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The invisible world of fingerprints revealed by mass spectrometry
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Resumo(s)
Fingerprints are unique to each individual and commonly correspond to a complex pattern of
ridges and valleys, crucial in Forensic Sciences for human identification. Throughout the years, this
has been one of the methods used in criminal investigations to place a suspect at a crime scene.
However, this method depends on the integrity of the fingermark, on the method used for its recovery,
and if the respective fingerprint is listed or not at the National/International Fingerprint Database.
However, the ridge pattern does not present all available human information. Most notably, the
chemical signature that is left behind, composed by endogenous, exogenous and semi-endogenous
compounds, are of great forensic importance.
Until now, human fingermarks have been mainly chemically analysed by low resolution mass
spectrometry methods. The first mass spectrometry technique used to study the fingerprint’s
composition was Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS).
With this technique, not only a fingerprint’s image is obtained, which may be used in a biometric
identification, but it is also possible to profile the fingerprint’s chemical composition. However, this
type of approach is not adequate to make a thorough characterization of small molecules, with
hundreds to thousands of metabolites detected. Another drawback in studying latent fingermarks
chemical composition, is their development with different reagents, making their characterization, by
mass spectrometry, an extremely complex affair in a realistic scenario.
Aiming an untargeted metabolomics approach to study the chemical composition in
fingermarks, this work was performed using the most extreme resolution and mass accuracy technique
available, Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS), enabling the
detailed description of the chemical complexity of dermo papillary residues and leading to the
identification of hundreds of chemical species and metabolites. Another purpose of this study was to
obtain relevant chemical information from fingermarks in the presence of common fingermark
developers like Instant White, Magnetic Latent Print Powder and Dragon’s Blood. In the optimization
tests the Magnetic Latent Print Powder proved that is not compatible with the analysis of fingermark
residue by FT-ICR MS. The study was performed with fingermarks of some volunteers, sex balanced
and within two age groups (18 - 30 years and 31 - 60 years), analysed by combining accurate mass
measurements using FT-ICR MS, database search like Human Metabolome Database (HMDB) and
molecular formula determination. Similarities between volunteers samples were identified by building
Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) models. Sex and
age discriminating compounds were identified by building Partial Least Squares – Discriminant
Analysis (PLS-DA) models.
With a small subset of samples with minor age ranges (20 – 30 years and 45 – 55 years), it
was possible to discriminate fingermarks by sex and age, where the fingermark developing powders
did not considerably affect the dermo papillary residue composition, since the chemical composition
of developed and non-developed samples was very similar. Several annotated compounds from this
group were obtained, most of them being lipids, mainly fatty acyls, glycerolipids, prenol lipids and
sphingolipids. In the analysis of all collected samples, the discrimination between sex and age was
more difficult due to similarities in the daily habits of individuals. Although it was not possible the
identification of chemical biomarkers of current daily habits or related with the medication taken by
the volunteers, it was possible the identification of some metabolites (hexadecasphinganine,
phytosphingosine and sphinganine) that most contribute for the discrimination of sex and age groups.
Therefore, the use of FT-ICR MS has proven to be a powerful analytical technique for
studying the chemical signature of fingermarks due to its unmatched resolution, mass accuracy and sensitivity for detecting any type of molecules, which could give an important contribution to Forensic
Sciences.
Descrição
Tese de mestrado, Química (Química), 2022, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Forense Impressões digitais Pós de revelação de impressões digitais Espectrometria de massa de ressonância ciclotrónica de ião com transformada de Fourier Metabolómica Teses de mestrado - 2023