A nutrient-specific gut hormone arbitrates between courtship and feeding.

Animals must set behavioural priority in a context-dependent manner and switch from one behaviour to another at the appropriate moment1-3. Here we probe the molecular and neuronal mechanisms that orchestrate the transition from feeding to courtship in Drosophila melanogaster. We find that feeding is prioritized over courtship in starved males, and the consumption of protein-rich food rapidly reverses this order within a few minutes. At the molecular level, a gut-derived, nutrient-specific neuropeptide hormone-Diuretic hormone 31 (Dh31)-propels a switch from feeding to courtship. We further address the underlying kinetics with calcium imaging experiments. Amino acids from food acutely activate Dh31+ enteroendocrine cells in the gut, increasing Dh31 levels in the circulation. In addition, three-photon functional imaging of intact flies shows that optogenetic stimulation of Dh31+ enteroendocrine cells rapidly excites a subset of brain neurons that express Dh31 receptor (Dh31R). Gut-derived Dh31 excites the brain neurons through the circulatory system within a few minutes, in line with the speed of the feeding-courtship behavioural switch. At the circuit level, there are two distinct populations of Dh31R+ neurons in the brain, with one population inhibiting feeding through allatostatin-C and the other promoting courtship through corazonin. Together, our findings illustrate a mechanism by which the consumption of protein-rich food triggers the release of a gut hormone, which in turn prioritizes courtship over feeding through two parallel pathways.

Single-chain heteropolymers transport protons selectively and rapidly.

Precise protein sequencing and folding are believed to generate the structure and chemical diversity of natural channels1,2, both of which are essential to synthetically achieve proton transport performance comparable to that seen in natural systems. Geometrically defined channels have been fabricated using peptides, DNAs, carbon nanotubes, sequence-defined polymers and organic frameworks3-13. However, none of these channels rivals the performance observed in their natural counterparts. Here we show that without forming an atomically structured channel, four-monomer-based random heteropolymers (RHPs)14 can mimic membrane proteins and exhibit selective proton transport across lipid bilayers at a rate similar to those of natural proton channels. Statistical control over the monomer distribution in an RHP leads to segmental heterogeneity in hydrophobicity, which facilitates the insertion of single RHPs into the lipid bilayers. It also results in bilayer-spanning segments containing polar monomers that promote the formation of hydrogen-bonded chains15,16 for proton transport. Our study demonstrates the importance of the adaptability that is enabled by statistical similarity among RHP chains and of the modularity provided by the chemical diversity of monomers, to achieve uniform behaviour in heterogeneous systems. Our results also validate statistical randomness as an unexplored approach to realize protein-like behaviour at the single-polymer-chain level in a predictable manner.

A pro-reparative bioelectronic device for controlled delivery of ions and biomolecules.

Wound healing is a complex physiological process that requires precise control and modulation of many parameters. Therapeutic ion and biomolecule delivery has the capability to regulate the wound healing process beneficially. However, achieving controlled delivery through a compact device with the ability to deliver multiple therapeutic species can be a challenge. Bioelectronic devices have emerged as a promising approach for therapeutic delivery. Here, we present a pro-reparative bioelectronic device designed to deliver ions and biomolecules for wound healing applications. The device incorporates ion pumps for the targeted delivery of H+ and zolmitriptan to the wound site. In vivo studies using a mouse model further validated the device's potential for modulating the wound environment via H+ delivery that decreased M1/M2 macrophage ratios. Overall, this bioelectronic ion pump demonstrates potential for accelerating wound healing via targeted and controlled delivery of therapeutic agents to wounds. Continued optimization and development of this device could not only lead to significant advancements in tissue repair and wound healing strategies but also reveal new physiological information about the dynamic wound environment.

Correlating Ionic Conductivity and Microstructure in Polyelectrolyte Hydrogels for Bioelectronic Devices.

Hydrogels have become the material of choice in bioelectronic devices because their high-water content leads to efficient ion transport and a conformal interface with biological tissue. While the morphology of hydrogels has been thoroughly studied, systematical studies on their ionic conductivity are less common. Here, an easy-to-implement strategy is presented to characterize the ionic conductivity of a series of polyelectrolyte hydrogels with different amounts of monomer and crosslinker and correlate their ionic conductivity with microstructure. Higher monomer increases the ionic conductivity of the polyelectrolyte hydrogel due to the increased charge carrier density, but also leads to excessive swelling that may cause device failure upon integration with bioelectronic devices. Increasing the amount of crosslinker can reduce the swelling ratio by increasing the crosslinking density and reducing the mesh size of the hydrogel, which cuts down the ionic conductivity. Further investigation on the porosity and tortuosity of the swollen hydrogels correlates the microstructure with the ionic conductivity. These results are generalizable for various polyelectrolyte hydrogel systems with other ions as the charge carrier and provide facile guidance to design polyelectrolyte hydrogel with desired ionic conductivity and microstructure for applications in bioelectronic devices.

