scholarly journals Systems protobiology: origin of life in lipid catalytic networks

2018 ◽  
Vol 15 (144) ◽  
pp. 20180159 ◽  
Author(s):  
Doron Lancet ◽  
Raphael Zidovetzki ◽  
Omer Markovitch
Keyword(s):  
Fitness Landscape ◽  
Entropy Change ◽  
Dissipative Systems ◽  
Sequence Information ◽  
Environmental Chemical ◽  
Self Organized ◽  
Replication Domain ◽  
Catalytic Network ◽  
Bona Fide ◽  
Covalent Modifications

Life is that which replicates and evolves, but there is no consensus on how life emerged. We advocate a systems protobiology view, whereby the first replicators were assemblies of spontaneously accreting, heterogeneous and mostly non-canonical amphiphiles. This view is substantiated by rigorous chemical kinetics simulations of the graded autocatalysis replication domain (GARD) model, based on the notion that the replication or reproduction of compositional information predated that of sequence information. GARD reveals the emergence of privileged non-equilibrium assemblies (composomes), which portray catalysis-based homeostatic (concentration-preserving) growth. Such a process, along with occasional assembly fission, embodies cell-like reproduction. GARD pre-RNA evolution is evidenced in the selection of different composomes within a sparse fitness landscape, in response to environmental chemical changes. These observations refute claims that GARD assemblies (or other mutually catalytic networks in the metabolism first scenario) cannot evolve. Composomes represent both a genotype and a selectable phenotype, anteceding present-day biology in which the two are mostly separated. Detailed GARD analyses show attractor-like transitions from random assemblies to self-organized composomes, with negative entropy change, thus establishing composomes as dissipative systems—hallmarks of life. We show a preliminary new version of our model, metabolic GARD (M-GARD), in which lipid covalent modifications are orchestrated by non-enzymatic lipid catalysts, themselves compositionally reproduced. M-GARD fills the gap of the lack of true metabolism in basic GARD, and is rewardingly supported by a published experimental instance of a lipid-based mutually catalytic network. Anticipating near-future far-reaching progress of molecular dynamics, M-GARD is slated to quantitatively depict elaborate protocells, with orchestrated reproduction of both lipid bilayer and lumenal content. Finally, a GARD analysis in a whole-planet context offers the potential for estimating the probability of life's emergence. The invigorated GARD scrutiny presented in this review enhances the validity of autocatalytic sets as a bona fide early evolution scenario and provides essential infrastructure for a paradigm shift towards a systems protobiology view of life's origin.

scholarly journals The (love & hate) role of entropy in process metallurgy

2019 ◽  
Vol 107 (5) ◽  
pp. 506 ◽  
Author(s):  
Halvard Tveit ◽  
Leiv Kolbeinsen
Keyword(s):  
Open Systems ◽  
Entropy Change ◽  
Dissipative Systems ◽  
Self Organized ◽  
Process Metallurgy ◽  
Almost Everywhere ◽  
Dynamical Regimes ◽  
Low Entropy ◽  
Metallurgical Processes

Process metallurgy is the basis for the production, refining and recycling of metals and is based on knowledge of transport phenomena, thermodynamics and reaction kinetics, and of their interaction in high-temperature, heterogeneous metallurgical processes. The entropy concept is crucial in describing such systems, but, because entropy is not directly observable, some effort is required to grasp the role of entropy in process metallurgy. In this paper, we will give some examples of how entropy has a positive effect on efforts to reach the process objectives in some cases, while in other cases, entropy acts in contradiction to the desired results. In order to do this, it is necessary to have a closer look at both the entropy concept itself as well as at other functions like free energy and exergy since they encompass entropy. The chosen case is the production of silicon. It is the huge entropy change in the process that is utilized. The case is not chosen arbitrary. Indeed, it is the authors’ strong belief that silicon will be one of the foundations for the environmental and energy future planned for in the “Paris-agreement”. We will also explore relatively recent research in physics and thermodynamics that led to the description of the concepts like “dissipative systems and structures”. Dissipative systems are thermodynamically open systems, operating out of, and often far from thermodynamic equilibrium and exhibit dynamical regimes that are in some sense in a reproducible self-organized steady state. Such structures can arise almost everywhere provided this structure, feeding on low entropy resources, dissipates entropy generated in the form of heat and waste material in parallel with the wanted products/results. Examples range from metallurgical processes to the emergence of industrial symbiosis.

scholarly journals Chromatin Enrichment for Proteomics in Plants (ChEP-P) Implicates the Histone Reader ALFIN-LIKE 6 in Jasmonate Signalling

