合成生物学及其在生物技术中的应用进展

合成生物学是一门21世纪生物学的新兴学科,它着眼生物科学与工程科学的结合,把生物系统当作工程系统"从下往上"进行处理,由"单元"(unit)到"部件"(device)再到"系统"(system)来设计,修改和组装细胞构件及生物系统.合成生物学是分子和细胞生物学、进化系统学、生物化学、信息学、数学、计算机和工程等多学科交叉的产物.目前研究应用包括两个主要方面:一是通过对现有的、天然存在的生物系统进行重新设计和改造,修改已存在的生物系统,使该系统增添新的功能.二是通过设计和构建新的生物零件、组件和系统,创造自然界中尚不存在的人工生命系统.合成生物学作为一门建立在基因组方法之上的学科,主要强调对创造人工生命形态的计算生物学与实验生物学的协同整合.必须强调的是,用来构建生命系统新结构、产生新功能所使用的组件单元既可以是基因、核酸等生物组件,也可以是化学的、机械的和物理的元件.本文跟踪合成生物学研究及应用,对其在DNA水平编程、分子修饰、代谢途径、调控网络和工业生物技术等方面的进展进行综述.     

Basic Gene Grammars and DNA-ChartParser for language processing of Escherichia coli promoter DNA sequences

MOTIVATION: The field of 'DNA linguistics' has emerged from pioneering work in computational linguistics and molecular biology. Most formal grammars in this field are expressed using Definite Clause Grammars but these have computational limitations which must be overcome. The present study provides a new DNA parsing system, comprising a logic grammar formalism called Basic Gene Grammars and a bidirectional chart parser DNA-ChartParser. RESULTS: The use of Basic Gene Grammars is demonstrated in representing many formulations of the knowledge of Escherichia coli promoters, including knowledge acquired from human experts, consensus sequences, statistics (weight matrices), symbolic learning, and neural network learning. The DNA-ChartParser provides bidirectional parsing facilities for BGGs in handling overlapping categories, gap categories, approximate pattern matching, and constraints. Basic Gene Grammars and the DNA-ChartParser allowed different sources of knowledge for recognizing E.coli promoters to be combined to achieve better accuracy as assessed by parsing these DNA sequences in real-world data sets.     

A syntactic model to design and verify synthetic genetic constructs derived from standard biological parts

MOTIVATION: The sequence of artificial genetic constructs is composed of multiple functional fragments, or genetic parts, involved in different molecular steps of gene expression mechanisms. Biologists have deciphered structural rules that the design of genetic constructs needs to follow in order to ensure a successful completion of the gene expression process, but these rules have not been formalized, making it challenging for non-specialists to benefit from the recent progress in gene synthesis. RESULTS: We show that context-free grammars (CFG) can formalize these design principles. This approach provides a path to organizing libraries of genetic parts according to their biological functions, which correspond to the syntactic categories of the CFG. It also provides a framework for the systematic design of new genetic constructs consistent with the design principles expressed in the CFG. Using parsing algorithms, this syntactic model enables the verification of existing constructs. We illustrate these possibilities by describing a CFG that generates the most common architectures of genetic constructs in Escherichia coli. AVAILABILITY: A web site allows readers to experiment with the algorithms presented in this article: www.genocad.org. SUPPLEMENTARY INFORMATION: Sequences and models are available at Bioinformatics online.     

基因组工程在医学合成生物学中的应用

合成生物学旨在建立一套完整的工程理论和方法,通过设计和组装基本生物学元件,更为有效地实现复杂生物系统的设计,并使其完成可编程的生物学功能。近年来随着可编程基因组元件的出现,特别是CRISPR和CRISPRi技术平台的建立和完善,使得合成生物学进入了一个全新发展的时期。本文重点综述CRISPR等基因组编辑和调控技术,其在构建可编程生物学元件和复杂基因线路的应用以及合成生物学在医学中(称为医学合成生物学)的发展前景。     

Molecular characterization of a spontaneously generated new allele at a VNTR locus: no exchange of flanking DNA sequence

Variable-number tandem-repeat (VNTR) DNA markers are contributing new power to human genetic studies because their hypervariable nature allows individualization at the DNA level. The practical value of VNTR markers has been well established for genetic linkage mapping, forensic biology, paternity testing, and monitoring of bone marrow transplants. A popular hypothesis attributes generation of variability at VNTR loci to unequal exchange between homologous chromosomes at meiosis. Contrary to the prediction of this hypothesis, we report here the finding that a newly generated VNTR allele is parental for closely spaced flanking markers; the new allele was generated by loss of one repeat unit, without exchange of flanking DNA sequences. These results are consistent with sister chromatid exchange and polymerase slippage or deletion, as well as with some models for gene conversion.     

