Trees, fungi and bacteria: tripartite metatranscriptomics of a root microbiome responding to soil contamination

Abstract

BackgroundOne method for rejuvenating land polluted with anthropogenic contaminants is through phytoremediation, the reclamation of land through the cultivation of specific crops. The capacity for phytoremediation crops, such as Salix spp., to tolerate and even flourish in contaminated soils relies on a highly complex and predominantly cryptic interacting community of microbial life.MethodsHere, Illumina HiSeq 2500 sequencing and de novo transcriptome assembly were used to observe gene expression in washed Salix purpurea cv. ‘Fish Creek’ roots from trees pot grown in petroleum hydrocarbon-contaminated or non-contaminated soil. All 189,849 assembled contigs were annotated without a priori assumption as to sequence origin and differential expression was assessed.ResultsThe 839 contigs differentially expressed (DE) and annotated from S. purpurea revealed substantial increases in transcripts encoding abiotic stress response equipment, such as glutathione S-transferases, in roots of contaminated trees as well as the hallmarks of fungal interaction, such as SWEET2 (Sugars Will Eventually Be Exported Transporter). A total of 8252 DE transcripts were fungal in origin, with contamination conditions resulting in a community shift from Ascomycota to Basidiomycota genera. In response to contamination, 1745 Basidiomycota transcripts increased in abundance (the majority uniquely expressed in contaminated soil) including major monosaccharide transporter MST1, primary cell wall and lamella CAZy enzymes, and an ectomycorrhiza-upregulated exo-β-1,3-glucanase (GH5). Additionally, 639 DE polycistronic transcripts from an uncharacterised Enterobacteriaceae species were uniformly in higher abundance in contamination conditions and comprised a wide spectrum of genes cryptic under laboratory conditions but considered putatively involved in eukaryotic interaction, biofilm formation and dioxygenase hydrocarbon degradation.ConclusionsFungal gene expression, representing the majority of contigs assembled, suggests out-competition of white rot Ascomycota genera (dominated by Pyronema), a sometimes ectomycorrhizal (ECM) Ascomycota (Tuber) and ECM Basidiomycota (Hebeloma) by a poorly characterised putative ECM Basidiomycota due to contamination. Root and fungal expression involved transcripts encoding carbohydrate/amino acid (C/N) dialogue whereas bacterial gene expression included the apparatus necessary for biofilm interaction and direct reduction of contamination stress, a potential bacterial currency for a role in tripartite mutualism. Unmistakable within the metatranscriptome is the degree to which the landscape of rhizospheric biology, particularly the important but predominantly uncharacterised fungal genetics, is yet to be discovered.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0432-5) contains supplementary material, which is available to authorized users.

ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples

“…Default recommended annotation uses four sequence repositories with strict BLASTn criteria (>99% identity and coverage) providing each amplicon with up to four pools of labels from: NCBI‐curated bacterial and Archaea RefSeq, NCBI nr/nt, SILVA and Ribosomal Database Project (RDP). Annotation selection against the four databases is based on de novo metatranscriptomics strategy (Brereton et al ., ; Gonzalez et al ., ), where all potential annotation is retained to allow for informed annotation selection and downstream interpretation. BLASTn returns with a query identity and coverage <99% are discarded and the highest identity/coverage scores are selected per query.…”

“…BLASTn returns with a query identity and coverage <99% are discarded and the highest identity/coverage scores are selected per query. When the highest identity/coverage for a given high‐count sequence is shared amongst different blast returns from a database, all are retained as equally ‘good’ annotation and designated as ambiguous hits (borrowed from the idea of secondary annotation in metatranscriptomics [Brereton et al ., ; Gonzalez et al ., )]. Accurately reporting ambiguity is important as fragments of a specific 16S rRNA gene [or a gene's entire sequence (Vetrovsky and Baldrian, )] are sometimes 100% similar between known species; the relative utility of a specific amplicon as a barcode therefore varies based on the species present in a sample as well as the technology used for sequencing and data processing.…”

Rhizoremediation of petroleum hydrocarbons: a model system for plant microbiome manipulation

“…These mechanisms are thought to enable holobionts to adapt within a single or a few generations (Voss et al, 2015;Rosenberg and Zilber-Rosenberg, 2016). It has recently been shown that the response of willows to stressful conditions (soil contamination) results in large shifts in the metatranscriptome of root and rhizosphere bacterial and fungal communities, but not in the plant root transcriptome (Gonzalez et al, 2018;Yergeau et al, 2018). Taken together, these results emphasize the importance of the plant microbiota in the response to environmental stresses and confirms that microbiota manipulation is a viable alternative to optimize phytoremediation (El Amrani et al, 2015;Quiza et al, 2015).…”

“…The rhizosphere microbes, especially bacteria, are thought to be the major players in organic contaminant degradation during rhizoremediation (Bell et al, 2014a,b;El Amrani et al, 2015), and recent plant-microbe metatranscriptomic studies confirmed that the hydrocarbon degradation genes expressed in the root-rhizosphere environment were mostly linked to bacteria (Gonzalez et al, 2018;Yergeau et al, 2018) (Box 1). Petroleum hydrocarbon contamination is often composed of a mixture of saturated aliphatic (alkanes) and aromatic hydrocarbons (including polycyclic aromatic hydrocarbons, PAHs).…”

Differential gene expression associated with fungal trophic shifts along the senescence gradient of the moss Dicranum scoparium

“…Transcripts with E values < 1e‐6 were kept. The E ‐value cut‐off was selected based on previous studies (Hesse et al ., ; Quandt et al ., ; Comtet‐Marre et al ., ; Meiser et al ., ; Gonzalez et al ., ) and after manual examination of a subset of sequences and their BLASTX results. To gain more taxonomic information and to confirm that the selected transcripts really belong to fungi, transcripts were first translated into proteins with Transdecoder (Haas et al ., ) and an additional round of BLASTP against the NCBI Non‐Redundant (NR) protein database was performed, saving the top five hits.…”