Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection.

Single-molecule proteomics based on nanopore technology has made significant advances in recent years. However, to achieve nanopore sensing with single amino acid resolution, several bottlenecks must be tackled: controlling nanopore sizes with nanoscale precision and slowing molecular translocation events. Herein, we address these challenges by integrating amino acid-specific DNA aptamers into interface nanopores with dynamically tunable pore sizes. A phenylalanine aptamer was used as a proof-of-concept: aptamer recognition of phenylalanine moieties led to the retention of specific peptides, slowing translocation speeds. Importantly, while phenylalanine aptamers were isolated against the free amino acid, the aptamers were determined to recognize the combination of the benzyl or phenyl and the carbonyl group in the peptide backbone, enabling binding to specific phenylalanine-containing peptides. We decoupled specific binding between aptamers and phenylalanine-containing peptides from nonspecific interactions (e.g., electrostatics and hydrophobic interactions) using optical waveguide lightmode spectroscopy. Aptamer-modified interface nanopores differentiated peptides containing phenylalanine vs. control peptides with structurally similar amino acids (i.e., tyrosine and tryptophan). When the duration of aptamer-target interactions inside the nanopore were prolonged by lowering the applied voltage, discrete ionic current levels with repetitive motifs were observed. Such reoccurring signatures in the measured signal suggest that the proposed method has the possibility to resolve amino acid-specific aptamer recognition, a step toward single-molecule proteomics.

Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays.

Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.

Engineering circuits of human iPSC-derived neurons and rat primary glia.

Novel in vitro platforms based on human neurons are needed to improve early drug testing and address the stalling drug discovery in neurological disorders. Topologically controlled circuits of human induced pluripotent stem cell (iPSC)-derived neurons have the potential to become such a testing system. In this work, we build in vitro co-cultured circuits of human iPSC-derived neurons and rat primary glial cells using microfabricated polydimethylsiloxane (PDMS) structures on microelectrode arrays (MEAs). Our PDMS microstructures are designed in the shape of a stomach, which guides axons in one direction and thereby facilitates the unidirectional flow of information. Such circuits are created by seeding either dissociated cells or pre-aggregated spheroids at different neuron-to-glia ratios. Furthermore, an antifouling coating is developed to prevent axonal overgrowth in undesired locations of the microstructure. We assess the electrophysiological properties of different types of circuits over more than 50 days, including their stimulation-induced neural activity. Finally, we demonstrate the inhibitory effect of magnesium chloride on the electrical activity of our iPSC circuits as a proof-of-concept for screening of neuroactive compounds.

Nanoscale Patterning of In Vitro Neuronal Circuits.

Methods for patterning neurons in vitro have gradually improved and are used to investigate questions that are difficult to address in or ex vivo. Though these techniques guide axons between groups of neurons, multiscale control of neuronal connectivity, from circuits to synapses, is yet to be achieved in vitro. As studying neuronal circuits with synaptic resolution in vivo poses significant challenges, we present an in vitro alternative to validate biophysical and computational models. In this work we use a combination of electron beam lithography and photolithography to create polydimethylsiloxane (PDMS) structures with features ranging from 150 nm to a few millimeters. Leveraging the difference between average axon and dendritic spine diameters, we restrict axon growth while allowing spines to pass through nanochannels to guide synapse formation between small groups of neurons (i.e., nodes). We show this technique can be used to generate large numbers of isolated feed-forward circuits where connections between nodes are restricted to regions connected by nanochannels. Using a genetically encoded calcium indicator in combination with fluorescently tagged postsynaptic protein, PSD-95, we demonstrate functional synapses can form in this region.

Topologically controlled circuits of human iPSC-derived neurons for electrophysiology recordings.

