Property:Abstract
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C
Converting Smooth, Time-Varying, Asymptotic Stabilizers for Driftless Systems to Homogeneous, Exponential Stabilizers +
The main result of this paper is a theorem that allows smooth,
time-varying controllers which asymptotically stabilize a driftless
nonlinear system to be converted to homogeneous, time-varying
controllers which provide {\em exponential} stability. The resulting
controllers are smooth everywhere except the origin and are easily
computed given the original asymptotic stabilizer. We illustrate the
result with experimental results on a simple mobile robot. +
I
The malachite green aptamer (MGapt) is known for its utility in RNA measurement in vivo and lysate-based cell-free protein systems. However, MGapt fluorescence dynamics do not accurately reflect mRNA concentration. Our study finds that MGapt fluorescence is unstable in commercial PURE systems. We discovered that the chemical composition of the cell-free reaction strongly influences MGapt fluorescence, which leads to inaccurate RNA calculations. Specific to the commercial system, we posit that MGapt fluorescence is significantly affected by the system’s chemical properties, governed notably by the presence of dithiothreitol (DTT). We propose a model that, on average, accurately predicts MGapt measurement within a 10% margin, leveraging DTT concentration as a critical factor. This model sheds light on the complex dynamics of MGapt in cell-free systems and underscores the importance of considering environmental factors in RNA measurements using aptamers. +
E
The mammalian gut contains trillions of microbes that interact with host cells and monitor changes in the environment. Opportunistic pathogens exploit environmental conditions to stimulate their growth and virulence, leading to a resurgence of chronic disorders such as inflammatory bowel disease (IBD). Current therapies are effective in less than 30% of patients due to the lack of adherence to prescription schedules and overall, off-target effects. Smart microbial therapeutics can be engineered to colonize the gut, providing in situ surveillance and conditional disease modulation. However, many current engineered microbes can only respond to single gut environmental factors, limiting their effectiveness. In this work, we implement the previously characterized split activator AND logic gate in the probiotic E. coli strain Nissle 1917. Our system can respond to two input signals: the inflammatory biomarker tetrathionate and a second input signal, IPTG. We report 4-6 fold induction with minimal leak when both signals are present. We model the dynamics of the AND gate using chemical reaction networks, and by tuning parameters in silico, we identified perturbations that affect our circuit's selectivity. We anticipate that our results will prove useful for designing living therapeutics for spatial targeting and signal processing in complex environments. +
R
The many successes of synthetic biology have come in a manner largely different from those in other en- gineering disciplines; in particular, without well-characterized and simplified prototyping environments to play a role analogous to wind-tunnels in aerodynamics and breadboards in electrical engineering. However, as the complexity of synthetic circuits increases, the benefitsÂin cost savings and design cycle time of a more traditional engineering approach can be significant. We have recently developed an in vitro Âbreadboard prototyping platform based on E. coli cell extract that allows biocircuits to operate in an environment considerably simpler than but functionally similar to in vivo. The simplicity of the cell-free transcription-translation breadboard makes it a promising tool for rapid biocircuit design and testing, as well as for probing the fundamentals of gene circuit functions that are normally masked by cellular complex- ity. In this work we characterize the cell-free breadboard using real-time and simultaneous measurements of transcriptional and translational activities of a small set of reporter genes and a transcriptional activation cascade. We determine the effects of promoter strength, gene and nucleoside triphosphate concentrations on biocircuits properties, and we isolate contributions of the essential componentsÂcore RNA polymerase, housekeeping sigma factor, and ribosomesÂto overall performance. Importantly, we show how limits on essential resources, particularly those involved in translation steps, manifest themselves in the form of reduced expression in the presence of orthogonal genes as load processes. +
E
Experimental Demonstration of the Dynamics and Stability of a Low Reynolds Number Swimmer Near a Plane Wall +
The motion of microorganisms as well as of tiny robotic swimmers for biomedical applications is governed by low Reynolds number (Re) hydrodynamics, where viscous effects dominate and inertial effects are negligible. This paper presents experimental results that verify theoretical predictions of our recent work which analyzed the dynamics and stability of a low-Re swimmer near a plane wall. The experimental setup uses macro-scale swimmer prototypes which are propelled by rotating cylinders in highly viscous silicone oil. The motion was recorded by a video camera and position measurements were taken by an optical tracking system. The results show good qualitative agreement with our recent theoretical predictions. +
S
The objective of this work is to study the benefits that delay can provide in simplifying the control process of large-scale systems, motivated by the availability of different types of delays in man-made and biological systems. We show that a continuous-time linear time-invariant (LTI) controller can be approximated by a simple controller that mainly uses delay blocks instead of integrators. More specifically, three methods are proposed to approximate a pre-designed stabilizing LTI controller arbitrarily precisely by a simple delay-based controller composed of delay blocks, a few integrators and possibly a unity feedback. Different problems associated with the developed approximation procedures, such as finding the optimal number of delay blocks or studying the robustness of the designed controller with respect to delay values, are then addressed. +
