually recovered as the organism adapts to the new condition. This adaptation can be modeled as a process of repeated metabolic adjustments obtained through the resilencings of the non-essential metabolic reactions, using growth rate as selection probability for the phenotypes obtained. The resulting metabolic adaptation process tends naturally to steer the metabolic fluxes towards high growth phenotypes. Quite remarkably, when applied to the central carbon metabolism of E. coli, it follows that nearly all flux distributions converge to the flux vector representing optimal growth, i.e., the solution of the biomass optimization problem turns out to be the dominant attractor of the metabolic adaptation process.
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| 4. |
- Andersen, Malin, 1977-, et al.
(författare)
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In silico detection of sequence variations modifying transcriptional regulation
- 2008
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 4:1, s. e5-
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Tidskriftsartikel (refereegranskat)abstract
- Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN ( regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.
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| 5. |
- Ardell, David H, et al.
(författare)
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The genomic pattern of tDNA operon expression in E. coli
- 2005
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 1:1, s. e12-
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Tidskriftsartikel (refereegranskat)abstract
- In fast-growing microorganisms, a tRNA concentration profile enriched in major isoacceptors selects for the biased usage of cognate codons. This optimizes translational rate for the least mass invested in the translational apparatus. Such translational streamlining is thought to be growth-regulated, but its genetic basis is poorly understood. First, we found in reanalysis of the E. coli tRNA profile that the degree to which it is translationally streamlined is nearly invariant with growth rate. Then, using least squares multiple regression, we partitioned tRNA isoacceptor pools to predicted tDNA operons from the E. coli K12 genome. Co-expression of tDNAs in operons explains the tRNA profile significantly better than tDNA gene dosage alone. Also, operon expression increases significantly with proximity to the origin of replication, oriC, at all growth rates. Genome location explains about 15% of expression variation in a form, at a given growth rate, that is consistent with replication-dependent gene concentration effects. Yet the change in the tRNA profile with growth rate is less than would be expected from such effects. We estimated per-copy expression rates for all tDNA operons that were consistent with independent estimates for rDNA operons. We also found that tDNA operon location, and the location dependence of expression, were significantly different in the leading and lagging strands. The operonic organization and genomic location of tDNA operons are significant factors influencing their expression. Nonrandom patterns of location and strandedness shown by tDNA operons in E. coli suggest that their genomic architecture may be under selection to satisfy physiological demand for tRNA expression at high growth rates.
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| 6. |
- Asplund-Samuelsson, Johannes, et al.
(författare)
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Wide range of metabolic adaptations to the acquisition of the Calvin cycle revealed by comparison of microbial genomes
- 2021
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 17:2
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of the genetic basis for autotrophic metabolism is valuable since it relates to both the emergence of life and to the metabolic engineering challenge of incorporating CO2 as a potential substrate for biorefining. The most common CO2 fixation pathway is the Calvin cycle, which utilizes Rubisco and phosphoribulokinase enzymes. We searched thousands of microbial genomes and found that 6.0% contained the Calvin cycle. We then contrasted the genomes of Calvin cycle-positive, non-cyanobacterial microbes and their closest relatives by enrichment analysis, ancestral character estimation, and random forest machine learning, to explore genetic adaptations associated with acquisition of the Calvin cycle. The Calvin cycle overlaps with the pentose phosphate pathway and glycolysis, and we could confirm positive associations with fructose-1,6-bisphosphatase, aldolase, and transketolase, constituting a conserved operon, as well as ribulose-phosphate 3-epimerase, ribose-5-phosphate isomerase, and phosphoglycerate kinase. Additionally, carbohydrate storage enzymes, carboxysome proteins (that raise CO2 concentration around Rubisco), and Rubisco activases CbbQ and CbbX accompanied the Calvin cycle. Photorespiration did not appear to be adapted specifically for the Calvin cycle in the non-cyanobacterial microbes under study. Our results suggest that chemoautotrophy in Calvin cycle-positive organisms was commonly enabled by hydrogenase, and less commonly ammonia monooxygenase (nitrification). The enrichment of specific DNA-binding domains indicated Calvin-cycle associated genetic regulation. Metabolic regulatory adaptations were illustrated by negative correlation to AraC and the enzyme arabinose-5-phosphate isomerase, which suggests a downregulation of the metabolite arabinose-5-phosphate, which may interfere with the Calvin cycle through enzyme inhibition and substrate competition. Certain domains of unknown function that were found to be important in the analysis may indicate yet unknown regulatory mechanisms in Calvin cycle-utilizing microbes. Our gene ranking provides targets for experiments seeking to improve CO2 fixation, or engineer novel CO2-fixing organisms.
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| 7. |
- Aurell, Erik
(författare)
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The Maximum Entropy Fallacy Redux?
- 2016
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Ingår i: PloS Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 12:5
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Tidskriftsartikel (refereegranskat)
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| 8. |
- Bahuguna, Jyotika, et al.
