Preliminary results

We have recently analyzed the shotgun metagenome derived by the combined Illumina MiSeq / PacBio sequencing strategy followed by an Illumina MiSeq sequencing transcriptome analysis contrasting TBZ vs succinate degradation. The metagenome analysis resulted in the assembly of large contigs and the grouping of contigs into bins according to traits like tetranucleotide frequencies, GC content, codon usage, phylogenetic marker genes. A total of 41 dominant bins were formed of completeness of up to 92.5 % (mean of 33.78% according to screened phylogenetic markers) by contigs with N50s of 828 – 48,536 bp and were taxonomically affiliated with Actinomycetales, Bacteroidetes, Bradyrhizobiaceae, Hydrocarboniphaga effusa, Hydrogenophaga, Hyphomicrobiaceae, Hyphomicrobium denitrificans, Kordiimonadales, Phyllobacteriaceae, Rhizobiales, Sphingomonas, Thiobacillus denitrificans (Fig. 1).

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Figure 1 Consortium composition overview according to bin phylogenies.

Functional gene annotation of the metagenome contigs using the InterProScan 5 (Jones et al., 2014) encompassed tools/databases demonstrated the existence of an extensive enzymatic toolbox. Pathway analysis of the predicted genes distinguished 8 bins being the most dominant in pathway content belonging in 7 taxa (cluster group 1 – Fig. 2).

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Figure 2 Metabolic capacity of the consortium according to pathway analysis and functional gene distribution among identified bins.

Transcriptome analysis after the depletion of rRNA sequences showed 10,058 genes being expressed at above the detection limits out of the 103,273 identified in all contigs. Out of these 1,980 were up-regulated and 3,687 were down-regulated during TBZ degradation when compared with succinate catabolism and lead to associated changes in pathway expression (Fig. 3).

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Figure 3 Wordcloud of pathway enrichment (phrase size differences reflect enrichment differences)  according to differential expression of genes during TBZ vs Succinate catabolism with 3 replicates in each case.

A wealth of aromatic compound catabolic pathways were enriched in the TBZ treatment, with a large portion of these enrichments being derived from the contig bin #2, classified as Sphingomonas, also found to be dominant in the phylogenetic screening previously published by our group members.

It is not the first time that sphingomonads keep our lab busy (Perruchon et al., 2016; Perruchon et al., 2017b) since the enzymatic toolbox identified in this fascinating group is intriguing. A pangenome analysis of 74 NCBI submitted reference genomes of taxonomical groups encompassing recalcitrant compound degraders and residing in the Sphingomonadaceae family was carried out using the enveomics (Rodriguez-R and Konstantinidis, 2016) and the Panviz (Pedersen et al., 2017) tools. The analysis showed an overall core genome parted by 220 orthologous gene clusters (OG - Fig. 4) throughout all tested genomes, whereas subclade selection showed relatively large accessory gene-sets of above 10,000 OG demonstrating the metabolic versatility of sphingomonads.

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Figure 4 Modeling of pan/core-genome orthologous gene clusters.


Jones, P., Binns, D., Chang, H.-Y., Fraser, M., Li, W., McAnulla, C. et al. (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30: 1236-1240 [->].

Pedersen, T.L., Nookaew, I., Wayne Ussery, D., and Månsson, M. (2017) PanViz: interactive visualization of the structure of functionally annotated pangenomes. Bioinformatics 33: 1081-1082 [->].

Perruchon, C., Patsioura, V., Vasileiadis, S., and Karpouzas, D.G. (2016) Isolation and characterisation of a Sphingomonas strain able to degrade the fungicide ortho-phenylphenol. Pest Manag Sci 72: 113-124 [->].

Perruchon, C., Vasileiadis, S., Rousidou, K., Papadopoulou, E., Tanou, G., Samiotaki, M. et al. (2017b) Metabolic pathway and cell adaptation mechanisms revealed through genomic, proteomic and transcription analysis of a Sphingomonas haloaromaticamans strain degrading ortho-phenylphenol. Scientific Reports 7: 6449 [->].

Rodriguez-R, L.M., and Konstantinidis, K.T. (2016) The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes. PeerJ Preprints 4: e1900v1901 [->].

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