Search

The increase incidence of early colorectal cancer (T1 CRC) last years is mainly due to the introduction of population-based screening for CRC. T1 CRC staging based on histological criteria remains challenging and there is high variability among pathologists in the scoring of these criteria. It is crucial to unravel the biology behind the progression of adenoma into T1 CRC. Glycomic studies have reported extensively on alterations of the

Alternative techniques for probing hyperbolic phonon polaritons (HPPs) in two-dimensional materials will support the development of the emerging technologies in this field. Previous reports have shown that it is possible for $\mathrm{W}{\mathrm{Se}}_{2}$ monolayers in contact with the hexagonal boron nitride ($h\text{\ensuremath{-}}\mathrm{BN}$) to generate HPPs in the $h\text{\ensuremath{-}}\mathrm{BN}$ via Raman scattering. In this paper, we set out our results on HPP Raman scattering induced in $h\text{\ensuremath{-}}\mathrm{BN}$ by $\mathrm{W}{\mathrm{Se}}_{2}$ and $\mathrm{Mo}{\mathrm{Se}}_{2}$ monolayers including multiple resonances at which the Raman scattering is enhanced. Analysis of the observed Raman line shapes demonstrates that Raman scattering allows HPPs with wave vectors with magnitudes significantly in excess of $15\phantom{\rule{0.16em}{0ex}}000\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{--1}$ to be probed. We present evidence that the Raman scattering can probe HPPs with frequencies less than the expected lower bound on the reststrahlen band, suggesting new HPP physics still waits to be discovered.

Background Increasing evidence linking epigenetic mechanisms and different diseases, including cancer, has prompted in the last 15 years the investigation of histone post-translational modifications (PTMs) in clinical samples. Methods allowing the isolation of histones from patient samples followed by the accurate and comprehensive quantification of their PTMs by mass spectrometry (MS) have been developed. However, the applicability of these methods is limited by the requirement for substantial amounts of material. Results To address this issue, in this study we streamlined the protein extraction procedure from low-amount clinical samples and tested and implemented different in-gel digestion strategies, obtaining a protocol that allows the MS-based analysis of the most common histone PTMs from laser microdissected tissue areas containing as low as 1000 cells, an amount approximately 500 times lower than what is required by available methods. We then applied this protocol to breast cancer patient laser microdissected tissues in two proof-of-concept experiments, identifying differences in histone marks in heterogeneous regions selected by either morphological evaluation or MALDI MS imaging. Conclusions These results demonstrate that analyzing histone PTMs from very small tissue areas and detecting differences from adjacent tumor regions is technically feasible. Our method opens the way for spatial epi-proteomics, namely the investigation of epigenetic features in the context of tissue and tumor heterogeneity, which will be instrumental for the identification of novel epigenetic biomarkers and aberrant epigenetic mechanisms.

The functional form of Coulomb interactions in the transition metal dichalcogenides (TDMs) and other van der Waals solids is critical to many of their unique properties, e.g. strongly-correlated electron states, superconductivity and emergent ferromagnetism. This paper presents measurements of key excitonic energy levels in MoSe2/WSe2 heterostructures. These measurements are obtained from resonance Raman experiments on specific Raman peaks only observed at excited states of the excitons. This data is used to validate a model of the Coulomb potential in these structures which predicts the exciton energies to within ∼5 meV. This model is used to determine the effect of heterostructure formation on the single-particle band gaps of the layers and will have a wide applicability in designing the next generation of more complex TDM structures.

Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) of intact proteins is mostly performed using time-of-flight (TOF) based mass spectrometers, operated in linear mode. Linear MALDI-TOF systems provide limited mass resolving power and mass accuracy, which complicates assigning identities to the peaks in the MSI datasets. In this work we report ultra-high mass resolution MALDI-MSI based on 15T Fourier transform ion cyclotron resonance (FTICR) mass spectrometry for the analysis of intact proteins directly from non-embedded and OCT-embedded mouse and human (control and type 2 diabetes) pancreas so that small endocrine compartments (islets of Langerhans) may be analyzed in control and pathological tissues. Sample preparation methods, in terms of increased sensitivity while limiting lateral diffusion of analytes, have been investigated. By combining protein localization, high mass accuracy, and the clearly resolved isotope patterns we were able to assign protein identities with additional confidence, including proteins of similar average mass and with interspersed isotopomers. These capabilities allowed us to ascertain the presence of many protein adducts that, with a low resolving power instrument, could be misinterpreted as distinct protein ions. (C) 2017 Published by Elsevier B.V

Small extracellular vesicles have been intensively studied as a source of biomarkers in neurodegenerative disorders. The possibility to isolate neuron-derived small extracellular vesicles (NDsEV) from blood represents a potential window into brain pathological processes. To date, the absence of sensitive NDsEV isolation and full proteome characterization methods has meant their protein content has been underexplored, particularly for individual patients. Here, we report a rapid method based on an immunoplate covalently coated with mouse monoclonal anti-L1CAM antibody for the isolation and the proteome characterization of plasma-NDsEV from individual Parkinson’s disease (PD) patients. We isolated round-shaped vesicles with morphological characteristics consistent with exosomes. On average, 349 ± 38 protein groups were identified by liquid chromatography–tandem mass spectrometry (LC-MS/MS) analysis, 20 of which are annotated in the Human Protein Atlas as being highly expressed in the brain, and 213 were shared with a reference NDsEV dataset obtained from cultured human neurons. Moreover, this approach enabled the identification of 23 proteins belonging to the Parkinson disease KEGG pathway, as well as proteins previously reported as PD circulating biomarkers.

