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Immuno-specific enrichment of extracellular vesicles (EVs) originating from specific cells/tissues is a promising source of information towards improving insights into cellular pathways underpinning various pathologies and developing novel non-invasive diagnostic methods. Enrichment is an important aspect in mass spectrometry-based analyses of EVs. Herein, we report a protocol for immuno-magnetic enrichment of subtype specific EVs and their subsequent processing for mass spectrometry. Specifically, we conjugated placental alkaline phosphatase (PLAP) antibodies to magnetic iron oxide nanowires (NWs) derived from bacterial biofilms and demonstrated the utility of this approach by enriching placental specific EVs (containing PLAP) from cell culture media. We demonstrate efficient PLAP+ve EV enrichment for both NW-PLAP and Dynabeads™-PLAP, with PLAP protein recovery (83.7±8.9% and 83.2±5.9%, respectively), high particle-to-protein ratio (7.5±0.7×109 and 7.1 ± 1.2×109, respectively), and low non-specific binding of non-target EVs (7±3.2% and 5.4±2.2%, respectively). Furthermore, our optimized EV enrichment and processing approach identified 2518 and 2545 protein groups with mass spectrometry for NW-PLAP and Dynabead™-PLAP, respectively, with excellent reproducibility (Pearson correlation 0.986 and 0.988). The proposed immuno-specific EVs enrichment and liquid chromatography-tandem mass spectrometry method using naturally occurring iron oxide magnetic NWs or gold-standard Dynabeads™ enables high-quality EV proteomic studies.

Refereed/Peer-reviewed Eighty percent of ovarian cancer patients initially respond to chemotherapy, but the majority eventually experience a relapse and die from the disease with acquired chemoresistance. In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography–mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not; the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan–Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.

The applicability of mass spectrometry imaging (MSI) has exponentially increased with the improvement of sample preparation, instrumentation (spatial resolution) and data analysis. The number of MSI publications listed in PubMed continues to grow with 378 published articles in 2020-2021. Initially, MSI was just sensitive enough to identify molecular features correlating with distinct tissue regions, similar to the resolution achieved by visual inspection after standard immunohistochemical staining. Although the spatial resolution was limited compared with other imaging modalities, the molecular intensity mapping added a new exciting capability. Over the past decade, significant improvements in every step of the workflow and most importantly in instrumentation were made, which now enables the molecular analysis at a cellular and even subcellular level. Here, we summarize the latest developments in MSI, with a focus on the latest approaches for tissue-based imaging described in 2020. Refereed/Peer-reviewed

N-Glycan alterations contribute to the pathophysiology and progression of various diseases. However, the involvement of N-glycans in knee osteoarthritis (KOA) progression at the tissue level, especially within articular cartilage, is still poorly understood. Thus, the aim of this study was to spatially map and identify KOA-specific N-glycans from formalin-fixed paraffin-embedded (FFPE) osteochondral tissue of the tibial plateau relative to cadaveric control (CTL) tissues. Human FFPE osteochondral tissues from end-stage KOA patients (n=3) and CTL individuals (n=3), aged >55 years old, were analyzed by matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI) and liquid chromatography–tandem mass spectrometry (LC-MS/MS). Overall, it was revealed that 22 N-glycans were found in the cartilage region of KOA and CTL tissue. Of those, 15 N-glycans were more prominent in KOA cartilage than CTL cartilage. We then compared sub-regions of KOA and CTL tissues based on the Osteoarthritis Research Society International (OARSI) histopathological grade (1 to 6), where 1 is an intact cartilage surface and 6 is cartilage surface deformation. Interestingly, three specific complex-type N-glycans, (Hex)4(HexNAc)3, (Hex)4(HexNAc)4, and (Hex)5(HexNAc)4, were found to be localized to the superficial fibrillated zone of degraded cartilage (KOA OARSI 2.5-4), compared to adjacent cartilage with less degradation (KOA OARSI 1-2) or relatively healthy cartilage (CTL OARSI 1-2). Our results demonstrate that N-glycans specific to degraded cartilage in KOA patients have been identified at the tissue level for the first time. The presence of these N-glycans could further be evaluated as potential diagnostic and prognostic biomarkers.

The strength of MALDI-MSI is to analyze and visualize spatial intensities of molecular features from an intact tissue. The distribution of the intensities can then be visualized within a single tissue section or compared in between sections, acquired consecutively. This method can be reliably used to reveal physiological structures and has the potential to identify molecular details, which correlate with biological outcomes. MALDI-MSI implementation in clinical laboratories requires the ability to ensure method quality and validation to meet diagnostic expectations. To be able to get consistent qualitative and quantitative results, standardized sample preparation and data acquisition are of highest priority. We have previously shown that the deposition of internal standards onto the tissue section during sample preparation can be used to improve the mass accuracy of monitored m/z features across the sample. Here, we present the use of external and internal controls for the quality check of sample preparation and data acquisition, which is particularly relevant when either many spectra are acquired during a single MALDI-MSI experiment or data from independent experiments are processed together. To monitor detector performance and sample preparation, we use egg white as an external control for peptide and N-glycan MALDI-MSI throughout the experiment. We have also identified endogenous peptides from cytoskeletal proteins, which can be reliably monitored in gynecological tissue samples. Lastly, we summarize our standard quality control workflow designed to produce reliable and comparable MALDI-MSI data from single sections and tissue microarrays (TMAs). Refereed/Peer-reviewed

