scholarly journals Optimal density of biological cells

2020 ◽  
Author(s):  
Tin Yau Pang ◽  
Martin J. Lercher
Keyword(s):  
Reaction Kinetics ◽  
Mass Density ◽  
Reaction Rates ◽  
Cellular Growth ◽  
Metabolic Reaction ◽  
Optimal Density ◽  
E Coli ◽  
Background Density ◽  
Model Cell ◽  
Metabolic Reactions

AbstractA substantial fraction of the bacterial cytosol is occupied by catalysts and their substrates. While a higher volume density of catalysts and substrates might boost biochemical fluxes, the resulting molecular crowding can slow down diffusion, perturb the reactions’ Gibbs free energies, and reduce the catalytic efficiency of proteins. Due to these tradeoffs, dry mass density likely possesses an optimum that facilitates maximal cellular growth and that is interdependent on the cytosolic molecule size distribution. Here, we analyse the balanced growth of a model cell with metabolic and ribosomal reactions, accounting systematically for crowding effects on reaction kinetics. We find that changes in cytosolic density affect biochemical efficiency more strongly for ribosomal reactions than for metabolic reactions, which involve much smaller catalysts and reactants. Accordingly, optimal cytosolic density depends on cellular resource allocation into ribosomal vs. metabolic reactions. A shift in the relative contributions of these sectors to the cellular economy explains the 10% difference in the cytosolic density between E. coli bacteria growing in nutrient-rich and -poor environments. We conclude that cytosolic density variation in E. coli is consistent with an optimality principle of cellular efficiency.Significance statementThe cellular cytosol harbours diverse molecules, whose crowding slows down diffusion and perturbs the chemical equilibrium of biochemical reactions. Reaction rates thus depend not only on the reactants themselves, but also on the background density of other molecules; consequently, maximal cell growth requires an optimal density. Here, we simulate a model cell with crowding-adjusted metabolic reaction kinetics. Its cytosol accommodates two types of reactions: metabolic reactions involving small molecules, and protein production reactions involving much larger molecules. These two cellular subsystems have distinct optimal densities, and a shift in their relative contribution to the cellular biomass explains the 10% difference in the cytosolic density between E. coli bacteria growing in nutrient-rich and -poor environments.

Kinetic Solvent Effects in Organic Reactions

2017 ◽  
Author(s):  
Belinda Slakman ◽  
Richard West
Keyword(s):  
Solvent Effect ◽  
Reaction Kinetics ◽  
Computational Methods ◽  
High Throughput ◽  
Kinetic Modeling ◽  
Solvent Effects ◽  
Reaction Rates ◽  
Prior Work ◽  
Solvent Phase ◽  
High Throughput Manner

<div> <div> <div> <p>This article reviews prior work studying reaction kinetics in solution, with the goal of using this information to improve detailed kinetic modeling in the solvent phase. Both experimental and computational methods for calculating reaction rates in liquids are reviewed. Previous studies, which used such methods to determine solvent effects, are then analyzed based on reaction family. Many of these studies correlate kinetic solvent effect with one or more solvent parameters or properties of reacting species, but it is not always possible, and investigations are usually done on too few reactions and solvents to truly generalize. From these studies, we present suggestions on how best to use data to generalize solvent effects for many different reaction types in a high throughput manner. </p> </div> </div> </div>

scholarly journals CONSERVATION OF NUCLEIC ACIDS DURING BACTERIAL GROWTH

1954 ◽  
Vol 38 (2) ◽  
pp. 145-148 ◽  
Author(s):  
A. D. Hershey
Keyword(s):  
Characteristic Feature ◽  
Nucleic Acids ◽  
Bacterial Growth ◽  
Cellular Growth ◽  
E Coli

In experiments of 6 hours duration, no replacement of phosphorus or purine and pyrimidine carbon in DNA, nor flow of these atoms from RNA to DNA, could be detected in rapidly growing cultures of E. coli. The slow replacement that has been demonstrated for many substances in non-proliferating tissues of other organisms, though it may occur also in bacteria, is not greatly accelerated under conditions of rapid cellular growth, and therefore cannot be a characteristic feature of synthetic processes.

scholarly journals Distinguishing different modes of growth using single-cell data

