How do control-based approaches enter into biology?

Thinking in 3 dimensions: philosophies of the microenvironment in organoids and organs-on-chip

Organoids and organs-on-a-chip are currently the two major families of 3D advanced organotypic in vitro culture systems, aimed at reconstituting miniaturized models of physiological and pathological states of human organs. Both share the tenets of the so-called "three-dimensional thinking", a Systems Physiology approach focused on recapitulating the dynamic interactions between cells and their microenvironment. We first review the arguments underlying the "paradigm shift" toward three-dimensional thinking in the in vitro culture community. Then, through a historically informed account of the technical affordances and the epistemic commitments of these two approaches, we highlight how they embody two distinct experimental cultures. We finally argue that the current systematic effort for their integration requires not only innovative "synergistic" engineering solutions, but also conceptual integration between different perspectives on biological causality.

The Microbiome and the Gut-Liver-Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models

The complexity of integrating microbiota into clinical pharmacology, environmental toxicology, and opioid studies arises from bidirectional and multiscale interactions between humans and their many microbiota, notably those of the gut. Hosts and each microbiota are governed by distinct central dogmas, with genetics influencing transcriptomics, proteomics, and metabolomics. Each microbiota's metabolome differentially modulates its own and the host's multi‐omics. Exogenous compounds (e.g., drugs and toxins), often affect host multi‐omics differently than microbiota multi‐omics, shifting the balance between drug efficacy and toxicity. The complexity of the host‐microbiota connection has been informed by current methods of in vitro bacterial cultures and in vivo mouse models, but they fail to elucidate mechanistic details. Together, in vitro organ‐on‐chip microphysiological models, multi‐omics, and in silico computational models have the potential to supplement the established methods to help clinical pharmacologists and environmental toxicologists unravel the myriad of connections between the gut microbiota and host health and disease.

Microdevice arrays with strain sensors for 3D mechanical stimulation and monitoring of engineered tissues

Native and engineered tissue development are regulated by the integrative effects of multiple microenvironmental stimuli. Microfabricated bioreactor array platforms can efficiently dissect cue-response networks, and have recently integrated critical 2D and 3D mechanical stimulation for greater physiological relevance. However, a limitation of these approaches is that assessment of tissue functional properties is typically limited to end-point analyses. Here we report a new deformable membrane platform with integrated strain sensors that enables mechanical stretching or compression of 3D cell-hydrogel arrays and simultaneous measurement of hydrogel construct stiffness in situ. We tested the ability of the integrated strain sensors to measure the evolution of the stiffness of cell-hydrogel constructs for two cases. First, we demonstrated in situ stiffness monitoring of degradable poly (ethylene glycol)-norbornene (PEG-NB) hydrogels embedded with mesenchymal stromal cells (MSCs) and cultured with or without cyclic tensile stimulation for up to 15 days. Whereas statically-cultured hydrogels degraded and softened throughout the culture period, mechanically-stimulated gels initially softened and then recovered their stiffness corresponding to extensive cell network and collagen production. Second, we demonstrated in situ measurement of compressive stiffening of MSC-seeded PEG-NB gels cultured statically under osteogenic conditions, corresponding to increased mineralization and cellularization. This measurement technique can be generalized to other relevant bioreactor and organ-on-a-chip platforms to facilitate online, non-invasive, and high-throughput functional analysis, and to provide insights into the dynamics of engineered tissue development that are otherwise not available.

Circadian hormone control in a human-on-a-chip: In vitro biology's ignored component?

Organs-on-Chips (OoCs) are poised to reshape dramatically the study of biology by replicating in vivo the function of individual and coupled human organs. Such microphysiological systems (MPS) have already recreated complex physiological responses necessary to simulate human organ function not evident in two-dimensional in vitro biological experiments. OoC researchers hope to streamline pharmaceutical development, accelerate toxicology studies, limit animal testing, and provide new insights beyond the capability of current biological models. However, to develop a physiologically accurate Human-on-a-Chip, i.e., an MPS homunculus that functions as an interconnected, whole-body, model organ system, one must couple individual OoCs with proper fluidic and metabolic scaling. This will enable the study of the effects of organ-organ interactions on the metabolism of drugs and toxins. Critical to these efforts will be the recapitulation of the complex physiological signals that regulate the endocrine, metabolic, and digestive systems. To date, with the exception of research focused on reproductive organs on chips, most OoC research ignores homuncular endocrine regulation, in particular the circadian rhythms that modulate the function of all organ systems. We outline the importance of cyclic endocrine regulation and the role that it may play in the development of MPS homunculi for the pharmacology, toxicology, and systems biology communities. Moreover, we discuss the critical end-organ hormone interactions that are most relevant for a typical coupled-OoC system, and the possible research applications of a missing endocrine system MicroFormulator (MES-µF) that could impose biological rhythms on in vitro models. By linking OoCs together through chemical messenger systems, advanced physiological phenomena relevant to pharmacokinetics and pharmacodynamics studies can be replicated. The concept of a MES-µF could be applied to other standard cell-culture systems such as well plates, thereby extending the concept of circadian hormonal regulation to much of in vitro biology. Impact statement Historically, cyclic endocrine modulation has been largely ignored within in vitro cell culture, in part because cultured cells typically have their media changed every day or two, precluding hourly adjustment of hormone concentrations to simulate circadian rhythms. As the Organ-on-Chip (OoC) community strives for greater physiological realism, the contribution of hormonal oscillations toward regulation of organ systems has been examined only in the context of reproductive organs, and circadian variation of the breadth of other hormones on most organs remains unaddressed. We illustrate the importance of cyclic endocrine modulation and the role that it plays within individual organ systems. The study of cyclic endocrine modulation within OoC systems will help advance OoC research to the point where it can reliably replicate in vitro key regulatory components of human physiology. This will help translate OoC work into pharmaceutical applications and connect the OoC community with the greater pharmacology and physiology communities.

