Analysis of microbial diversity by pyrosequencing the small-subunit ribosomal RNA without PCR amplification

The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications

Similar to other organisms, plants establish interactions with a variety of microorganisms in their natural environment. The plant microbiome occupies the host plant's tissues, either internally or on its surfaces, showing interactions that can assist in its growth, development, and adaptation to face environmental stresses. The advance of metagenomics and metatranscriptomics approaches has strongly driven the study and recognition of plant microbiome impacts. Research in this regard provides comprehensive information about the taxonomic and functional aspects of microbial plant communities, contributing to a better understanding of their dynamics. Evidence of the plant microbiome's functional potential has boosted its exploitation to develop more ecological and sustainable agricultural practices that impact human health. Although microbial inoculants' development and use are promising to revolutionize crop production, interdisciplinary studies are needed to identify new candidates and promote effective practical applications. On the other hand, there are challenges in understanding and analyzing complex data generated within a plant microbiome project's scope. This review presents aspects about the complex structuring and assembly of the microbiome in the host plant's tissues, metagenomics, and metatranscriptomics approaches for its understanding, covering descriptions of recent studies concerning metagenomics to characterize the microbiome of non-model plants under different aspects. Studies involving bio-inoculants, isolated from plant microbial communities, capable of assisting in crops' productivity, are also reviewed.

A Modified Low-quantity RNA-Seq Method for Microbial Community and Diversity Analysis Using Small Subunit Ribosomal RNA

We propose a modified RNA-Seq method for small subunit ribosomal RNA (SSU rRNA)-based microbial community analysis that depends on the direct ligation of a 5' adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10-100 ng) and does not require a DNA removal step. Using this method, we could obtain more 16S rRNA sequences of the same regions (variable regions V1-V2) without the interference of DNA in order to analyze OTU (operational taxonomic unit)-based microbial communities and diversity. The generated SSU rRNA sequences are also suitable for the coverage evaluation for bacterial universal primer 8F (Escherichia coli position 8 to 27), which is commonly used for bacterial 16S rRNA gene amplification. The modified RNA-Seq method will be useful to determine potentially active microbial community structures and diversity for various environmental samples, and will also be useful for identifying novel microbial taxa.

Microbial Communities and Diversities in Mudflat Sediments Analyzed Using a Modified Metatranscriptomic Method

Intertidal mudflats are land–sea interaction areas and play important roles in global nutrient cycles. However, a comprehensive understanding of microbial communities in these mudflats remains elusive. In this study, mudflat sediment samples from the Dongtan wetland of Chongming Island, the largest alluvial island in the world, were collected. Using a modified metatranscriptomic method, the depth-wise distributions of potentially active microbial communities were investigated based on small subunit ribosomal RNA (SSU rRNA) sequences. Multiple environmental factors were also measured and analyzed in conjunction with the prokaryotic composition profiles. A prokaryotic diversity analysis based on the metatranscriptome datasets revealed two or threefold higher diversity indices (associated with potentially active microbes participating in biogeochemical processes in Dongtan) compared with the diversity indices based on 16S rRNA gene amplicons. Bacteria were numerically dominant relative to archaea, and the potentially active prokaryotic taxa were mostly assigned to the bacterial phyla Chloroflexi, Acidobacteria, and Bacteroidetes and the classes Delta- and Gamma-proteobacteria, along with the archaeal lineages phylum Bathyarchaeota and the order Thermoplasmatales. The total nitrogen and carbon content of the sediment samples were environmental factors that significantly affected the depth-wise distributions of both bacterial and archaeal communities. Furthermore, the activity of potentially active taxa (including the prevalent order Desulfobacterales and family Anaerolineaceae) appeared to be significantly underestimated by PCR-based methods, notably at the DNA level, and indicates that using normal PCR amplification of DNA limits the study of potential microbial activity. This is the first study of potentially active microbial communities in depth-wise sediments from Dongtan. The improved knowledge of microbial communities in Dongtan provides a foundation for exploring biogeochemical cycling and microbial functions.

Modified RNA-seq method for microbial community and diversity analysis using rRNA in different types of environmental samples

