Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells

In this work, we demonstrate the development and first application of nanocapillary sampling followed by analytical flow liquid chromatography–mass spectrometry for single-cell lipidomics. Around 260 lipids were tentatively identified in a single cell, demonstrating remarkable sensitivity. Human pancreatic ductal adenocarcinoma cells (PANC-1) treated with the chemotherapeutic drug gemcitabine can be distinguished from controls solely on the basis of their single-cell lipid profiles. Notably, the relative abundance of LPC(0:0/16:0) was significantly affected in gemcitabine-treated cells, in agreement with previous work in bulk. This work serves as a proof of concept that live cells can be sampled selectively and then characterized using automated and widely available analytical workflows, providing biologically relevant outputs

Changes to the sebum lipidome upon COVID-19 infection observed via rapid sampling from the skin

Background: The COVID-19 pandemic has led to an unprecedented demand for testing - for diagnosis and prognosis - as well as for investigation into the impact of the disease on the host metabolism. Sebum sampling has the potential to support both needs by looking at what the virus does to us, rather than looking for the virus itself. Methods: In this pilot study, sebum samples were collected from 67 hospitalised patients (30 COVID-19 positive and 37 COVID-19 negative) by gauze swab. Lipidomics analysis was carried out using liquid chromatography mass spectrometry, identifying 998 reproducible features. Univariate and multivariate statistical analyses were applied to the resulting feature set. Findings: Lipid levels were depressed in COVID-19 positive participants, indicative of dyslipidemia; p-values of 0·022 and 0·015 were obtained for triglycerides and ceramides respectively, with effect sizes of 0·44 and 0·57. Partial Least Squares-Discriminant Analysis showed separation of COVID-19 positive and negative participants with sensitivity of 57% and specificity of 68%, improving to 79% and 83% respectively when controlled for confounding comorbidities. Interpretation: COVID-19 dysregulates many areas of metabolism; in this work we show that the skin lipidome can be added to the list. Given that samples can be provided quickly and painlessly, we conclude that sebum is worthy of future consideration for clinical sampling. Funding: The authors acknowledge funding from the EPSRC Impact Acceleration Account for sample collection and processing, as well as EPSRC Fellowship Funding EP/R031118/1, the University of Surrey and BBSRC BB/T002212/1. Mass Spectrometry was funded under EP/P001440/1

A novel blood proteomic signature for prostate cancer

International audienceSimple Summary Despite intensive research, effective tools for detection and monitoring of prostate cancer remain to be found. Prostate-specific antigen (PSA), commonly used in prostate cancer assessments, can lead to overdiagnosis and overtreatment of indolent disease. This highlights the need for supporting non-invasive diagnostic, prognostic, and disease stratification biomarkers that could complement PSA in clinical decision-taking via increased sensitivity and specificity. In order to address this need, we uncover novel prostate cancer protein signatures by leveraging a cutting-edge analytical technique to measure proteins in patient samples. This strategy was used as a discovery tool to identify changes in protein levels in the serum of newly diagnosed patients as compared with healthy controls; the feature set was then further validated by reference to a second cohort of patients, achieving a high discriminatory ability. The proteomic maps generated also identified relevant changes in biological functions, notably the complement cascade. Prostate cancer is the most common malignant tumour in men. Improved testing for diagnosis, risk prediction, and response to treatment would improve care. Here, we identified a proteomic signature of prostate cancer in peripheral blood using data-independent acquisition mass spectrometry combined with machine learning. A highly predictive signature was derived, which was associated with relevant pathways, including the coagulation, complement, and clotting cascades, as well as plasma lipoprotein particle remodeling. We further validated the identified biomarkers against a second cohort, identifying a panel of five key markers (GP5, SERPINA5, ECM1, IGHG1, and THBS1) which retained most of the diagnostic power of the overall dataset, achieving an AUC of 0.91. Taken together, this study provides a proteomic signature complementary to PSA for the diagnosis of patients with localised prostate cancer, with the further potential for assessing risk of future development of prostate cancer. Data are available via ProteomeXchange with identifier PXD025484

Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry

BackgroundThe global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date.Method23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2 858 COVID-19 positive participants and 2 544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden’s Index, in addition to assessing heterogeneity.FindingsSensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81 - 0.96) and specificity 0.88 (interquartile range 0.82 - 0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application.ConclusionsThis systematic review and meta-analysis demonstrates the potential for mass spectrometry and ‘omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications

Fully Degradable Thioester-functional Homo- and Alternating Copolymers Prepared through Thiocarbonyl Addition–Ring-opening RAFT Radical Polymerization

The radical ring-opening polymerization (RROP) of thionolactones provides access to thioester backbone-functional copolymers but has, to date, only been demonstrated on acrylic copolymers. Herein, the thionolactone dibenzo[c,e]oxepane-5-thione (DOT) was subjected to azobisisobutyronitrile (AIBN)-initiated free-radical homopolymerization, which produced a thioester-functional homopolymer with a glass-transition temperature of 95 °C and the ability to degrade exclusively into predetermined small molecules. However, the homopolymerization was impractically slow and precluded the introduction of functionality. Conversely, the reversible addition–fragmentation chain-transfer (RAFT)-mediated copolymerization of DOT with N-methylmaleimide (MeMI), N-phenylmaleimide (PhMI), and N-2,3,4,5,6-pentafluorophenylmaleimide (PFPMI) rapidly produced well-defined copolymers with the tendency to form alternating sequences increasing in the order MeMI ≪ PhMI < PFPMI, with estimated reactivity ratios of rDOT = 0.198 and rPFPMI = 0.0078 for the latter system. Interestingly, defects in the alternating structure were more likely caused by (degradable) DOT–DOT sequences rather than (nondegradable) MI–MI sequences, which was confirmed through the paper spray mass spectrometric analysis of the products from aminolytic degradation. Upon the aminolysis of backbone thioesters, maleimide repeating units were ring-opened, forming bisamide structures. Conversely, copolymer degradation through a thiolate did not result in imide substitution but nucleophilic para-fluoro substitution on PFPMI comonomer units, indicating the ability of DOT–MI copolymers to degrade under different conditions and to form differently functional products. The RROP of thionolactones has distinct advantages over the RROP of cyclic ketene acetals and is anticipated to find use in the development of well-defined degradable polymer materials

Thioester-functional Polyacrylamides: Rapid Selective Backbone Degradation Triggers Solubility Switch Based on Aqueous LCST/UCST

Radical ring-opening polymerization is a clever strategy to incorporate cleavable linkages into otherwise non-degradable vinyl polymers. But conventional systems suffer from slow copolymerization, harsh non-selective degradation conditions, and limited application potential because the degradation products (often oligomers or polymers themselves) have properties like the intact species. This work presents fast selective degradation accompanied by a drastic change in a key property, aqueous solubility. The thionolactone dibenzo[c,e]oxepane-5-thione was found to copolymerise radically with a range of primary, secondary, and tertiary neutral and zwitterionic acrylamides with rapid incorporation of degradable biphenyl thiocarboxylate repeat units. Intact copolymers displayed temperature-responsive (LCST or UCST-type) aqueous solubility behaviour, tuneable through the molar composition and (exploiting the non-azeotropic copolymerization behaviour) comonomer sequence. Various conditions led to selective and complete degradation of the backbone thioesters through hydrolysis, aminolysis, transthioesterification (including under physiological conditions), and oxidative hydrolysis which drastically increased aqueous solubility. Polymers containing as little as 8 mol-% of thioester repeat units underwent a temperature-independent insoluble–soluble transition upon degradation with cysteine or potassium persulfate. Insoluble polymers were used to block syringe filters which allowed flow of degradant solutions only, relevant relevant to lab-on-a-chip, sensing, and embolic biomedical applications

Changes to the sebum lipidome upon COVID-19 infection observed via rapid sampling from the skin

Description This dataset of participant, field blank and quality control liquid-chromatography-mass spectrometry .raw files supports the following article: Changes to the sebum lipidome upon COVID-19 infection observed via rapid sampling from the skin - EClinicalMedicine (thelancet.com) Background The COVID-19 pandemic has led to an unprecedented demand for testing - for diagnosis and prognosis - as well as for investigation into the impact of the disease on the host metabolism. Sebum sampling has the potential to support both needs by looking at what the virus does to us, rather than looking for the virus itself. Methods and attached dataset description In this pilot study, sebum samples were collected from 67 hospitalised patients (30 COVID-19 positive and 37 COVID-19 negative) by gauze swab. Lipidomics analysis was carried out using liquid chromatography mass spectrometry, identifying 998 reproducible features. Univariate and multivariate statistical analyses were applied to the resulting feature set. The dataset uploaded here represents .raw liquid chromatography-mass spectrometry files for participants (triplicate injections), field blanks and pooled quality control standards, as well as the output peak:area matrix. Findings Lipid levels were depressed in COVID-19 positive participants, indicative of dyslipidemia; p-values of 0·022 and 0·015 were obtained for triglycerides and ceramides respectively, with effect sizes of 0·44 and 0·57. Partial Least Squares-Discriminant Analysis showed separation of COVID-19 positive and negative participants with sensitivity of 57% and specificity of 68%, improving to 79% and 83% respectively when controlled for confounding comorbidities. Interpretation COVID-19 dysregulates many areas of metabolism; in this work we show that the skin lipidome can be added to the list. Given that samples can be provided quickly and painlessly, we conclude that sebum is worthy of future consideration for clinical sampling

Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers

The global COVID-19 pandemic resulted in widespread harms but also rapid advances in vaccine development, diagnostic testing, and treatment. As the disease moves to endemic status, the need to identify characteristic biomarkers of the disease for diagnostics or therapeutics has lessened, but lessons can still be learned to inform biomarker research in dealing with future pathogens. In this work, we test five sets of research-derived biomarkers against an independent targeted and quantitative Liquid Chromatography–Mass Spectrometry metabolomics dataset to evaluate how robustly these proposed panels would distinguish between COVID-19-positive and negative patients in a hospital setting. We further evaluate a crowdsourced panel comprising the COVID-19 metabolomics biomarkers most commonly mentioned in the literature between 2020 and 2023. The best-performing panel in the independent dataset—measured by F1 score (0.76) and AUROC (0.77)—included nine biomarkers: lactic acid, glutamate, aspartate, phenylalanine, β-alanine, ornithine, arachidonic acid, choline, and hypoxanthine. Panels comprising fewer metabolites performed less well, showing weaker statistical significance in the independent cohort than originally reported in their respective discovery studies. Whilst the studies reviewed here were small and may be subject to confounders, it is desirable that biomarker panels be resilient across cohorts if they are to find use in the clinic, highlighting the importance of assessing the robustness and reproducibility of metabolomics analyses in independent populations

Loss of a pyoverdine secondary receptor in Pseudomonas aeruginosa results in a fitter strain suitable for population invasion

The rapid emergence of antibiotic resistant bacterial pathogens constitutes a critical problem in healthcare and requires the development of novel treatments. Potential strategies include the exploitation of microbial social interactions based on public goods, which are produced at a fitness cost by cooperative microorganisms, but can be exploited by cheaters that do not produce these goods. Cheater invasion has been proposed as a ‘Trojan horse’ approach to infiltrate pathogen populations with strains deploying built-in weaknesses (e.g., sensitiveness to antibiotics). However, previous attempts have been often unsuccessful because population invasion by cheaters was prevented by various mechanisms including the presence of spatial structure (e.g., growth in biofilms), which limits the diffusion and exploitation of public goods. Here we followed an alternative approach and examined whether the manipulation of public good uptake and not its production could result in potential ‘Trojan horses’ suitable for population invasion. We focused on the siderophore pyoverdine produced by the human pathogen Pseudomonas aeruginosa MPAO1 and manipulated its uptake by deleting and/or overexpressing the pyoverdine primary (FpvA) and secondary (FpvB) receptors. We found that receptor synthesis feeds back on pyoverdine production and uptake rates, which led to strains with altered pyoverdine-associated costs and benefits. Moreover, we found that the receptor FpvB was advantageous under iron-limited conditions but revealed hidden costs in the presence of an antibiotic stressor (gentamicin). As a consequence, FpvB mutants became the fittest strain under gentamicin exposure, displacing the wildtype in liquid cultures, and in biofilms and during infections of the wax moth larvae Galleria mellonella, which both represent structured environments. Our findings reveal that an evolutionary trade-off associated with the costs and benefits of a versatile pyoverdine uptake strategy can be harnessed for devising a Trojan-horse candidate for medical interventions

Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia

There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants diagnosed with PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model separated PCa from controls with sensitivity of 0.82 and specificity of 0.95, adding BPH resulted in a statistically significant decline in specificity for prostate cancer to 0.76, with half of BPH cases being misclassified by the model as PCa. A small number of biomarkers differentiating between BPH and prostate cancer were identified, including proteins in MAP Kinase pathways, as well as in lipids containing oleic acid; these may offer a route to greater specificity. These results highlight, however, that whilst there are opportunities for machine learning, these will only be achieved by use of appropriate training sets that include confounding comorbidities, especially when calculating the specificity of a test