We present a high-resolution resonance Raman study of hBN encapsulated MoSe$_2$ and WSe$_2$ monolayers at 4 K using excitation energies from 1.6 eV to 2.25 eV. We report resonances with the WSe$_2$ A2s and MoSe$_2$ A2s and B2s excited Rydberg states despite their low oscillator strength. When resonant with the 2s states we identify new Raman peaks which are associated with intravalley scattering between different Rydberg states via optical phonons. By calibrating the Raman scattering efficiency and separately constraining the electric dipole matrix elements, we reveal that the scattering rates for k=0 optical phonons are comparable for both 1s and 2s states despite differences in the envelope functions. We also observe multiple new dispersive Raman peaks including a peak at the WSe$_2$ A2s resonance that demonstrates non-linear dispersion and peak-splitting behavior that suggests that the dispersion relations for dark excitonic states at energies near the 2s state are extremely complex., Submitted to IOP 2D Materials 16/04/20. Accepted in IOP 2D Materials 02/06/20. This is the version of the article before peer review or editing, as submitted by the authors to 2D Materials. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it

Myxoid liposarcoma (MLS) is the second most common subtype of liposarcoma, accounting for ~6% of all sarcomas. MLS is characterized by a pathognomonic FUS-DDIT3, or rarely EWSR1-DDIT3, gene fusion. The presence of ≥5% hypercellular round cell areas is associated with a worse prognosis for the patient and is considered high grade. The prognostic significance of areas with moderately increased cellularity (intermediate) is currently unknown. Here we have applied matrix-assisted laser desorption/ionization mass spectrometry imaging to analyze the spatial distribution of N-linked glycans on an MLS microarray in order to identify molecular markers for tumor progression. Comparison of the N-glycan profiles revealed that increased relative abundances of high-mannose type glycans were associated with tumor progression. Concomitantly, an increase of the average number of mannoses on high-mannose glycans was observed. Although overall levels of complex-type glycans decreased, an increase of tri- and tetra-antennary N-glycans was observed with morphological tumor progression and increased tumor histological grade. The high abundance of tri-antennary N-glycan species was also associated with poor disease-specific survival. These findings mirror recent observations in colorectal cancer, breast cancer, ovarian cancer, and cholangiocarcinoma, and are in line with a general role of high-mannose glycans and higher-antennary complex-type glycans in cancer progression.

Glioblastoma multiforme (GBM) is one of the most aggressive types of brain cancer, characterized by rapid progression, resistance to treatments, and low survival rates; the development of a targeted treatment for this disease is still today an unattained objective. Among the different strategies developed in the latest few years for the targeted delivery of nanotherapeutics, homotypic membrane-membrane recognition is one of the most promising and efficient. In this work, we present an innovative drug-loaded nanocarrier with improved targeting properties based on the homotypic recognition of GBM cells. The developed nanoplatform consists of boron nitride nanotubes (BNNTs) loaded with doxorubicin (Dox) and coated with cell membranes (CM) extracted from GBM cells (Dox-CM-BNNTs). We demonstrated as Dox-CM-BNNTs are able to specifically target and kill GBM cells in vitro, leaving unaffected healthy brain cells, upon successful crossing an in vitro blood-brain barrier model. The excellent targeting performances of the nanoplatform can be ascribed to the protein component of the membrane coating, and proteomic analysis of differently expressed membrane proteins present on the CM of GBM cells and of healthy astrocytes allowed the identification of potential candidates involved in the process of homotypic cancer cell recognition. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement N°709613, SLaMM).

Mass spectrometry imaging (MSI) can reveal biochemical information directly from a tissue section. MSI generates a large quantity of complex spectral data which is still challenging to translate into relevant biochemical information. Here, we present rMSIproc, an open-source R package that implements a full data processing workflow for MSI experiments performed using TOF or FT-based mass spectrometers. The package provides a novel strategy for spectral alignment and recalibration, which allows to process multiple datasets simultaneously. This enables to perform a confident statistical analysis with multiple datasets from one or several experiments. rMSIproc is designed to work with files larger than the computer memory capacity and the algorithms are implemented using a multi-threading strategy. rMSIproc is a powerful tool able to take full advantage of modern computer systems to completely develop the whole MSI potential., This work has been supported by the Spanish Ministry of Economy and Competitiveness through project TEC2015-69076-P, PRs predoctoral grant no. BES-2013-065572, project BFU2017-89336-R, the Direcció General de Recerca of the Government of Catalonia through project 2017 SGR 1119 and IPT’s fellowship from the Spanish Ministry of Education, Culture and Sports grant no. FPU 14/04457.