RNA-seq-based SSU (small subunit) rRNA (ribosomal RNA) analysis has provided a better understanding of potentially active microbial community within environments. However, for RNA-seq library construction, high quantities of purified RNA are typically required. We propose a modified RNA-seq method for SSU rRNA-based microbial community analysis that depends on the direct ligation of a 5’ adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10–100 ng) and does not require a DNA removal step. The method was initially tested on three mock communities synthesized with enriched SSU rRNA of archaeal, bacterial and fungal isolates at different ratios, and was subsequently used for environmental samples of high or low biomass. For high-biomass salt-marsh sediments, enriched SSU rRNA and total nucleic acid-derived RNA-seq datasets revealed highly consistent community compositions for all of the SSU rRNA sequences, and as much as 46.4%-59.5% of 16S rRNA sequences were suitable for OTU (operational taxonomic unit)-based community and diversity analyses with complete coverage of V1-V2 regions. OTU-based community structures for the two datasets were also highly consistent with those determined by all of the 16S rRNA reads. For low-biomass samples, total nucleic acid-derived RNA-seq datasets were analyzed, and highly active bacterial taxa were also identified by the OTU-based method, notably including members of the previously underestimated genus Nitrospira and phylum Acidobacteria in tap water, members of the phylum Actinobacteria on a shower curtain, and members of the phylum Cyanobacteria on leaf surfaces. More than half of the bacterial 16S rRNA sequences covered the complete region of primer 8F, and non-coverage rates as high as 38.7% were obtained for phylum-unclassified sequences, providing many opportunities to identify novel bacterial taxa. This modified RNA-seq method will provide a better snapshot of diverse microbial communities, most notably by OTU-based analysis, even communities with low-biomass samples.

MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples.

Rheology and Microbiology of Sludge from a Thermophilic Aerobic Membrane Reactor

A thermophilic aerobic membrane reactor (TAMR) treating high-strength COD liquid wastes was submitted to an integrated investigation, with the aim of characterizing the biomass and its rheological behaviour. These processes are still scarcely adopted, also because the knowledge of their biology as well as of the physical-chemical properties of the sludge needs to be improved. In this paper, samples of mixed liquor were taken from a TAMR and submitted to fluorescent in situ hybridization for the identification and quantification of main bacterial groups. Measurements were also targeted at flocs features, filamentous bacteria, and microfauna, in order to characterize the sludge. The studied rheological properties were selected as they influence significantly the performances of membrane bioreactors (MBR) and, in particular, of the TAMR systems that operate under thermophilic conditions (i.e., around 50°C) with high MLSS concentrations (up to 200 gTS L−1). The proper description of the rheological behaviour of sludge represents a useful and fundamental aspect that allows characterizing the hydrodynamics of sludge suspension devoted to the optimization of the related processes. Therefore, in this study, the effects on the sludge rheology produced by the biomass concentration, pH, temperature, and aeration were analysed.

Characterising the Canine Oral Microbiome by Direct Sequencing of Reverse-Transcribed rRNA Molecules

PCR amplification and sequencing of phylogenetic markers, primarily Small Sub-Unit ribosomal RNA (SSU rRNA) genes, has been the paradigm for defining the taxonomic composition of microbiomes. However, ‘universal’ SSU rRNA gene PCR primer sets are likely to miss much of the diversity therein. We sequenced a library comprising purified and reverse-transcribed SSU rRNA (RT-SSU rRNA) molecules from the canine oral microbiome and compared it to a general bacterial 16S rRNA gene PCR amplicon library generated from the same biological sample. In addition, we have developed BIONmeta, a novel, open-source, computer package for the processing and taxonomic classification of the randomly fragmented RT-SSU rRNA reads produced. Direct RT-SSU rRNA sequencing revealed that 16S rRNA molecules belonging to the bacterial phyla Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria and Spirochaetes, were most abundant in the canine oral microbiome (92.5% of total bacterial SSU rRNA). The direct rRNA sequencing approach detected greater taxonomic diversity (1 additional phylum, 2 classes, 1 order, 10 families and 61 genera) when compared with general bacterial 16S rRNA amplicons from the same sample, simultaneously provided SSU rRNA gene inventories of Bacteria, Archaea and Eukarya, and detected significant numbers of sequences not recognised by ‘universal’ primer sets. Proteobacteria and Spirochaetes were found to be under-represented by PCR-based analysis of the microbiome, and this was due to primer mismatches and taxon-specific variations in amplification efficiency, validated by qPCR analysis of 16S rRNA amplicons from a mock community. This demonstrated the veracity of direct RT-SSU rRNA sequencing for molecular microbial ecology.

Effect of fumigation with 1,3-dichloropropene on soil bacterial communities

1,3-Dichloropropene (1,3-D) is a potential candidate as a soil fumigant because of the restriction of methyl bromide (MB) in soil fumigation. So far, little is known about the bacteria diversity in 1,3-D fumigated soil. Therefore, the impact of 1,3-D on soil bacterial community was determined by the 16S rRNA gene amplicon 454 sequencing. A total of 230,617 valid reads and 19,366 OTUs were obtained from the thirteen samples. 454 sequencing results revealed that Proteobacteria, Bacteroidetes, Actinobacteria, Acidobacteria and Firmicutes were predominant phylum in soils. Bacterial diversity was affected initially, while recovered in the later treatments and soils from 1,3-D treatment plots had a higher bacterial diversity. The results of this study demonstrated that 1,3-D had only a short-term and transitory impact on the indigenous soil microbial community. Our study would provide useful information for evaluating ecological safety of 1,3-D in China.