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Nuclear factor (erythroid-derived 2)-like 2 and its Caenorhabditis elegans ortholog, SKN-1, are transcription factors that have a pivotal role in the oxidative stress response, cellular homeostasis, and organismal lifespan. Similar to other defense systems, the NRF2-mediated stress response is compromised in aging and neurodegenerative diseases. Here, we report that the FDA approved drug hydralazine is a bona fide activator of the NRF2/SKN-1 signaling pathway. We demonstrate that hydralazine extends healthy lifespan (~25%) in wild type and tauopathy model C. elegans at least as effectively as other anti-aging compounds, such as curcumin and metformin. We show that hydralazine-mediated lifespan extension is SKN-1 dependent, with a mechanism most likely mimicking calorie restriction. Using both in vitro and in vivo models, we go on to demonstrate that hydralazine has neuroprotective properties against endogenous and exogenous stressors. Our data suggest that hydralazine may be a viable candidate for the treatment of age-related disorders. Hydralazine is an FDA approved drug for the treatment of hypertension. Here, Dehghan et al. report that hydralazine triggers the cellular oxidative stress response by activating NRF2/SKN-1 signaling and extends C. elegans healthy lifespan, suggesting hydralazine may have potential to treat age-associated diseases more broadly.

The benefit of statins in the prevention of cardiovascular disease is well founded, derived from their lipid lowering and pleiotropic effects. The concept of lipoproteins as lipid transporters has evolved to encompass functions in coagulation, inflammation, and redox reactions due to their unique protein cargo. The aim of this study was to determine the effect of statin therapy on lipoproteins and their protein cargo by use of an unbiased bottom-up proteomics approach in people with hypercholesterolaemia. 11 people fulfilling the inclusion criteria were recruited into this UK-based single centre prospective observational study. They were started on statins for primary prevention. Blood was withdrawn at baseline and after a minimum of 2 months of statin therapy. Plasma was co-incubated with a lipoaffinity resin. Isolated proteins were digested and analysed with label-free two-dimensional liquid chromatography coupled to electrospray high-definition ion mobility tandem mass spectrometry. 218 proteins were identified with Progenesis QI software, with 33 proteins demonstrating significant differential expression between the pre-statin and the on-statin samples (each p<0·05). 17 proteins were upregulated by statin therapy, including proteins concerned with cytoskeletal organisation (vinculin p<0·0001, tropomyosin α4 p=0·0108), antioxidative (peroxiredoxin 2 p=0·0092), and anti-inflammatory effects (transgelin-2 p=0·0071). Apolipoprotein B100 was downregulated by statin therapy, consistent with it mechanism of action (p=0·0006). Statin therapy downregulated novel proteins concerned with the modulation of pancreatic β-cell function (adipsin p=0·0056) and haemopoietic precursor proliferation (stem cell growth factor p<0·0001). Our findings show that statins remodel the cytoskeletal architecture and mediate various anti-inflammatory, antioxidant, and antiproliferative effects that might limit endothelial dysfunction. The downregulation of adipsin, a novel adipokine that stimulates insulin secretion, could explain the controversial link between statin use and the development of diabetes. This study extends our understanding of the beneficial and harmful pleiotropic effects of statin therapy. British Heart Foundation.

BackgroundThe understanding of diastolic heart failure (DHF) has developed in recent years, a condition that was often misdiagnosed for systolic heart failure (SHF). Although there are constant advances in diagnostic technologies, treatment and diagnosis for DHF still remain a challenge prompting a need for biomarker discovery within human plasma. Prospecting for new protein biomarkers can be hindered by the presence of high abundant proteins (HAPs), masking the appearance of potentially diagnostic low abundance proteins (LAPs) due to their dominance in the sample matrix. A novel method, termed Mixed Mode Matrix (M3), is described to reduce the complexity and improve the dynamic range of plasma proteomics to investigate biomarkers in DHF. A pilot study involving controls (n = 10) and disease (DHF n = 10, SHF n = 10) plasma was carried out.MethodHAPs were depleted using MARS14 column, bound to M3, eluted into fractions using increasing concentrations of NaH2PO4 and purified by solid-phase-extraction. A BCA protein assay was used to determine protein concentration prior to digestion. Peptides were separated using high-resolution liquid-chromatography (nano-UPLC) and high-definition-MSE analysis.ResultsA method for LAPs enrichment was developed. Over 300 LAPs were identified with 1% false discovery rate and contained at least 2 identified peptides. In depleting and enriching plasma with M3, we are able to expand the dynamic range of plasma thus enabling us to identify the LAPs.ConclusionM3 has the potential to improve efficiency and cost-effectiveness of LAPs enrichment, leading to plasma protein biomarker identification for diagnosis and treatment of a multitude of disease states.

