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Microrheology based on video microscopy of embedded tracer particles has the potential to be used for high-throughput protein-based materials characterization. This potential is due to a number of characteristics of the techniques, including the suitability for measurement of low sample volumes, noninvasive and noncontact measurements, and the ability to set up a large number of samples for facile, sequential measurement. In addition to characterization of the bulk rheological properties of proteins in solution, for example, viscosity, microrheology can provide insight into the dynamics and self-assembly of protein-based materials as well as heterogeneities in the microenvironment being probed. Specifically, passive microrheology in the form of multiple particle tracking and differential dynamic microscopy holds promise for applications in high-throughput characterization because of the lack of user interaction required while making measurements. Herein, recent developments in the use of multiple particle tracking and differential dynamic microscopy are reviewed for protein characterization and their potential to be applied in a high-throughput, automatable setting.

Transmission electron microscopy (TEM) is being pushed to new capabilities which enable studies on systems that were previously out of reach. Among recent innovations, TEM through liquid cells (LC-TEM) enables in operando observation of biological phenomena. This work applies LC-TEM to the study of biological components as they interact on an abiotic surface. Specifically, analytes or target molecules like neuropeptide Y (NPY) are observed in operando on functional graphene field-effect transistor (GFET) biosensors. Biological recognition elements (BREs) identified using biopanning with affinity to NPY are used to functionalize graphene to obtain selectivity. On working devices capable of achieving picomolar responsivity to neuropeptide Y, LC-TEM reveals translational motion, stochastic positional fluctuations due to constrained Brownian motion, and rotational dynamics of captured analyte. Coupling these observations with the electrical responses of the GFET biosensors in response to analyte capture and/or release will potentially enable new insights leading to more advanced and capable biosensor designs.

Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing mechanical and biological properties in living hydrogels—for example gel time of the hydrogel formulation and viability of the embedded organisms—can be challenging. In this work, a pipeline is developed to automate characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli—formulated from within a 4D parameter space—are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between AI-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 minutes, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties—at least over a finite range—while maintaining biological activity.

Microbes embedded in hydrogels comprise one form of living material. Discovering formulations that balance potentially competing for mechanical and biological properties in living hydrogels-for example, gel time of the hydrogel formulation and viability of the embedded organisms-can be challenging. In this study, a pipeline is developed to automate the characterization of the gel time of hydrogel formulations. Using this pipeline, living materials comprised of enzymatically crosslinked silk and embedded E. coli-formulated from within a 4D parameter space-are engineered to gel within a pre-selected timeframe. Gelation time is estimated using a novel adaptation of microrheology analysis using differential dynamic microscopy (DDM). In order to expedite the discovery of gelation regime boundaries, Bayesian machine learning models are deployed with optimal decision-making under uncertainty. The rate of learning is observed to vary between artificial intelligence (AI)-assisted planning and human planning, with the fastest rate occurring during AI-assisted planning following a round of human planning. For a subset of formulations gelling within a targeted timeframe of 5-15 min, fluorophore production within the embedded cells is substantially similar across treatments, evidencing that gel time can be tuned independent of other material properties-at least over a finite range-while maintaining biological activity.

This work describes an enhancement to the loop-mediated isothermal amplification (LAMP) reaction which results in improved performance. Enhancement is achieved by adding a new set of primers to conventional LAMP reactions. These primers are termed "swarm primers" based on their relatively high concentration and their ability to create new amplicons despite the theoretical lack of single-stranded annealing sites. The primers target a region upstream of the FIP/BIP primer recognition sequences on opposite strands, substantially overlapping F1/B1 sites. Thus, despite the addition of a new primer set to an already complex assay, no significant increase in assay complexity is incurred. Swarm priming is presented for three DNA templates: Lambda phage, Synechocystis sp. PCC 6803 rbcL gene, and human HFE. The results of adding swarm primers to conventional LAMP reactions include increased amplification speed, increased indicator contrast, and increased reaction products. For at least one template, minor improvements in assay repeatability are also shown. In addition, swarm priming is shown to be effective at increasing the reaction speed for RNA amplification via RT-LAMP. Collectively, these results suggest that the addition of swarm primers will likely benefit most if not all existing LAMP assays based on state-of-the-art, six-primer reactions.

