Virulence-associated genes, resistance genes and adhesion and probiotic activity tested by a new screening method

We established an automated screening method to characterize adhesion of Escherichia coli to intestinal porcine epithelial cells (IPEC-J2) and their probiotic activity against infection by enteropathogenic E. coli (EPEC). 104 intestinal E. coli isolates from domestic pigs were tested by PCR for the occurrence of virulence-associated genes, genes coding for resistances to antimicrobial agents and metals, and for phylogenetic origin by PCR. Adhesion rates and probiotic activity were examined for correlation with the presence of these genes. Finally, data were compared with those from 93 E. coli isolates from wild boars. Isolates from domestic pigs carried a broad variety of all tested genes and showed great diversity in gene patterns. Adhesions varied with a maximum of 18.3 or 24.2 mean bacteria adherence per epithelial cell after 2 or 6 hours respectively. Most isolates from domestic pigs and wild boars showed low adherence, with no correlation between adhesion/probiotic activity and E. coli genes or gene clusters. The gene sfa/foc, encoding for a subunit of F1C fimbriae did show a positive correlative association with adherence and probiotic activity; however E. coli isolates from wild boars with the sfa/foc gene showed less adhesion and probiotic activity than E. coli with the sfa/foc gene isolated from domestic pigs after 6 hour incubation. In conclusion, screening porcine E. coli for virulence associated genes genes, adhesion to intestinal epithelial cells, and probiotic activity revealed a single important adhesion factor, several probiotic candidates, and showed important differences between E. coli of domestic pigs and wild boars

Porcine E. coli: Virulence-Associated Genes, Resistance Genes and Adhesion and Probiotic Activity Tested by a New Screening Method

We established an automated screening method to characterize adhesion of Escherichia colito intestinal porcine epithelial cells (IPEC-J2) and their probiotic activity against infection by enteropathogenic E. coli (EPEC). 104 intestinal E. coli isolates from domestic pigs were tested by PCR for the occurrence of virulence-associated genes, genes coding for resistances to antimicrobial agents and metals, and for phylogenetic origin by PCR. Adhesion rates and probiotic activity were examined for correlation with the presence of these genes. Finally, data were compared with those from 93 E. coli isolates from wild boars. Isolates from domestic pigs carried a broad variety of all tested genes and showed great diversity in gene patterns. Adhesions varied with a maximum of 18.3 or 24.2 mean bacteria adherence per epithelial cell after 2 or 6 hours respectively. Most isolates from domestic pigs and wild boars showed low adherence, with no correlation between adhesion/probiotic activity and E. coli genes or gene clusters. The gene sfa/foc, encoding for a subunit of F1C fimbriae did show a positive correlative association with adherence and probiotic activity; however E. coliisolates from wild boars with the sfa/foc gene showed less adhesion and probiotic activity thanE. coli with the sfa/foc gene isolated from domestic pigs after 6 hour incubation. In conclusion, screening porcine E. coli for virulence associated genes genes, adhesion to intestinal epithelial cells, and probiotic activity revealed a single important adhesion factor, several probiotic candidates, and showed important differences between E. coli of domestic pigs and wild boars

Microbial and Chemical Characterization of Underwater Fresh Water Springs in the Dead Sea

Due to its extreme salinity and high Mg concentration the Dead Sea is characterized by a very low density of cells most of which are Archaea. We discovered several underwater fresh to brackish water springs in the Dead Sea harboring dense microbial communities. We provide the first characterization of these communities, discuss their possible origin, hydrochemical environment, energetic resources and the putative biogeochemical pathways they are mediating. Pyrosequencing of the 16S rRNA gene and community fingerprinting methods showed that the spring community originates from the Dead Sea sediments and not from the aquifer. Furthermore, it suggested that there is a dense Archaeal community in the shoreline pore water of the lake. Sequences of bacterial sulfate reducers, nitrifiers iron oxidizers and iron reducers were identified as well. Analysis of white and green biofilms suggested that sulfide oxidation through chemolitotrophy and phototrophy is highly significant. Hyperspectral analysis showed a tight association between abundant green sulfur bacteria and cyanobacteria in the green biofilms. Together, our findings show that the Dead Sea floor harbors diverse microbial communities, part of which is not known from other hypersaline environments. Analysis of the water’s chemistry shows evidence of microbial activity along the path and suggests that the springs supply nitrogen, phosphorus and organic matter to the microbial communities in the Dead Sea. The underwater springs are a newly recognized water source for the Dead Sea. Their input of microorganisms and nutrients needs to be considered in the assessment of possible impact of dilution events of the lake surface waters, such as those that will occur in the future due to the intended establishment of the Red Sea−Dead Sea water conduit

The ScaleX campaign: scale-crossing land-surface and boundary layer processes in the TERENO-preAlpine observatory

Augmenting long-term ecosystem-atmosphere observations with multidisciplinary intensive campaigns aims at closing gaps in spatial and temporal scales of observation for energy- and biogeochemical cycling, and at stimulating collaborative research. ScaleX is a collaborative measurement campaign, co-located with a long-term environmental observatory of the German TERENO (TERrestrial ENvironmental Observatories) network in mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land-surface atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated on a small number of locations

Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model

Summary Background Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal–external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9–168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63–1·79), age at onset (1·03, 1·03–1·03), definite versus probable or possible ALS (1·47, 1·39–1·55), diagnostic delay (0·52, 0·51–0·53), forced vital capacity (HR 0·99, 0·99–0·99), progression rate (6·33, 5·92–6·76), frontotemporal dementia (1·34, 1·20–1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31–1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77–0·80; 95% prediction interval [PI] 0·74–0·82) and the calibration slope was 1·01 (95% CI 0·95–1·07; 95% PI 0·83–1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding Netherlands ALS Foundation