In the UK, bladder cancer is the 4th most common cancer in men and 11th most common in women. In 2010, just over 10,000 new cases were diagnosed and 4,900 deaths were recorded. At their first diagnosis, the majority of bladder cancer patients (75-85%) present with non-muscle invasive disease. In 50-70% of these patients the tumour will recur and in 10-20% of them it will progress to muscle invasive disease. Mass spectrometry based proteomics has been chosen for clinical biomarker discovery due to its ability to perform qualitative and quantitative protein profiling on clinical samples. In total 90 plasma samples were used in this study in two groups of disease and control. An optimised and evaluated UPLC-IMS-DIA-MSE label-free quantitation method was used for plasma protein profiling. To our knowledge, this is the first report investigating the biomarkers of bladder cancer incorporating label-free quantitation and UPLC-IMS-DIA-MSE methodology. To assess expression level of proteins of samples in different groups a plan consisting of four data processing packages was used. Each of the packages uses different statistical means by which to identify proteins and/or compare expression levels alteration. Optimisation of the methodology helped in the thorough investigation of the plasma proteome with coverage of up to five orders of magnitude of plasma protein concentration dynamic range. In total, 11 proteins were found as possible markers of diagnosis for bladder cancer. Four of these candidates (afamin, alpha 1-B-glycoprotein, apolipoprotein-A1 and haptoglobin) were previously reported to be urinary markers of bladder cancer. CRP was overexpressed when plasma samples from patients with low grade-Ta tumours were compared to every other sample and may be used as a diagnostic marker. Similarly, afamin and haptoglobin were overexpressed in plasma samples from patients with high grade-high stage tumours when compared to samples from patients with high grade-low stage disease.

Across the globe, fungi are impacting the lives of millions of people through the development of infections ranging from superficial to systemic with limited treatment options. To effectively combat fungal disease, rapid and reliable diagnostic methods are required, including current methodologies using antigen detection, culturing, microscopy, and molecular tools. However, the flexibility of these platforms to diagnose infection using non-invasive methods and predict the outcome of disease are limited. In this study, we apply state-of-the-art mass spectrometry-based proteomics to perform dual perspective (i.e., host and pathogen) profiling of cryptococcal infection. Whole blood collected over a temporal scale following murine model challenged with the human fungal pathogen, Cryptococcus neoformans, detected >3,000 host proteins and 160 fungal proteins. From the host perspective, temporal regulation of known immune-associated proteins, including eosinophil peroxidase and lipocalin-2, along with suppression of lipoproteins, demonstrated infection- and time-dependent host remodeling. Conversely, from the pathogen perspective, known and putative virulence-associated proteins were detected, including proteins associated with fungal extracellular vesicles and host immune modulation. We also observed and validated a new mechanism of immune system response to C. neoformans through modulation of haptoglobin. Further, we assessed the predictive power of dual perspective proteome profiling toward prognostics of cryptococcal infection and report a previously undisclosed integration among virulence factor production, immune system modulation, and individual model survival. Together, our findings pose novel biomarkers of cryptococcal infection from whole blood and highlight the potential of personal proteome profiles to determine the prognosis of cryptococcal infection, a new parameter in fungal disease management.

The wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics.BackgroundThe wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics.Investigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments.MethodsInvestigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph™ Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments.We show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts.ResultsWe show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts.The automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.ConclusionsThe automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

The threat and incidence of fungal diseases are increasing, as is the severity and mortality rates associated with these infections. New strategies to combat fungal infections are urgently needed to overcome rising rates of resistance and the emergence of new pathogens. To promote invasion within a host, fungi use highly adapted and regulated virulence factors, and, in turn, the host adopts an active and dynamic immune response to suppress infection. Understanding the interplay between these processes is crucial to move fungal disease management and treatment forward and improve global health outcomes. Within the present study, we tackle these challenges using state-of-the-art mass spectrometry instrumentation to explore proteome remodeling during active infection of Cryptococcus neoformans at an unprecedented depth with spatiotemporal resolution. Our prioritization of three host organs (i.e., lungs, brain, spleen) critical to initiation, progression, and response of disease discovers tissue-specific remodeling across time. Within the lungs, we revealed early and sustained activation of the host immune response integrated with characterization of a promising new antifungal target, and we propose the discovery of a competitive inhibitor for functional target disruption. Within the brain, proteome remodeling aligns with disease progression, and we define a new mechanistic role for haptoglobin in fungal cell modulation, as well as showcasing an adaptive survival response of C. neoformans within an hypoxic environment. Within the spleen, we reveal new dynamics of immune system activation upon cryptococcal infection. Overall, we provide the deepest integrated view of cryptococcal disease dynamics across temporal and spatial scales, revealing unrecognized mechanisms of host immunity and fungal pathogenesis that offer new avenues for targeted therapeutic intervention and disease management.

The growing trend towards high-throughput proteomics demands rapid liquid chromatography-mass spectrometry (LC-MS) cycles that limit the available time to gather the large numbers of MS/MS fragmentation spectra required for identification. Orbitrap analyzers scale performance with acquisition time, and necessarily sacrifice sensitivity and resolving power to deliver higher acquisition rates. We developed a new mass spectrometer that combines a mass resolving quadrupole, the Orbitrap and the novel Asymmetric Track Lossless (Astral) analyzer. The new hybrid instrument enables faster acquisition of high-resolution accurate mass (HRAM) MS/MS spectra compared to state-of-the-art mass spectrometers. Accordingly, new proteomics methods were developed that leverage the strengths of each HRAM analyzer, whereby the Orbitrap analyzer performs full scans with high dynamic range and resolution, synchronized with Astral analyzer’s acquisition of fast and sensitive HRAM MS/MS scans. Substantial improvements are demonstrated over previous methods using current state-of-the-art mass spectrometers.