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At least 19 records

Permeability-Engineered Compartmentalization Enables In Vitro Reconstitution of Sustained Synthetic Biology Systems

In nature, biological compartments such as cells rely on dynamically controlled permeability for matter exchange and complex cellular activities. Likewise, the ability to engineer compartment permeability is crucial for in vitro systems to gain sustainability, robustness, and complexity. However, rendering in vitro compartments such a capability is challenging. Here, a facile strategy is presented to build permeability-configurable compartments, and marked advantages of such compartmentalization are shown in reconstituting sustained synthetic biology systems in vitro. Through microfluidics, the strategy produces micrometer-sized layered microgels whose shell layer serves as a sieving structure for biomolecules and particles. In this configuration, the transport of DNAs, proteins, and bacteriophages across the compartments can be controlled an guided by a physical model. Through permeability engineering, a compartmentalized cell-free protein synthesis system sustains multicycle protein production; ≈100 000 compartments are repeatedly used in a five-cycle synthesis, featuring a yield of 2.2 mg mL -1 . Further, the engineered bacteria-enclosing compartments possess near-perfect phage resistance and enhanced environmental fitness. In a complex river silt environment, compartmentalized whole-cell biosensors show maintained activity throughout the 32 h pollutant monitoring. It is anticipated that permeability-engineered compartmentalization should pave the way for practical synthetic biology applications such as green bioproduction, environmental sensing, and bacteria-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗

Vaccination compartmental epidemiological models for the delta and omicron SARS-CoV-2 variants

We explore the inclusion of vaccination in compartmental epidemiological models concerning the delta and omicron variants of the SARS-CoV-2 virus that caused the COVID-19 pandemic. We expand on our earlier compartmental-model work by incorporating vaccinated populations. We present two classes of models that differ depending on the immunological properties of the variant. The first one is for the delta variant, where we do not follow the dynamics of the vaccinated individuals since infections of vaccinated individuals were rare. The second one for the far more contagious omicron variant incorporates the evolution of the infections within the vaccinated cohort. We explore comparisons with available data involving two possible classes of counts, fatalities and hospitalizations. We present our results for two regions, Andalusia and Switzerland (including the Principality of Liechtenstein), where the necessary data are available. In the majority of the considered cases, the models are found to yield good agreement with the data and have a reasonable predictive capability beyond their training window, rendering them potentially useful tools for the interpretation of the COVID-19 and further pandemic waves, and for the design of intervention strategies during these waves.

60 APPLIED LIFE SCIENCES↗

Compartmentalized storage tank for electrochemical cell system

A compartmentalized storage tank is disclosed. The compartmentalized storage tank includes a housing, a first fluid storage section disposed within the housing, a second fluid storage section disposed within the housing, the first and second fluid storage sections being separated by a movable divider, and a constant force spring. The constant force spring is disposed between the housing and the movable divider to exert a constant force on the movable divider to cause a pressure P1 in the first fluid storage section to be greater than a pressure P2 in the second fluid storage section, thereby defining a pressure differential.

Piecuch, Benjamin Michael↗

3D seismic imaging of a fracture damage zone controlling reservoir compartmentalization at the Raft River EGS using multi-azimuth walkaway VSP

Accurate imaging of steeply dipping fracture zones in crystalline enhanced geothermal systems (EGS) is critical for constraining permeability architecture and guiding stimulation design. However, such structures remain poorly resolved by conventional surface seismic methods. We present a fully three-dimensional (3D) elastic-waveform inversion-migration workflow applied to multi-azimuth walkaway vertical seismic profiling (VSP) data acquired in a deviated borehole at the Raft River EGS. The workflow integrates first-arrival traveltime tomography, multi-scale elastic waveform inversion (EWI), and elastic least-squares reverse-time migration (ELSRTM) to recover high-resolution compressional-and shear-wave velocity models and to image structural discontinuities in the crystalline basement. The results reveal a laterally continuous low-velocity anomaly, with shear-wave velocity reductions of 25-30%, consistent with fractureinduced mechanical weakening. Two steeply dipping discontinuities bound a 50-80 m wide fracture damage zone. Independent constraints from microseismic clustering and geochemical compartmentalization corroborate the geometry and structural significance of this feature. Synthetic modeling further confirms that structures of this scale are resolvable (~30 m). These findings indicate that the Narrows structure is a distributed fracture damage zone rather than a discrete fault plane. By resolving fracture-zone geometry at the tens-of-meters scale using a single borehole, this workflow provides a practical and transferable approach for improving structural characterization, reducing uncertainty in permeability architecture, and supporting reservoir modeling and stimulation design in fractured crystalline EGS reservoirs.

