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.

Wearable electronics with real-time biosensing capabilities are very important for future applications in monitoring and augmenting human health and performance. Graphene-based potentiometric sensing offers a route for developing wearable sensors that can selectively sense biomarkers in biofluids such as sweat and saliva. This manuscript studies the sensitivity of potentiometric sensors made with graphene-based electrolyte-gated field-effect transistors (GFETs). Selectivity in the sensor toward a nanoscale biomarker, neuropeptide Y (NPY), was achieved by functionalizing graphene with a peptide-based biorecognition element. The sensors were then characterized extensively by varying concentrations of NPY in a complex medium containing artificial sweat with varying ionic concentrations and pH. This medium, therefore, emulated the response of the sensor to biomarkers in a physiologically relevant condition approaching a real-world scenario. Analysis using Gouy−Chapman−Stern theory for the liquid−solid interface at nanoscale highlighted important features of potentiometric sensing such as log-linear response and charge screening effects in GFET sensors.

A high-throughput microrheological assay is employed to assess the gelation kinetics of a coiled-coil protein, Q, across a compositional space with varying ionic strengths and pH values. Two methods of passive microrheologymultiple particle tracking (MPT) and differential dynamic microscopy (DDM)are used to determine mean-squared displacements of tracer beads embedded in protein solutions with respect to lag time over a fixed period. MPT data was analyzed to determine gelation kinetics in a high-throughput, automatable manner by fitting relaxation exponents to sigmoidal curves and verifying with the more traditionally used time-cure superposition. DDM-determined gelation time was assessed as the last resolvable time, which we found to be on a similar scale to gelation times given by MPT. Both methods show distinct advantages with regard to being used in a highthroughput, automatable setup; DDM can serve as an effective initial screen for rapid gelation kinetics due to it requiring less user intervention and inputs, with MPT giving a more complete understanding of the entire gelation process. Using these methods, a clear optimum for rapid gelation was observed near the isoelectric point of Q and at higher ionic strengths over the compositional space studied.

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 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.