Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum.

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10-8 and 3.7 × 10-8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum

A JEDI NMR pulse experiment incorporating relaxational, diffusional and J-modulation peak editing has been implemented for a low field (80 MHz proton resonance frequency) spectrometer system to measure quantitatively two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation. JEDI spectra capture a unique signature of two biomarker signals from acetylated glycoproteins (Glyc) and the supramolecular phospholipid composite (SPC) signals that are relatively enhanced by the combination of relaxation, diffusion and J-editing properties of the JEDI experiment that strongly attenuate contributions from the other molecular species in plasma. The SPC/Glyc ratio data were essentially identical in the 600 MHz and 80 MHz spectra obtained (R2 = 0.97) and showed significantly different ratios for control (n = 28) versus SARS-CoV-2 positive patients (n = 29) (p = 5.2 × 10−8 and 3.7 × 10−8 respectively). Simplification of the sample preparation allows for data acquisition in a similar time frame to high field machines (∼4 min) and a high-throughput version with 1 min experiment time could be feasible. These data show that these newly discovered inflammatory biomarkers can be measured effectively on low field NMR instruments that do not not require housing in a complex laboratory environment, thus lowering the barrier to clinical translation of this diagnostic technology

Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection

Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management

Diagnostic potential of the plasma lipidome in infectious disease: application to acute SARS-CoV-2 infection

Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management

An NMR-based model to investigate the metabolic phenoreversion of COVID-19 patients throughout a longitudinal study.

After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts

The RNA-binding protein human antigen R controls global changes in gene expression during Schwann cell development.

Contains fulltext : 109744.pdf (publisher's version ) (Open Access)An important prerequisite to myelination in peripheral nerves is the establishment of one-to-one relationships between axons and Schwann cells. This patterning event depends on immature Schwann cell proliferation, apoptosis, and morphogenesis, which are governed by coordinated changes in gene expression. Here, we found that the RNA-binding protein human antigen R (HuR) was highly expressed in immature Schwann cells, where genome-wide identification of its target mRNAs in vivo in mouse sciatic nerves using ribonomics showed an enrichment of functionally related genes regulating these processes. HuR coordinately regulated expression of several genes to promote proliferation, apoptosis, and morphogenesis in rat Schwann cells, in response to NRG1, TGFbeta, and laminins, three major signals implicated in this patterning event. Strikingly, HuR also binds to several mRNAs encoding myelination-related proteins but, contrary to its typical function, negatively regulated their expression, likely to prevent ectopic myelination during development. These functions of HuR correlated with its abundance and subcellular localization, which were regulated by different signals in Schwann cells

Integrative modeling of plasma metabolic and lipoprotein biomarkers of SARS-CoV-2 infection in Spanish and Australian COVID-19 patient cohorts

Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T2-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping

Mdm2 regulates HuR stability in human liver and colon cancer through neddylation.

Hu antigen R (HuR) is a central RNA-binding protein regulating cell dedifferentiation, proliferation and survival, well-established hallmarks of cancer. HuR is frequently overexpressed in tumors correlating with tumor malignancy, in line with a role for HuR in tumorigenesis. However, the precise mechanism leading to changes in HuR expression remains unclear. In the liver, HuR plays a crucial role in hepatocyte proliferation, differentiation, and transformation. Here, we unravel a novel mean of regulation of HuR expression in HCC and colon cancer. HuR levels correlate with the abundance of the oncogene Mdm2 in human HCC and colon cancer metastases. HuR is stabilized by Mdm2-mediated NEDDylation in at least three lysine residues, ensuring its nuclear localization and protection from degradation. CONCLUSION: This novel Mdm2/NEDD8/HuR regulatory framework is essential for malignant transformation of tumor cells, which in turn unveils a novel signaling paradigm, pharmacologically amenable for cancer therapy. (HEPATOLOGY 2011.)