Dynamic localization of a helper NLR at the plant-pathogen interface underpins pathogen recognition

Plants employ sensor-helper pairs of NLR immune receptors to recognize pathogen effectors and activate immune responses (1). Yet the subcellular localization of NLRs pre- and post-activation during pathogen infection remains poorly understood. Here we show that NRC4, from the ‘NRC’ solanaceous helper NLR family (1), undergoes dynamic changes in subcellular localization by shuttling to and from the plant-pathogen haustorium interface established during infection by the Irish potato famine pathogen Phytophthora infestans. Specifically, prior to activation, NRC4 accumulates at the extra-haustorial membrane (EHM), presumably to mediate response to perihaustorial effectors, that are recognized by NRC4- dependent sensor NLRs. However not all NLRs accumulate at the EHM, as the closely related helper NRC2, and the distantly related ZAR1, did not accumulate at the EHM. NRC4 required an intact N-terminal coiled coil domain to accumulate at the EHM, whereas the functionally conserved MADA motif implicated in cell death activation and membrane insertion was dispensable for this process. Strikingly, a constitutively autoactive NRC4 mutant did not accumulate at the EHM and showed punctate distribution that mainly associated with the plasma membrane, suggesting that post-activation, NRC4 may undergo a conformation switch to form clusters that do not preferentially associate with the EHM. When NRC4 is activated by a sensor NLR during infection however, NRC4 forms puncta mainly at the EHM and to a lesser extent at the plasma membrane. We conclude that following activation at the EHM, NRC4 may spread to other cellular membranes from its primary site of activation to trigger immune responses

Maternal smoking during pregnancy and subcutaneous fat mass in early childhood. The Generation R Study

Maternal smoking during pregnancy increases the risk of obesity in the offspring. Not much is known about the associations with other measures of body composition. We assessed the associations of maternal smoking during pregnancy with the development of subcutaneous fat mass measured as peripheral and central skinfold thickness measurements in early childhood, in a population-based prospective cohort study from early fetal life onward in the city of Rotterdam, The Netherlands. The study was performed in 907 mothers and their children at the ages of 1.5, 6 and 24 months. As compared to non-smoking mothers, mothers who continued smoking during pregnancy were more likely to have a younger age and a lower educational level. Their children had a lower birth weight, higher risk of small size for gestational age and were breastfed for a shorter duration (P-values <0.01). We did not observe differences in peripheral, central and total subcutaneous fat mass between the offspring of non-smoking mothers, mothers who smoked in first trimester only and mothers who continued smoking during pregnancy (P > 0.05). Also, the reported number of cigarettes smoked by mothers in both first and third trimester of pregnancy were not associated with peripheral, central and total subcutaneous fat mass in the offspring at the ages of 1.5, 6 and 24 months. Our findings suggest that fetal exposure to cigarette smoke during pregnancy does not influence subcutaneous fat mass in early childhood. Follow-up studies are needed in children at older ages and to identify associations of maternal smoking during pregnancy with other measures of body composition

Integrating Ion Mobility Mass Spectrometry with Molecular Modelling to Determine the Architecture of Multiprotein Complexes

Current challenges in the field of structural genomics point to the need for new tools and technologies for obtaining structures of macromolecular protein complexes. Here, we present an integrative computational method that uses molecular modelling, ion mobility-mass spectrometry (IM-MS) and incomplete atomic structures, usually from X-ray crystallography, to generate models of the subunit architecture of protein complexes. We begin by analyzing protein complexes using IM-MS, and by taking measurements of both intact complexes and sub-complexes that are generated in solution. We then examine available high resolution structural data and use a suite of computational methods to account for missing residues at the subunit and/or domain level. High-order complexes and sub-complexes are then constructed that conform to distance and connectivity constraints imposed by IM-MS data. We illustrate our method by applying it to multimeric protein complexes within the Escherichia coli replisome: the sliding clamp, (β2), the γ complex (γ3δδ′), the DnaB helicase (DnaB6) and the Single-Stranded Binding Protein (SSB4)

