RNA-seq with RNase H-based ribosomal RNA depletion specifically designed for C. elegans

Here we describe a rRNA depletion protocol based on RNase H digestion using antisense oligonucleotides (ASOs) specifically designed for C. elegans cytoplasmic rRNA (Fig. 1A). We suggest that this rRNA depletion protocol is applicable to RNA-seq applications where the yield of mRNA enrichment should be independent of poly(A) status, or any application which benefits from the removal of rRNA sequences, such ribosome profiling, or sequencing of non-coding RNAs other than rRNA

Hordeum vulgare differentiates its response to beneficial bacteria

Background In nature, beneficial bacteria triggering induced systemic resistance (ISR) may protect plants from potential diseases, reducing yield losses caused by diverse pathogens. However, little is known about how the host plant initially responds to different beneficial bacteria. To reveal the impact of different bacteria on barley (Hordeum vulgare), bacterial colonization patterns, gene expression, and composition of seed endophytes were explored. Results This study used the soil-borne Ensifer meliloti, as well as Pantoea sp. and Pseudomonas sp. isolated from barley seeds, individually. The results demonstrated that those bacteria persisted in the rhizosphere but with different colonization patterns. Although root-leaf translocation was not observed, all three bacteria induced systemic resistance (ISR) against foliar fungal pathogens. Transcriptome analysis revealed that ion- and stress-related genes were regulated in plants that first encountered bacteria. Iron homeostasis and heat stress responses were involved in the response to E. meliloti and Pantoea sp., even if the iron content was not altered. Heat shock protein-encoding genes responded to inoculation with Pantoea sp. and Pseudomonas sp. Furthermore, bacterial inoculation affected the composition of seed endophytes. Investigation of the following generation indicated that the enhanced resistance was not heritable. Conclusions Here, using barley as a model, we highlighted different responses to three different beneficial bacteria as well as the influence of soil-borne Ensifer meliloti on the seed microbiome. In total, these results can help to understand the interaction between ISR-triggering bacteria and a crop plant, which is essential for the application of biological agents in sustainable agriculture

Salmonella enterica relies on carbon metabolism to adapt to agricultural environments

Salmonella enterica, a foodborne and human pathogen, is a constant threat to human health. Agricultural environments, for example, soil and plants, can be ecological niches and vectors for Salmonella transmission. Salmonella persistence in such environments increases the risk for consumers. Therefore, it is necessary to investigate the mechanisms used by Salmonella to adapt to agricultural environments. We assessed the adaptation strategy of S. enterica serovar Typhimurium strain 14028s to agricultural-relevant situations by analyzing the abundance of intermediates in glycolysis and the tricarboxylic acid pathway in tested environments (diluvial sand soil suspension and leaf-based media from tomato and lettuce), as well as in bacterial cells grown in such conditions. By reanalyzing the transcriptome data of Salmonella grown in those environments and using an independent RT-qPCR approach for verification, several genes were identified as important for persistence in root or leaf tissues, including the pyruvate dehydrogenase subunit E1 encoding gene aceE. In vivo persistence assay in tomato leaves confirmed the crucial role of aceE. A mutant in another tomato leaf persistence-related gene, aceB, encoding malate synthase A, displayed opposite persistence features. By comparing the metabolites and gene expression of the wild-type strain and its aceB mutant, fumarate accumulation was discovered as a potential way to replenish the effects of the aceB mutation. Our research interprets the mechanism of S. enterica adaptation to agriculture by adapting its carbon metabolism to the carbon sources available in the environment. These insights may assist in the development of strategies aimed at diminishing Salmonella persistence in food production systems

Upregulation of MMP-13 and TIMP-1 expression in response to mechanical strain in MC3T3-E1 osteoblastic cells

<p>Abstract</p> <p>Background</p> <p>Mechanical strain plays a significant role in the regulation of bone matrix turnover, which is mediated in part by matrix metalloproteinase (MMP)-13 and tissue inhibitors of matrix metalloproteinase (TIMP)-1. However, little is known about the correlation between mechanical strain and osteoblastic cell activities, including extracellular matrix (ECM) metabolism. Herein, we determined the effect of different magnitudes of cyclic tensile strain (0%, 6%, 12%, and 18%) on MMP-13 and TIMP-1 mRNA and protein expression in MC3T3-E1 osteoblasts. Furthermore, we employed specific inhibitors to examine the role of distinct signal transduction pathways known to mediate cellular responses to mechanical strain.</p> <p>Results</p> <p>We identified a magnitude-dependent increase in MMP-13 and TIMP-1 mRNA and protein levels in response to mechanical strains corresponding to 6%, 12%, and 18% elongation. The strain-induced increases in MMP-13 and TIMP-1 mRNA expression were inhibited by PD098059 and cycloheximide, respectively.</p> <p>Conclusions</p> <p>Our results suggest a mechanism for the regulation of bone matrix metabolism mediated by the differential expression of MMP-13 and TIMP-1 in response to increasing magnitudes of mechanical strain.</p

Integrated Photonics for NASA Applications

No abstract availabl

ONE IMPROVED AGENT GENETIC ALGORITHM — RING-LIKE AGENT GENETIC ALGORITHM FOR GLOBAL NUMERICAL OPTIMIZATION

In this paper, a novel genetic algorithm — dynamic ring-like agent genetic algorithm (RAGA) is proposed for solving global numerical optimization problem. The RAGA combines the ring-like agent structure and dynamic neighboring genetic operators together to get better optimization capability. An agent in ring-like agent structure represents a candidate solution to the optimization problem. Any agent interacts with neighboring agents to evolve. With dynamic neighboring genetic operators, they compete and cooperate with their neighbors, and they can also use knowledge to increase energies. Global numerical optimization problems are the most important ones to verify the performance of evolutionary algorithm, especially of genetic algorithm and are mostly of interest to the corresponding researchers. In the corresponding experiments, several complex benchmark functions were used for optimization, several popular GAs were used for comparison. In order to better compare two agents GAs (MAGA: multi-agent genetic algorithm and RAGA), the several dimensional experiments (from low dimension to high dimension) were done. These experimental results show that RAGA not only is suitable for optimization problems, but also has more precise and more stable optimization results.Genetic algorithm, ring-like agent, numerical optimization, multiagent system