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It is essential to have a thorough knowledge of the bioavailability and metabolism of dietary flavonols to understand their role in disease prevention. Lightly fried onions containing 275μmol flavonols, principally quercetin-4′-glucoside and quercetin-3,4′-diglucoside, were fed to healthy human volunteers and plasma and urine were collected over a 24h period. Samples were analysed by HPLC with diode array and tandem mass spectrometric detection. Five flavonol metabolites, quercetin-3′-sulphate, quercetin-3-glucuronide, isorhamnetin-3-glucuronide, a quercetin diglucuronide and a quercetin glucuronide sulphate, were detected in plasma in quantifiable amounts with trace quantities of six additional quercetin metabolites. Sub-micromolar peak plasma concentrations (cmax) of quercetin-3′-sulphate, quercetin-3-glucuronide, isorhamnetin-3-glucuronide and quercetin diglucuronide were observed 0.6–0.8h after ingestion. In contrast, the cmax of quercetin glucuronide sulphate was 2.5h. The elimination half-lives (t1/2) of quercetin-3′-sulphate, quercetin-3-glucuronide and quercetin diglucuronide were 1.71, 2.33 and 1.76h respectively, while the t1/2 of isorhamnetin-3-glucuronide was 5.34h and that of quercetin glucuronide sulphate was 4.54h. The profile of metabolites excreted in urine was markedly different to that of plasma with many of the major urinary components, including quercetin-3′-glucuronide, two quercetin glucoside sulphates and a methylquercetin diglucuronide, absent or present in only trace amounts in the bloodstream indicative of substantial phase II metabolism. Total urinary excretion of quercetin metabolites was 12·9μmol, corresponding to 4·7% of intake. If these samples had been subjected to hydrolysis, as in many previous studies, only quercetin and isorhamnetin would have been detected and quantified. The bioactivity of these metabolites should be considered.

The complexity of the cellular proteome is massively expanded by a repertoire of chemically distinct reversible post-translational modifications (PTMs) that control protein localisation, interactions, and function. The temporal and spatial control of these PTMs is central to organism physiology, and mis-regulation of PTMs is a hallmark of many diseases. Here we present an approach to manipulate PTMs on target proteins using nanobodies fused to enzymes that control these PTMs. Anti-GFP nanobodies fused to thioesterases (which depalmitoylate protein cysteines) depalmitoylate GFP tagged substrates. A chemogenetic approach to enhance nanobody affinity for its target enables temporal control of target depalmitoylation. Using a thioesterase fused to a nanobody directed against the Ca(v)1.2 beta subunit we reduce palmitoylation of the Ca(v)1.2 alpha subunit, modifying the channel’s voltage dependence and arrhythmia susceptibility in stem cell derived cardiac myocytes. We conclude that nanobody enzyme chimeras represent an approach to specifically manipulate PTMs, with applications in both the laboratory and the clinic. Reversible palmitoylation regulates the activity and localisation of numerous proteins. Here, Kuo et al develop nanobody-based reagents to specifically target palmitoylation of individual proteins, using this approach to tune the biophysical properties of a single ion channel to prevent arrhythmias in cardiac myocytes.

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.

Air pollution, particularly from fine and ultrafine particulate matter (PM), has been increasingly associated with cardiovascular diseases. Ultrafine carbon, a component of ultrafine PM widely used in industrial settings, is both an environmental and occupational hazard. But the cardiac toxicity of repeated inhalation exposure to ultrafine carbon black (CB) remains unclear. In this study, we investigated how repeated inhalation of CB affects cardiac mitochondrial function, focusing on metabolic pathways and regulatory mechanisms involved in energy production. Male C57BL/6J mice were exposed to either filtered air or CB aerosols (10 mg/m3) for four consecutive days. Cardiac tissues were collected and analyzed to assess changes in metabolic enzyme activity, protein expression, and mitochondrial function using Western blotting, enzymatic assays, and immunoprecipitation. Despite there being few changes in overall protein expression levels, we observed significant impairments in fatty acid oxidation, increased glucose oxidation, and disrupted electron transport chain (ETC) supercomplex assembly, particularly in Complexes III and IV. These changes were accompanied by increased hyperacetylation of mitochondrial proteins and elevated levels of GCN5L1, a mitochondrial acetyltransferase. We also found increased lipid peroxidation and hyperacetylation of antioxidant enzyme SOD2 at the K-122 site, which reflects reduced enzymatic activity contributing to oxidative stress. Our findings suggest that repeated CB inhalation leads to mitochondrial dysfunction in the heart by dysregulating substrate utilization, impairing ETC activities, and weakening antioxidant defenses primarily through lysine acetylation. These findings reveal a potential role of key post-translational mechanisms in environmental particulate exposure to mitochondrial impairment and provide a potential therapeutic target for CB-induced cardiotoxicity.

Chronic kidney disease (CKD) is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR) at mild (59.9±16.5 mL/min/1.73 m2; n = 10) or advanced (8.9±4.5 mL/min/1.73 m2; n = 10) CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = -0.8031; p<0.0001 and ρ = -0.6009; p = 0.0019, respectively). Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = -0.6557; p = 0.0001 and ρ = -0.6574; p = 0.0005). A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = -0.7752; p<0.0001 and ρ = -0.8400; p<0.0001). The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In conclusion, we found excellent association of plasma and urinary metabolites and urinary peptides with kidney function, and disease progression, but no added value in combining the different biomarkers data.

