Neisseria meningitidis accumulate in large organs during meningococcal sepsis

BackgroundNeisseria meningitidis (Nm) is the cause of epidemic meningitis and fulminant meningococcal septicemia. The clinical presentations and outcome of meningococcal septic shock is closely related to the circulating levels of lipopolysaccharides (LPS) and of Neisseria meningitidis DNA (Nm DNA). We have previously explored the distribution of Nm DNA in tissues from large organs of patients dying of meningococcal septic shock and in a porcine meningococcal septic shock model.Objective1) To explore the feasibility of measuring LPS levels in tissues from the large organs in patients with meningococcal septic shock and in a porcine meningococcal septic shock model. 2) To evaluate the extent of contamination of non-specific LPS during the preparation of tissue samples.Patients and methodsPlasma, serum, and fresh frozen (FF) tissue samples from the large organs of three patients with lethal meningococcal septic shock and two patients with lethal pneumococcal disease. Samples from a porcine meningococcal septic shock model were included. Frozen tissue samples were thawed, homogenized, and prepared for quantification of LPS by Pyrochrome® Limulus Amoebocyte Lysate (LAL) assay.ResultsN. meningitidis DNA and LPS was detected in FF tissue samples from large organs in all patients with meningococcal septic shock. The lungs are the organs with the highest LPS and Nm DNA concentration followed by the heart in two of the three meningococcal shock patients. Nm DNA was not detected in any plasma or tissue sample from patients with lethal pneumococcal infection. LPS was detected at a low level in all FF tissues from the two patients with lethal pneumococcal disease. The experimental porcine meningococcal septic shock model indicates that also in porcinis the highest LPS and Nm DNA concentration are detected in lungs tissue samples. The quantification analysis showed that the highest concentration of both Nm DNA and LPS are in the organs and not in the circulation of patients with lethal meningococcal septic shock. This was also shown in the experimental porcine meningococcal septic shock model.ConclusionOur results suggest that LPS can be quantified in mammalian tissues by using the LAL assay

Distinct microRNA and protein profiles of extracellular vesicles secreted from myotubes from morbidly obese donors with type 2 diabetes in response to electrical pulse stimulation

Lifestyle disorders like obesity, type 2 diabetes (T2D), and cardiovascular diseases can be prevented and treated by regular physical activity. During exercise, skeletal muscles release signaling factors that communicate with other organs and mediate beneficial effects of exercise. These factors include myokines, metabolites, and extracellular vesicles (EVs). In the present study, we have examined how electrical pulse stimulation (EPS) of myotubes, a model of exercise, affects the cargo of released EVs. Chronic low frequency EPS was applied for 24 h to human myotubes isolated and differentiated from biopsy samples from six morbidly obese females with T2D, and EVs, both exosomes and microvesicles (MV), were isolated from cell media 24 h thereafter. Size and concentration of EV subtypes were characterized by nanoparticle tracking analysis, surface markers were examined by flow cytometry and Western blotting, and morphology was confirmed by transmission electron microscopy. Protein content was assessed by high-resolution proteomic analysis (LC-MS/MS), non-coding RNA was quantified by Affymetrix microarray, and selected microRNAs (miRs) validated by real time RT-qPCR. The size and concentration of exosomes and MV were unaffected by EPS. Of the 400 miRs identified in the EVs, EPS significantly changed the level of 15 exosome miRs, of which miR-1233-5p showed the highest fold change. The miR pattern of MV was unaffected by EPS. Totally, about 1000 proteins were identified in exosomes and 2000 in MV. EPS changed the content of 73 proteins in exosomes, 97 in MVs, and of these four were changed in both exosomes and MV (GANAB, HSPA9, CNDP2, and ATP5B). By matching the EPS-changed miRs and proteins in exosomes, 31 targets were identified, and among these several promising signaling factors. Of particular interest were CNDP2, an enzyme that generates the appetite regulatory metabolite Lac-Phe, and miR-4433b-3p, which targets CNDP2. Several of the regulated miRs, such as miR-92b-5p, miR-320b, and miR-1233-5p might also mediate interesting signaling functions. In conclusion, we have used a combined transcriptome-proteome approach to describe how EPS affected the cargo of EVs derived from myotubes from morbidly obese patients with T2D, and revealed several new factors, both miRs and proteins, that might act as exercise factors

Effect of Storage Temperature on Key Functions of Cultured Retinal Pigment Epithelial Cells

