scholarly journals Quantification of microbial robustness

2021 ◽  
Author(s):  
Cecilia Trivellin ◽  
Lisbeth Olsson ◽  
Peter Rugbjerg
Keyword(s):  
Fano Factor ◽  
Product Yield ◽  
Bioethanol Production ◽  
Cellular Functions ◽  
Negative Function ◽  
Trade Offs ◽  
Synthetic Cell ◽  
The Mean ◽  
End Use ◽  
Cell Functionality

Stable cell performance in a fluctuating environment is essential for sustainable bioproduction and synthetic cell functionality; however, microbial robustness is rarely quantified. Here, we describe a high-throughput strategy for quantifying robustness of multiple cellular functions and strains in a perturbation space. We evaluated quantifications theory on experimental data and concluded that the mean-normalized Fano factor allowed accurate, reliable, and standardized quantification. Our methodology applied to perturbations related to lignocellulosic bioethanol production showed that Saccharomyces cerevisiae Ethanol Red exhibited both higher and more robust growth rates than CEN.PK and PE-2, while a more robust product yield traded off for lower mean levels. The methodology validated that robustness is function-specific and characterized by positive and negative function-specific trade-offs. Systematic quantification of robustness to end-use perturbations will be important to analyze and construct robust strains with more predictable functions.

Computing trade-offs in robust design: Perspectives of the mean squared error

2011 ◽  
Vol 60 (2) ◽  
pp. 248-255 ◽  
Author(s):  
Sangmun Shin ◽  
Funda Samanlioglu ◽  
Byung Rae Cho ◽  
Margaret M. Wiecek
Keyword(s):  
Robust Design ◽  
Mean Squared Error ◽  
Squared Error ◽  
Trade Offs ◽  
The Mean

scholarly journals Fano factor and the mean energy per ion pair in counting gases, at low x-ray energies

1997 ◽  
Vol 82 (2) ◽  
pp. 871-877 ◽  
Author(s):  
A. Pansky ◽  
A. Breskin ◽  
R. Chechik
Keyword(s):  
Fano Factor ◽  
Ion Pair ◽  
X Ray ◽  
The Mean ◽  
Low X

scholarly journals A modified fluctuation test for elucidating drug resistance in microbial and cancer cells

2020 ◽  
Author(s):  
Pavol Bokes ◽  
Abhyudai Singh
Keyword(s):  
Drug Resistance ◽  
Cancer Cells ◽  
Colony Size ◽  
Random Number ◽  
Initial Conditions ◽  
Fano Factor ◽  
Persister Cells ◽  
Efficient Treatment ◽  
Fluctuation Test ◽  
The Mean

AbstractClonal populations of microbial and cancer cells are often driven into a drug-tolerant persister state in response to drug therapy, and these persisters can subsequently adapt to the new drug environment via genetic and epigenetic mechanisms. Estimating the frequency with which drug-tolerance states arise, and its transition to drug-resistance, is critical for designing efficient treatment schedules. Here we study a stochastic model of cell proliferation where drug-tolerant persister cells transform into a drug-resistant state with a certain adaptation rate, and the resistant cells can then proliferate in the presence of the drug. Assuming a random number of persisters to begin with, we derive an exact analytical expression for the statistical moments and the distribution of the total cell count (i.e., colony size) over time. Interestingly, for Poisson initial conditions the noise in the colony size (as quantified by the Fano factor) becomes independent of the initial condition and only depends on the adaptation rate. Thus, experimentally quantifying the fluctuations in the colony sizes provides an estimate of the adaptation rate, which then can be used to infer the starting persister numbers from the mean colony size. Overall, our analysis introduces a modification of the classical Luria–Delbrück experiment, also called the “Fluctuation Test”, providing a valuable tool to quantify the emergence of drug resistance in cell populations.

Design strategies for oxy-combustion power plant captured CO2 purification

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ikenna J. Okeke ◽  
Tia Ghantous ◽  
Thomas A. Adams
Keyword(s):  
Power Plant ◽  
Flue Gas ◽  
Capture Rate ◽  
Ghg Emissions ◽  
Oxygen Removal ◽  
Water Removal ◽  
Design Strategies ◽  
Technoeconomic Analysis ◽  
Trade Offs ◽  
End Use

Abstract This study presents a novel design and techno-economic analysis of processes for the purification of captured CO2 from the flue gas of an oxy-combustion power plant fueled by petroleum coke. Four candidate process designs were analyzed in terms of GHG emissions, thermal efficiency, pipeline CO2 purity, CO2 capture rate, levelized costs of electricity, and cost of CO2 avoided. The candidates were a classic process with flue-gas water removal via condensation, flue-gas water removal via condensation followed by flue-gas oxygen removal through cryogenic distillation, flue-gas water removal followed by catalytic conversion of oxygen in the flue gas to water via reaction with hydrogen, and oxy-combustion in a slightly oxygen-deprived environment with flue-gas water removal and no need for flue gas oxygen removal. The former two were studied in prior works and the latter two concepts are new to this work. The eco-technoeconomic analysis results indicated trade-offs between the four options in terms of cost, efficiency, lifecycle greenhouse gas emissions, costs of CO2 avoided, technical readiness, and captured CO2 quality. The slightly oxygen-deprived process has the lowest costs of CO2 avoided, but requires tolerance of a small amount of H2, CO, and light hydrocarbons in the captured CO2 which may or may not be feasible depending on the CO2 end use. If infeasible, the catalytic de-oxygenation process is the next best choice. Overall, this work is the first study to perform eco-technoeconomic analyses of different techniques for O2 removal from CO2 captured from an oxy-combustion power plant.

