Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published December 5, 2022 | Published
Journal Article Open

Molecular Level Sucrose Quantification: A Critical Review

Abstract

Sucrose is a primary metabolite in plants, a source of energy, a source of carbon atoms for growth and development, and a regulator of biochemical processes. Most of the traditional analytical chemistry methods for sucrose quantification in plants require sample treatment (with consequent tissue destruction) and complex facilities, that do not allow real-time sucrose quantification at ultra-low concentrations (nM to pM range) under in vivo conditions, limiting our understanding of sucrose roles in plant physiology across different plant tissues and cellular compartments. Some of the above-mentioned problems may be circumvented with the use of bio-compatible ligands for molecular recognition of sucrose. Nevertheless, problems such as the signal-noise ratio, stability, and selectivity are some of the main challenges limiting the use of molecular recognition methods for the in vivo quantification of sucrose. In this review, we provide a critical analysis of the existing analytical chemistry tools, biosensors, and synthetic ligands, for sucrose quantification and discuss the most promising paths to improve upon its limits of detection. Our goal is to highlight the criteria design need for real-time, in vivo, highly sensitive and selective sucrose sensing capabilities to enable further our understanding of living organisms, the development of new plant breeding strategies for increased crop productivity and sustainability, and ultimately to contribute to the overarching need for food security.

Additional Information

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This work was partially funded by the "OMICAS program: Optimización Multiescala In-silico de Cultivos Agrícolas Sostenibles (Infraestructura y validación en Arroz y Caña de Azúcar)" Scientific Ecosystem belonging to the Colombia Científica Program, sponsored by The World Bank, The Ministry of Science, Technology and Innovation (MINCIENCIAS), ICETEX, the Colombian Ministry of Education and the Colombian Ministry of Commerce, Industry and Tourism, under GRANT ID: FP44842-217-2018, OMICAS Award ID: 792-61187. Author Contributions. Conceptualization, G.A.L.-C. and A.J.-B.; writing—original draft preparation, G.A.L.-C.; writing—review and editing, A.J.-B. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.

Attached Files

Published - sensors-22-09511.pdf

Files

sensors-22-09511.pdf
Files (9.2 MB)
Name Size Download all
md5:fbb4434b1a5a851d919865cc7f159b2f
9.2 MB Preview Download

Additional details

Created:
August 22, 2023
Modified:
November 16, 2023