[P002] Poster

1:00 PM - 1:50 PM JST(4:00 AM - 4:50 AM UTC)

[P01-110] Direct illumination of secondary metabolites in microbial colonies using Raman spectroscopy

○Shunnosuke Suwa¹, Masahiro Ando², Haruko Takeyama^1,2,3 (1. Grad. Sch. Adv. Sci. Eng., Waseda Univ. (Japan), 2. Res. Org. Nano Life Innov., Waseda Univ. (Japan), 3. Inst. Adv. Res. Biosyst. Dynam., Waseda Res. Inst. Sci. Eng., Waseda Univ. (Japan))

Keywords:

Secondary metabolites,Microbiology,Vibratinal Spectroscopy,Machine Learning,Macrobial Screening

[Purpose]We developed in situ microbial metabolomics for colonies making use of Raman spectroscopy and multivariate spectral analysis (Colony-Raman). Metabolites detection typically relies on LC, MS or NMR, requiring laborious and time-consuming sample processing. Shortening the experimental duration will lead to a rapid discovery of new compounds and selection of highly producing strains of specific compounds in biomanufacturing. We employed Raman spectroscopy, offering molecular fingerprint with no label and sample preprocessing, suitable for in situ biomolecular detection.[Method]First, to acquire enough signal, a new Raman spectrometer specifically for microbial colony analysis was configured. The petri dish was also modified to shorten the distance between colonies and the objective to tighten the laser focus. Second, to evaluate the metabolites production, semi-supervised MCR-ALS was developed. It decomposes the recorded data to the known compounds using reference standard spectra of the compounds and simultaneously to unknown ones, presumably new compounds. The approach was first considered using the artificially tailored Raman spectral dataset, the mixture of 15 components spectra including random noise and background. Next, the evaluation of metabolites production was performed by using several actinomycetes strains, prolific metabolites producers. Streptomyces coelicolor A3(2) produces undecylprodigiosin and actinorhodin. The production of the two compounds was evaluated by using reference spectra for the case of detecting the known compounds. Furthermore, amphotericin B produced by S. nodosus was also explored with no standard input, for the case of unknown detection.[Results]Refining the instruments allowed the acquisition of high signal-to-noise ratio Raman spectra from E. coli K12. The concept of semi-supervised MCR was proven by the successful decomposition of the artificial dataset with accuracy. For the microbial analysis, the production of undecylprodigiosin and actinorhodin in S. coelicolor A3(2) was successfully distinguished in colonies under both productive and unproductive conditions. For the exploration of amphotericin B, a newly extracted Raman spectrum showed prominent Raman bands which can be assigned to the compounds, with the strong spectral concentration in the colony area. The production of these metabolites was also confirmed by conventional LC-MS analysis.[Consideration]The limitation is the lower sensitivity compared to the conventional instrumental analysis and even for the single-cell Raman study. One possible cause is the inability of using objectives with high numerical aperture to minimize the autofluorescence. Further improvement in instrument and analysis is desired to make the method practical.[Conclusion]Colony-Raman was developed by both instrumental and analytical enhancement. It will open a new avenue for the new microbial metabolomics with the ability of label free, comprehensive molecular detection.