Control: Read Article 09 P. R. LeDuc, W. C. Messner, and J. P. Wikswo.
How do control-based approaches enter into biology?
Annu.Rev.Biomed.Engr. 13:369-396, 2011.
This article addresses a problem central to much of existing biology,
systems biology, and organs on a chip -- much of the work to date has
been done in an open-loop manner, and hence does not adequately probe
the system dynamics. Post a PCRC on the Blog.
The Systems Biology of COVID-19 and the SARS-CoV-2 virus. The class will build a foundation that includes the emergence of complexity, simple biological subsystems, their reductionist and equivalent toy and organ-chip models, and the measurements required to specify model architecture and parameters. Applications to biology, physiology, medicine, chemical and biological defense, pharmacology, drug discovery, and toxicology. UGrad: PHYS 240 01 and BME 290B; Grad: PHYS 326 and BME 395C.
Arman Chowdhury
ReplyDeleteAssignment 6A
0. Knew: Cells are actively controlling and modifying their environment at both the intracellular and extracellular levels. Control challenges for cells extend over multiple scales in space and time, with some cells being affected at long distances by other cells (for example, through paracrine signals such as hormones).
1. Learned: Control theory would allow external control of particular cellular processes that ultimately may help in areas “from cellular production of biopharmaceuticals to biofilm control to novel cancer treatment approaches”. Black-box approach uses input-output behavior alone to derive a mathematical model. Gray-box approach uses input-output behavior to determine unknown parameters in a model of the system. Clear-box approach (heavily reductionist) models all internal details and dynamics. Three fundamental types of feedback control are: proportional control (control action proportional to error), derivative control (control action depends on instantaneous rate of change of control), integral control (control action proportional to integral error).
2. Pressing ?: The paper mentions that optogenetics allows “optical control of transmembrane channels, G-protein receptor-controlled enzymes, ion pumps…”, but how exactly is control achieved? How can external stimulation of genetically engineered cells with light sensitive proteins relay the stimulus to other proteins like ion channels, for example? Can optogentics be used in organ-on-a-chip?
3. Presentation: (Mostly) exhaustive review of different aspects of control biology and the concept of BioMIMO.
4. Thoughts: Although I can more clearly acknowledge the complexity and nonlinearity of biological systems after reading this review, I am also excited more than before about the future of control biology and BioMIMO. I was interested to learn about the various input control methods currently being used, and I was wondering whether future studies could combine all the different modes of input (chemical, mechanical, electrical and optical) for studying cellular behavior more comprehensively, or whether that would interfere with the cell’s activity to give accurate results.
Kate Jones
ReplyDeleteAssignment 6A Article 9
0. Knew: I knew that cells exhibit control over their environment and each other through feedback and other signaling mechanisms and that the environment also influences cellular response. I have learned about the voltage clamp experiments as a way to measure the electrical output of a cell during an action potential.
1. Learned: I learned that a major reason that we cannot understand cellular regulation is the inadequacy of experimental systems and cell-scale actuators as well as imaging techniques. Another obstacle is the inability to measure multiple protein species at a time. I also learned about the different approaches used based on what you already know about the system in order to determine the input and output relationships.
2. Pressing ?: The article stresses the importance of being able to manipulate the cell in order to control the environment and manipulate the environment in order to control the cell. Wouldn't controlling the environment allow you to analyze the cellular response and be enough to be able to control cellular output?
3. Presentation: the use of microfluidic devices to analyze cellular output based on varying hormonal, electrical, and mechanical input
4. Thoughts: I can see how the ability to control the rate of production of a cell could be extremely helpful in pharmaceuticals because we could increase the amount of enzymes or other products we use. As the article states, further developing this type of sensing, feedback, and control could be extremely useful in cancer treatments.
Juan Gnecco
ReplyDeleteAsgn_6A
0.Knew: Need and difficulty in mapping the spatio temporal dynamics of a cell and its properties to define a function. Paracrine and autocrine signaling is a key aspect of input actuators. The different types of imputs and their examples. The power of fluorescent proteins.
1:Learned: Control theory and what it entails and how it doesnt just encompass individual cells. Diffence betweeen engineering and biology domains = no distinct control unit. The problems with certain types of modeling i.e. proportional control due to steady state error.
