Secreted proteins involved in KEGG metabolic pathways.

<p>Secreted proteins involved in KEGG metabolic pathways.</p

Venn diagram showing orthologues among the <i>H</i>. <i>oryzae</i>, <i>M</i>. <i>oryzae</i>, <i>G</i>. <i>graminis</i>, and <i>M</i>. <i>poae</i> secretomes.

<p>The values indicate the counts of the orthologue groups.</p

Expression patterns of genes encoding secreted proteins in <i>H</i>. and <i>M</i>. <i>oryzae</i>.

<p>(a) <i>H</i>. <i>oryzae</i> genes. (b) <i>M</i>. <i>oryzae</i> genes. Red, decrease in transcript abundance; green, increase in transcript abundance. Heat maps were produced based on expression changes (log2 DAI6/DAI2). 1, proteins with Glyco_hydro domain; 2, peptidase; 3, lipase; 4, tyrosinase; 5, cutinase; 6, cellulase; 7, proteins with CBM domain; 8, proteins with Chitin_bind_1 domain; 9, proteins with LysM domain, 10, proteins with FAD_binding_4 domain; 11, proteins with Cu-oxidase domain; and 12, proteins with GMC_oxred_N domain.</p

Differential Communications between Fungi and Host Plants Revealed by Secretome Analysis of Phylogenetically Related Endophytic and Pathogenic Fungi

<div><p>During infection, both phytopathogenic and endophytic fungi form intimate contact with living plant cells, and need to resist or disable host defences and modify host metabolism to adapt to their host. Fungi can achieve these changes by secreting proteins and enzymes. A comprehensive comparison of the secretomes of both endophytic and pathogenic fungi can improve our understanding of the interactions between plants and fungi. Although <i>Magnaporthe oryzae</i>, <i>Gaeumannomyces graminis</i>, and <i>M</i>. <i>poae</i> are economically important fungal pathogens, and the related species <i>Harpophora oryzae</i> is an endophyte, they evolved from a common pathogenic ancestor. We used a pipeline analysis to predict the <i>H</i>. <i>oryzae</i>, <i>M</i>. <i>oryzae</i>, <i>G</i>. <i>graminis</i>, and <i>M</i>. <i>poae</i> secretomes and identified 1142, 1370, 1001, and 974 proteins, respectively. Orthologue gene analyses demonstrated that the <i>M</i>. <i>oryzae</i> secretome evolved more rapidly than those of the other three related species, resulting in many species-specific secreted protein-encoding genes, such as avirulence genes. Functional analyses highlighted the abundance of proteins involved in the breakdown of host plant cell walls and oxidation-reduction processes. We identified three novel motifs in the <i>H</i>. and <i>M</i>. <i>oryzae</i> secretomes, which may play key roles in the interaction between rice and <i>H</i>. <i>oryzae</i>. Furthermore, we found that expression of the <i>H</i>. <i>oryzae</i> secretome involved in plant cell wall degradation was downregulated, but the <i>M</i>. <i>oryzae</i> secretome was upregulated with many more upregulated genes involved in oxidation-reduction processes. The divergent <i>in planta</i> expression patterns of the <i>H</i>. and <i>M</i>. <i>oryzae</i> secretomes reveal differences that are associated with mutualistic and pathogenic interactions, respectively.</p></div

<i>De novo</i> motif searches of the unannotated <i>H</i>. and <i>M</i>. <i>oryzae</i> secretomes.

<p>(a) Sequences of the three motifs. (b) Distribution of the three motifs in the amino acid sequence of each protein. Each circle represents one motif.</p

Profiles of <i>H</i>. <i>oryzae</i>, <i>M</i>. <i>oryzae</i>, <i>G</i>. <i>graminis</i>, and <i>M</i>. <i>poae</i> annotated secretomes.

(a) Major enzyme classes in the four secretomes. (b) Major targets of the hydrolyases. (c) The 10 most abundant GO categories (biological processes, level 6) of the four secretomes.</p

Summary of <i>H</i>. and <i>M</i>. <i>oryzae</i> secretome expression. Fold-changes of gene expression (DAI6 versus DAI2) are presented.

<p>(a) Annotated secretomes. (b) Unannotated secretomes. DAI2 and DAI6 refer to transcripts expressed by <i>H</i>. or <i>M</i>. <i>oryzae</i> infecting rice roots at 2 and 6 days after inoculation, respectively. Unregulated genes, genes with fold-change ≤ 2 and ≥ 0.5; Upregulated genes, genes with fold change > 2; Downregulated genes, genes with fold change < 0.5.</p

The 25 most abundant PFAM domains in the four secretomes.

<p>The 25 most abundant PFAM domains in the four secretomes.</p

Table_1_Shift in Bacterial Community Structure Drives Different Atrazine-Degrading Efficiencies.DOCX

Compositions of pollutant-catabolic consortia and interactions between community members greatly affect the efficiency of pollutant catabolism. However, the relationships between community structure and efficiency of catabolic function in pollutant-catabolic consortia remain largely unknown. In this study, an original enrichment (AT) capable of degrading atrazine was obtained. And two enrichments – with a better/worse atrazine-degrading efficiency (ATB/ATW) – were derived from the original enrichment AT by continuous sub-enrichment with or without atrazine. Subsequently, an Arthrobacter sp. strain, AT5, that was capable of degrading atrazine was isolated from enrichment AT. The bacterial community structures of these three enrichments were investigated using high-throughput sequencing analysis of the 16S rRNA gene. The atrazine-degrading efficiency improved as the abundance of Arthrobacter species increased in enrichment ATB. The relative abundance of Arthrobacter was positively correlated with those of Hyphomicrobium and Methylophilus, which enhanced atrazine degradation via promoting the growth of Arthrobacter. Furthermore, six genera/families such as Azospirillum and Halomonas showed a significantly negative correlation with atrazine-degrading efficiency, as they suppressed atrazine degradation directly. These results suggested that atrazine-degrading efficiency was affected by not only the degrader but also some non-degraders in the community. The promotion and suppression of atrazine degradation by Methylophilus and Azospirillum/Halomonas, respectively, were experimentally validated in vitro, showing that shifts in both the composition and abundance in consortia can drive the change in the efficiency of catabolic function. This study provides valuable information for designing enhanced bioremediation strategies.</p

The analysis pipeline applied to the <i>H</i>. <i>oryzae</i>, <i>M</i>. <i>oryzae</i>, <i>G</i>. <i>graminis</i>, and <i>M</i>. <i>poae</i> secretomes.

<p>The pipeline can be divided in three main steps: 1) secretome prediction, 2) functional analysis, and 3) expression analysis.</p