scholarly journals Engineering Translational Resource Allocation Controllers: Mechanistic Models, Design Guidelines, and Potential Biological Implementations

2018 ◽  
Author(s):  
Alexander P.S. Darlington ◽  
Juhyun Kim ◽  
José I. Jiménez ◽  
Declan G. Bates
Keyword(s):  
Gene Expression ◽  
Resource Allocation ◽  
Rational Design ◽  
Controller Design ◽  
Mechanistic Model ◽  
Design Guidelines ◽  
Negative Effects ◽  
Trade Off ◽  
Resource Limitations ◽  
Synthetic Gene Circuits

AbstractThe use of orthogonal ribosomes in combination with dynamic resource allocation controllers is a promising approach for relieving the negative effects of cellular resource limitations on the modularity of synthetic gene circuits. Here, we develop a detailed mechanistic model of gene expression and resource allocation, which when simplified to a tractable level of complexity, allows the rational design of translational resource allocation controllers. Analysis of this model reveals a fundamental design trade-off; that reducing coupling acts to decrease gene expression. Through a sensitivity analysis of the experimentally tuneable controller parameters, we identify how each controller design parameter affects the overall closed-loop behaviour of the system, leading to a detailed set of design guidelines for optimally managing this trade-off. Based on our designs, we evaluated a number of alternative potential experimental implementations of the proposed system using commonly available biological components. Finally, we show that the controller is capable of dynamically allocating ribosomes as needed to restore modularity in a number of more complex synthetic circuits, such as the repressilator, and activation cascades composed of multiple interacting modules.

scholarly journals Population Design for Synthetic Gene Circuits

2021 ◽  
pp. 181-197
Author(s):  
Baptiste Turpin ◽  
Eline Y. Bijman ◽  
Hans-Michael Kaltenbach ◽  
Jörg Stelling
Keyword(s):  
Computer Aided Design ◽  
Rational Design ◽  
Design Method ◽  
Industrial Applications ◽  
Design Guidelines ◽  
Synthetic Gene Circuits ◽  
Ode Models ◽  
Nonlinear Mixed Effect ◽  
Reliable Performance ◽  
Cell To Cell Variability

AbstractSynthetic biologists use and combine diverse biological parts to build systems such as genetic circuits that perform desirable functions in, for example, biomedical or industrial applications. Computer-aided design methods have been developed to help choose appropriate network structures and biological parts for a given design objective. However, they almost always model the behavior of the network in an average cell, despite pervasive cell-to-cell variability. Here, we present a computational framework to guide the design of synthetic biological circuits while accounting for cell-to-cell variability explicitly. Our design method integrates a NonLinear Mixed-Effect (NLME) framework into an existing algorithm for design based on ordinary differential equation (ODE) models. The analysis of a recently developed transcriptional controller demonstrates first insights into design guidelines when trying to achieve reliable performance under cell-to-cell variability. We anticipate that our method not only facilitates the rational design of synthetic networks under cell-to-cell variability, but also enables novel applications by supporting design objectives that specify the desired behavior of cell populations.

scholarly journals Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources

Life ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 271
Author(s):  
Chentao Yong ◽  
Andras Gyorgy
Keyword(s):  
Cell Fate ◽  
Rational Design ◽  
Resource Competition ◽  
Dynamic Properties ◽  
Mechanistic Model ◽  
Robustness Analysis ◽  
System Level ◽  
Genetic Circuits ◽  
Scarce Resources ◽  
Genetic Systems

While the vision of synthetic biology is to create complex genetic systems in a rational fashion, system-level behaviors are often perplexing due to the context-dependent dynamics of modules. One major source of context-dependence emerges due to the limited availability of shared resources, coupling the behavior of disconnected components. Motivated by the ubiquitous role of toggle switches in genetic circuits ranging from controlling cell fate differentiation to optimizing cellular performance, here we reveal how their fundamental dynamic properties are affected by competition for scarce resources. Combining a mechanistic model with nullcline-based stability analysis and potential landscape-based robustness analysis, we uncover not only the detrimental impacts of resource competition, but also how the unbalancedness of the switch further exacerbates them. While in general both of these factors undermine the performance of the switch (by pushing the dynamics toward monostability and increased sensitivity to noise), we also demonstrate that some of the unwanted effects can be alleviated by strategically optimized resource competition. Our results provide explicit guidelines for the context-aware rational design of toggle switches to mitigate our reliance on lengthy and expensive trial-and-error processes, and can be seamlessly integrated into the computer-aided synthesis of complex genetic systems.

scholarly journals Anisotropic, Wrinkled, and Crack-Bridging Structure for Ultrasensitive, Highly Selective Multidirectional Strain Sensors

