scholarly journals The interplay between growth rate and nutrient quality defines gene expression capacity

2021 ◽  
Author(s):  
Juhyun Kim ◽  
Alexander P.S. Darlington ◽  
Declan G Bates ◽  
Jose Ignacio Jimenez
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Physiological Parameter ◽  
Bacterial Cells ◽  
Heterologous Proteins ◽  
Efficient Design ◽  
Translational Machinery ◽  
Trade Offs ◽  
Individual Contributions ◽  
The Individual

The gene expression capacity of bacterial cells depends on the interplay between growth and the availability of the transcriptional and translational machinery. Growth rate is widely accepted as the global physiological parameter controlling the allocation of cell resources. This allocation has an impact on the ability of the cell to produce both host and heterologous proteins required for synthetic circuits and pathways. Understanding the relationship between growth and resources is key for the efficient design of artificial genetic constructs, however, it is obscured by the mutual dependence of growth and gene expression on each other. In this work, we investigate the individual contributions of molecular factors, growth rate and metabolism to gene expression by investigating the behaviour of bacterial cells growing in chemostats in growth-limited conditions. We develop a model of the whole cell that captures trade-offs in gene expression arising from the individual contributions of different factors, and validate it by analysing gene couplings which emerge from competition for the gene expression machinery. Our results show that while growth rate and molecular factors, such as the number of rRNA operons, set the abundance of transcriptional and translational machinery available, it is metabolism that governs the usage of those resources by tuning elongation rates. We show that synthetic gene expression capacity can be maximised by using low growth in a high-quality medium. These findings provide valuable insights into fundamental trade-offs in microbial physiology that will inform future strain and bioprocesses optimisation.

scholarly journals Noise propagation in an integrated model of bacterial gene expression and growth

2018 ◽  
Author(s):  
Istvan T. Kleijn ◽  
Laurens H. J. Krah ◽  
Rutger Hermsen
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Integrated Approach ◽  
Control Analysis ◽  
Instantaneous Growth Rate ◽  
Bacterial Cells ◽  
Noise Propagation ◽  
Bacterial Gene ◽  
Trade Offs ◽  
Cross Correlations

AbstractIn bacterial cells, gene expression, metabolism, and growth are highly interdependent and tightly coordinated. As a result, stochastic fluctuations in expression levels and instantaneous growth rate show intricate cross-correlations. These correlations are shaped by feedback loops, trade-offs and constraints acting at the cellular level; therefore a quantitative understanding requires an integrated approach. To that end, we here present a mathematical model describing a cell that contains multiple proteins that are each expressed stochastically and jointly limit the growth rate. Conversely, metabolism and growth affect protein synthesis and dilution. Thus, expression noise originating in one gene propagates to metabolism, growth, and the expression of all other genes. Nevertheless, under a small-noise approximation many statistical quantities can be calculated analytically. We identify several routes of noise propagation, illustrate their origins and scaling, and establish important connections between noise propagation and the field of metabolic control analysis. We then present a many-protein model containing > 1000 proteins parameterized by previously measured abundance data and demonstrate that the predicted cross-correlations between gene expression and growth rate are in broad agreement with published measurements.

scholarly journals Starvation resistance and tissue-specific gene expression of stress-related genes in a naturally inbred ant population

2016 ◽  
Vol 3 (4) ◽  
pp. 160062 ◽  
Author(s):  
Nick Bos ◽  
Unni Pulliainen ◽  
Liselotte Sundström ◽  
Dalial Freitak
Keyword(s):  
Gene Expression ◽  
Stress Responses ◽  
Specific Gene ◽  
Starvation Resistance ◽  
Specific Expression ◽  
Tissue Specific ◽  
Trade Offs ◽  
Stress Related Genes ◽  
The Individual ◽  
Different Tissues

Starvation is one of the most common and severe stressors in nature. Not only does it lead to death if not alleviated, it also forces the starved individual to allocate resources only to the most essential processes. This creates energetic trade-offs which can lead to many secondary challenges for the individual. These energetic trade-offs could be exacerbated in inbred individuals, which have been suggested to have a less efficient metabolism. Here, we studied the effect of inbreeding on starvation resistance in a natural population of Formica exsecta ants, with a focus on survival and tissue-specific expression of stress, metabolism and immunity-related genes. Starvation led to large tissue-specific changes in gene expression, but inbreeding had little effect on most of the genes studied. Our results illustrate the importance of studying stress responses in different tissues instead of entire organisms.

