Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China

Ma, Bin; Wang, Haizhen; Dsouza, Melissa; Lou, Jun; He, Yan; Dai, Zhongmin; Brookes, Philip C.; Xu, Jianming; Gilbert, Jack A.

doi:10.1038/ismej.2015.261

Cited by 876 publications

(579 citation statements)

References 43 publications

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“…Cooccurrence analyses have recently been increasingly used in microbial ecology to better understand community structure, characterize potential intracommunity interactions, and identify potentially shared and contrasting niches (89,90). The cooccurrence network analysis in this study was performed with the igraph R package (91).…”

Section: Methodsmentioning

confidence: 99%

Soil Bacterial and Fungal Communities Show Distinct Recovery Patterns during Forest Ecosystem Restoration

Sun

Song

Avera

et al. 2017

Appl Environ Microbiol

202

109

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Bacteria and fungi are important mediators of biogeochemical processes and play essential roles in the establishment of plant communities, which makes knowledge about their recovery after extreme disturbances valuable for understanding ecosystem development. However, broad ecological differences between bacterial and fungal organisms, such as growth rates, stress tolerance, and substrate utilization, suggest they could follow distinct trajectories and show contrasting dynamics during recovery. In this study, we analyzed both the intra-annual variability and decade-scale recovery of bacterial and fungal communities in a chronosequence of reclaimed mined soils using next-generation sequencing to quantify their abundance, richness, ␤-diversity, taxonomic composition, and cooccurrence network properties. Bacterial communities shifted gradually, with overlapping ␤-diversity patterns across chronosequence ages, while shifts in fungal communities were more distinct among different ages. In addition, the magnitude of intra-annual variability in bacterial ␤-diversity was comparable to the changes across decades of chronosequence age, while fungal communities changed minimally across months. Finally, the complexity of bacterial cooccurrence networks increased with chronosequence age, while fungal networks did not show clear age-related trends. We hypothesize that these contrasting dynamics of bacteria and fungi in the chronosequence result from (i) higher growth rates for bacteria, leading to higher intra-annual variability; (ii) higher tolerance to environmental changes for fungi; and (iii) stronger influence of vegetation on fungal communities. IMPORTANCE Both bacteria and fungi play essential roles in ecosystem functions, and information about their recovery after extreme disturbances is important for understanding whole-ecosystem development. Given their many differences in phenotype, phylogeny, and life history, a comparison of different bacterial and fungal recovery patterns improves the understanding of how different components of the soil microbiota respond to ecosystem recovery. In this study, we highlight key differences between soil bacteria and fungi during the restoration of reclaimed mine soils in the form of long-term diversity patterns, intra-annual variability, and potential interaction networks. Cooccurrence networks revealed increasingly complex bacterial community interactions during recovery, in contrast to much simpler and more isolated fungal network patterns. This study compares bacterial and fungal cooccurrence networks and reveals cooccurrences persisting through successional ages.KEYWORDS bacteria, chronosequence, cooccurrence networks, disturbance, fungi, reclaimed mine soils, soil microbiota E cologists have been studying the succession dynamics of plant communities for more than a century (1, 2), and the patterns of changes in plant community composition are used as indicators for the restoration of ecosystems (3-5). However,

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Section: Methodsmentioning

confidence: 99%

Soil Bacterial and Fungal Communities Show Distinct Recovery Patterns during Forest Ecosystem Restoration

Sun

Song

Avera

et al. 2017

Appl Environ Microbiol

202

109

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“…Moreover, reliable assignment of DNA sequences to named taxonomic units (Schloss & Westcott 2011;Creer et al 2016) and ecological interpretation of the resulting highly complex community data (e.g. Ma et al 2016) also present challenges. As is typical for the initial uptake of any technology, early applications (e.g.…”

Section: Future Research Directionsmentioning

confidence: 99%

Using DNA meta barcoding to assess New Zealand's terrestrial biodiversity

Holdaway¹,

Wood²,

Dickie³

et al. 2017

NZ J Ecol

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High throughput DNA sequencing technology has enabled entire biological communities to be characterised from DNA derived from pools of organisms, such as bulk-collected invertebrates, or DNA extracted from environmental samples (e.g. soil). These DNA-based techniques have the potential to revolutionise biodiversity monitoring. One approach in particular, DNA metabarcoding, can provide unprecedented taxonomic breadth at a scale not practically achievable through the morphological identification of individual organisms. Here, we assess the current strengths and weaknesses of DNA metabarcoding techniques for biodiversity assessment. We argue that it is essential to integrate conventional monitoring methods with novel DNA methods, to validate methods, and to better use and interpret data. We present a conceptual framework for how this might be done, explore potential applications within national biodiversity assessment frameworks, Maori biodiversity monitoring and the primary sector, and highlight areas of current uncertainty and future research directions. Rapid developments in DNA sequencing technology and bioinformatics will make DNA-based community data increasingly accessible to ecologists, and there needs to be a corresponding shift in research focus from DNA metabarcoding method development and evaluation to real-world applications that provide rich information for a range of purposes, including conservation planning and land management decisions.

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“…Network analyses-based approaches have recently been used to investigate co-occurrence patterns between microorganisms in complex environments ranging from the human gut to oceans and soils (Ma et al, 2016). MetaAmp also constructs meta-community co-occurrence networks based on Spearman or Pearson correlation coefficients and P-values.…”

Section: Metaamp Pipeline Implementationmentioning

confidence: 99%

Fast and simple analysis of MiSeq amplicon sequencing data with MetaAmp

Dong

Kleiner

Sharp

et al. 2017

Preprint

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Microbial community profiling by barcoded 16S rRNA gene amplicon sequencing currently has many applications in microbial ecology. The low costs of the parallel sequencing of multiplexed samples, combined with the relative ease of data processing and interpretation (compared to shotgun metagenomes) have made this an entry-level approach. Here we present the MetaAmp pipeline for processing of SSU rRNA gene and other non-coding or protein-coding amplicon sequencing data by investigators that are inexperienced with bioinformatics procedures. It accepts single-end or paired-end sequences in fasta or fastq format from various sequencing platforms. It includes read quality control, and merging of forward and reverse reads of paired-end reads. It makes use of UPARSE, Mothur, and the SILVA database for clustering, removal of chimeric reads, taxonomic classification, and generation of diversity metrics. The pipeline has been validated with a mock community of known composition. MetaAmp provides a convenient web interface as well as command line interface. It is freely available at: http://ebg.ucalgary.ca/metaamp. Since its launch 2 years ago, MetaAmp has been used >2,800 times, by many users worldwide.

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Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China

Cited by 876 publications

References 43 publications

Soil Bacterial and Fungal Communities Show Distinct Recovery Patterns during Forest Ecosystem Restoration

Soil Bacterial and Fungal Communities Show Distinct Recovery Patterns during Forest Ecosystem Restoration

Using DNA meta barcoding to assess New Zealand's terrestrial biodiversity

Fast and simple analysis of MiSeq amplicon sequencing data with MetaAmp

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