(författare)
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Existence and control of Go/No-Go decision transition threshold in the striatum
- 2015
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Ingår i: PloS Computational Biology. - : PLOS. - 1553-734X .- 1553-7358. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- A typical Go/No-Go decision is suggested to be implemented in the brain via the activation of the direct or indirect pathway in the basal ganglia. Medium spiny neurons (MSNs) in the striatum, receiving input from cortex and projecting to the direct and indirect pathways express D1 and D2 type dopamine receptors, respectively. Recently, it has become clear that the two types of MSNs markedly differ in their mutual and recurrent connectivities as well as feedforward inhibition from FSIs. Therefore, to understand striatal function in action selection, it is of key importance to identify the role of the distinct connectivities within and between the two types of MSNs on the balance of their activity. Here, we used both a reduced firing rate model and numerical simulations of a spiking network model of the striatum to analyze the dynamic balance of spiking activities in D1 and D2 MSNs. We show that the asymmetric connectivity of the two types of MSNs renders the striatum into a threshold device, indicating the state of cortical input rates and correlations by the relative activity rates of D1 and D2 MSNs. Next, we describe how this striatal threshold can be effectively modulated by the activity of fast spiking interneurons, by the dopamine level, and by the activity of the GPe via pallidostriatal backprojections. We show that multiple mechanisms exist in the basal ganglia for biasing striatal output in favour of either the `Go' or the `No-Go' pathway. This new understanding of striatal network dynamics provides novel insights into the putative role of the striatum in various behavioral deficits in patients with Parkinson's disease, including increased reaction times, L-Dopa-induced dyskinesia, and deep brain stimulation-induced impulsivity.
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| 9. |
- Bahuguna, Jyotika, et al.
(författare)
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Uncoupling the roles of firing rates and spike bursts in shaping the STN-GPe beta band oscillations
- 2020
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Ingår i: PloS Computational Biology. - : Public Library of Science. - 1553-734X .- 1553-7358. ; 16:3
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Tidskriftsartikel (refereegranskat)abstract
- The excess of 15-30 Hz (beta-band) oscillations in the basal ganglia is one of the key signatures of Parkinson's disease (PD). The STN-GPe network is integral to generation and modulation of beta band oscillations in basal ganglia. However, the role of changes in the firing rates and spike bursting of STN and GPe neurons in shaping these oscillations has remained unclear. In order to uncouple their effects, we studied the dynamics of STN-GPe network using numerical simulations. In particular, we used a neuron model, in which firing rates and spike bursting can be independently controlled. Using this model, we found that while STN firing rate is predictive of oscillations but GPe firing rate is not. The effect of spike bursting in STN and GPe neurons was state-dependent. That is, only when the network was operating in a state close to the border of oscillatory and non-oscillatory regimes, spike bursting had a qualitative effect on the beta band oscillations. In these network states, an increase in GPe bursting enhanced the oscillations whereas an equivalent proportion of spike bursting in STN suppressed the oscillations. These results provide new insights into the mechanisms underlying the transient beta bursts and how duration and power of beta band oscillations may be controlled by an interplay of GPe and STN firing rates and spike bursts. Author summary The STN-GPe network undergoes a change in firing rates as well as increased bursting during excessive beta band oscillations during Parkinson's disease. In this work we uncouple their effects by using a novel neuron model and show that presence of oscillations is contingent on the increase in STN firing rates, however the effect of spike bursting on oscillations depends on the network state. In a network state on the border of oscillatory and non-oscillatory regime, GPe spike bursting strengthens oscillations. The effect of spike bursting in the STN depends on the proportion of GPe neurons bursting. These results suggest a mechanism underlying a transient beta band oscillation bursts often seen in experimental data.
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| 10. |
- Balbi, P., et al.
(författare)
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A single Markov-type kinetic model accounting for the macroscopic currents of all human voltage-gated sodium channel isoforms
- 2017
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Ingår i: PloS Computational Biology. - : Public Library of Science. - 1553-734X .- 1553-7358. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Modelling ionic channels represents a fundamental step towards developing biologically detailed neuron models. Until recently, the voltage-gated ion channels have been mainly modelled according to the formalism introduced by the seminal works of Hodgkin and Huxley (HH). However, following the continuing achievements in the biophysical and molecular comprehension of these pore-forming transmembrane proteins, the HH formalism turned out to carry limitations and inconsistencies in reproducing the ion-channels electrophysiological behaviour. At the same time, Markov-type kinetic models have been increasingly proven to successfully replicate both the electrophysiological and biophysical features of different ion channels. However, in order to model even the finest non-conducting molecular conformational change, they are often equipped with a considerable number of states and related transitions, which make them computationally heavy and less suitable for implementation in conductance-based neurons and large networks of those. In this purely modelling study we develop a Markov-type kinetic model for all human voltage-gated sodium channels (VGSCs). The model framework is detailed, unifying (i.e., it accounts for all ion-channel isoforms) and computationally efficient (i.e. with a minimal set of states and transitions). The electrophysiological data to be modelled are gathered from previously published studies on whole-cell patch-clamp experiments in mammalian cell lines heterologously expressing the human VGSC subtypes (from NaV1.1 to NaV1.9). By adopting a minimum sequence of states, and using the same state diagram for all the distinct isoforms, the model ensures the lightest computational load when used in neuron models and neural networks of increasing complexity. The transitions between the states are described by original ordinary differential equations, which represent the rate of the state transitions as a function of voltage (i.e., membrane potential). The kinetic model, developed in the NEURON simulation environment, appears to be the simplest and most parsimonious way for a detailed phenomenological description of the human VGSCs electrophysiological behaviour.
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