Morphology and organization of the internal shell of Ariolimax californicus (Gastropoda; Stylommatophora), an asymmetric two-face biomineralized matrix.

A slug is a shell-less terrestrial gastropod mollusk. During evolution, slugs have lost their mineralized external shell but some of them have retained an internal shell (IS). Unlike external shells, which have been widely investigated, the ISs have been poorly studied. We report for the first time the compositional and complete morphological characterization of Ariolimax californicus' IS. According to literature, this shell calcifies and decalcifies depending on the animal's needs. Its composition is mostly organic, consisting of proteins and ß-chitin. The internal shell is organized in layers and membranes in which CaCO3 crystal formation occurs in specific areas. In the two faces of the IS we observed different morphologies and aggregations of calcite bio-crystals along with a different organization of the organic matrix. Dorsally, the mineral forms a thick layer composed of misaligned crystal aggregates of large dimensions, separated by thin organic layers. This suggests a protective purpose and the use of this layer as a long-term calcium storage system. Ventrally, the mineral phase is organized in small crystal aggregates of comparable size, separated by thin organic layers, and quite aligned one to the other. The whole ventral mineral layer is covered by a membrane, identified as the hypostracum. This face is proposed to be a short-term calcium storage system. In vitro crystallization experiments suggest massive calcium ions sequestration from the solution for the precipitation of calcite crystals inside the organic matrix. In conclusion, this research provides new information on the dynamic of biomineralization on mollusk evolved in calcium-poor environments.

Diverse Proton-Conducting Nanotubes via a Tandem Macrocyclization and Assembly Strategy.

Macrocycles that assemble into nanotubes exhibit emergent properties stemming from their low dimensionality, structural regularity, and distinct interior environments. We report a versatile strategy to synthesize diverse nanotube structures in a single, efficient reaction by using a conserved building block bearing a pyridine ring. Imine condensation of a 2,4,6-triphenylpyridine-based diamine with various aromatic dialdehydes yields chemically distinct pentagonal [5 + 5], hexagonal [3 + 3], and diamond-shaped [2 + 2] macrocycles depending on the substitution pattern of the aromatic dialdehyde monomer. Atomic force microscopy and in solvo X-ray diffraction demonstrate that protonation of the macrocycles under the mild conditions used for their synthesis drives assembly into high-aspect ratio nanotubes. Each of the pyridine-containing nanotube assemblies exhibited measurable proton conductivity by electrochemical impedance spectroscopy, with values as high as 10-3 S m-1 (90% R.H., 25 °C) that we attribute to differences in their internal pore sizes. This synthetic strategy represents a general method to access robust nanotube assemblies from a universal pyridine-containing monomer, which will enable systematic investigations of their emergent properties.

Natural biopolymers as proton conductors in bioelectronics.

Bioelectronic devices sense or deliver information at the interface between living systems and electronics by converting biological signals into electronic signals and vice-versa. Biological signals are typically carried by ions and small molecules. As such, ion conducting materials are ideal candidates in bioelectronics for an optimal interface. Among these materials, ion conducting polymers that are able to uptake water are particularly interesting because, in addition to ionic conductivity, their mechanical properties can closely match the ones of living tissue. In this review, we focus on a specific subset of ion-conducting polymers: proton (H+ ) conductors that are naturally derived. We first provide a brief introduction of the proton conduction mechanism, and then outline the chemical structure and properties of representative proton-conducting natural biopolymers: polysaccharides (chitosan and glycosaminoglycans), peptides and proteins, and melanin. We then highlight examples of using these biopolymers in bioelectronic devices. We conclude with current challenges and future prospects for broader use of natural biopolymers as proton conductors in bioelectronics and potential translational applications.

Single-Crystal Polycationic Polymers Obtained by Single-Crystal-to-Single-Crystal Photopolymerization.

