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16 July 2026

Fighting crime with mass spectrometry imaging technology

Fingerprints have been the most powerful means of biometric identification for over a century. However, the process has remained largely unchanged in scope as only the physical characteristics of the ridge pattern are exploited to compare a crime scene mark with a fingerprint record, a process that leads to suspect identification if a match is found. Nonetheless, current fingerprinting may fail as in the case of smudged, partial and/or overlapped marks, or no fingerprint record. 

A new technique

In 2008, the Fingerprint Research Group (FRG) at Sheffield Hallam University led by Professor Simona Francese, initiated the development of Matrix Assisted Laser Desorption Ionisation Mass Spectrometry Profiling/Imaging (MALDI MSP/I) based methods for the chemical profiling/imaging of fingermarks (molecular fingerprinting), as well as their translation in an operational environment. 

Molecular fingerprinting enhances the forensic value of the fingermark evidence by detecting and visualising the molecules that can be found within, including contaminants, naturally occurring and introduced into the body. Molecular fingerprinting enables a novel way to conduct criminal profiling and to inform crime scene management, narrow down the pool of suspects and speed up investigations. 

The ridge pattern can be reconstructed through visualising the molecules that are detected while preserving the integrity of the evidence (Figure 1). 

The technology can provide ridge detail additional to that obtained by conventional CSI techniques in high spatial resolution (Figure 2).


Finger print lab work
Figure 4: Segmentation analysis of MALDI MSI of overlapping fingerprints. Three fingerprints could be distinguished in A (cluster image) and B (m/z 825.0822). The three prints are labelled in panel B as i-iii. Partial separation and recovery of ridge detail were achieved when imaging the cluster ions at m/z 368.4134 (C, mark i, complete separation), m/z 494.5507 (D, mark ii) and m/z 550.6123 (7E, mark iii). Francese et al 2026, submitted to FSI, under review.
Image showing the application of MALDI MSI on a fingerprint
Figure 2. Application of MALDI MSI following sequential processing of a latent fingermark on brown tape. Figure adapted from Bradshaw et al, Forensic Science International (2021), https://doi.org/10.1016/j.forsciint.2020.110643. Panels iii and v indicate optical images of the mark after CAF→ BY 40, CAF→ BY 40→PS and CAF→ BY 40→PS→BV3 respectively. Panels iv and vi indicate the corresponding MALDI MS images showing ridge flowing/detail complementing that revealed by the CSI technique.

Identifying a suspect

Higher likelihood of suspect identification can be achieved through:

• Stitching/superimposition of multiple molecular images from the thousands of molecules simultaneously detected (improving ridge pattern coverage/continuity).

• Separating overlapping fingermarks by individually recalling images of molecules that are uniquely distributed in each overlapping mark.

• Quickly grading fingermark ion images acquired. 

iFIS (intelligent Fingermark Imaging System), the first fingermark imaging dedicated software, developed in collaboration with Molecular Discovery Ltd, The University of Bradford UK, Waters Corporation UK and UK West Yorkshire Police, thanks to a UKDI, award boosts molecular fingerprinting by incorporating the above capabilities (and more) in one environment. As an example, Figure 3 shows improved ridge pattern coverage by superimposing multiple molecular images) and Figure 4 shows the separation of 3 finger mark's of which 2 belong to the same donor.

 

A mass spectrometry image of fingermarks
Figure 3: Separation of overlapping fingermarks by MALDI MSI. A: optical image of overlapping marks. B: Overlapping MALDI MS images from m/z signals unique to each mark. C: Separate recalling of MALDI MS images showing six different fingermarks (Bradshaw R. and Francese S, MALDI-MSI in the Forensic arena; In: Porta-Siegel T. (Ed) MALDI Mass Spectrometry Imaging: From Fundamentals to spatial Omics, RSC 2021).

Augmented by Artificial Intelligence, iFIS is capable of automatically grade fingermark images according to the Scotland Yard1-5 scale to rapidly retrieve the fingermark images with the highest potential to be identifiable marks.

Shaping the future of forensics

Since 2011, the applicability of molecular fingerprinting to crime scene investigation has attracted funding and research-shaping input from the Home Office, the Defence Science and Technology Laboratory (Dstl), West Yorkshire Police and the Netherlands Forensic Institute. 

As a result, molecular fingerprinting has been used in operational casework in the UK and overseas. One notable case was the examination of a crime scene mark from the Emilie Meng murder case in Denmark (the case was covered by Netflix in the documentary "A friend, a murderer" in 2026). Because of the increasing TRL, molecular fingerprinting by MALDI MSI has been incorporated into Home Office/Dstl edited Fingermark Visualisation Manual, and promoted to Cat B in 2022.

In collaboration with Waters Corporation, PhD student Rohith Krishna (co-funded by Waters Corporation and Sheffield Hallam University) is currently working in advancing further the capabilities of molecular fingerprinting particularly in the context of Drug Facilitated Sexual Assaults. PhD student George Ward is instead working at a new groundbreaking way to visualising fingermark through imaging bacterial molecular signatures in collaboration with West Midlands Police.


 

Molecular Fingerprinting at the intersection with clinical diagnostics

Fingermarks contain a plethora of biological molecules that are both sweat and migrating from the bloodstream to sweat glands. We have discovered that protein profiles of breast cancer patients differ according to their staging. In particular, from a swipe of a fingertip, using a combination of proteomics, MALDI MS and artificial intelligence, we can distinguish benign patients from early breast cancer women and metastatic patients with the 98% accuracy (Russo et al 2023 https://doi.org/10.1038/s41598-023-29036-7).

PhD student Lucy Burton, funded by the Yorkshire Biosciences Doctoral Training Programme, is currently working on validating the test on a larger cohort of donors.


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