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Prathitha Kar ◽  
Sriram Tiruvadi-Krishnan ◽  
Jaana Männik ◽  
Jaan Männik ◽  
Ariel Amir
Keyword(s):  
Data Analysis ◽  
Single Cell ◽  
Statistical Methods ◽  
Synthetic Data ◽  
Cellular Growth ◽  
Biological Mechanisms ◽  
E Coli ◽  
High Throughput Data ◽  
Consistent Method ◽  
Cell Data

Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.

scholarly journals Enzymes and Substrates Are Balanced at Minimal Combined Mass Concentration in vivo

2017 ◽  
Author(s):  
Hugo Dourado ◽  
Veronica G. Maurino ◽  
Martin J. Lercher
Keyword(s):  
Fundamental Problem ◽  
Geometric Mean ◽  
Physiological State ◽  
Cellular Systems ◽  
Cellular Growth ◽  
Metabolic Efficiency ◽  
E Coli ◽  
Molecular Masses ◽  
Enzyme Molecules

AbstractA fundamental problem in biology is how cells organize their resource investment. Cellular metabolism, for example, typically involves hundreds of enzymes and metabolites, but it is unclear according to which principles their concentrations are set. Reasoning that natural selection will drive cells towards achieving a given physiological state at minimal cost, we derive a general equation that predicts the concentration of a metabolite from the concentration of the most abundant and costly enzyme consuming it. Simulations of cellular growth as well as experimental data demonstrate that costs are approximately proportional to molecular masses. For effectively irreversible reactions, the cell maximizes its metabolic efficiency by investing equally into substrate and unbound enzyme molecules. Without fitting any free parameters, the resulting model predicts in vivo substrate concentrations from enzyme concentrations and substrate affinities with high accuracy across data from E. coli and diverse eukaryotes (R2=0.79, geometric mean fold-error 1.74). The corresponding organizing principle – the minimization of the summed mass concentrations of solutes – may facilitate reducing the complexity of kinetic models and will contribute to the design of more efficient synthetic cellular systems.

scholarly journals Bayesian metabolic flux analysis reveals intracellular flux couplings

2019 ◽  
Vol 35 (14) ◽  
pp. i548-i557 ◽  
Author(s):  
Markus Heinonen ◽  
Maria Osmala ◽  
Henrik Mannerström ◽  
Janne Wallenius ◽  
Samuel Kaski ◽  
...  
Keyword(s):  
Steady State ◽  
Metabolic Flux Analysis ◽  
Metabolic Flux ◽  
Reaction Network ◽  
Reaction Rates ◽  
Supplementary Information ◽  
Flux Analysis ◽  
Metabolic Reaction ◽  
Metabolic Systems ◽  
Genome Scale

AbstractMotivationMetabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.ResultsWe introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.Availability and implementationThe COBRA compatible software is available at github.com/markusheinonen/bamfa.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Principles of RNA and nucleotide discrimination by the RNA processing enzyme RppH

2020 ◽  
Vol 48 (7) ◽  
pp. 3776-3788 ◽  
Author(s):  
Ang Gao ◽  
Nikita Vasilyev ◽  
Abhishek Kaushik ◽  
Wenqian Duan ◽  
Alexander Serganov
Keyword(s):  
Rna Processing ◽  
Reaction Rates ◽  
Growth Conditions ◽  
Rna Degradation ◽  
Nudix Hydrolase ◽  
X Ray ◽  
E Coli ◽  
Cellular Processes ◽  
Protein Factor ◽  
Hydrolysis Of

