Mass Spectrometry-based Analysis Research Articles

AML-VAC-XS15-01: protocol of a first-in-human clinical trial to evaluate the safety, tolerability and preliminary efficacy of a multi-peptide vaccine based on leukemia stem cell antigens in acute myeloid leukemia patients.

Acute myeloid leukemia (AML) has a dismal prognosis, mostly due to minimal residual disease-driven relapse, making an elimination of persisting therapy-resistant leukemia progenitor/stem cells (LPCs) the main goal for novel therapies. Peptide-based immunotherapy offers a low-side-effect approach aiming to induce T cell responses directed against human leukocyte antigen (HLA) presented tumor antigens on malignant cells by therapeutic vaccination. Mass spectrometry-based analysis of the naturally presented immunopeptidome of primary enriched LPC and AML samples enabled the selection of antigens exclusively expressed on LPC/AML cells, which showed de novo induction and spontaneous memory T cell responses in AML patients, and whose presentation and memory T cell recognition was associated with improved disease outcome. Based on these data the therapeutic vaccine AML-VAC-XS15 was designed, comprising two mutated HLA class I-restricted peptides from the common AML-specific mutation in NPM1 and seven HLA class II-restricted peptides (six non-mutated high-frequent AML/LPC-associated antigens and one mutated peptide from the AML-specific mutation R140Q in IDH2), adjuvanted with the toll like receptor 1/2 ligand XS15 and emulsified in Montanide ISA 51 VG. A phase I open label clinical trial investigating AML-VAC-XS15 was designed, recruiting AML patients in complete cytological remission (CR) or CR with incomplete blood count recovery. Patients are vaccinated twice with a six-week interval, with an optional booster vaccination four months after 2nd vaccination, and are then followed up for two years. The trial's primary objectives are the assessment of the vaccine's immunogenicity, safety and toxicity, secondary objectives include characterization of vaccine-induced T cell responses and assessment of preliminary clinical efficacy. The AML-VAC-XS15-01 study was approved by the Ethics Committee of the Bavarian State medical association and the Paul-Ehrlich Institut (P01392). Clinical trial results will be published in peer-reviewed journals.

Detection of host cell microprotein impurities in antibody drug products

Chinese hamster ovary (CHO) cells are used to produce almost 90% of therapeutic monoclonal antibodies (mAbs) and antibody fusion proteins (Fc-fusion). The annotation of non-canonical translation events in these cellular factories remains incomplete, limiting our ability to study CHO cell biology and detect host cell protein (HCP) impurities in the final antibody drug product. We utilised ribosome footprint profiling (Ribo-seq) to identify novel open reading frames (ORFs) including N-terminal extensions and thousands of short ORFs (sORFs) predicted to encode microproteins. Mass spectrometry-based HCP analysis of eight commercial antibody drug products (7 mAbs and 1 Fc-fusion protein) using the extended protein sequence database revealed the presence of microprotein impurities. We present evidence that microprotein abundance varies with growth phase and can be affected by the cell culture environment. In addition, our work provides a vital resource to facilitate future studies of non-canonical translation and the regulation of protein synthesis in CHO cell lines.

Chronic Exposure to Petroleum-Derived Hydrocarbons Alters Human Skin Microbiome and Metabolome Profiles: A Pilot Study.

Petroleum-derived substances, like industrial oils and grease, are ubiquitous in our daily lives. Comprised of petroleum hydrocarbons (PH), these substances can come into contact with our skin, potentially causing molecular disruptions and contributing to the development of chronic disease. In this pilot study, we employed mass spectrometry-based untargeted metabolomics and 16S rRNA gene sequencing analyses to explore these effects. Superficial skin samples were collected from subjects with and without chronic dermal exposure to PH at two anatomical sites: the fingers (referred to as the hand) and arms (serving as an intersubject variability control). Exposed hands exhibited higher bacterial diversity (Shannon and Simpson indices) and an enrichment of oil-degrading bacteria (ODB), including Dietzia, Paracoccus, and Kocuria. Functional prediction suggested enriched pathways associated with PH degradation in exposed hands vs non-exposed hands, while no differences were observed when comparing the arms. Furthermore, carboxylic acids, glycerophospholipids, organooxygen compounds, phenol ethers, among others, were found to be more abundant in exposed hands. We observed positive correlations among multiple ODB and xenobiotics, suggesting a chemical remodeling of the skin favorable for ODB thriving. Overall, our study offers insights into the complex dysregulation of bacterial communities and the chemical milieu induced by chronic dermal exposure to PH.

