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Raman microspectroscopy for microbiology

Nature Reviews Methods Primers volume 1, Article number: 80 (2021) Cite this article

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Abstract

Raman microspectroscopy offers microbiologists a rapid and non-destructive technique to assess the chemical composition of individual live microorganisms in near real time. In this Primer, we outline the methodology and potential for its application to microbiology. We describe the technical aspects of Raman analyses and practical approaches to apply this method to microbiological questions. We discuss recent and potential future applications to determine the composition and distribution of microbial metabolites down to subcellular scale; to investigate the host–microorganism, cell–cell and cell–environment molecular exchanges that underlie the structure of microbial ecosystems from the ocean to the human gut microbiomes; and to interrogate the microbial diversity of functional roles in environmental and industrial processes — key themes in modern microbiology. We describe the current technical limitations of Raman microspectroscopy for investigation of microorganisms and approaches to minimize or address them. Recent technological innovations in Raman microspectroscopy will further reinforce the power and capacity of this method for broader adoptions in microbiology, allowing microbiologists to deepen their understanding of the microbial ecology of complex communities at nearly any scale of interest.

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Fig. 1: Raman spectroscopy working principles.
Fig. 2: Configuration of a Raman microspectroscopy system.
Fig. 3: Sample preparation.
Fig. 4: Raman data processing.
Fig. 5: Raman data interpretation.
Fig. 6: Applications of Raman-based cell sorting to link ecological roles of microorganisms to their genomic identities.
Fig. 7: Use of SERS tags for the quantification of the pathogen Staphylococcus aureus in various biofluids.

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Acknowledgements

R.S. acknowledges support from a Gordon and Betty Moore Foundation Symbiosis in Aquatic Systems Initiative Investigator Award (GBMF9197; https://doi.org/10.37807/GBMF9197), a grant from the Simons Foundation (542395) as part of the Principles of Microbial Ecosystems (PriME) Collaborative, a grant (315230_176189) from the Swiss National Science Foundation and support from the National Centre of Competence in Research (NCCR) Microbiomes (51NF40_180575). F.C.P. was supported by a Young Independent Research Group grant from the Austrian Science Fund (FWF; ZK-57). D.B. was supported by the Austrian Science Fund (FWF; P26127-B20 and P27831-B28), the United States Department of Energy (DE-SC0019012) and the European Research Council (ERC; Starting Grant: FunKeyGut 741623). Research in the lab of M.W. on Raman microspectroscopy and its application in microbial ecology was supported by an ERC Advanced Grant (Nitricare; 294343) and the Wittgenstein Award of the FWF (Z-383-B). W.E.H. acknowledges financial and instrumentational support from EPSRC (EP/M002403/1, EP/M02833X/1) and NERC (NE/M002934/1). G.T.T. acknowledges support from NSF-MRI grant OCE-1336724 and a Gordon and Betty Moore Foundation Grant no. 5064. J.K. acknowledges funding by ERC Starting Grant 259432 Multibiophot. J.-X.C. acknowledges support from NIH (R35 GM136223 and R01AI141439). The Stocker group thanks R. Naisbit for scientific editing.

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Author notes

  1. These authors contributed equally: Kang Soo Lee, Zachary Landry.

Authors and Affiliations

  1. Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland

    Kang Soo Lee, Zachary Landry & Roman Stocker

  2. Division of Microbial Ecology, Department of Microbiology and Ecosystem Science, Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

    Fátima C. Pereira, Michael Wagner & David Berry

  3. Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark

    Michael Wagner

  4. Department of Engineering Science, University of Oxford, Oxford, UK

    Wei E. Huang

  5. School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA

    Gordon T. Taylor

  6. Department of Chemistry, Humboldt-Universität zu Berlin, Berlin, Germany

    Janina Kneipp

  7. Institute of Physical Chemistry and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Jena, Germany

    Juergen Popp

  8. Leibniz Institute of Photonics Technology e.V. Jena and Leibniz Health Technology, Jena, Germany

    Juergen Popp

  9. Department of Electrical and Computer Engineering & Department of Biomedical Engineering, Boston University, Boston, MA, USA

    Meng Zhang & Ji-Xin Cheng

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Contributions

Introduction (R.S., K.S.L. and Z.L.); Experimentation (R.S., K.S.L., Z.L., M.W., G.T.T., J.K., M.Z. and J.-X.C.); Results (R.S., K.S.L., Z.L., M.W., W.E.H., G.T.T., J.K., M.Z. and J.-X.C.); Applications (R.S., K.S.L., Z.L., F.C.P., M.W., D.B. and J.P.); Reproducibility and data deposition (R.S., K.S.L. and Z.L.); Limitations and optimizations (R.S., K.S.L., Z.L. and G.T.T.); Outlook (R.S., K.S.L. and Z.L.); Overview of the Primer (R.S., K.S.L. and Z.L.).

Corresponding authors

Correspondence to Kang Soo Lee or Roman Stocker.

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The authors declare no competing interests.

