Biological Characterization of Gene Response to Insulin-Induced Hypoglycemia in Mouse Retina.

Glucose is the most important metabolic substrate of the retina and maintenance of normoglycemia is an essential challenge for diabetic patients. Chronic, exaggerated, glycemic excursions could lead to cardiovascular diseases, nephropathy, neuropathy and retinopathy. We recently showed that hypoglycemia induced retinal cell death in mouse via caspase 3 activation and glutathione (GSH) decrease. Ex vivo experiments in 661W photoreceptor cells confirmed the low-glucose induction of death via superoxide production and activation of caspase 3, which was concomitant with a decrease of GSH content. We evaluate herein retinal gene expression 4 h and 48 h after insulin-induced hypoglycemia. Microarray analysis demonstrated clusters of genes whose expression was modified by hypoglycemia and we discuss the potential implication of those genes in retinal cell death. In addition, we identify by gene set enrichment analysis, three important pathways, including lysosomal function, GSH metabolism and apoptotic pathways. Then we tested the effect of recurrent hypoglycemia (three successive 4h periods of hypoglycemia spaced by 48 h recovery) on retinal cell death. Interestingly, exposure to multiple hypoglycemic events prevented GSH decrease and retinal cell death, or adapted the retina to external stress by restoring GSH level comparable to control situation. We hypothesize that scavenger GSH is a key compound in this apoptotic process, and maintaining "normal" GSH level, as well as a strict glycemic control, represents a therapeutic challenge in order to avoid side effects of diabetes, especially diabetic retinopathy

Polymorphism in cyclohexanol

The crystal structures and phase behaviour of phase II and the metastable phases III0 and III of cyclohexanol, C6H11OH, have been determined using high-resolution neutron powder, synchrotron X-ray powder and single-crystal X-ray diffraction techniques. Cyclohexanol-II is formed by a transition from the plastic phase I cubic structure at 265 K and crystallizes in a tetragonal structure, space group P�4421c (Z0 = 1), in which the molecules are arranged in a hydrogen-bonded tetrameric ring motif. The structures of phases III0 and III are monoclinic, space groups P21/c (Z0 = 3) and Pc (Z0 = 2), respectively, and are characterized by the formation of hydrogen-bonded molecular chains with a threefold-helical and wave-like nature, respectively. Phase III crystallizes at 195 K from a sample of phase I that is supercooled to ca 100 K. Alternatively, phase III may be grown via phase III0, the latter transforming from supercooled phase I at ca 200 K. Phase III0 is particularly unstable and is metastable with respect to both I and II. Its growth is realised only under very restricted conditions, thus making its characterization especially challenging. The cyclohexanol molecules adopt a chair conformation in all three phases with the hydroxyl groups in an equatorial orientation. No evidence was found indicating hydroxyl groups adopting an axial orientation, contrary to the majority of spectroscopic literature on solid-state cyclohexanol; however, the H atom of the equatorial OH groups is found to adopt both in-plane and out-of-plane orientations

Large Anisotropic Thermal Expansion Anomaly near the Superconducting Transition Temperature in MgB2

An anisotropic lattice anomaly near the superconducting transition temperature, Tc, was observed in MgB2 by high-resolution neutron powder diffraction. The a-axis thermal expansion becomes negative near Tc, while the c-axis thermal expansion is unaffected. This is qualitatively consistent with a depletion of the boron-boron s-band as the superconducting gap opens, resulting in weaker bonding. However, the observed anomaly is much larger than predicted by the Ehrenfest relation, strongly suggesting that the phonon thermal expansion also changes sign, as commonly observed in hexagonal layered crystals. These two effects may be connected through subtle changes in the phonon spectrum at Tc.Comment: 11 pages, 4 figure

\u3ci\u3eStaphylococcus aureus\u3c/i\u3e Hyaluronidase Is a CodY-Regulated Virulence Factor

Staphylococcus aureus is a Gram-positive pathogen that causes a diverse range of bacterial infections. Invasive S. aureus strains secrete an extensive arsenal of hemolysins, immunomodulators, and exoenzymes to cause disease. Our studies have focused on the secreted enzyme hyaluronidase (HysA), which cleaves the hyaluronic acid polymer at the β-1,4 glycosidic bond. In the study described in this report, we have investigated the regulation and contribution of this enzyme to S. aureus pathogenesis. Using the Nebraska Transposon Mutant Library (NTML), we identified eight insertions that modulate extracellular levels of HysA activity. Insertions in the sigB operon, as well as in genes encoding the global regulators SarA and CodY, significantly increased HysA protein levels and activity. By altering the availability of branched-chain amino acids, we further demonstrated CodY-dependent repression of HysA activity. Additionally, through mutation of the CodY binding box upstream of hysA, the repression of HysA production was lost, suggesting that CodY is a direct repressor of hysA expression. To determine whether HysA is a virulence factor, a ΔhysA mutant of a community-associated methicillin-resistant S. aureus (CA-MRSA) USA300 strain was constructed and found to be attenuated in a neutropenic, murine model of pulmonary infection. Mice infected with this mutant strain exhibited a 4-log-unit reduction in bacterial burden in their lungs, as well as reduced lung pathology and increased levels of pulmonary hyaluronic acid, compared to mice infected with the wild-type, parent strain. Taken together, these results indicate that S. aureus hyaluronidase is a CodY-regulated virulence factor