Bottom-up neuroscience, which consists of building and studying controlled networks of neurons in vitro, is a promising method to investigate information processing at the neuronal level. However, in vitro studies tend to use cells of animal origin rather than human neurons, leading to conclusions that might not be generalizable to humans and limiting the possibilities for relevant studies on neurological disorders. Here we present a method to build arrays of topologically controlled circuits of human induced pluripotent stem cell (iPSC)-derived neurons. The circuits consist of 4 to 50 neurons with well-defined connections, confined by microfabricated polydimethylsiloxane (PDMS) membranes. Such circuits were characterized using optical imaging and microelectrode arrays (MEAs), suggesting the formation of functional connections between the neurons of a circuit. Electrophysiology recordings were performed on circuits of human iPSC-derived neurons for at least 4.5 months. We believe that the capacity to build small and controlled circuits of human iPSC-derived neurons holds great promise to better understand the fundamental principles of information processing and storing in the brain.

Engineered Biological Neural Networks on High Density CMOS Microelectrode Arrays.

In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23 % of structurally fully connected but sealed networks on the CMOS MEA of which about 45 % showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.

An experimental paradigm to investigate stimulation dependent activity in topologically constrained neuronal networks.

We present a stimulate and record paradigm to examine the behavior of multiple neuronal networks with controlled topology in vitro. Our approach enabled us to electrically induce and record neuronal activity from 60 independent networks in parallel over multiple weeks. We investigated the network performance of neuronal networks of primary hippocampal neurons until 29 days in vitro. We introduced a systematic stimulate and record protocol during which well-defined 4-node neural networks were stimulated electrically 4 times per second (4Hz) and their response was recorded over many days. We found that the network response pattern to a stimulus remained fairly stable for at least 12 h. Moreover, continuous stimulation over multiple weeks did not cause a significant change in the stimulation-induced mean spiking frequency of a circuit. We investigated the effect of stimulation amplitude and stimulation timing on the detailed network response. Finally, we could show that our setup can apply complex stimulation protocols with 125 different stimulation patterns. We used these patterns to perform basic addition tasks with the network, revealing the highly non-linear nature of biological networks' responses to complex stimuli.

Magnetic Manipulation of Nanowires for Engineered Stretchable Electronics.

Nanowires are often key ingredients of high-tech composite materials. The properties and performance of devices created using these, depend heavily on the structure and density of the embedded nanowires. Despite significant efforts, a process that can be adapted to different materials, compatible with current nanowire deposition methods, and that is able to control both variables simultaneously has not been achieved yet. In this work, we show that we can use low magnetic fields (80 mT) to manipulate nanowires by electrostatically coating them with superparamagnetic iron oxide nanoparticles in an aqueous solution. Monolayers, multilayers, and hierarchical structures of oriented nanowires were achieved in a highly ordered manner using vacuum filtration for two types of nanowires: silver and gold-coated titanium dioxide nanowires. The produced films were embedded in an elastomer, and the strain-dependent electrical properties of the resulting composites were investigated. The orientation of the assembly with respect to the tensile strain heavily impacts the performance of the composites. Composites containing nanowires perpendicular to the strain direction exhibit an extremely low gauge factor. On the other hand, when nanowires are arranged parallel to the strain direction, the composites have a high gauge factor. The possibility to orient nanowires during the processing steps is not only interesting for the shown strain sensing application but also expected to be useful in many other areas of material science.

Nonspecific Binding-Fundamental Concepts and Consequences for Biosensing Applications.

Nature achieves differentiation of specific and nonspecific binding in molecular interactions through precise control of biomolecules in space and time. Artificial systems such as biosensors that rely on distinguishing specific molecular binding events in a sea of nonspecific interactions have struggled to overcome this issue. Despite the numerous technological advancements in biosensor technologies, nonspecific binding has remained a critical bottleneck due to the lack of a fundamental understanding of the phenomenon. To date, the identity, cause, and influence of nonspecific binding remain topics of debate within the scientific community. In this review, we discuss the evolution of the concept of nonspecific binding over the past five decades based upon the thermodynamic, intermolecular, and structural perspectives to provide classification frameworks for biomolecular interactions. Further, we introduce various theoretical models that predict the expected behavior of biosensors in physiologically relevant environments to calculate the theoretical detection limit and to optimize sensor performance. We conclude by discussing existing practical approaches to tackle the nonspecific binding challenge in vitro for biosensing platforms and how we can both address and harness nonspecific interactions for in vivo systems.