The efficient preparation of single-crystalline ionic polymers and fundamental understanding of their structure-property relationships at the molecular level remains a challenge in chemistry and materials science. Here, we describe the single-crystal structure of a highly ordered polycationic polymer (polyelectrolyte) and its proton conductivity. The polyelectrolyte single crystals can be prepared on a gram-scale in quantitative yield, by taking advantage of an ultraviolet/sunlight-induced topochemical polymerization, from a tricationic monomer-a self-complementary building block possessing a preorganized conformation. A single-crystal-to-single-crystal photopolymerization was revealed unambiguously by in situ single-crystal X-ray diffraction analysis, which was also employed to follow the progression of molecular structure from the monomer, to a partially polymerized intermediate, and, finally, to the polymer itself. Collinear polymer chains are held together tightly by multiple Coulombic interactions involving counterions to form two-dimensional lamellar sheets (1 nm in height) with sub-nanometer pores (5 Å). The polymer is extremely stable under 254 nm light irradiation and high temperature (above 500 K). The extraordinary mechanical strength and environmental stability-in combination with its impressive proton conductivity (∼3 × 10-4 S cm-1)-endow the polymer with potential applications as a robust proton-conducting material. By marrying supramolecular chemistry with macromolecular science, the outcome represents a major step toward the controlled synthesis of single-crystalline polyelectrolyte materials with perfect tacticity.

A Microfluidic Ion Sensor Array.

A balanced concentration of ions is essential for biological processes to occur. For example, [H+ ] gradients power adenosine triphosphate synthesis, dynamic changes in [K+ ] and [Na+ ] create action potentials in neuronal communication, and [Cl- ] contributes to maintaining appropriate cell membrane voltage. Sensing ionic concentration is thus important for monitoring and regulating many biological processes. This work demonstrates an ion-selective microelectrode array that simultaneously and independently senses [K+ ], [Na+ ], and [Cl- ] in electrolyte solutions. To obtain ion specificity, the required ion-selective membranes are patterned using microfluidics. As a proof of concept, the change in ionic concentration is monitored during cell proliferation in a cell culture medium. This microelectrode array can easily be integrated in lab-on-a-chip approaches to physiology and biological research and applications.

Suppression of Oligomer Formation and Formation of Non-Toxic Fibrils upon Addition of Mirror-Image Aß42 to the Natural l-Enantiomer.

Racemates often have lower solubility than enantiopure compounds, and the mixing of enantiomers can enhance the aggregation propensity of peptides. Amyloid beta (Aß) 42 is an aggregation-prone peptide that is believed to play a key role in Alzheimer's disease. Soluble Aß42 aggregation intermediates (oligomers) have emerged as being particularly neurotoxic. We hypothesized that the addition of mirror-image d-Aß42 should reduce the concentration of toxic oligomers formed from natural l-Aß42. We synthesized l- and D-Aß42 and found their equimolar mixing to lead to accelerated fibril formation. Confocal microscopy with fluorescently labeled analogues of the enantiomers showed their colocalization in racemic fibrils. Owing to the enhanced fibril formation propensity, racemic Aß42 was less prone to form soluble oligomers. This resulted in the protection of cells from the toxicity of l-Aß42 at concentrations up to 50 µm. The mixing of Aß42 enantiomers thus accelerates the formation of non-toxic fibrils.

Delivering biochemicals with precision using bioelectronic devices enhanced with feedback control.

Precision medicine endeavors to personalize treatments, considering individual variations in patient responses based on factors like genetic mutations, age, and diet. Integrating this approach dynamically, bioelectronics equipped with real-time sensing and intelligent actuation present a promising avenue. Devices such as ion pumps hold potential for precise therapeutic drug delivery, a pivotal aspect of effective precision medicine. However, implementing bioelectronic devices in precision medicine encounters formidable challenges. Variability in device performance due to fabrication inconsistencies and operational limitations, including voltage saturation, presents significant hurdles. To address this, closed-loop control with adaptive capabilities and explicit handling of saturation becomes imperative. Our research introduces an enhanced sliding mode controller capable of managing saturation, adept at satisfactory control actions amidst model uncertainties. To evaluate the controller's effectiveness, we conducted in silico experiments using an extended mathematical model of the proton pump. Subsequently, we compared the performance of our developed controller with classical Proportional Integral Derivative (PID) and machine learning (ML)-based controllers. Furthermore, in vitro experiments assessed the controller's efficacy using various reference signals for controlled Fluoxetine delivery. These experiments showcased consistent performance across diverse input signals, maintaining the current value near the reference with a relative error of less than 7% in all trials. Our findings underscore the potential of the developed controller to address challenges in bioelectronic device implementation, offering reliable precision in drug delivery strategies within the realm of precision medicine.