Abstract All enzymes face a challenge of discriminating cognate substrates from similar cellular compounds. Finding a correct substrate is especially difficult for the Escherichia coli Nudix hydrolase RppH, which triggers 5′-end-dependent RNA degradation by removing orthophosphate from the 5′-diphosphorylated transcripts. Here we show that RppH binds and slowly hydrolyzes NTPs, NDPs and (p)ppGpp, which each resemble the 5′-end of RNA. A series of X-ray crystal structures of RppH-nucleotide complexes, trapped in conformations either compatible or incompatible with hydrolysis, explain the low reaction rates of mononucleotides and suggest two distinct mechanisms for their hydrolysis. While RppH adopts the same catalytic arrangement with 5′-diphosphorylated nucleotides as with RNA, the enzyme hydrolyzes 5′-triphosphorylated nucleotides by extending the active site with an additional Mg2+ cation, which coordinates another reactive nucleophile. Although the average intracellular pH minimizes the hydrolysis of nucleotides by slowing their reaction with RppH, they nevertheless compete with RNA for binding and differentially inhibit the reactivity of RppH with triphosphorylated and diphosphorylated RNAs. Thus, E. coli RppH integrates various signals, such as competing non-cognate substrates and a stimulatory protein factor DapF, to achieve the differential degradation of transcripts involved in cellular processes important for the adaptation of bacteria to different growth conditions.

scholarly journals Current Issues in Sol-Gel Reaction Kinetics

1990 ◽  
Vol 180 ◽  
Author(s):  
Roger A. Assink ◽  
Bruce D. Kay
Keyword(s):  
Reaction Kinetics ◽  
Sol Gel ◽  
Early Time ◽  
Acid Catalyst ◽  
Reaction Rates ◽  
Reaction Conditions ◽  
Reaction Rate Constants ◽  
Condensation Reactions ◽  
Experimental Findings ◽  
Kinetics Of

ABSTRACTThis paper surveys a few of the current issues in sol-gel reaction kinetics. Many times seemingly modest changes in reactants or reaction conditions can lead to substantial differences in the overall reaction rates and pathways. For example, qualitative features of the reaction kinetics can depend on catalyst concentration. At very high acid-catalyst concentrations, reverse reactions are significant for TMOS solgels, while for moderate acid-catalyst concentrations, reverse reactions are substantially reduced. The reaction kinetics of two similar tetraalkoxysilanes: tetramethoxysilane (TMOS) and tetraethoxysilane (TEOS), can be markedly different under identical reaction conditions. Under acid-catalyzed reaction conditions, a TMOS sol-gel undergoes both water- and alcoholproducing condensation reactions while a TEOS sol-gel undergoes only water-producing condensation. The early time hydrolysis and condensation reactions of a TMOS sol-gel are statistical in nature and can be quantitatively described by a few simple reaction rate constants while the reaction behavior of a TEOS sol-gel is markedly nonstatistical. A comprehensive theory of sol-gel kinetics must address these diverse experimental findings.

scholarly journals The role of incoherent feedforward circuits in regulating precision of event timing

2020 ◽  
Author(s):  
Supravat Dey ◽  
Sherin Kannoly ◽  
Pavol Bokes ◽  
John J Dennehy ◽  
Abhyudai Singh
Keyword(s):  
Single Cells ◽  
Threshold Level ◽  
Cellular Growth ◽  
Critical Threshold ◽  
E Coli ◽  
Cellular Events ◽  
Event Timing ◽  
Simple Model System ◽  
Cell Data

AbstractTriggering of cellular events often relies on the level of a key gene product crossing a critical threshold. Achieving precision in event timing in spite of noisy gene expression facilitates high-fidelity functioning of diverse processes from biomolecular clocks, apoptosis and cellular differentiation. Here we investigate the role of an incoherent feedforward circuit in regulating the time taken by a bacterial virus (bacteriophage lambda) to lyse an infected Escherichia coli cell. Lysis timing is the result of expression and accumulation of a single lambda protein (holin) in the E. coli cell membrane up to a critical threshold level, which triggers the formation of membrane lesions. This easily visualized process provides a simple model system for characterizing event-timing stochasticity in single cells. Intriguingly, lambda’s lytic pathway synthesizes two functionally opposite proteins: holin and antiholin from the same mRNA in a 2:1 ratio. Antiholin sequesters holin and inhibits the formation of lethal membrane lesions, thus creating an incoherent feedforward circuit. We develop and analyze a stochastic model for this feedforward circuit that considers correlated bursty expression of holin/antiholin, and their concentrations are diluted from cellular growth. Interestingly, our analysis shows the noise in timing is minimized when both proteins are expressed at an optimal ratio, hence revealing an important regulatory role for antiholin. These results are in agreement with single cell data, where removal of antiholin results in enhanced stochasticity in lysis timing.

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