scholarly journals A mechanistic link between cellular trade-offs, gene expression and growth

2015 ◽  
Author(s):  
Andrea Y. Weisse ◽  
Diego A. Oyarzun ◽  
Vincent Danos ◽  
Peter S. Swain
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Metabolic Pathways ◽  
Mechanistic Model ◽  
Living Cells ◽  
Coarse Grained ◽  
Empirical Relationships ◽  
Cellular Energy ◽  
Modelling Framework ◽  
Trade Offs

Intracellular processes rarely work in isolation but continually interact with the rest of the cell. In microbes, for example, we now know that gene expression across the whole genome typically changes with growth rate. The mechanisms driving such global regulation, however, are not well understood. Here we consider three trade-offs that because of limitations in levels of cellular energy, free ribosomes, and proteins are faced by all living cells and construct a mechanistic model that comprises these trade-offs. Our model couples gene expression with growth rate and growth rate with a growing population of cells. We show that the model recovers Monod's law for the growth of microbes and two other empirical relationships connecting growth rate to the mass fraction of ribosomes. Further, we can explain growth related effects in dosage compensation by paralogs and predict host-circuit interactions in synthetic biology. Simulating competitions between strains, we find that the regulation of metabolic pathways may have evolved not to match expression of enzymes to levels of extracellular substrates in changing environments but rather to balance a trade-off between exploiting one type of nutrient over another. Although coarse-grained, the trade-offs that the model embodies are fundamental, and, as such, our modelling framework has potentially wide application, including in both biotechnology and medicine.

scholarly journals Precise optical control of gene expression in C. elegans using improved genetic code expansion and Cre recombinase

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Lloyd Davis ◽  
Inja Radman ◽  
Angeliki Goutou ◽  
Ailish Tynan ◽  
Kieran Baxter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Code ◽  
Cre Recombinase ◽  
Symmetric Pair ◽  
Control Of Gene Expression ◽  
C Elegans ◽  
Individual Contributions ◽  
Touch Response ◽  
Genetic Code Expansion ◽  
The Individual

Synthetic strategies for optically controlling gene expression may enable the precise spatiotemporal control of genes in any combination of cells that cannot be targeted with specific promoters. We develop an improved genetic code expansion system in C. elegans and use it to create a photo-activatable Cre recombinase. We laser-activate Cre in single neurons within a bilaterally symmetric pair to selectively switch on expression of a loxP controlled optogenetic channel in the targeted neuron. We use the system to dissect, in freely moving animals, the individual contributions of the mechanosensory neurons PLML/PLMR to the C. elegans touch response circuit, revealing distinct and synergistic roles for these neurons. We thus demonstrate how genetic code expansion and optical targeting can be combined to break the symmetry of neuron pairs and dissect behavioural outputs of individual neurons that cannot be genetically targeted.

scholarly journals Codon optimisation for maximising gene expression in multiple species and microbial consortia

2020 ◽  
Author(s):  
David J. Skelton ◽  
Lucy E. Eland ◽  
Martin Sim ◽  
Michael A. White ◽  
Russell J. Davenport ◽  
...  
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Optimal Parameter ◽  
Microbial Consortia ◽  
Heterologous Proteins ◽  
Coding Sequences ◽  
Coding Sequence ◽  
Mutation Operators ◽  
Codon Optimisation ◽  
The Individual

AbstractMotivationCodon optimisation, the process of adapting the codon composition of a coding sequence, is often used in synthetic biology to increase expression of a heterologous protein. Recently, a number of synthetic biology approaches that allow synthetic constructs to be deployed in multiple organisms have been published. However, so far, design tools for codon optimisation have not been updated to reflect these new approaches.ApproachWe designed an evolutionary algorithm (EA) to design coding sequences (CDSs) that encode a target protein for one or more target organisms, based on the Chimera average repetitive substring (ARS) metric — a correlate of gene expression. A parameter scan was then used to find optimal parameter sets. Using the optimal parameter sets, three heterologous proteins were repeatedly optimised Bacillus subtilis 168 and Escherichia coli MG1655. The ARS scores of the resulting sequences were compared to the ARS scores of coding sequences that had been optimised for each organism individually (using Chimera Map).ResultsWe demonstrate that an EA is a valid approach to optimising a coding sequence for multiple organisms at once; both crossover and mutation operators were shown to be necessary for the best performance. In some scenarios, the EA generated CDSs that had higher ARS scores than CDSs optimised for the individual organisms, suggesting that the EA exploits the CDS design space in a way that Chimera Map does not.Availability and implementationThe implementation of the EA, with instructions, is available on GitHub: https://github.com/intbio-ncl/chimera_evolve.