Deep learning classification for macrophage subtypes through cell migratory pattern analysis.

Macrophages can exhibit pro-inflammatory or pro-reparatory functions, contingent upon their specific activation state. This dynamic behavior empowers macrophages to engage in immune reactions and contribute to tissue homeostasis. Understanding the intricate interplay between macrophage motility and activation status provides valuable insights into the complex mechanisms that govern their diverse functions. In a recent study, we developed a classification method based on morphology, which demonstrated that movement characteristics, including speed and displacement, can serve as distinguishing factors for macrophage subtypes. In this study, we develop a deep learning model to explore the potential of classifying macrophage subtypes based solely on raw trajectory patterns. The classification model relies on the time series of x-y coordinates, as well as the distance traveled and net displacement. We begin by investigating the migratory patterns of macrophages to gain a deeper understanding of their behavior. Although this analysis does not directly inform the deep learning model, it serves to highlight the intricate and distinct dynamics exhibited by different macrophage subtypes, which cannot be easily captured by a finite set of motility metrics. Our study uses cell trajectories to classify three macrophage subtypes: M0, M1, and M2. This advancement holds promising implications for the future, as it suggests the possibility of identifying macrophage subtypes without relying on shape analysis. Consequently, it could potentially eliminate the necessity for high-quality imaging techniques and provide more robust methods for analyzing inherently blurry images.

Modulation of neuronal activity in cortical organoids with bioelectronic delivery of ions and neurotransmitters.

Precise modulation of brain activity is fundamental for the proper establishment and maturation of the cerebral cortex. To this end, cortical organoids are promising tools to study circuit formation and the underpinnings of neurodevelopmental disease. However, the ability to manipulate neuronal activity with high temporal resolution in brain organoids remains limited. To overcome this challenge, we introduce a bioelectronic approach to control cortical organoid activity with the selective delivery of ions and neurotransmitters. Using this approach, we sequentially increased and decreased neuronal activity in brain organoids with the bioelectronic delivery of potassium ions (K+) and γ-aminobutyric acid (GABA), respectively, while simultaneously monitoring network activity. This works highlights bioelectronic ion pumps as tools for high-resolution temporal control of brain organoid activity toward precise pharmacological studies that can improve our understanding of neuronal function.

A bioelectronic device for electric field treatment of wounds reduces inflammation in an in vivo mouse model.

Electrical signaling plays a crucial role in the cellular response to tissue injury in wound healing and an external electric field (EF) may expedite the healing process. Here, we have developed a standalone, wearable, and programmable electronic device to administer a well-controlled exogenous EF, aiming to accelerate wound healing in an in vivo mouse model to provide pre-clinical evidence. We monitored the healing process by assessing the re-epithelization rate and the ratio of M1/M2 macrophage phenotypes through histology staining. Following three days of treatment, the M1/M2 macrophage ratio decreased by 30.6% and the re-epithelization in the EF-treated wounds trended towards a non-statically significant 24.2% increase compared to the control. These findings provide point towards the effectiveness of the device in shortening the inflammatory phase by promoting reparative macrophages over inflammatory macrophages, and in speeding up re-epithelialization. Our wearable device supports the rationale for the application of programmed EFs for wound management in vivo and provides an exciting basis for further development of our technology based on the modulation of macrophages and inflammation to better wound healing.

Carbon-binding designer proteins that discriminate between sp2- and sp3-hybridized carbon surfaces.

Robust and simple strategies to directly functionalize graphene- and diamond-based nanostructures with proteins are of considerable interest for biologically-driven manufacturing, biosensing, and bioimaging. Here, we identify a new set of carbon-binding peptides that vary in overall hydrophobicity and charge and engineer two of these sequences (Car9 and Car15) within the framework of E. coli thioredoxin 1 (TrxA). We develop purification schemes to recover the resulting TrxA derivatives in a soluble form and conduct a detailed analysis of the mechanisms that underpin the interaction of the fusion proteins with carbonaceous surfaces. Although equilibrium quartz crystal microbalance measurements show that TrxA::Car9 and TrxA::Car15 have similar affinities for sp(2)-hybridized graphitic carbon (Kd = 50 and 90 nM, respectively), only the latter protein is capable of dispersing carbon nanotubes. Further investigation by surface plasmon resonance and atomic force microscopy reveals that TrxA::Car15 interacts with sp(2)-bonded carbon through a combination of hydrophobic and π-π interactions but that TrxA::Car9 exhibits a cooperative mode of binding that relies on a combination of electrostatics and weaker π stacking. Consequently, we find that TrxA::Car9 binds equally well to sp(2)- and sp(3)-bonded (diamondlike) carbon particles whereas TrxA::Car15 is capable of discriminating between the two carbon allotropes. Our results emphasize the importance of understanding both bulk and molecular recognition events when exploiting the adhesive properties of solid-binding peptides and proteins in technological applications.

