"MALDI-CSI": A proposed method for the tandem detection of human blood and DNA typing from enhanced fingermarks

Matrix- and surface-assisted laser desorption/ionization-mass spectrometry analysis of fingermark components for forensic studies: current trends and future prospects

The chemical analysis of fingermarks (FMs) has attracted considerable attention in the realm of forensic investigations. Techniques based on direct ionization of a sample by laser irradiation, specifically matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS), have provided excellent figures of merit for analyzing high molecular-weight compounds. However, it can be challenging to analyze low molecular-weight compounds using MALDI-MS owing to potential interference produced by the organic matrices in the low molecular-weight region, which can impede the detection of small molecules (m/z < 700 Da). Alternately, surface-assisted laser desorption/ionization-mass spectrometry (SALDI-MS) has shown great promise for small molecules analysis owing to the unique properties of the nanostructures used, particularly, minimal chemical background in low m/z region improved the production of ions involved in this method. The advancement of MALDI-MS and SALDI-MS has propelled their application in the analysis of FM components, focused on gaining deep insights into individual traits. This review aims to outline the current role of MALDI-MS and SALDI-MS in the chemical analysis of FMs. It also describes the latest achievements in forensic intelligence derived from fingermark analysis using these powerful methods. The accomplishments include the understanding of certain characteristics and lifestyles of donors. The review offers a comprehensive overview of the challenges and demands in this field. It suggests potential enhancements in this rapidly expanding domain to bridge the gap between research and practical police casework.

Saliva identification in forensic samples by automated microextraction and intact mass analysis of statherin

The enzyme α-amylase has long been a commonly targeted protein in serological tests for saliva. While being especially abundant in saliva, α-amylase is detectable in vaginal secretions, sweat, fecal matter, breast milk and other matrices. As a result, assays for α-amylase only provide a presumptive indication of saliva. The availability of mass spectrometry-based tools for the detection of less abundant, but more specific, protein targets (e.g., human statherin) has enabled the development of high confidence assays for human saliva. Sample throughput, however, has traditionally been low due to multi-step workflows for protein extraction, quantitation, enzymatic digestion, solid phase cleanup, and nano-/capillary-based chromatography. Here, we present two novel "direct" single-stage extraction strategies for sample preparation. These feature immunoaffinity purification and reversed-phase solid-phase microextraction in conjunction with intact mass analysis of human statherin for saliva identification. Mass analysis was performed on the Thermo Scientific Q-Exactive™ Orbitrap mass spectrometer with a 10-min analytical run time. Data analysis was performed using Byos® from Protein Metrics. Two sample sets were analyzed with a population of 20 individuals to evaluate detection reliability. A series of casework-type samples were then assayed to evaluate performance in an authentic forensic context. Statherin was confidently identified in 92% and 71% of samples extracted using the immunoaffinity purification and solid phase microextraction approaches, respectively. Overall, immunoaffinity purification outperformed the solid phase microextraction, especially with complex mixtures. In toto, robotic extraction and intact mass spectrometry enable the reliable identification of trace human saliva in a variety of sample types.

Statistical Modelling Investigation of MALDI-MSI-Based Approaches for Document Examination

Questioned document examination aims to assess if a document of interest has been forged. Spectroscopy-based methods are the gold standard for this type of evaluation. In the past 15 years, Matrix-Assisted Laser Desorption Ionisation-Mass Spectrometry Imaging (MALDI-MSI) has emerged as a powerful analytical tool for the examination of finger marks, blood, and hair. Therefore, this study intended to explore the possibility of expanding the forensic versatility of this technique through its application to questioned documents. Specifically, a combination of MALDI-MSI and chemometric approaches was investigated for the differentiation of seven gel pens, through their ink composition, over 44 days to assess: (i) the ability of MALDI MSI to detect and image ink chemical composition and (ii) the robustness of the combined approach for the classification of different pens over time. The training data were modelled using elastic net logistic regression to obtain probabilities for each pen class and assess the time effect on the ink. This strategy led the classification model to yield predictions matching the ground truth. This model was validated using signatures generated by different pens (blind to the analyst), yielding a 100% accuracy in machine learning cross-validation. These data indicate that the coupling of MALDI-MSI with machine learning was robust for ink discrimination within the dataset and conditions investigated, which justifies further studies, including that of confounders such as paper brands and environmental factors.

Differentiating individuals through the chemical composition of their fingermarks

Fingermark patterns are one of the oldest means of biometric identification. During this last decade, the molecules that constitute the fingermark residue have gained interest among the forensic research community to gain additional intelligence regarding its donor profile including its gender, age, lifestyle or even its pathological state. In this work, the molecular composition of fingermarks have been studied to monitor the variability between donors and to explore its capacity to differentiate individuals using supervised multi-class classification models. Over one year, fingermarks from thirteen donors have been analysed by Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry Imaging (n = 716) and mined by different machine learning approaches. We demonstrate the potential of the fingermark chemical composition to help differentiating individuals with an accuracy between 80% and 96% depending on the period of sample collection for each donor and size of the pool of donors. It would be premature at this stage to transpose the results of this research to real cases, however the conclusions of this study can provide a better understanding of the variations of the chemical composition of the fingermark residue in between individuals over long periods and help clarifying the notion of donorship.

Use of Nanoparticle Decorated Surface-Enhanced Raman Scattering Active Sol-Gel Substrates for SALDI-MS Analysis

Spectroscopy and mass spectrometry techniques are sometimes combined into the same analytical workflow to leverage each technique's analytical benefits. This combined workflow is especially useful in forensic and medical contexts where samples are often precious in nature. Here, we adopt metal nanoparticle (NP) doped sol-gel substrates, initially developed for surface-enhanced Raman scattering (SERS) analysis, as surface-assisted laser desorption/ionization-mass spectrometry (SALDI-MS) substrates. Using dried blood and sample protocols previously developed for SERS analysis, we observe heme-related spectral features on both silver and gold NP substrates by SALDI-MS, demonstrating dual functionality for these orthogonal techniques. Modifying the dried blood extraction procedures also allows for the observation of blood triacylglycerols by SALDI-MS. This is the first demonstration of a SERS/SALDI-MS substrate based on a sol-gel scaffold and the first demonstration of a gold NP sol-gel substrate for SALDI-MS which features lower substrate-related SALDI-MS background compared to the silver substrate.

Forensic Discrimination of Differentially Sourced Animal Blood Using a Bottom-Up Proteomics Based MALDI MS Approach

Recently published work has reported the development and application of a bottom-up proteomic approach to distinguish between human and animal blood (down to animal species level), by rapid screening using Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS). In that study, it was additionally observed that intravenous animal blood exhibits different spectral profiles from blood collected within the animal chest cavity as well as from the diluted blood collected within packets of meat. In this follow-up study we explored the resulting hypothesis that, depending on how blood is shed or collected, protein biomarker profiles vary to the extent of systematically permitting a distinction between possible sources of blood (for example, flesh wound versus packaged meat). This intelligence may be important in reconstructing the dynamics of the crime. The combination of statistical analysis and tandem mass spectrometry has yielded additional animal blood markers as well as confirming the ability to correctly determine the animal species from which blood derived, regardless of the retailer selling it (amongst the five investigated). These data confirm the initial hypothesis and demonstrate the opportunity for the proteomics-MALDI combined approach to provide additional intelligence to the investigation of violent crimes when examining blood evidence.