Quantitation using mass spectrometry (MS) is a routine approach for multiple analytes, including small molecules and peptides. Electrospray-based MS platforms are typically employed, as they provide highly reproducible outputs for batch processing of multiple samples. Quantitation using matrix-assisted laser desorption/ionization (MALDI) time-of-flight (ToF) mass spectrometry, while less commonly adopted, offers the ability to monitor analytes at significantly higher throughput and lower cost compared with ESI MS. Achieving accurate quantitation using this approach requires the development of appropriate sample preparation, spiking of appropriate internal standards, and acquisition to minimize spot-to-spot variability. Here we describe the preparation of samples for accurate quantitation using MALDI-ToF MS. The methodology presented shows the ability to quantitate perfluorooctanesulfonic acid (PFOS) from contaminated water. Refereed/Peer-reviewed

Protein glycosylation is a common post-translational modification that modulates biological processes such as the immune response and protein trafficking. Altered glycosylation profiles are associated with cancer and inflammatory diseases, as well as impacting the efficacy of therapeutic monoclonal antibodies. Consisting of oligosaccharides attached to asparagine residues, enzymatically released N-linked glycans are analytically challenging due to the diversity of isomeric structures that exist. A commonly used technique for quantitative N-glycan analysis is liquid chromatography-mass spectrometry (LC-MS), which performs glycan separation and characterization. Although many reversed and normal stationary phases have been utilized for the separation of N-glycans, porous graphitic carbon (PGC) chromatography has become desirable because of its higher resolving capability, but is difficult to implement in a robust and reproducible manner. Herein, we demonstrate the analytical properties of a 15 cm fused silica capillary (75 µm i.d., 360 µm o.d.) packed in-house with Hypercarb PGC (3 µm) coupled to an Agilent 6550 Q-TOF mass spectrometer for N-glycan analysis in positive ion mode. In repeatability and intermediate precision measurements conducted on released N-glycans from a glycoprotein standard mixture, the majority of N-glycans reported low coefficients of variation with respect to retention times (≤4.2%) and peak areas (≤14.4%). N-glycans released from complex samples were also examined by PGC LC-MS. A total of 120 N-glycan structural and compositional isomers were obtained from formalin-fixed paraffin-embedded ovarian cancer tissue sections. Finally, a comparison between early- and late-stage formalin-fixed paraffin-embedded ovarian cancer tissues revealed qualitative changes in the α2,3- and α2,6-sialic acid linkage of a fucosylated bi-antennary complex N-glycan. Although the α2,3-linkage was predominant in late-stage ovarian cancer, the alternate α2,6-linkage was more prevalent in early-stage ovarian cancer. This study establishes the utility of in-house packed PGC columns for the robust and reproducible LC-MS analysis of N-glycans.

Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) has been successfully used to elucidate the relative abundance and spatial mapping of analytes in situ. Currently, sample preparation workflows for soft formalin-fixed paraffin-embedded (FFPE) tissues, such as brain, liver, kidney, and heart, have been successfully developed. However, hard tissues, such as cartilage-bone, tooth, and whole mouse body, have resulted in the loss of morphology or tissue during the heat-induced epitope retrieval (HIER) step on commercially available conductive indium tin oxide (ITO) slides. Therefore, we have successfully developed a novel and cost-effective sample preparation workflow in which commercial conductive ITO slides are pre-coated with gelatin and chromium potassium sulfate dodecahydrate to improve the adherence of FFPE human osteoarthritic cartilage-bone tissue sections. Gelatin-coated ITO slides also resulted in overall higher N-glycan signal intensity for not only FFPE osteoarthritic cartilage-bone tissue but also for FFPE hard-boiled egg white used as a quality control to assess the quality of sample preparation and MALDI-MSI acquisition. In summary, we present a novel straightforward workflow to improve slide adherence and morphological preservation of FFPE cartilage-bone tissue sections during HIER while improving the signal intensity of N-glycans spatially mapped from the same tissue sections by MALDI-MSI. Refereed/Peer-reviewed

