Titelangaben
Liu, Xiao-Yang ; Guo, Shuxia ; Ramoji, Anuradha ; Bocklitz, Thomas ; Rösch, Petra ; Popp, Jürgen ; Yu, Han-Qing:
Spatiotemporal Organization of Biofilm Matrix Revealed by Confocal Raman Mapping Integrated with Non-negative Matrix Factorization Analysis.
In: Analytical Chemistry.
Bd. 92
(2020)
Heft 1
.
- S. 707-715.
ISSN 1520-6882
DOI: https://doi.org/10.1021/acs.analchem.9b02593
Abstract
Biofilms are microbial aggregates of microorganisms surrounded by a hydrogel-like matrix formed by extracellular polymeric substances (EPS). The formation of biofilms is intrinsically complex, from the attachment of microbial cells to the dispersion of the biofilm. Meanwhile, the three-dimensional framework built up by EPS changes with time and protects the microorganisms against environmental stress. Simultaneously acquiring chemical and structural information within the biofilm matrix is vital for the cognition and regulation of biofilms, yet it remains a great challenge due to the sample complexity and the limited approaches. In this study, confocal Raman microscopy and non-negative matrix factorization (NMF) analysis were combined to investigate spatiotemporal organization of Escherichia coli biofilms during development at molecular-level detail. The alternating non-negative least-squares (ANLS) approach was incorporated with the sequential coordinate-wise descent (SCD) algorithm to realize the NMF analysis for the large-scale hyperspectral data set. As a result, three components, including bacteria, protein, and polyhydroxybutyrate (PHB), were successfully resolved from the spectra of E. coli biofilm. Furthermore, the structural changes of biofilms could be visualized and quantified by their abundances derived from the NMF analysis, which might be related to the nutrient and oxygen gradient and physiological functions. This methodology provides a comprehensive understanding of the chemical constituents and their spatiotemporal distribution within the biofilm matrix. Furthermore, it also shows great potential for the analysis of unknown and complex biological samples with 3D Raman mapping. Biofilms are microbial aggregates of microorganisms surrounded by a hydrogel-like matrix formed by extracellular polymeric substances (EPS). The formation of biofilms is intrinsically complex, from the attachment of microbial cells to the dispersion of the biofilm. Meanwhile, the three-dimensional framework built up by EPS changes with time and protects the microorganisms against environmental stress. Simultaneously acquiring chemical and structural information within the biofilm matrix is vital for the cognition and regulation of biofilms, yet it remains a great challenge due to the sample complexity and the limited approaches. In this study, confocal Raman microscopy and non-negative matrix factorization (NMF) analysis were combined to investigate spatiotemporal organization of Escherichia coli biofilms during development at molecular-level detail. The alternating non-negative least-squares (ANLS) approach was incorporated with the sequential coordinate-wise descent (SCD) algorithm to realize the NMF analysis for the large-scale hyperspectral data set. As a result, three components, including bacteria, protein, and polyhydroxybutyrate (PHB), were successfully resolved from the spectra of E. coli biofilm. Furthermore, the structural changes of biofilms could be visualized and quantified by their abundances derived from the NMF analysis, which might be related to the nutrient and oxygen gradient and physiological functions. This methodology provides a comprehensive understanding of the chemical constituents and their spatiotemporal distribution within the biofilm matrix. Furthermore, it also shows great potential for the analysis of unknown and complex biological samples with 3D Raman mapping.
Weitere Angaben
Publikationsform: | Artikel in einer Zeitschrift |
---|---|
Begutachteter Beitrag: | Ja |
Institutionen der Universität: | Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
Titel an der UBT entstanden: | Nein |
Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 530 Physik |
Eingestellt am: | 16 Mai 2023 11:31 |
Letzte Änderung: | 16 Mai 2023 11:31 |
URI: | https://eref.uni-bayreuth.de/id/eprint/76339 |