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. 2022 May 12;12(1):7832.
doi: 10.1038/s41598-022-11907-0.

Transitions of foliar mycobiota community and transcriptome in response to pathogenic conifer needle interactions

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Transitions of foliar mycobiota community and transcriptome in response to pathogenic conifer needle interactions

Jessa P Ata et al. Sci Rep. .

Abstract

Profiling the host-mycobiota interactions in healthy vs. diseased forest ecosystems helps understand the dynamics of understudied yet increasingly important threats to forest health that are emerging due to climate change. We analyzed the structural and functional changes of the mycobiota and the responses of Pinus contorta in the Lophodermella needle cast pathosystem through metabarcoding and metatranscriptomics. When needles transitioned from asymptomatic to symptomatic, dysbiosis of the mycobiota occurred, but with an enrichment of Lophodermella pathogens. Many pathogenicity-related genes were highly expressed by the mycobiota at the necrotrophic phase, showing an active pathogen response that are absent in asymptomatic needles. This study also revealed that Lophodermella spp. are members of a healthy needle mycobiota that have latent lifestyles suggesting that other pine needle pathogens may have similar biology. Interestingly, Pinus contorta upregulated defense genes in healthy needles, indicating response to fungal recognition, while a variety of biotic and abiotic stresses genes were activated in diseased needles. Further investigation to elucidate the possible antagonistic interplay of other biotic members leading to disease progression and/or suppression is warranted. This study provides insights into microbial interactions in non-model pathosystems and contributes to the development of new forest management strategies against emerging latent pathogens.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Relative abundance of fungal taxa (removing OTUs assigned as unclassified fungi) within the mycobiome across Pinus contorta needles that were asymptomatic (ASYM) and symptomatic (SYM) of Lophodermella concolor and L. montivaga identified through metabarcoding.
Figure 2
Figure 2
Principal coordinate analysis (PCoA) using Bray–Curtis distances based on relative abundance of fungal operational taxonomic units (OTUs) showing fungal community structure on Pinus contorta needles that are symptomatic or asymptomatic of Lophodermella concolor (LC) and L. montivaga (LM). Ellipses represent one standard deviation.
Figure 3
Figure 3
Heatmap of the differentially expressed transcripts (isoforms) in P. contorta needles that were asymptomatic (ASYM) and symptomatic (SYM) of Lophodermella concolor (LC) or L. montivaga (LM) based on counts per million (CPM) reads. Trinity transcripts shown are the top 10 differentially expressed features (p-value < 0.001, fold change ≥ 2) within each of the four pairwise comparisons. Similar colors at tree tips represent replicate samples within each of the following treatments: LC_ASYM (purple), LC_SYM (blue), LM_ASYM (green), and LM_SYM (red).
Figure 4
Figure 4
Abundance of the top 25 taxonomic families of differentially expressed (DE) fungal transcripts among P. contorta needles symptomatic (SYM) of Lophodermella concolor (LC) or L. montivaga (LM) when compared to their corresponding asymptomatic needles (LC_ASYM vs. LC_SYM and LM_ASYM vs. LM_SYM); in these two comparisons, no fungal DE transcripts in asymptomatic needles were among the top 25 families. Taxonomic annotations were obtained from concatenated databases of NCBI-nr and JGI Mycocosm.
Figure 5
Figure 5
Number of differentially expressed (DE) fungal transcripts annotated as (a) enzymes that degrade proteins and various substrates, (b) genes important to pathogenicity, and (c) metabolic pathways in needles symptomatic of Lophodermella concolor (LC) and L. montivaga (LM) in comparisons LC_ASYM vs. LC_SYM and LM_ASYM vs. LM_SYM, respectively; in these two comparisons, no fungal DE transcripts in asymptomatic needles. Annotations were inferred from dbCAN2 and PFAM, PHI-base and KEGG, respectively.

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