Leukocyte homing driven by the chemokine CCL21 is pivotal for adaptive immunity because it controls dendritic cell (DC) and T cell migration through CCR7. ACKR4 scavenges CCL21 and has been shown to play an essential role in DC trafficking at the steady state and during immune responses to tumors and cutaneous inflammation. However, the mechanism by which ACKR4 regulates peripheral DC migration is unknown, and the extent to which it regulates CCL21 in steady-state skin and lymph nodes (LNs) is contested. Specifically, our previous findings that CCL21 levels are increased in LNs of ACKR4-deficient mice [I. Comerford et al., Blood 116, 4130–4140 (2010)] were refuted [M. H. Ulvmar et al., Nat. Immunol. 15, 623–630 (2014)], and no differences in CCL21 levels in steady-state skin of ACKR4-deficient mice were reported despite compromised CCR7-dependent DC egress in these animals [S. A. Bryce et al., J. Immunol. 196, 3341–3353 (2016)]. Here, we resolve these issues and reveal that two forms of CCL21, full-length immobilized and cleaved soluble CCL21, exist in steady-state barrier tissues, and both are regulated by ACKR4. Without ACKR4, extracellular CCL21 gradients in barrier sites are saturated and nonfunctional, DCs cannot home directly to lymphatic vessels, and excess soluble CCL21 from peripheral tissues pollutes downstream LNs. The results identify the mechanism by which ACKR4 controls DC migration in barrier tissues and reveal a complex mode of CCL21 regulation in vivo, which enhances understanding of functional chemokine gradient formation. Refereed/Peer-reviewed

Provided is the annotated raw data for N-glycan mass spectrometry imaging (MSI) annotations in thin cross-sections of formalin-fixed and paraffin-embedded murine kidney. Relevant meta-data have been provided in this brief and the raw MSI data can be accessed using ProteomeXchange with the PRoteomics IDEntifications (PRIDE) identifier PXD009808. This brief is the first in a set of submissions from our group which will make raw data publicly accessible for existing and future MSI studies. Refereed/Peer-reviewed

Simple Summary Classic histopathological examination of tissues remains the mainstay for cancer diagnosis and staging. However, in some cases histopathologic analysis yields ambiguous results, leading to inconclusive disease classification. We set out to explore the diagnostic potential of mass spectrometry-based imaging for tumour classification based on proteomic fingerprints. Combining mass spectrometry with supervised machine learning, we were able to distinguish colorectal tumor from normal tissue with an overall accuracy of 98%. In addition, this approach was able to predict the presence of lymph node metastasis in primary tumour of endometrial cancer with an overall accuracy of 80%. These results highlight the potential of this technology to determine the optimal treatment for cancer patients to reduce morbidity and improve patients’ outcomes. Abstract Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.

© 2019 The Royal Society of Chemistry. Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS), in combination with Biotyper software, is a rapid, high-throughput, and accurate method for the identification of microbes. Microbial outbreaks in a brewery present a major risk for companies as it can lead to cost-intensive recalls and damage to the brand reputation. MALDI-TOF MS has been implemented into a brewery setting for quality control practices and the identification of beer spoilage microorganisms. However, the applicability of this approach is hindered by compatibility issues associated with mixed cultures, requiring the use of time-consuming selective cultivation techniques prior to identification. We propose a novel, low-cost approach based on the combination of inertial microfluidics and secondary flows in a spiral microchannel for high-throughput and efficient separation of yeasts (Saccharomyces pastorianus and Saccharomyces cerevisiae) from beer spoilage microorganisms (Lactobacillus brevis and Pediococcus damnosus). Flow rates were optimised using S. pastorianus and L. brevis, leading to separation of more than 90% of the L. brevis cells from yeast. The microorganisms were then identified to the species level using the MALDI-TOF MS platform using standard sample preparation protocols. This study shows the high-throughput and rapid separation of spoilage microorganisms (0.3-3 μm) from background yeast (5 μm) from beer, subsequent identification using MALDI Biotyper, and the potential applicability of the approach for biological control in the brewing industry.

Osteoarthritis (OA) is the most common degenerative joint disease, predicted to increase in incidence year by year due to an ageing population. Due to the biological complexity of the disease, OA remains highly heterogeneous. Although much work has been undertaken in the past few years, underlying molecular mechanisms leading to joint tissue structural deterioration are not fully understood, with only few validated markers for disease diagnosis and progression being available. Discovery and quantitation of various OA-specific biomarkers is still largely focused on the bodily fluids which does not appear to be reliable and sensitive enough. However, with the advancement of spatial proteomic techniques, several novel peptides and proteins, as well as N-glycans, can be identified and localised in a reliable and sensitive manner. To summarise the important findings from OA biomarker studies, papers published between 2000 and 2020 were searched via Google Scholar and PubMed. Medical subject heading (MeSH) terms ‘osteoarthritis’, ‘biomarker’, ‘synovial fluid’, ‘serum’, ‘urine’, ’matrix-assisted laser desorption/ionisation’, ‘mass spectrometry imaging’, ‘proteomic’, ‘glycomic’, ‘cartilage’, ‘synovium’ AND ‘subchondral bone’ were selectively used. The literature search was restricted to full-text original research articles and written only in English. Two main areas were reviewed for OA biomarker studies: (1) an overview of disease-specific markers detected from different types of OA bio-samples, and (2) an up-to-date summary of the tissue-specific OA studies that have utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging(MALDI-MSI). Overall, these OA biomarkers could provide clinicians with information for better the diagnosis, and prognosis of individual patients, and ultimately help facilitate the development of disease-modifying treatments. Refereed/Peer-reviewed