Computational methods in synthetic biology

We discuss how a theoretical synthetic biology research programme may liberate empiricism in biological sciences beyond the unaided human brain. Because synthetic biological systems are relatively small and largely independent of evolutionary contexts, they can be represented with mathematical models strongly founded on first principles of molecular biology and laws of statistical thermodynamics. A universal mathematical formalism for describing synthetic constructs may then be plausibly used to explain in unambiguous, quantitative terms how biological phenotypic complexity emerges as a result of well-defined biomolecular interactions. SynBioSS, a publicly available software package, is described that implements this mathematical formalism.     

Computer models of auxin transport: a review and commentary

With the recent proliferation of computer models of auxin transport, it is important that plant biologists understand something about these techniques and how to evaluate them. The paper begins with a brief introduction to the parts of a computer model, followed by a discussion of the limitations of the most common auxin modelling technique. Lastly, several recent models of organ initiation in the shoot apical meristem (i.e. phyllotaxis) are reviewed. The cell and molecular biology of phyllotaxis is now understood well enough that computer models can go beyond a simple 'proof of principle' and start to provide insights into gene function.     

果蝇中顺式调控序列的进化

顺式调控序列(cis-regularory sequences)是与基因表达调控相关、能够被调控因子特异性识别和结合的非编码DNA序列。顺式调控序列可以通过增减所含转录因子结合位点的数目,重构转录调控网络,以精准调控基因的时空表达模式,从而调控动物的生理和形态表型。顺式调控假说认为顺式调控序列进化是自然界丰富的动物表型进化的主要遗传机制。本文首先简述了顺式调控序列的结构和功能,然后重点讨论了近年来顺式调控序列进化调控果蝇表型进化如刚毛表型进化、色素沉积表型进化和胚胎发育方面的研究进展,阐释了顺式调控序列进化是动物表型进化的主要遗传机制之一。最后本文展望了顺式调控序列未来研究方向,例如应用功能基因组研究、开展ENCODE计划等,为进化发育生物学中顺式调控序列的研究提供了参考。     

群体遗传结构中的基因流

群体遗传结构上的差异是遗传多样性的一种重要体现,对群体遗传结构的研究已有较久的历史,而其中的基因流研究近些年来越来越受到重视。它对群体遗传学、进化生物学、保护生物学、生态学有着极其重要的作用。虽然传统的群体遗传学能估测基因流大小,但它的精确性还有很大局限性。随着生物技术的进步,对基因流的研究逐渐向分子水平过渡,应用蛋白质电泳技术、分子标记技术(RAPD、RFLP、VNTR、ISSR、DNA测序等)方法对群体间基因流的流动水平进行了深入细致的研究。通过综述群体遗传结构的几种模式:陆岛模式、海岛模式、阶石模式、距离隔离模式、层次模式,以及在群体遗传结构的几种模式基础上的基因流的研究方法、作用、地位和近些年来研究者的研究成果,并指出了这些方法的局限性。     