Implementing QR codes in academia to improve sample tracking, data accessibility, and traceability in multicampus interdisciplinary collaborations.

The growing number of multicampus interdisciplinary projects in academic institutions expedites a necessity for tracking systems that provide instantly accessible data associated with devices, samples, and experimental results to all collaborators involved. This need has become particularly salient with the COVID pandemic when consequent travel restrictions have hampered in person meetings and laboratory visits. Minimizing post-pandemic travel can also help reduce carbon footprint of research activities. Here we developed a Quick Response (QR) code tracking system that integrates project management tools for seamless communication and tracking of materials and devices between multicampus collaborators: one school of medicine, two engineering laboratories, three manufacturing cleanroom sites, and three research laboratories. Here we aimed to use this system to track the design, fabrication, and quality control of bioelectronic devices, in vitro experimental results, and in vivo testing. Incorporating the tracking system into our project helped our multicampus teams accomplish milestones on a tight timeline via improved data traceability, manufacturing efficiency, and shared experimental results. This tracking system is particularly useful to track device issues and ensure engineering device consistency when working with expensive biological samples in vitro and animals in vivo to reduce waste of biological and animal resources associated with device failure.

Influence of Backbone Regioregularity on the Optoelectronic and Mechanical Response of Conjugated Polyelectrolyte-Based Hydrogels.

The ability to form robust, optoelectronically responsive, and mechanically tunable hydrogels using facile processing is desirable for sensing, biomedical, and light-harvesting applications. We demonstrate that such a hydrogel can be formed using aqueous complexation between one conjugated and one nonconjugated polyelectrolyte. We show that the rheological properties of the hydrogel can be tuned using the regioregularity of the conjugated polyelectrolyte (CPE) backbone, leading to significantly different mesoscale gel morphologies. We also find that the exciton dynamics in the long-time limit reflect differences in the underlying electronic connectivity of the hydrogels as a function CPE regioregularity. The influence of excess small ions on the hydrogel structure and the exciton dynamics similarly depends on the regioregularity in a significant way. Finally, electrical impedance measurements lead us to infer that these hydrogels can act as mixed ionic/electronic conductors. We believe that such gels possess an attractive combination of physical-chemical properties that can be leveraged in multiple applications.

DNA nanopores as artificial membrane channels for bioprotonics.

Biological membrane channels mediate information exchange between cells and facilitate molecular recognition. While tuning the shape and function of membrane channels for precision molecular sensing via de-novo routes is complex, an even more significant challenge is interfacing membrane channels with electronic devices for signal readout, which results in low efficiency of information transfer - one of the major barriers to the continued development of high-performance bioelectronic devices. To this end, we integrate membrane spanning DNA nanopores with bioprotonic contacts to create programmable, modular, and efficient artificial ion-channel interfaces. Here we show that cholesterol modified DNA nanopores spontaneously and with remarkable affinity span the lipid bilayer formed over the planar bio-protonic electrode surface and mediate proton transport across the bilayer. Using the ability to easily modify DNA nanostructures, we illustrate that this bioprotonic device can be programmed for electronic recognition of biomolecular signals such as presence of Streptavidin and the cardiac biomarker B-type natriuretic peptide, without modifying the biomolecules. We anticipate this robust interface will allow facile electronic measurement and quantification of biomolecules in a multiplexed manner.

Quantifying innervation facilitated by deep learning in wound healing.

The peripheral nerves (PNs) innervate the dermis and epidermis, which have been suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and noise/background associated with the Immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, DnCNN, to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3,7,10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly we found a positive correlation (R 2 = 0.933) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Quantifying innervation facilitated by deep learning in wound healing.

The peripheral nerves (PNs) innervate the dermis and epidermis, and are suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and the noise/background associated with the immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, Denoising Convolutional Neural Network (DnCNN), to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8 mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3, 7, 10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly, we found a positive correlation (R2 = 0.926) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.