Magnetic stress as a driving force of structural distortions: the case of CrN

We show that the observed transition from rocksalt to orthorhombic P$_{nma}$ symmetry in CrN can be understood in terms of stress anisotropy. Using local spin density functional theory, we find that the imbalance between stress stored in spin-paired and spin-unpaired Cr nearest neighbors causes the rocksalt structure to be unstable against distortions and justifies the observed antiferromagnetic ordering. This stress has a purely magnetic origin, and may be important in any system where the coupling between spin ordering and structure is strong.Comment: 4 pages (two columns) 4 figure

Identification of Extracellular DNA-Binding Proteins in the Biofilm Matrix.

We developed a new approach that couples Southwestern blotting and mass spectrometry to discover proteins that bind extracellular DNA (eDNA) in bacterial biofilms. Using Staphylococcus aureus as a model pathogen, we identified proteins with known DNA-binding activity and uncovered a series of lipoproteins with previously unrecognized DNA-binding activity. We demonstrated that expression of these lipoproteins results in an eDNA-dependent biofilm enhancement. Additionally, we found that while deletion of lipoproteins had a minimal impact on biofilm accumulation, these lipoprotein mutations increased biofilm porosity, suggesting that lipoproteins and their associated interactions contribute to biofilm structure. For one of the lipoproteins, SaeP, we showed that the biofilm phenotype requires the lipoprotein to be anchored to the outside of the cellular membrane, and we further showed that increased SaeP expression correlates with more retention of high-molecular-weight DNA on the bacterial cell surface. SaeP is a known auxiliary protein of the SaeRS system, and we also demonstrated that the levels of SaeP correlate with nuclease production, which can further impact biofilm development. It has been reported that S. aureus biofilms are stabilized by positively charged cytoplasmic proteins that are released into the extracellular environment, where they make favorable electrostatic interactions with the negatively charged cell surface and eDNA. In this work we extend this electrostatic net model to include secreted eDNA-binding proteins and membrane-attached lipoproteins that can function as anchor points between eDNA in the biofilm matrix and the bacterial cell surface.IMPORTANCE Many bacteria are capable of forming biofilms encased in a matrix of self-produced extracellular polymeric substances (EPS) that protects them from chemotherapies and the host defenses. As a result of these inherent resistance mechanisms, bacterial biofilms are extremely difficult to eradicate and are associated with chronic wounds, orthopedic and surgical wound infections, and invasive infections, such as infective endocarditis and osteomyelitis. It is therefore important to understand the nature of the interactions between the bacterial cell surface and EPS that stabilize biofilms. Extracellular DNA (eDNA) has been recognized as an EPS constituent for many bacterial species and has been shown to be important in promoting biofilm formation. Using Staphylococcus aureus biofilms, we show that membrane-attached lipoproteins can interact with the eDNA in the biofilm matrix and promote biofilm formation, which suggests that lipoproteins are potential targets for novel therapies aimed at disrupting bacterial biofilms

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish.

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration

A transcribed enhancer dictates mesendoderm specification in pluripotency.

Enhancers and long noncoding RNAs (lncRNAs) are key determinants of lineage specification during development. Here, we evaluate remodeling of the enhancer landscape and modulation of the lncRNA transcriptome during mesendoderm specification. We sort mesendodermal progenitors from differentiating embryonic stem cells (ESCs) according to Eomes expression, and find that enhancer usage is coordinated with mesendoderm-specific expression of key lineage-determining transcription factors. Many of these enhancers are associated with the expression of lncRNAs. Examination of ESC-specific enhancers interacting in three-dimensional space with mesendoderm-specifying transcription factor loci identifies MesEndoderm Transcriptional Enhancer Organizing Region (Meteor). Genetic and epigenetic manipulation of the Meteor enhancer reveal its indispensable role during mesendoderm specification and subsequent cardiogenic differentiation via transcription-independent and -dependent mechanisms. Interestingly, Meteor-deleted ESCs are epigenetically redirected towards neuroectodermal lineages. Loci, topologically associating a transcribed enhancer and its cognate protein coding gene, appear to represent therefore a class of genomic elements controlling developmental competence in pluripotency

Competition between Magnetic and Structural Transition in CrN

CrN is observed to undergo a paramagnetic to antiferromagnetic transition accompanied by a shear distortion from cubic NaCl-type to orthorhombic structure. Our first-principle plane wave and ultrasoft pseudopotential calculations confirm that the distorted antiferromagnetic phase with spin configuration arranged in double ferromagnetic sheets along [110] is the most stable. Antiferromagnetic ordering leads to a large depletion of states around Fermi level, but it does not open a gap. Simultaneous occurence of structural distortion and antiferromagnetic order is analyzed.Comment: 10 pages, 10 figure

An omics-based machine learning approach to predict diabetes progression:a RHAPSODY study

Aims/hypothesis: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA 1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. Methods: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA 1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel’s C statistic. Results: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0–11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3–11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA 1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA 1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. Conclusions/interpretation: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. Data availability: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch. Graphical Abstract: (Figure presented.).</p