Surface Percolation for Soil Improvement by Biocementation Utilizing In Situ Enriched Indigenous Aerobic and Anaerobic Ureolytic Soil Microorganisms

The use of biocementation via microbially induced carbonate precipitation (MICP) for improving the mechanical properties of weak soils in the laboratory has gained increased attention in recent years. This study proposes an approach for applying biocementation in situ, by combining the surface percolation of nutrients and cementation solution (urea/CaCl2) with in situ cultivation of indigenous soil urease positive microorganisms under non-sterile conditions. The enrichment of indigenous ureolytic soil bacteria was firstly tested in batch reactors. Using selective conditions (i.e., pH of 10 and urea concentrations of 0.17 M), highly active ureolytic microorganisms were enriched from four diverse soil samples under both oxygen-limited (anoxic) and oxygen-free (strictly anaerobic) conditions, providing final urease activities of more than 10 and 5 U/mL, respectively. The enrichment of indigenous ureolytic soil microorganisms was secondly tested in pure silica sand columns (300 and 1000 mm) for biocementation applications using the surface percolation approach. By applying the same selective conditions, the indigenous ureolytic soil microorganisms with high urease activity were also successfully enriched for both the fine and coarse sand columns. However, the in situ enriched urease activity was highly related to the dissolved oxygen of the percolated growth medium. The results showed that the in situ cultivated urease activity may produce non-clogging cementation over the entire 1000-mm columns, with unconfined compressive strength varying between 850–1560 kPa (for coarse sand) and 150–700 kPa (for fine sand), after 10 subsequent applications of cementation solution. The typically observed loss of ureolytic activity during the repeated application of the cementation solution was recovered by providing more growth medium under selective enrichment conditions, enabling the in situ enriched ureolytic microorganisms to increase in numbers and urease activity in such a way that continued cementation was possible

Prediction of Ligand Binding Using an Approach Designed to Accommodate Diversity in Protein-Ligand Interactions

Computational determination of protein-ligand interaction potential is important for many biological applications including virtual screening for therapeutic drugs. The novel internal consensus scoring strategy is an empirical approach with an extended set of 9 binding terms combined with a neural network capable of analysis of diverse complexes. Like conventional consensus methods, internal consensus is capable of maintaining multiple distinct representations of protein-ligand interactions. In a typical use the method was trained using ligand classification data (binding/no binding) for a single receptor. The internal consensus analyses successfully distinguished protein-ligand complexes from decoys (r2, 0.895 for a series of typical proteins). Results are superior to other tested empirical methods. In virtual screening experiments, internal consensus analyses provide consistent enrichment as determined by ROC-AUC and pROC metrics

Fitness of Escherichia coli during Urinary Tract Infection Requires Gluconeogenesis and the TCA Cycle

Microbial pathogenesis studies traditionally encompass dissection of virulence properties such as the bacterium's ability to elaborate toxins, adhere to and invade host cells, cause tissue damage, or otherwise disrupt normal host immune and cellular functions. In contrast, bacterial metabolism during infection has only been recently appreciated to contribute to persistence as much as their virulence properties. In this study, we used comparative proteomics to investigate the expression of uropathogenic Escherichia coli (UPEC) cytoplasmic proteins during growth in the urinary tract environment and systematic disruption of central metabolic pathways to better understand bacterial metabolism during infection. Using two-dimensional fluorescence difference in gel electrophoresis (2D-DIGE) and tandem mass spectrometry, it was found that UPEC differentially expresses 84 cytoplasmic proteins between growth in LB medium and growth in human urine (P<0.005). Proteins induced during growth in urine included those involved in the import of short peptides and enzymes required for the transport and catabolism of sialic acid, gluconate, and the pentose sugars xylose and arabinose. Proteins required for the biosynthesis of arginine and serine along with the enzyme agmatinase that is used to produce the polyamine putrescine were also up-regulated in urine. To complement these data, we constructed mutants in these genes and created mutants defective in each central metabolic pathway and tested the relative fitness of these UPEC mutants in vivo in an infection model. Import of peptides, gluconeogenesis, and the tricarboxylic acid cycle are required for E. coli fitness during urinary tract infection while glycolysis, both the non-oxidative and oxidative branches of the pentose phosphate pathway, and the Entner-Doudoroff pathway were dispensable in vivo. These findings suggest that peptides and amino acids are the primary carbon source for E. coli during infection of the urinary tract. Because anaplerosis, or using central pathways to replenish metabolic intermediates, is required for UPEC fitness in vivo, we propose that central metabolic pathways of bacteria could be considered critical components of virulence for pathogenic microbes

Extreme Evolutionary Disparities Seen in Positive Selection across Seven Complex Diseases

Positive selection is known to occur when the environment that an organism inhabits is suddenly altered, as is the case across recent human history. Genome-wide association studies (GWASs) have successfully illuminated disease-associated variation. However, whether human evolution is heading towards or away from disease susceptibility in general remains an open question. The genetic-basis of common complex disease may partially be caused by positive selection events, which simultaneously increased fitness and susceptibility to disease. We analyze seven diseases studied by the Wellcome Trust Case Control Consortium to compare evidence for selection at every locus associated with disease. We take a large set of the most strongly associated SNPs in each GWA study in order to capture more hidden associations at the cost of introducing false positives into our analysis. We then search for signs of positive selection in this inclusive set of SNPs. There are striking differences between the seven studied diseases. We find alleles increasing susceptibility to Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA), and Crohn's Disease (CD) underwent recent positive selection. There is more selection in alleles increasing, rather than decreasing, susceptibility to T1D. In the 80 SNPs most associated with T1D (p-value <7.01×10−5) showing strong signs of positive selection, 58 alleles associated with disease susceptibility show signs of positive selection, while only 22 associated with disease protection show signs of positive selection. Alleles increasing susceptibility to RA are under selection as well. In contrast, selection in SNPs associated with CD favors protective alleles. These results inform the current understanding of disease etiology, shed light on potential benefits associated with the genetic-basis of disease, and aid in the efforts to identify causal genetic factors underlying complex disease

