Targeted disruption of the extracellular polymeric network of Pseudomonas aeruginosa biofilms by alginate oligosaccharides.

Acquisition of a mucoid phenotype by Pseudomonas sp. in the lungs of cystic fibrosis (CF) patients, with subsequent over-production of extracellular polymeric substance (EPS), plays an important role in mediating the persistence of multi-drug resistant (MDR) infections. The ability of a low molecular weight (Mn = 3200 g mol-1) alginate oligomer (OligoG CF-5/20) to modify biofilm structure of mucoid Pseudomonas aeruginosa (NH57388A) was studied in vitro using scanning electron microscopy (SEM), confocal laser scanning microscopy (CLSM) with Texas Red (TxRd®)-labelled OligoG and EPS histochemical staining. Structural changes in treated biofilms were quantified using COMSTAT image-analysis software of CLSM z-stack images, and nanoparticle diffusion. Interactions between the oligomers, Ca2+ and DNA were studied using molecular dynamics (MD) simulations, Fourier transform infrared spectroscopy (FTIR) and isothermal titration calorimetry (ITC). Imaging demonstrated that OligoG treatment (≥0.5%) inhibited biofilm formation, revealing a significant reduction in both biomass and biofilm height (P < 0.05). TxRd®-labelled oligomers readily diffused into established (24 h) biofilms. OligoG treatment (≥2%) induced alterations in the EPS of established biofilms; significantly reducing the structural quantities of EPS polysaccharides, and extracellular (e)DNA (P < 0.05) with a corresponding increase in nanoparticle diffusion (P < 0.05) and antibiotic efficacy against established biofilms. ITC demonstrated an absence of rapid complex formation between DNA and OligoG and confirmed the interactions of OligoG with Ca2+ evident in FTIR and MD modelling. The ability of OligoG to diffuse into biofilms, potentiate antibiotic activity, disrupt DNA-Ca2+-DNA bridges and biofilm EPS matrix highlights its potential for the treatment of biofilm-related infections.

Alginate oligosaccharides inhibit fungal cell growth and potentiate the activity of antifungals against Candida and Aspergillus spp.

The oligosaccharide OligoG, an alginate derived from seaweed, has been shown to have anti-bacterial and anti-biofilm properties and potentiates the activity of selected antibiotics against multi-drug resistant bacteria. The ability of OligoG to perturb fungal growth and potentiate conventional antifungal agents was evaluated using a range of pathogenic fungal strains. Candida (n = 11) and Aspergillus (n = 3) spp. were tested using germ tube assays, LIVE/DEAD staining, scanning electron microscopy (SEM), atomic force microscopy (AFM) and high-throughput minimum inhibition concentration assays (MICs). In general, the strains tested showed a significant dose-dependent reduction in cell growth at ≥6% OligoG as measured by optical density (OD600; P<0.05). OligoG (>0.5%) also showed a significant inhibitory effect on hyphal growth in germ tube assays, although strain-dependent variations in efficacy were observed (P<0.05). SEM and AFM both showed that OligoG (≥2%) markedly disrupted fungal biofilm formation, both alone, and in combination with fluconazole. Cell surface roughness was also significantly increased by the combination treatment (P<0.001). High-throughput robotic MIC screening demonstrated the potentiating effects of OligoG (2, 6, 10%) with nystatin, amphotericin B, fluconazole, miconazole, voriconazole or terbinafine with the test strains. Potentiating effects were observed for the Aspergillus strains with all six antifungal agents, with an up to 16-fold (nystatin) reduction in MIC. Similarly, all the Candida spp. showed potentiation with nystatin (up to 16-fold) and fluconazole (up to 8-fold). These findings demonstrate the antifungal properties of OligoG and suggest a potential role in the management of fungal infections and possible reduction of antifungal toxicity.

A gene expression pattern in blood for the early detection of Alzheimer's disease.