2021 ◽  
Author(s):  
Isabel Cristina Vélez-Bermúdez ◽  
Wolfgang Schmidt
Keyword(s):  
Histone Variants ◽  
Homeodomain Protein ◽  
Chromatin Dynamics ◽  
Histone 3 ◽  
Plant Homeodomain ◽  
Associated Proteins ◽  
Bona Fide ◽  
Covalent Modifications ◽  
And Function

Abstract BackgroundCovalent modifications of core histonesgoverndownstream DNA-templated processes such as transcription by altering chromatin structure and function. Previously, we reported that the plant homeodomain protein ALFIN-LIKE6 (AL6), a bona fide histone reader that preferentially binds trimethylated lysin 4 on histone 3 (H3K4me3), is critical for recalibration of cellular phosphate (Pi) homeostasis and root hair elongation under Pi-deficient conditions. ResultsHere, we demonstrate that AL6 is also involved in the response of Arabidopsis seedlings to jasmonic acid (JA) during skotomorphogenesis, possibly by modulating chromatin dynamics that affect the transcriptional regulation of JA-responsivegenes. Dark-grown al6 seedlings showed a compromised reduction in hypocotyl elongation upon exogenously supplied JA, a response that was calibrated by the availability of Pi in the growth medium. A comparison of protein profiles between wild-type and al6 mutant seedlings using a quantitative Chromatin Enrichment for Proteomics (ChEP) approach,that we modified for plant tissue and designated ChEP-P (ChEP in Plants), yielded a comprehensive suite of chromatin-associated proteins and candidates that may be causative for the mutant phenotype. ConclusionsAltered abundance of proteins involved in chromatin organization in al6 seedlings suggests a role of AL6 in coordinating the deposition of histone variants upon perception of internal or environmental stimuli. Our study shows that ChEP-P is well suited to gain holistic insights into chromatin-related processes in plants. Data are available via ProteomeXchange with identifier PXD026541.

scholarly journals MiPepid: MicroPeptide identification tool using machine learning

2019 ◽  
Author(s):  
Mengmeng Zhu ◽  
Michael Gribskov
Keyword(s):  
Machine Learning ◽  
Dna Sequences ◽  
Biological Activities ◽  
Prediction Methods ◽  
Sequence Information ◽  
Blind Test ◽  
Small Proteins ◽  
Bona Fide ◽  
Genome Scale ◽  
Coding Potential

Abstract Background Micropeptides are small proteins with a length <= 100 amino acids. They were traditionally ignored as few were discovered due to technical difficulties. In the past decade, a growing number of micropeptides have been shown to play significant roles in vital biological activities. Despite the increased amount of data, we still lack bioinformatics tools specifically for identifying micropeptides from DNA sequences. Indeed, most existing tools for classifying coding and noncoding ORFs were built on datasets in which “normal-sized” proteins are considered to be positives and short ORFs are generally considered to be noncoding. Since the functional and biophysical constraints on small peptides are likely to be different from those on “normal” proteins, methods for predicting short translated ORFs must be trained independently from those for longer proteins. Results In this study, we developed MiPepid, a machine-learning tool specifically for the identification of micropeptides. We trained MiPepid using carefully cleaned data from existing databases and logistic regression with 4-mer features. With only the sequence information of an ORF, MiPepid is able to predict whether it encodes a micropeptide with 96% accuracy on a blind dataset of high-confidence micropeptides, and to correctly classify newly discovered micropeptides not included in either the training or the blind test data. Compared with state-of-the-art coding potential prediction methods, MiPepid performs exceptionally well, as other methods incorrectly classify most bona fide micropeptides as noncoding. MiPepid is alignment-free and runs sufficiently fast for genome-scale analyses. It is easy to use and is available at https://github.com/MindAI/MiPepid. Conclusion MiPepid was developed to specifically predict micropeptides, a category of proteins with increasing significance, from DNA sequences. It shows evident advantages over existing coding potential prediction methods on micropeptide identification. It is ready to use and runs fast.

scholarly journals Evolution in the weak-mutation limit: Stasis periods punctuated by fast transitions between saddle points on the fitness landscape

2021 ◽  
Vol 118 (4) ◽  
pp. e2015665118
Author(s):  
Yuri Bakhtin ◽  
Mikhail I. Katsnelson ◽  
Yuri I. Wolf ◽  
Eugene V. Koonin
Keyword(s):  
Fitness Landscape ◽  
Large Population ◽  
Saddle Points ◽  
Selection Coefficient ◽  
Beneficial Mutation ◽  
Effective Population ◽  
Phenotypic Changes ◽  
Self Organized ◽  
Evolving System ◽  
Self Organized Criticality