A Review of Control Strategies in Closed-Loop Neuroprosthetic Systems

It has been widely recognized that closed-loop neuroprosthetic systems achieve more favorable outcomes for users then equivalent open-loop devices. Improved performance of tasks, better usability, and greater embodiment have all been reported in systems utilizing some form of feedback. However, the interdisciplinary work on neuroprosthetic systems can lead to miscommunication due to similarities in well-established nomenclature in different fields. Here we present a review of control strategies in existing experimental, investigational and clinical neuroprosthetic systems in order to establish a baseline and promote a common understanding of different feedback modes and closed-loop controllers. The first section provides a brief discussion of feedback control and control theory. The second section reviews the control strategies of recent Brain Machine Interfaces, neuromodulatory implants, neuroprosthetic systems, and assistive neurorobotic devices. The final section examines the different approaches to feedback in current neuroprosthetic and neurorobotic systems.

Cell-matrix interaction during strain-dependent remodelling of simulated collagen networks

The importance of tissue remodelling is widely accepted, but the mechanism by which the remodelling process occurs remains poorly understood. At the tissue scale, the concept of tensional homeostasis, in which there exists a target stress for a cell and remodelling functions to move the cell stress towards that target, is an important foundation for much theoretical work. We present here a theoretical model of a cell in parallel with a network to study what factors of the remodelling process help the cell move towards mechanical stability. The cell-network system was deformed and kept at constant stress. Remodelling was modelled by simulating strain-dependent degradation of collagen fibres and four different cases of collagen addition. The model did not lead to complete tensional homeostasis in the range of conditions studied, but it showed how different expressions for deposition and removal of collagen in a fibre network can interact to modulate the cell's ability to shield itself from an imposed stress by remodelling the surroundings. This study also showed how delicate the balance between deposition and removal rates is and how sensitive the remodelling process is to small changes in the remodelling rules.

Automated adaptive inference of phenomenological dynamical models

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Mechanistic modelling of dynamical phenomena with many degrees of freedom runs the risk of overfitting and making faulty predictions, whereas ad hoc models may miss defining features. Here the authors develop an approach to construct dynamical models that adapt their complexity to the amount of available data.

Real-Time Monitoring of Cellular Bioenergetics with a Multianalyte Screen-Printed Electrode

Real-time monitoring of changes to cellular bioenergetics can provide new insights into mechanisms of action for disease and toxicity. This work describes the development of a multianalyte screen-printed electrode for the detection of analytes central to cellular bioenergetics: glucose, lactate, oxygen, and pH. Platinum screen-printed electrodes were designed in-house and printed by Pine Research Instrumentation. Electrochemical plating techniques were used to form quasi-reference and pH electrodes. A Dimatix materials inkjet printer was used to deposit enzyme and polymer films to form sensors for glucose, lactate, and oxygen. These sensors were evaluated in bulk solution and microfluidic environments, and they were found to behave reproducibly and possess a lifetime of up to 6 weeks. Linear ranges and limits of detection for enzyme-based sensors were found to have an inverse relationship with enzyme loading, and iridium oxide pH sensors were found to have super-Nernstian responses. Preliminary measurements where the sensor was enclosed within a microfluidic channel with RAW 264.7 macrophages were performed to demonstrate the sensors' capabilities for performing real-time microphysiometry measurements.

