Bio-logic: gene expression and the laws of combinatorial logic

Original article can be found at: http://www.mitpressjournals.org/ Copyright MIT Press DOI: 10.1162/artl.2008.14.1.121At the heart of the development of fertilized eggs into fully formed organisms and the adaptation of cells to changed conditions are genetic regulatory networks (GRNs). In higher multi-cellular organisms, signal selection and multiplexing is performed at the cis-regulatory domains of genes, where combinations of transcription factors (TFs) regulate the rates at which the genes are transcribed into mRNA. To be able to act as activators or repressors of gene transcription, TFs must first bind to target sequences on the regulatory domains. Two TFs that act in concert may bind entirely independently of each other, but more often binding of the first one will alter the affinity of the other for its binding site. This paper presents a systematic investigation into the effect of TF binding dependencies on the predicted regulatory function of this “bio-logic”. Four extreme scenarios, commonly used to classify enzyme activation and inhibition patterns, for the binding of two TFs were explored: independent (the TFs bind without affecting each other’s affinities), competitive (the TFs compete for the same binding site), ordered (the TFs bind in a compulsory order), and joint binding (the TFs either bind as a preformed complex, or binding of one is virtually impossible in the absence of the other). The conclusions are: 1) the laws of combinatorial logic hold only for systems with independently binding TFs; 2) systems formed according to the other scenarios can mimic the functions of their Boolean logical counterparts, but cannot be combined or decomposed in the same way; and 3) the continuously scaled output of systems consisting of competitively binding activators and repressors can be more robustly controlled than that of single TF or (quasi-) logical multi-TF systems. Keywords: Transcription regulation, Genetic regulatory networks, Enzyme kinetics, Combinatorial logic, Non-Boolean continuous logic, Modelling.Peer reviewe

Making serine integrases work for us

DNA site-specific recombinases are enzymes (often associated with mobile DNA elements) that catalyse breaking and rejoining of DNA strands at specific points, thereby bringing about precise genetic rearrangements. Serine integrases are a group of recombinases derived from bacteriophages. Their unusual properties, including directionality of recombination and simple site requirements, are leading to their development as efficient, versatile tools for applications in experimental biology, biotechnology, synthetic biology and gene therapy. This article summarizes our current knowledge of serine integrase structure and mechanism, then outlines key factors that affect the performance of these phage recombination systems. Recently published studies, that have expanded the repertoire of available systems and reveal system-specific characteristics, will help us to choose the best integrases for envisaged applications

The impact of synthetic biology in chemical engineering - Educational issues

This paper describes the development of syntheticbiology as a distinct entity from current industrial biotechnology and the implications for a future based on its concepts. The role of the engineering design cycle, in syntheticbiology is established and the difficulties in making and exact analogy between the two emphasised. It is suggested that process engineers can offer experience in the application of syntheticbiology to the manufacture of products which should influence the approach of the synthetic biologist. The style of teaching for syntheticbiology appears to offer a new approach at undergraduate level and the challenges to the education of process engineers in this technology are raised. Possible routes to the development of syntheticbiology teaching are suggested

GUBS, a Behavior-based Language for Open System Dedicated to Synthetic Biology

In this article, we propose a domain specific language, GUBS (Genomic Unified Behavior Specification), dedicated to the behavioral specification of synthetic biological devices, viewed as discrete open dynamical systems. GUBS is a rule-based declarative language. By contrast to a closed system, a program is always a partial description of the behavior of the system. The semantics of the language accounts the existence of some hidden non-specified actions possibly altering the behavior of the programmed device. The compilation framework follows a scheme similar to automatic theorem proving, aiming at improving synthetic biological design safety.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347