Decoding the impact of neighboring amino acids on ESI-MS intensity output through deep learning

Peptide-level quantification using mass spectrometry (MS) is no trivial task as the physicochemical properties affect both response and detectability. The specific amino acid (AA) sequence affects these properties, however the connection between sequence and intensity output remains poorly understood. In this work, we explore combinations of amino acid pairs (i.e., dimer motifs) to determine a potential relationship between the local amino acid environment and MS1 intensity. For this purpose, a deep learning (DL) model, consisting of an encoder-decoder with an attention mechanism, was built. The attention mechanism allowed to identify the most relevant motifs. Specific patterns were consistently observed where a bulky/aromatic and hydrophobic AA followed by a cationic AA as well as consecutive bulky/aromatic and hydrophobic AAs were found important for the prediction of the MS1 intensity. Correlating attention weights to mean MS1 intensities revealed that some important motifs, particularly containing Trp, His, and Cys, were linked with low responding peptides whereas motifs containing Lys and most bulky hydrophobic AAs were often associated with high responding peptides. Moreover, Asn-Gly was associated with low response. The model predicts MS1 response with a mean average percentage error of ∼11 % and a Pearson correlation coefficient of ∼0.64. While dimer representation of peptide sequences did not improve predictive capacity compared to single AA representation in earlier work, this work adds valuable insight for a better understanding of peptide response in MS analysis. SignificanceMass spectrometry is not inherently quantitative, and the response of a compound relies not only on its concentration but also on the molecular composition. For mass spectrometry-based analysis of peptides, such as in bottom-up proteomics, this directly implies that the response cannot be used directly to quantify individual peptides. Moreover, the dependency of the response on the amino acid sequence of individual peptides remains poorly understood. Using a deep learning model based on a recurrent neural network with an attention mechanism, we here investigate how the presence of dimer motifs within a peptide affects the MS1 response through the analysis of intended equimolar peptide pools comprising almost 200,000 unique peptides in total. Not only do we identify certain dimer classes and specific dimers that substantially affect the MS1 response, but the model is also able to predict peptide intensity with low error rates within the independent test subset. The findings not only improve our understanding of the link between sequence and response for peptides but also highlight the potential of utilizing deep learning for developing methods allowing for absolute, label-free peptide quantification.

Cocoa bean metabolomics reveals polyphenols as potential markers relating to fine dark chocolate color shades.

This study aimed to evaluate the color and the discriminating compounds for two types of cocoa beans (black and brown beans) related to 70% dark chocolates of black and brown colors from a previous work of our group. Color analysis and untargeted high-resolution mass spectrometry-based metabolomic analysis were performed on eight beans of each type. Mass spectral data processing, univariate and multivariate statistical methods were conducted for classification of beans and selection of discriminant features. The results showed that the color difference already observed for black and brown chocolates preexists in the beans. Black and brown beans had 45 and 50 discriminant features, respectively, of which 16 and 41 were phenolic compounds. Most of them were also previously identified as discriminating compounds for black and brown chocolates. Black beans predominantly contained glycosylated flavanols, ranging from monomers to trimers, with dimers and trimers being A-type procyanidins, along with a phenolic acid (protocatechuic acid), and an O-glycosylated flavonol (quercetin-3-O-glucoside). In contrast, brown beans mostly contained non-glycosylated B-type procyanidins ranging from dimers to decamers, but also dimers and trimers of A-type procyanidins, and a glycosylated and sulfated flavanol ((epi) catechin hexoside-sulfate). These markers may be useful for quality control purposes and may contribute to the selection of beans that yield black or brown dark chocolates.