Mass spectrometry imaging (MSI) has provided many results with translational character, which still have to be proven robust in large patient cohorts and across different centers. Although formalin-fixed paraffin-embedded (FFPE) specimens are most common in clinical practice, no MSI multicenter study has been reported for FFPE samples. Here, we report the results of the first round robin MSI study on FFPE tissues with the goal to investigate the consequences of inter- and intracenter technical variation on masking biological effects. A total of four centers were involved with similar MSI instrumentation and sample preparation equipment. A FFPE multi-organ tissue microarray containing eight different types of tissue was analyzed on a peptide and metabolite level, which enabled investigating different molecular and biological differences. Statistical analyses revealed that peptide intercenter variation was significantly lower and metabolite intercenter variation was significantly higher than the respective intracenter variations. When looking at relative univariate effects of mass signals with statistical discriminatory power, the metabolite data was more reproducible across centers compared to the peptide data. With respect to absolute effects (cross-center common intensity scale), multivariate classifiers were able to reach on average > 90% accuracy for peptides and > 80% for metabolites if trained with sufficient amount of cross-center data. Overall, our study showed that MSI data from FFPE samples could be reproduced to a high degree across centers. While metabolite data exhibited more reproducibility with respect to relative effects, peptide data-based classifiers were more directly transferable between centers and therefore more robust than expected. Graphical abstractᅟ Electronic supplementary material The online version of this article (10.1007/s00216-018-1216-2) contains supplementary material, which is available to authorized users.

Chemical hydrolysis assisted by microwave irradiation has been proposed as an alternative method for the analysis of proteins in highly insoluble matrices. In this work, chemical hydrolysis was applied for the first time to detect degraded proteins from paintings and polychromies. To evaluate the performance of this approach, the number of identified peptides, protein sequence coverage (%), and PSMs were compared with those obtained using two trypsin-based proteomics procedures used for the analysis of samples from cultural heritage objects. It was found that chemical hydrolysis allowed the successful identification of all proteinaceous materials in all paint samples analyzed except for egg proteins in one extremely degraded sample. Moreover, in one sample, casein was only identified by chemical digestion. In general, chemical hydrolysis identified more peptides, more PSM's, and greater sequence coverage in the samples containing caseins, and often also in animal glue, highlighting the great potential of this approach for the rapid digestion and identification of insoluble and degraded proteins from the field of the cultural heritage.

We present temperature-dependent resonance Raman measurements on monolayer WS2 for the temperature range 4–295 K using excitation photon energies from 1.9 to 2.15 eV in ∼7 meV steps. These are analyzed to determine the resonance profiles of five previously assigned phonon based Raman peaks (A1′, E′, 2ZA, LA, 2LA) and a previously unassigned peak at 485 cm–1 whose possible attributions are discussed. The resonance profiles obtained are fitted to a perturbation theory derived model and it is shown that both excitons and trions are required to explain the profiles. The model is used to separate the contribution of exciton–exciton, trion–trion, and exciton–trion scattering to each of the Raman peaks at 4 K. This separation allows the ratios of the rates of scattering involving the A1′ and E′ phonons for each of the three types of scattering to be determined. The explanation of the multiphonon Raman peaks requires the coupling of bright excitons and trions to large wavevector dark states. The fitting of the resonance Raman profiles for these Raman peaks demonstrates scattering of bright excitons to bright trions via these large wavevector dark states.

In a polychrome artefact, coloured paint layers are applied on architectural elements or sculptures. Paint layers are made up of the colour, which is most typically an inorganic pigment and, with the exception of frescos, an organic binder, which enables the pigment to be dispersed and applied with a brush. From an analytical point of view the characterisation of organic paint binders is very challenging: the organic matter represents a very small amount of the total weight of the sample which is very small and aged. In this paper we describe the analytical approach applied for the characterisation of samples collected from a selection Gandhara polychromies. The analytical strategies and techniques employed are described and examples of the results obtained are presented., Restauro Archeologico, Vol. 27 No. 1 (2019)

Scope In biomedical research, mass spectrometry imaging (MSI) can obtain spatially-resolved molecular information from tissue sections. Especially matrix-assisted laser desorption/ionization (MALDI) MSI offers, depending on the type of matrix, the detection of a broad variety of molecules ranging from metabolites to proteins, thereby facilitating the collection of multilevel molecular data. Lately, integrative clustering techniques have been developed that make use of the complementary information of multilevel molecular data in order to better stratify patient cohorts, but which have not yet been applied in the field of MSI. Materials and Methods In this study, the potential of integrative clustering is investigated for multilevel molecular MSI data to subdivide cancer patients into different prognostic groups. Metabolomic and peptidomic data are obtained by MALDI-MSI from a tissue microarray containing material of 46 esophageal cancer patients. The integrative clustering methods Similarity Network Fusion, iCluster, and moCluster are applied and compared to non-integrated clustering. Conclusion The results show that the combination of multilevel molecular data increases the capability of integrative algorithms to detect patient subgroups with different clinical outcome, compared to the single level or concatenated data. This underlines the potential of multilevel molecular data from the same subject using MSI for subsequent integrative clustering.