O
The observability properties of a class of hybrid
systems whose continuous variables are available for measurement
are considered. We show that the discrete variables'
dynamics can be always extended for observable systems to
a lattice in such a way that the extended system has the
properties that allow the construction of the LU discrete
state estimator. Such an estimator updates two variables at
each step, namely the upper and lower bound of the set
of all possible discrete variables' values compatible with the
output sequence. We give an estimate of the complexity of the
estimator in the worst case. +
I
Implementation And Simulation Of Phosphorylation-Based Insulator In Transcription-Translation Platform +
The operational amplifier (OPAMP) is a very useful insulation module in electric circuits to avoid loading effect (retroactivity). In synthetic biological circuits, we also have the same retroactivity problem, in which the biomolecular systems are not always modular due to downstream components. The output of the upstream component will be affected as the downstream component sequesters that output, which in turn impedes the process of constructing more complex biocircuits. To address this obstacle, the retroactivity needs to be attenuated by implementing a similar OPAMP device using biocircuits. Previous theoretical papers suggested a potential function of a phosphorylation based circuit in providing the feature of atten- uating retroactivity. Here we presented a successful prototyping and implementation of such a phosphorylation-based insulator (PBI) in an in vitro cell-free transcription-translation system (TX- TL). We demonstrated that retroactivity also exists in TX-TL system, if not stronger, by testing a simple negative regulation circuit. Besides we showed that the TX-TL system contains all the protein, DNA components and other resources required for the PBI circuit to work properly. We then demonstrated that the PBI circuit helps minimizing the loading effect to less than 10% compared to control circuit. With this preliminary PBI circuit design, attenuation of retroactivity while connecting two modules in vitro becomes possible. In concert with another paper from our group (E. Yeung, S. Guo, R. Murray QBIO2014) which used system identification to estimate all three essential parameters in a simplified PBI model, we showed that the simulations based on these parameters match the experimental data very well and provide an interesting insight into future designs. +
G
The paper studies the problem which we refer to as geometric trajectory filtering, where only trajectories that satisfy the local safety constraints are selected from a library of trajectories. The goal is to speed up primitive-based motion planning while still maintaining a relatively a large collection of motion primitives. One way to solve this problem is to obtain a proper (preferably smooth) function, referred to as the containment indicator function, that describes the shape of the free space. To construct the containment indicator function for an arbitrary shape, the paper uses conformal mapping to transform the original shape of interest to a simpler target shape (e.g. disk, rectangle), which can then be characterized by elementary functions. Computational methods for finding the desired conformal maps are studied. It is shown that they can be formulated as convex optimization problems, whose solution can be obtained efficiently. +
L
The problem of bootstrapping consists in designing agents that can learn from scratch the model of their sensori- motor cascade (the series of robot actuators, the external world, and the robot sensors) and use it to achieve useful tasks. In principle, we would want to design agents that can work for any robot dynamics and any robot sensor(s). One of the difficulties of this problem is the fact that the observations are very high dimensional, the dynamics is nonlinear, and there is a wide range of "representation nuisances" to which we would want the agent to be robust. In this paper, we model the dynamics of sensorimotor cascades using diffeomorphisms of the sensel space. We show that this model captures the dynamics of camera and range-finder data, that it can be used for long-term predictions, and that it can capture nonlinear phenomena such as a limited field of view. Moreover, by analyzing the learned diffeomorphisms it is possible to recover the "linear structure" of the dynamics in a manner which is independent of the commands representation. +
D
The problem of estimating the discrete variables
in nondeterministic hybrid systems where the continuous
variables are available for measurement is considered. Using
partial order and lattice theory, we construct a discrete state
estimator, the LU estimator, which updates two variables at
each step. Namely, it updates the lower (L) and upper (U)
bounds of the set of all possible discrete variables values
compatible with the output sequence and with the systems'
dynamics. If the system is weakly observable, we show that
there always exist a lattice on which to construct the LU
estimator. For computational issues, some partial orders are to
be preferred to others.We thus show that nondeterminism may
be added to a system so as to obtain a new system that satisfies
the requirements for the construction of the LU estimator on
a chosen lattice. These ideas are applied to a nondeterministic
multi-robot system. +
N
The problem of finding a real time optimal
trajectory to minimize the probability of detection (to maximize
the probability of notbeingdetected, pnd, function) of
unmanned air vehicles by opponent radar detection systems
is investigated. This paper extends our preliminary results
on low observable trajectory generation in three ways. First,
trajectory planning in the presence of detection by multiple
radar systems, rather than single radar systems, is considered.
