Intracellular Uropathogenic E. coli Exploits Host Rab35 for Iron Acquisition and Survival within Urinary Bladder Cells

Recurrent urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC) are common and morbid infections with limited therapeutic options. Previous studies have demonstrated that persistent intracellular infection of bladder epithelial cells (BEC) by UPEC contributes to recurrent UTI in mouse models of infection. However, the mechanisms employed by UPEC to survive within BEC are incompletely understood. In this study we aimed to understand the role of host vesicular trafficking proteins in the intracellular survival of UPEC. Using a cell culture model of intracellular UPEC infection, we found that the small GTPase Rab35 facilitates UPEC survival in UPEC-containing vacuoles (UCV) within BEC. Rab35 plays a role in endosomal recycling of transferrin receptor (TfR), the key protein responsible for transferrin–mediated cellular iron uptake. UPEC enhance the expression of both Rab35 and TfR and recruit these proteins to the UCV, thereby supplying UPEC with the essential nutrient iron. Accordingly, Rab35 or TfR depleted cells showed significantly lower intracellular iron levels and reduced ability to support UPEC survival. In the absence of Rab35, UPEC are preferentially trafficked to degradative lysosomes and killed. Furthermore, in an in vivo murine model of persistent intracellular infection, Rab35 also colocalizes with intracellular UPEC. We propose a model in which UPEC subverts two different vesicular trafficking pathways (endosomal recycling and degradative lysosomal fusion) by modulating Rab35, thereby simultaneously enhancing iron acquisition and avoiding lysosomal degradation of the UCV within bladder epithelial cells. Our findings reveal a novel survival mechanism of intracellular UPEC and suggest a potential avenue for therapeutic intervention against recurrent UTI

Role of PheE15 gate in ligand entry and nitric oxide detoxification function of Mycobacterium tuberculosis truncated hemoglobin N

The truncated hemoglobin N, HbN, of Mycobacterium tuberculosis is endowed with a potent nitric oxide dioxygenase (NOD) activity that allows it to relieve nitrosative stress and enhance in vivo survival of its host. Despite its small size, the protein matrix of HbN hosts a two-branched tunnel, consisting of orthogonal short and long channels, that connects the heme active site to the protein surface. A novel dual-path mechanism has been suggested to drive migration of O(2) and NO to the distal heme cavity. While oxygen migrates mainly by the short path, a ligand-induced conformational change regulates opening of the long tunnel branch for NO, via a phenylalanine (PheE15) residue that acts as a gate. Site-directed mutagenesis and molecular simulations have been used to examine the gating role played by PheE15 in modulating the NOD function of HbN. Mutants carrying replacement of PheE15 with alanine, isoleucine, tyrosine and tryptophan have similar O(2)/CO association kinetics, but display significant reduction in their NOD function. Molecular simulations substantiated that mutation at the PheE15 gate confers significant changes in the long tunnel, and therefore may affect the migration of ligands. These results support the pivotal role of PheE15 gate in modulating the diffusion of NO via the long tunnel branch in the oxygenated protein, and hence the NOD function of HbN

Intracellular Uropathogenic E. coli Exploits Host Rab35 for Iron Acquisition and Survival within Urinary Bladder Cells

Recurrent urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC) are common and morbid infections with limited therapeutic options. Previous studies have demonstrated that persistent intracellular infection of bladder epithelial cells (BEC) by UPEC contributes to recurrent UTI in mouse models of infection. However, the mechanisms employed by UPEC to survive within BEC are incompletely understood. In this study we aimed to understand the role of host vesicular trafficking proteins in the intracellular survival of UPEC. Using a cell culture model of intracellular UPEC infection, we found that the small GTPase Rab35 facilitates UPEC survival in UPEC-containing vacuoles (UCV) within BEC. Rab35 plays a role in endosomal recycling of transferrin receptor (TfR), the key protein responsible for transferrin–mediated cellular iron uptake. UPEC enhance the expression of both Rab35 and TfR and recruit these proteins to the UCV, thereby supplying UPEC with the essential nutrient iron. Accordingly, Rab35 or TfR depleted cells showed significantly lower intracellular iron levels and reduced ability to support UPEC survival. In the absence of Rab35, UPEC are preferentially trafficked to degradative lysosomes and killed. Furthermore, in an in vivo murine model of persistent intracellular infection, Rab35 also colocalizes with intracellular UPEC. We propose a model in which UPEC subverts two different vesicular trafficking pathways (endosomal recycling and degradative lysosomal fusion) by modulating Rab35, thereby simultaneously enhancing iron acquisition and avoiding lysosomal degradation of the UCV within bladder epithelial cells. Our findings reveal a novel survival mechanism of intracellular UPEC and suggest a potential avenue for therapeutic intervention against recurrent UTI

A two-year participatory intervention project with owners to reduce lameness and limb abnormalities in working horses in Jaipur, India

Participatory methods are increasingly used in international human development, but scientific evaluation of their efficacy versus a control group is rare. Working horses support families in impoverished communities. Lameness and limb abnormalities are highly prevalent in these animals and a cause for welfare concern. We aimed to stimulate and evaluate improvements in lameness and limb abnormalities in horses whose owners took part in a 2-year participatory intervention project to reduce lameness (PI) versus a control group (C) in Jaipur, India.In total, 439 owners of 862 horses participated in the study. PI group owners from 21 communities were encouraged to meet regularly to discuss management and work practices influencing lameness and poor welfare and to track their own progress in improving these. Lameness examinations (41 parameters) were conducted at the start of the study (Baseline), and after 1 year and 2 years. Results were compared with control horses from a further 21 communities outside the intervention. Of the 149 horses assessed on all three occasions, PI horses showed significantly (P<0.05) greater improvement than C horses in 20 parameters, most notably overall lameness score, measures of sole pain and range of movement on limb flexion. Control horses showed slight but significantly greater improvements in four parameters, including frog quality in fore and hindlimbs.This participatory intervention succeeded in improving lameness and some limb abnormalities in working horses, by encouraging changes in management and work practices which were feasible within owners’ socioeconomic and environmental constraints. Demonstration of the potentially sustainable improvements achieved here should encourage further development of participatory intervention approaches to benefit humans and animals in other contexts

Long lead time drought forecasting using lagged climate variables and a stacked long short-term memory model.

