Single Exosome Amperometric Measurements Reveal Encapsulation of Chemical Messengers for Intercellular Communication

Unlocking the electrochemical functions of biomolecular condensates

Biomolecular condensation is a key mechanism for organizing cellular processes in a spatiotemporal manner. The phase-transition nature of this process defines a density transition of the whole solution system. However, the physicochemical features and the electrochemical functions brought about by condensate formation are largely unexplored. We here illustrate the fundamental principles of how the formation of condensates generates distinct electrochemical features in the dilute phase, the dense phase and the interfacial region. We discuss the principles by which these distinct chemical and electrochemical environments can modulate biomolecular functions through the effects brought about by water, ions and electric fields. We delineate the potential impacts on cellular behaviors due to the modulation of chemical and electrochemical environments through condensate formation. This Perspective is intended to serve as a general road map to conceptualize condensates as electrochemically active entities and to assess their functions from a physical chemistry aspect.

Monitoring the electroactive cargo of extracellular vesicles can differentiate various cancer cell lines

Extracellular vesicles (EVs) are pivotal in cell-to-cell communication due to the array of cargo contained within these vesicles. EVs are considered important biomarkers for identification of disease, however most measurement approaches have focused on monitoring specific surface macromolecular targets. Our study focuses on exploring the electroactive component present within cargo from EVs obtained from various cancer and non-cancer cell lines using a disk carbon fiber microelectrode. Variations in the presence of oxidizable components were observed when the total cargo from EVs were measured, with the highest current detected in EVs from MCF7 cells. There were differences observed in the types of oxidizable species present within EVs from MCF7 and A549 cells. Single entity measurements showed clear spikes due to the detection of oxidizable cargo within EVs from MCF7 and A549 cells. These studies highlight the promise of monitoring EVs through the presence of varying electroactive components within the cargo and can drive a wave of new strategies towards specific detection of EVs for diagnosis and prognosis of various diseases.

Building a stable and robust anti-interference DNA dissipation system by eliminating the accumulation of systemic specified errors

BACKGROUND

The emergence of DNA nanotechnology has enabled the systematic design of diverse bionic dissipative behaviors under the precise control of nucleic acid nanodevices. Nevertheless, when compared to the dissipation observed in robust living systems, it is highly desirable to enhance the anti-interference for artificial DNA dissipation to withstand perturbations and facilitate repairs within the complex biological environments.

RESULTS

In this study, we introduce strategically designed "trash cans" to facilitate kinetic control over interferences, transforming the stochastic binding of individual components within a homogeneous solution into a competitive binding process. This approach effectively eliminates incorrect binding and the accumulation of systemic interferences while ensuring a consistent pattern of energy fluctuation from response to silence. Remarkably, even in the presence of numerous interferences differing by only one base, we successfully achieve complete system reset through multiple cycles, effectively restoring the energy level to a minimum.

SIGNIFICANCE

The system was able to operate stably without any adverse effect under conditions of irregular interference, high-abundance interference, and even multiplex interferences including DNA and RNA crosstalk. This work not only provides an effective paradigm for constructing robust DNA dissipation systems but also greatly broadens the potential of DNA dissipation for applications in high-precision molecular recognition and complex biological reaction networks.

Emerging Data Processing Methods for Single-Entity Electrochemistry

Single-entity electrochemistry is a powerful tool that enables the study of electrochemical processes at interfaces and provides insights into the intrinsic chemical and structural heterogeneities of individual entities. Signal processing is a critical aspect of single-entity electrochemical measurements and can be used for data recognition, classification, and interpretation. In this review, we summarize the recent five-year advances in signal processing techniques for single-entity electrochemistry and highlight their importance in obtaining high-quality data and extracting effective features from electrochemical signals, which are generally applicable in single-entity electrochemistry. Moreover, we shed light on electrochemical noise analysis to obtain single-molecule frequency fingerprint spectra that can provide rich information about the ion networks at the interface. By incorporating advanced data analysis tools and artificial intelligence algorithms, single-entity electrochemical measurements would revolutionize the field of single-entity analysis, leading to new fundamental discoveries.

A Potentiometric Dual-Channel Microsensor Reveals that Fluctuation of H2 S is Less pH-Dependent During Spreading Depolarization in the Rat Brain

Spreading depolarization (SD) is one of the most common neuropathologic phenomena in the nervous system, relating to numerous diseases. However, real-time monitoring the rapid chemical changes during SD to probe the molecular mechanism remains a great challenge. We develop a potentiometric dual-channel microsensor for simultaneous monitoring of H2 S and pH featuring excellent selectivity and spatiotemporal resolution. Using this microsensor we first observe real time changes of H2 S and pH in the rat brain induced by SD. This changes of H2 S are completely suppressed when the rat pre-treats with aminooxyacetic acid (AOAA), a blocker to inhibit the H2 S-producing enzyme, indicating H2 S fluctuation might be related to enzyme-dependent pathway during SD and less pH-dependent. This study provides a new perspective for studying the function of H2 S and the molecular basis of SD-associated diseases.

Elucidating the Shape of Current Transients in Electrochemical Resistive-Pulse Sensing of Single Liposomes

Electrochemical resistive-pulse (ERP) sensing with conductive carbon nanopipettes (CNPs) has recently been developed and employed for the detection of single liposomes and biological vesicles, and for the analysis of redox molecules contained in such vesicles. However, the origins of different shapes of current transients produced by the translocation of single vesicles through the CNP remain poorly understood. Herein, we report extensive finite-element simulations of both portions of an ERP transient, the current blockage by a vesicle approaching and passing through the pipet orifice and the faradaic current spike due to oxidation/reduction of redox species released from a vesicle on the carbon surface, for different values of parameters defining the geometry and dynamics of the vesicle/CNP system. The effects of the pipet geometry, surface charge, transport, vesicle trajectory, and collision location on the shape of current transients are investigated. The possibility of quantitative analysis of experimental ERP transients produced by translocations of liposomes and extracellular vesicles by fitting them to simulated curves is demonstrated. The developed theory can enable a more reliable interpretation of complicated ERP signals and characterization of the size and contents of single biological and artificial vesicles.

Amperometric Identification of Single Exosomes and Their Dopamine Contents Secreted by Living Cells

Dopamine (DA) is an important neurotransmitter, which not only participates in the regulation of neural processes but also plays critical roles in tumor progression and immunity. However, direct identification of DA-containing exosomes, as well as quantification of DA in single vesicles, is still challenging. Here, we report a nanopipette-assisted method to detect single exosomes and their dopamine contents via amperometric measurement. The resistive-pulse current measured can simultaneously provide accurate information of vesicle translocation and DA contents in single exosomes. Accordingly, DA-containing exosomes secreted from HeLa and PC12 cells under different treatment modes successfully detected the DA encapsulation efficiency and the amount of exosome secretion that distinguish between cell types. Furthermore, a custom machine learning model was constructed to classify the exosome signals from different sources, with an accuracy of more than 99%. Our strategy offers a useful tool for investigating single exosomes and their DA contents, which facilitates the analysis of DA-containing exosomes derived from other untreated or stimulated cells and may open up a new insight to the research of DA biology.