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Nature Reviews Methods Primers thanks C. Garcia-Timmermans, A. Locke, G. Pezzotti and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Biostudies: http://www.ebi.ac.uk/biostudies

GAMESS: https://www.msg.chem.iastate.edu/gamess/capabilities.html

Horiba Scientific: https://static.horiba.com/fileadmin/Horiba/Products/Scientific/Molecular_and_Microanalysis/ACC_SERS_Subtrate/SERS_Substrate_Raman_MM_Brochure_Fr.pdf

KnowItAll: https://sciencesolutions.wiley.com/knowitall-spectroscopy-software/

OptiFDTD: https://optiwave.com/optifdtd-overview/

ORCA: https://www.orcasoftware.de/tutorials_orca/spec/IR.html#predicting-raman-spectra

Raman processor: https://github.com/harubang2/Raman_processor

SERSitive: https://sersitive.eu/about-substrates/?gclid=Cj0KCQjw24qHBhCnARIsAPbdtlIvxejBMIy2YjTc0L7kMLgjrAc6F97lVsLj_stqb32zoPx47PUIb2QaAhjsEALw_wcB

Supplementary information

Glossary

Fourier transform infrared (FTIR) spectroscopy

The other prominent method of vibrational spectroscopy, whereby absorption of light by a sample is used to identify the molecular composition of the sample.

Normal Raman microspectroscopy

A fundamental form of Raman microspectroscopy that relies on measurement of non-resonant, spontaneous scattering signals in which one out of ~106 incoming photons to a sample is scattered.

Wavenumber

A unit of frequency used in vibrational spectroscopy, defined as the frequency divided by the speed of the wave and thus equal to the number of waves within one centimetre.

Resonance Raman scattering

Raman scattering that arises when the wavelength of the incident laser beam matches the electronic transitions of a molecule, which generates much more intense Raman signals than normal Raman scattering.

Raman reporter

A chemical that generates a known surface-enhanced Raman scattering signal.

Mode-locked laser

A laser that produces ultrashort pulses on the picosecond or femtosecond scale.

Selection rules

Constraints that govern the likelihood of whether undergoing particular quantum transitions from one state to another is allowed or forbidden.

Beating frequency

Frequency difference between two electromagnetic waves that interfere constructively and destructively.

Spectral window

A spectral region of interest.

Diffraction grating

A glass plate etched with very close parallel lines that produces a spectrum from a coherent light beam by diffraction and interference of light and thus functions as a planar prism.

Chromatic aberration

Discrepancy of focus in axial and transverse directions between rays with different wavelengths after a focusing lens owing to the discordance of their refraction angles.

Galvomirrors

A pair of mirrors, each of which is integrated with a rapidly moving scanning motor, which enables enlargement of a laser beam spot to a small scanning area.

Dichroic mirror

An optical component for fluorescence microscopy by which monochromatic light for the excitation of fluorophores in a sample is separated from generated fluorescence signals.

Isotopologue

A molecule that is structurally identical yet differs from another by the presence of at least one atom that possesses a different number of neutrons.

Uniformly labelled tracer

A molecule in which all available positions for a given element are occupied by an isotopically heavy or radioactive nuclide, typically noted as [U-nE]compound, where n = atomic mass, E = elemental symbol, U = uniformly, followed by chemical form.

Fractional isotopic abundance

The proportion of atoms in a molecular pool populated by the heavy isotope — also referred to as atom% (multiplied by 100).

Biomolecular fingerprint

An indicator in which chemical properties of a biomolecule are encoded; in vibrational spectroscopy, collective vibrational frequencies in wavenumber of chemical bonds within a biomolecule.

Raman-silent

The absence of Raman-active vibrational modes.

Savitzky–Golay filter

A filter algorithm that fits a polynomial of a known order to each point in the spectrum, using a sliding window of a user-defined width, subsequently replacing each point with the fitted value at the centre of the window.

Vector normalization

A normalization approach in which the intensity at each wavenumber is divided by the square root of the sum of squares of intensities for all wavenumbers within a spectral window, such that the Euclidean distance from the origin in the multidimensional space is equal to 1.

Mahalanobis distance

A measure of the distance between a point and the centroid of a multivariate normal distribution, in units of standard deviation.

Non-negative matrix factorization

A technique that represents each point in a set of mixed spectra as a weighted mixture of a finite number of conserved sub-spectra, with the axes being directly interpretable as Raman sub-spectra.

Independent component analysis

A technique that optimizes a new set of axes to naively capture covariance between variables separately for each of a finite number of independently varying subsets of data.

Isotopomers

Isotopomers of a compound have the same number of each isotope, but their positions differ.

Voigt probability distribution profile

A convolution of Gaussian and Lorentzian probability distributions that is widely used in peak-fitting routines to describe the symmetry of peaks in Raman spectroscopy.

Chromophore

A region of a molecule where the energy difference between two molecular orbitals is within the visible spectrum, thus determining the colour of the molecule.

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Lee, K.S., Landry, Z., Pereira, F.C. et al. Raman microspectroscopy for microbiology. Nat Rev Methods Primers 1, 80 (2021). https://doi.org/10.1038/s43586-021-00075-6

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