Plant immunity is often triggered by the specific recognition of pathogen effectors by intracellular nucleotide-binding, leucine-rich repeat receptors (NLR). Plant NLRs contain an N-terminal ...signaling domain that is mostly represented by either a Toll-interleukin1 receptor (TIR) domain or a coiled coil (CC) domain. In many cases, single NLR proteins are sufficient for both effector recognition and signaling activation. However, many paired NLRs have now been identified where both proteins are required to confer resistance to pathogens. Recent detailed studies on the Arabidopsis thaliana TIR-NLR pair RRS1 and RPS4 and on the rice CC-NLR pair RGA4 and RGA5 have revealed for the first time how such protein pairs function together. In both cases, the paired partners interact physically to form a hetero-complex receptor in which each partner plays distinct roles in effector recognition or signaling activation, highlighting a conserved mode of action of NLR pairs across both monocotyledonous and dicotyledonous plants. We also describe an "integrated decoy" model for the function of these receptor complexes. In this model, a plant protein targeted by an effector has been duplicated and fused to one member of the NLR pair, where it acts as a bait to trigger defense signaling by the second NLR upon effector binding. This mechanism may be common to many other plant NLR pairs.
Rust fungi (Pucciniales, Basidiomycota) are obligate biotrophic pathogens that cause rust diseases in plants, inflicting severe damage to agricultural crops. Pucciniales possess the most complex life ...cycles known in fungi. These include an alternation of generations, the development of up to five different sporulating stages, and, for many species, the requirement of infecting two unrelated host plants during different parts of their life cycle, termed heteroecism. These fungi have been extensively studied in the past century through microscopy and inoculation studies, providing precise descriptions of their infection processes, although the molecular mechanisms underlying their unique biology are poorly understood. In this review, we cover recent genomic and life cycle transcriptomic studies in several heteroecious rust species, which provide insights into the genetic tool kits associated with host adaptation and virulence, opening new avenues for unraveling their unique evolution.
The first plant disease resistance (
R
) genes were identified and cloned more than two decades ago. Since then, many more
R
genes have been identified and characterized in numerous plant ...pathosystems. Most of these encode members of the large family of intracellular NLRs (NOD-like receptors), which also includes animal immune receptors. New discoveries in this expanding field of research provide new elements for our understanding of plant NLR function. But what do we know about plant NLR function today? Genetic, structural, and functional analyses have uncovered a number of commonalities and differences in pathogen recognition strategies as well as how NLRs are regulated and activate defense signaling, but many unknowns remain. This review gives an update on the latest discoveries and breakthroughs in this field, with an emphasis on structural findings and some comparison to animal NLRs, which can provide additional insights and paradigms in plant NLR function.
Identifying and communicating relationships between causes and effects is important for understanding our world, but is affected by language structure, cognitive and emotional biases, and the ...properties of the communication medium. Despite the increasing importance of social media, much remains unknown about causal statements made online. To study real-world causal attribution, we extract a large-scale corpus of causal statements made on the Twitter social network platform as well as a comparable random control corpus. We compare causal and control statements using statistical language and sentiment analysis tools. We find that causal statements have a number of significant lexical and grammatical differences compared with controls and tend to be more negative in sentiment than controls. Causal statements made online tend to focus on news and current events, medicine and health, or interpersonal relationships, as shown by topic models. By quantifying the features and potential biases of causality communication, this study improves our understanding of the accuracy of information and opinions found online.
Abstract
In recent years, the global public health community has increasingly recognized the importance of antimicrobial stewardship (AMS) in the fight to improve outcomes, decrease costs, and curb ...increases in antimicrobial resistance around the world. However, the subject of antifungal stewardship (AFS) has received less attention. While the principles of AMS guidelines likely apply to stewarding of antifungal agents, there are additional considerations unique to AFS and the complex field of fungal infections that require specific recommendations. In this article, we review the literature on AMS best practices and discuss AFS through the lens of the global core elements of AMS. We offer recommendations for best practices in AFS based on a synthesis of this evidence by an interdisciplinary expert panel of members of the Mycoses Study Group Education and Research Consortium. We also discuss research directions in this rapidly evolving field. AFS is an emerging and important component of AMS, yet requires special considerations in certain areas such as expertise, education, interventions to optimize utilization, therapeutic drug monitoring, and data analysis and reporting.