Second, an overall probability of detection function is
developed for the multiple radar case. In previous work, both
probability of detection by a single radar and signature were
developed in the theory section, but the examples used only
signature constraints. In this work, the use of the overall
probability of detection function is used, both because it
aids in the extension to multiple radar systems and because
it is a more direct measure of the desirable optimization
criteria. The third extension is the use of updated signature
and probability of detection models. The new models have a
greater number of sharp gradients than the previous models,
with low detectability regions for both a cone shaped areas
centered around the nose as in the previous paper, as well as a
cone-shaped area centered around rear of the air vehicle. The
Nonlinear Trajectory Generation method (NTG), developed
at Caltech, is used and motivated by the ability to provide
real time solutions for constrained nonlinear optimization
problems. Numerical simulations of multiple radar scenarios
illustrate UAV trajectories optimized for both detectability and
time. +
M
The problem of model reduction of linear systems with certain interconnection structure is considered
in this paper. To preserve the interconnection structure between subsystems in the reduction, special
care needs to be taken. This problem is important and timely because of the recent focus on complex
networked systems in control engineering. Two different model-reduction methods are introduced and
compared in the paper. Both methods are extensions to the well-known balanced truncation method.
Compared to earlier work in the area these methods use a more general linear fractional transformation
framework, and utilize linear matrix inequalities. Furthermore, new approximation error bounds that
reduce to classical bounds in special cases are derived. So-called structured Hankel singular values +
F
The prolific rise in autonomous systems has led to questions regarding their safe instantiation in real-world scenarios. Failures in safety-critical contexts such as human-robot interactions or even autonomous driving can ultimately lead to loss of life. In this context, this paper aims to provide a method by which one can algorithmically test and evaluate an autonomous system. Given a black-box autonomous system with some operational specifications, we construct a minimax problem based on control barrier functions to generate a family of test parameters designed to optimally evaluate whether the system can satisfy the specifications. To illustrate our results, we utilize the Robotarium as a case study for an autonomous system that claims to satisfy waypoint navigation and obstacle avoidance simultaneously. We demonstrate that the proposed test synthesis framework systematically finds those sequences of events (tests) that identify points of system failure. +
E
Engineering Transcriptional Regulator Effector Specificity Using Computational Design and In Vitro Rapid Prototyping: Developing a Vanillin Sensor +
The pursuit of circuits and metabolic pathways of increasing complexity and robustness in synthetic biology will require engineering new regulatory tools. Feedback control based on relevant molecules, including toxic intermediates and environmental signals, would enable genetic circuits to react appropriately to changing conditions. In this work, variants of qacR, a tetR family repressor, were generated by computational protein design and screened in a cell-free transcription-translation (TX-TL) system for responsiveness to a new targeted effector. The modified repressors target vanillin, a growth-inhibiting small molecule found in lignocellulosic hydrolysates and other industrial processes. Promising candidates from the in vitro screen were further characterized in vitro and in vivo in a gene circuit. The screen yielded two qacR mutants that respond to vanillin both in vitro and in vivo. While the mutants exhibit some toxicity to cells, presumably due to off-target effects, they are prime starting points for directed evolution toward vanillin sensors with the specifications required for use in a dynamic control loop. We believe this process, a combination of the generation of variants coupled with in vitro screening, can serve as a framework for designing new sensors for other target compounds. +
Engineering Transcriptional Regulator Effector Specificity using Computational Design and In Vitro Rapid Prototyping: Developing a Vanillin Sensor +
The pursuit of circuits and metabolic pathways of increasing complexity and robustness in synthetic biology will require engineering new regulatory tools. Feedback control based on relevant molecules, including toxic intermediates and environmental signals, would enable genetic circuits to react appropriately to changing conditions. In this work, variants of qacR, a tetR family repressor, were generated by compu- tational protein design and screened in a cell-free transcription-translation (TX-TL) system for responsiveness to a new targeted effector. The modified repressors target vanillin, a growth-inhibiting small molecule found in lignocellulosic hydrolysates and other industrial processes. Promising candidates from the in vitro screen were further characterized in vitro and in vivo in a gene circuit. The screen yielded two qacR mutants that respond to vanillin both in vitro and in vivo. We believe this process, a combination of the generation of variants coupled with in vitro screening, can serve as a framework for designing new sensors for other target compounds. +
