Article, 2024

Multiparameter Sensing of Oxygen and pH at Biological Interfaces via Hyperspectral Imaging of Luminescent Sensor Nanoparticles

ACS Sensors, ISSN 2379-3694, Volume 9, 4, Pages 1763-1774, 10.1021/acssensors.3c01941

Contributors

Bognár, Zsófia 0000-0001-9270-8863 [1] [2] Moßhammer, Maria 0000-0002-7296-8673 [3] Brodersen, Kasper Elgetti 0000-0001-9010-1179 [3] [4] Bollati, Elena [3] Gyurcsányi, Róbert Ervin 0000-0002-9929-7865 [2] Kühl, Michael 0000-0002-1792-4790 (Corresponding author) [3]

Affiliations

  1. [1] Technical University of Denmark
  2. [NORA names: DTU Technical University of Denmark; University; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Budapest University of Technology and Economics
  4. [NORA names: Hungary; Europe, EU; OECD];
  5. [3] University of Copenhagen
  6. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD];
  7. [4] Roskilde University
  8. [NORA names: RUC Roskilde University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Chemical dynamics in biological samples are seldom stand-alone processes but represent the outcome of complicated cascades of interlinked reaction chains. In order to understand these processes and how they correlate, it is important to monitor several parameters simultaneously at high spatial and temporal resolution. Hyperspectral imaging is a promising tool for this, as it provides broad-range spectral information in each pixel, enabling the use of multiple luminescent indicator dyes, while simultaneously providing information on sample structures and optical properties. In this study, we first characterized pH- and O2-sensitive indicator dyes incorporated in different polymer matrices as optical sensor nanoparticles to provide a library for (hyperspectral) chemical imaging. We then demonstrate the successful combination of a pH-sensitive indicator dye (HPTS(DHA)3), an O2-sensitive indicator dye (PtTPTBPF), and two reference dyes (perylene and TFPP), incorporated in polymer nanoparticles for multiparameter chemical imaging of complex natural samples such as green algal biofilms (Chlorella sorokiniana) and seagrass leaves (Zostera marina) with high background fluorescence. We discuss the system-specific challenges and limitations of our approach and further optimization possibilities. Our study illustrates how multiparameter chemical imaging with hyperspectral read-out can now be applied on natural samples, enabling the alignment of several chemical parameters to sample structures.

Keywords

Hyperspectral, algal biofilms, alignment, biofilm, biological interfaces, biological samples, biology, cascade, chain, challenges, characterize PH, chemical, chemical dynamics, chemical imaging, combination, complex natural samples, complicated cascade, dye, dynamics, fluorescence, hyperspectral images, images, indicator dye, indicators, information, interface, leaves, library, limitations, matrix, multiparameter, multiparameter sensing, nanoparticles, natural samples, optical properties, optimization, optimization possibilities, outcomes, oxygen, pH, pH-sensitive indicator dye, parameters, pixel, polymer, polymer matrix, polymer nanoparticles, possibilities, process, properties, reaction, reaction chain, read-out, reference, reference dye, resolution, sample structure, samples, seagrass, seagrass leaves, seldom, sensing of oxygen, sensor nanoparticles, spectral information, stand-alone process, structure, study, system-specific challenges, temporal resolution

Funders

  • Danish Agency for Science and Higher Education
  • Danish National Research Foundation
  • European Commission
  • The Velux Foundations
  • Gordon and Betty Moore Foundation

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