scholarly journals N-Acetylglucosamine Utilization by Saccharomyces cerevisiae Based on Expression of Candida albicans NAG Genes

2009 ◽  
Vol 75 (18) ◽  
pp. 5840-5845 ◽  
Author(s):  
Jürgen Wendland ◽  
Yvonne Schaub ◽  
Andrea Walther
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Candida Albicans ◽  
Carbon Source ◽  
Sole Carbon Source ◽  
De Novo ◽  
Biofuel Production ◽  
Bioethanol Production ◽  
Catabolic Pathway ◽  
Cellular Functions ◽  
Kinase A

ABSTRACT Synthesis of chitin de novo from glucose involves a linear pathway in Saccharomyces cerevisiae. Several of the pathway genes, including GNA1, are essential. Genes for chitin catabolism are absent in S. cerevisiae. Therefore, S. cerevisiae cannot use chitin as a carbon source. Chitin is the second most abundant polysaccharide after cellulose and consists of N-acetylglucosamine (GlcNAc) moieties. Here, we have generated S. cerevisiae strains that are able to use GlcNAc as a carbon source by expressing four Candida albicans genes (NAG3 or its NAG4 paralog, NAG5, NAG2, and NAG1) encoding a GlcNAc permease, a GlcNAc kinase, a GlcNAc-6-phosphate deacetylase, and a glucosamine-6-phosphate deaminase, respectively. Expression of NAG3 and NAG5 or NAG4 and NAG5 in S. cerevisiae resulted in strains in which the otherwise-essential ScGNA1 could be deleted. These strains required the presence of GlcNAc in the medium, indicating that uptake of GlcNAc and its phosphorylation were achieved. Expression of all four NAG genes produced strains that could use GlcNAc as the sole carbon source for growth. Utilization of a GlcNAc catabolic pathway for bioethanol production using these strains was tested. However, fermentation was slow and yielded only minor amounts of ethanol (approximately 3.0 g/liter), suggesting that fructose-6-phosphate produced from GlcNAc under these conditions is largely consumed to maintain cellular functions and promote growth. Our results present the first step toward tapping a novel, renewable carbon source for biofuel production.

Alvena hard red spring wheat

2008 ◽  
Vol 88 (3) ◽  
pp. 513-518 ◽  
Author(s):  
R. E. Knox ◽  
R. M. DePauw ◽  
F. R. Clarke ◽  
F. R. Clarke ◽  
T. N. McCaig ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Grain Yield ◽  
Spring Wheat ◽  
Protein Concentration ◽  
Triticum Aestivum L ◽  
Head Blight ◽  
Hard Red Spring Wheat ◽  
The Mean ◽  
End Use ◽  
Moderate Resistance

Based on 38 replicated trials over 3 yr, Alvena, hard red spring wheat (Triticum aestivum L.) expressed significantly higher mean grain yield than the checks. It was significantly earlier maturing than AC Barrie and significantly more resistant to lodging than Katepwa. Wheat protein concentration of Alvena was similar to the mean of the checks and flour protein concentration was significantly higher than the check mean. Amylograph viscosity was significantly lower than the mean of the checks. Alvena meets the end-use quality and Canadian Grain Commission’s kernel visual distinguishability specifications of the Canada Western Red Spring wheat market class. Alvena expressed moderate resistance to prevalent races of loose smut and stem rust, intermediate resistance to prevalent races of leaf rust and common bunt, and moderate susceptibility to fusarium head blight. Key words: Triticum aestivum L., cultivar description, grain yield, maturity, disease resistance

scholarly journals Optimal metabolic states in cells

2018 ◽  
Author(s):  
Wolfram Liebermeister
Keyword(s):  
Resource Allocation ◽  
Metabolic Pathways ◽  
Network Models ◽  
Cellular Systems ◽  
Biochemical Network ◽  
Mathematical Form ◽  
Cellular Functions ◽  
Trade Offs ◽  
Metabolic States ◽  
Common Framework

AbstractCells need to make an efficient use of metabolites, proteins, energy, membrane space, and time, and resource allocation is also an important aspect of metabolism. How, for example, should cells distribute their protein budget between different cellular functions, e.g. different metabolic pathways, to maximise growth? Cellular resource allocation can be studied by combining biochemical network models with optimality problems that choose metabolic states by their cost and benefit. Various types of resource allocation problems have been proposed. The underlying mechanistic models may describe different cellular systems (e.g. metabolic pathways, networks, or compromises between metabolism and protein production) on different level of detail and using different mathematical formulations (e.g. stoichiometric or kinetic). The optimality problems may use metabolite levels, enzyme levels, or fluxes as variables, assume different cost or benefit functions, and describe different kinds of trade-offs, in which cell variables are either constrained or treated as optimisation objectives. Due to all these differences, optimality problems may be hard to compare or combine. To bring them under one umbrella, I show that they can be derived from a common framework, and that their optimality conditions all show the same mathematical form. This unified view on metabolic optimality problems can be used to justify and combine various modelling approaches and biochemical optimality problems.