Two classes of genes are used for breeding rust resistant wheat. The first class, called R (for resistance) genes, are pathogen race specific in their action, effective at all plant growth stages and ...probably mostly encode immune receptors of the nucleotide binding leucine rich repeat (NB-LRR) class. The second class is called adult plant resistance genes (APR) because resistance is usually functional only in adult plants, and, in contrast to most R genes, the levels of resistance conferred by single APR genes are only partial and allow considerable disease development. Some but not all APR genes provide resistance to all isolates of a rust pathogen species and a subclass of these provides resistance to several fungal pathogen species. Initial indications are that APR genes encode a more heterogeneous range of proteins than R proteins. Two APR genes, Lr34 and Yr36, have been cloned from wheat and their products are an ABC transporter and a protein kinase, respectively. Lr34 and Sr2 have provided long lasting and widely used (durable) partial resistance and are mainly used in conjunction with other R and APR genes to obtain adequate rust resistance. We caution that some APR genes indeed include race specific, weak R genes which may be of the NB-LRR class. A research priority to better inform rust resistance breeding is to characterize further APR genes in wheat and to understand how they function and how they interact when multiple APR and R genes are stacked in a single genotype by conventional and GM breeding. An important message is do not be complacent about the general durability of all APR genes.
The patterns of life exhibited by large populations have been described and modeled both as a basic science exercise and for a range of applied goals such as reducing automotive congestion, improving ...disaster response, and even predicting the location of individuals. However, these studies previously had limited access to conversation content, rendering changes in expression as a function of movement invisible. In addition, they typically use the communication between a mobile phone and its nearest antenna tower to infer position, limiting the spatial resolution of the data to the geographical region serviced by each cellphone tower. We use a collection of 37 million geolocated tweets to characterize the movement patterns of 180,000 individuals, taking advantage of several orders of magnitude of increased spatial accuracy relative to previous work. Employing the recently developed sentiment analysis instrument known as the 'hedonometer', we characterize changes in word usage as a function of movement, and find that expressed happiness increases logarithmically with distance from an individual's average location.
ApoplastP Sperschneider, Jana; Dodds, Peter N.; Singh, Karam B. ...
The New phytologist,
March 2018, Letnik:
217, Številka:
4
Journal Article
Recenzirano
Odprti dostop
The plant apoplast is integral to intercellular signalling, transport and plant–pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no ...computational method currently exists to discriminate between these localizations.
We present ApoplastP, the first method for predicting whether an effector or plant protein localizes to the apoplast.
ApoplastP uncovers features of apoplastic localization common to both effectors and plant proteins, namely depletion in glutamic acid, acidic amino acids and charged amino acids and enrichment in small amino acids. ApoplastP predicts apoplastic localization in effectors with a sensitivity of 75% and a false positive rate of 5%, improving the accuracy of cysteine-rich classifiers by > 13%. ApoplastP does not depend on the presence of a signal peptide and correctly predicts the localization of unconventionally secreted proteins. The secretomes of fungal saprophytes as well as necrotrophic, hemibiotrophic and extracellular fungal pathogens are enriched for predicted apoplastic proteins. Rust pathogens have low proportions of predicted apoplastic proteins, but these are highly enriched for predicted effectors.
ApoplastP pioneers apoplastic localization prediction using machine learning. It will facilitate functional studies and will be valuable for predicting if an effector localizes to the apoplast or if it enters plant cells.
Eukaryotic filamentous plant pathogens secrete effector proteins that modulate the host cell to facilitate infection. Computational effector candidate identification and subsequent functional ...characterization delivers valuable insights into plant–pathogen interactions. However, effector prediction in fungi has been challenging due to a lack of unifying sequence features such as conserved N‐terminal sequence motifs. Fungal effectors are commonly predicted from secretomes based on criteria such as small size and cysteine‐rich, which suffers from poor accuracy. We present EffectorP which pioneers the application of machine learning to fungal effector prediction. EffectorP improves fungal effector prediction from secretomes based on a robust signal of sequence‐derived properties, achieving sensitivity and specificity of over 80%. Features that discriminate fungal effectors from secreted noneffectors are predominantly sequence length, molecular weight and protein net charge, as well as cysteine, serine and tryptophan content. We demonstrate that EffectorP is powerful when combined with in planta expression data for predicting high‐priority effector candidates. EffectorP is the first prediction program for fungal effectors based on machine learning. Our findings will facilitate functional fungal effector studies and improve our understanding of effectors in plant–pathogen interactions. EffectorP is available at http://effectorp.csiro.au.
Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. ...Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/.
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