Single-cell lipidomics: protocol development for reliable cellular profiling using capillary sampling.

Single-cell lipidomics enables detailed analysis of the lipidomes of cells, but is challenged by small sample volumes, the risk of background interference and a lack of validation data. In this study, we explore the effect of different sampling variables on the lipid profiles of single pancreatic cancer cells, detected using liquid chromatography-mass spectrometry (LC-MS). We use automated and manual capillary sampling methods to isolate living single cells and evaluate different sampling media, capillary tips, aspiration volume, and temperature and humidity control.

Challenges and opportunities for statistical power and biomarker identification arising from rhythmic variation in proteomics.

Time-of-day variation in the molecular profile of biofluids and tissues is a well-described phenomenon, but-especially for proteomics-is rarely considered in terms of the challenges this presents to reproducible biomarker identification. We provide a case study analysis of human circadian and ultradian rhythmicity in proteins, including in the complement and coagulation cascades and apolipoproteins, with PLG, CFAH, ZA2G and ITIH2 demonstrated as rhythmic for the first time. We also show that rhythmicity increases the risk of Type II errors due to the reduction in statistical power from increased variance, and that controlling for rhythmic time-of-day variation improves statistical power and reduces the chances of Type II errors.

Identifying key weather factors influencing human salmonellosis: A conditional incidence analysis in England, Wales, and the Netherlands.

Objectives: This study aimed to improve the understanding of seasonal incidence pattern observed in salmonellosis by identifying the most influential weather factors, characterising the nature of this association, and assessing whether it is geographically restricted or generalisable to other locations.

Methods: A novel statistical model was employed to estimate the incidence of salmonellosis conditional to various combinations of three simultaneous weather factors from 14 available. The analysis utilised daily salmonellosis cases reported from 2000 to 2016 along with detailed spatial and temporal weather data from England and Wales, and the Netherlands.

Single-Cell Lipidomics: An Automated and Accessible Microfluidic Workflow Validated by Capillary Sampling.

We report the first demonstration of a microfluidics-based approach to measure lipids in single living cells using widely available liquid chromatography mass spectrometry (LC-MS) instrumentation. The method enables the rapid sorting of live cells into liquid chambers formed on standard Petri dishes and their subsequent dispensing into vials for analysis using LC-MS. This approach facilitates automated sampling, data acquisition, and analysis and carries the additional advantage of chromatographic separation, aimed at reducing matrix effects present in shotgun lipidomics approaches.

Challenges in Lipidomics Biomarker Identification: Avoiding the Pitfalls and Improving Reproducibility.

Identification of features with high levels of confidence in liquid chromatography-mass spectrometry (LC-MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in biomarker identification. In this work, we illustrate the reproducibility gap for two open-access lipidomics platforms, MS DIAL and Lipostar, finding just 14.

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.

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.

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.

A Novel Blood Proteomic Signature for Prostate Cancer.

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.

Metabolomic Analysis of Plasma in Huntington's Disease Transgenic Sheep (Ovis aries) Reveals Progressive Circadian Rhythm Dysregulation.

Background: Metabolic abnormalities have long been predicted in Huntington's disease (HD) but remain poorly characterized. Chronobiological dysregulation has been described in HD and may include abnormalities in circadian-driven metabolism.

Objective: Here we investigated metabolite profiles in the transgenic sheep model of HD (OVT73) at presymptomatic ages.

Multi-Omics Reveals Mechanisms of Partial Modulation of COVID-19 Dysregulation by Glucocorticoid Treatment.

Treatments for COVID-19 infections have improved dramatically since the beginning of the pandemic, and glucocorticoids have been a key tool in improving mortality rates. The UK's National Institute for Health and Care Excellence guidance is for treatment to be targeted only at those requiring oxygen supplementation, however, and the interactions between glucocorticoids and COVID-19 are not completely understood. In this work, a multi-omic analysis of 98 inpatient-recruited participants was performed by quantitative metabolomics (using targeted liquid chromatography-mass spectrometry) and data-independent acquisition proteomics.

Untargeted saliva metabolomics by liquid chromatography-Mass spectrometry reveals markers of COVID-19 severity.

Background: The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression.

Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.

The effect of COVID-19 infection on the human metabolome has been widely reported, but to date all such studies have focused on a single wave of infection. COVID-19 has generated numerous waves of disease with different clinical presentations, and therefore it is pertinent to explore whether metabolic disturbance changes accordingly, to gain a better understanding of its impact on host metabolism and enable better treatments. This work used a targeted metabolomics platform (Biocrates Life Sciences) to analyze the serum of 164 hospitalized patients, 123 with confirmed positive COVID-19 RT-PCR tests and 41 providing negative tests, across two waves of infection.

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

Background: The 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.

Method: 23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls.

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.

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.