Purpose. Replacement of the diseased retinal pigment epithelium (RPE) with cells capable of performing the specialized functions of the RPE is the aim of cell replacement therapy for treatment of macular degenerative diseases. A storage method for RPE is likely to become a prerequisite for the establishment of such treatment. Herein, we analyze the effect of storage temperature on key functions of cultured RPE cells. Methods. Cultured ARPE-19 cells were stored in Minimum Essential Medium at 4°C, 16°C, and 37°C for seven days. Total RNA was isolated and the gene expression profile was determined using DNA microarrays. Comparison of the microarray expression values with qRT-PCR analysis of selected genes validated the results. Results. Expression levels of several key genes involved in phagocytosis, pigment synthesis, the visual cycle, adherens, and tight junctions, and glucose and ion transport were maintained close to control levels in cultures stored at 4°C and 16°C. Cultures stored at 37°C displayed regulational changes in a larger subset of genes related to phagocytosis, adherens, and tight junctions. Conclusion. RPE cultures stored at 4°C and 16°C for one week are capable of maintaining the expression levels of genes important for key RPE functions close to control levels

Cigarette smoking represses expression of cytokine IL-12 and its regulator miR-21-An observational study in patients with coronary artery disease.

Rationale The heterodimer IL-12 is an inducer of Th1 responses and stimulates INFƴ production. Micro-RNA-21 (miR-21) is described as a key regulator of the pro-inflammatory response and has IL-12p35 mRNA as one of its main targets. The IL-12p40 1188A/C genetic variant located in 3’untranslated region (UTR), thus environmentally exposed, has further been reported to modify IL-12 levels. We have previously reported on the lowering effect of cigarette smoke on circulating IL-12 in patients with coronary artery disease (CAD). Objectives To explore if cigarette smoking affects IL-12p35, IL-12p40, INFƴ and miR-21 gene-expression and further modulates any effect of the IL-12p40 polymorphism on circulating IL-12 levels. Methods and Results The IL-12p40 1188A/C polymorphism was analyzed in 1001 stable CAD patients, of which 330 subjects were included for IL-12p35, IL-12p40 and INFƴ gene-expression analyses in circulating leukocytes and 200 were further selected for plasma miR-21 analysis. Smoking associated with lower expression of miR-21 and its target IL-12p35 mRNA (adjusted p < 0.05, both) whereas the influence on INFƴ expression tended to be high-dose reliant (p = 0.057). The IL-12p40 CC genotype associated with elevated circulating IL-12 levels, however, when stratified according to smoking, only in the non-smoking group (adjusted p < 0.05). Although the markers were mainly downregulated in current smokers, their inter-correlations were potentiated. Conclusion Smoking associated with reduced miR-21 gene-repression and the results can therefore not explain the previously observed reduction in circulating IL-12. Smoking attenuated the IL-12 pro-inflammatory axis in which the investigated IL-12p40 genetic variant may have different clinical impact in smokers vs non-smokers. Opstad, T. B., et al. "Cigarette smoking represses expression of cytokine IL-12 and its regulator miR-21—An observational study in patients with coronary artery disease." Immunobiology 222.2 (2017): 169-175. © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license

Urine β-2-Microglobulin, Osteopontin, and Trefoil Factor 3 May Early Predict Acute Kidney Injury and Outcome after Cardiac Arrest

Purpose. Acute kidney injury (AKI) is a common complication after out-of-hospital cardiac arrest (OHCA), leading to increased mortality and challenging prognostication. Our aim was to examine if urine biomarkers could early predict postarrest AKI and patient outcome. Methods. A prospective observational study of resuscitated, comatose OHCA patients admitted to Oslo University Hospital in Norway. Urine samples were collected at admission and day three postarrest and analysed for β-2-microglobulin (β2M), osteopontin, and trefoil factor 3 (TFF3). Outcome variables were AKI within three days according to the Kidney Disease Improving Global Outcome criteria, in addition to six-month mortality and poor neurological outcome (PNO) (cerebral performance category 3–5). Results. Among 195 included patients (85% males, mean age 60 years), 88 (45%) developed AKI, 88 (45%) died, and 96 (49%) had PNO. In univariate analyses, increased urine β2M, osteopontin, and TFF3 levels sampled at admission and day three were independent risk factors for AKI, mortality, and PNO. Exceptions were that β2M measured at day three did not predict any of the outcomes, and TFF3 at admission did not predict AKI. In multivariate analyses, combining clinical parameters and biomarker levels, the area under the receiver operating characteristics curves (95% CI) were 0.729 (0.658–0.800), 0.797 (0.733–0.861), and 0.812 (CI 0.750–0.874) for AKI, mortality, and PNO, respectively. Conclusions. Urine levels of β2M, osteopontin, and TFF3 at admission and day three were associated with increased risk for AKI, mortality, and PNO in comatose OHCA patients. This trail is registered with NCT01239420

