Otávio J. B. Brustolini

NIK1-mediated translation suppression functions as a plant antiviral immunity mechanism

Plants and plant pathogens are subject to continuous co-evolutionary pressure for dominance, and the outcomes of these interactions can substantially impact agriculture and food security. In virus–plant interactions, one of the major mechanisms for plant antiviral immunity relies on RNA silencing, which is often suppressed by co-evolving virus suppressors, thus enhancing viral pathogenicity in susceptible hosts. In addition, plants use the nucleotide-binding and leucine-rich repeat (NB-LRR) domain-containing resistance proteins, which recognize viral effectors to activate effector-triggered immunity in a defence mechanism similar to that employed in non-viral infections. Unlike most eukaryotic organisms, plants are not known to activate mechanisms of host global translation suppression to fight viruses. Here we demonstrate in Arabidopsis that the constitutive activation of NIK1, a leucine-rich repeat receptor-like kinase (LRR-RLK) identified as a virulence target of the begomovirus nuclear shuttle protein (NSP), leads to global translation suppression and translocation of the downstream component RPL10 to the nucleus, where it interacts with a newly identified MYB-like protein, L10-INTERACTING MYB DOMAIN-CONTAINING PROTEIN (LIMYB), to downregulate translational machinery genes fully. LIMYB overexpression represses ribosomal protein genes at the transcriptional level, resulting in protein synthesis inhibition, decreased viral messenger RNA association with polysome fractions and enhanced tolerance to begomovirus. By contrast, the loss of LIMYB function releases the repression of translation-related genes and increases susceptibility to virus infection. Therefore, LIMYB links immune receptor LRR-RLK activation to global translation suppression as an antiviral immunity strategy in plants.

The Endoplasmic Reticulum Binding Protein BiP Displays Dual Function in Modulating Cell Death Events

The endoplasmic reticulum binding protein BiP can function as a positive and negative modulator of cell death events in plant cells. The binding protein (BiP) has been demonstrated to participate in innate immunity and attenuate endoplasmic reticulum- and osmotic stress-induced cell death. Here, we employed transgenic plants with manipulated levels of BiP to assess whether BiP also controlled developmental and hypersensitive programmed cell death (PCD). Under normal conditions, the BiP-induced transcriptome revealed a robust down-regulation of developmental PCD genes and an up-regulation of the genes involved in hypersensitive PCD triggered by nonhost-pathogen interactions. Accordingly, the BiP-overexpressing line displayed delayed leaf senescence under normal conditions and accelerated hypersensitive response triggered by Pseudomonas syringae pv tomato in soybean (Glycine max) and tobacco (Nicotiana tabacum), as monitored by measuring hallmarks of PCD in plants. The BiP-mediated delay of leaf senescence correlated with the attenuation of N-rich protein (NRP)-mediated cell death signaling and the inhibition of the senescence-associated activation of the unfolded protein response (UPR). By contrast, under biological activation of salicylic acid (SA) signaling and hypersensitive PCD, BiP overexpression further induced NRP-mediated cell death signaling and antagonistically inhibited the UPR. Thus, the SA-mediated induction of NRP cell death signaling occurs via a pathway distinct from UPR. Our data indicate that during the hypersensitive PCD, BiP positively regulates the NRP cell death signaling through a yet undefined mechanism that is activated by SA signaling and related to ER functioning. By contrast, BiP’s negative regulation of leaf senescence may be linked to its capacity to attenuate the UPR activation and NRP cell death signaling. Therefore, BiP can function either as a negative or positive modulator of PCD events.

Sustained NIK-mediated antiviral signalling confers broad-spectrum tolerance to begomoviruses in cultivated plants.