An automated programmable platform enabling multiplex dynamic stimuli delivery and cellular response monitoring for high-throughput suspension single-cell signaling studies

Cell signaling events are orchestrated by dynamic external biochemical cues. By rapidly perturbing cells with dynamic inputs and examining the output from these systems, one could study the structure and dynamic properties of a cellular signaling network. Conventional experimental techniques limit the implementation of these systematic approaches due to the lack of sophistication in manipulating individual cells and the fluid microenvironment around them; existing microfluidic technologies thus far are mainly targeting adherent cells. In this paper we present an automated platform to interrogate suspension cells with dynamic stimuli while simultaneously monitoring cellular responses in a high-throughput manner at single-cell resolution. We demonstrate the use of this platform in an experiment to measure Jurkat T cells in response to distinct dynamic patterns of stimuli; we find cells exhibit highly heterogeneous responses under each stimulation condition. More interestingly, these cells act as low-pass filters, only entrained to the low frequency stimulus signals. We also demonstrate that this platform can be easily programmed to actively generate arbitrary dynamic signals. We envision our platform to be useful in other contexts to study cellular signaling dynamics, which may be difficult using conventional experimental methods.

Real-time cellular exometabolome analysis with a microfluidic-mass spectrometry platform

To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of "in-culture" experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (e.g., cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell's metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform's capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional "in-culture" UPLC-ESI-IM-MS experiment, further demonstrating this platform's capabilities.

Biology coming full circle: joining the whole and the parts

The new cover of Experimental Biology and Medicine features the hermeneutic circle of biology, a concept we have adapted from the hermeneutic principle that one understands the whole only in terms of each part and the parts only in terms of the whole. Our hermeneutic circle summarizes the course of experimental biology through 2500 years of the achievements of reductionist research (understanding the parts), which culminates in our ability to rapidly sequence the genome. Rather than returning along the same path in a constructionist approach that simply builds upon this knowledge, but in reverse, an alternative is to close the circle with synthetic constructions that seek to integrate the full complexity of biological and physiological systems (understanding the whole), of which organs-on-chips are one example. This closing of the circle cannot be a comprehensively accurate representation of biology, but it can be a synthetic one that effectively defines particular biological subsystems. The illustration of the hermeneutic circle of biology is also intended to suggest both the multiple cycles that may be required to reach such a synthesis and the expansion of the circle in an outward spiral as knowledge increases. Our commentary explains the symbolism of the new cover in a philosophical and scientific discussion.

Approaching the in vitro clinical trial: engineering organs on chips

In vitro cell culture and animal models are the most heavily relied upon tools of the pharmaceutical industry. When these tools fail, the results are costly and have at times, proven deadly. One promising new tool to enhance preclinical development of drugs is Organs on Chips (OOCs), proposed as a clinically and physiologically relevant means of modeling health and disease. Bringing the patient from bedside to bench in this form requires that the design, build, and test of OOCs be founded in clinical observations and methods. By creating OOCs as models of the patient, the industry may be better positioned to evaluate medicinal therapeutics.

The relevance and potential roles of microphysiological systems in biology and medicine

Microphysiological systems (MPS), consisting of interacting organs-on-chips or tissue-engineered, 3D organ constructs that use human cells, present an opportunity to bring new tools to biology, medicine, pharmacology, physiology, and toxicology. This issue of Experimental Biology and Medicine describes the ongoing development of MPS that can serve as in-vitro models for bone and cartilage, brain, gastrointestinal tract, lung, liver, microvasculature, reproductive tract, skeletal muscle, and skin. Related topics addressed here are the interconnection of organs-on-chips to support physiologically based pharmacokinetics and drug discovery and screening, and the microscale technologies that regulate stem cell differentiation. The initial motivation for creating MPS was to increase the speed, efficiency, and safety of pharmaceutical development and testing, paying particular regard to the fact that neither monolayer monocultures of immortal or primary cell lines nor animal studies can adequately recapitulate the dynamics of drug-organ, drug-drug, and drug-organ-organ interactions in humans. Other applications include studies of the effect of environmental toxins on humans, identification, characterization, and neutralization of chemical and biological weapons, controlled studies of the microbiome and infectious disease that cannot be conducted in humans, controlled differentiation of induced pluripotent stem cells into specific adult cellular phenotypes, and studies of the dynamics of metabolism and signaling within and between human organs. The technical challenges are being addressed by many investigators, and in the process, it seems highly likely that significant progress will be made toward providing more physiologically realistic alternatives to monolayer monocultures or whole animal studies. The effectiveness of this effort will be determined in part by how easy the constructs are to use, how well they function, how accurately they recapitulate and report human pharmacology and toxicology, whether they can be generated in large numbers to enable parallel studies, and if their use can be standardized consistent with the practices of regulatory science.