Normalized expression profiles of the (A) miR-17-92 cluster and its (B) paralogs in five precursor B cell subsets in adults (solid lines) and children (dotted lines).

<p>All 10 microRNAs followed the same expression profile in both age groups and showed a near inverse pattern with age.</p

Extensive changes in transcriptomic “fingerprints” and immunological cells in the large organs of patients dying of acute septic shock and multiple organ failure caused by Neisseria meningitidis

Background: Patients developing meningococcal septic shock reveal levels of Neisseria meningitidis (106-108/mL) and endotoxin (101-103 EU/mL) in the circulation and organs, leading to acute cardiovascular, pulmonary and renal failure, coagulopathy and a high case fatality rate within 24 h. Objective: To investigate transcriptional profiles in heart, lungs, kidneys, liver, and spleen and immunostain key inflammatory cells and proteins in post mortem formalin-fixed, paraffin-embedded (FFPE) tissue samples from meningococcal septic shock patients. Patients and Methods: Total RNA was isolated from FFPE and fresh frozen (FF) tissue samples from five patients and two controls (acute non-infectious death). Differential expression of genes was detected using Affymetrix microarray analysis. Lung and heart tissue samples were immunostained for T-and B cells, macrophages, neutrophils and the inflammatory markers PAI-1 and MCP-1. Inflammatory mediators were quantified in lysates from FF tissues. Results: The transcriptional profiles showed a complex pattern of protein-coding and non-coding RNAs with significant regulation of pathways associated with organismal death, cell death and survival, leukocyte migration, cellular movement, proliferation of cells, cell-to-cell signaling, immune cell trafficking, and inflammatory responses in an organ-specific clustering manner. The canonical pathways including acute phase response-, EIF2-, TREM1-, IL-6-, HMBG1-, PPAR signaling, and LXR/RXR activation were associated with acute heart, pulmonary, and renal failure. Fewer genes were regulated in the liver and particularly in the spleen. The main upstream regulators were TNF, IL-1β, IL-6, RICTOR, miR-6739-3p, and CD3. Increased numbers of inflammatory cells (CD68+, MPO+, CD3+, and CD20+) were found in lungs and heart. PAI-1 inhibiting fibrinolysis and MCP-1 attracting leukocyte were found significantly present in the septic tissue samples compared to the controls. Conclusions: FFPE tissue samples can be suitable for gene expression studies as well as immunostaining of specific cells or molecules. The most pronounced gene expression patterns were found in the organs with highest levels of Neisseria meningitidis DNA. Thousands of protein-coding and non-coding RNA transcripts were altered in lungs, heart and kidneys. We identified specific biomarker panels both protein-coding and non-coding RNA transcripts, which differed from organ to organ. Involvement of many genes and pathways add up and the combined effect induce organ failure

Principle component analysis (PCA) of regulated genes.

<p>The clustering represents the overall expression pattern of significantly regulated mRNAs at FDR 0.1% (p-value ≤1.13×10⁻⁴) in five subsets of precursor B cells. Color codes represent the various maturation stages as indicated under the plot. The Partek® Genomics Suite™ program draws the elipsoids encompassing the individual datapoints. Note the dots for the children (spheres) and adults (angular balls) are tightly grouped together.</p

MicroRNA profiles of precursor B cell subsets.

<p>Principle component analysis (PCA) showing the overall expression pattern of 17 microRNAs (18 assays) that were at least once differentially expressed between the various subsets (FDR 10%, p≤0,004). The color codes indicating differentiation stage (right) and age group (left) are explained below.</p

Functional analysis of 1796 differentially expressed mRNAs (FDR 0.1%, p-value≤1.13×10⁻⁴).

<p>Functional analysis of 1796 differentially expressed mRNAs (FDR 0.1%, p-value≤1.13×10⁻⁴).</p