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1. In situ genetically targeted chemical assembly of polymers on living neuronal membranes

   Anqi Zhang, Kang Yong ( December 2022 , bioRxiv)

   Multicellular biological systems, most notably living neural networks, exhibit highly complex physical organization properties that pose challenges for building cell-specific and biocompatible interfaces. We developed a novel approach to genetically program cells to chemically assemble artificial structures that modify the electrical properties of neurons in situ, opening up the possibility of minimally-invasive cell-specific interfaces with neural circuits in living animals. However, the efficiency and biocompatibility of this approach were challenged by limited membrane targeting of the constructed material. Here, we report a method with significantly improved molecular construct properties, which expresses highly localized enzymes targeted to the plasma membrane of primary neurons with minimal intracellular retention. Polymers synthesized in situ by this approach form dense clusters on the targeted cell membrane, and neurons remain viable after polymerization. This platform can be readily extended to incorporate a broad range of materials onto the surface membranes of specific cells within complex tissues, using chemistry that may further enable the next generation of interfaces with living biological systems. 

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2. Genetically-encoded photosensitizers enable light-controlled polymerization on living neuronal membranes

   Anqi Zhang, Chandan S. ( December 2022 , bioRxiv)

   The ability to record, stimulate, and modify brains of living animals would unlock numerous research opportunities and create potential clinical interventions, but it is difficult to interface with a living neural network without damaging it. We previously reported a novel approach to building neural interfaces, namely: genetically programming cells to build artificial structures to modify the electrical properties of neurons in situ, which opens up the possibility of modifying neural circuits in living animals without surgery. However, the spatiotemporal resolution, efficiency, and biocompatibility of this approach were still limited and lacked selectivity on cell membrane. Here, we demonstrate an approach using genetically-targeted photosensitizers to instruct living cells to synthesize functional materials directly on the plasma membrane under the control of light. Polymers synthesized by this approach were selectively deposited on the membrane of targeted live neurons. This platform can be readily extended to incorporate a broad range of light-controlled reactions onto specific cells, which may enable researchers to grow seamless, dynamic interfaces directly in living animals. 

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3. Controlling Polymer Material Structure during Reaction-Induced Phase Transitions

   https://doi.org/10.1021/accountsmr.3c00071  

   Hickey, Robert J. ( September 2023 , Accounts of Materials Research)

   Living systems are composed of a select number of biopolymers and minerals yet exhibit an immense diversity in materials properties. The wide-ranging characteristics, such as enhanced mechanical properties of skin and bone, or responsive optical properties derived from structural coloration, are a result of the multiscale, hierarchical structure of the materials. The fields of materials and polymer chemistry have leveraged equilibrium concepts in an effort to mimic the structure complex materials seen in nature. However, realizing the remarkable properties in natural systems requires moving beyond an equilibrium perspective. An alternative method to create materials with multiscale structures is to approach the issue from a kinetic perspective and utilize chemical processes to drive phase transitions. This Account features an active area of research in our group, reaction-induced phase transitions (RIPT), which uses chemical reactions such as polymerizations to induce structural changes in soft material systems. Depending on the type of phase transition (e.g., microphase versus macrophase separation), the resulting change in state will occur at different length scales (e.g., nm – μm), thus dictating the structure of the material. For example, the in situ formation of either a block copolymer or a homopolymer initially in a monomer mixture during a polymerization will drive nanoscale or macroscale transitions, respectively. Specifically, three different examples utilizing reaction-driven phase changes will be discussed: 1) in situ polymer grafting from block copolymers, 2) multiscale polymer nanocomposites, and 3) Lewis adduct-driven phase transitions. All three areas highlight how chemical changes via polymerizations or specific chemical binding result in phase transitions that lead to nanostructural and multiscale changes. Harnessing kinetic chemical processes to promote and control material structure, as opposed to organizing pre-synthesized molecules, polymers, or nanoparticles within a thermodynamic framework, is a growing area of interest. Trapping nonequilibrium states in polymer materials has been primarily focused from a polymer chain conformation viewpoint in which synthesized polymers are subjected to different thermal and processing conditions. The impact of reaction kinetics and polymerization rate on final polymer material structure is starting to be recognized as a new way to access different morphologies not available through thermodynamic means. Furthermore, kinetic control of polymer material structure is not specific to polymerizations and encompasses any chemical reaction that induce morphology transitions. Kinetically driven processes to dictate material structure directly impact a broad range of areas including separation membranes, biomolecular condensates, cell mobility, and the self-assembly of polymers and colloids. Advancing polymer material syntheses using kinetic principles such as RIPT opens new possibilities for dictating material structure and properties beyond what is currently available with traditional self-assembly techniques. 