Begomovirus-associated epidemics currently threaten tomato production worldwide due to the emergence of highly pathogenic virus species and the proliferation of a whitefly B biotype vector that is adapted to tomato. To generate an efficient defence against begomovirus, we modulated the activity of the immune defence receptor nuclear shuttle protein (NSP)-interacting kinase (NIK) in tomato plants; NIK is a virulence target of the begomovirus NSP during infection. Mutation of T474 within the kinase activation loop promoted the constitutive activation of NIK-mediated defences, resulting in the down-regulation of translation-related genes and the suppression of global translation. Consistent with these findings, transgenic lines harbouring an activating mutation (T474D) were tolerant to the tomato-infecting begomoviruses ToYSV and ToSRV. This phenotype was associated with reduced loading of coat protein viral mRNA in actively translating polysomes, lower infection efficiency and reduced accumulation of viral DNA in systemic leaves. Our results also add some relevant insights into the mechanism underlying the NIK-mediated defence. We observed that the mock-inoculated T474D-overexpressing lines showed a constitutively infected wild-type transcriptome, indicating that the activation of the NIK-mediated signalling pathway triggers a typical response to begomovirus infection. In addition, the gain-of-function mutant T474D could sustain an activated NIK-mediated antiviral response in the absence of the virus, further confirming that phosphorylation of Thr-474 is the crucial event that leads to the activation of the kinase.

Genomic growth curves of an outbred pig population

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

The molecular chaperone binding protein BiP prevents leaf dehydration-induced cellular homeostasis disruption.

BiP overexpression improves leaf water relations during droughts and delays drought-induced leaf senescence. However, whether BiP controls cellular homeostasis under drought conditions or simply delays dehydration-induced leaf senescence as the primary cause for water stress tolerance remains to be determined. To address this issue, we examined the drought-induced transcriptomes of BiP-overexpressing lines and wild-type (WT) lines under similar leaf water potential (ψw) values. In the WT leaves, a ψw reduction of −1.0 resulted in 1339 up-regulated and 2710 down-regulated genes; in the BiP-overexpressing line 35S::BiP-4, only 334 and 420 genes were induced and repressed, respectively, at a similar leaf ψw = −1.0 MPa. This level of leaf dehydration was low enough to induce a repertory of typical drought-responsive genes in WT leaves but not in 35S::BiP-4 dehydrated leaves. The responders included hormone-related genes, functional and regulatory genes involved in drought protection and senescence-associated genes. The number of differentially expressed genes in the 35S::BiP-4 line approached the wild type number at a leaf ψw = −1.6 MPa. However, N-rich protein (NRP)- mediated cell death signaling genes and unfolded protein response (UPR) genes were induced to a much lower extent in the 35S::BiP-4 line than in the WT even at ψw = −1.6 MPa. The heatmaps for UPR, ERAD (ER-associated degradation protein system), drought-responsive and cell death-associated genes revealed that the leaf transcriptome of 35S::BiP-4 at ψw = −1.0 MPa clustered together with the transcriptome of well-watered leaves and they diverged considerably from the drought-induced transcriptome of the WT (ψw = −1.0, −1.7 and −2.0 MPa) and 35S::BiP-4 leaves at ψw = −1.6 MPa. Taken together, our data revealed that BiP-overexpressing lines requires a much higher level of stress (ψw = −1.6 MPa) to respond to drought than that of WT (ψw = −1.0). Therefore, BiP overexpression maintains cellular homeostasis under water stress conditions and thus ameliorates endogenous osmotic stress.

Computational analysis of the interaction between transcription factors and the predicted secreted proteome of the yeast Kluyveromyces lactis