Krabbe disease is a rare, childhood lysosomal storage disorder caused by a deficiency of galactosylceramide beta-galactosidase (GALC). The major effect of GALC deficiency is the accumulation of psychosine in the nervous system and widespread degeneration of oligodendrocytes and Schwann cells, causing rapid demyelination. The molecular mechanisms of Krabbe disease are not yet fully elucidated and a definite cure is still missing. Here we report the first in-depth characterization of the proteome of the Twitcher mouse, a spontaneous mouse model of Krabbe disease, to investigate the proteome changes in the Central and Peripheral Nervous System. We applied a TMT-based workflow to compare the proteomes of the corpus callosum, motor cortex and sciatic nerves of littermate homozygous Twitcher and wild-type mice. More than 400 protein groups exhibited differences in expression and included proteins involved in pathways that can be linked to Krabbe disease, such as inflammatory and defense response, lysosomal proteins accumulation, demyelination, reduced nervous system development and cell adhesion. These findings provide new insights on the molecular mechanisms of Krabbe disease, representing a starting point for future functional experiments to study the molecular pathogenesis of Krabbe disease. Data are available via ProteomeXchange with identifier PXD010594.

Mass spectrometry imaging (MSI) is a molecular imaging technique that maps the distribution of molecules in biological tissues with high spatial resolution. The most widely used MSI modality is matrix-assisted laser desorption/ionization (MALDI), mainly due to the large variety of analyte classes amenable for MALDI analysis. However, the organic matrices used in classical MALDI may impact the quality of the molecular images due to limited lateral resolution and strong background noise in the low mass range, hindering its use in metabolomics. Here we present a matrix-free laser desorption/ionization (LDI) technique based on the deposition of gold nanolayers on tissue sections by means of sputter-coating. This gold coating method is quick, fully automated, reproducible, and allows growing highly controlled gold nanolayers, necessary for high quality and high resolution MS image acquisition. The performance of the developed method has been tested through the acquisition of MS images of brain tissues. The obtained spectra showed a high number of MS peaks in the low mass region (m/z below 1000 Da) with few background peaks, demonstrating the ability of the sputtered gold nanolayers of promoting the desorption/ionization of a wide range of metabolites. These results, together with the reliable MS spectrum calibration using gold peaks, make the developed method a valuable alternative for MSI applications.

Atherosclerosis is characterized by fatty plaques in large and medium sized arteries. Their rupture can causes thrombi, occlusions of downstream vessels and adverse clinical events. The investigation of atherosclerotic plaques is made difficult by their highly heterogeneous nature. Here we propose a spatially resolved approach based on matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging to investigate lipids in specific regions of atherosclerotic plaques. The method was applied to a small dataset including symptomatic and asymptomatic human carotid atherosclerosis plaques. Tissue sections of symptomatic and asymptomatic human carotid atherosclerotic plaques were analyzed by MALDI mass spectrometry imaging (MALDI MSI) of lipids, and adjacent sections analyzed by histology and immunofluorescence. These multimodal datasets were used to compare the lipid profiles of specific histopathological regions within the plaque. The lipid profiles of macrophage-rich regions and intimal vascular smooth muscle cells exhibited the largest changes associated with plaque outcome. Macrophage-rich regions from symptomatic lesions were found to be enriched in sphingomyelins, and intimal vascular smooth muscle cells of symptomatic plaques were enriched in cholesterol and cholesteryl esters. The proposed method enabled the MALDI MSI analysis of specific regions of the atherosclerotic lesion, confirming MALDI MSI as a promising tool for the investigation of histologically heterogeneous atherosclerotic plaques.

Hybridisation of electronic bands of two-dimensional materials, assembled into twistronic heterostructures, enables one to tune their optoelectronic properties by selecting conditions for resonant interlayer hybridisation. Resonant interlayer hybridisation qualitatively modifies the excitons in such heterostructures, transforming these optically active modes into superposition states of interlayer and intralayer excitons. For MoSe$_2$/WSe$_2$ heterostructures, strong hybridization occurs between the holes in the spin-split valence band of WSe$_2$ and in the top valence band of MoSe$_2$, especially when both are bound to the same electron in the lowest conduction band of WSe$_2$. Here we use resonance Raman scattering to provide direct evidence for the hybridisation of excitons in twistronic MoSe$_2$/WSe$_2$ structures, by observing scattering of specific excitons by phonons in both WSe$_2$ and MoSe$_2$. We also demonstrate that resonance Raman scattering spectroscopy opens up a wide range of possibilities for quantifying the layer composition of the superposition states of the exciton and the interlayer hybridisation parameters in heterostructures of two-dimensional materials., Comment: 32 pages, 5 figures, 8 supplementary figures, 8 supplementary tables. 2D Mater. (2021)

Background Glioblastomas are the most aggressive type of brain tumor. A successful treatment should aim at halting tumor growth and protecting neuronal cells to prevent functional deficits and cognitive deterioration. Here, we exploited a Rho GTPase-activating bacterial protein toxin, cytotoxic necrotizing factor 1 (CNF1), to interfere with glioma cell growth in vitro and vivo. We also investigated whether this toxin spares neuron structure and function in peritumoral areas. Methods We performed a microarray transcriptomic and in-depth proteomic analysis to characterize the molecular changes triggered by CNF1 in glioma cells. We also examined tumor cell senescence and growth in vehicle- and CNF1-treated glioma-bearing mice. Electrophysiological and morphological techniques were used to investigate neuronal alterations in peritumoral cortical areas. Results Administration of CNF1 triggered molecular and morphological hallmarks of senescence in mouse and human glioma cells in vitro. CNF1 treatment in vivo induced glioma cell senescence and potently reduced tumor volumes. In peritumoral areas of glioma-bearing mice, neurons showed a shrunken dendritic arbor and severe functional alterations such as increased spontaneous activity and reduced visual responsiveness. CNF1 treatment enhanced dendritic length and improved several physiological properties of pyramidal neurons, demonstrating functional preservation of the cortical network. Conclusions Our findings demonstrate that CNF1 reduces glioma volume while at the same time maintaining the physiological and structural properties of peritumoral neurons. These data indicate a promising strategy for the development of more effective antiglioma therapies.

