Recombinant "IMS TAG" proteins : a new method for validating bottom-up matrix-assisted laser desorption/ionisation ion mobility separation mass spectrometry imaging

Rationale - Matrix assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI) provides a methodology to map the distribution of peptides generated by in situ tryptic digestion of biological tissue. It is challenging to correlate these peptides to the proteins from which they arise because of the many potentially overlapping and hence interfering peptide signals generated. Methods - A recombinant protein has been synthesised that when cleaved with trypsin yields a range of peptide standards for use as identification and quantification markers for multiple proteins in one MALDI-IMS-MSI experiment. Mass spectrometry images of the distribution of proteins in fresh frozen and formalin fixed paraffin embedded tissue samples following in situ tryptic digestion were generated by isolating signals on the basis of their m/z value and ion mobility drift time which were correlated to matching peptides in the recombinant standard. Results - Tryptic digestion of the IMS-TAG protein and MALDI-MS analysis yielded values for m/z and ion mobility drift time for the signature peptides included in it. MALDI-IMS-MSI images for the distribution of the proteins HSP 90 and Vimentin, in FFPE EMT6 mouse tumours and HSP-90 and Plectin in a fresh frozen mouse fibrosarcoma were generated by extracting ion images at the corresponding m/z and drift time from the tissue samples. Conclusions - The IMS-TAG approach provides a new means to confirm the identity of peptides generated by in situ digestion of biological tissue.</p

Examination of tumour tissues by direct MALDI-mass spectrometry imaging and profiling.

The purpose of the work described in this thesis was to develop and apply efficient methodologies based on MALDI-MSI for the direct analysis and targeting of protein tumour biomarkers within both frozen and formalin fixed paraffin embedded (FFPE) cancerous tissue sections.Method development for protein analysis directly in tumour tissue sections were performed using tumour xenograft models. This involved improvements in sample preparation, such as tissue washing protocols, and the development of data pre-processing methods prior to statistical analysis using a freely available software package, which referred to as Spec Align.The use of MALDI-MSI for studying proteome patterns directly from tumour tissue sections with no requirement for known targets is demonstrated. In addition, in situ identification of proteins within tumour tissue sections was achieved and correlated with their localisation. The method demonstrated here involved the use of octyl glucoside, a non-ionic detergent, which aims to improve the solubilisation and detection of low abundance and membrane-associated proteins within tumour tissue section after on-tissue digestion. The coupling of MALDI-MSI with ion mobility separation (IMS) has been found to improve the specificity and selectivity of the method.Combining these two methodological approaches allowed the targeting and identification of known tumour biomarkers and potential protein markers in various tumour tissue samples including frozen AQ4N dosed colon tumour xenografts and FFPE human adenocarcinoma tissue sections. The localisation and identification of proteins correlated to tumour growth and aggressiveness were studied using IMS-Tag MALDI-MSI, a novel concept developed in this work.In order to demonstrate its use as a potential biomarker discovery tool, MALDI-MSI was used for high throughput analysis of proteins within tissue micro arrays. Combining MALDI-MSI with statistical analysis allowed the design of a novel tumour classification model based on proteomic imaging information after on-tissue digestion.Another challenge for the MALDI-MSI technology is to achieve more targeted quantitative approaches for in situ analysis of proteins. A proof-of-concept based on multiple reaction monitoring (MRM) analysis with MALDI-MSI is described using a high repetition rate solid state laser. This aimed to improve the sensitivity and specificity of the methodology for the investigation of peptides/proteins directly within tumour tissue sections

A proteomic approach for the rapid, multi-informative and reliable identification of blood

Blood evidence is frequently encountered at the scene of violent crimes and can provide valuable intelligence in the forensic investigation of serious offences. Because many of the current enhancement methods used by crime scene investigators are presumptive, the visualisation of blood is not always reliable nor does it bear additional information. In the work presented here, two methods employing a shotgun bottom up proteomic approach for the detection of blood are reported; the developed protocols employ both an in solution digestion method and a recently proposed procedure involving immobilization of trypsin on hydrophobin Vmh2 coated MALDI sample plate. The methods are complementary as whilst one yields more identifiable proteins (as biomolecular signatures), the other is extremely rapid (5 minutes). Additionally, data demonstrate the opportunity to discriminate blood provenance even when two different blood sources are present in a mixture. This approach is also suitable for old bloodstains which had been previously chemically enhanced, as experiments conducted on a 9-year-old bloodstain deposited on a ceramic tile demonstrate

Identification of Hypoxia-Regulated Proteins Using MALDI-Mass Spectrometry Imaging Combined with Quantitative Proteomics

Hypoxia is present in most solid tumors and is clinically correlated with increased metastasis and poor patient survival. While studies have demonstrated the role of hypoxia and hypoxia-regulated proteins in cancer progression, no attempts have been made to identify hypoxia-regulated proteins using quantitative proteomics combined with MALDI-mass spectrometry imaging (MALDI-MSI). Here we present a comprehensive hypoxic proteome study and are the first to investigate changes in situ using tumor samples. In vitro quantitative mass spectrometry analysis of the hypoxic proteome was performed on breast cancer cells using stable isotope labeling with amino acids in cell culture (SILAC). MS analyses were performed on laser-capture microdissected samples isolated from normoxic and hypoxic regions from tumors derived from the same cells used in vitro. MALDI-MSI was used in combination to investigate hypoxia-regulated protein localization within tumor sections. Here we identified more than 100 proteins, both novel and previously reported, that were associated with hypoxia. Several proteins were localized in hypoxic regions, as identified by MALDI-MSI. Visualization and data extrapolation methods for the in vitro SILAC data were also developed, and computational mapping of MALDI-MSI data to IHC results was applied for data validation. The results and limitations of the methodologies described are discussed. 2014 American Chemical Societ

Distribution analysis of the putative cancer marker S100A4 across invasive squamous cell carcinoma penile tissue

MS-based proteomic methods were utilised for the first time in the discovery of novel penile cancer biomarkers. MALDI MS imaging was used to obtain the in situ biomolecular MS profile of squamous cell carcinoma of the penis which was then compared to benign epithelial MS profiles. Spectra from cancerous and benign tissue areas were examined to identify MS peaks that best distinguished normal epithelial cells from invasive squamous epithelial cells, providing crucial evidence to suggest S100A4 to be differentially expressed. Verification by immunohistochemistry resulted in positive staining for S100A4 in a sub-population of invasive but not benign epithelial cells

Proteomic analyses of serous and endometrioid epithelial ovarian cancers - cases studies - molecular insights of a possible histological etiology of serous ovarian cancer.

Peer reviewe

Multivariate analyses for biomarkers hunting and validation through on-tissue bottom-up or in-source decay in MALDI-MSI: application to prostate cancer.

peer reviewe

Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information

Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a powerful tool that enables the simultaneous detection and identification of biomolecules in analytes. MALDI-imaging mass spectrometry (MALDI-IMS) is a two-dimensional MALDI-mass spectrometric technique used to visualize the spatial distribution of biomolecules without extraction, purification, separation, or labeling of biological samples. MALDI-IMS has revealed the characteristic distribution of several biomolecules, including proteins, peptides, amino acids, lipids, carbohydrates, and nucleotides, in various tissues. The versatility of MALDI-IMS has opened a new frontier in several fields such as medicine, agriculture, biology, pharmacology, and pathology. MALDI-IMS has a great potential for discovery of unknown biomarkers. In this review, we describe the methodology and applications of MALDI-IMS for biological samples