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4. Development of a PointNet for Detecting Morphologies of Self-Assembled Block Oligomers in Atomistic Simulations

   Shen, Z. ; Sun, Y. ; Lodge, T.P. ; Siepmann, J.I. ( May 2021 , The journal of physical chemistry)

   ABSTRACT: Molecular simulations with atomistic or coarse- 6 grained force fields are a powerful approach for understanding and 7 predicting the self-assembly phase behavior of complex molecules. 8 Amphiphiles, block oligomers, and block polymers can form 9 mesophases with different ordered morphologies describing the 10 spatial distribution of the blocks, but entirely amorphous nature for 11 local packing and chain conformation. Screening block oligomer 12 chemistry and architecture through molecular simulations to find 13 promising candidates for functional materials is aided by effective 14 and straightforward morphology identification techniques. Captur- 15 ing 3-dimensional periodic structures, such as ordered network 16 morphologies, is hampered by the requirement that the number of 17 molecules in the simulated system and the shape of the periodic simulation box need to be commensurate with those of the resulting 18 network phase. Common strategies for structure identification include structure factors and order parameters, but these fail to 19 identify imperfect structures in simulations with incorrect system sizes. Building upon pioneering work by DeFever et al. [Chem. Sci. 20 2019, 10, 7503−7515] who implemented a PointNet (i.e., a neural network designed for computer vision applications using point 21 clouds) to detect local structure in simulations of single-bead particles and water molecules, we present a PointNet for detection of 22 nonlocal ordered morphologies of complex block oligomers. Our PointNet was trained using atomic coordinates from molecular 23 dynamics simulation trajectories and synthetic point clouds for ordered network morphologies that were absent from previous 24 simulations. In contrast to prior work on simple molecules, we observe that large point clouds with 1000 or more points are needed 25 for the more complex block oligomers. The trained PointNet model achieves an accuracy as high as 0.99 for globally ordered 26 morphologies formed by linear diblock, linear triblock, and 3-arm and 4-arm star-block oligomers, and it also allows for the discovery 27 of emerging ordered patterns from nonequilibrium systems. 

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5. Functional Interdependence in Coupled Dissipative Structures: Physical Foundations of Biological Coordination

   https://doi.org/10.3390/e23050614  

   De Bari, Benjamin ; Paxton, Alexandra ; Kondepudi, Dilip K. ; Kay, Bruce A. ; Dixon, James A. ( May 2021 , Entropy)

   null (Ed.)

   Coordination within and between organisms is one of the most complex abilities of living systems, requiring the concerted regulation of many physiological constituents, and this complexity can be particularly difficult to explain by appealing to physics. A valuable framework for understanding biological coordination is the coordinative structure, a self-organized assembly of physiological elements that collectively performs a specific function. Coordinative structures are characterized by three properties: (1) multiple coupled components, (2) soft-assembly, and (3) functional organization. Coordinative structures have been hypothesized to be specific instantiations of dissipative structures, non-equilibrium, self-organized, physical systems exhibiting complex pattern formation in structure and behaviors. We pursued this hypothesis by testing for these three properties of coordinative structures in an electrically-driven dissipative structure. Our system demonstrates dynamic reorganization in response to functional perturbation, a behavior of coordinative structures called reciprocal compensation. Reciprocal compensation is corroborated by a dynamical systems model of the underlying physics. This coordinated activity of the system appears to derive from the system’s intrinsic end-directed behavior to maximize the rate of entropy production. The paper includes three primary components: (1) empirical data on emergent coordinated phenomena in a physical system, (2) computational simulations of this physical system, and (3) theoretical evaluation of the empirical and simulated results in the context of physics and the life sciences. This study reveals similarities between an electrically-driven dissipative structure that exhibits end-directed behavior and the goal-oriented behaviors of more complex living systems. 

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