scholarly journals Challenges of analysing stochastic gene expression in bacteria using single-cell time-lapse experiments

2021 ◽  
Author(s):  
Georgeos Hardo ◽  
Somenath Bakshi
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Cells ◽  
Time Lapse ◽  
Careful Consideration ◽  
Stochastic Gene Expression ◽  
Bacterial Cells ◽  
Rigorous Framework ◽  
Cell Gene Expression ◽  
The Individual

Abstract Stochastic gene expression causes phenotypic heterogeneity in a population of genetically identical bacterial cells. Such non-genetic heterogeneity can have important consequences for the population fitness, and therefore cells implement regulation strategies to either suppress or exploit such heterogeneity to adapt to their circumstances. By employing time-lapse microscopy of single cells, the fluctuation dynamics of gene expression may be analysed, and their regulatory mechanisms thus deciphered. However, a careful consideration of the experimental design and data-analysis is needed to produce useful data for deriving meaningful insights from them. In the present paper, the individual steps and challenges involved in a time-lapse experiment are discussed, and a rigorous framework for designing, performing, and extracting single-cell gene expression dynamics data from such experiments is outlined.

scholarly journals Operon Concatenation Is an Ancient Feature That Restricts the Potential to Rearrange Bacterial Chromosomes

2019 ◽  
Vol 36 (9) ◽  
pp. 1990-2000 ◽  
Author(s):  
Gerrit Brandis ◽  
Sha Cao ◽  
Diarmaid Hughes
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Significant Role ◽  
Common Ancestor ◽  
Last Common Ancestor ◽  
Selective Force ◽  
Translational Machinery ◽  
Ancestral Chromosome ◽  
Bacterial Chromosomes ◽  
Operon Organization

Abstract The last common ancestor of the Gammaproteobacteria carried an important 40-kb chromosome section encoding 51 proteins of the transcriptional and translational machinery. These genes were organized into eight contiguous operons (rrnB-tufB-secE-rpoBC-str-S10-spc-alpha). Over 2 Gy of evolution, in different lineages, some of the operons became separated by multigene insertions. Surprisingly, in many Enterobacteriaceae, much of the ancient organization is conserved, indicating a strong selective force on the operons to remain colinear. Here, we show for one operon pair, tufB-secE in Salmonella, that an interruption of contiguity significantly reduces growth rate. Our data show that the tufB-secE operons are concatenated by an interoperon terminator–promoter overlap that plays a significant role regulating gene expression. Interrupting operon contiguity interferes with this regulation, reducing cellular fitness. Six operons of the ancestral chromosome section remain contiguous in Salmonella (tufB-secE-rpoBC and S10-spc-alpha) and, strikingly, each of these operon pairs is also connected by an interoperon terminator–promoter overlap. Accordingly, we propose that operon concatenation is an ancient feature that restricts the potential to rearrange bacterial chromosomes and can select for the maintenance of a colinear operon organization over billions of years.

scholarly journals Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments

2020 ◽  
Author(s):  
Yu Chen ◽  
Eunice van Pelt-KleinJan ◽  
Berdien van Olst ◽  
Sieze Douwenga ◽  
Sjef Boeren ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Nitrogen Sources ◽  
Metabolic Model ◽  
Proteomics Data ◽  
Available Nitrogen ◽  
Regulatory Strategies ◽  
Trade Offs ◽  
Evolutionary Changes ◽  
Genome Scale