BackgroundProtein secretion is a cell translocation process of major biological and technological significance. The secretion and downstream processing of proteins by recombinant cells is of great commercial interest. The yeast Kluyveromyces lactis is considered a promising host for heterologous protein production. Because yeasts naturally do not secrete as many proteins as filamentous fungi, they can produce secreted recombinant proteins with few contaminants in the medium. An ideal system to address the secretion of a desired protein could be exploited among the native proteins in certain physiological conditions. By applying algorithms to the completed K. lactis genome sequence, such a system could be selected. To this end, we predicted protein subcellular locations and correlated the resulting extracellular secretome with the transcription factors that modulate the cellular response to a particular environmental stimulus.ResultsTo explore the potential Kluyveromyces lactis extracellular secretome, four computational prediction algorithms were applied to 5076 predicted K. lactis proteins from the genome database. SignalP v3 identified 418 proteins with N-terminal signal peptides. From these 418 proteins, the Phobius algorithm predicted that 176 proteins have no transmembrane domains, and the big-PI Predictor identified 150 proteins as having no glycosylphosphatidylinositol (GPI) modification sites. WoLF PSORT predicted that the K. lactis secretome consists of 109 putative proteins, excluding subcellular targeting. The transcription regulators of the putative extracellular proteins were investigated by searching for DNA binding sites in their putative promoters. The conditions to favor expression were obtained by searching Gene Ontology terms and using graph theory.ConclusionA public database of K. lactis secreted proteins and their transcription factors are presented. It consists of 109 ORFs and 23 transcription factors. A graph created from this database shows 134 nodes and 884 edges, suggesting a vast number of relationships to be validated experimentally. Most of the transcription factors are related to responses to stress such as drug, acid and heat resistance, as well as nitrogen limitation, and may be useful for inducing maximal expression of potential extracellular proteins.

Genomic Sequence of the Yeast Kluyveromyces marxianus CCT 7735 (UFV-3), a Highly Lactose-Fermenting Yeast Isolated from the Brazilian Dairy Industry

ABSTRACT Here, we present the draft genome sequence of Kluyveromyces marxianus CCT 7735 (UFV-3), including the eight chromosomes and the mitochondrial genomic sequences.

The Stress-Induced Soybean NAC Transcription Factor GmNAC81 Plays a Positive Role in Developmentally Programmed Leaf Senescence

The onset of leaf senescence is a highly regulated developmental change that is controlled by both genetics and the environment. Senescence is triggered by massive transcriptional reprogramming, but functional information about its underlying regulatory mechanisms is limited. In the current investigation, we performed a functional analysis of the soybean (Glycine max) osmotic stress- and endoplasmic reticulum (ER) stress-induced NAC transcription factor GmNAC81 during natural leaf senescence using overexpression studies and reverse genetics. GmNAC81-overexpressing lines displayed accelerated flowering and leaf senescence but otherwise developed normally. The precocious leaf senescence of GmNAC81-overexpressing lines was associated with greater Chl loss, faster photosynthetic decay and higher expression of hydrolytic enzyme-encoding GmNAC81 target genes, including the vacuolar processing enzyme (VPE), an executioner of vacuole-triggered programmed cell death (PCD). Conversely, virus-induced gene silencing-mediated silencing of GmNAC81 delayed leaf senescence and was associated with reductions in Chl loss, lipid peroxidation and the expression of GmNAC81 direct targets. Promoter-reporter studies revealed that the expression pattern of GmNAC81 was associated with senescence in soybean leaves. Our data indicate that GmNAC81 is a positive regulator of age-dependent senescence and may integrate osmotic stress- and ER stress-induced PCD responses with natural leaf senescence through the GmNAC81/VPE regulatory circuit.

NIK1, a host factor specialized in antiviral defense or a novel general regulator of plant immunity?

NIK1 is a receptor‐like kinase involved in plant antiviral immunity. Although NIK1 is structurally similar to the plant immune factor BAK1, which is a key regulator in plant immunity to bacterial pathogens, the NIK1‐mediated defenses do not resemble BAK1 signaling cascades. The underlying mechanism for NIK1 antiviral immunity has recently been uncovered. NIK1 activation mediates the translocation of RPL10 to the nucleus, where it interacts with LIMYB to fully down‐regulate translational machinery genes, resulting in translation inhibition of host and viral mRNAs and enhanced tolerance to begomovirus. Therefore, the NIK1 antiviral immunity response culminates in global translation suppression, which represents a new paradigm for plant antiviral defenses. Interestingly, transcriptomic analyses in nik1 mutant suggest that NIK1 may suppress antibacterial immune responses, indicating a possible opposite effect of NIK1 in bacterial and viral infections.

Geminivirus data warehouse: a database enriched with machine learning approaches

BackgroundThe Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics.ResultsHere, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes.ConclusionsThe use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.