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Heng Zhang ◽  
Dan Liu ◽  
Jeng-Hun Lee ◽  
Haomin Chen ◽  
Eunyoung Kim ◽  
...  
Keyword(s):  
Rational Design ◽  
Full Range ◽  
Human Motion ◽  
Strain Sensors ◽  
Gauge Factor ◽  
Wearable Electronics ◽  
Trade Off ◽  
Human Motion Detection ◽  
Sensing Applications ◽  
Anisotropic Structures

AbstractFlexible multidirectional strain sensors are crucial to accurately determining the complex strain states involved in emerging sensing applications. Although considerable efforts have been made to construct anisotropic structures for improved selective sensing capabilities, existing anisotropic sensors suffer from a trade-off between high sensitivity and high stretchability with acceptable linearity. Here, an ultrasensitive, highly selective multidirectional sensor is developed by rational design of functionally different anisotropic layers. The bilayer sensor consists of an aligned carbon nanotube (CNT) array assembled on top of a periodically wrinkled and cracked CNT–graphene oxide film. The transversely aligned CNT layer bridge the underlying longitudinal microcracks to effectively discourage their propagation even when highly stretched, leading to superior sensitivity with a gauge factor of 287.6 across a broad linear working range of up to 100% strain. The wrinkles generated through a pre-straining/releasing routine in the direction transverse to CNT alignment is responsible for exceptional selectivity of 6.3, to the benefit of accurate detection of loading directions by the multidirectional sensor. This work proposes a unique approach to leveraging the inherent merits of two cross-influential anisotropic structures to resolve the trade-off among sensitivity, selectivity, and stretchability, demonstrating promising applications in full-range, multi-axis human motion detection for wearable electronics and smart robotics.

scholarly journals Are Honey Bees at Risk from Microplastics?

Toxics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 109
Author(s):  
Yahya Al Naggar ◽  
Markus Brinkmann ◽  
Christie M. Sayes ◽  
Saad N. AL-Kahtani ◽  
Showket A. Dar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gut Microbiota ◽  
Honey Bees ◽  
Rural Areas ◽  
Aquatic Systems ◽  
Wide Spread ◽  
Negative Effects ◽  
Potential Threat ◽  
Persistent Pollutants ◽  
Research Questions

Microplastics (MPs) are ubiquitous and persistent pollutants, and have been detected in a wide variety of media, from soils to aquatic systems. MPs, consisting primarily of polyethylene, polypropylene, and polyacrylamide polymers, have recently been found in 12% of samples of honey collected in Ecuador. Recently, MPs have also been identified in honey bees collected from apiaries in Copenhagen, Denmark, as well as nearby semiurban and rural areas. Given these documented exposures, assessment of their effects is critical for understanding the risks of MP exposure to honey bees. Exposure to polystyrene (PS)-MPs decreased diversity of the honey bee gut microbiota, followed by changes in gene expression related to oxidative damage, detoxification, and immunity. As a result, the aim of this perspective was to investigate whether wide-spread prevalence of MPs might have unintended negative effects on health and fitness of honey bees, as well as to draw the scientific community’s attention to the possible risks of MPs to the fitness of honey bees. Several research questions must be answered before MPs can be considered a potential threat to bees.

scholarly journals Linking Ligand-Induced Alterations in Androgen Receptor Structure to Differential Gene Expression: A First Step in the Rational Design of Selective Androgen Receptor Modulators

2006 ◽  
Vol 20 (6) ◽  
pp. 1201-1217 ◽  
Author(s):  
Dmitri Kazmin ◽  
Tatiana Prytkova ◽  
C. Edgar Cook ◽  
Russell Wolfinger ◽  
Tzu-Ming Chu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Androgen Receptor ◽  
Rational Design ◽  
Dynamic Structure ◽  
Rational Approach ◽  
Peptide Phage Display ◽  
Differential Gene ◽  
Receptor Modulators ◽  
Kinetics Of

Abstract We have previously identified a family of novel androgen receptor (AR) ligands that, upon binding, enable AR to adopt structures distinct from that observed in the presence of canonical agonists. In this report, we describe the use of these compounds to establish a relationship between AR structure and biological activity with a view to defining a rational approach with which to identify useful selective AR modulators. To this end, we used combinatorial peptide phage display coupled with molecular dynamic structure analysis to identify the surfaces on AR that are exposed specifically in the presence of selected AR ligands. Subsequently, we used a DNA microarray analysis to demonstrate that differently conformed receptors facilitate distinct patterns of gene expression in LNCaP cells. Interestingly, we observed a complete overlap in the identity of genes expressed after treatment with mechanistically distinct AR ligands. However, it was differences in the kinetics of gene regulation that distinguished these compounds. Follow-up studies, in cell-based assays of AR action, confirmed the importance of these alterations in gene expression. Together, these studies demonstrate an important link between AR structure, gene expression, and biological outcome. This relationship provides a firm underpinning for mechanism-based screens aimed at identifying SARMs with useful clinical profiles.

