Bacillus proteolyticus OSUB18 triggers induced systemic resistance against bacterial and fungal pathogens in Arabidopsis

Pseudomonas syringae and Botrytis cinerea cause destructive bacterial speck and grey mold diseases in many plant species, leading to substantial economic losses in agricultural production. Our study discovered that the application of Bacillus proteolyticus strain OSUB18 as a root-drench enhanced the resistance of Arabidopsis plants against P. syringae and B. cinerea through activating Induced Systemic Resistance (ISR). The underlying mechanisms by which OSUB18 activates ISR were studied. Our results revealed that the Arabidopsis plants with OSUB18 root-drench showed the enhanced callose deposition and ROS production when inoculated with Pseudomonas syringae and Botrytis cinerea pathogens, respectively. Also, the increased salicylic acid (SA) levels were detected in the OSUB18 root-drenched plants compared with the water root-drenched plants after the P. syringae infection. In contrast, the OSUB18 root-drenched plants produced significantly higher levels of jasmonyl isoleucine (JA-Ile) than the water root-drenched control after the B. cinerea infection. The qRT-PCR analyses indicated that the ISR-responsive gene MYC2 and the ROS-responsive gene RBOHD were significantly upregulated in OSUB18 root-drenched plants upon both pathogen infections compared with the controls. Also, twenty-four hours after the bacterial or fungal inoculation, the OSUB18 root-drenched plants showed the upregulated expression levels of SA-related genes (PR1, PR2, PR5, EDS5, and SID2) or JA-related genes (PDF1.2, LOX3, JAR1 and COI1), respectively, which were consistent with the related hormone levels upon these two different pathogen infections. Moreover, OSUB18 can trigger ISR in jar1 or sid2 mutants but not in myc2 or npr1 mutants, depending on the pathogen’s lifestyles. In addition, OSUB18 prompted the production of acetoin, which was reported as a novel rhizobacterial ISR elicitor. In summary, our studies discover that OSUB18 is a novel ISR inducer that primes plants’ resistance against bacterial and fungal pathogens by enhancing the callose deposition and ROS accumulation, increasing the production of specific phytohormones and other metabolites involved in plant defense, and elevating the expression levels of multiple defense genes

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe

The culturable endophytic fungal communities of switchgrass grown on a coal-mining site and their effects on plant growth

<div><p>Plants have a diverse endophytic microbiome that is functionally important for their growth, development, and health. In this study, the diversity and specificity of culturable endophytic fungal communities were explored in one of the most important biofuel crops, switchgrass plants (<i>Panicum virgatum</i> L.), which have been cultivated on a reclaimed coal-mining site for more than 20 years. The endophytic fungi were isolated from the surface-sterilized shoot (leaf and stem), root, and seed tissues of switchgrass plants and then cultured for identification. A total of 1339 fungal isolates were found and 22 operational taxonomic units (OTUs) were sequence identified by internal transcribed spacer (ITS) primers and grouped into 7 orders and 4 classes. Although a diverse range of endophytic fungi associated with switchgrass were documented, the most abundant class, order, and species were Sordariomycetes, Hypocreales, and <i>Fusarium spp</i>. respectively. About 86% of the isolated endophytic fungi were able to enhance the heights of the shoots; 69% could increase the shoot fresh weights; and 62% could improve the shoot dry weights after being reintroduced back into the switchgrass plants, which illustrated their functional importance. Through the Shannon Diversity Index analysis, we observed a gradation of species diversity, with shoots and roots having the similar values and seeds having a lesser value. It was observed that the switchgrass plants showing better growth performance displayed higher endophytic fungal species diversity and abundance. It was also discovered that the rhizosphere soil organic matter content was positively correlated with the fungal species diversity. All these data demonstrate the functional association of these beneficial endophytic fungi with switchgrass and their great potential in improving the switchgrass growth and biomass to benefit the biofuel industry by reducing chemical inputs and burden to the environment.</p></div

The shoot dry weights of the switchgrass plants.

<p>The plants were treated with water control and the water broth containing diverse fungal spores and mycelia at 8 weeks under greenhouse condition. The triangle represents the significant difference existing between the fungal broth treated and water treated plants; the data were further analyzed by the Student’s t-test (P<0.05).</p

The levels of pH, organic matter, and major nutrient contents of plant rhizosphere soil.

<p>The levels of pH, organic matter, and major nutrient contents of plant rhizosphere soil.</p

The distribution of endophytic fungal isolates from switchgrass.

<p>The isolate numbers (A) and strain types (B) at the order level; and the isolate numbers (C) and strain types (D) at the class level.</p

Endophytic fungal species abundance among tissues.

<p>Endophytic fungal species abundance among tissues.</p