The engineering of artificial cellular nanosystems using synthetic biology approaches

Artificial cellular systems are minimal systems that mimic certain properties of natural cells, including signaling pathways, membranes, and metabolic pathways. These artificial cells (or protocells) can be constructed following a synthetic biology approach by assembling biomembranes, synthetic gene circuits, and cell-free expression systems. As artificial cells are built from bottom-up using minimal and a defined number of components, they are more amenable to predictive mathematical modeling and engineered controls when compared with natural cells. Indeed, artificial cells have been implemented as drug delivery machineries and in situ protein expression systems. Furthermore, artificial cells have been used as biomimetic systems to unveil new insights into functions of natural cells, which are otherwise difficult to investigate owing to their inherent complexity. It is our vision that the development of artificial cells would bring forth parallel advancements in synthetic biology, cell-free systems, and in vitro systems biology. For further resources related to this article, please visit the WIREs website. Conflict of interests: The authors declare that they have no competing financial interests.

Mathematical modeling of the Phoenix Rising pathway

Apoptosis is a tightly controlled process in mammalian cells. It is important for embryogenesis, tissue homoeostasis, and cancer treatment. Apoptosis not only induces cell death, but also leads to the release of signals that promote rapid proliferation of surrounding cells through the Phoenix Rising (PR) pathway. To quantitatively understand the kinetics of interactions of different molecules in this pathway, we developed a mathematical model to simulate the effects of various changes in the PR pathway on the secretion of prostaglandin E2 (PGE2), a key factor for promoting cell proliferation. These changes include activation of caspase 3 (C3), caspase 7 (C7), and nuclear factor κB (NFκB). In addition, we simulated the effects of cyclooxygenase-2 (COX2) inhibition and C3 knockout on the level of secreted PGE2. The model predictions on PGE2 in MEF and 4T1 cells at 48 hours after 10-Gray radiation were quantitatively consistent with the experimental data in the literature. Compared to C7, the model predicted that C3 activation was more critical for PGE2 production. The model also predicted that PGE2 production could be significantly reduced when COX2 expression was blocked via either NFκB inactivation or treatment of cells with exogenous COX2 inhibitors, which led to a decrease in the rate of conversion from arachidonic acid to prostaglandin H2 in the PR pathway. In conclusion, the mathematical model developed in this study yielded new insights into the process of tissue regrowth stimulated by signals from apoptotic cells. In future studies, the model can be used for experimental data analysis and assisting development of novel strategies/drugs for improving cancer treatment or normal tissue regeneration.

Apoptosis, or programmed cell death, is known to be important for embryogenesis, tissue homoeostasis, and cancer treatment. Furthermore, researchers have recently observed that apoptosis may promote wound healing and tissue regeneration, and accelerate undesired solid tumor regrowth after chemotherapy/radiation therapy. Mechanisms of apoptosis-induced tissue regrowth are related to a molecular network discovered recently in our lab. To quantitatively understand the kinetics of interactions of different molecules in this network, we developed a mathematical model and validated it by comparing the simulation results to experimental data reported in previous studies. To gain new insights into the process of tissue regrowth after inducing apoptosis, we used the model to simulate the effects of radiation on the production of a key growth stimulating factor, PGE2, in apoptotic cells. Additionally, we simulated how PGE2 production could be altered when cells were treated with different inhibitors. We expect that the new mathematical model can be used in future studies to facilitate design of better approaches to cancer treatment or normal tissue regeneration.

Neurovascular unit on a chip: implications for translational applications

The blood-brain barrier (BBB) dynamically controls exchange between the brain and the body, but this interaction cannot be studied directly in the intact human brain or sufficiently represented by animal models. Most existing in vitro BBB models do not include neurons and glia with other BBB elements and do not adequately predict drug efficacy and toxicity. Under the National Institutes of Health Microtissue Initiative, we are developing a three-dimensional, multicompartment, organotypic microphysiological system representative of a neurovascular unit of the brain. The neurovascular unit system will serve as a model to study interactions between the central nervous system neurons and the cerebral spinal fluid (CSF) compartment, all coupled to a realistic blood-surrogate supply and venous return system that also incorporates circulating immune cells and the choroid plexus. Hence all three critical brain barriers will be recapitulated: blood-brain, brain-CSF, and blood-CSF. Primary and stem cell-derived human cells will interact with a variety of agents to produce critical chemical communications across the BBB and between brain regions. Cytomegalovirus, a common herpesvirus, will be used as an initial model of infections regulated by the BBB. This novel technological platform, which combines innovative microfluidics, cell culture, analytical instruments, bioinformatics, control theory, neuroscience, and drug discovery, will replicate chemical communication, molecular trafficking, and inflammation in the brain. The platform will enable targeted and clinically relevant nutritional and pharmacologic interventions for or prevention of such chronic diseases as obesity and acute injury such as stroke, and will uncover potential adverse effects of drugs. If successful, this project will produce clinically useful technologies and reveal new insights into how the brain receives, modifies, and is affected by drugs, other neurotropic agents, and diseases.