Mass spectrometry-based multi-omics analysis reveals distinct molecular features in early and advanced stages of hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a serious primary solid tumor that is prevalent worldwide. Due to its high mortality rate, it is crucial to explore both early diagnosis and advanced treatment for HCC. In recent years, multi-omics approaches have emerged as promising tools to identify biomarkers and investigate molecular mechanisms of biological processes and diseases. In this study, we performed proteomics, phosphoproteomics, metabolomics, and lipidomics to reveal the molecular features of early- and advanced-stage HCC. The data obtained from these omics were analyzed separately and then integrated to provide a comprehensive understanding of the disease. The multi-omics results unveiled intricate biological pathways and interaction networks underlying the initiation and progression of HCC. Moreover, we proposed specific potential biomarker panels for both early- and advanced-stage HCC by overlapping our data with CPTAC database for HCC diagnosis, and deduced novel insights and mechanisms related to HCC origination and development, such as glucose depletion during tumor progression, ROCK1 deactivation and GSK3A activation.

Linking metabolism and histone acetylation dynamics by integrated metabolic flux analysis of Acetyl-CoA and histone acetylation sites

ObjectivesHistone acetylation is an important epigenetic modification that regulates various biological processes and cell homeostasis. Acetyl-CoA, a hub molecule of metabolism, is the substrate for histone acetylation, thus linking metabolism with epigenetic regulation. However, still relatively little is known about the dynamics of histone acetylation and its dependence on metabolic processes, due to the lack of integrated methods that can capture site-specific histone acetylation and deacetylation reactions together with the dynamics of acetyl-CoA synthesis. MethodsIn this study, we present a novel proteo-metabo-flux approach that combines mass spectrometry-based metabolic flux analysis of acetyl-CoA and histone acetylation with computational modelling. We developed a mathematical model to describe metabolic label incorporation into acetyl-CoA and histone acetylation based on experimentally measured relative abundances. ResultsWe demonstrate that our approach is able to determine acetyl-CoA synthesis dynamics and site-specific histone acetylation and deacetylation reaction rate constants, and that consideration of the metabolically labelled acetyl-CoA fraction is essential for accurate determination of histone acetylation dynamics. Furthermore, we show that without correction, changes in metabolic fluxes would be misinterpreted as changes in histone acetylation dynamics, whereas our proteo-metabo-flux approach allows to distinguish between the two processes. ConclusionsOur proteo-metabo-flux approach expands the repertoire of metabolic flux analysis and cross-omics and represents a valuable approach to study the regulatory interplay between metabolism and epigenetic regulation by histone acetylation.

Circadian migrations of cave-dwelling crustaceans guided by their home chemical seascape

Organisms release and detect molecules for defense, reproduction, feeding strategies and finding suitable habitats. For some migratory species, homing behavior could be related to the recognition of their home chemical fingerprint made of an assemblage of molecules from their habitat. In the marine realm, the functioning of ecosystems such as underwater caves largely depends on trophic interactions between the caves and the outside environment. A key feature of these interactions relies on the circadian migration of small crustaceans (Mysida) from the cave habitat to the open sea. Recently, it has been hypothesized that these migrations could involve chemical mediation. Behavioral experiments using a two-choice system have shown that cave mysids significantly detect cave seawater rather than a control water from the open sea. Here, we used the same experimental system to investigate habitat recognition by two populations of the cave mysid Hemimysis margalefi. Both populations were submitted to a choice between three distinct cave seawaters vs. a control seawater. Additionally, experiments tested the water preference of a non-cave mysid species (Leptomysis sp.) between control and cave seawaters. To evaluate whether the choice of mysids was influenced by chemical cues from conspecifics, a complementary experiment on H. margalefi was conducted. Results demonstrated that each studied mysids population significantly recognizes the water of its own home habitat, and that this behavior is not influenced by the occurrence of H. margalefi’s exudates. Mass spectrometry-based metabolomic analyses revealed that each cave seawater had a specific chemical fingerprint with only a few reproducibly detected signals belonging to different chemical classes: peptides, alkaloids, fatty acids, steroids but also inorganic molecules. Organic pollutants have also been reproducibly detected. Among the detected compounds, one oxylipin derivative and one peptide could be considered as chemical markers of the cave ecosystem. Therefore, we postulate that the chemical seascape of each cave participates to mysid circadian migrations which are analogous to a daily-based homing behavior.