Pair hidden Markov models on tree structures

MOTIVATION: Computationally identifying non-coding RNA regions on the genome has much scope for investigation and is essentially harder than gene-finding problems for protein-coding regions. Since comparative sequence analysis is effective for non-coding RNA detection, efficient computational methods are expected for structural alignments of RNA sequences. On the other hand, Hidden Markov Models (HMMs) have played important roles for modeling and analysing biological sequences. Especially, the concept of Pair HMMs (PHMMs) have been examined extensively as mathematical models for alignments and gene finding. RESULTS: We propose the pair HMMs on tree structures (PHMMTSs), which is an extension of PHMMs defined on alignments of trees and provides a unifying framework and an automata-theoretic model for alignments of trees, structural alignments and pair stochastic context-free grammars. By structural alignment, we mean a pairwise alignment to align an unfolded RNA sequence into an RNA sequence of known secondary structure. First, we extend the notion of PHMMs defined on alignments of 'linear' sequences to pair stochastic tree automata, called PHMMTSs, defined on alignments of 'trees'. The PHMMTSs provide various types of alignments of trees such as affine-gap alignments of trees and an automata-theoretic model for alignment of trees. Second, based on the observation that a secondary structure of RNA can be represented by a tree, we apply PHMMTSs to the problem of structural alignments of RNAs. We modify PHMMTSs so that it takes as input a pair of a 'linear' sequence and a 'tree' representing a secondary structure of RNA to produce a structural alignment. Further, the PHMMTSs with input of a pair of two linear sequences is mathematically equal to the pair stochastic context-free grammars. We demonstrate some computational experiments to show the effectiveness of our method for structural alignments, and discuss a complexity issue of PHMMTSs.     

Potentials of single‐cell biology in identification and validation of disease biomarkers

Single‐cell biology is considered a new approach to identify and validate disease‐specific biomarkers. However, the concern raised by clinicians is how to apply single‐cell measurements for clinical practice, translate the message of single‐cell systems biology into clinical phenotype or explain alterations of single‐cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single‐cell gene sequencing in the identification and development of disease‐specific biomarkers, the definition and significance of single‐cell biology and single‐cell systems biology in the understanding of single‐cell full picture, the development and establishment of whole‐cell models in the validation of targeted biological function and the figure and meaning of single‐molecule imaging in single cell to trace intra‐single‐cell molecule expression, signal, interaction and location. We headline the important role of single‐cell biology in the discovery and development of disease‐specific biomarkers with a special emphasis on understanding single‐cell biological functions, e.g. mechanical phenotypes, single‐cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi‐dimensional, multi‐layer, multi‐crossing and stereoscopic single‐cell biology definitely benefits the discovery and development of disease‐specific biomarkers.     

TinkerCell: modular CAD tool for synthetic biology

Background

Synthetic biology brings together concepts and techniques from engineering and biology. In this field, computer-aided design (CAD) is necessary in order to bridge the gap between computational modeling and biological data. Using a CAD application, it would be possible to construct models using available biological "parts" and directly generate the DNA sequence that represents the model, thus increasing the efficiency of design and construction of synthetic networks.

Results

An application named TinkerCell has been developed in order to serve as a CAD tool for synthetic biology. TinkerCell is a visual modeling tool that supports a hierarchy of biological parts. Each part in this hierarchy consists of a set of attributes that define the part, such as sequence or rate constants. Models that are constructed using these parts can be analyzed using various third-party C and Python programs that are hosted by TinkerCell via an extensive C and Python application programming interface (API). TinkerCell supports the notion of a module, which are networks with interfaces. Such modules can be connected to each other, forming larger modular networks. TinkerCell is a free and open-source project under the Berkeley Software Distribution license. Downloads, documentation, and tutorials are available at http://www.tinkercell.com.

Conclusion

An ideal CAD application for engineering biological systems would provide features such as: building and simulating networks, analyzing robustness of networks, and searching databases for components that meet the design criteria. At the current state of synthetic biology, there are no established methods for measuring robustness or identifying components that fit a design. The same is true for databases of biological parts. TinkerCell's flexible modeling framework allows it to cope with changes in the field. Such changes may involve the way parts are characterized or the way synthetic networks are modeled and analyzed computationally. TinkerCell can readily accept third-party algorithms, allowing it to serve as a platform for testing different methods relevant to synthetic biology.     

Synthetic biology: new strategies for directing design

The advancement of synthetic biology is thanks, in large part, to continuing improvements in DNA synthesis. The expansion of synthetic biology into the realm of metabolic engineering has shifted the focus from simply making novel synthetic biological parts to answering the question of how we employ these biological parts to construct genomes that ultimately give rise to useful phenotypes. Much like protein engineering, the answer to this will be arrived at following the combination of rational design and evolutionary approaches. This review will highlight some of the new DNA synthesis-enabled search methods and discuss the application of such methods to the creation of synthetic gene networks and genomes.     