2. Pressing: Cant we use highly studied toxicant or drugs as imput actuators as cannonical samples to validate cellular response? (never mind this is open loop) What is the best model of synthetic extracellular matrix? Matrigel?
3.Presentation: The need to study the dynamics of a cell and thus an organ.
4.Thoughts: Conceptual theory - some things kind of went over my head at times. I hope we discuss this in detail tomorrow. Current developments of closed loop.
James Pino
ReplyDeleteAssignment 6A
0:Knew: Very little about control and even less about ways to control biological systems.
1:Learned: Types and levels of control. Types of inputs and actuators. Methods of measuring output. Difficulties of multiple measurements and resolution of space and time.
2:Pressings: Are there any examples of using control signals to induce phenotype that continue once the signal is removed (relocating it in epigentic landscape)?
3:Thoughts: I like the idea of using increased resolution in control. Controlling an input and just seeing how it responds than gradually increasing the resolution of the model.
Tim Lee
ReplyDeleteAsgn_6A
0. Knew: Basic principles about control and the need for them in experimentation for biology. Need for better technologies for higher resolution measurements.
1. Learned: Significance of manipulating multiple inputs into experiment and measuring multiple outputs. Different types of box approaches (black, gray, clear) and their advantages over one another. Different types of feedback control and kinds of inputs one can impose onto a cell.
2. Pressing: Can someone explain closed loop approaches in more laymen's terms? Possibly some examples with easy to follow explanations of those examples?
3. Presentation: Control theory and different aspects of manipulation and measurement
4. Thoughts: It feels like the only approach I've been drilled to learn for almost four years at Vanderbilt is the open loop approach. Is it just too difficult to pursue closed loop approaches with the current methods and technologies to teach to undergraduates? Maybe we have been using it but I haven't been able to recognize it...
Cameron Togrye
ReplyDeleteAsgn_6A/ How do control based approaches enter into Biology
0. Knew: An example of control theory application is the BZ reaction where the temporal and spatial progression of oscillatory was modeled. GFP's and their usefulness and limitations in biomarking.
1. Learned: I was not aware that gene transcription could be regulated by as few as ten copies of a single regulatory protein. This would seem to create the stochastic effect the paper refers to.
2. Pressing: The paper makes mention of redundant proteins in a pathway or entire redundant pathways that exist. How can we be sure these elements are "redundant"? Couldn't it be that their role in the pathway or control mechanism hasn't been fully realized as of yet? Also, why is it obvious that the control of temperature in the body is the result of integral control? Isn't it possible that we could be experiencing the slight oscillations mentioned, but they are so imperceptible so as to make it look constant?
3. Presentation: Varieties in GFP like proteins
4. Thoughts: I think the notion of how the cell would sense or "feel" the time derivative of a certain product in a pathway is an interesting question. Perhaps it could involve cooperative binding? Similar to what happens in hemoglobin
Selene van der Walt
ReplyDeleteAssignment 6A
0. Knew: Control is central to organismal behavior, and that appropriately scaling the temporal and spatial resolution is one of the biggest challenges in creating models of control systems. The concept of control cycles, and identifying inputs/outputs to a system.
1. Learned: That much of our current understanding of biological processes relies on qualitative reasoning, not quantitative models. The inability to monitor many proteins at once is a large obstacle in modeling cellular control systems, even with advances made in using GFPs for detection. The distinction between proportional, differential and integral control, as well as about open and closed loop approaches.
2. Pressing ?: I am still a bit unclear about the difference between black-, grey-, and clear- box , systems and how to know which of these is the appropriate modeling method.
3. Presentation: The benefits of closed-loop approaches to control theory in biology.
4. Thoughts: I find the idea of using closed loop systems to alter the internal function of cells very interesting. Although I don’t completely understand the way this would be achieved, I can imagine there would be a host of potential applications if you could prompt cells to perform specific chemical reactions at the push of a button.
This comment has been removed by the author.
ReplyDeleteCami Johnson
ReplyDeleteAssignment 6A: Article 9
0. Knew: The basics of control and feedback loops. That many biological processes are nonlinear and involve complicated systems of feedback.
1. Learned: I've never taken a class on controls before, so some things that were maybe basic to others were new to me. The different approaches to describing a system's dynamics: black-box, gray-box, and clear-box. The types of feedback control: proportional, derivative, and integral.
