1. Jenaer Workshop Spektralsensorik 0. September 00 Chemotaxonomische Identifikation einzelner Bakterienzellen mit Hilfe der Mikro-Raman- Spektroskopie Online-Monitoring von Bioaerosolen (OMIB) P. Rösch 1, M. Krause 1, R. Riesenberg und J. Popp 1, 1 Institute of Physical Chemistry, Friedrich-Schiller-University Jena, Helmholtzweg 4, D-043 Jena, Germany Institut für Photonische Technologien, Albert-Einstein-Str. 9, D-04 Jena, Germany http://www.ipc.uni-jena.de/ email: petra.roesch@uni-jena.de Content Bioaerosol Why Raman spectroscopy on bacteria? Online monitoring and identification of bioaerosols (OMIB) Classification and identification of bacteria by means of Raman spectroscopy Localization of bacteria Bacterial characterization with nanometer resolution Summary and outlook 1
Motivation - Bioaerosol Pollen 10 µm Bacteria Allergies, Diseases, Food Spoilage, etc. Dandruff, Grit, etc. 10 µm Fungi, Yeast 10 µm 10 µm 1 µm Identification of microorganisms without cultivation and the possibility to perform additional microbiological investigations 3 Bacterial identification in clean room productions Why clean room? Bacteria Bacillus pumilus (10) Bacillus sphaericus (10) Bacillus subtilis (19) Micrococcus luteus () Micrococcus lylae (3) Staphylococcus aureus (3) Staphylococcus cohnii (6) Staphylococcus epidermitis () Staphylococcus hominis (3) Staphylococcus warneri (3) Escherichia coli (10) Limited amount of species needed to be identified!!!! 4
Content Bioaerosol Why Raman spectroscopy on bacteria? Online monitoring and identification of bioaerosols (OMIB) Classification and identification of bacteria by means of Raman spectroscopy Localization of bacteria Bacterial characterization with nanometer resolution Summary and outlook The Raman Effect Rayleigh scattering Stokes-Raman scattering ν laser ν vib Anti-Stokes-Raman scattering ν laser + ν vib virtual states v = 1 Eigenstates v = 3 v = v = 1 v = 0 6 v = 0 3
Experimental setup C microscope µm BS1 M L N IF CCD spectrometer BS High specificity High spatial resolution (< 1 µm) Minimal sample preparation MO S W laser Content Bioaerosol Why Raman spectroscopy on bacteria? Online monitoring and identification of bioaerosols (OMIB) Classification and identification of bacteria by means of Raman spectroscopy Localization of bacteria Bacterial characterization with nanometer resolution Summary and outlook 4
Identification of a single microorganism (3 nm) M. luteus DSM 34 M. luteus DSM 0030 S. cohnii DSM 6669 M. lylae DSM 031 S. cohnii DSM 61 E. coli DSM 43 B. pumilus DSM B. pumilus DSM 361 B. sphaericus DSM B. sphaericus DSM 396 S. cohnii DSM 619 S. cohnii DSM 060 S. warneri DSM 0036 S. warneri DSM 0316 B. subtilis DSM 10 B. subtilis DSM 34 S. epidermitis RP 6A 3000 00 000 100 1000 3000 00 000 100 1000 9 Classification of single microorganism (3 nm) Data analysis by means of support vector machine Number of strains Number of spectra Number of wrong classified strain spectra Recognition rate for strains (%) Number of wrong classified species spectra Recognition rate for species (%) B. pumilus 100 19 0. 9. B. sphaericus 9 1 1. 11. B. subtilis 34 1 94.0 96.6 E. coli 666 1 3.1 99.1 M. luteus 66 10 93. 96.6 M. lylae 40 1 9. 1 9. S. cohnii 4 60 0 9. 11 9. S. epidermidis 9 9 9.6 9 9.6 S. warneri 13 11 9.1 4 9. S. cerevisiae 3 4 0. 6.9 Average recognition rate 33.6 9.4 10 P. Rösch, M. Harz, K.-D. Peschke, O. Ronneberger, H. Burkhardt, A. Schüle, G. Schmautz, M. Lankers, S. Hofer, H. Thiele, H-W. Motzkus, and J. Popp, Anal. Chem. 006,, 163-10.
