scholarly journals Predictive evolution of metabolic phenotypes using model-designed selection niches

2021 ◽  
Author(s):  
Paula Jouhten ◽  
Dimitrios Konstantinidis ◽  
Filipa Pereira ◽  
Sergej Andrejev ◽  
Kristina Grkovska ◽  
...  
Keyword(s):  
Darwinian Evolution ◽  
Biotechnological Applications ◽  
Adaptive Laboratory Evolution ◽  
Laboratory Evolution ◽  
Darwinian Selection ◽  
Metabolic Phenotypes ◽  
Design Selection ◽  
Costly Traits ◽  
Trait Correlations ◽  
Selection Of

Traits lacking fitness benefit cannot be directly selected for under Darwinian evolution. Thus, features such as metabolite secretion are currently inaccessible to adaptive laboratory evolution. Here, we utilize environment-dependency of trait correlations to enable Darwinian selection of fitness-neutral or costly traits. We use metabolic models to design selection niches and to identify surrogate traits that are genetically correlated with cell fitness in the selection niche but coupled to the desired trait in the target niche. Adaptive evolution in the selection niche and subsequent return to the target niche is thereby predicted to enhance the desired trait. We experimentally validate the theory by evolving Saccharomyces cerevisiae for increased secretion of aroma compounds in wine fermentation. Genomic, transcriptomic, and proteomic changes in the evolved strains confirmed the predicted flux re-routing to aroma biosynthesis. The use of model-designed selection niches facilitates the predictive evolution of fitness-costly traits for ecological and biotechnological applications.

scholarly journals Asymptotic Expansions and Strategies in the Online Increasing Subsequence Problem

2021 ◽  
Vol 174 (1) ◽  
Author(s):  
Amirlan Seksenbayev
Keyword(s):  
Dynamic Programming ◽  
Asymptotic Expansions ◽  
Dual Problem ◽  
Infinite Length ◽  
Expected Time ◽  
Selection Strategies ◽  
Dynamic Programming Equation ◽  
Optimal Values ◽  
Design Selection ◽  
Selection Of

AbstractWe study two closely related problems in the online selection of increasing subsequence. In the first problem, introduced by Samuels and Steele (Ann. Probab. 9(6):937–947, 1981), the objective is to maximise the length of a subsequence selected by a nonanticipating strategy from a random sample of given size $n$ n . In the dual problem, recently studied by Arlotto et al. (Random Struct. Algorithms 49:235–252, 2016), the objective is to minimise the expected time needed to choose an increasing subsequence of given length $k$ k from a sequence of infinite length. Developing a method based on the monotonicity of the dynamic programming equation, we derive the two-term asymptotic expansions for the optimal values, with $O(1)$ O ( 1 ) remainder in the first problem and $O(k)$ O ( k ) in the second. Settling a conjecture in Arlotto et al. (Random Struct. Algorithms 52:41–53, 2018), we also design selection strategies to achieve optimality within these bounds, that are, in a sense, best possible.

scholarly journals Engineering improved ethylene production: Leveraging systems Biology and adaptive laboratory evolution

2021 ◽  
Author(s):  
Sophie Vaud ◽  
Nicole Pearcy ◽  
Marko Hanževački ◽  
Alexander M.W. Van Hagen ◽  
Salah Abdelrazig ◽  
...  
Keyword(s):  
Systems Biology ◽  
Ethylene Production ◽  
Adaptive Laboratory Evolution ◽  
Laboratory Evolution

scholarly journals Adaptive Laboratory Evolution of Cupriavidus necator H16 for Carbon Co-Utilization with Glycerol

2019 ◽  
Vol 20 (22) ◽  
pp. 5737 ◽  
Author(s):  
Miriam González-Villanueva ◽  
Hemanshi Galaiya ◽  
Paul Staniland ◽  
Jessica Staniland ◽  
Ian Savill ◽  
...  
Keyword(s):  
Type Strain ◽  
Wild Type Strain ◽  
Carbon Sources ◽  
Strain Engineering ◽  
Cupriavidus Necator ◽  
Superior Performance ◽  
Wild Type ◽  
Adaptive Laboratory Evolution ◽  
Laboratory Evolution ◽  
Cupriavidus Necator H16