Sensing serotonin secreted from human serotonergic neurons using aptamer-modified nanopipettes.

The serotonergic system in the human brain modulates several physiological processes, and altered serotonergic neurotransmission has been implicated in the neuropathology of several psychiatric disorders. The study of serotonergic neurotransmission in psychiatry has long been restricted to animal models, but advances in cell reprogramming technology have enabled the generation of serotonergic neurons from patient-induced pluripotent stem cells (iPSCs). While iPSC-derived human serotonergic neurons offer the possibility to study serotonin (5-HT) release and uptake, particularly by 5-HT-modulating drugs such as selective serotonin reuptake inhibitors (SSRIs), a major limitation is the inability to reliably quantify 5-HT secreted from neurons in vitro. Herein, we address this technical gap via a novel sensing technology that couples 5-HT-specific DNA aptamers into nanopores (glass nanopipettes) with orifices of ~10 nm to detect 5-HT in complex neuronal culture medium with higher selectivity, sensitivity, and stability than existing methods. The 5-HT aptamers undergo conformational rearrangement upon target capture and serve as gatekeepers of ionic flux through the nanopipette opening. We generated human serotonergic neurons in vitro and detected secreted 5-HT using aptamer-coated nanopipettes in a low nanomolar range, with the possibility of detecting significantly lower (picomolar) concentrations. Furthermore, as a proof of concept, we treated human serotonergic neurons in vitro with the SSRI citalopram and detected a significant increase in extracellular 5-HT using the aptamer-modified nanopipettes. We demonstrate the utility of such methods for 5-HT detection, raising the possibility of fast quantification of neurotransmitters secreted from patient-derived live neuronal cells.

An Approach for the Real-Time Quantification of Cytosolic Protein-Protein Interactions in Living Cells.

In recent years, cell-based assays have been frequently used in molecular interaction analysis. Cell-based assays complement traditional biochemical and biophysical methods, as they allow for molecular interaction analysis, mode of action studies, and even drug screening processes to be performed under physiologically relevant conditions. In most cellular assays, biomolecules are usually labeled to achieve specificity. In order to overcome some of the drawbacks associated with label-based assays, we have recently introduced "cell-based molography" as a biosensor for the analysis of specific molecular interactions involving native membrane receptors in living cells. Here, we expand this assay to cytosolic protein-protein interactions. First, we created a biomimetic membrane receptor by tethering one cytosolic interaction partner to the plasma membrane. The artificial construct is then coherently arranged into a two-dimensional pattern within the cytosol of living cells. Thanks to the molographic sensor, the specific interactions between the coherently arranged protein and its endogenous interaction partners become visible in real time without the use of a fluorescent label. This method turns out to be an important extension of cell-based molography because it expands the range of interactions that can be analyzed by molography to those in the cytosol of living cells.

Investigating Complex Samples with Molograms of Low-Affinity Binders.

In vitro diagnostics relies on the quantification of minute amounts of a specific biomolecule, called biomarker, from a biological sample. The majority of clinically relevant biomarkers for conditions beyond infectious diseases are detected by means of binding assays, where target biomarkers bind to a solid phase and are detected by biochemical or physical means. Nonspecifically bound biomolecules, the main source of variation in such assays, need to be washed away in a laborious process, restricting the development of widespread point-of-care diagnostics. Here, we show that a diffractometric assay provides a new, label-free possibility to investigate complex samples, such as blood plasma. A coherently arranged sub-micron pattern, that is, a peptide mologram, is created to demonstrate the insensitivity of this diffractometric assay to the unwanted masking effect of nonspecific interactions. In addition, using an array of low-affinity binders, we also demonstrate the feasibility of molecular profiling of blood plasma in real time and show that individual patients can be differentiated based on the binding kinetics of circulating proteins.

