Biology subjects
Publications and source records attributed to Moghimianavval, H..
We present a membrane-associated, cell-free biosensing reporter based on rapalog-induced split sfCherry reconstitution. Rapalog increased fluorescence in solution, lipid vesicles, and supported lipid bilayers. Antibodies binding to epitope tags near the dimerization interface reduced the fluorescence signal, consistent with steric interference with reporter assembly.
The laboratory Escherichia coli K-12 strain has doubled no faster than [~]20 minutes for decades. This plateau could reflect a biophysical limit or simply the way batch culture selects on growth rate. Here we show it can be broken through amplified selection with a Red Queen gene circuit, which takes advantage of growth rate heterogeneity in monoclonal populations to selectively suppress slow-growing cells and creates a tunable mapping from intrinsic growth rate to survival. After 70 days ([~]1,000 generations) of amplified selection in MG1655+FHr and subsequent removal of the circuit, a top evolved clone (RQ70) reached a maximum specific growth rate of 2.61 h-{superscript 1} in shake-flask culture. This corresponds to a doubling time of 15.9 minutes, to our knowledge the shortest reported for E. coli K-12, against 18.1 minutes for evolved controls and 20.3 minutes for the ancestor. The gain came at the cost of a [~]3-fold increase in lag time, indicating that the 20-minute plateau is a multi-trait optimum under conventional batch selection rather than an absolute constraint. We argue that synthetic gene circuits can therefore reshape the evolutionary process itself, pushing performance beyond apparent physiological limits.
Cytoplasmic abundant heat-soluble (CAHS) proteins, a stress-responsive intrinsically disordered protein from tardigrades, have been discovered to form gel-like networks providing structural support during dehydration, thus enabling anhydrobiosis. However, the mechanism by which CAHS proteins protect the dehydrating cellular membrane remains enigmatic. Using giant unilamellar vesicles (GUVs) as a model membrane system, we show that encapsulated CAHS12 undergoes a reversible structural transformation that reinforces membrane integrity and preserves encapsulated components, mimicking natural anhydrobiosis. CAHS12-containing GUVs demonstrated stability for weeks and mechanical robustness under dehydration, elevated temperature, and osmotic stresses. Molecular simulations suggest that CAHS12 forms a filamentous network within the vesicle lumen that mitigates membrane collapse and preserves compartmental architecture. Synthetic cells with cell-free transcription-translation capabilities withstand desiccation and recover biochemical activities, akin to the tun state of the tardigrade. This discovery opens up synthetic cell applications in bioengineering, cold-chain-independent biomanufacturing, and adaptive biointerfaces.
Classification of high-dimensional information is a ubiquitous computing paradigm across diverse biological systems, including organs such as the brain, down to signaling between individual cells. Inspired by the success of artificial neural networks in machine learning, the idea of engineering genetic circuits that operate as neural networks emerges as a strategy to expand the classification capabilities of living systems. In this work, we design these biomolecular neural networks (BNNs) based on the molecular sequestration reaction, and experimentally characterize their behavior as linear classifiers for increasing levels of complexity. Initially, we demonstrate that a static, DNA-based system can effectively prototype a linear classifier, though we also identify its limitations to easily tune the slope of the decision boundary it generates. We then propose and experimentally validate a BNN at the protein level using a cell-free transcription-translation (TXTL) system, which overcomes the DNA-based systems limitation and behaves as a linear classifier even before it reaches its steady state (or, equivalently, out-of-equilibrium). Ultimately, we test a CRISPR-based design and its out-of-equilibrium behavior in a biological context by successfully constructing a linear classifier within mammalian cells. Overall, by leveraging mathematical modeling and experimental automation, we establish molecular sequestration as a universal scheme for implementing neural networks within living systems, paving the way for transformative advances in synthetic biology and programmable biocomputing systems.
Synthetic cells offer a versatile platform for addressing biomedical and environmental challenges, due to their modular design and capability to mimic cellular processes such as biosensing, intercellular communication, and metabolism. Constructing synthetic cells capable of stimuli-responsive secretion is vital for applications in targeted drug delivery and biosensor development. Previous attempts at engineering secretion for synthetic cells have been confined to non-specific cargo release via membrane pores, limiting the spatiotemporal precision and specificity necessary for selective secretion. Here, we designed and constructed a protein-based platform termed TEV Protease-mediated Releasable Actin-binding protein (TRAP) for selective, rapid, and triggerable secretion in synthetic cells. TRAP is designed to bind tightly to reconstituted actin networks and is proteolytically released from bound actin, followed by secretion via cell-penetrating peptide membrane translocation. We demonstrated TRAPs efficacy in facilitating light-activated secretion of both fluorescent and luminescent proteins. By equipping synthetic cells with a controlled secretion mechanism, TRAP paves the way for the development of stimuli-responsive biomaterials, versatile synthetic cell-based biosensing systems, and therapeutic applications through the integration of synthetic cells with living cells for targeted delivery of protein therapeutics.
