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Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors.

ABSTRACT: The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localization predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes.

SUBMITTER: Sperschneider J

PROVIDER: S-EPMC4688413 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors.

Sperschneider Jana J Williams Angela H AH Hane James K JK Singh Karam B KB Taylor Jennifer M JM

Frontiers in plant science 20151223

The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from ...[more]

PMID: 26779196

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Project description:Oomycete pathogens cause diverse plant diseases. To successfully colonize their hosts, they deliver a suite of effector proteins that can attenuate plant defenses. In the oomycete downy mildews, effectors carry a signal peptide and an RxLR motif. Hyaloperonospora arabidopsidis (Hpa) causes downy mildew on the model plant Arabidopsis thaliana (Arabidopsis). We investigated if candidate effectors predicted in the genome sequence of Hpa isolate Emoy2 (HaRxLs) were able to manipulate host defenses in different Arabidopsis accessions. We developed a rapid and sensitive screening method to test HaRxLs by delivering them via the bacterial type-three secretion system (TTSS) of Pseudomonas syringae pv tomato DC3000-LUX (Pst-LUX) and assessing changes in Pst-LUX growth in planta on 12 Arabidopsis accessions. The majority (~70%) of the 64 candidates tested positively contributed to Pst-LUX growth on more than one accession indicating that Hpa virulence likely involves multiple effectors with weak accession-specific effects. Further screening with a Pst mutant (ΔCEL) showed that HaRxLs that allow enhanced Pst-LUX growth usually suppress callose deposition, a hallmark of pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI). We found that HaRxLs are rarely strong avirulence determinants. Although some decreased Pst-LUX growth in particular accessions, none activated macroscopic cell death. Fewer HaRxLs conferred enhanced Pst growth on turnip, a non-host for Hpa, while several reduced it, consistent with the idea that turnip's non-host resistance against Hpa could involve a combination of recognized HaRxLs and ineffective HaRxLs. We verified our results by constitutively expressing in Arabidopsis a sub-set of HaRxLs. Several transgenic lines showed increased susceptibility to Hpa and attenuation of Arabidopsis PTI responses, confirming the HaRxLs' role in Hpa virulence. This study shows TTSS screening system provides a useful tool to test whether candidate effectors from eukaryotic pathogens can suppress/trigger plant defense mechanisms and to rank their effectiveness prior to subsequent mechanistic investigation.

Project description:BackgroundPhytophthora cactorum, a hemibiotrophic oomycete pathogen, can cause destructive diseases on numerous crops worldwide, leading to essential economic losses every year. However, little has been known about its molecular pathogenicity mechanisms. To gain insight into its repertoire of effectors, the P. cactorum transcriptome was investigated using Illumina RNA-seq.ResultsWe first demonstrated an in vitro inoculation method that can be used to mimic natural cyst germination on host plants. Over 28 million cDNA reads were obtained for five life cycle stages (mycelium, sporangium, zoospore, cyst and germinating cyst) and de novo assembled into 21,662 unique genes. By comparisons with 11 public databases, 88.99% of the unique genes were annotated, including 15,845 mapped to the gene models of the annotated relative Phytophthora infestans. Using TribeMCL, 5,538 gene families conserved across P. cactorum and other three completely sequenced Phytophthora pathogen species were determined. In silico analyses revealed that 620 P. cactorum effector homologues including 94 RXLR effector candidates matched known or putative virulence genes in other oomycetes. About half of the RXLR effector candidates were predicted to share a conserved structure unit, termed the WY-domain fold. A subset of the effector genes were checked and validated by PCR amplification. Transcriptional experiments indicated that effector genes were differentially expressed during the life cycle and host infection stages of P. cactorum. Ectopic expression in Nicotiana benthamiana revealed that RXLR, elicitin and NLP effectors can trigger plant cell death. These effectors are highly conserved across oomycete species. Single nucleotide polymorphisms for RXLR effectors were detected in a collection of P. cactorum isolates from different countries and hosts.ConclusionsThis study demonstrates the comprehensive sequencing, de novo assembly, and analyses of the transcriptome of P. cactorum life cycle stages. In the absence of genome sequence, transcriptome data is important for infection-related gene discovery in P. cactorum, as demonstrated here for the effector genes. The first look at the transcriptome and effector arsenal of P. cactorum provides valuable data to elucidate the pathogenicity basis of this broad-host-range pathogen.

Dataset Information

Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors.

Publications

Evaluation of Secretion Prediction Highlights Differing Approaches Needed for Oomycete and Fungal Effectors.

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