Efficient genetic markers for population biology

Population genetics has come of age. Three important components have come together: efficient techniques to examine informative segments of DNA, statistics to analyse DNA data and the availability of easy-to-use computer packages. Single-locus genetic markers and those that produce gene genealogies yield information that is truly comparable among studies. These markers answer biological questions most efficiently and also contribute to much broader investigations of evolutionary, population and conservation biology. For these reasons, single-locus and genealogical markers should be the focus of the intensive genetic data collection that has begun owing to the power of genetics in population biology.     

Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift

Scientists studying how languages change over time often make an analogy between biological and cultural evolution, with words or grammars behaving like traits subject to natural selection. Recent work has exploited this analogy by using models of biological evolution to explain the properties of languages and other cultural artefacts. However, the mechanisms of biological and cultural evolution are very different: biological traits are passed between generations by genes, while languages and concepts are transmitted through learning. Here we show that these different mechanisms can have the same results, demonstrating that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright–Fisher model of genetic drift. This simple learning mechanism thus provides a justification for the use of models of genetic drift in studying language evolution. In addition to providing an explicit connection between biological and cultural evolution, this allows us to define a ‘neutral’ model that indicates how languages can change in the absence of selection at the level of linguistic variants. We demonstrate that this neutral model can account for three phenomena: the s-shaped curve of language change, the distribution of word frequencies, and the relationship between word frequencies and extinction rates.     

An approximate matching algorithm for finding (sub-)optimal sequences in S-attributed grammars

MOTIVATION: S-attributed grammars (a generalization of classical Context-Free grammars) provide a versatile formalism for sequence analysis which allows to express long range constraints: the RNA folding problem is a typical example of application. Efficient algorithms have been developed to solve problems expressed with these tools, which generally compute the optimal attribute of the sequence w.r.t. the grammar. However, it is often more meaningful and/or interesting from the biological point of view to consider almost optimal attributes as well as approximate sequences; we thus need more flexible and powerful algorithms able to perform these generalized analyses. RESULTS: In this paper we present a basic algorithm which, given a grammar G and a sequence omega, computes the optimal attribute for all (approximate) strings omega(') in L(G) such that d(omega, omega(')) < or = M, and whose complexity is O(n(r + 1)) in time and O(n(2)) in space (r is the maximal length of the right-hand side of any production of G). We will also give some extensions and possible improvements of this algorithm.     

Restricting restriction

Systems biology is a new, fashionable and well-funded discipline, which to quote from a recent review aims to 'examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism em leader ' (Kitano, H. (2002) Science 295:1662-1664). Systems biology will do this by profiting from the vast amounts of biological information that are available in the genomics era and make extensive use of computer modelling. But: 'many breakthroughs in experimental devices, advanced software and analytical methods are required before the achievements of system biology can live up to their much-touted potential'. This edition of Molecular Microbiology contains a paper that is the product of traditional experimental biology but which could serve as a test case for systems biology. The paper shows how bacteria integrate such disparate subsystems as DNA restriction, homologous recombination and regulated proteolysis to protect their chromosomes from degradation. When systems biology can predict this level of choreography, it will be a mature discipline.     

Allelic variants of hereditary prions: The bimodularity principle

Modern biology requires modern genetic concepts equally valid for all discovered mechanisms of inheritance, either “canonical” (mediated by DNA sequences) or epigenetic. Applying basic genetic terms such as “gene” and “allele” to protein hereditary factors is one of the necessary steps toward these concepts. The basic idea that different variants of the same prion protein can be considered as alleles has been previously proposed by Chernoff and Tuite. In this paper, the notion of prion allele is further developed. We propose the idea that any prion allele is a bimodular hereditary system that depends on a certain DNA sequence (DNA determinant) and a certain epigenetic mark (epigenetic determinant). Alteration of any of these 2 determinants may lead to establishment of a new prion allele. The bimodularity principle is valid not only for hereditary prions; it seems to be universal for any epigenetic hereditary factor.