# Non-Invasive Real-Time Monitoring of Bacterial Activity by Non-Contact Impedance Spectroscopy for Off-the-Shelf Labware

## TL;DR

This paper introduces a non-contact method to monitor bacteria in real-time using impedance spectroscopy with regular lab equipment.

## Contribution

The novel non-contact impedance spectroscopy technique enables real-time bacterial monitoring without altering samples or using specialized equipment.

## Key findings

- NCIS data from KCl solutions align with a simple electrolytic conductivity model, showing its accuracy.
- NCIS measurements of bacterial cultures in glass bottles and plates correlated strongly with optical density measurements.
- Raman spectroscopy and machine learning confirmed the presence of bacterial cultures monitored via NCIS.

## Abstract

Monitoring bacterial activity is essential for numerous scientific and industrial applications. However, current benchmark measurements, i.e., optical density (OD), exhibit a limited dynamic range and require transparent or translucent media. Conventional impedance spectroscopy involves direct electrode contact with the bacterial medium or biofilm, potentially perturbing the sample environment and compromising measurement fidelity. Moreover, many real-time methods rely on costly, specialized labware that limits scalability and versatility. Here, we introduce a non-contact impedance spectroscopy (NCIS) technique with customizable electrodes for off-the-shelf labware and show that the data collected from a KCl solution series agree well with the simplest electrolytic conductivity cell model solution, demonstrating the accuracy and simplicity of NCIS. As an example of bacterial activity monitoring, NCIS was performed in glass laboratory bottles and 24-well plates in which Staphylococcus epidermidis and Escherichia coli cultures were inoculated into Brain Heart Infusion media, maintained at 37 °C. Comparative OD measurements acquired intermittently from the same media exhibited a strong correlation between NCIS and OD data, confirming reliability and reproducibility. The bacterial culture was verified by Raman spectroscopy assisted by machine learning. NCIS eliminates the risks of contamination and sample alteration, minimizing costs and operational complexity and providing a scalable, versatile solution for biological and chemical research.