Drought forecasting with a long lead time is essential for early warning systems and risk management strategies. The use of machine learning algorithms has been proven to be beneficial in forecasting droughts. However, forecasting at long lead times remains a challenge due to the effects of climate change and the complexities involved in drought assessment. The rise of deep learning techniques can solve this issue, and the present work aims to use a stacked long short-term memory (LSTM) architecture to forecast a commonly used drought measure, namely, the Standard Precipitation Evaporation Index. The model was then applied to the New South Wales region of Australia, with hydrometeorological and climatic variables as predictors. The multivariate interpolated grid of the Climatic Research Unit was used to compute the index at monthly scales, with meteorological variables as predictors. The architecture was trained using data from the period of 1901-2000 and tested on data from the period of 2001-2018. The results were then forecasted at lead times ranging from 1 month to 12 months. The forecasted results were analysed in terms of drought characteristics, such as drought intensity, drought onset, spatial extent and number of drought months, to elucidate how these characteristics improve the understanding of drought forecasting. The drought intensity forecasting capability of the model used two statistical metrics, namely, the coefficient of determination (R2) and root-mean-square error. The variation in the number of drought months was examined using the threat score technique. The results of this study showed that the stacked LSTM model can forecast effectively at short-term and long-term lead times. Such findings will be essential for government agencies and can be further tested to understand the forecasting capability of the presented architecture at shorter temporal scales, which can range from days to weeks

Determination of rainfall thresholds for landslide prediction using an algorithm-based approach: Case study in the Darjeeling Himalayas, India

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Landslides are one of the most devastating and commonly recurring natural hazards in the Indian Himalayas. They contribute to infrastructure damage, land loss and human casualties. Most of the landslides are primarily rainfall-induced and the relationship has been well very well-established, having been commonly defined using empirical-based models which use statistical approaches to determine the parameters of a power-law equation. One of the main drawbacks using the traditional empirical methods is that it fails to reduce the uncertainties associated with threshold calculation. The present study overcomes these limitations by identifying the precipitation condition responsible for landslide occurrence using an algorithm-based model. The methodology involves the use of an automated tool which determines cumulated event rainfall–rainfall duration thresholds at various exceedance probabilities and the associated uncertainties. The analysis has been carried out for the Kalimpong Region of the Darjeeling Himalayas using rainfall and landslide data for the period 2010–2016. The results signify that a rainfall event of 48 h with a cumulated event rainfall of 36.7 mm can cause landslides in the study area. Such a study is the first to be conducted for the Indian Himalayas and can be considered as a first step in determining more reliable thresholds which can be used as part of an operational early-warning system

The role of the subtropical jet in deficient winter precipitation across the mid-Holocene Indus basin

The mid-Holocene (7-5 ka) was a period with an increased seasonal insolation cycle, resulting from decreased insolation during northern hemisphere winter. Here, a set of six CMIP5 models is used to show that the decreased insolation reduced the upper-tropospheric meridional temperature gradient, producing a weaker subtropical jet with less horizontal shear. These effects work to reduce the baroclinic and barotropic instability available for perturbations to grow, and in consequence, storm-tracking results show that there are fewer winter storms over India and Pakistan (known as western disturbances). These western disturbances are weaker, resulting in a reduction in winter precipitation of around 15% in the north Indus Basin. Combined with previous work showing greater northwestward extent of the Indian monsoon during the mid-Holocene, our GCM-derived results are consistent with the Indus Basin changing from a summer-growing season in the mid-Holocene to a winter-growing season in the present day

Frequency and temperature-dependence ZnO based fractional order capacitor using machine learning

This paper investigates the fractional order behavior of ZnO ceramics at different frequencies. ZnO ceramic was prepared by high energy ball milling technique (HEBM) sintered at 1300℃ to study the frequency response properties. The frequency response properties (impedance and phase angles) were examined by analyzing through impedance analyzer (100 Hz - 1 MHz). Constant phase angles (84°-88°) were obtained at low temperature ranges (25 ℃-125 ℃). The structural and morphological composition of the ZnO ceramic was investigated using X-ray diffraction techniques and FESEM. Raman spectrum was studied to understand the different modes of ZnO ceramics. Machine learning (polynomial regression) models were trained on a dataset of 1280 experimental values to accurately predict the relationship between frequency and temperature with respect to impedance and phase values of the ZnO ceramic FOC. The predicted impedance values were found to be in good agreement (R2 ~ 0.98, MSE ~ 0.0711) with the experimental results. Impedance values were also predicted beyond the experimental frequency range (at 50 Hz and 2 MHz) for different temperatures (25℃ - 500℃) and for low temperatures (10°, 15° and 20℃) within the frequency range (100Hz - 1MHz)