A synthetic regulatory construct based on a two-stage amplifying promoter cascade is applied to whole-cell biosensing. Green fluorescent protein (GFP) and red fluorescent protein (RFP) enable two-component tracking of the response event, enabling the system to exhibit increased sensitivity, a lower limit of detection, and a unique optical density-free assessment mode. Specifically, the recA and tac promoters are linked by the LacI repressor in Escherichia coli, where DNA-damage activates the recA promoter and the up-regulation of GFP and LacI proteins. LacI represses the tac promoter, down-regulating the otherwise constitutive mCherry transcription. The response of the construct was compared with two singly tagged, conventional recA promoter-reporter constructs: recA::gfpmut3.1 and recA::mCherry. Using a miniature LED-based flow-through optical detector developed for remote sensing applications, limits of detection for the dual reporter construct reached as low as 0.1 nM MMC. By comparison, single-ended reporters recA::mCherry and recA::gfpmut3.1 achieved best limits of detection of 0.25 nM and 2.0 nM, respectively. An approach to three-component optical analysis, based on a system of detectors with coupled calibration equations enables accurate assessments of the red fluorescence, green fluorescence, and biomass of sensor cell suspensions. The system approach is effective at overcoming interferences caused by optically dense samples and overlapping fluorescence spectra. Such a technique may be useful in studying the biological mechanisms which underlie the synthetic regulatory device of this work and others.

A miniature flow-through optical cell has been developed with the potential for integration into a stand-alone, potentially disposable whole-cell biosensor platform. The compact and inexpensive optical system is comprised of closely coupled light-emitting diodes (LEDs), light-to-frequency (LTF) photodiodes, and celluloid filters. The system has been optimized to measure fluorescent reporters produced by cultures of biosensor cells in liquid suspension. As demonstration subjects, Escherichia coli cells carrying medium-copy plasmids with fluorescent reporter fusions to the rec promoter were exposed to the DNA-damaging agent mitomycin C (MMC). As reporter proteins, green fluorescent protein (GFP) and red fluorescent protein (RFP) were compared for suitability in the compact instrument. The RFP mCherry outperformed GFP (GFPmut3.1) as a reporter protein in the developed system on two counts. First, measurement distortions due to high optical density suspensions are minimal using RFP compared to GFP. Second, the limit of detection for MMC is estimated at 0.25 nM for recA::mCherry and 2.0 nM for recA::gfpmut3.1. Finally, a measurement method is presented whereby multiple channels of optical data are calibrated in an integrated fashion to allow simultaneous measurement of fluorescence and biomass concentration. The method substantially eliminates optical distortions due to dense samples and thus obviates the conventional need for sample dilution prior to measurement.

One well-developed paradigm for biosensing uses living microorganisms as sensors for environmental stimuli. In this paradigm, engineered cells contain plasmid or chromosomal sequences that link stress-inducible promoters to the production of fluorescent reporter proteins. We are developing such a sensor system with an aim for portability. This work describes the development and performance of a compact optical system designed for low-power detection of fluorescent reporter proteins in microliter-scale cell suspensions. Light-emitting diodes (LEDs) and silicon photodetectors (PDs) were configured to measure red fluorescence, green fluorescence, and cell biomass pseudo-simultaneously in 100 mul samples. The optical detectors were calibrated using E. coli cells that expressed red and green fluorescent proteins (dsRed2 and gfp-asv, Clontech) either constitutively or through chemical induction. We show that sufficient sensitivity for certain whole-cell biosensor applications is achievable in low-volume samples, despite the simplicity and low-cost nature of the detector system. The prototype optical detector occupies approximately 1.8 cmtimes2.2 cmtimes3.0 cm

Metabolic changes of a continuously-fed bacterial microculture are monitored as a potential means of understanding the effects of the space environment on life. A hand-held plastic device supports and monitors the metabolism of a 100 /spl mu/l microculture of E. coli. Both a semipermeable microdialysis fiber and a gas-permeable microbore silicone hollow fiber membrane (HFM) are threaded through the microculture. Microliter quantity solutions flow through the lumen of the microdialysis fiber to extract metabolic wastes and to deliver nutrients. A carbon dioxide absorbance-based indicator flows through the lumen of the silicone HFM to supply oxygen, remove carbon dioxide, and monitor carbon dioxide production. Carbon dioxide production, which is tracked as an indicator of metabolic response, is monitored with an optical sensor that has a response time of 15 minutes and a sensitivity of /spl plusmn/0.6 mmHg. We evaluated the device using ultraviolet light as a test stressor for the instrumentation. We were able to detect changes in metabolic activity by varying dialysis feed rate and stressing the cells with UV.

High frequency tone bursts of ultrasound are capable of suppressing and enhancing peripheral nerve action potential events. An in vitro frog sciatic nerve preparation was used as a biological model. The peak intensity of the sound delivered to the nerve was 150-200 W/cm/sup 2/. Tone bursts consisted of 0.5 to 75 ms pulses delivered at a rate of 1-10 Hz and had center frequencies between 17 and 20 MHz.