Comparison of Dynamical Behaviors Between Monofunctional and Bifunctional Two-Component Signaling Modules

2015 ◽  
Vol 25 (07) ◽  
pp. 1540010
Author(s):  
Xiyan Yang ◽  
Yahao Wu ◽  
Zhanjiang Yuan
Keyword(s):  
Response Regulator ◽  
Fano Factor ◽  
Stable Steady State ◽  
Sensor Kinase ◽  
Dynamical Behaviors ◽  
Two Component ◽  
System Components ◽  
The Mean ◽  
Signaling Modules ◽  
Deterministic Behavior

Two-component signaling modules exist extensively in bacteria and microbes. These modules can be, based on their distinct network structures, divided into two types: the monofunctional system (denoted by MFS) where the sensor kinase (SK) modulates only phosphorylation of the response regulator (RR), and the bifunctional system (denoted by BFS) where the SK catalyzes both phosphorylation and dephosphorylation of the RR. Here, we analyze dynamical behaviors of these two systems based on stability theory, focusing on differences between them. The analysis of the deterministic behavior indicates that there is no difference between the two modules, that is, each system has the unique stable steady state. However, there are significant differences in stochastic behavior between them. Specifically, if the mean phosphorylated SK level is kept the same for the two modules, then the variance and the Fano factor for the phosphorylated RR in the BFS are always no less than those in the MFS, indicating that bifunctionality always enhances fluctuations. The correlation between the phosphorylated SK and the phosphorylated RR in the BFS is always positive mainly due to competition between system components, but this correlation in the MFS may be positive, almost zero, or negative, depending on the ratio between two rate constants. Our overall analysis indicates that differences between dynamical behaviors of monofunctional and bifunctional signaling modules are mainly in the stochastic rather than deterministic aspect.

Using Existing Anthropometric Data to Design Industrial Workplaces

1979 ◽  
Vol 23 (1) ◽  
pp. 168-168
Author(s):  
Paul C. Champney
Keyword(s):  
Functional Data ◽  
Regional Differences ◽  
Anthropometric Data ◽  
Single Population ◽  
Trade Offs ◽  
The Mean ◽  
The Military ◽  
Number Of Individuals ◽  
Percent Female ◽  
Adequate Data

Designing industrial workplaces is hampered by the lack of data that describe the potential workforce. The civilian data base is not adequate because it is small, is taken on specific populations, and is not stratified to reveal ethnic and regional differences. Military data are often used as an alternative, but these data also have shortcomings. Among these are the truncation of extremes, a paucity of functional data and the fact that the data are often taken for special purposes. Since Eastman Kodak remains committed to a policy of providing safe workplaces that accommodate females, males, and the various ethnic groups, the lack of adequate data is acute. To fill the need for data, it has been necessary to statistically combine the military data into a single population that is theoretically 50 percent female and 50 percent male. This has been done for forty measurements using the mean standard deviation, and the number of individuals measured. Data on this mixed population are being used to design and redesign workplaces, equipment and product at Eastman Kodak Company. The problems encountered using existing anthropometric data to design a comfortable standing workplace are only one example of what trade-offs must be made and where further data are needed.

Behavioral considerations for effective time-varying electricity prices

2017 ◽  
Vol 1 (2) ◽  
pp. 219-251 ◽  
Author(s):  
IAN SCHNEIDER ◽  
CASS R. SUNSTEIN
Keyword(s):  
Electricity Consumption ◽  
Default Rule ◽  
Time Varying ◽  
System A ◽  
Trade Offs ◽  
Short Run ◽  
Rate Design ◽  
End Use ◽  
Price Distortions ◽  
Rate Type

AbstractWholesale prices for electricity vary significantly due to high fluctuations and low elasticity of short-run demand. End-use customers have typically paid flat retail rates for their electricity consumption, and time-varying prices (TVPs) have been proposed to help reduce peak consumption and lower the overall cost of servicing demand. Unfortunately, the general practice is an opt-in system: a default rule in favor of TVPs would be far better. A behaviorally informed analysis also shows that when transaction costs and decision biases are taken into account, the most cost-reflective policies are not necessarily the most efficient. On reasonable assumptions, real-time prices can result in less peak conservation of manually controlled devices than time-of-use or critical-peak prices. For that reason, the trade-offs between engaging automated and manually controlled loads must be carefully considered in time-varying rate design. The rate type and accompanying program details should be designed with the behavioral biases of consumers in mind, while minimizing price distortions for automated devices.

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