P016 METAPROTEOMICS ANALYSIS IN HEALTHY INDIVIDUALS REVEALS A HIGH CARDIOVASCULAR RISK PROFILE ACROSS BLOOD PRESSURE, DIET, HUMAN AND MICROBIAL PROTEINS

Background/Objective: The gut microbiota is a crucial link between diet and cardiovascular health by producing beneficial metabolites, such as short-chain fatty acids (SCFAs), through fibre fermentation. However, most studies have focused on microbial DNA to infer microbiota function. Here, we employed metaproteomics, a novel method to capture gut human and microbiota protein expression profiles concurrently. We aimed to investigate the crosstalk between gut microbiota, diet, host gut health, and blood pressure (BP). Methods: Mass spectrometry-based metaproteomic analysis was performed on 61 faecal samples with paired ambulatory BP monitoring, food intake (food frequency questionnaire), and demographic data. Results: We identified 21,594 microbial and 1,072 human proteins. Traditional risk factors (age, BMI, sex, BP) explained only ∼10% of the proteome variance. However, unsupervised clustering analysis of both human and microbial proteome revealed two distinct clusters (low-risk and high-risk) with significantly different 24-hour systolic BP (mean±SD, low-risk 116±13mmHg vs high-risk: 126±15mmHg, P=0.016), women prevalence (72.4% vs 40.6%, P=0.025), and diet quality (assessed as Athlete Diet Index, 61.6±6.7 vs 57.8±7.6, P=0.044). In the human proteome, the low-risk group had lower expression of the VEGFA-VEGFR2 signalling pathway and tight junction proteins and higher SCFA production (particularly propionate), suggesting an anti-inflammatory gut environment. In the microbial proteome, the low-risk group had higher activity of inorganic ion transport and metabolism-related proteins, with increased expression of acetate kinase that produces both the SCFAs acetate and propionate, particularly in primary fibre-fermenting bacteria, including Phocaeicola dorei and Blautia wexlerae. Finally, via co-expression networks, we identified profilin-1 (PFN1), which contributes to hypertension and atherosclerosis, as a crucial human protein associated with several bacteria present in the high-risk group. Conclusions: Employing an unsupervised clustering based on human and microbial proteomics, we identified two groups of participants with varying traditional and emerging cardiovascular risk factors. This was explained by complex interactions among diet, gut microbiota, and BP. This underscores the need for sophisticated models to understand multifactorial risk factors for cardiovascular disease.

Distinct protein patterns related to postnatal development in small for gestational age preterm infants.

Preterm infants, especially those born small for gestational age (SGA), are at risk of short-term and long-term health complications. Characterization of changes in circulating proteins postnatally in preterm infants may provide valuable fundamental insights into this population. Here, we investigated postnatal developmental patterns in preterm infants and explored protein signatures that deviate between SGA infants and appropriate for gestational age (AGA) infants using a mass spectrometry (MS)-based proteomics workflow. Longitudinal serum samples obtained at postnatal days 0, 3, 7, 14, and 28 from 67 preterm infants were analyzed using unbiased MS-based proteomics. 314 out of 833 quantified serum proteins change postnatally, including previously described age-related changes in immunoglobulins, hemoglobin subunits, and new developmental patterns, e.g. apolipoproteins (APOA4) and terminal complement cascade (C9) proteins. Limited differences between SGA and AGA infants were found at birth while longitudinal monitoring revealed 69 deviating proteins, including insulin-sensitizing hormone adiponectin, platelet proteins, and 24 proteins with an annotated function in the immune response. This study shows the potential of MS-based serum profiling in defining circulating protein trajectories in the preterm infant population and its ability to identify longitudinal alterations in protein levels associated with SGA. Postnatal changes of circulating proteins in preterm infants have not fully been elucidated but may contribute to development of health complications. Mass spectrometry-based analysis is an attractive approach to study circulating proteins in preterm infants with limited material. Longitudinal plasma profiling reveals postnatal developmental-related patterns in preterm infants (314/833 proteins) including previously described changes, but also previously unreported proteins. Longitudinal monitoring revealed an immune response signature between SGA and AGA infants. This study highlights the importance of taking postnatal changes into account for translational studies in preterm infants.

