Theo Murphy scientific meeting organised by Professor Ian Gilmore, Professor John Vickerman, Professor R. Graham Cooks, Professor Anne Dell CBE FRS and Professor Richard Caprioli
Theo Murphy scientific meeting organised by Professor Ian Gilmore, Professor John Vickerman, Professor R. Graham Cooks, Professor Anne Dell CBE FRS and Professor Richard Caprioli
Mass spectrometry imaging is a rapidly growing field to study molecules from the macro to nanoscale in 2D and 3D and in real-time. There are major challenges ahead to meet demanding requirements in biosciences and emerging electronics. This meeting brought together leaders in the principal techniques, innovators in instrumentation and data interpretation for in-depth scientific debate.
Download the meeting programme (PDF).
Enquiries: please contact Kavli.Events@royalsociety.org
Mass spectrometry based imaging (MSI) has matured to a high throughput tool in biomedical research. MALDI-MSI is routinely used to study protein and peptide distributions on tissue sections for the analysis of molecular signalling processes in various diseases. Studies have demonstrated excellent diagnostic and prognostic value that can be directly translated to the clinic. It is key to employ a multimodal biomolecular imaging approach combined with quantitative analytical proteomics and metabolomics. Innovations in the field target breaking boundaries in resolution, sensitivity and speed. The development of novel approaches such as microscope mode imaging combined with innovative detector technology and cluster based SIMS is one of these development areas. Here we discuss how the novel pixelated detectors can extend speed, spatial resolution and the molecular weight range that can sensitively be imaged. The imaging MS community is driving translational molecular imaging research and these needed developments rapidly forward. The results of the implementation of a pixelated detector array with extremely high charge sensitivity on a MALDI-equipped linear time-of-flight mass spectrometer or a q-ToF MS system are described. This coupling is shown to allow a significant increase in detection efficiency for large macromolecules (i.e., intact antibodies) having m/z values up and above 400,000 and thereby providing a means to make the detection of large macromolecules more accessible in MALDI-mass spectrometry. In addition, the direct imaging capabilities of this detector are shown allow visualisation of mass-dependent spatial distributions in the MALDI ion cloud and the effect the ion optics exerts on the ion cloud. Such capabilities are demonstrated to provide new insights into dynamic chemical phenomena occurring in the ion source, ion optics and resulting from fragmentation.
Mass spectrometry imaging (MSI) is ideally suited for the label-free spatially-resolved analysis of molecules in complex biological samples with high sensitivity, speed and unprecedented chemical specificity. We have developed nanospray desorption electrospray ionisation (nano-DESI) for ambient pressure imaging of biological samples without special sample pre-treatment. Furthermore, we have developed approaches for quantitative nano-DESI imaging of lipids and metabolites. In these experiments, quantification is performed by doping the nano-DESI solvent with appropriate standards and normalising the ion image of the endogenous lipids and metabolites to the ion image of the standard. This approach enables online quantification of biomolecules extracted from the biological sample without introducing any complexity into the experimental protocol. Nano-DESI has been used for or studying metabolite exchange between living microbial communities and quantitative imaging of lipids and metabolites in tissues.
MALDI MS is a versatile technique suitable for direct analysis and imaging of small and large molecules at atmosphere and in vacuo. Achievable sensitivity and laser focusing has improved significantly since MALDI MSI was first introduced and pixel sizes of ∼ 1 – 10 µm have been reported for some analytes in both microprobe and microscope modes of analysis. Fast stage operation and continuous movement and control of high-repetition rate lasers have been reported providing the increased throughput essential for wider use. The routine application of MALDI MSI in drug development and clinical settings is not yet widespread but steady development and innovation over the last 20 years has moved the technique ever closer to these goals. In this presentation the current state of the art in methods and instrumentation for MALDI MS imaging will be discussed.
Imaging imposes very stringent and ever increasing requirements on throughput and quality of mass spectrometric analysis. This talk is devoted to evolution of Orbitrap mass spectrometry from a non-relevance to imaging toward its current status as the one of the most important mass spectrometric technique for high-resolution, high mass accuracy imaging. This evolution was greatly facilitated by increasing variety and power of atmospheric pressure imaging ion sources as well as drastic increase of transmission of atmospheric-to-vacuum interfaces. As the result, paradigm shift from in-vacuum imaging to imaging at atmospheric pressure took place over recent years. It was accelerated by recent improvements in throughput for Q Exactive and Orbitrap Fusion families of instruments, with numerous new modes of operation and quantitation enabled by parallelisation of detection and ion processing and concerted operation of different ion-optical devices. In conclusion, future trends and perspectives of Orbitrap mass spectrometry for imaging applications are discussed.
Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME has three components—an open data model for biological imaging: OME data model; standardised file formats (OME-TIFF) and software libraries for file conversion (Bio-Formats); and a software platform for image data management and analysis (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualisation and analysis by remote access, enabling sharing and publishing of image data. OMERO’s model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening and recently into applications using non-image data from clinical and genomic studies Our current version, OMERO-5 improves support for large datasets and reads images directly from their original file format, allowing access by third party software. OMERO and Bio-Formats run the JCB DataViewer, the world’s first on-line scientific image publishing system and several other institutional image data repositories.
Metabolite profiling via LC/MS can reveal ‘interesting’ features, and subsequent tandem MS experiments provide powerful structural hints for the elucidation of these unknown mass spectral features. Reference libraries like MassBank and in-silico methods such as MetFrag help to identify compounds with tandem MS among candidate structures obtained from general purpose compound libraries. I won't give an answer to the question in the title; that will be part of the discussion.
Statistical methods are key for detecting systematic signal (e.g., caused by an intervention or a disease) in presence of variation and uncertainty, and for making objective and reproducible conclusions. This is particularly important for mass spectrometry-based imaging, where signals are obscured by 3 types of variation: the variation between different biological replicates, the spatial variation within images of a same biological replicate, and the technical variation due to sample handling and spectral acquisition. Moreover, the large-scale nature of mass spectrometry imaging experiments presents an additional challenge. As spatial and mass resolution increase, the experiments become more prone to generating spurious associations, and to amplifying bias and confounding. This talk will discuss the importance of statistical inference when designing and analysing mass spectrometry-based imaging experiments, as well as statistical methods and open-source software designed to facilitate the statistical inference tasks.
Imaging mass spectrometry (IMS) is a rapidly advancing technology, however the identification of species detected from tissue remains a significant challenge. Biomolecular identification strategies for IMS fall into two general categories: on-tissue fragmentation and indirect identification approaches. Since IMS analysis often ablates all material from the measurement area, on-tissue identification is typically performed using serial tissue sections or unmeasured regions of the sample. This can prove problematic because, for many ions, optical inspection alone is insufficient to determine their location, making manual prediction of where to focus fragmentation experiments impractical. Indirect identification is performed by using secondary information such as mass accuracy to link separate IMS and LC-ESI MS/MS experiments. This approach is often hampered by insufficient mass resolving power and accuracy for the imaging experiment to correlate results with high confidence. Here we describe novel methods for the identification of metabolites, lipids and proteins in molecular imaging experiments using high performance instrumentation and advanced computational approaches.
Now that mass spectrometry imaging has come of age, it is appropriate to ask more sophisticated questions about our images and to move away from the ‘show and tell’ modality. Do the mass spectra really provide an accurate view of the material, or do we see only what the technique wants us to see? A closer look at ionisation and a renewed effort at quantification seems appropriate at this point. Matrix effects, ion suppression and molecular desorption probabilities are all well-known factors that influence ion yields. For SIMS experiments, the chemical and physical nature of the projectile often leads to very different endpoints. Our use of laser post-ionisation of neutral molecules is helpful in disentangling the origin of matrix effects during imaging. Here we discuss how these factors interact and suggest approaches to mitigate these dreaded effects.
How does one map the chemistry of people as well as their associations with microbes? This is the fundamental question that will be addressed in this lecture. The key approach to understanding large volumes of mass spectrometry data that is generated generate is through visualisation. We will show how we map the chemistry of microbes on people and how to tease apart the origin of this information. Such chemistries are highly specialised. It turns out that people leave behind chemical traces, which we refer to as lifestyle chemistries, which can be detected on personal objects such as phones. Phones are great reporters of lifestyle chemistries. Similar human derived lifestyle chemistries can be detected in buildings, highlighting how people affect the chemistries in the build environment.
Matrix effects are a concern for most types of mass spectrometric approaches and are especially problematic for desorption ionisation techniques that employed for imaging. The lack of a separation step prior to ionisation of the analyte means that competition for charge during the desorption process can lead to extreme challenges for quantitation as one analyte may significantly suppress or enhance the ionisation of another. In biological analysis using both MALDI and SIMS the competition for charge has been shown to be related to the gas phase basicity of the analyte for the formation of [M±H]± ions although a wide range of different ion species can also be formed. In SIMS matrix effects can also arise from changes in the local sputter yield in the sample. Examples of matrix effects in SIMS analysis, particularly imaging, will be presented and the challenges associated with understanding and hence overcome these challenges will be discussed.