Engineering Transcriptional Regulator Effector Specificity Through Rational Design and Rapid Prototyping +
The pursuit of circuits and metabolic pathways of increasing complexity and robustness in synthetic biology will require engineering new regulatory tools. Feedback control based on relevant molecules, including toxic intermediates and environmental signals, would enable genetic circuits to react appropriately to changing conditions. In this work, computational protein design was used to create functional variants of qacR, a tetR family repressor, responsive to a new targeted effector. The modified repressors target vanillin, a growth-inhibiting small molecule found in lignocellulosic hydrolysates and other industrial processes. A computatio ally designed library was screened using an in vitro transcription-translation (TX-TL) system. Leads from the in vitro screen were characterized in vivo. Preliminary results demonstrate dose-dependent regulation of a downstream fluorescent reporter by vanillin. These repressor designs provide a starting point for the evolution of improved variants. We believe this process can serve as a framework for designing new sensors for other target compounds. +
T
The realization of artificial biochemical reaction networks with unique functionality is one of the main challenges for the development of synthetic biology. Due to the reduced number of components, biochemical circuits constructed in vitro promise to be more amenable to systematic design and quantitative assessment than circuits embedded within living organisms. To make good on that promise, effective methods for composing subsystems into larger systems are needed. Here we used an artificial biochemical oscillator based on in vitro transcription and RNA degradation reactions to drive a variety of âloadâ processes such as the operation of a DNA-based nanomechanical device (âDNA tweezersâ) or the production of a functional RNA molecule (an aptamer for malachite green). We implemented several mechanisms for coupling the load processes to the oscillator circuit and compared them based on how much the load affected the frequency and amplitude of the core oscillator, and how much of the load was effectively driven. Based on heuristic insights and computational modeling, an âinsulator circuitâ was developed, which strongly reduced the detrimental influence of the load on the oscillator circuit. Understanding how to design effective insulation between biochemical subsystems will be critical for the synthesis of larger and more complex systems. +
Q
Quantitative Modeling of Integrase Dynamics Using a Novel Python Toolbox for Parameter Inference in Synthetic Biology +
The recent abundance of high-throughput data for biological circuits enables data-driven quantitative modeling and parameter estimation. Common modeling issues include long computational times during parameter estimation, and the need for many iterations of this cycle to match data. Here, we present BioSCRAPE (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation) - a Python package for fast and flexible modeling and simulation for biological circuits. The BioSCRAPE package can be used for deterministic or stochastic simulations and can incorporate delayed reactions, cell growth, and cell division. Simulation run times obtained with the package are comparable to those obtained using C code - this is particularly advantageous for computationally expensive applications such as Bayesian inference or simulation of cell lineages. We first show the package's simulation capabilities on a variety of example simulations of stochastic gene expression. We then further demonstrate the package by using it to do parameter inference for a model of integrase dynamics using experimental data. The BioSCRAPE package is publicly available online along with more detailed documentation and examples. +
I
The rules that govern decision making in systems
controlled by humans are often simple to describe. However,
deriving these rules from the actions of a group can be very
difficult, making human behavior hard to predict. We develop
an algorithm to determine the rules implemented by drivers
at a traffic intersection by observing the trajectories of their
cars. We applied such algorithm to a traffic intersection scenario
reproduced in the Caltech multi-vehicle lab, with human subjects
remotely driving kinematic robots. The results obtained on these
data suggest that this kind of human behavior is to some extent
predictable on our data set, and different subjects implement
similar rules. +
