Biology using engineering tools

Negative feedback is an ubiquitous feature of biological networks. Recent work from Sturm and colleaguespresents experimental evidence that biological negative feedback can serve the same function as it does for engineered systems: robustness to perturbations within the feedback loop. Such behavior has important implications for how to attack deregulated signaling networks containing negative feedback in diseases such as cancer.     

Biology inspires engineering

A report of the Cold Spring Harbor Laboratory/Wellcome Trust Meeting on Engineering Principles in Biology, Cambridge, UK, 14-16 October 2009.     

Site-specific recombinases: tools for genome engineering

Site-specific recombinases from bacteriophage and yeasts have been developed as novel tools for manipulating DNA both in the test-tube and in living organisms. We discuss the characteristics of these enzyme systems, review their application in genetic and developmental studies and speculate on their future potential for large-scale directed modifications of eukaryotic genomes.     

Yeast polarity: negative feedback shifts the focus

A new study of Cdc42p polarization in yeast suggests that the actin cytoskeleton can destabilize the polarity axis, causing Cdc42p foci to wander aimlessly around the cell cortex.     

Chromosome engineering: power tools for plant genetics

The term "chromosome engineering" describes technologies in which chromosomes are manipulated to change their mode of genetic inheritance. This review examines recent innovations in chromosome engineering that promise to greatly increase the efficiency of plant breeding. Haploid Arabidopsis thaliana have been produced by altering the kinetochore protein CENH3, yielding instant homozygous lines. Haploid production will facilitate reverse breeding, a method that downregulates recombination to ensure progeny contain intact parental chromosomes. Another chromosome engineering success is the conversion of meiosis into mitosis, which produces diploid gametes that are clones of the parent plant. This is a key step in apomixis (asexual reproduction through seeds) and could help to preserve hybrid vigor in the future. New homologous recombination methods in plants will potentiate many chromosome engineering applications.     

Regulation of release factor expression using a translational negative feedback loop: A systems analysis

The essential eukaryote release factor eRF1, encoded by the yeast SUP45 gene, recognizes stop codons during ribosomal translation. SUP45 nonsense alleles are, however, viable due to the establishment of feedback-regulated readthrough of the premature termination codon; reductions in full-length eRF1 promote tRNA-mediated stop codon readthrough, which, in turn, drives partial production of full-length eRF1. A deterministic mathematical model of this eRF1 feedback loop was developed using a staged increase in model complexity. Model predictions matched the experimental observation that strains carrying the mutant SUQ5 tRNA (a weak UAA suppressor) in combination with any of the tested sup45^UAA nonsense alleles exhibit threefold more stop codon readthrough than that of an SUQ5 yeast strain. The model also successfully predicted that eRF1 feedback control in an SUQ5 sup45^UAA mutant would resist, but not completely prevent, imposed changes in eRF1 expression. In these experiments, the introduction of a plasmid-borne SUQ5 copy into a sup45^UAASUQ5 mutant directed additional readthrough and full-length eRF1 expression, despite feedback. Secondly, induction of additional sup45^UAA mRNA expression in a sup45^UAASUQ5 strain also directed increased full-length eRF1 expression. The autogenous sup45 control mechanism therefore acts not to precisely control eRF1 expression, but rather as a damping mechanism that only partially resists changes in release factor expression level. The validated model predicts that the degree of feedback damping (i.e., control precision) is proportional to eRF1 affinity for the premature stop codon. The validated model represents an important tool to analyze this and other translational negative feedback loops.     

Computational tools for metabolic engineering

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area.     

Enabling tools for tissue engineering

Tissue engineering is a multidisciplinary field that combines engineering, physical sciences, biology, and medicine to restore or replace tissues and organs functions. In this review, enabling tools for tissue engineering are discussed in the context of four key areas or pillars: prediction, production, performance, and preservation. Prediction refers to the computational modeling where the ability to simulate cellular behavior in complex three-dimensional environments will be essential for design of tissues. Production refer imaging modalities that allow high resolution, non-invasive monitoring of the development and incorporation of tissue engineered constructs. Lastly, preservation includes biochemical tools that permit cryopreservation, vitrification, and freeze-drying of cells and tissues. Recent progress and future perspectives for development in each of these key areas are presented.     

Homeostatic signaling: the positive side of negative feedback

Synaptic homeostasis provides a means for neurons and circuits to maintain stable function in the face of perturbations such as developmental or activity-dependent changes in synapse number or strength. These forms of plasticity are thought to utilize negative feedback signaling to sense some aspect of activity, compare this with an internal set point, and then adjust synaptic properties to keep activity close to this set point. However, the molecular identity of these signaling components has not been firmly established. Recent work suggests that there are likely to be multiple forms of synaptic homeostasis, mediated by distinct signaling pathways and with distinct expression mechanisms. These include presynaptic forms that depend on retrograde signaling to presynaptic Ca(2+) channels, and postsynaptic forms influenced by BDNF, TNFalpha and Arc signaling. Current challenges include matching signaling elements to their functions (i.e. as detectors of activity, as part of the set-point mechanism and/or as effectors of synaptic change), and fitting these molecular candidates into a unified view of the signaling pathways that underlie synaptic homeostasis.     