Validation of a multifactorial risk factor model used for predicting future caries risk with nevada adolescents

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting.</p> <p>Methods</p> <p>This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model.</p> <p>Results</p> <p>Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%.</p> <p>Conclusions</p> <p>Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.</p

The Free Energy Landscape of Small Molecule Unbinding

The spontaneous dissociation of six small ligands from the active site of FKBP (the FK506 binding protein) is investigated by explicit water molecular dynamics simulations and network analysis. The ligands have between four (dimethylsulphoxide) and eleven (5-diethylamino-2-pentanone) non-hydrogen atoms, and an affinity for FKBP ranging from 20 to 0.2 mM. The conformations of the FKBP/ligand complex saved along multiple trajectories (50 runs at 310 K for each ligand) are grouped according to a set of intermolecular distances into nodes of a network, and the direct transitions between them are the links. The network analysis reveals that the bound state consists of several subbasins, i.e., binding modes characterized by distinct intermolecular hydrogen bonds and hydrophobic contacts. The dissociation kinetics show a simple (i.e., single-exponential) time dependence because the unbinding barrier is much higher than the barriers between subbasins in the bound state. The unbinding transition state is made up of heterogeneous positions and orientations of the ligand in the FKBP active site, which correspond to multiple pathways of dissociation. For the six small ligands of FKBP, the weaker the binding affinity the closer to the bound state (along the intermolecular distance) are the transition state structures, which is a new manifestation of Hammond behavior. Experimental approaches to the study of fragment binding to proteins have limitations in temporal and spatial resolution. Our network analysis of the unbinding simulations of small inhibitors from an enzyme paints a clear picture of the free energy landscape (both thermodynamics and kinetics) of ligand unbinding

The prognostic and predictive power of redox rotein expression for anthracycline-based chemotherapy response in locally advanced breast cancer

Neoadjuvant chemotherapy has become the standard of care for locally advanced primary breast cancer. Anthracycline-based regimens have proven to be one of the most effective treatments in this setting. As certain cytotoxic antineoplastic agents, such as anthracyclines, generate reactive oxygen species as a by-product of their mechanism of action, we examined whether redox protein expression was involved in the response to anthracycline-based chemotherapy and with clinical outcome. Pre treatment needle core biopsy and postanthracycline treatment tumour sections were analysed from 98 cases. In all, 32 individuals had a complete clinical response and 17 had a complete pathological response. Immunohistochemical staining was performed for eight redox proteins: thioredoxin, thioredoxin reductase thioredoxin interacting protein (TxNIP), glutathione S-transferase (GST) p, h and a, catalase and manganese superoxide dismutase. GST p (P¼0.05) and catalase (P¼0.045) were associated with pathological complete response in pre-chemotherapy samples. TxNIP (P¼0.017) and thioredoxin reductase (P¼0.022) were independent prognostic factors for distant metastasis free survival and TxNIP for overall survival (P¼0.014). In oestrogen receptor negative patients that are known to have a poor overall survival, a considerably worse prognosis was seen in cases that exhibited low expression of TxNIP (P¼0.000003), stratifying patients into more defined groups. This study indicates the importance of redox regulation in determining breast cancer response to anthracycline-based chemotherapy and provides ways of further stratifying pre-chemotherapy patients to potentially allow more tailored treatments

Drug Discovery Using Chemical Systems Biology: Weak Inhibition of Multiple Kinases May Contribute to the Anti-Cancer Effect of Nelfinavir

Nelfinavir is a potent HIV-protease inhibitor with pleiotropic effects in cancer cells. Experimental studies connect its anti-cancer effects to the suppression of the Akt signaling pathway, but the actual molecular targets remain unknown. Using a structural proteome-wide off-target pipeline, which integrates molecular dynamics simulation and MM/GBSA free energy calculations with ligand binding site comparison and biological network analysis, we identified putative human off-targets of Nelfinavir and analyzed the impact on the associated biological processes. Our results suggest that Nelfinavir is able to inhibit multiple members of the protein kinase-like superfamily, which are involved in the regulation of cellular processes vital for carcinogenesis and metastasis. The computational predictions are supported by kinase activity assays and are consistent with existing experimental and clinical evidence. This finding provides a molecular basis to explain the broad-spectrum anti-cancer effect of Nelfinavir and presents opportunities to optimize the drug as a targeted polypharmacology agent

Challenges in measuring measles case fatality ratios in settings without vital registration

Measles, a highly infectious vaccine-preventable viral disease, is potentially fatal. Historically, measles case-fatality ratios (CFRs) have been reported to vary from 0.1% in the developed world to as high as 30% in emergency settings. Estimates of the global burden of mortality from measles, critical to prioritizing measles vaccination among other health interventions, are highly sensitive to the CFR estimates used in modeling; however, due to the lack of reliable, up-to-date data, considerable debate exists as to what CFR estimates are appropriate to use. To determine current measles CFRs in high-burden settings without vital registration we have conducted six retrospective measles mortality studies in such settings. This paper examines the methodological challenges of this work and our solutions to these challenges, including the integration of lessons from retrospective all-cause mortality studies into CFR studies, approaches to laboratory confirmation of outbreaks, and means of obtaining a representative sample of case-patients. Our experiences are relevant to those conducting retrospective CFR studies for measles or other diseases, and to those interested in all-cause mortality studies