For years, forensic scientists have been seeking new methods to improve existing techniques for the visualization of latent fingerprints. The structured combination of optical methods (diffused reflection, luminescence, UV absorption and reflection), physical methods (powdering, vacuum metal deposition, small particle reagent), physico-chemical methods (physical developer, multi-metal-deposition, iodine, cyanoacrylate), and chemical methods (ninhydrin and its analogues, DFO, etc.), permits a highly efficient processing of the secretions deposited by the fingers on a great variety of substrates. To visualize these developed fingerprints, alternative light sources or laser-based detection methods are commonly used. However, like all other existing techniques, these optical methods do not work in all possible cases, and certain types of latent fingerprints or object surfaces with unique characteristics may be problematic.

Matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) has been developed for visualization in which a UV pulsed laser rasters sequentially over a defined area of a sample while acquiring a mass spectrum from every location. From this array of spectra, analyte-specific images (molecular profiles) can be generated based on the selected masses, mapping precisely the analytes’ location on a surface.

To assess the possibility of fingerprint visualization with simultaneous chemical analysis based on MALDI-MSI, a model experiment was performed. Specifically, the finger of a 30-year-old man was lightly coated with ointment containing tocopherol and imprinted on a stainless steel MALDI plate. Application of low-concentrated tocopherol allows efficient laser ionization without use of matrices or additional treatment of the fingerprint. The result of the MS imaging scan shows that MALDI-MSI is a very promising analytical tool to be used in biometric research with good enough resolution and sensitivity, even for fast-mode of a scan.

The mass spectrometry method optimized for molecular peak and main fragments of tocopherol gave signal increase of over one order of magnitude. However, no clear fingerprint pattern was achieved for fingerprints without additives. The main reason is a lack of an efficient method for ionization, spectrometry, and data-processing of sweat components at this point. To develop improved mass spectrometry methods optimized for fingerprint scanning and signal enhancing, a better understanding of sweat component mass spectrometry was required.

As a result, the major objective of the second phase of this research was characterization of relevant biometry sweat components and MALDI-MS methods optimization. The most intensive, significant, and informative signal for fingerprint biometry applications can be attributed to 1.2 to 10.0 KDa mass range, which is characteristic for peptides and small proteins. A series of matrices and deposition techniques was evaluated for fingerprint signal enhancing in this mass range.

Another set of experiments was aimed to characterize previously described sweat compounds. For that purpose, collected sweat secretions were pre-concentrated and gel-filtrated through Sephadex G-10 Column to remove small molecules. MALDI-MS analysis of the concentrated sweat samples demonstrated features similar to the mass spectrum of the subject’s fingerprint.

This work was done by Bogdan Belgorodsky, Ludmila Fadeev, and Michael Gozin of Tel Aviv University for the Air Force Office of Aerospace Research & Development. For more information, download the Technical Support Package (free white paper) at  under the Physical Sciences category. AFRL-0173

This Brief includes a Technical Support Package (TSP).
MALDI-MSI Imaging of Latent Fingerprints

(reference AFRL-0173) is currently available for download from the TSP library.

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