Transcription Factor-Based Biosensors for Detecting Pathogens

Biosensors (Basel). 2022 Jun 29;12(7):470. doi: 10.3390/bios12070470.

Abstract

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.

Keywords: TF-based biosensors; biodetection; biosensors; cell-based biosensors; cell-free biosensors; pathogens.

Publication types

  • Review

MeSH terms

  • Biosensing Techniques* / methods
  • Electrochemistry / methods
  • Food Contamination
  • Humans
  • Nanotechnology / methods
  • Toxins, Biological*
  • Transcription Factors

Substances

  • Toxins, Biological
  • Transcription Factors

Grants and funding

This research was funded by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure, and Transport (Grant 22UGCP-B157945-03 to K.K.), the BioGreen21 Agri-Tech Innovation Program Rural Development Administration, Republic of Korea (Project No. PJ01567301 to G.J.), and the Basic Science Research Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning (NRF-2021R1F1A1056635 to Y.Y.).