The Group Structure of Pivot and Loop Complementation on Graphs and Set Systems

We study the interplay between principal pivot transform (pivot) and loop complementation for graphs. This is done by generalizing loop complementation (in addition to pivot) to set systems. We show that the operations together, when restricted to single vertices, form the permutation group S_3. This leads, e.g., to a normal form for sequences of pivots and loop complementation on graphs. The results have consequences for the operations of local complementation and edge complementation on simple graphs: an alternative proof of a classic result involving local and edge complementation is obtained, and the effect of sequences of local complementations on simple graphs is characterized.Comment: 21 pages, 7 figures, significant additions w.r.t. v3 are Thm 7 and Remark 2

Is defining life pointless? Operational definitions at the frontiers of Biology

Despite numerous and increasing attempts to define what life is, there is no consensus on necessary and sufficient conditions for life. Accordingly, some scholars have questioned the value of definitions of life and encouraged scientists and philosophers alike to discard the project. As an alternative to this pessimistic conclusion, we argue that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices. This paper examines the possible contributions of definitions of life in scientific domains where such definitions are used most (e.g., Synthetic Biology, Origins of Life, Alife, and Astrobiology). Rather than as classificatory tools for demarcation of natural kinds, we highlight the pragmatic utility of what we call operational definitions that serve as theoretical and epistemic tools in scientific practice. In particular, we examine contexts where definitions integrate criteria for life into theoretical models that involve or enable observable operations. We show how these definitions of life play important roles in influencing research agendas and evaluating results, and we argue that to discard the project of defining life is neither sufficiently motivated, nor possible without dismissing important theoretical and practical research

"Going back to our roots": second generation biocomputing

Researchers in the field of biocomputing have, for many years, successfully "harvested and exploited" the natural world for inspiration in developing systems that are robust, adaptable and capable of generating novel and even "creative" solutions to human-defined problems. However, in this position paper we argue that the time has now come for a reassessment of how we exploit biology to generate new computational systems. Previous solutions (the "first generation" of biocomputing techniques), whilst reasonably effective, are crude analogues of actual biological systems. We believe that a new, inherently inter-disciplinary approach is needed for the development of the emerging "second generation" of bio-inspired methods. This new modus operandi will require much closer interaction between the engineering and life sciences communities, as well as a bidirectional flow of concepts, applications and expertise. We support our argument by examining, in this new light, three existing areas of biocomputing (genetic programming, artificial immune systems and evolvable hardware), as well as an emerging area (natural genetic engineering) which may provide useful pointers as to the way forward.Comment: Submitted to the International Journal of Unconventional Computin

Aggregate assembly process planning for concurrent engineering

In today's consumer and economic climate, manufacturers are finding it increasingly difficult to produce finished products with increased functionality whilst fulfilling the aesthetic requirements of the consumer. To remain competitive, manufacturers must always look for ways to meet the faster, better, and cheaper mantra of today's economy. The ability for any industry to mirror the ideal world, where the design, manufacturing, and assembly process of a product would be perfected before it is put mto production, will undoubtedly save a great deal of time and money. This thesis introduces the concept of aggregate assembly process planning for the conceptual stages of design, with the aim of providing the methodology behind such an environment. The methodology is based on an aggregate product model and a connectivity model. Together, they encompass all the requirements needed to fully describe a product in terms of its assembly processes, providing a suitable means for generating assembly sequences. Two general-purpose heuristics methods namely, simulated annealing and genetic algorithms are used for the optimisation of assembly sequences generated, and the loading of the optimal assembly sequences on to workstations, generating an optimal assembly process plan for any given product. The main novelty of this work is in the mapping of the optimisation methods to the issue of assembly sequence generation and line balancing. This includes the formulation of the objective functions for optimismg assembly sequences and resource loading. Also novel to this work is the derivation of standard part assembly methodologies, used to establish and estimate functional tunes for standard assembly operations. The method is demonstrated using CAPABLEAssembly; a suite of interlinked modules that generates a pool of optimised assembly process plans using the concepts above. A total of nine industrial products have been modelled, four of which are the conceptual product models. The process plans generated to date have been tested on industrial assembly lines and in some cases yield an increase in the production rate