Detection of Synergistic Combinatorial Perturbations by a Bifurcation-Based Approach

2021 ◽  
Vol 31 (12) ◽  
pp. 2150175
Author(s):  
Min Luo ◽  
Dasong Huang ◽  
Jianfeng Jiao ◽  
Ruiqi Wang
Keyword(s):  
Gene Expression ◽  
Rational Design ◽  
Epithelial To Mesenchymal Transition ◽  
Regulation Of Gene Expression ◽  
Drug Combinations ◽  
Bifurcation Curve ◽  
Combinatorial Regulation ◽  
Mesenchymal Transition ◽  
Combinatorial Control ◽  
Two Parameters

Drug combination has become an attractive strategy against complex diseases, despite the challenges in handling a large number of possible combinations among candidate drugs. How to detect effective drug combinations and determine the dosage of each drug in the combination is still a challenging task. When regarding a drug as a perturbation, we propose a bifurcation-based approach to detect synergistic combinatorial perturbations. In the approach, parameters of a dynamical system are divided into two groups according to their responses to perturbations. By combining two parameters chosen from two groups, three types of combinations can be obtained. Synergism for different perturbation combinations can be detected by relative positions of the bifurcation curve and the isobole. The bifurcation-based approach can be used not only to detect combinatorial perturbations but also to determine their perturbation quantities. To demonstrate the effectiveness of the approach, we apply it to the epithelial-to-mesenchymal transition (EMT) network. The approach has implications for the rational design of drug combinations and other combinatorial control, e.g. combinatorial regulation of gene expression.

scholarly journals Best Trade-Off Point Method for Efficient Resource Provisioning in Spark

Algorithms ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 190
Author(s):  
Peter Nghiem
Keyword(s):  
Resource Allocation ◽  
Cluster Computing ◽  
High Energy ◽  
Optimal Number ◽  
Resource Provisioning ◽  
Trade Off ◽  
Energy Efficient Computing ◽  
Hadoop Mapreduce ◽  
Efficient Resource ◽  
Mathematical Formulas

Considering the recent exponential growth in the amount of information processed in Big Data, the high energy consumed by data processing engines in datacenters has become a major issue, underlining the need for efficient resource allocation for more energy-efficient computing. We previously proposed the Best Trade-off Point (BToP) method, which provides a general approach and techniques based on an algorithm with mathematical formulas to find the best trade-off point on an elbow curve of performance vs. resources for efficient resource provisioning in Hadoop MapReduce. The BToP method is expected to work for any application or system which relies on a trade-off elbow curve, non-inverted or inverted, for making good decisions. In this paper, we apply the BToP method to the emerging cluster computing framework, Apache Spark, and show that its performance and energy consumption are better than Spark with its built-in dynamic resource allocation enabled. Our Spark-Bench tests confirm the effectiveness of using the BToP method with Spark to determine the optimal number of executors for any workload in production environments where job profiling for behavioral replication will lead to the most efficient resource provisioning.

scholarly journals Protein Complexes Detection Based on Node Local Properties and Gene Expression On PPI Weighted Networks

2021 ◽  
Author(s):  
Yang Yu ◽  
Dezhou Kong
Keyword(s):  
Gene Expression ◽  
Resource Allocation ◽  
Protein Complex ◽  
Protein Complexes ◽  
Second Order ◽  
Topological Properties ◽  
Ppi Network ◽  
Weighted Networks ◽  
Gene Expression Information ◽  
Local Properties

Abstract Background Identifying protein complexes from protein–protein interaction (PPI) networks is a crucial task, and many related algorithms have been developed to solve this issue. These algorithms usually consider a node’s direct neighbors and ignore resource allocation and second-order neighbors. The effective use of such information is crucial to protein complex detection.Results To overcome this deficiency, this paper proposes a new protein complex identification method based on node-local topological properties and gene expression information on a new weighted PPI network, named NLPGE-WPN (joint node-local topological properties and gene expression information on weighted PPI network). First, based on the resource allocation of the PPI network and gene expression, a new weight metric is designed to describe the interaction between proteins. Second, our method constructs a series of dense complex cores based on density and network diameter constraints; the final complexes are recognized by expanding the second-order neighbor nodes of core complexes. Experimental results demonstrate that this algorithm has improved the performances of precision and f-measure, which is more valid in identifying protein complexes．Conclusions This identification method is simple and can accurately identify more complexes by integrating node-local properties and gene expression on PPI weighted networks.

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