Scaling and systems biology for integrating multiple organs-on-a-chip

Coupled systems of in vitro microfabricated organs-on-a-chip containing small populations of human cells are being developed to address the formidable pharmacological and physiological gaps between monolayer cell cultures, animal models, and humans that severely limit the speed and efficiency of drug development. These gaps present challenges not only in tissue and microfluidic engineering, but also in systems biology: how does one model, test, and learn about the communication and control of biological systems with individual organs-on-chips that are one-thousandth or one-millionth of the size of adult organs, or even smaller, i.e., organs for a milliHuman (mHu) or microHuman (μHu)? Allometric scaling that describes inter-species variation of organ size and properties provides some guidance, but given the desire to utilize these systems to extend and validate human pharmacokinetic and pharmacodynamic (PK/PD) models in support of drug discovery and development, it is more appropriate to scale each organ functionally to ensure that it makes the suitable physiological contribution to the coupled system. The desire to recapitulate the complex organ-organ interactions that result from factors in the blood and lymph places a severe constraint on the total circulating fluid (~5 mL for a mHu and ~5 μL for a μHu) and hence on the pumps, valves, and analytical instruments required to maintain and study these systems. Scaling arguments also provide guidance on the design of a universal cell-culture medium, typically without red blood cells. This review presents several examples of scaling arguments and discusses steps that should ensure the success of this endeavour.

Creating living cellular machines

Development of increasingly complex integrated cellular systems will be a major challenge for the next decade and beyond, as we apply the knowledge gained from the sub-disciplines of regenerative medicine, synthetic biology, micro-fabrication and nanotechnology, systems biology, and developmental biology. In this prospective, we describe the current state-of-the-art in the assembly of source cells, derived from pluripotent cells, into populations of a single cell type to produce the components or building blocks of higher order systems and finally, combining multiple cell types, possibly in combination with scaffolds possessing specific physical or chemical properties, to produce higher level functionality. We also introduce the issue, questions and ample research opportunities to be explored by others in the field. As these "living machines" increase in capabilities, exhibit emergent behavior and potentially reveal the ability for self-assembly, self-repair, and even self-replication, questions arise regarding the ethical implications of this work. Future prospects as well as ways of addressing these complex ethical questions will be discussed.

Mechanistic analysis of challenge-response experiments

We present an application of mechanistic modeling and nonlinear longitudinal regression in the context of biomedical response-to-challenge experiments, a field where these methods are underutilized. In this type of experiment, a system is studied by imposing an experimental challenge, and then observing its response. The combination of mechanistic modeling and nonlinear longitudinal regression has brought new insight, and revealed an unexpected opportunity for optimal design. Specifically, the mechanistic aspect of our approach enables the optimal design of experimental challenge characteristics (e.g., intensity, duration). This article lays some groundwork for this approach. We consider a series of experiments wherein an isolated rabbit heart is challenged with intermittent anoxia. The heart responds to the challenge onset, and recovers when the challenge ends. The mean response is modeled by a system of differential equations that describe a candidate mechanism for cardiac response to anoxia challenge. The cardiac system behaves more variably when challenged than when at rest. Hence, observations arising from this experiment exhibit complex heteroscedasticity and sharp changes in central tendency. We present evidence that an asymptotic statistical inference strategy may fail to adequately account for statistical uncertainty. Two alternative methods are critiqued qualitatively (i.e., for utility in the current context), and quantitatively using an innovative Monte-Carlo method. We conclude with a discussion of the exciting opportunities in optimal design of response-to-challenge experiments.

Microfluidic interrogation and mathematical modeling of multi-regime calcium signaling dynamics

Through microfluidic interrogation we analyzed real-time calcium responses of HEK293 cells stimulated with short pulses of the M3 muscarinic receptor ligand carbachol in two different concentration regimes. Lower ligand concentrations elicit oscillatory calcium signals while higher concentrations trigger a rapid rise that eventually settles down at a steady-state slightly above pre-stimulus levels, referred to as an acute signal. Cells were periodically pulsed with carbachol at these two concentration regimes using a custom-made microfluidic platform, and the resulting calcium signals were measured with a single fluorescent readout. Pulsed stimulations at these two concentration regimes resulted in multiple types of response patterns that each delivered complementary information about the M3 muscarinic receptor signaling pathway. These multiple types of calcium response patterns enabled development of a comprehensive mathematical model of multi-regime calcium signaling. The resulting model suggests that dephosphorylation of deactivated receptors is rate limiting for recovery of calcium signals in the acute regime (high ligand concentration), while calcium replenishment and IP3 production determine signal recovery in the oscillatory regime (low ligand concentration). This study not only provides mechanistic insight into multi-regime signaling of the M3 muscarinic receptor pathway, but also provides a general strategy for analyzing multi-regime pathways using only one fluorescent readout.