Mass spectrometry imaging (MSI) is a powerful molecular imaging technique. In microprobe MSI, images are created through a grid-wise interrogation of individual spots by mass spectrometry across a surface. Classical statistical tests for within-sample comparisons fail as close-by measurement spots violate the assumption of independence of these tests, which can lead to an increased false-discovery rate. For spatial data this effect is referred to as spatial autocorrelation. In this study we investigated spatial autocorrelation in three different matrix-assisted laser desorption/ionization MSI datasets. These datasets cover different molecular classes (metabolites/drugs, lipids, and proteins) and different spatial resolutions ranging from 20 µm to 100 µm. Significant spatial autocorrelation was detected in all three datasets and found to increase with decreasing pixel size. To enable statistical testing for differences in mass signal intensities between regions of interest within MSI datasets, we propose the use of Conditional Autoregressive (CAR) models. We show that by accounting for spatial autocorrelation, discovery rates (i.e. the ratio between the features identified and the total number of features) could be reduced between 21% and 69%. The reliability of this approach was validated by control mass signals based on prior knowledge. In light of the advent of larger MSI datasets based on either an increased spatial resolution or 3D datasets, accounting for effects due to spatial autocorrelation becomes even more indispensable. Here we propose a generic and easily applicable workflow to enable within-sample statistical comparisons.

This paper presents the results of measurements of the temperature dependence of resonance Raman scattering from 2 atom diameter HgTe nanowires embedded in the central pore of single walled carbon nanotubes, over the temperature range 4–295 K and excitation photon energies in the range 1.65 to 1.90 eV. The spectra are analysed to extract the temperature dependence of the phonon energies and linewidths and the central energy, linewidth and peak scattering strength of the optical resonances. The temperature dependence of the peak scattering strength is explained by a model in which the resonance broadening is dominated by coherence lifetime broadening, allowing us to determine the coherence lifetime of the underlying optical transition: 9 fs at 295 K and 18 fs at 50 K. The results are comparable with similar results on carbon nanotubes which suggests that the optical transitions responsible for the Raman resonances are excitonic.

Background: Development of theranostic concepts that include inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS (LA-ICP-MS) imaging can be hindered by the lack of a direct comparison to more standardly used methods for in vitro and in vivo evaluation; e.g. fluorescence or nuclear medicine. In this study a bimodal (or rather, hybrid) tracer that contains both a fluorescent dye and a chelate was used to evaluate the existence of a direct link between mass spectrometry (MS) and in vitro and in vivo molecular imaging findings using fluorescence and radioisotopes. At the same time, the hybrid label was used to determine whether the use of a single isotope label would allow for MS-based diagnostics. Methods: A hybrid label that contained both a DTPA chelate (that was coordinated with either Ho-165 or In-111) and a Cy5 fluorescent dye was coupled to the chemokine receptor 4 (CXCR4) targeting peptide Ac-TZ14011 (hybrid-Cy5-Ac-TZ4011). This receptor targeting tracer was used to 1) validate the efficacy of (Ho-165-based) mass-cytometry in determining the receptor affinity via comparison with fluorescence-based flow cytometry (Cy5), 2) evaluate the microscopic binding pattern of the tracer in tumor cells using both fluorescence confocal imaging (Cy5) and LA-ICP-MS-imaging (Ho-165), 3) compare in vivo biodistribution patterns obtained with ICP-MS (Ho-165) and radiodetection (In-111) after intravenous administration of hybrid-Cy5-Ac-TZ4011 in tumor-bearing mice. Finally, LA-ICP-MS-imaging (Ho-165) was linked to fluorescence-based analysis of excised tissue samples (Cy5). Results: Analysis with both mass-cytometry and flow cytometry revealed a similar receptor affinity, respectively 352 +/- 141 nM and 245 +/- 65 nM (p = 0.08), but with a much lower detection sensitivity for the first modality. In vitro LA-ICP-MS imaging (Ho-165) enabled clear discrimination between CXCR4 positive and negative cells, but fluorescence microscopy was required to determine the intracellular distribution. In vivo biodistribution patterns obtained with ICP-MS (Ho-165) and radiodetection (In-111) of the hybrid peptide were shown to be similar. Assessment of tracer distribution in excised tissues revealed the location of tracer uptake with both LA-ICP-MS-imaging and fluorescence imaging. Conclusion: Lanthanide-isotope chelation expands the scope of fluorescent/ radioactive hybrid tracers to include MS-based analytical tools such as mass-cytometry, ICP-MS and LA-ICP-MS imaging in molecular pathology. In contradiction to common expectations, MS detection using a single chelate imaging agent was shown to be feasible, enabling a direct link between nuclear medicine-based imaging and theranostic methods.