Investigations into the role of platelet-activating factor in the peri-conception period of the mare.

In many mammals, the lipid platelet-activating factor (PAF) has important functions in female reproduction and fertility. This study shows that PAF is present in the reproductive tissues of mares and is involved in processes related to ovulation and early pregnancy. Platelet-activating factor (PAF) has been implicated in a number of reproductive processes ranging from ovulation to embryo motility but has not been widely explored in the mare. To identify the presence and examine the role of PAF in the equine periconception processes, targeted mass spectrometry coupled with chromatographic separation was performed on equine follicular fluid (FF), and PAF was quantitatively detected. Subsequently, untargeted high-resolution mass spectrometry-based lipidomic analysis was carried out to quantify PAF in different-sized pre-ovulatory follicles, whereby different molecular species of PAF, PAF (14:0) and PAF (16:1), were both seen to be increasing with follicle diameter. These findings suggest that PAF within FF is increasing as preovulatory follicles approach ovulation. Additionally, immunofluorescence staining identified the PAF receptor in the luminal pericellular, apical, and basal aspect of equine oviductal epithelial cells. Lastly, an equine oviductal epithelial organoid model was generated and showed that the addition of PAF significantly increased the ciliary beat frequency (CBF) (Hz), an action consistent with a role for PAF in embryo migration. It is proposed that the local action of PAF on the ciliated cells of the oviduct propels both the oocyte and the conceptus towards the uterus. In the mare, it appears that PAF is a contributor during the periconception period, potentially being a mediator in the mechanisms of ovulation and in the dialogue of very early pregnancy.

Direct Enantiomer Differentiation of Drugs and Drug-Like Compounds via Noncovalent Copper-Amino Acid Complexation and Ion Mobility-Mass Spectrometry.

Drug enantiomers can possess vastly different pharmacological properties, yet they are identical in their chemical composition and structural connectivity. Thus, resolving enantiomers poses a great challenge in the field of separation science. Enantiomer separations necessitate interaction of the analyte with a chiral environment─in mass spectrometry-based analysis, a common approach is through a three-point interaction with a chiral selector commonly introduced during sample preparation. In select cases, the structural difference imparted through noncovalent complexation results in enantiomer-specific structural differences, facilitating measurement using a structurally selective analytical technique such as ion mobility-mass spectrometry (IM-MS). In this work, we investigate the direct IM-MS differentiation of chiral drug compounds using mononuclear copper complexes incorporating an amino acid chiral selector. A panel of 20 chiral drugs and drug-like compounds were investigated for separation, and four l-amino acids (l-histidine, l-tryptophan, l-proline, and l-tyrosine) were evaluated as chiral selectors (CS) to provide the chiral environment necessary for differentiation. Enantiomer differentiation was achieved for four chiral molecule pairs (R/S-thalidomide, R/S-baclofen, R/S-metoprolol, and d/l-panthenol) with two-peak resolution (Rp-p) values ranging from 0.7 (>10% valley) to 1.5 (baseline separation). Calibration curves relating IM peak areas to enantiomeric concentrations enabled enantiomeric excess quantitation of racemic thalidomide and metoprolol with residuals of 5.7 and 2.5%, respectively. Theoretical models suggest that CuII and l-histidine complexation around the analyte chiral center is important for gas-phase stereoselectivity. This study demonstrates the potential of combining enantioselective noncovalent copper complexation with structurally selective IM-MS for differentiating chiral drugs and drug-like compounds.

Liquid chromatography-mass spectrometry quantification of phytochemicals in Withania somnifera using data-dependent acquisition, multiple-reaction-monitoring, and parallel-reaction-monitoring with an inclusion list.

Characterization of botanical extracts by mass spectrometry-based metabolomics analysis helps in determining the phytochemical composition that underlies their bioactivity and potential health benefits, while also supporting reproducibility of effects in clinical trials. The quantification of seven withanolides in Withania somnifera using three mass-spectrometry methods was evaluated using Deming regression. Two high-resolution time-of-flight mass spectrometry methods were used, one operating in data-dependent acquisition mode and the other in parallel-reaction-monitoring mode with an inclusion list. The two high-resolution time-of-flight mass spectrometry methods were compared to a multiple-reaction-monitoring method. We evaluated in-source fragmentation of steroidal glycosides and optimized the methods accordingly. A novel software approach to integrating parallel-reaction-monitoring data acquired with an inclusion list was developed. Combining and comparing quantitative results allowed for quantitative specificity, good precision, and adjustment of instrument source conditions for optimal quantification by multiple-reaction-monitoring mass spectrometry, an analytical method that is widely accessible in analytical and phytochemical laboratories.