Aptamer Conformational Change Enables Serotonin Biosensing with Nanopipettes.

We report artificial nanopores in the form of quartz nanopipettes with ca. 10 nm orifices functionalized with molecular recognition elements termed aptamers that reversibly recognize serotonin with high specificity and selectivity. Nanoscale confinement of ion fluxes, analyte-specific aptamer conformational changes, and related surface charge variations enable serotonin sensing. We demonstrate detection of physiologically relevant serotonin amounts in complex environments such as neurobasal media, in which neurons are cultured in vitro. In addition to sensing in physiologically relevant matrices with high sensitivity (picomolar detection limits), we interrogate the detection mechanism via complementary techniques such as quartz crystal microbalance with dissipation monitoring and electrochemical impedance spectroscopy. Moreover, we provide a novel theoretical model for structure-switching aptamer-modified nanopipette systems that supports experimental findings. Validation of specific and selective small-molecule detection, in parallel with mechanistic investigations, demonstrates the potential of conformationally changing aptamer-modified nanopipettes as rapid, label-free, and translatable nanotools for diverse biological systems.

Ultra-Stable Molecular Sensors by Sub-Micron Referencing and Why They Should Be Interrogated by Optical Diffraction-Part I. The Concept of a Spatial Affinity Lock-in Amplifier.

Label-free optical biosensors, such as surface plasmon resonance, are sensitive and well-established for the characterization of molecular interactions. Yet, these sensors require stabilization and constant conditions even with the use of reference channels. In this paper, we use tools from signal processing to show why these sensors are so cross-sensitive and how to overcome their drawbacks. In particular, we conceptualize the spatial affinity lock-in as a universal design principle for sensitive molecular sensors even in the complete absence of stabilization. The spatial affinity lock-in is analogous to the well-established time-domain lock-in. Instead of a time-domain signal, it modulates the binding signal at a high spatial frequency to separate it from the low spatial frequency environmental noise in Fourier space. In addition, direct sampling of the locked-in sensor's response in Fourier space enabled by diffraction has advantages over sampling in real space as done by surface plasmon resonance sensors using the distributed reference principle. This paper and part II hint at the potential of spatially locked-in diffractometric biosensors to surpass state-of-the-art temperature-stabilized refractometric biosensors. Even simple, miniaturized and non-stabilized sensors might achieve the performance of bulky lab instruments. This may enable new applications in label-free analysis of molecular binding and point-of-care diagnostics.

Soft Electronics Based on Stretchable and Conductive Nanocomposites for Biomedical Applications.

Research on the field of implantable electronic devices that can be directly applied in the body with various functionalities is increasingly intensifying due to its great potential for various therapeutic applications. While conventional implantable electronics generally include rigid and hard conductive materials, their surrounding biological objects are soft and dynamic. The mechanical mismatch between implanted devices and biological environments induces damages in the body especially for long-term applications. Stretchable electronics with outstanding mechanical compliance with biological objects effectively improve such limitations of existing rigid implantable electronics. In this article, the recent progress of implantable soft electronics based on various conductive nanocomposites is systematically described. In particular, representative fabrication approaches of conductive and stretchable nanocomposites for implantable soft electronics and various in vivo applications of implantable soft electronics are focused on. To conclude, challenges and perspectives of current implantable soft electronics that should be considered for further advances are discussed.

Ultra Stable Molecular Sensors by Submicron Referencing and Why They Should Be Interrogated by Optical Diffraction-Part II. Experimental Demonstration.