Constructing molecular classifiers that enable cells to recognize linear and non-linear input patterns would expand the biocomputational capabilities of engineered cells, thereby unlocking their potential in diagnostics and therapeutic applications. While several biomolecular classifier schemes have been designed, the effect of biological constraints such as resource limitation and competitive binding on the function of those classifiers has been left unexplored. Here, we first demonstrate the design of a sigma factor-based perceptron as a molecular classifier working on the principles of molecular sequestration between the sigma factor and its anti-sigma molecule. We then investigate how the output of the biomolecular perceptron, i.e., its response pattern or decision boundary, is affected by the competitive binding of sigma factors to a pool of shared and limited resources of core RNA polymerase. Finally, we reveal the influence of sharing limited resources on multi-layer perceptron neural networks and outline design principles that enable the construction of non-linear classifiers using sigma-based biomolecular neural networks in the presence of competitive resource-sharing effects.
Cell signaling through direct physical cell-cell contacts plays vital roles in biology during development, angiogenesis, and immune response. Intercellular communication mechanisms between synthetic cells constructed from the bottom up are majorly reliant on diffusible chemical signals, thus limiting the range of responses in receiver cells. Engineering contact-dependent signaling between synthetic cells promises to unlock more complicated signaling schemes with different types of responses. Here, we design and demonstrate a light-activated contact-dependent communication tool for synthetic cells. We utilize a split bioluminescent protein to limit signal generation exclusively to contact interfaces of synthetic cells, driving the recruitment of a photoswitchable protein in receiver cells, akin to juxtacrine signaling in living cells. Our modular design not only demonstrates contact-dependent communication between synthetic cells but also provides a platform for engineering orthogonal contact-dependent signaling mechanisms.
In cells, membrane fusion is mediated by SNARE proteins, whose activities are calcium-dependent. While several non-native membrane fusion mechanisms have been demonstrated, few can respond to external stimuli. Here, we develop a calcium-triggered DNA-mediated membrane fusion strategy where fusion is regulated using surface-bound PEG chains that are cleavable by the calcium-activated protease calpain-1.
Engineering synthetic interfaces between membranes has potential applications in designing non-native cellular communication pathways and creating synthetic tissues. Here, InterSpy is introduced as a synthetic biology tool consisting of a heterodimeric protein engineered to form and maintain membrane-membrane interfaces between apposing synthetic as well as cell membranes through SpyTag/SpyCatcher interaction. Inclusion of split fluorescent protein fragments in the designed InterSpy toolkit allows tracking the formation of membrane-membrane interface and reconstitution of functional fluorescent protein in the space between apposing membranes. We first demonstrate InterSpy by testing split protein designs using a mammalian cell-free expression system. By utilizing co-translational helix insertion, cell-free synthesized InterSpy fragments are incorporated into the membrane of liposomes and supported lipid bilayers with a desired topology. Functional reconstitution of split fluorescent protein between the membranes is strictly dependent on SpyTag/SpyCatcher. Finally, since InterSpy is fully genetically encoded, the engineered system is adapted to cells and showcased. InterSpy demonstrates the power of cell-free expression systems in functional reconstitution of synthetic membrane interfaces via proximity-inducing proteins. This technology may also prove useful for synthetic biology where cell-cell contacts and communication are recreated in a controlled manner using minimal components.
Cell shape changes from locomotion to cytokinesis are, to a large extent, driven by myosin-driven remodeling of cortical actin patterns. Passive crosslinkers such as -actinin and fascin as well actin nucleator Arp2/3 complex largely determine the architecture and connectivity of actin network patterns; consequently, they regulate network remodeling and membrane shape changes. Membrane constriction in animal cell cytokinesis proceeds by assembly and contraction of a contractile ring pattern rich in -actinin and myosin at the equator of the cell cortex, with which the ring is contiguous. Here we reconstitute actomyosin networks inside cell-sized lipid bilayer vesicles and show that, depending on vesicle size and concentrations of -actinin and fascin, actomyosin networks assemble into ring and aster-like patterns. Anchoring actin to the membrane enhances the interaction of the contractile networks with lipid membrane but does not change the architecture of the patterns. A membrane-bound actomyosin ring exerts force and constricts the membrane. An Arp2/3 complex-mediated actomyosin cortex is shown to assemble a ring-like pattern at the equatorial cortex and contribute to myosin-driven clustering of the cortex and consequently membrane deformation. An active gel theory unifies a model for the observed membrane constriction and protrusion induced by the membrane-bound actomyosin networks.