The Succession of the Cellulolytic Microbial Community from the Soil during Oat Straw Decomposition

Abstract

The decomposition of straw is a dynamic process, which is reflected in the decomposing microbial consortia, however, this process is poorly understood. Here we performed an experiment on the gradual colonization of oat straw by the soil microbial community. The results showed that soil respiration and bacterial diversity were negatively correlated – while the first decreased, the latter increased. In accordance with the dynamics of diversity and respiration, succession was divided into early, middle, and late decomposition phases. Analysis of 16S rRNA and ITS2 amplicon sequencing data revealed three jointly changing groups of phylotypes, corresponding with distinguished phases of decomposition. The presence of cellulolytic members of Proteobacteria, Bacteroidota, Firmicutes, and Actinobacteriota for bacteria and Ascomycota for fungi had been detected since the early phase, but most of the initial phylotypes were gone by the end of the phase. The second phase marked the functional core with a constant set of other phylotypes from these phyla, persisting in the community. Full metagenome sequencing of the microbial community from the end of the middle phase confirmed that major members of this consortium had GH genes, connected to cellulose and chitin degradation. The appearance of non-cellulolytic members from Bdellovibrio, Myxococcota, Chloroflexi, and Crenarchaeota characterized the last phase of the mature community.

Metagenomic insights into the development of microbial communities of straw and leaf composts

“…This effect is particularly evident in the late stages of decomposition and is substrate dependent. A similar effect was shown previously, as we detected that a significant part of microbial taxonomic diversity at the later phases of straw colonization does not participate in cellulose degradation because it does not have genes for the corresponding enzymes in its genomes, while these groups of microorganisms can make a serious contribution to the community by shifting the representation of effective cellulolytic microorganisms (39).…”

“…However, both composts shared similar patterns of microbiome development. Our choice of longer periods of sample incubation had a significant effect on the outcome: we detected long-term shifts in microbial and functional composition, with an increase in bacterial diversity and a decrease in fungi, coinciding with one of our previous experiments (39). The observations of dynamics at the taxonomic level are consistent with the earlier findings, specifically the prevalence of Pseudomonadota during the initial stages of straw colonization from soil and the diversification of the community in the later phases (8,39).…”

“…Our choice of longer periods of sample incubation had a significant effect on the outcome: we detected long-term shifts in microbial and functional composition, with an increase in bacterial diversity and a decrease in fungi, coinciding with one of our previous experiments (39). The observations of dynamics at the taxonomic level are consistent with the earlier findings, specifically the prevalence of Pseudomonadota during the initial stages of straw colonization from soil and the diversification of the community in the later phases (8,39). Genera detected by Illumina sequencing in both types of composts -Pseudomonas, Bacillus, Flavobacterium, Sphingobacterium, and Novosphingobium -were reported multiple times to contain potentially active cellulolytic species (77)(78)(79)(80).…”

“…The amplicon sequencing data was processed in R Studio (37) using the DADA2 pipeline (38) as described earlier (39), including analysis of alpha (observed and Shannon (40) indices) and betadiversity (NMDS (41) with Bray-Curtis distances (42)). Taxonomic identification was performed using Silva 138.1 (for 16S rRNA gene) (43) and Unite (for ITS amplicons, general release 02.02.2019) (44) databases.…”

The effect of geographic location and physiochemical characteristics on the cryoconite prokaryotic communities from the Arctic, Antarctic, and Central Caucasus regions

“…Processing of the data from the sequenced 16S rRNA gene amplicon libraries, including analysis of alpha-diversity, beta-diversity, taxonomy identi cation, and WGCNA, was performed as described earlier [19,20] using the DADA2 pipeline [21] in the R software environment v. 4.2 [22]. The ANCOM-BC set of statistical tools [23] was used as the basis for compositional statistical post-processing of data, including the search of structural zeros [24] in the core microbiome and the differential abundance test for the Pimpirev glacier.…”