BACKGROUND: Stochastic models are commonly employed in the system and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. Many important models feature complex dynamics, involving a state-space explosion, stiffness, and multimodality, that complicate the quantitative analysis needed to understand their stochastic behavior. Direct numerical analysis of such models is typically not feasible and generating many simulation runs that adequately approximate the model's dynamics may take a prohibitively long time. RESULTS: We propose a new memoization technique that leverages a population-based abstraction and combines previously generated parts of simulations, called segments, to generate new simulations more efficiently while preserving the original system's dynamics and its diversity. Our algorithm adapts online to identify the most important abstract states and thus utilizes the available memory efficiently. CONCLUSION: We demonstrate that in combination with a novel fully automatic and adaptive hybrid simulation scheme, we can speed up the generation of trajectories significantly and correctly predict the transient behavior of complex stochastic systems.
- Klíčová slova
- Memoization, Population abstraction, Reaction networks, Stochastic simulation,
- MeSH
- algoritmy * MeSH
- biologické modely MeSH
- počítačová simulace * MeSH
- stochastické procesy * MeSH
- syntetická biologie metody MeSH
- Publikační typ
- časopisecké články MeSH
Microalgae are a diverse group of photosynthetic organisms that can be exploited for the production of different compounds, ranging from crude biomass and biofuels to high value-added biochemicals and synthetic proteins. Traditionally, algal biotechnology relies on bioprospecting to identify new highly productive strains and more recently, on forward genetics to further enhance productivity. However, it has become clear that further improvements in algal productivity for biotechnology is impossible without combining traditional tools with the arising molecular genetics toolkit. We review recent advantages in developing high throughput screening methods, preparing genome-wide mutant libraries, and establishing genome editing techniques. We discuss how algae can be improved in terms of photosynthetic efficiency, biofuel and high value-added compound production. Finally, we critically evaluate developments over recent years and explore future potential in the field.
- Klíčová slova
- Algae, Astaxanthin, Biofuel, Carbon concentrating mechanism, Carotenoid, Ethyl methanesulfonate, Genetic engineering, Genome, Mutagenesis, Mutant library, Photosynthesis, Ribulose-1,5-bisphosphate carboxylase/oxygenase, UV irradiation,
- MeSH
- biomasa MeSH
- biopaliva MeSH
- biotechnologie metody MeSH
- mikrořasy * metabolismus MeSH
- syntetická biologie metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
- Názvy látek
- biopaliva MeSH
Methods of artificial evolution such as SELEX and in vitro selection have made it possible to isolate RNA and DNA motifs with a wide range of functions from large random sequence libraries. Once the primary sequence of a functional motif is known, the sequence space around it can be comprehensively explored using a combination of random mutagenesis and selection. However, methods to explore the sequence space of a secondary structure are not as well characterized. Here we address this question by describing a method to construct libraries in a single synthesis which are enriched for sequences with the potential to form a specific secondary structure, such as that of an aptamer, ribozyme, or deoxyribozyme. Although interactions such as base pairs cannot be encoded in a library using conventional DNA synthesizers, it is possible to modulate the probability that two positions will have the potential to pair by biasing the nucleotide composition at these positions. Here we show how to maximize this probability for each of the possible ways to encode a pair (in this study defined as A-U or U-A or C-G or G-C or G.U or U.G). We then use these optimized coding schemes to calculate the number of different variants of model stems and secondary structures expected to occur in a library for a series of structures in which the number of pairs and the extent of conservation of unpaired positions is systematically varied. Our calculations reveal a tradeoff between maximizing the probability of forming a pair and maximizing the number of possible variants of a desired secondary structure that can occur in the library. They also indicate that the optimal coding strategy for a library depends on the complexity of the motif being characterized. Because this approach provides a simple way to generate libraries enriched for sequences with the potential to form a specific secondary structure, we anticipate that it should be useful for the optimization and structural characterization of functional nucleic acid motifs.
- Klíčová slova
- DNA, RNA, SELEX, aptamer, artificial evolution, deoxyribozyme, in vitro selection, nucleic acids, ribozyme, secondary structure, synthetic biology,
- MeSH
- aptamery nukleotidové genetika MeSH
- DNA katalytická genetika MeSH
- genová knihovna * MeSH
- konformace nukleové kyseliny MeSH
- mutageneze MeSH
- nukleotidové motivy genetika MeSH
- obrácené repetice genetika MeSH
- párování bází MeSH
- pravděpodobnost MeSH
- řízená evoluce molekul metody MeSH
- RNA katalytická genetika MeSH
- syntetická biologie metody MeSH
- techniky in vitro MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- aptamery nukleotidové MeSH
- DNA katalytická MeSH
- RNA katalytická MeSH
- MeSH
- antivirové látky farmakologie MeSH
- biopaliva MeSH
- biotechnologie metody MeSH
- CRISPR-Cas systémy MeSH
- editace genu metody MeSH
- kongresy jako téma MeSH
- lidé MeSH
- manipulace s potravinami metody MeSH
- potravinářská mikrobiologie MeSH
- preklinické hodnocení léčiv metody MeSH
- střevní mikroflóra MeSH
- syntetická biologie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- úvodní články MeSH
- úvodníky MeSH
- Názvy látek
- antivirové látky MeSH
- biopaliva MeSH
Microalgae have traditionally been used in many biotechnological applications, where each new application required a different species or strain expressing the required properties; the challenge therefore is to isolate or develop, characterize and optimize species or strains that can express more than one specific property. In agriculture, breeding of natural variants has been successfully used for centuries to improve production traits in many existing plant and animal species. With the discovery of the concepts of classical genetics, these new ideas have been extensively used in selective breeding. However, many biotechnologically relevant algae do not possess the sexual characteristics required for traditional breeding/crossing, although they can be modified by chemical and physical mutagens. The resulting mutants are not considered as genetically modified organisms (GMOs) and their cultivation is therefore not limited by legislation. On the other hand, mutants prepared by random or specific insertion of foreign DNA are considered to be GMOs. This review will compare the effects of two genetic approaches on model algal species and will summarize their advantages in basic research. Furthermore, we will discuss the potential of mutagenesis to improve microalgae as a biotechnological resource, to accelerate the process from specific strain isolation to growth optimization, and discuss the production of new products. Finally, we will explore the potential of algae in synthetic biology.
- Klíčová slova
- Biotechnology, Genetics, Microalgae, Mutagenesis, Reverse genetics, Synthetic biology,
- MeSH
- biotechnologie metody MeSH
- mikrořasy genetika MeSH
- mutageneze MeSH
- reverzní genetika MeSH
- syntetická biologie metody MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