Proteome analysis of complex biological samples for biomarker identification remains challenging, among others due to the extended range of protein concentrations. High-abundance proteins like albumin or IgG of plasma and urine, may interfere with the detection of potential disease biomarkers. Currently, several options are available for the depletion of abundant proteins in plasma. However, the applicability of these methods in urine has not been thoroughly investigated. In this study, we compared different, commercially available immunodepletion and ion-exchange based approaches on urine samples from both healthy subjects and CKD patients, for their reproducibility and efficiency in protein depletion. A starting urine volume of 500 μL was used to simulate conditions of a multi-institutional biomarker discovery study. All depletion approaches showed satisfactory reproducibility (n=5) in protein identification as well as protein abundance. Comparison of the depletion efficiency between the unfractionated and fractionated samples and the different depletion strategies, showed efficient depletion in all cases, with the exception of the ion-exchange kit. The depletion efficiency was found slightly higher in normal than in CKD samples and normal samples yielded more protein identifications than CKD samples when using both initial as well as corresponding depleted fractions. Along these lines, decrease in the amount of albumin and other targets as applicable, following depletion, was observed. Nevertheless, these depletion strategies did not yield a higher number of identifications in neither the urine from normal nor CKD patients. Collectively, when analyzing urine in the context of CKD biomarker identification, no added value of depletion strategies can be observed and analysis of unfractionated starting urine appears to be preferable.

There is absence of specific biomarkers and an incomplete understanding of the pathophysiology of exudative age-related macular degeneration (AMD). Eighty-eight vitreous samples (73 from patients with treatment naïve AMD and 15 control samples from patients with idiopathic floaters) were analyzed with capillary electrophoresis coupled to mass spectrometry in this retrospective case series to define potential candidate protein markers of AMD. Nineteen proteins were found to be upregulated in vitreous of AMD patients. Most of the proteins were plasma derived and involved in biological (ion) transport, acute phase inflammatory reaction, and blood coagulation. A number of proteins have not been previously associated to AMD including alpha-1-antitrypsin, fibrinogen alpha chain and prostaglandin H2-D isomerase. Alpha-1-antitrypsin was validated in vitreous of an independent set of AMD patients using Western blot analysis. Further systems biology analysis of the data indicated that the observed proteomic changes may reflect upregulation of immune response and complement activity. Proteome analysis of vitreous samples from patients with AMD, which underwent an intravitreal combination therapy including a core vitrectomy, steroids and bevacizumab, revealed apparent AMD-specific proteomic changes. The identified AMD-associated proteins provide some insight into the pathophysiological changes associated with AMD.

Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69), compared to controls (n = 33), and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004) or 35 biomarkers (nominal p-value <0.01). When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (-0.30 to 1.25) in cases compared to -1.04 (IQR -1.86 to -0.09) in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials.

Background The timely and accurate diagnosis of bloodstream infection (BSI) is critical for patient management. With longstanding challenges for routine blood culture, metagenomics is a promising approach to rapidly provide sequence-based detection and characterisation of bloodborne bacteria. Long-read sequencing technologies have successfully supported the use of clinical metagenomics for syndromes such as respiratory illness, and modified approaches may address two requisite factors for metagenomics to be used as a BSI diagnostic: depletion of the high level of host DNA to then detect the low abundance of microbes in blood. Methods Blood samples from healthy donors were spiked with different concentrations of four prevalent causative species of BSI. All samples were then subjected to a modified saponin-based host DNA depletion protocol and optimised DNA extraction, whole genome amplification and debranching steps in preparation for sequencing, followed by bioinformatical analyses. Two related variants of the protocol are presented: 1mL of blood processed without bacterial enrichment, and 5mL of blood processed following a rapid bacterial enrichment protocol—Sepsi PURE . Results After first identifying that a large proportion of host mitochondrial DNA remained, the host depletion process was optimised by increasing saponin concentration to 3% and scaling the reaction to allow more sample volume. Compared to non-depleted controls, the 3% saponin-based depletion protocol reduced the presence of host chromosomal and mitochondrial DNA < 10 6 and < 10 3 fold respectively. When the modified depletion method was further combined with a rapid bacterial enrichment method (Sepsi PURE ; with 5mL blood samples) the depletion of mitochondrial DNA improved by a further > 10X while also increasing detectable bacteria by > 10X. Parameters during DNA extraction, whole genome amplification and long-read sequencing were also adjusted, and subsequently amplicons were detected for each input bacterial species at each of the spiked concentrations, ranging from 50–100 colony forming units (CFU)/mL to 1–5 CFU/mL. Conclusion In this proof-of-concept study, four prevalent BSI causative species were detected in under 12 h to species level (with antimicrobial resistance determinants) at concentrations relevant to clinical blood samples. The use of a rapid and precise metagenomic protocols has the potential to advance the diagnosis of BSI.

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.