Metabolic Profiling Changes Induced by Fermented Blackberries in High-Fat-Diet-Fed Mice Utilizing Gas Chromatography-Mass Spectrometry Analysis.

The aim of this study was to investigate the metabolic changes associated with the anti-obesity effects of fermented blackberry extracts in the liver tissues of high-fat-diet-fed mice using mass spectrometry-based metabolomics analysis. C57BL/6J mice were divided into eight groups: normal-diet-fed mice, high-fat-diet-fed mice, high-fat diet treated with blackberry extract, high-fat-diet mice treated with blackberry fermented by L. plantarum, and high-fat diet with blackberry fermented by L. brevis. After 12 weeks, the high-fat-diet group exhibited a greater increase in liver weight compared to the control group, and among the groups, the group administered with blackberry fermented with L. plantarum showed the most pronounced reduction in liver weight. As the primary organ responsible for amino acid metabolism, the liver is crucial for maintaining amino acid homeostasis. In our study, we observed that the levels of several essential amino acids, including isoleucine and valine, were decreased by the high-fat diet, and were recovered by administration of blackberry extract fermented with L. plantarum. Our results demonstrated the potential of blackberry extract fermented with L. plantarum as a functional material for metabolic disorders by restoring some of the amino acid metabolism disturbances induced by a high-fat diet.

Spatio-temporal plant hormonomics: from tissue to subcellular resolution.

Due to technological advances in mass spectrometry, significant progress has been achieved recently in plant hormone research. Nowadays, plant hormonomics is well established as a fully integrated scientific field focused on the analysis of phytohormones, mainly on their isolation, identification, and spatiotemporal quantification in plants. This review represents a comprehensive meta-study of the advances in the phytohormone analysis by mass spectrometry over the past decade. To address current trends and future perspectives, Web of Science data were systematically collected and key features such as mass spectrometry-based analyses were evaluated using multivariate data analysis methods. Our findings showed that plant hormonomics is currently divided into targeted and untargeted approaches. Both aim to miniaturize the sample, allowing high-resolution quantification to be covered in plant organs as well as subcellular compartments. Therefore, we can study plant hormone biosynthesis, metabolism, and signalling at a spatio-temporal resolution. Moreover, this trend has recently been accelerated by technological advances such as fluorescence-activated cell sorting or mass spectrometry imaging.

Metabolomic characterization of monoclonal antibody-producing Chinese hamster lung (CHL)-YN cells in glucose-controlled serum-free fed-batch operation.

The fast-growing Chinese hamster lung (CHL)-YN cell line was recently developed for monoclonal antibody production. In this study, we applied a serum-free fed-batch cultivation process to immunoglobulin (Ig)G1-producing CHL-YN cells, which were then used to design a dynamic glucose supply system to stabilize the extracellular glucose concentration based on glucose consumption. Glucose consumption of the cultures rapidly oscillated following three phases of glutamine metabolism: consumption, production, and re-consumption. Use of the dynamic glucose supply prolonged the viability of the CHL-YN-IgG1 cell cultures and increased IgG1 production. Liquid chromatography with tandem mass spectrometry-based target metabolomics analysis of the extracellular metabolites during the first glutamine shift was conducted to search for depleted compounds. The results suggest that the levels of four amino acids, namely arginine, aspartate, methionine, and serine, were sharply decreased in CHL-YN cells during glutamine production. Supporting evidence from metabolic and gene expression analyses also suggest that CHL-YN cells acquired ornithine- and cystathionine-production abilities that differed from those in Chinese hamster ovary-K1 cells, potentially leading to proline and cysteine biosynthesis.