2. Pressing ?: With such a range in time (milliseconds to years) for biological processes, can time be appropriately scaled in a BioMEMS device? Are there any reversible actuators being used?
3. Presentation: Different means of applying shear stress/flow to cells (relevant to my current research)
4. Thoughts: This is really interesting to me and sounds like an important direction for biological research to go in. As always in biomedical engineering research, though, it seems like cooperation between scientists with various backgrounds is crucial for all of the elements to come together.
Chuck Herring
ReplyDeleteAssignment 6A
0. Knew: Briefly knew the challenges of controlling a cell with various inputs to monitor its outputs.
1. Learned: I learned a lot more about the challenges of controlling a cell and the different types of feed-back controls.
2. Pressings: How do you monitor with single cell resolution and not disturb the cell?
3. Presentation: Applying control based approaches to better understand biology.
4. Thoughts: How does scale to the tissue level? Cell heterogeneity contributes to the homogeneity of tissues, I fell like controlling single cells to monitor tissue level outputs would be a significant challenge.
Priyanka Ravichandran
ReplyDeleteAssignment 6A
0. Knew - I knew that cells are involved in a control system where they affect their environment and their environment affects them. I also knew of some of the challenges involved in trying to model/analyze cellular regulation.
1. Learned - what black/gray/clear box testing is; that developing a BioMIMO system will allow us to better model a dynamic cell because it has multiple sensors and actuators
2. Pressing - The main problem seems to be how to acquire long-duration, quantitative data for BioMIMO systems. Even though some methods exist now for sensors and actuators, they are mostly used for SISO systems.
3. Presentation - an overview of control-based systems and how they are applied to cells
4. Thoughts - Overall, very interesting article. It seems that there are many actuators, but not that many sensors. In addition, the actuators do not always affect the cell in the same way they are affected in the body and the sensors are not effective enough in measuring data to the extent that we want to measure it. I thought it was interesting at the end when the article measured the future potential of BioMIMO systems in treating diseases.
Nathaniel Braman
ReplyDeleteAssignment 6A
0. Knew - Cellular control is a complex system, and it is possible to model its behavior with traditional engineering modeling approaches. Some methods for cellular control, and some basics of modeling.
1. Learned - BioMIMO/SISI systems. Black, grey, and clear box modeling. Various methods of single cell actuation and the stimuli they can be used to control. Specific biological examples of different feedback control types.
2. Pressing - Can we use models of different types to elucidate each other - can we, for example, grey box model as a tool in the development of a clear box model?
3. Presentation - An introduction to systems for biological control, both theoretically and in practice.
4. Thoughts - This has been one of my favorite articles so far. I really enjoyed the parallel presentation of biology and mathematics - a concept we had talked about abstractly previously, but was a little more concrete here.
Shuaipeng "Jimmy" Zhang
ReplyDeleteAssignment 6A
0. Knew: Closed loop and open loop approaches to control intracellular functions. Some of the different types of inputs currently used to control cellular environments.
1. Learned: Black-box, gray-box, and clear-box approaches. The 3 types of feedback control: proportional control, derivative control, and integral control. Challenges in accurately measuring the output of cells and controlling the input.
2. Pressing ?: What are some more examples of proportional control, derivative control, and integral control in the body? For integral control, what are some theoretical ways in which the body carries it out?
3. Presentation: Different methods of actuating a cell, and the challenges associated with them.
4. Thoughts: The article provided a detailed explanation of the different types of control systems and approaches currently used in research. Also, the fact that the body carries out an Leibnez of operations continuously is astounding.
Mark Vander Roest
ReplyDeleteAssignment 6A
0. Knew: The difficulties of non-disruptive measurements (opening loops to perturb or measure), a few current methods of cellular control, in vivo control.
1. Learned: Some new forms of control, including optical input, SISO/MIMO/MISO concepts, closed loop approaches, overarching goals of cellular measurement/control.
2. Pressing ?: Is exerting control itself a good enough simulation of the in vivo environment for systems biology applications, or does cellular control have to be in the same manner and pattern for useful applications?
3. Presentation: methods of measuring and controlling cells, current practices and future needs.
4. Thoughts: It's a really cool topic with a sense of more achievable goals. I like that there are a lot of examples of existing technology to create a more relevant understanding of the topic.