58 GEOSCIENCES↗

Compartmental Control of UDP-Araf Supply: Golgi Lumen UDP-Arabinopyranose Mutase Depletes Plant Cell Wall Araf Linkages

L-Arabinofuranose (Araf) is a major constituent of plant cell wall polysaccharides. UDP-Araf is generated from UDP-L-arabinopyranose (UDP-Arap) by a UDP-Arap mutase (UAM) on the cytosolic face of the Golgi and then imported into the Golgi lumen for utilization by arabinosyltransferases (AraTs). Yet, a substantial fraction of UDP-Arap is synthesized in the Golgi lumen by the UDP-xylose 4-epimerase (UXE), creating a topological paradox where luminal UDP-Arap must be exported to the cytosol for conversion to UDP-Araf by UAM and then re-imported into the Golgi lumen. To test the functional significance of this compartmentation, we mislocalized Arabidopsis (Arabidopsis thaliana) UAM1 to the Golgi lumen by fusing it to the UXE1 transmembrane domain. The fusion protein was present in the Golgi, and protease-protection assays on microsomes supported its luminal orientation. In wild-type and uam1 plants, Golgi-targeted UAM1 reduced total cell wall Arabinose without consistent changes in other monosaccharides. Linkage analyses showed that this decrease reflects selective loss of Araf residues, whereas Arap remain largely unchanged, consistent with reduced UDP-Araf availability for luminal AraTs. Under salt stress, expression of Golgi-targeted UAM1 in uam1 caused root-growth inhibition and maturation-zone swelling that exogenous L-Ara failed to rescue. These results support a hypothesis that the strong thermodynamic bias of the UAM reaction toward UDP-Arap requires spatial separation of UDP-Arap production from UDP-Araf formation to sustain UDP-Araf flux into Golgi arabinosylation and avoid futile intraluminal back-conversion.

59 BASIC BIOLOGICAL SCIENCES↗

Nonparametric Inference for the Reproductive Rate in Generalized Compartmental Models

We develop a tractable nonparametric model for the time-varying reproductive rate of infectious diseases that combines the structure of a deterministic compartmental model and a stochastic model for incidence data. We use Bayesian inference to estimate, with uncertainty, the reproductive rate of the Coronavirus 2019 outbreak in the U.S. states of California, Florida, Michigan, New Mexico, New York, and Texas from January 2020 to March 2022. Employing the inferred reproductive rates, we estimate the posterior distribution of the time-varying reproduction numbers for each state. Compering the time-varying reproduction numbers across the states, we identify some epidemic waves, potentially driven from changes in human behavior and virus mutations.

97 MATHEMATICS AND COMPUTING↗

Badger COMET Compartmentalized Onboard Material Extrusion Technology

In response to the 2014 NASA Academic Innovation Challenge, the University of Wisconsin – Madison team presents the design of a collapsible Fused Deposition Modeling (FDM) system for in situ manufacturing in a space habitat environment, the Badger Compartmentalized Onboard Material Extrusion Technology (COMET). The proposed mechanism incorporates one year of design and testing on an array of current additive manufacturing techniques, with the goal of providing a reliable and maintainable manufacturing solution. Seven Level 1 requirements were employed to guide the design process, based on information in the challenge, communications with NASA, and the evolving systems feedback of project work groups. These requirements provided a baseline for the development of the System Requirements Document (SRD, Appendix I), which framed the design of the system. The design requirements deemed critical to the success of the systems are as follows: - The system shall compose an FDM workstation capable of producing parts within industry standard tolerances. - The system shall reduce to a minimum of 50 percent or less of its deployed volume when not in use, and must collapse without the need for disassembly. - The system shall meet all relevant NASA safety and functional standards. The final design for the Badger COMET was selected from multiple design iterations, which balanced the critical design requirements listed above with system reliability, with the final goal of providing a minimal system weight. The system collapses in the vertical direction, allowing for a maximum reduction in volume. Guide rods and precision, anti-backlash lead screws provide all linear movement in the device. Stepper motors were chosen to actuate each system axis, due to their high precision and repeatable accuracy. The system is controlled through an on-board computer system and embedded electronics package.

Frederick T. Elder↗

Sequential membrane- and protein-bound organelles compartmentalize genomes during phage infection

Many eukaryotic viruses require membrane-bound compartments for replication, but no such organelles are known to be formed by prokaryotic viruses. Bacteriophages of the Chimalliviridae family sequester their genomes within a phage-generated organelle, the phage nucleus, which is enclosed by a lattice of the viral protein ChmA. We show that inhibiting phage nucleus formation arrests infections at an early stage in which the injected phage genome is enclosed within a membrane-bound early phage infection (EPI) vesicle. Early phage genes are expressed from the EPI vesicle, demonstrating its functionality as a prokaryotic, transcriptionally active, membrane-bound organelle. We also show that the phage nucleus is essential, with genome replication beginning after the injected DNA is transferred from the EPI vesicle to the phage nucleus. Our results show that Chimalliviridae require two sophisticated subcellular compartments of distinct compositions and functions that facilitate successive stages of the viral life cycle.

59 BASIC BIOLOGICAL SCIENCES↗