Non-destructive Search for Life and Cancer
Multi-wavelength Raman Spectroscopy
Ideal instruments to search for life on an alien planet should follow the ancient truism from medicine "first do no harm" while at the same time providing unambiguous signatures for both geological and biological artifacts.
The reflectance, absorption, and fluorescence instruments discussed on this web site are rugged, highly efficient, and can rapidly identify "targets of geobioylogical interest". However, the signals generated by these techniques are often ambiguous at best and certainly fall far short of providing compelling identification of either geological or biological targets.
Laser Raman spectroscopy (LRS) can provide highly specific spectral fingerprints unambiguously identifying both geological and biological unknowns. Unlike infrared spectroscopy, LRS requires no sample preparation and operates without difficulty in aqueous environments. The two constraints on LRS are  fluorescence emissions from the target that swamp the Raman signa, and  the breaking and random rearrangement of covalent bonds either from high energy photons when employing laser wavelengths below 660 nm, or from increased thermal load when using infrared wavelengths. Dramatic increases in sensor efficiencies have significantly shortened exposure time sufficiently to make LRS safe for medical diagnostics and even allow the safe exploration of a single microbial cell.
Deep Ocean Drilling Project
Satellite image of drill site in Hilo Bay along with incident light photomicrograph and deep UV excited (Ex= both 224.3 & 248.6 nm ) native fluorescence image of 1 km deep basalt core. The glass contains vesicles (gas bubbles) up to 300 mm in diameter. Fluorescence signals from the clay lining the rim of the vesicles mark the regions of interest for the Raman probe.
Resonance Raman data were obtained with laser excitation (Ex=248.6 nm) of the sample area shown in Figures 4d and 4e. The activity between 1200 and 1600 wave numbers (cm-1) is expected from vibrational bending and stretching of heterocyclic and homocyclic ring structures of nucleic and aromatic amino acids (see text for details). The strong peak at 470 cm-1 can be assigned to silica, the activity at 800 cm1 is most likely the barely resolved doublet of olivine, and the peak at 1086 cm1 us characteristic of calcite. The Raman activity at 949 cm-1 is most similar to the calcium phosphate signatures found in the varnish coatings of basalt cobbles from the Lunar Crater volcanic field in Nevada [Israel et al., 1997]. The broad regions of activity around 2300 cm-1 and 3300 cm-1 result from CH and HOH, respectively.
Extraction of Both Laser Induced Fluorescence Emission (L.I.F.E.) and Raman Spectral Data
In the rush to acquire definitive Raman spectral data, the strong fluorescence response is most often discarded as simply confounding noise. We prefer to mine the information contained in both phenomena. Often the strong fluorescence response originates in trace molecular species not easily detected in the LRS data.
The upper panel in the graphic depicts the combined raw signal generated for the Pisgah crater exudate by laser excitation (Ex = 532 nm). The deconvolved fluorescence and Raman signals characteristic of diadochite appear in the two lower panels.
The rover, arm, and both spectrometers were designed and constructed by undergraduate physics and engineering students at Harvey Mudd College, Claremont, California.
Raman Detection of Breast Cancer Cells
Laser Raman spectra can provide a biochemical signature of the DNA, RNA, proteins, lipids, carbohydrates, and water comprising a human cell. A collaborative project between Harvey Mudd College, the City of Hope Cancer Research Hospital, and the Institute has now confirmed that near-infrared laser Raman spectroscopy (Ex = 1064 or 785 nm) can distinguish breast cancer cells from healthy tissue in 10 seconds. The project goal is the rapid evaluation of suspected tumor during surgical intervention.
Raman Exploration of Lava Tubes
A robotic rover interrogating a pale white exudate (broadband visible light excitation) in a Mojave desert lava tube near Pisgah Craer using an arm-mounted laser Raman spectrometer (Ex = 532 nm).
The resulting spectrum most closely resembles the Raman signature for the mineral diadochite with strong peaks at 996 and 1064 cm-1. This is a secondary mineral often found in caves resulting from a sulfate-rich solution reacting with an earlier phosphate deposit.
Storrie-Lombardi, M.C. et al.(1999) Ultraviolet Raman spectroscopy for in situ geobiological exploration of Mars. Amer Chem Soc 217: 069
Nealson, K. H., A. Tsapin and M. Storrie-Lombardi (2002). "Searching for life in the Universe: Unconventional methods for an unconventional problem." Intl. Microbio. 5(4): 223-230.
Fisk, M. R., M. C. Storrie-Lombardi, S. Douglas, R. Popa, G. McDonald and C. Di Meo-Savoie (2003). Evidence of biological activity in Hawaiian subsurface basalts. Geochem., Geophys., and Geosys. 4.
Storrie-Lombardi, M.C. (2005) Post-Bayesian strategies to optimize astrobiology instrument suites: lessons from Antarctica and the Pilbara. Proc. SPIE 5906: 288-301.
Ruiz La Riva, Alberto J. (2014) Simultaneous Collection of Resonance Raman and Fluorescent Signatures using a 405 nm Excitation Source (Senior Thesis) Department of Physics, Harvey Mudd College, Claremont, California, USA
Berger , Brett (2015) Designing, Building, and Testing a Robust Raman Spectrometer for Rapid and Nondestructive Material Characterization (Senior Thesis) Department of Physics, Harvey Mudd College, Claremont, California, USA
Zúñiga, W. C., Jones, V., Anderson, S. M., Echevarria, A., Miller, N. L., Stashko, C., Schmolze, D., Cha, P. D., Kothari, R., Fong, Y. and Storrie-Lombardi, M. C. (2019) Raman spectroscopy for rapid evaluation of surgical margins during breast cancer lumpectomy. Scientific Reports 9(1): 14639. https://www.nature.com/articles/s41598-019-51112-0
Kothari, R., Fong, Y. and Storrie-Lombardi, M. C. (2020) Review of laser raman spectroscopy for surgical breast cancer detection: Stochastic backpropagation neural networks. Sensors 20, 1-20 DOI: doi:10.3390/s20216260, (2020).
Kothari R, Jones V, Mena D, Reyes VBd, Shon Y, Smith JP, Schmolze D, Cha PD, Lai L, Fong Y and Storrie‐Lombardi MC. Raman spectroscopy and artificial intelligence to predict the bayesian probability of breast cancer. Scientific Reports 2021; 11: 11:6482. DOI: https://doi.org/10.1038/s41598-021-85758-6