A whole genome screen was performed using oligonucleotide microarray analysis on blood from a large clinical cohort of Alzheimer's disease (AD) patients and control subjects as clinical sample. Blood samples for total RNA extraction were collected in PAXgene tubes, and gene expression analysis performed on the AB1700 Whole Genome Survey Microarrays. When comparing the gene expression of 94 AD patients and 94 cognitive healthy controls, a Jackknife gene selection based method and Partial Least Square Regression (PLSR) was used to develop a disease classifier algorithm, which gives a test score indicating the presence (positive) or absence (negative) of AD. This algorithm, based on 1239 probes, was validated in an independent test set of 63 subjects comprising 31 AD patients, 25 age-matched cognitively healthy controls, and 7 young controls. This algorithm correctly predicted the class of 55/63 (accuracy 87%), including 26/31 AD samples (sensitivity 84%) and 29/32 controls (specificity 91%). The positive likelihood ratio was 8.9 and the area under the receiver operating characteristic curve (ROC AUC) was 0.94. Furthermore, the algorithm also discriminated AD from Parkinson's disease in 24/27 patients (accuracy 89%). We have identified and validated a gene expression signature in blood that classifies AD patients and cognitively healthy controls with high accuracy and show that alterations specific for AD can be detected distant from the primary site of the disease.

A novel blood test for the early detection of Alzheimer's disease.

Despite a variety of testing approaches, it is often difficult to make an accurate diagnosis of Alzheimer's disease (AD), especially at an early stage of the disease. Diagnosis is based on clinical criteria as well as exclusion of other causes of dementia but a definitive diagnosis can only be made at autopsy. We have investigated the diagnostic value of a 96-gene expression array for detection of early AD. Gene expression analysis was performed on blood RNA from a cohort of 203 probable AD and 209 cognitively healthy age matched controls. A disease classification algorithm was developed on samples from 208 individuals (AD = 103; controls = 105) and was validated in two steps using an independent initial test set (n = 74; AD = 32; controls = 42) and another second test set (n = 130; AD = 68; controls = 62). In the initial analysis, diagnostic accuracy was 71.6 ± 10.3%, with sensitivity 71.9 ± 15.6% and specificity 71.4 ± 13.7%. Essentially the same level of agreement was achieved in the two independent test sets. High agreement (24/30; 80%) between algorithm prediction and subjects with available cerebrospinal fluid biomarker was found. Assuming a clinical accuracy of 80%, calculations indicate that the agreement with underlying true pathology is in the range 85%-90%. These findings suggest that the gene expression blood test can aid in the diagnosis of mild to moderate AD, but further studies are needed to confirm these findings.

Up close and personal: molecular diagnostics in oncology.

The almost overwhelming volume of information and new technological developments that has demanded so much of our scientific attention over the last decade will shortly revolutionize clinical diagnostics. Some of these developments are already affecting the working lives of scientists and clinicians alike, but will eventually require a greater understanding and acceptance from a much wider audience. Therefore it is important in our current scientific endeavor and commercial enthusiasm for molecular diagnostics that we maintain some awareness of the significant obstacles that must be overcome if we are to see an appropriate, timely and widespread adoption of molecular diagnostic testing in oncology. This article presents a brief commentary on the current state of the art in molecular diagnostics in oncology and how this relates to a more personalized approach to treatment.

Polyglycine II nanosheets: supramolecular antivirals?

Tetraantennary peptides [glycine(n)-NHCH(2)](4)C can form stable noncovalent structures by self-assembly through intermolecular hydrogen bonding. The oligopeptide chains assemble as polyglycine II to yield submicron-sized, flat, one-molecule-thick sheets. Attachment of alpha-N-acetylneuraminic acid (Neu5Acalpha) to the terminal glycine residues gives rise to water-soluble assembled glycopeptides that are able to bind influenza virus multivalently and inhibit adhesion of the virus to cells 10(3)-fold more effectively than a monomeric glycoside of Neu5Acalpha. Another antiviral strategy based on virus-promoted assembly of the glycopeptides was also demonstrated. Consequently, the self-assembly principle offers new perspectives on the design of multivalent antivirals.