Biology subjects

Fu, K. X.

Publications and source records attributed to Fu, K. X..

3 recordsLinked to original sources

bioRxiv2026

Electrode-Tethered DNA: Interfacial Mechanics and Switching Dynamics from Ensemble-Level Atomistic Simulations

Surface-tethered DNA, anchored to gold by the late 1990s, has matured into a versatile platform for biosensing, computing and actuation. Whereas the molecular behavior of DNA in bulk solution is well characterized, that of DNA at electrode interfaces remains far less understood. Here we investigate the mechanics and dynamics of electrode-tethered double-stranded DNA across surface chemistries, salt concentrations and applied potentials. Using GPU-accelerated all-atom molecular dynamics, we sample trajectory ensembles totaling 144 s over 620 simulations. The simulations reproduce key experimental observations yet uncover molecular behavior that had gone unnoticed despite nearly three decades of research. Ensemble statistics reveal a preferred orientation about the helical axis upon surface contact. Energetic analysis identifies a substantial role for Onsager-Samaras-type repulsion in opposing that contact. By reproducing experimental trends while resolving their molecular origins, these ensembles substantially narrow the longstanding simulation-experiment gap and provide a basis for engineering tethered-DNA devices.

biophysics↗

bioRxiv2025

Algorithm-Powered Analyzer for Continuous Electrochemistry: A Toolkit for Real-Time Electrochemical Data Analysis

Real-time biosensors offer significant potential for continuous monitoring of biomolecules. However, their practical application and further development face challenges on data analysis, including poor signal-to-noise ratio when effective sensing area decreases due to signal degradation by biofouling, time-consuming and subjective process of manual or semi-automated peak identification, and inconsistencies in data interpretation, thereby complicating reproducibility and cross-comparison of biosensing results. In this study, we introduce the Algorithm-Powered Analyzer for Continuous Electrochemistry (A-PACE), an open-source toolkit providing streamlined and automated data analysis protocol optimized for real-time electrochemical data analysis. A-PACE comprises three modules: (1) Change point detection for automated identification of peak regions; (2) Baseline fitting with multiple algorithms to handle diverse electrochemical signals and baseline screening to eliminate unreasonable fits; (3) Large dataset input with user-friendly interface for data processing, exporting and visualization. To ensure optimal performance, we curated a training set of 2000 electrochemical curves from an extensive electrochemical dataset (>100,000 curves) collected over the past five years under varied electrochemical measurement conditions. These curves were analyzed using 2046 algorithm sets to identify a default algorithm set, compared to existing tools, demonstrating its capability in peak detection and baseline fitting across a broad spectrum of electrochemical data. Case studies reveal the A-PACE can analyze month-long in vitro serum data and week-long in vivo intravenous blood data, extending the operational lifespan of real-time sensors. This cross-platform compatible toolkit supports both real-time and post-processing analysis, reducing the processing time from minute level per signal by human labeling to second level by A-PACE and subjectivity associated with electrochemical signal processing. By providing this solution for continuous electrochemical data analysis, A-PACE enhances biosensors applications in medical diagnostics and continuous monitoring with high throughput analysis.

bioengineering↗

bioRxiv2023

Continuous optical detection of small-molecule analytes in complex biomatrices

Current technology for measuring specific biomarkers - continuously in complex samples, without sample preparation - is limited to just handful of molecules such as glucose and blood oxygen. In this work, we present the first optical biosensor system that enables continuous detection of a wide range of biomarkers in complex samples, such as human plasma. Our system employs a modular duplex-bubble switch (DBS) architecture that converts aptamers into structure-switching fluorescence probes whose affinity and kinetics can be readily tuned. These DBS constructs are coupled to a fiber-optic detector that measures the fluorescence change only within an evanescent field, thereby minimizing the impact of background autofluorescence and enabling direct detection of analytes at physiologically relevant concentrations even in interferent-rich sample matrices. Using our system, we achieved continuous detection of dopamine in artificial cerebrospinal fluid for >24 hours with sub-second resolution and a limit of detection (LOD) of 1 {micro}M. We subsequently demonstrated the systems generalizability by configuring it to detect cortisol with nanomolar sensitivity in undiluted human plasma. Both sensors achieved LODs orders of magnitude lower than the KD of the DBS element, highlighting the potential to achieve sensitive detection even when using aptamers with modest affinity.

biophysics↗