Labelled IMS TAG Proteins for Quantitative Mass Spectrometry Imaging


The aim of this project is to reduce animal use by improving the utility of tissue engineered constructs through the development of quantitative mass spectrometry imaging (MSI) of proteins in these biomimetic 3D tissues.


Matrix-assisted laser deabsorption/deionisation mass spectrometric (MALDI-MS) imaging is a novel label-free imaging technique that can be used to image the responses of multiple proteins following drug treatment. The technique has been applied in the study of ex vivo human skin, 3D cellular skin models, human tumours, and allogenic animal tumour models. One of the major challenges facing MALDI-MS imaging is that changes in protein responses observed in the images generated cannot be quantified. This project will build on the concept of ‘IMS-TAG’ proteins to overcome this challenge and to validate the identity, and quantity, of specific proteins within biomimetic tissue constructs. These tools will be developed and tested in 3D skin and tumour spheroid models to demonstrate their utility in addressing specific research questions without animals.

Research details and methods

This project will demonstrate the use of MALDI-MS imaging for the quantification of proteins in response to treatments for common skin diseases and cytotoxic anti-tumour agents. It will develop novel ‘IMS-TAG’ proteins labelled with 15N and which contain signature peptides for clinically-relevant skin proteins involved in psoriasis and eczema, and one for proteins involved in responses to anti-tumour agents. These peptides will be released by enzymatic digestion of the ‘IMS-TAG’ protein and will be used as internal standards for quantitative MALDI-MS imaging experiments. Distribution of the target proteins as imaged using MALDI-MS imaging will be validated using traditional immunohistochemistry of the skin and tumour constructs.

MALDI-MS Imaging is a novel label free imaging technique that can be used to image the changes in multiple protein responses following treatment.  We have previously applied MALDI-MS imaging to the study of; ex vivo human skin, 3D cellular skin models as well as human tumours, xenografts  and allogenic animal tumour models. One of the major challenges facing MALDI-MS imaging is the quantification of changes in protein response observed in the images. To date, whilst progress has been made in quantitative analysis of small molecules by MALDI-MS imaging quantitative analysis of protein images has not been attempted.

We have recently introduced the concept of 'IMS-TAG' proteins for validation of protein identity. 'IMS-TAG' proteins are recombinant proteins produced to contain signature peptides from a variety of proteins of interest that are present in the tissue under study. These peptides are released by enzymatic digestion of the recombinant protein and are used as positive controls for matching accurate mass, ms/ms spectra and ion mobility drift times in imaging experiments.

Here it is proposed to further develop the 'IMS-TAG' idea by producing two 15N labelled 'IMS-TAG' proteins: one containing signature peptides for clinically relevant skin proteins involved in psoriasis and eczema and  one containig peptides for those proteins involved in cancer progressions. The enzymatically generated labelled peptides will then be used as internal standards for quantitative MALDI-MS imaging experiments by incorporation of the unlabelled protein into tissue homogenates to create calibration standard arrays and by subsequently spraying cut sections of the homogenate arrays with labelled protein as an internal standard. Although this study is being carried out on skin and tumour models the methodology would be directly applicable to all other tissues.

Software for the extraction of quantitative information will be developed in collaboration with Waters Corp.

Cole LM, Clench MR (2015). Mass spectrometry imaging tools in oncology. Biomark Med. 9(9): 863-8. doi: 10.2217/bmm.15.61.


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Strategic grant



Principal investigator

Professor Malcolm Clench


Sheffield Hallam University


Dr David Smith
Dr Neil Cross

Grant reference number


Award date:

Aug 2014 - Jul 2016

Grant amount