Cupriavidus necator H16 is a non-pathogenic Gram-negative betaproteobacterium that can utilize a broad range of renewable heterotrophic resources to produce chemicals ranging from polyhydroxybutyrate (biopolymer) to alcohols, alkanes, and alkenes. However, C. necator H16 utilizes carbon sources to different efficiency, for example its growth in glycerol is 11.4 times slower than a favorable substrate like gluconate. This work used adaptive laboratory evolution to enhance the glycerol assimilation in C. necator H16 and identified a variant (v6C6) that can co-utilize gluconate and glycerol. The v6C6 variant has a specific growth rate in glycerol 9.5 times faster than the wild-type strain and grows faster in mixed gluconate–glycerol carbon sources compared to gluconate alone. It also accumulated more PHB when cultivated in glycerol medium compared to gluconate medium while the inverse is true for the wild-type strain. Through genome sequencing and expression studies, glycerol kinase was identified as the key enzyme for its improved glycerol utilization. The superior performance of v6C6 in assimilating pure glycerol was extended to crude glycerol (sweetwater) from an industrial fat splitting process. These results highlight the robustness of adaptive laboratory evolution for strain engineering and the versatility and potential of C. necator H16 for industrial waste glycerol valorization.

Evidence for Positive Darwinian Selection of Vip Gene in Bacillus thuringiensis

2007 ◽  
Vol 34 (7) ◽  
pp. 649-660 ◽  
Author(s):  
Jinyu Wu ◽  
Fangqing Zhao ◽  
Jie Bai ◽  
Gang Deng ◽  
Song Qin ◽  
...  
Keyword(s):  
Bacillus Thuringiensis ◽  
Positive Darwinian Selection ◽  
Darwinian Selection ◽  
Selection Of

scholarly journals Mooring Design Selection of Aquaculture Cage for Indonesian Ocean

2018 ◽  
Vol 135 ◽  
pp. 012022
Author(s):  
Y Mulyadi ◽  
N Syahroni ◽  
K Sambodho ◽  
M Zikra ◽  
Wahyudi ◽  
...  
Keyword(s):  
Design Selection ◽  
Selection Of

scholarly journals ALEdb 1.0: a database of mutations from adaptive laboratory evolution experimentation

2018 ◽  
Vol 47 (D1) ◽  
pp. D1164-D1171 ◽  
Author(s):  
Patrick V Phaneuf ◽  
Dennis Gosting ◽  
Bernhard O Palsson ◽  
Adam M Feist
Keyword(s):  
Adaptive Laboratory Evolution ◽  
Laboratory Evolution

scholarly journals Application of Microalgal Stress Responses in Industrial Microalgal Production Systems

Marine Drugs ◽  
2021 ◽  
Vol 20 (1) ◽  
pp. 30
Author(s):  
Jia Wang ◽  
Yuxin Wang ◽  
Yijian Wu ◽  
Yuwei Fan ◽  
Changliang Zhu ◽  
...  
Keyword(s):  
Stress Responses ◽  
Production Systems ◽  
Strain Improvement ◽  
Value Added ◽  
Product Yield ◽  
Adaptive Laboratory Evolution ◽  
Laboratory Evolution ◽  
Theoretical Support ◽  
Further Development ◽  
Value Added Products

Adaptive laboratory evolution (ALE) has been widely utilized as a tool for developing new biological and phenotypic functions to explore strain improvement for microalgal production. Specifically, ALE has been utilized to evolve strains to better adapt to defined conditions. It has become a new solution to improve the performance of strains in microalgae biotechnology. This review mainly summarizes the key results from recent microalgal ALE studies in industrial production. ALE designed for improving cell growth rate, product yield, environmental tolerance and wastewater treatment is discussed to exploit microalgae in various applications. Further development of ALE is proposed, to provide theoretical support for producing the high value-added products from microalgal production.

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