Structure and mechanism of maximum stability of isolated alpha-helical protein domains at a critical length scale

The stability of alpha helices is important in protein folding, bioinspired materials design, and controls many biological properties under physiological and disease conditions. Here we show that a naturally favored alpha helix length of 9 to 17 amino acids exists at which the propensity towards the formation of this secondary structure is maximized. We use a combination of thermodynamical analysis, well-tempered metadynamics molecular simulation and statistical analyses of experimental alpha helix length distributions and find that the favored alpha helix length is caused by a competition between alpha helix folding, unfolding into a random coil and formation of higher-order tertiary structures. The theoretical result is suggested to be used to explain the statistical distribution of the length of alpha helices observed in natural protein structures. Our study provides mechanistic insight into fundamental controlling parameters in alpha helix structure formation and potentially other biopolymers or synthetic materials. The result advances our fundamental understanding of size effects in the stability of protein structures and may enable the design of de novo alpha-helical protein materials.

Neurosensory mechanotransduction through acid-sensing ion channels

Acid-sensing ion channels (ASICs) are voltage-insensitive cation channels responding to extracellular acidification. ASIC proteins have two transmembrane domains and a large extracellular domain. The molecular topology of ASICs is similar to that of the mechanosensory abnormality 4- or 10-proteins expressed in touch receptor neurons and involved in neurosensory mechanotransduction in nematodes. The ASIC proteins are involved in neurosensory mechanotransduction in mammals. The ASIC isoforms are expressed in Merkel cell-neurite complexes, periodontal Ruffini endings and specialized nerve terminals of skin and muscle spindles, so they might participate in mechanosensation. In knockout mouse models, lacking an ASIC isoform produces defects in neurosensory mechanotransduction of tissue such as skin, stomach, colon, aortic arch, venoatrial junction and cochlea. The ASICs are thus implicated in touch, pain, digestive function, baroreception, blood volume control and hearing. However, the role of ASICs in mechanotransduction is still controversial, because we lack evidence that the channels are mechanically sensitive when expressed in heterologous cells. Thus, ASIC channels alone are not sufficient to reconstruct the path of transducing molecules of mechanically activated channels. The mechanotransducers associated with ASICs need further elucidation. In this review, we discuss the expression of ASICs in sensory afferents of mechanoreceptors, findings of knockout studies, technical issues concerning studies of neurosensory mechanotransduction and possible missing links. Also we propose a molecular model and a new approach to disclose the molecular mechanism underlying the neurosensory mechanotransduction.

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

Engineering challenges for instrumenting and controlling integrated organ-on-chip systems

The sophistication and success of recently reported microfabricated organs-on-chips and human organ constructs have made it possible to design scaled and interconnected organ systems that may significantly augment the current drug development pipeline and lead to advances in systems biology. Physiologically realistic live microHuman (μHu) and milliHuman (mHu) systems operating for weeks to months present exciting and important engineering challenges such as determining the appropriate size for each organ to ensure appropriate relative organ functional activity, achieving appropriate cell density, providing the requisite universal perfusion media, sensing the breadth of physiological responses, and maintaining stable control of the entire system, while maintaining fluid scaling that consists of ~5 mL for the mHu and ~5 μL for the μHu. We believe that successful mHu and μHu systems for drug development and systems biology will require low-volume microdevices that support chemical signaling, microfabricated pumps, valves and microformulators, automated optical microscopy, electrochemical sensors for rapid metabolic assessment, ion mobility-mass spectrometry for real-time molecular analysis, advanced bioinformatics, and machine learning algorithms for automated model inference and integrated electronic control. Toward this goal, we are building functional prototype components and are working toward top-down system integration.

Grand challenges in interfacing engineering with life sciences and medicine

This paper summarizes the discussions held during the First IEEE Life Sciences Grand Challenges Conference, held on October 4-5, 2012, at the National Academy of Sciences, Washington, DC, and the grand challenges identified by the conference participants. Despite tremendous efforts to develop the knowledge and ability that are essential in addressing biomedical and health problems using engineering methodologies, the optimization of this approach toward engineering the life sciences and healthcare remains a grand challenge. The conference was aimed at high-level discussions by participants representing various sectors, including academia, government, and industry. Grand challenges were identified by the conference participants in five areas including engineering the brain and nervous system; engineering the cardiovascular system; engineering of cancer diagnostics, therapeutics, and prevention; translation of discoveries to clinical applications; and education and training. A number of these challenges are identified and summarized in this paper.