Subclinical atherosclerosis cannot be predicted and novel therapeutic targets are needed. The molecular anatomy of healthy and atherosclerotic tissue is pursued to identify ongoing molecular changes in atherosclerosis development. Mass Spectrometry Imaging (MSI) accounts with the unique advantage of analyzing proteins and metabolites (lipids) while preserving their original localization; thus two dimensional maps can be obtained. Main molecular alterations were investigated in a rabbit model in response to early development of atherosclerosis. Aortic arterial layers (intima and media) and calcified regions were investigated in detail by MALDI-MSI and proteins and lipids specifically defining those areas of interest were identified. These data further complement main findings previously published in J Proteomics (M. Martin-Lorenzo et al., J. Proteomics. (In press); M. Martin-Lorenzo et al., J. Proteomics 108 (2014) 465–468.) [1,2].

Mass spectrometry imaging (MSI) is a powerful tool for the molecular characterization of specific tissue regions. Histochemical staining provides anatomic information complementary to MSI data. The combination of both modalities has been proven to be beneficial. However, direct comparison of histology based and mass spectrometry-based molecular images can become problematic because of potential tissue damages or changes caused by different sample preparation. Curated atlases such as the Allen Brain Atlas (ABA) offer a collection of highly detailed and standardized anatomic information. Direct comparison of MSI brain data to the ABA allows for conclusions to be drawn on precise anatomic localization of the molecular signal. Here we applied secondary ion mass spectrometry imaging at high spatial resolution to study brains of knock-out mouse models with impaired peroxisomal β-oxidation. Murine models were lacking D-multifunctional protein (MFP2), which is involved in degradation of very long chain fatty acids. SIMS imaging revealed deposits of fatty acids within distinct brain regions. Manual comparison of the MSI data with the histologic stains did not allow for an unequivocal anatomic identification of the fatty acids rich regions. We further employed an automated pipeline for co-registration of the SIMS data to the ABA. The registration enabled precise anatomic annotation of the brain structures with the revealed lipid deposits. The precise anatomic localization allowed for a deeper insight into the pathology of Mfp2 deficient mouse models. Graphical Abstract ᅟ Electronic supplementary material The online version of this article (doi:10.1007/s13361-015-1146-6) contains supplementary material, which is available to authorized users.

IntroductionMass spectrometry imaging (MSI) uses biomolecular massspectrometry techniques to simultaneously record the distri-butions of molecules directly from tissue samples [1] andwithin their histological context [2]. MSI is now applied inincreasingly diverse biomedical and biological applications,from the identification of clinical biomarkers [3], to the label-free quantification of drugs and metabolites [4], to revealingthe molecular cartography of plant tissues [5]. The differentfocus areas have necessarily led to application-specific ap-proaches, but even within the basic MSI experiment there isstill muchscopeformethodologicaldifferencesthataffecttheresulting data [6]. A cursory overview of an MSI experimentincludes multiple aspects where differences may arise: tissueprocessing (e.g., embedding and storage conditions), tissuepreparation (e.g., sectioning and matrix application), dataacquisition (e.g., ionization method, spatial resolution, andmass analyzer), data processing (e.g., mass spectral process-ing, intensity normalization, and color scale).If we consider just the ionization method used for dataacquisition, MSI data sets have been recorded using laserdesorption ionization (LDI) [7], matrix-assisted desorption/ionization using ultraviolet lasers UV-MALDI [1], MALDIusinginfraredlasers(IR-MALDI)[8],desorptionelectrosprayionization(DESI)[9],nano-DESI[10],nanostructure-initiatormass spectrometry (NIMS) [11], secondary ion mass spec-trometry (SIMS) [12], and laser ablation–inductively coupledplasma mass spectrometry (LA-ICP-MS) [13]. For exampleUV-MALDI can be performed under high vacuum or at

Matrix-Assisted Laser Desorption Ionization, MALDI, has been increasingly used in a variety of biomedical applications, including tissue imaging of clinical tissue samples, and in drug discovery and development. These studies strongly depend on the performance of the analytical instrumentation and would drastically benefit from improved sensitivity, reproducibility, and mass/spatial resolution. In this work, we report on a novel combined MALDI/ESI interface, which was coupled to different Orbitrap mass spectrometers (Elite and Q Exactive Plus) and extensively characterized with peptide and protein standards, and in tissue imaging experiments. In our approach, MALDI is performed in the elevated pressure regime (5-8 Torr) at a spatial resolution of 15-30 mu m, while ESI-generated ions are injected orthogonally to the interface axis. We have found that introduction of the MALDI-generated ions into an electrodynamic dual funnel interface results in increased sensitivity characterized by a limit of detection of,similar to 400 zmol, while providing a mass measurement accuracy of 1 ppm and a mass resolving power of 120 OW in analysis of protein digests. In tissue imaging experiments, the MALDI/ESI interface has been employed in experiments with rat brain sections and was shown to be capable of visualizing and spatially characterizing very low abundance analytes separated only by 20 mDa. Comparison of imaging data has revealed excellent agreement between the MALDI and histological images.

