Illumina sequencing of bacterial 16S rDNA and 16S rRNA reveals seasonal and species-specific variation in bacterial communities in four moss species

Abstract

In order to better understand the factors that influence bacterial diversity and community composition in moss-associated bacteria, a study of bacterial communities in four moss species collected in three seasons was carried out via high-throughput sequencing of 16S rDNA and 16S rRNA. Moss species included Cratoneuron filicinum, Pylaisiella polyantha, Campyliadelphus polygamum, and Grimmia pilifera, with samples collected in May, July, and October 2015 from rocks at Beijing Songshan National Nature Reserve. In total, the bacterial richness and diversity were high regardless of moss species, sampling season, or data source (DNA vs. RNA). Bacterial sequences were assigned to a total of 558 OTUs and 279 genera in 16 phyla. Proteobacteria and Actinobacteria were the two most abundant phyla, and Cellvibrio, Lapillicoccus, Jatrophihabitans, Friedmanniella, Oligoflexus, and Bosea the most common genera in the samples. A clustering algorithm and principal coordinate analysis revealed that C. filicinum and C. polygamum had similar bacterial communities, as did P. polyantha and G. pilifera. Metabolically active bacteria showed the same pattern in addition to seasonal variation: bacterial communities were most similar in summer and autumn, looking at each moss species separately. In contrast, DNA profiles lacked obvious seasonal dynamics. A partial least squares discriminant analysis identified three groups of samples that correlated with differences in moss species resources. Although bacterial community composition did vary with the sampling season and data source, these were not the most important factors influencing bacterial communities. Previous reports exhibited that mosses have been widely used in biomonitoring of air pollution by enriching some substances or elements in the moss-tag technique and the abundant moss associated bacteria might also be important components involved in the related biological processes. Thus, this survey not only enhanced our understanding of the factors which influence microbial communities in mosses but also would be helpful for better use and development of the moss-tag technique in the environmental biomonitoring.

Bryophytes and the symbiotic microorganisms, the pioneers of vegetation restoration in karst rocky desertification areas in southwestern China

“…Taxonomic analysis revealed that Actinobacteria and Proteobacteria were most abundant across all samples at the phylum level, with relatively stable proportions of 19.54-45.83% and 19.21-31.20%, respectively, which are similar to some previous studies on bryophytes collected from different areas (Ma et al 2017;Tang et al 2016). Additionally, Cyanobacteria, Chloroflexi, Acidobacteria, Bacteroidetes, and Verrucomicrobia were the dominant phyla from the whole areas of two moss species according to relative abundance (> 1% was identified as a dominant bacterium) (Supplemental Fig.…”

“…Nevertheless, exploration of the diversity and community of non-lichenized fungi with bryophytes is still quite limited (Bates et al 2012;Zhang et al 2016;Liu et al 2017). Most of these studies focused on the diversity of mossrelated bacterial communities in deserts, forests, grasslands, and alpine regions, while the structure and function of bryophyte-symbiotic microbial communities in karst rocky desertification habitats have not been reported (Opelt et al 2007;Tang et al 2016;Ma et al 2017). Studies have shown that Proteobacteria and Actinobacteria were the two most abundant phyla associated with mosses under different habitats, and large amounts of unclassified bacteria could interact with the moss.…”

The bias generated by sequencing platforms in analyzing of maternal-neonate gut microbiota profiles and diversity

“…In our study, for low-quality sequence removal rate, it seems that Ion S5-xl platform showed better than Hiseq 2500 platform. For the microbiota analysis, alpha diversity index is usually used to show the diversity within individual, where Chao1, Shannon, simpson, observed_specise, PD_whole_tree, good_coverage are the general index included [18,19,20].There existed significant statistical difference in the alpha diversity index in this study between the two sequencing platforms (P<0.01), except the Shannon index, which is to evaluate the diversity of the bacterial community. As expected, microbial species sequenced by two platforms are basically the same evaluated by Shannon index [21].…”

RNA isolation from taxonomically diverse photosynthetic protists

“…Metatranscriptomic analyses provide insight into current metabolic state of a sample community, but without evidence of enzyme activity or translation (Blazewicz et al ). Combined DNA and RNA analyses lead to more accurate environmental assessments (Dupont et al ; Stecher et al ; Ma et al ).…”

“…Metatranscriptomic analyses provide insight into current metabolic state of a sample community, but without evidence of enzyme activity or translation (Blazewicz et al 2013). Combined DNA and RNA analyses lead to more accurate environmental assessments (Dupont et al 2015;Stecher et al 2016;Ma et al 2017). The effectiveness of molecular biologic procedures involving RNA mostly depends on the integrity, purity, and quantity of the extracted RNA (Santiago-Vazquez et al 2006;Johnson et al 2012).…”