Attenuation of cell mechanosensitivity in colon cancer cells during in vitro metastasis

Human colon carcinoma (HCT-8) cells show a stable transition from low to high metastatic state when cultured on appropriately soft substrates (21 kPa). Initially epithelial (E) in nature, the HCT-8 cells become rounded (R) after seven days of culture on soft substrate. R cells show a number of metastatic hallmarks [1]. Here, we use gradient stiffness substrates, a bio-MEMS force sensor, and Coulter counter assays to study mechanosensitivity and adhesion of E and R cells. We find that HCT-8 cells lose mechanosensitivity as they undergo E-to-R transition. HCT-8 R cells' stiffness, spread area, proliferation and migration become insensitive to substrate stiffness in contrast to their epithelial counterpart. They are softer, proliferative and migratory on all substrates. R cells show negligible cell-cell homotypic adhesion, as well as non-specific cell-substrate adhesion. Consequently they show the same spread area on all substrates in contrast to E cells. Taken together, these results indicate that R cells acquire autonomy and anchorage independence, and are thus potentially more invasive than E cells. To the best of our knowledge, this is the first report of quantitative data relating changes in cancer cell adhesion and stiffness during the expression of an in vitro metastasis-like phenotype.

Frontiers of optofluidics in synthetic biology

The development of optofluidic-based technology has ushered in a new era of lab-on-a-chip functionality, including miniaturization of biomedical devices, enhanced sensitivity for molecular detection, and multiplexing of optical measurements. While having great potential, optofluidic devices have only begun to be exploited in many biotechnological applications. Here, we highlight the potential of integrating optofluidic devices with synthetic biological systems, which is a field focusing on creating novel cellular systems by engineering synthetic gene and protein networks. First, we review the development of synthetic biology at different length scales, ranging from single-molecule, single-cell, to cellular population. We emphasize light-sensitive synthetic biological systems that would be relevant for the integration with optofluidic devices. Next, we propose several areas for potential applications of optofluidics in synthetic biology. The integration of optofluidics and synthetic biology would have a broad impact on point-of-care diagnostics and biotechnology.

Cystamine-terminated poly(beta-amino ester)s for siRNA delivery to human mesenchymal stem cells and enhancement of osteogenic differentiation

Enhancing human mesenchymal stem cell (hMSC) differentiation via RNA interference (RNAi) could provide an effective way of controlling cell fate for tissue engineering, but a safe and effective delivery vehicle must first be developed. Here, we evaluated an array of synthetic end-modified poly(beta-amino ester) (PBAE)-based nanoparticles to optimize siRNA delivery into hMSCs. In general, cystamine-terminated polymers caused the most knockdown, with the best polymer achieving 91% knockdown 20 days post-transfection. Binding studies revealed that the cystamine-terminated polymer bound siRNA tightly at lower weight ratios of polymer to siRNA but then efficiently released siRNA upon exposure to a reducing environment, suggesting that this class of PBAEs can form tight initial interactions with its cargo and then cause efficient, environmentally-triggered release in the cytoplasm. Finally, we tested a functional application of this system by transfecting hMSCs with siRNA against an inhibitor of osteogenesis, B-cell lymphoma (Bcl)-like protein 2 (BCL2L2). This resulted in enhanced osteogenesis over 4 weeks as evidenced by Alizarin Red S staining and calcium quantification. The bioreducible PBAE/siRNA nanoparticles developed here can provide a means of safe and effective control of hMSC differentiation for a wide variety of applications.

A Novel Technique for Micro-patterning Proteins and Cells on Polyacrylamide Gels

Spatial patterning of proteins (extracellular matrix, ECM) for living cells on polyacrylamide (PA) hydrogels has been technically challenging due to the compliant nature of the hydrogels and their aqueous environment. Traditional micro-fabrication process is not applicable. Here we report a simple, novel and general method to pattern a variety of commonly used cell adhesion molecules, i.e. Fibronectin (FN), Laminin (LN) and Collagen I (CN), etc. on PA gels. The pattern is first printed on a hydrophilic glass using polydimethylsiloxane (PDMS) stamp and micro-contact printing (μCP). Pre-polymerization solution is applied on the patterned glass and is then sandwiched by a functionalized glass slide, which covalently binds to the gel. The hydrophilic glass slide is then peeled off from the gel when the protein patterns detach from the glass, but remain intact with the gel. The pattern is thus transferred to the gel. The mechanism of pattern transfer is studied in light of interfacial mechanics. It is found that hydrophilic glass offers strong enough adhesion with ECM proteins such that a pattern can be printed, but weak enough adhesion such that they can be completely peeled off by the polymerized gel. This balance is essential for successful pattern transfer. As a demonstration, lines of FN, LN and CN with widths varying from 5-400 μm are patterned on PA gels. Normal fibroblasts (MKF) are cultured on the gel surfaces. The cell attachment and proliferation are confined within these patterns. The method avoids the use of any toxic chemistry often used to pattern different proteins on gel surfaces.