MALDI mass spectrometry imaging is able to simultaneously determine the spatial distribution of hundreds of molecules directly from tissue sections, without labeling and without prior knowledge. Ultra-high mass resolution measurements based on Fourier-transform mass spectrometry have been utilized to resolve isobaric lipids, metabolites and tryptic peptides. Here we demonstrate the potential of 15T MALDI-FTICR MSI for molecular pathology in a mouse model of high-grade glioma. The high mass accuracy and resolving power of high field FTICR MSI enabled tumor specific proteoforms, and tumor-specific proteins with overlapping and isobaric isotopic distributions to be clearly resolved. The protein ions detected by MALDI MSI were assigned to proteins identified by region-specific microproteomics (0.8 mm2 regions isolated using laser capture microdissection) on the basis of exact mass and isotopic distribution. These label free quantitative experiments also confirmed the protein expression changes observed by MALDI MSI and revealed changes in key metabolic proteins, which were supported by in-situ metabolite MALDI MSI.

Glycosylation is an abundant co- and post-translational protein modification of importance to protein processing and activity. Although not template-defined, glycosylation does reflect the biological state of an organism and is a high-potential biomarker for disease and patient stratification. However, to interpret a complex but informative sample like the total plasma N-glycome, it is important to establish its baseline association with plasma protein levels and systemic processes. Thus far, large-scale studies (n >200) of the total plasma N-glycome have been performed with methods of chromatographic and electrophoretic separation, which, although being informative, are limited in resolving the structural complexity of plasma N-glycans. MS has the opportunity to contribute additional information on, among others, antennarity, sialylation, and the identity of high-mannose type species.Here, we have used matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance (FTICR)-MS to study the total plasma N-glycome of 2144 healthy middle-aged individuals from the Leiden Longevity Study, to allow association analysis with markers of metabolic health and inflammation. To achieve this, N-glycans were enzymatically released from their protein backbones, labeled at the reducing end with 2-aminobenzoic acid, and following purification analyzed by negative ion mode intermediate pressure MALDI-FTICR-MS. In doing so, we achieved the relative quantification of 61 glycan compositions, ranging from Hex4HexNAc2 to Hex7HexNAc6dHex1Neu5Ac4, as well as that of 39 glycosylation traits derived thereof. Next to confirming known associations of glycosylation with age and sex by MALDI-FTICR-MS, we report novel associations with C-reactive protein (CRP), interleukin 6 (IL-6), body mass index (BMI), leptin, adiponectin, HDL cholesterol, triglycerides (TG), insulin, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and smoking. Overall, the bisection, galactosylation, and sialylation of diantennary species, the sialylation of tetraantennary species, and the size of high-mannose species proved to be important plasma characteristics associated with inflammation and metabolic health.

Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival (m/z 180.9436 and 241.0118) and metastasis-free survival (m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine. Graphical Abstractᅟ Electronic supplementary material The online version of this article (doi:10.1007/s13361-016-1544-4) contains supplementary material, which is available to authorized users.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) can simultaneously measure hundreds of biomolecules directly from tissue. Using different sample preparation strategies, proteins and metabolites have been profiled to study the molecular changes in a 3×Tg mouse model of Alzheimer's disease. In comparison with wild-type (WT) control mice MALDI-MSI revealed Alzheimer's disease-specific protein profiles, highlighting dramatic reductions of a protein with m/. z 7560, which was assigned to neurogranin and validated by immunohistochemistry. The analysis also revealed substantial metabolite changes, especially in metabolites related to the purine metabolic pathway, with a shift towards an increase in hypoxanthine/xanthine/uric acid in the 3×Tg AD mice accompanied by a decrease in AMP and adenine. Interestingly these changes were also associated with a decrease in ascorbic acid, consistent with oxidative stress. Furthermore, the metabolite N-arachidonyl taurine was increased in the diseased mouse brain sections, being highly abundant in the hippocampus. Overall, we describe an interesting shift towards pro-inflammatory molecules (uric acid) in the purinergic pathway associated with a decrease in anti-oxidant level (ascorbic acid). Together, these observations fit well with the increased oxidative stress and neuroinflammation commonly observed in AD. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Atmospheric pressure MALDI on a Q-Exactive instrument was optimized for in-source decay and pseudo-MS3. The dependence of AP-MALDI ISD on the MALDI liquid matrix was investigated for peptides and proteins. The liquid matrices enabled long-life ISD signal, and exhibited high fragment ion yield and signal stability. Extensive a-, b-, c-, y-, and z-type fragment series were observed depending on the matrix used but were most extensive with 2,5-DHB. Complete sequence coverage of small peptide and intact protein-terminus sequence tags were obtained and confirmed using HCD as a pseudo-MS3 method.