MDB-36. 22-HDOHE, A PREDICTIVE MARKER IN CSF OF PATIENTS WITH RECURRENT MEDULLOBLASTOMA TREATED WITH MEMMAT

Abstract BACKGROUND With the antiangiogenic metronomic MEMMAT combinatorial regimen, we could achieve sustained responses in a quarter of the patients with previously irradiated recurrent medulloblastoma. There are currently no molecular biomarkers predicting response to MEMMAT treatment for recurrent medulloblastoma. Lipid mediators, including classical arachidonic acid-derived eicosanoids and docosanoids, are locally acting bioactive signaling lipids that regulate a diverse set of homeostatic and inflammatory processes. Before initiation of MEMMAT treatment for relapsed medulloblastoma, we examined the bioactive lipid mediator profile in the cerebrospinal fluid (CSF) of patients and compared it with samples from patients with different neurological disorders, but without cancer. METHODS We analyzed CSF samples from 23 patients with relapsed MBL before initiation of MEMMAT treatment and from 12 controls. Lipid mediators were enriched via solid phase extraction and analyzed using liquid chromatography coupled to a high resolution orbitrap Exploris 480 mass spectrometer. RESULTS Mass spectrometry-based untargeted oxylipin analysis led to the identification of 98 lipid mediators. Several molecules were downregulated in medulloblastoma samples versus control, such as lipoxin A4 and 14(15)-DiHETE. Non-responders had lower levels of these molecules than responders. Glycodeoxycholic acid and deoxycholic acid were up-regulated in medulloblastoma patients, again with higher levels in non-responders. Remarkably, the docosahexaenoic acid (DHA)-derived 22-HDoHE was specifically identified in the CSF samples of medulloblastoma patients but not in control samples. CONCLUSION An oxylipin pattern in CSF might serve as a predictive biomarker signature for response in patients with recurrent medulloblastoma treated with the antiangiogenic metronomic MEMMAT regimen. Our findings advocate for the prospective assessment of CSF-derived lipid markers in future trials for recurrent medulloblastoma.

The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses.

Mass spectrometry-based approaches to assess protein conformation have become widely utilized due to their sensitivity, low sample requirements, and broad applicability to proteins regardless of size and environment. Their wide applicability and sensitivity also make these techniques suitable for the analysis of complex mixtures of proteins, and thus, they have been applied at the cell and even the simple organism levels. These works are impressive, but they predominately employ "bottom-up" workflows and require proteolytic digestion prior to analysis. Once digested, it is not possible to distinguish the proteoform from which any single peptide is derived and therefore, one cannot associate distal-in primary structure-concurrent post-translational modifications (PTMs) or covalent labels, as they would be found on separate peptides. Thus, analyses via bottom-up proteomics report the average PTM status and higher-order structure (HOS) of all existing proteoforms. Second, these works predominately employ promiscuous reagents to probe protein HOS. While this does lead to improved conformational resolution, the formation of many products can divide the signal associated with low-copy number proteins below signal-to-noise thresholds and complicate the bioinformatic analysis of these already challenging systems. In this perspective, I further detail these limitations and discuss the positives and negatives of top-down proteomics as an alternative.

Multi Omics Applications in Biological Systems.

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Proteomics and lipidomic analysis reveal dysregulated pathways associated with loss of sacsin.

Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a rare incurable neurodegenerative disease caused by mutations in the SACS gene, which codes for sacsin, a large protein involved in protein homeostasis, mitochondrial function, cytoskeletal dynamics, autophagy, cell adhesion and vesicle trafficking. However, the pathogenic mechanisms underlying sacsin dysfunction are still largely uncharacterized, and so attempts to develop therapies are still in the early stages. To achieve further understanding of how processes are altered by loss of sacsin, we used untargeted proteomics to compare protein profiles in ARSACS fibroblasts versus controls. Our analyses confirmed the involvement of known biological pathways and also implicated calcium and lipid homeostasis in ARSACS skin fibroblasts, a finding further verified in SH-SY5Y SACS -/- cells. Validation through mass spectrometry-based analysis and comparative quantification of lipids by LC-MS in fibroblasts revealed increased levels of ceramides coupled with a reduction of diacylglycerols. In addition to confirming aberrant Ca2+ homeostasis in ARSACS, this study described abnormal lipid levels associated with loss of sacsin.