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Characterizing glucose, illumination, and nitrogen-deprivation phenotypes of Synechocystis PCC6803 with Raman spectroscopy
- Source :
- PeerJ, Vol 8, p e8585 (2020)
- Publication Year :
- 2020
-
Abstract
- Background. Synechocystis sp. PCC6803 is a model cyanobacterium that has been studied widely and is considered for metabolic engineering applications. Here, Raman spectroscopy and Raman chemometrics (Rametrix (TM)) were used to (i) study broad phenotypic changes in response to growth conditions, (ii) identify phenotypic changes associated with its circadian rhythm, and (iii) correlate individual Raman bands with biomolecules and verify these with more accepted analytical methods. Methods. Synechocystis cultures were grown under various conditions, exploring dependencies on light and/or external carbon and nitrogen sources. The Rametrix (TM) LITE Toolbox for MATLAB (R) was used to process Raman spectra and perform principal component analysis (PCA) and discriminant analysis of principal components (DAPC). The Rametrix (TM) PRO Toolbox was used to validate these models through leave-oneout routines that classified a Raman spectrum when growth conditions were withheld from the model. Performance was measured by classification accuracy, sensitivity, and specificity. Raman spectra were also subjected to statistical tests (ANOVA and pairwise comparisons) to identify statistically relevant changes in Synechocystis phenotypes. Finally, experimental methods, including widely used analytical and spectroscopic assays were used to quantify the levels of glycogen, fatty acids, amino acids, and chlorophyll a for correlations with Raman data. Results. PCA and DAPC models produced distinct clustering of Raman spectra, representing multiple Synechocystis phenotypes, based on (i) growth in the presence of 5 mM glucose, (ii) illumination (dark, light/dark [12 h/12 h], and continuous light at 20 mE), (iii) nitrogen deprivation (0-100%NaNO3 of native BG-11 medium in continuous light), and (iv) throughout a 24 h light/dark (12 h/12 h) circadian rhythm growth cycle. Rametrix (TM) PRO was successful in identifying glucose-induced phenotypes with 95.3% accuracy, 93.4% sensitivity, and 96.9% specificity. Prediction accuracy was above random chance values for all other studies. Circadian rhythm analysis showed a return to the initial phenotype after 24 hours for cultures grown in light/dark (12 h/12 h) cycles; this did not occur for cultures grown in the dark. Finally, correlation coefficients (R > 0.7) were found for glycogen, all amino acids, and chlorophyll a when comparing specific Raman bands to other experimental results. National Science FoundationNational Science Foundation (NSF) [NSF1243988]; HATCH funds This research was funded by the National Science Foundation award NSF1243988. Collakova and Senger salaries are supported by HATCH funds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Subjects :
- Cyanobacteria
Principal component analysis
lcsh:Medicine
General Biochemistry, Genetics and Molecular Biology
Chemometrics
03 medical and health sciences
symbols.namesake
chemistry.chemical_compound
RametrixTM
Circadian rhythm
030304 developmental biology
Microbial phenotyping
chemistry.chemical_classification
0303 health sciences
biology
Glycogen
030306 microbiology
General Neuroscience
Synechocystis
lcsh:R
General Medicine
biology.organism_classification
Discriminant analysis
Amino acid
chemistry
Biochemistry
Raman spectroscopy
symbols
Rametrix (TM)
General Agricultural and Biological Sciences
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- PeerJ, Vol 8, p e8585 (2020)
- Accession number :
- edsair.doi.dedup.....5320f5822b9c534b0a65aa0e3561f3d9