Modeling and simulation: tools for metabolic engineering.

Mathematical modeling is one of the key methodologies of metabolic engineering. Based on a given metabolic model different computational tools for the simulation, data evaluation, systems analysis, prediction, design and optimization of metabolic systems have been developed. The currently used metabolic modeling approaches can be subdivided into structural models, stoichiometric models, carbon flux models, stationary and nonstationary mechanistic models and models with gene regulation. However, the power of a model strongly depends on its basic modeling assumptions, the simplifications made and the data sources used. Model validation turns out to be particularly difficult for metabolic systems. The different modeling approaches are critically reviewed with respect to their potential and benefits for the metabolic engineering cycle. Several tools that have emerged from the different modeling approaches including structural pathway synthesis, stoichiometric pathway analysis, metabolic flux analysis, metabolic control analysis, optimization of regulatory architectures and the evaluation of rapid sampling experiments are discussed.     

Chaos in multi-looped negative feedback systems

Non-linear control systems with multiple negative feedback loops display periodicity, quasiperiodicity and period-doubling bifurcations leading to chaos. The possibility that normal fluctuations in physiological control may result from deterministic chaos in multi-looped negative feedback systems is discussed.     

Synthetic regulatory tools for microbial engineering

Microbial engineering requires accurate information about cellular metabolic networks and a set of molecular tools that can be predictably applied to the efficient redesign of such networks. Recent advances in the field of metabolic engineering and synthetic biology, particularly the development of molecular tools for synthetic regulation in the static and dynamic control of gene expression, have increased our ability to efficiently balance the expression of genes in various biological systems. It would accelerate the creation of synthetic pathways and genetic programs capable of adapting to environmental changes in real time to perform the programmed cellular behavior. In this paper, we review current developments in the field of synthetic regulatory tools for static and dynamic control of microbial gene expression.     

BioModel engineering for multiscale Systems Biology

We discuss some motivational challenges arising from the need to model and analyse complex biological systems at multiple scales (spatial and temporal), and present a biomodel engineering framework to address some of these issues within the context of multiscale Systems Biology. Our methodology is based on a structured family of Petri net classes which enables the investigation of a given system using various modelling abstractions: qualitative, stochastic, continuous and hybrid, optionally in a spatial context. We illustrate our approach with case studies demonstrating hierarchical flattening, treatment of space, and hierarchical organisation of space.     

The p38 pathway provides negative feedback for Ras proliferative signaling

Ras activates three mitogen-activated protein kinases (MAPKs) including ERK, JNK, and p38. Whereas the essential roles of ERK and JNK in Ras signaling has been established, the contribution of p38 remains unclear. Here we demonstrate that the p38 pathway functions as a negative regulator of Ras proliferative signaling via a feedback mechanism. Oncogenic Ras activated p38 and two p38-activated protein kinases, MAPK-activated protein kinase 2 (MK2) and p38-related/activated protein kinase (PRAK). MK2 and PRAK in turn suppressed Ras-induced gene expression and cell proliferation, whereas two mutant PRAKs, unresponsive to Ras, had little effect. Moreover, the constitutive p38 activator MKK6 also suppressed Ras activity in a p38-dependent manner whereas arsenite, a potent chemical inducer of p38, inhibited proliferation only in a tumor cell line that required Ras activity. MEK was required for Ras stimulation of the p38 pathway. The p38 pathway inhibited Ras activity by blocking activation of JNK, without effect upon ERK, as evidenced by the fact that PRAK-mediated suppression of Ras-induced cell proliferation was reversed by coexpression of JNKK2 or JNK1. These studies thus establish a negative feedback mechanism by which Ras proliferative activity is regulated via signaling integrations of MAPK pathways.     

Next generation simulation tools: the Systems Biology Workbench and BioSPICE integration

Researchers in quantitative systems biology make use of a large number of different software packages for modelling, analysis, visualization, and general data manipulation. In this paper, we describe the Systems Biology Workbench (SBW), a software framework that allows heterogeneous application components--written in diverse programming languages and running on different platforms--to communicate and use each others' capabilities via a fast binary encoded-message system. Our goal was to create a simple, high performance, opensource software infrastructure which is easy to implement and understand. SBW enables applications (potentially running on separate, distributed computers) to communicate via a simple network protocol. The interfaces to the system are encapsulated in client-side libraries that we provide for different programming languages. We describe in this paper the SBW architecture, a selection of current modules, including Jarnac, JDesigner, and SBWMeta-tool, and the close integration of SBW into BioSPICE, which enables both frameworks to share tools and compliment and strengthen each others capabilities.