Network systems biology for targeted cancer therapies

The era of targeted cancer therapies has arrived. However, due to the complexity of biological systems, the current progress is far from enough. From biological network modeling to structural/dynamic network analysis, network systems biology provides unique insight into the potential mechanisms underlying the growth and progression of cancer cells. It has also introduced great changes into the research paradigm of cancer-associated drug discovery and drug resistance.

A whole-body model for glycogen regulation reveals a critical role for substrate cycling in maintaining blood glucose homeostasis

Timely, and sometimes rapid, metabolic adaptation to changes in food supply is critical for survival as an organism moves from the fasted to the fed state, and vice versa. These transitions necessitate major metabolic changes to maintain energy homeostasis as the source of blood glucose moves away from ingested carbohydrates, through hepatic glycogen stores, towards gluconeogenesis. The integration of hepatic glycogen regulation with extra-hepatic energetics is a key aspect of these adaptive mechanisms. Here we use computational modeling to explore hepatic glycogen regulation under fed and fasting conditions in the context of a whole-body model. The model was validated against previous experimental results concerning glycogen phosphorylase a (active) and glycogen synthase a dynamics. The model qualitatively reproduced physiological changes that occur during transition from the fed to the fasted state. Analysis of the model reveals a critical role for the inhibition of glycogen synthase phosphatase by glycogen phosphorylase a. This negative regulation leads to high levels of glycogen synthase activity during fasting conditions, which in turn increases substrate (futile) cycling, priming the system for a rapid response once an external source of glucose is restored. This work demonstrates that a mechanistic understanding of the design principles used by metabolic control circuits to maintain homeostasis can benefit from the incorporation of mathematical descriptions of these networks into “whole-body” contextual models that mimic in vivo conditions.

Homeostasis of blood glucose concentrations during circadian shifts in survival-related activities, sleep and food availability is crucial for the survival of mammals. This process depends upon glucose intake, short-term storage as glycogen, and gluconeogenesis. The integration of hepatic glycogen anabolic and catabolic dynamics with whole body energetics is critical for survival. In this paper we use computational modeling to investigate the potential survival advantage of substrate (futile) cycling of glycogen and glycogen precursors. Our simulations, combined with published experimental results of other researchers, indicate that as the body enters a state of fasting, the activity of enzymes involved in the synthesis of glycogen increases leading to increased substrate cycling. This increase in substrate cycling allows the system to respond more rapidly once new external sources of glucose become available. The whole-body computational model developed for this work allows the metabolic control circuitry to be studied under simulated in vivo conditions, providing functional insights that are not evident when individual modules of glycogen regulatory circuitry are examined in isolation.

Investigating circular dorsal ruffles through varying substrate stiffness and mathematical modeling

Circular dorsal ruffles (CDRs) are transient actin-rich ringlike structures that form on the dorsal surface of growth-factor stimulated cells. However, the dynamics and mechanism of formation of CDRs are still unknown. It has been observed that CDR formation leads to stress fibers disappearing near the CDRs. Because stress fiber formation can be modified by substrate stiffness, we examined the effect of substrate stiffness on CDR formation by seeding NIH 3T3 fibroblasts on glass and polydimethylsiloxane substrates of varying stiffnesses from 20 kPa to 1800 kPa. We found that increasing substrate stiffness increased the lifetime of the CDRs. We developed a mathematical model of the signaling pathways involved in CDR formation to provide insight into this lifetime and size dependence that is linked to substrate stiffness via Rac-Rho antagonism. From the model, increasing stiffness raised mDia1-nucleated stress fiber formation due to Rho activation. The increased stress fibers present increased replenishment of the G-actin pool, therefore prolonging Arp2/3-nucleated CDR formation due to Rac activation. Negative feedback by WAVE-related RacGAP on Rac explained how CDR actin propagates as an excitable wave, much like wave propagation in other excitable medium, e.g., nerve signal transmission.

Automated refinement and inference of analytical models for metabolic networks

The reverse engineering of metabolic networks from experimental data is traditionally a labor-intensive task requiring a priori systems knowledge. Using a proven model as a test system, we demonstrate an automated method to simplify this process by modifying an existing or related model--suggesting nonlinear terms and structural modifications--or even constructing a new model that agrees with the system's time series observations. In certain cases, this method can identify the full dynamical model from scratch without prior knowledge or structural assumptions. The algorithm selects between multiple candidate models by designing experiments to make their predictions disagree. We performed computational experiments to analyze a nonlinear seven-dimensional model of yeast glycolytic oscillations. This approach corrected mistakes reliably in both approximated and overspecified models. The method performed well to high levels of noise for most states, could identify the correct model de novo, and make better predictions than ordinary parametric regression and neural network models. We identified an invariant quantity in the model, which accurately derived kinetics and the numerical sensitivity coefficients of the system. Finally, we compared the system to dynamic flux estimation and discussed the scaling and application of this methodology to automated experiment design and control in biological systems in real time.