Cells adapt to different conditions via gene expression that tunes metabolism and stress resistance for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs1; Resource allocation under proteome constraints has emerged as a powerful paradigm to explain regulatory strategies in bacteria2. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, such as the lactic acid bacterium Lactococcus lactis. Here we present an approach to identify preferred nutrients from integration of experimental data with a proteome-constrained genome-scale metabolic model of L. lactis (pcLactis), which explicitly accounts for gene expression processes and associated constraints. Using glucose-limited chemostat data3, we identified the uptake of glucose and arginine as dominant constraints, whose pathway proteins were indeed upregulated in evolved mutants. However, above a growth rate of 0.5 h-1, pcLactis suggests that available enzymes function at their maximum capacity, which allows an increase in growth rate only by altering gene expression to change metabolic fluxes, as was mainly observed for arginine metabolism. Thus, our integrative analysis of flux and proteomics data with a proteome-constrained model is able to identify and explain the constraints that form targets of regulation and fitness improvement in nutrient-rich growth environments.

scholarly journals Mechanistic links between cellular trade-offs, gene expression, and growth

2015 ◽  
Vol 112 (9) ◽  
pp. E1038-E1047 ◽  
Author(s):  
Andrea Y. Weiße ◽  
Diego A. Oyarzún ◽  
Vincent Danos ◽  
Peter S. Swain
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Metabolic Pathways ◽  
Mechanistic Model ◽  
Living Cells ◽  
Coarse Grained ◽  
Modeling Framework ◽  
Empirical Relationships ◽  
Cellular Energy ◽  
Trade Offs

Intracellular processes rarely work in isolation but continually interact with the rest of the cell. In microbes, for example, we now know that gene expression across the whole genome typically changes with growth rate. The mechanisms driving such global regulation, however, are not well understood. Here we consider three trade-offs that, because of limitations in levels of cellular energy, free ribosomes, and proteins, are faced by all living cells and we construct a mechanistic model that comprises these trade-offs. Our model couples gene expression with growth rate and growth rate with a growing population of cells. We show that the model recovers Monod’s law for the growth of microbes and two other empirical relationships connecting growth rate to the mass fraction of ribosomes. Further, we can explain growth-related effects in dosage compensation by paralogs and predict host–circuit interactions in synthetic biology. Simulating competitions between strains, we find that the regulation of metabolic pathways may have evolved not to match expression of enzymes to levels of extracellular substrates in changing environments but rather to balance a trade-off between exploiting one type of nutrient over another. Although coarse-grained, the trade-offs that the model embodies are fundamental, and, as such, our modeling framework has potentially wide application, including in both biotechnology and medicine.

A Handbook to Eddic Poetry: Myths and Legends of Early Scandinavia, ed. Carolyne Larrington, Judy Quinn, and Brittany Schorn. Cambridge: Cambridge University Press, 2016, xii, 413 pp., 12 b/w ill.

Mediaevistik ◽  
2018 ◽  
Vol 31 (1) ◽  
pp. 366-366
Author(s):  
Albrecht Classen
Keyword(s):  
Old Norse ◽  
Entire Volume ◽  
Cambridge University ◽  
Critical Studies ◽  
Individual Contributions ◽  
The Many ◽  
The Individual ◽  
Made In ◽  
Scandinavian Literature

Eddic poetry constitutes one of the most important genres in Old Norse or Scandinavian literature and has been studied since the earliest time of modern-day philology. The progress we have made in that field is impressive, considering the many excellent editions and translations, not to mention the countless critical studies in monographs and articles. Nevertheless, there is always a great need to revisit, to summarize, to review, and to digest the knowledge gained so far. The present handbook intends to address all those goals and does so, to spell it out right away, exceedingly well. But in contrast to traditional concepts, the individual contributions constitute fully developed critical article, each with a specialized topic elucidating it as comprehensively as possible, and concluding with a section of notes. Those are kept very brief, but the volume rounds it all off with an inclusive, comprehensive bibliography. And there is also a very useful index at the end. At the beginning, we find, following the table of contents, a list of the contributors, unfortunately without emails, a list of translations and abbreviations of the titles of Eddic poems in the Codex Regius and then elsewhere, and a very insightful and pleasant introduction by Carolyne Larrington. She briefly introduces the genre and then summarizes the essential points made by the individual authors. The entire volume is based on the Eddic Network established by the three editors in 2012, and on two workshops held at St. John’s College, Oxford in 2013 and 2014.

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