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Bacillus pumilis F3-4 utilized feather as a sole source of carbon, nitrogen and sulfur. Supplementation of the feather medium with glucose or MgSO(4) . 7H(2)O increased keratinolytic protease production (14.6-16.7 U/mg). The synthesis of keratinolytic protease was repressed by an exogenous nitrogen source. Keratinolytic protease was produced in the absence of feather (9.4 U/mg). Feather degradation resulted in sulfhydryl group formation (0.8-2.6 microM). B. pumilis F3-4 effectively degraded chicken feather (75%), duck feather (81%) and feather meal (97%), whereas human nails, human hair and sheep wool under went less degradation (9-15%).

We isolated and characterized novel insoluble phosphate (P)-solubilizing bacteria tolerant to environmental factors like high salt, low and high pHs, and low temperature. A bacterium M6 was isolated from a ginseng rhizospheric soil and confirmed to belong to Burkholderia vietnamiensis by BIOLOG system and 16S rRNA gene analysis. The optimal cultural conditions for the solubilization of P were 2.5% (w/v) glucose, 0.015% (w/v) urea, and 0.4% (w/v) MgCl(2).6H(2)O along with initial pH 7.0 at 35 degrees C. High-performance liquid chromatography analysis showed that B. vietnamiensis M6 produced gluconic and 2-ketogluconic acids. During the culture, the pH was reduced with increase in gluconic acid concentration and was inversely correlated with P solubilization. Insoluble P solubilization in the optimal medium was about 902 mg l(-1), which was approximately 1.6-fold higher than the yield in NBRIP medium (580 mg l(-1)). B. vietnamiensis M6 showed resistance against different environmental stresses like 10-45 degrees C, 1-5% (w/v) salt, and 2-11 pH range. The maximal concentration of soluble P produced by B. vietnamiensis M6 from Ca(3)(PO(4))(2), CaHPO(4), and hydroxyapatite was 1,039, 2,132, and 1,754 mg l(-1), respectively. However, the strain M6 produced soluble P with 20 mg l(-1) from FePO(4) after 2 days and 100 mg l(-1) from AlPO(4) after 6 days, respectively. Our results indicate that B. vietnamiensis M6 could be a potential candidate for the development of biofertilizer applicable to environmentally stressed soil.

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The recent advances in deep learning-based approaches hold great promise for unravelling biological mechanisms, discovering biomarkers, and predicting gene function. Here, we deployed a deep generative model for simulating the molecular progression of tauopathy and dissecting its early features. We applied generative adversarial networks (GANs) for bulk RNA-seq analysis in a mouse model of tauopathy (TPR50-P301S). The union set of differentially expressed genes from four comparisons (two phenotypes with two time points) was used as input training data. We devised four-way transition curves for a virtual simulation of disease progression, clustered and grouped the curves by patterns, and identified eight distinct pattern groups showing different biological features from Gene Ontology enrichment analyses. Genes that were upregulated in early tauopathy were associated with vasculature development, and these changes preceded immune responses. We confirmed significant disease-associated differences in the public human data for the genes of the different pattern groups. Validation with weighted gene co-expression network analysis suggested that our GAN-based approach can be used to detect distinct patterns of early molecular changes during disease progression, which may be extremely difficult in in vivo experiments. The generative model is a valid systematic approach for exploring the sequential cascades of mechanisms and targeting early molecular events related to dementia.