Background Previous studies on high grade sarcomas using mass spectrometry imaging showed proteasome activator complex subunit 1 (PSME1) to be associated with poor survival in soft tissue sarcoma patients. PSME1 is involved in immunoproteasome assembly for generating tumor antigens presented by MHC class I molecules. In this study, we aimed to validate PSME1 as a prognostic biomarker in an independent and larger series of soft tissue sarcomas by immunohistochemistry. Methods Tissue microarrays containing leiomyosarcomas (n = 34), myxofibrosarcomas (n = 14), undifferentiated pleomorphic sarcomas (n = 15), undifferentiated spindle cell sarcomas (n = 4), pleomorphic liposarcomas (n = 4), pleomorphic rhabdomyosarcomas (n = 2), and uterine leiomyomas (n = 7) were analyzed for protein expression of PSME1 using immunohistochemistry. Survival times were compared between high and low expression groups using Kaplan–Meier analysis. Cox regression models as multivariate analysis were performed to evaluate whether the associations were independent of other important clinical covariates. Results PSME1 expression was variable among soft tissue sarcomas. In leiomyosarcomas, high expression was associated with overall poor survival (p = 0.034), decreased metastasis-free survival (p = 0.002) and lower event-free survival (p = 0.007). Using multivariate analysis, the association between PSME1 expression and metastasis-free survival was still significant (p = 0.025) and independent of the histological grade. Conclusions High expression of PSME1 is associated with poor metastasis-free survival in soft tissue leiomyosarcoma patients, and might be used as an independent prognostic biomarker. Electronic supplementary material The online version of this article (doi:10.1186/s13569-016-0057-z) contains supplementary material, which is available to authorized users.

Atmospheric pressure MALDI on a Q-Exactive instrument was optimized for in-source decay and pseudo-MS3. The dependence of AP-MALDI ISD on the MALDI liquid matrix was investigated for peptides and proteins. The liquid matrices enabled long-life ISD signal, and exhibited high fragment ion yield and signal stability. Extensive a-, b-, c-, y-, and z-type fragment series were observed depending on the matrix used but were most extensive with 2,5-DHB. Complete sequence coverage of small peptide and intact protein-terminus sequence tags were obtained and confirmed using HCD as a pseudo-MS3 method. Graphical Abstractᅟ Electronic supplementary material The online version of this article (doi:10.1007/s13361-016-1511-0) contains supplementary material, which is available to authorized users.

Tissue preparation is the key to a successful matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) experiment. Rapid post-mortem changes contribute a significant challenge to the use of MSI approaches for the analysis of peptides and metabolites. In this technical note we aimed to compare the tissue fixation method ex-vivo heat-stabilization with in-situ funnel-freezing in a middle cerebral artery occlusion (MCAo) mouse model of stroke, which causes profound alterations in metabolite concentrations. The influence of the duration of the thaw-mounting of the tissue sections on metabolite stability was also determined. We demonstrate improved stability and biomolecule visualization when funnel-freezing was used to sacrifice the mouse compared with heat-stabilization. Results were further improved when funnel-freezing was combined with fast thaw-mounting of the brain sections.

This paper briefly describes how nanowires with diameters corresponding to 1 to 5 atoms can be produced by melting a range of inorganic solids in the presence of carbon nanotubes. These nanowires are extreme in the sense that they are the limit of miniaturization of nanowires and their behavior is not always a simple extrapolation of the behavior of larger nanowires as their diameter decreases. The paper then describes the methods required to obtain Raman spectra from extreme nanowires and the fact that due to the van Hove singularities that 1D systems exhibit in their optical density of states, that determining the correct choice of photon excitation energy is critical. It describes the techniques required to determine the photon energy dependence of the resonances observed in Raman spectroscopy of 1D systems and in particular how to obtain measurements of Raman cross-sections with better than 8% noise and measure the variation in the resonance as a function of sample temperature. The paper describes the importance of ensuring that the Raman scattering is linearly proportional to the intensity of the laser excitation intensity. It also describes how to use the polarization dependence of the Raman scattering to separate Raman scattering of the encapsulated 1D systems from those of other extraneous components in any sample.

The identification of tumor subpopulations that adversely affect patient outcomes is essential for a more targeted investigation into how tumors develop detrimental phenotypes, as well as for personalized therapy. Mass spectrometry imaging has demonstrated the ability to uncover molecular intratumor heterogeneity. The challenge has been to conduct an objective analysis of the resulting data to identify those tumor subpopulations that affect patient outcome. Here we introduce spatially mapped t-distributed stochastic neighbor embedding (t-SNE), a nonlinear visualization of the data that is able to better resolve the biomolecular intratumor heterogeneity. In an unbiased manner, t-SNE can uncover tumor subpopulations that are statistically linked to patient survival in gastric cancer and metastasis status in primary tumors of breast cancer.

Since the introduction of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS), numerous instrumental developments have been presented. The introduction of microscope MALDI IMS was a major breakthrough, making micron-range resolution MALDI imaging of kiloDalton mass species possible. We discuss new developments that makes large (cm range) field of view, high resolution (μm range) microscope mode imaging mass spectrometry (IMS) possible in a single experiment, using three different data acquisition approaches simultaneously. We demonstrate how a combination of these acquisition approaches is used to correlate mass spectral and high resolution imaging data.

High-resolution imaging mass spectrometry of large biological samples is the goal of several research groups. In mosaic imaging, the most common method, the large sample is divided into a mosaic of small areas that are then analyzed with high resolution. Here we present an automated alignment routine that uses principal component analysis to reduce the uncorrelated noise in the imaging datasets, which previously obstructed automated image alignment. An additional signal quality metric ensures that only those regions with sufficient signal quality are considered. We demonstrate that this algorithm provides superior alignment performance than manual stitching and can be used to automatically align large imaging mass spectrometry datasets comprising many individual mosaic tiles.