Label-free optical biosensors are an invaluable tool for molecular interaction analysis. Over the past 30 years, refractometric biosensors and, in particular, surface plasmon resonance have matured to the de facto standard of this field despite a significant cross reactivity to environmental and experimental noise sources. In this paper, we demonstrate that sensors that apply the spatial affinity lock-in principle (part I) and perform readout by diffraction overcome the drawbacks of established refractometric biosensors. We show this with a direct comparison of the cover refractive index jump sensitivity as well as the surface mass resolution of an unstabilized diffractometric biosensor with a state-of-the-art Biacore 8k. A combined refractometric diffractometric biosensor demonstrates that a refractometric sensor requires a much higher measurement precision than the diffractometric to achieve the same resolution. In a conceptual and quantitative discussion, we elucidate the physical reasons behind and define the figure of merit of diffractometric biosensors. Because low-precision unstabilized diffractometric devices achieve the same resolution as bulky stabilized refractometric sensors, we believe that label-free optical sensors might soon move beyond the drug discovery lab as miniaturized, mass-produced environmental/medical sensors. In fact, combined with the right surface chemistry and recognition element, they might even bring the senses of smell/taste to our smart devices.

Continuous Heart Volume Monitoring by Fully Implantable Soft Strain Sensor.

Cardiothoracic open-heart surgery has revolutionized the treatment of cardiovascular disease, the leading cause of death worldwide. After the surgery, hemodynamic and volume management can be complicated, for example in case of vasoplegia after endocarditis. Timely treatment is crucial for outcomes. Currently, treatment decisions are made based on heart volume, which needs to be measured manually by the clinician each time using ultrasound. Alternatively, implantable sensors offer a real-time window into the dynamic function of our body. Here it is shown that a soft flexible sensor, made with biocompatible materials, implanted on the surface of the heart, can provide continuous information of the heart volume after surgery. The sensor works robustly for a period of two days on a tensile machine. The accuracy of measuring heart volume is improved compared to the clinical gold standard in vivo, with an error of 7.1 mL for the strain sensor versus impedance and 14.0 mL versus ultrasound. Implanting such a sensor would provide essential, continuous information on heart volume in the critical time following the surgery, allowing early identification of complications, facilitating treatment, and hence potentially improving patient outcome.

Force-Controlled Formation of Dynamic Nanopores for Single-Biomolecule Sensing and Single-Cell Secretomics.

Nanopore sensing of single nucleotides has emerged as a promising single-molecule technology for DNA sequencing and proteomics. Despite the conceptual simplicity of nanopores, adoption of this technology for practical applications has been limited by a lack of pore size adjustability and an inability to perform long-term recordings in complex solutions. Here we introduce a method for fast and precise on-demand formation of a nanopore with controllable size between 2 and 20 nm through force-controlled adjustment of the nanospace formed between the opening of a microfluidic device (made of silicon nitride) and a soft polymeric substrate. The introduced nanopore system enables stable measurements at arbitrary locations. By accurately positioning the nanopore in the proximity of single neurons and continuously recording single-molecule translations over several hours, we have demonstrated this is a powerful approach for single-cell proteomics and secretomics.

Opto-E-Dura: A Soft, Stretchable ECoG Array for Multimodal, Multiscale Neuroscience.

Soft, stretchable materials hold great promise for the fabrication of biomedical devices due to their capacity to integrate gracefully with and conform to biological tissues. Conformal devices are of particular interest in the development of brain interfaces where rigid structures can lead to tissue damage and loss of signal quality over the lifetime of the implant. Interfaces to study brain function and dysfunction increasingly require multimodal access in order to facilitate measurement of diverse physiological signals that span the disparate temporal and spatial scales of brain dynamics. Here the Opto-e-Dura, a soft, stretchable, 16-channel electrocorticography array that is optically transparent is presented. Its compatibility with diverse optical and electrical readouts is demonstrated enabling multimodal studies that bridge spatial and temporal scales. The device is chronically stable for weeks, compatible with wide-field and 2-photon calcium imaging and permits the repeated insertion of penetrating multielectrode arrays. As the variety of sensors and effectors realizable on soft, stretchable substrates expands, similar devices that provide large-scale, multimodal access to the brain will continue to improve fundamental understanding of brain function.