An integrated analysis of molecular aberrations in NCI-60 cell lines

<p>Abstract</p> <p>Background</p> <p>Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.</p> <p>Results</p> <p>We propose an integrated modeling framework to identify the statistical and putative causal relations of various molecular aberrations and gene expressions in cancer. To reduce spurious associations among the massive number of probed features, we sequentially applied three layers of logistic regression models with increasing complexity and uncertainty regarding the possible mechanisms connecting molecular aberrations and gene expressions. Layer 1 models associate gene expressions with the molecular aberrations on the same loci. Layer 2 models associate expressions with the aberrations on different loci but have known mechanistic links. Layer 3 models associate expressions with nonlocal aberrations which have unknown mechanistic links. We applied the layered models to the integrated datasets of NCI-60 cancer cell lines and validated the results with large-scale statistical analysis. Furthermore, we discovered/reaffirmed the following prominent links: (1)Protein expressions are generally consistent with mRNA expressions. (2)Several gene expressions are modulated by composite local aberrations. For instance, CDKN2A expressions are repressed by either frame-shift mutations or DNA methylations. (3)Amplification of chromosome 6q in leukemia elevates the expression of MYB, and the downstream targets of MYB on other chromosomes are up-regulated accordingly. (4)Amplification of chromosome 3p and hypo-methylation of PAX3 together elevate MITF expression in melanoma, which up-regulates the downstream targets of MITF. (5)Mutations of TP53 are negatively associated with its direct target genes.</p> <p>Conclusions</p> <p>The analysis results on NCI-60 data justify the utility of the layered models for the incoming flow of cancer genomic data. Experimental validations on selected prominent links and application of the layered modeling framework to other integrated datasets will be carried out subsequently.</p

Chronic Obstructive Pulmonary Disease and Lung Cancer: Underlying Pathophysiology and New Therapeutic Modalities

Chronic obstructive pulmonary disease (COPD) and lung cancer are major lung diseases affecting millions worldwide. Both diseases have links to cigarette smoking and exert a considerable societal burden. People suffering from COPD are at higher risk of developing lung cancer than those without, and are more susceptible to poor outcomes after diagnosis and treatment. Lung cancer and COPD are closely associated, possibly sharing common traits such as an underlying genetic predisposition, epithelial and endothelial cell plasticity, dysfunctional inflammatory mechanisms including the deposition of excessive extracellular matrix, angiogenesis, susceptibility to DNA damage and cellular mutagenesis. In fact, COPD could be the driving factor for lung cancer, providing a conducive environment that propagates its evolution. In the early stages of smoking, body defences provide a combative immune/oxidative response and DNA repair mechanisms are likely to subdue these changes to a certain extent; however, in patients with COPD with lung cancer the consequences could be devastating, potentially contributing to slower postoperative recovery after lung resection and increased resistance to radiotherapy and chemotherapy. Vital to the development of new-targeted therapies is an in-depth understanding of various molecular mechanisms that are associated with both pathologies. In this comprehensive review, we provide a detailed overview of possible underlying factors that link COPD and lung cancer, and current therapeutic advances from both human and preclinical animal models that can effectively mitigate this unholy relationship

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Modulation of plant autophagy during pathogen attack

In plants, the highly conserved catabolic process of autophagy has long been known as a means of maintaining cellular homeostasis and coping with abiotic stress conditions. Accumulating evidence has linked autophagy to immunity against invading pathogens, regulating plant cell death, and antimicrobial defences. In turn, it appears that phytopathogens have evolved ways not only to evade autophagic clearance but also to modulate and co-opt autophagy for their own benefit. In this review, we summarize and discuss the emerging discoveries concerning how pathogens modulate both host and self-autophagy machineries to colonize their host plants, delving into the arms race that determines the fate of interorganismal interaction