In this work, we present the introductory methodology for a graphene field-effect transistor (GFET)-based platform for probing the electrochemical fingerprints of amino acids, designed to enable stable and controlled surface chemistry and electrochemical measurements toward peptide and protein sequencing. We begin with a focused conceptual review that motivates electrochemical fingerprinting as a strategy for amino acid and peptide identification and contextualizes this approach within recent advances in protein manipulation relevant to sequencing. We then describe a graphene functionalization protocol that facilitates the directional attachment of amino acids onto the graphene surface. This surface chemistry is quantitatively characterized through surface plasmon resonance (SPR), yielding surface densities in the order of 10¹² molecules/cm². The same functionalization protocol enables in situ peptide synthesis directly on graphene, as demonstrated by the successful synthesis of a model tripeptide. To support electrochemical interrogation, we developed three complementary platforms for sensor preconditioning, surface functionalization, and titration-based electrochemical measurements, compatible with both aqueous and organic solutions. Preliminary stability measurements indicate a Dirac point drift below 10 mV over 45 min. Altogether, this work establishes the experimental foundations for electrochemical amino acid and peptide fingerprinting using GFET sensors and provides a framework for the future development of electrochemically enabled protein sequencing technologies.

Dopamine is a neurotransmitter with critical roles in the human brain and body, and abnormal dopamine levels underlie brain disorders such as Parkinson’s Disease, Alzheimer’s Disease, and substance addiction. Herein, we present a novel high-throughput biosensor based on graphene multitransistor arrays (gMTAs) functionalized with a selective aptamer for robust ultrasensitive dopamine detection. The miniaturized biosensor integrates multiple electrolyte-gated graphene field-effect transistors (EG-gFETs) in an array configuration, fabricated by high-yield reproducible and scalable methodologies optimized at the wafer level. With these gMTA aptasensors, we reliably detected ultra-low dopamine concentrations in physiological buffers, including undiluted phosphate-buffered saline (PBS), artificial cerebral spinal fluid (aCSF), and high ionic strength complex biological samples. We report a record limit-of-detection (LOD) of 1 aM (10 ⁻¹⁸ ) for dopamine in both PBS, and dopamine-depleted brain homogenate samples spiked with dopamine. The gMTAs also display wide sensing ranges across all media, up to 100 μM (10 ⁻⁸ ), with a 22 mV/decade peak sensitivity in aCSF. Furthermore, we show that the gMTAs can detect minimal changes in dopamine concentrations in small working volume biological CSF samples obtained from a mouse model of Parkinson’s Disease.

Graphene field-effect transistors (GFETs) are emerging sensors for monitoring chemical molecules in the brain due to their nanoscale dimensions and high sensitivity to ionic concentrations. In such systems, compact electronic readouts that allow high spatiotemporal resolution of dense sensor arrays are desired for improved brain spatial mapping at relevant physiological temporal scales. This work presents a CMOS-based platform capable of reading GFET arrays at a sampling rate of 512 kS/s, time-multiplexed across 32 channels, with an ENOB of 8.38 bits and a power consumption of $173~\mu $ W per channel. The ASIC, fabricated using a 180 nm CMOS process, has a core area of $970~\mu $ m $\times 500~\mu $ m and integrates a transimpedance amplifier, a fully differential amplifier, and a SAR ADC. This ASIC can be scalable to support larger GFET arrays. An All-Programmable System-on-Chip is employed for system control and real-time data acquisition, with data streamed via gigabit Ethernet to a computer for visualization and storage using custom-written software. Measurements in physiological buffers, such as phosphate-buffered saline (PBS) and dopamine diluted in artificial cerebrospinal fluid (aCSF), confirm the system’s capability for real-time current monitoring, analysis of V-shaped transfer curves, evaluation of frequency-doubling behavior, and spatiotemporal visualization of sensor responses to varying ionic conditions and targets.

Glutamate, the principal excitatory neurotransmitter in the brain, is crucial for cognition and memory, and its dysregulation is implicated in several neurological disorders, including Alzheimer’s Disease and epilepsy. However, precise and high-throughput quantification of glutamate in physiological samples remains challenging. Here, we report an ultrasensitive and highly specific glutamate aptamer-based biosensor, or aptasensor, developed through in silico design and microfabrication, followed by in vitro and clinical validation. The biosensor consists of arrays of graphene field-effect transistors functionalized with a novel DNA aptamer, NG-Apt-Glu, designed and characterized computationally and biochemically, revealing two putative glutamate binding sites. The aptasensor detects glutamate in artificial cerebrospinal fluid with a 1 aM detection limit, a wide linear range (1 aM–10 pM), and 24 mV/decade sensitivity, showing strong selectivity against GABA, glutamine, dopamine, and serotonin. To evaluate clinical applicability, glutamate levels were measured in cerebrospinal fluid from patients with Alzheimer’s Disease, showing a significant increase relative to controls and correlating with neurofilament light chain concentrations, a biomarker of neuronal death. These findings underscore glutamate’s involvement in Alzheimer’s pathophysiology and its potential as a biomarker for neurodegeneration. This ultrasensitive graphene-based aptasensor enables point-of-care monitoring, paving the way for early diagnosis and the development of novel therapeutic strategies.

Optogenetics is a widely used tool to dissect neural circuits with optical stimulation, but it requires that light is delivered to photosensitive neurons inside the brain. Implantable neural probes with microscale LEDs (μLEDs) are an emerging approach to delivering light to the brain with superior light output control. However, approaches to integrate μLEDs in neural probes depend on complex fabrication processes. Here, we developed an implantable small form factor neural probe that integrates highly efficient commercial flip chip μLEDs using only standard lithography processes in silicon and a custom automated LED mounting approach with custom 3D-printed tools on a pick-and-place machine. The probe has a cross-sectional area under 0.013 mm ² but can output up to 2.5 mW of optical power with an irradiance of 175 mW/mm ² . Due to the high plug efficiency of the LED, the neural probe can perform stimulation protocols up to 20 Hz and 80% duty cycles without surpassing estimated hotspot temperature elevations above 1 ºC. The neural probes were validated in vivo, with brain activity in the motor cortex of transgenic mice being reliably modulated by pulsed light emitted from the probe.

Optogenetics is an invaluable technique in neuroscience to study brain circuits, but conventional optogenetic systems use tethered approaches to deliver light to the brain which can hinder natural behavior. Optoelectronic advances led to the development of wireless optical stimulators for optogenetics experiments, but most reported devices have low widespread use due to complex builds and reduced versatility, which has also limited their integration in closed-loop systems. Here, we developed BOWIe, a battery-powered, low-weight, wireless headstage for photostimulation in optogenetics experiments with rodents, especially designed for simple integration in multiple behavioral setups, including those requiring closed-loop operation. BOWIe is based on a Bluetooth-Low Energy system-on-a-chip that allows simultaneous control and communication capabilities with a reduced number of components, and can be paired with an Arduino-based transmitter for simple integration in any behavioral paradigm using analogue or digital triggers. Two modes of optical stimulation are possible, either with ferrule-coupled optical fibers or µLED neural probes, which permit adapting the headstage according to material availability or experimental demands. A user-friendly app was also developed to simplify headstage pairing, definition of stimulation parameters, and protocol design. BOWIe was validated in two behavioral paradigms, including in a closed-loop experiment using computer vision, Bonsai RX, and Deeplabcut Live to track behavioral parameters online and remotely trigger photostimulation upon detected events. BOWIe’s modular design and flexible integration with behavioral setups make it a practical tool for in vivo experiments with optogenetics.