Sequential MyD88-Independent and -Dependent Activation of Innate Immune Responses to Intracellular Bacterial Infection

AbstractMicrobial infections induce chemokine and cytokine cascades that coordinate innate immune defenses. Infection with the intracellular bacterial pathogen Listeria monocytogenes induces CCR2-dependent monocyte recruitment and activation, an essential response for host survival. Herein we show that invasive L. monocytogenes, but not killed or noninvasive bacteria, induce secretion of MCP-1, the requisite chemokine for monocyte recruitment. Induction of MCP-1, but not TNF or IL-12, following L. monocytogenes infection is MyD88 independent. Consistent with these results, MyD88 deficiency does not impair monocyte recruitment to L. monocytogenes infected spleens, but prevents monocyte activation. Our results indicate that distinct microbial signals activate innate immune responses in an ordered, step-wise fashion, providing a mechanism to specify and modulate antimicrobial effector functions

Community recommendations on terminology and procedures used in flooding and low oxygen stress research

Apart from playing a key role in important biochemical reactions, molecular oxygen (O2) and its by-products also have crucial signaling roles in shaping plant developmental programs and environmental responses. Even under normal conditions, sharp O2 gradients can occur within the plant when cellular O2 demand exceeds supply, especially in dense organs such as tubers, seeds and fruits. Spatial and temporal variations in O2 concentrations are important cues for plants to modulate development (van Dongen & Licausi, 2015; Considine et al., 2016). Environmental conditions can also expand the low O2 regions within the plant. For example, excessive rainfall can lead to partial or complete plant submergence resulting in O2 deficiency in the root or the entire plant (Voesenek & Bailey-Serres, 2015). Climate change-associated increases in precipitation events have made flooding a major abiotic stress threatening crop production and food sustainability. This increased flooding and associated crop losses highlight the urgency of understanding plant flooding responses and tolerance mechanisms. Timely manifestation of physiological and morphological changes triggering developmental adjustments or flooding survival strategies requires accurate sensing of O2 levels. Despite progress in understanding how plants sense and respond to changes in intracellular O2 concentrations (van Dongen & Licausi, 2015), several questions remain unanswered due to a lack of high resolution tools to accurately and noninvasively monitor (sub)cellular O2 concentrations. In the absence of such tools, it is therefore critical for researchers in the field to be aware of how experimental conditions can influence plant O2 levels, and thus on the importance of accurately reporting specific experimental details. This also requires a consensus on the definition of frequently used terms. At the 15th New Phytologist Workshop on Flooding stress (Voesenek et al., 2016), community members discussed and agreed on unified nomenclature and standard norms for low O2 and flooding stress research. This consensus on terminology and experimental guidelines is presented here. We expect that these norms will facilitate more effective interpretation, comparison and reproducibility of research in this field. We also highlight the current challenges in noninvasively monitoring and measuring O2 concentrations in plant cells, outlining the technologies currently available, their strengths and drawbacks, and their suitability for use in flooding and low O2 research

GBScleanR: robust genotyping error correction using a hidden Markov model with error pattern recognition

Reduced-representation sequencing (RRS) provides cost-effective and time-saving genotyping platforms. Despite the outstanding advantage of RRS in throughput, the obtained genotype data usually contain a large number of errors. Several error correction methods employing the hidden Markov model (HMM) have been developed to overcome these issues. These methods assume that markers have a uniform error rate with no bias in the allele read ratio. However, bias does occur because of uneven amplification of genomic fragments and read mismapping. In this paper, we introduce an error correction tool, GBScleanR, which enables robust and precise error correction for noisy RRS-based genotype data by incorporating marker-specific error rates into the HMM. The results indicate that GBScleanR improves the accuracy by more than 25 percentage points at maximum compared to the existing tools in simulation data sets and achieves the most reliable genotype estimation in real data even with error-prone markers

イネの矮性遺伝子Dwarf 1のマップベースドクローニング

Chapter 1.RFLP linkage mapping of d1 locus Chapter 2.Physical mapping of D1 gene Chapter 3.Cloning of D1 geneMade available in DSpace on 2012-09-06T04:10:16Z (GMT). No. of bitstreams: 1 ashikari.pdf: 10746489 bytes, checksum: 5e94d07cf742f3cd67bed0b213090d35 (MD5) Previous issue date: 1999-03-17主1-参

The Gibberellin Signaling Pathway Is Regulated by the Appearance and Disappearance of SLENDER RICE1 in Nuclei

The slender rice1 mutant (slr1) shows a constitutive gibberellin (GA) response phenotype. To investigate the mode of action of SLR1, we generated transgenic rice expressing a fusion protein consisting of SLR1 and green fluorescent protein (SLR1-GFP) and analyzed the phenotype of the transformants and the subcellular localization of GFP in vivo. SLR1-GFP worked in nuclei to repress the GA signaling pathway; its overproduction caused a dwarf phenotype. Application of GA(3) to SLR1-GFP overproducers induced GA actions such as shoot elongation, downregulation of GA 20-oxidase expression, and upregulation of SLR1 expression linked with the disappearance of the nuclear SLR1-GFP protein. We also performed domain analyses of SLR1 using transgenic plants overproducing different kinds of truncated SLR1 proteins. The analyses revealed that the SLR1 protein can be divided into four parts: a GA signal perception domain located at the N terminus, a regulatory domain for its repression activity, a dimer formation domain essential for signal perception and repression activity, and a repression domain at the C terminus. We conclude that GA signal transduction is regulated by the appearance or disappearance of the nuclear SLR1 protein, which is controlled by the upstream GA signal