No abstract

Identification of suspects via fingermark analysis is one of the mainstays of forensic science. The success in matching fingermarks, using conventional fingermark scanning and database searching, strongly relies on the enhancement method adopted for fingermark recovery; this in turn depends on the components present in the fingermarks, which will change over time. This work aims to develop a robust methodology for improved analytical detection of the fingermark components. For the first time, matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) has been used to image endogenous lipids from fresh and aged, groomed and ungroomed fingermarks. The methodology was initially developed using oleic acid which was detected along with its degradation products over a 7-day period, at three different temperatures in a time-course experiment. The optimised methodology was then transferred to the imaging analysis of real fingermark samples. Fingermark patterns were reconstructed by retrieving the m/z values of oleic acid and its degradation products. This allowed the three aged fingermarks to be distinguished. In order to prove that MALDI-MSI can be used in a non-destructive way, a simple washing protocol was adopted which returned a fingermark that could be further investigated with classical forensic approaches. The work reported here proves the potential and the feasibility of MALDI-MSI for the forensic analysis of fingermarks, thus making it competitive with other MSI techniques such as desorption electrospray ionisation (DESI)-MS. The feasibility of using MALDI-MSI in fingermark ageing studies is also demonstrated along with the potential to be integrated into routine fingermark forensic analysis.

The interactions of cisplatin and its analogues, transplatin, carboplatin and oxaliplatin, with hen egg white lysozyme were analysed through ESI mass spectrometry, and the resulting metallodrug-protein adducts identified; the X-ray crystal structure of the cisplatin lysozyme derivative, solved at 1.9 A resolution, reveals selective platination of imidazole Nepsilon of His15.

Matrix deposition is a crucial aspect for successful matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) analysis. The search for more efficient protocols over the years has resulted in the devising of "dry matrix methods" in which the matrix is solely or preliminarily deposited as powder and acts in most cases as a seeding agent. Although not fully embraced by the MALDI MSI community, these methods have proven to be more efficient in terms of ion intensity, ion abundance, and ion images in the experimental circumstances they were employed. Here we report a novel two-step matrix application method, that we have named the "dry-wet" method, where the matrix is dusted onto the sample followed by solvent spray using a robotic device. The new method has been successfully applied to the detection and mapping of several analyte classes within latent fingermarks. Dusting the matrix generated the added advantage of enhancing the latent fingermarks which are invisible. This allows not only for an optical image to be taken of the fingermark in situ but also bridges the gap in the application of MALDI MSI technology in this field; with the use of the methodology reported, fingermark enhancement, recovery, and analysis from different surfaces is now compatible with subsequent MALDI MSI analysis thus allowing visual and chemical information to be obtained simultaneously.

The development of tissue micro-array (TMA) technologies provides insights into high-throughput analysis of proteomics patterns from a large number of archived tumour samples. In the work reported here, matrix-assisted laser desorption/ionisation-ion mobility separation-mass spectrometry (MALDI-IMS-MS) profiling and imaging methodology has been used to visualise the distribution of several peptides and identify them directly from TMA sections after on-tissue tryptic digestion. A novel approach that combines MALDI-IMS-MSI and principal component analysis-discriminant analysis (PCA-DA) is described, which has the aim of generating tumour classification models based on protein profile patterns. The molecular classification models obtained by PCA-DA have been validated by applying the same statistical analysis to other tissue cores and patient samples. The ability to correlate proteomic information obtained from samples with known and/or unknown clinical outcome by statistical analysis is of great importance, since it may lead to a better understanding of tumour progression and aggressiveness and hence improve diagnosis, prognosis as well as therapeutic treatments. The selectivity, robustness and current limitations of the methodology are discussed.

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Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) can detect and image a variety of endogenous and exogenous compounds from latent fingermarks. This opportunity potentially provides investigators with both an image for suspect identification and chemical information to be used as additional intelligence. The latter becomes particularly important when the fingermark is distorted or smudged or when the suspect is not a previously convicted offender and therefore their fingerprints are not present in the National Fingerprint Database. One of the desirable pieces of intelligence would be the sex of the suspect from the chemical composition of a fingermark. In this study we show that the direct detection of peptides and proteins from fingermarks by MALDI MS Profiling (MALDI MSP), along with the multivariate modeling of the spectra, enables the determination of sex with 85% accuracy. The chemical analysis of the fingermark composition is expected to additionally provide information on traits such as nutritional habits, drug use or hormonal status.

MALDI-mass spectrometry imaging (MALDI-MSI) is a technique that allows proteomic information, that is, the spatial distribution and identification of proteins, to be obtained directly from tissue sections. The use of in situ enzymatic digestion as a sample pretreatment prior to MALDI-MSI analysis has been found to be useful for retrieving protein identification directly from formalin-fixed, paraffin-embedded (ffpe) tissue sections. Here, an improved method for the study of the distribution and the identification of peptides obtained after in situ digestion of fppe pancreatic tumor tissue sections by using MALDI-mass spectrometry imaging coupled with ion mobility separation (IMS) is described. MALDI-IMS-MS images of peptide obtained from pancreatic tumor tissue sections allowed the localization of tumor regions within the tissue section, while minimizing the peak interferences which were observed with conventional MALDI-TOF MSI. The use of ion mobility separation coupled with MALDI-MSI improved the selectivity and specificity of the method and, hence, enabled both the localization and in situ identification of glucose regulated protein 78 kDa (Grp78), a tumor biomarker, within pancreatic tumor tissue sections. These findings were validated using immunohistochemical staining.