A mathematical analysis of the evolution of a large population under the weak-mutation limit shows that such a population would spend most of the time in stasis in the vicinity of saddle points on the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe/s time (Ne, effective population size; s, selection coefficient of a mutation), when a new beneficial mutation is fixed in the evolving population, which accordingly moves to a different saddle, or on much rarer occasions from a saddle to a local peak. Phenomenologically, this mode of evolution of a large population resembles punctuated equilibrium (PE) whereby phenotypic changes occur in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but the phenotype does not change substantially. Theoretically, PE has been linked to self-organized criticality (SOC), a model in which the size of “avalanches” in an evolving system is power-law-distributed, resulting in increasing rarity of major events. Here we show, however, that a PE-like evolutionary regime is the default for a very simple model of an evolving population that does not rely on SOC or any other special conditions.

Self-Organized Critical Models

2003 ◽  
Author(s):  
M. E. J. Newman ◽  
R. G. Palmer
Keyword(s):  
Computer Simulations ◽  
Power Law ◽  
Large Scale ◽  
Fitness Landscape ◽  
Fitness Landscapes ◽  
Power Law Distribution ◽  
Edge Of Chaos ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Phenotype Space

The models discussed in the last chapter are intriguing, but present a number of problems. In particular, most of the results about them come from computer simulations, and little is known analytically about their properties. Results such as the power-law distribution of extinction sizes and the system's evolution to the "edge of chaos" are only as accurate as the simulations in which they are observed. Moreover, it is not even clear what the mechanisms responsible for these results are, beyond the rather general arguments that we have already given. In order to address these shortcomings, Bak and Sneppen (1993; Sneppen et al. 1995; Sneppen 1995; Bak 1996) have taken Kauffman's ideas, with some modification, and used them to create a considerably simpler model of large-scale coevolution which also shows a power-law distribution of avalanche sizes and which is simple enough that its properties can, to some extent, be understood analytically. Although the model does not directly address the question of extinction, a number of authors have interpreted it, using arguments similar to those of section 1.2.2.5, as a possible model for extinction by biotic causes. The Bak-Sneppen model is one of a class of models that show "self-organized criticality," which means that regardless of the state in which they start, they always tune themselves to a critical point of the type discussed in section 2.4, where power-law behavior is seen. We describe self-organized criticality in more detail in section 3.2. First, however, we describe the Bak-Sneppen model itself. In the model of Bak and Sneppen there are no explicit fitness landscapes, as there are in NK models. Instead the model attempts to mimic the effects of landscapes in terms of "fitness barriers." Consider figure 3.1, which is a toy representation of a fitness landscape in which there is only one dimension in the genotype (or phenotype) space. If the mutation rate is low compared with the time scale on which selection takes place (as Kauffman assumed), then a population will spend most of its time localized around a peak in the landscape (labeled P in the figure).

scholarly journals Spiral structure in galaxies: large-scale stochastic self-organization of interstellar matter and young stars

1985 ◽  
Vol 106 ◽  
pp. 559-560
Author(s):  
J. V. Feitzinger
Keyword(s):  
Star Formation ◽  
Large Scale ◽  
Spiral Structure ◽  
Reaction Diffusion ◽  
Young Stars ◽  
Reaction Diffusion Equations ◽  
Dissipative Systems ◽  
Interstellar Matter ◽  
Self Organized ◽  
Analytical Work

Galaxies are dissipative systems, and the spatial and time structure of the interstellar medium and young stars is governed by reaction-diffusion equations. The coherent galactic oscillations of star formation self-organized in spiral waves, previously detected by numerical simulations (Seiden, Schulman, Feitzinger, 1982) can be analytically described by the concept of a limit cycle. Analytical work on self-propagating stochastic star formation is also done by Kaufman (1979), Shore (1981, 1982) and Cowie and Rybicki (1982).

scholarly journals A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity

2016 ◽  
Author(s):  
Fumitaka Inoue ◽  
Martin Kircher ◽  
Beth Martin ◽  
Gregory M. Cooper ◽  
Daniela M. Witten ◽  
...  
Keyword(s):  
Functional Characterization ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Sequence Information ◽  
Regulatory Sequences ◽  
Enhancer Activity ◽  
Functional Activities ◽  
Reporter Assays ◽  
Bona Fide ◽  
Massively Parallel Reporter Assay