Identification of single microorganism (3 nm) Identification of an independent dataset Strain Number of Spectra Correctly Identified as Bacillus subtilis DSM 34 Bacillus sphaericus DSM Bacillus sphaericus DSM 396 Escherichia coli DSM 43 Escherichia coli DSM 49 Escherichia coli DSM 10 0 1 E. coli DSM 499, E. coli DSM 43, E. coli DSM 69 Micrococcus luteus DSM 0030 6 6 Micrococcus lylae DSM 031 Micrococcus lylae DSM 031 Staphylococcus cohnii DSM 6669 Staphylococcus cohnii DSM 61 Staphylococcus cohnii DSM 619 Staphylococcus cohnii DSM 060 Staphylococcus epidermidis RP 6A Staphylococcus epidermidis 19 0 1 S. warner, E. coli Staphylococcus warneri DSM 0036 Identification 130 1 11 System integration P. Rösch, M. Harz, K.-D. Peschke, O. Ronneberger, H. Burkhardt, A. Schüle, G. Schmautz, M. Lankers, S. Hofer, H. Thiele, H-W. Motzkus, and J. Popp, Anal. Chem. 006,, 163-10. 1 6
Particles from clean room samples µm Raman-Intensität µm 3000 00 000 100 1000 00 Wellenzahl / cm -1 13 Online monitoring and identification of bioaerosols (OMIB) Particle deposition B. sphaericus S. epidermidis E. coli Microscopy Fluorescence Monitoring Raman Identification Identification rate: ~ 96 % M. luteus DSM 34 M. luteus DSM 0030 M. lylae DSM 031 M. lylae DSM 031 S. cohnii DSM 6669 S. cohnii DSM 61 S. cohnii DSM 619 S. cohnii DSM 060 S. warneri DSM 0036 S. warneri DSM 0316 14 S. epidermidis RP 6A P. Rösch, M. Harz, M. Schmitt, K.-D. Peschke, O. Ronneberger, H. Burkhardt, H-W. Motzkus, 3000 00 000 100 1000 M. Lankers, S. Hofer, H. Thiele and J. Popp, Appl. Environm. Microbiol. 00, 1, 166. Wavenumber / cm -1
Raman measurements on fluorescence marked bacteria SYTO 9 CH-stretching amide-i CN-stretching CH -scissoring 40µm 40µm 3000 00 000 100 1000 1 M. Krause, B. Radt, P. Rösch and J. Popp, J. Raman Spectrosc. 00, 3, 369-3. Content Bioaerosol Why Raman spectroscopy on bacteria? Online monitoring and identification of bioaerosols (OMIB) Classification and identification of bacteria by means of Raman spectroscopy Localization of bacteria Bacterial characterization with nanometer resolution Summary and outlook 16
Outlook: TERS - Tip enhanced Raman spectroscopy AFM-Cantilever Single SERS active particle Sample Illumination-/Collection- Optics Spatial resolution < 0 nm R. Stöckle, Y. D. Suh, V. Deckert, R. Zenobi, Chem. Phys. Lett., 000, 31, 131. 1 TER spectra on the bacterial cell TERS spectrum of a bacterial cell background 100 1600 1400 100 1000 00 600 U. Neugebauer, P. Rösch, M. Schmitt, J. Popp, C. Julien, A. Rasmussen, C. Budich, V. Deckert ChemPhysChem, 006,, 14-1430. 1 9
TERS: Characterization of cell wall components Amid I Amid II CO Streck (Aminos.) Amid III CC-Streck, CH-def. ip (Phe) NCO Deformation (Phe) Si (AFM-Tip) protein 100 1600 1400 100 1000 00 600 19 C=O (Ester) Phospholipid C=C Streck CH -deform CH -torsion.=ch in plane deform CC Streck lipid 100 1600 1400 100 1000 00 600 Si (AFM-Tip) Amid I Amid II CH 3, C(6)-H *COH CH -def CH -Kipp+OH-deform carbohydrate C-O-C in-plane symm. 100 1600 1400 100 1000 00 600 Si (AFM-Tip) Content Bioaerosol Why Raman spectroscopy on bacteria? Online monitoring and identification of bioaerosols (OMIB) Classification and identification of bacteria by means of Raman spectroscopy Localization of bacteria Bacterial characterization with nanometer resolution Summary and outlook 0 10
Summary and Outlook Identification of bacteria without cultivation by means of Raman spectroscopy and chemometric methods Localization of microorganisms with appropriate fluorescence staining techniques Adaptation of the database to the real condition Database with fluorescence stained bacteria Enlargement of meningitis database 1 Thanks! Prof. Dr. Jürgen Popp Dr. Denis Akimov, Dana Cialla, Valerian Ciobota, Susana Chatzipapadopoulos, Dr. Claudiu Dem, Thomas Dörfer, Torsten Frosch, Michaela Harz, Katharina Hering, Mario Krause, PD Dr. Antje Kriltz, Michael Kühnert, Christian Kuhnt, Susanne Liedtke, Tobias Meyer, Dr. Thomas Mayerhöfer, Dr. Robert Möller, Ute Neugebauer, Martin Presselt, Thomas Schüler, Stephan Stöckel, Katrin Strehle, PD Dr. Michael Schmitt, Dr. Nicu Tarcea, Dr. Beate Truckenbrodt, Stefanie Tschierlei, Ute Uhlemann, Angela Walter, Linda Zedler OMIB Prof. Dr. K. Baumann Prof. Dr. Dr. h.c. W. Kiefer Dr. Rainer Riesenberg Prof. H. Burkhardt, K.-D. Peschke and O. Ronneberger TERS Prof. Dr. V. Deckert, Dr. A. Rasmussen, C. Julien 11