A newly discovered matrix-assisted ionisation (MAI) method is capable of spontaneously transferring compounds at least as large as the 66 KDa bovine serum albumin protein into multiply protonated gas-phase ions when the matrix:analyte sample is simply exposed to sub-atmospheric pressure conditions. Sub-atmospheric pressure can be assessed from atmospheric pressure at the inlet of a mass spectrometer or by introduction of the sample directly into vacuum using an intermediate pressure MALDI source. Further, gas-phase ions are observed multiply protonated even using aprotic matrices. 3-Nitrobenzonitrile was the first spontaneous MAI matrix discovered, but over 40 additional compounds with no specific structural motifs have subsequently been discovered. All spontaneous MAI matrices sublime in vacuum and thus are no more likely to contaminate the mass spectrometer ion optics than solvents used with ESI or APCI. The method has excellent sensitivity producing clean full-scan mass spectra using low femtomoles of, for example, peptides.
Current state-of-the-art in cancer diagnostics is centred around the histological examination of tumour tissue using classical histopathology complemented by immunochemical and molecular genetic methods. Due to the complexity of the diagnostic procedures, the reporting times range from few days to a few weeks, depending on the disease and the healthcare system. Excessively long reporting times combined with the high inter-observer variability of results lead to sub-optimal performance both for pre-interventional and intra-interventional diagnostics. Imaging mass spectrometry has been proposed more than a decade ago as an alternative to classical histopathology, however the technology has only recently reached sufficient maturity for clinical translation regarding both hardware and data interpretation algorithms. Desorption Electrospray Ionization is one of the most widely used imaging mass spectrometric modality showing certain advantages with regard to the ease of sample processing. We have used DESI MS imaging to analyse solid tumour specimens obtained from tumour resection procedures performed on ovarian cancer, colorectal cancer, breast cancer and oesophageal cancer patients. Imaging datasets were subjected to data pre-processing and were co-registered with optical image of the tissue sections stained following imaging MS. Tumour and peritumoral spectral data was associated with the histological type of the tumours, status of various biomarkers (including genetic and protein expression markers) and the stage of the disease. Additionally, data obtained by the analysis of gastrointestinal tumours was also associated with 16S rRNA sequencing-based microbiome composition data. Results revealed that lipidomic profiles of both solid tumours and their histological environment carry information about the diagnostic classification, stage and prognosis of the disease. Using this information, an MS imaging-based histological workflow have been developed for the diagnostics and stratification of cancer patients.
Recent improvements in spatial resolution and sensitivity will be reported for atmospheric-pressure scanning microprobe MALDI mass spectrometry imaging (AP-SMALDI MSI). The method has gained significant attention especially due to its capability to disclose morphologic distributions of substances in complex biological samples with high sensitivity, without vacuum-induced analyte losses or morphological artefacts. High resolution in mass and space has been used to derive distinct molecular information from sub-cellular structures. A commercial imaging ion source (AP-SMALDI10, TransMIT GmbH, Giessen, Germany) was modified in order to further improve spatial resolution. A new objective lens was developed and integrated into the ion source. Both, the commercial and the modified imaging ion sources were coupled to a Q ExactiveTM (Thermo Fisher Scientific) orbital trapping mass spectrometer, operated at a mass resolution of 140000 at m/z 200. Biological tissue samples were prepared from fresh frozen material and matrix-coated by various methods, for comparison of analytical sensitivity. Results demonstrate routine capability of the instrumentation to obtain high-quality, highly sensitive images without oversampling down to a step size (pixel resolution) of 2 µm.
I will sketch directions for instrument improvements and extensions of biomedical applications. The increase of ionisation yield with low energy cesium deposition. The elimination of analytical dead space and vignetting by replacing dynamic transfer and step scanning of the primary beam with nanometric stage scanning. The identification of individual cell types within a population, of cell organelles within a cell, and of molecules within organelles; this can be accomplished with correlated microscopy, SEM or TEM, and immuno-typing; it can be performed either on alternate sections or on the sample studied with several methodologies. Finally, the characterization of depth resolution using a model of a transmembrane protein labeled at a variety of positions with different tags.