AbstractCandidate enhancers can be identified on the basis of chromatin modifications, the binding of chromatin modifiers and transcription factors and cofactors, or chromatin accessibility. However, validating such candidates as bona fide enhancers requires functional characterization, typically achieved through reporter assays that test whether a sequence can drive expression of a transcriptional reporter via a minimal promoter. A longstanding concern is that reporter assays are mainly implemented on episomes, which are thought to lack physiological chromatin. However, the magnitude and determinants of differences incis-regulation for regulatory sequences residing in episomes versus chromosomes remain almost completely unknown. To address this question in a systematic manner, we developed and applied a novel lentivirus-based massively parallel reporter assay (lentiMPRA) to directly compare the functional activities of 2,236 candidate liver enhancers in an episomal versus a chromosomally integrated context. We find that the activities of chromosomally integrated sequences are substantially different from the activities of the identical sequences assayed on episomes, and furthermore are correlated with different subsets of ENCODE annotations. The results of chromosomally-based reporter assays are also more reproducible and more strongly predictable by both ENCODE annotations and sequence-based models. With a linear model that combines chromatin annotations and sequence information, we achieve a Pearson’s R2of 0.347 for predicting the results of chromosomally integrated reporter assays. This level of prediction is better than with either chromatin annotations or sequence information alone and also outperforms predictive models of episomal assays. Our results have broad implications for howcis-regulatory elements are identified, prioritized and functionally validated.

scholarly journals A two-level, dynamic fitness landscape of hepatitis C virus revealed by self-organized haplotype maps

2021 ◽  
Author(s):  
Soledad Delgado ◽  
Celia Perales ◽  
Carlos García-Crespo ◽  
María Eugenia Soria ◽  
Isabel Gallego ◽  
...  
Keyword(s):  
Cell Culture ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Deep Sequencing ◽  
Fitness Landscape ◽  
Lower Number ◽  
Fitness Landscapes ◽  
Self Organized ◽  
High Fitness ◽  
Culture Environment

ABSTRACTFitness landscapes reflect the adaptive potential of viruses. There is no information on how fitness peaks evolve when a virus replicates extensively in a controlled cell culture environment. Here we report the construction of Self-Organized Maps (SOMs), based on deep sequencing reads of three amplicons of the NS5A-NS5B-coding region of hepatitis C virus (HCV). A two-dimensional neural network was constructed and organized according to sequence relatedness. The third dimension of the fitness profile was given by the haplotype frequencies at each neuron. Fitness maps were derived for 44 HCV populations that share a common ancestor that was passaged up to 210 times in human hepatoma Huh-7.5 cells. As the virus increased its adaptation to the cells, the number of fitness peaks expanded, and their distribution shifted in sequence space. The landscape consisted of an extended basal platform, and a lower number of protruding higher fitness peaks. The function that relates fitness level and peak abundance corresponds a power law, a relationship observed with other complex natural phenomena. The dense basal platform may serve as spring-board to attain high fitness peaks. The study documents a highly dynamic, double-layer fitness landscape of HCV when evolving in a monotonous cell culture environment. This information may help interpreting HCV fitness landscapes in complex in vivo environments.IMPORTANCEThe study provides for the first time the fitness landscape of a virus in the course of its adaptation to a cell culture environment, in absence of external selective constraints. The deep sequencing-based self-organized maps document a two-layer fitness distribution with an ample basal platform, and a lower number of protruding, high fitness peaks. This landscape structure offers potential benefits for virus resilience to mutational inputs.

scholarly journals METTL6 is a tRNA m3C methyltransferase that regulates pluripotency and tumor cell growth

2020 ◽  
Vol 6 (35) ◽  
pp. eaaz4551
Author(s):  
Valentina V. Ignatova ◽  
Steffen Kaiser ◽  
Jessica Sook Yuin Ho ◽  
Xinyang Bing ◽  
Paul Stolz ◽  
...  
Keyword(s):  
Cell Growth ◽  
Tumor Cell ◽  
Translation Efficiency ◽  
Tumor Cell Growth ◽  
Rna Biology ◽  
Trna Methyltransferase ◽  
Bona Fide ◽  
Covalent Modifications

Recently, covalent modifications of RNA, such as methylation, have emerged as key regulators of all aspects of RNA biology and have been implicated in numerous diseases, for instance, cancer. Here, we undertook a combination of in vitro and in vivo screens to test 78 potential methyltransferases for their roles in hepatocellular carcinoma (HCC) cell proliferation. We identified methyltransferase-like protein 6 (METTL6) as a crucial regulator of tumor cell growth. We show that METTL6 is a bona fide transfer RNA (tRNA) methyltransferase, catalyzing the formation of 3-methylcytidine at C32 of specific serine tRNA isoacceptors. Deletion of Mettl6 in mouse stem cells results in changes in ribosome occupancy and RNA levels, as well as impaired pluripotency. In mice, Mettl6 knockout results in reduced energy expenditure. We reveal a previously unknown pathway in the maintenance of translation efficiency with a role in maintaining stem cell self-renewal, as well as impacting tumor cell growth profoundly.

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