A global network of coexisting microbes from environmental and whole-genome sequence data

Abstract

Microbes are the most abundant and diverse organisms on Earth. In contrast to macroscopic organisms, their environmental preferences and ecological interdependencies remain difficult to assess, requiring laborious molecular surveys at diverse sampling sites. Here, we present a global meta-analysis of previously sampled microbial lineages in the environment. We grouped publicly available 16S ribosomal RNA sequences into operational taxonomic units at various levels of resolution and systematically searched these for co-occurrence across environments. Naturally occurring microbes, indeed, exhibited numerous, significant interlineage associations. These ranged from relatively specific groupings encompassing only a few lineages, to larger assemblages of microbes with shared habitat preferences. Many of the coexisting lineages were phylogenetically closely related, but a significant number of distant associations were observed as well. The increased availability of completely sequenced genomes allowed us, for the first time, to search for genomic correlates of such ecological associations. Genomes from coexisting microbes tended to be more similar than expected by chance, both with respect to pathway content and genome size, and outliers from these trends are discussed. We hypothesize that groupings of lineages are often ancient, and that they may have significantly impacted on genome evolution.

Insights in the ecology and evolutionary history of the Miscellaneous Crenarchaeotic Group lineage

“…Modularity Insights in the ecology and evolutionary history of MCG M Fillol et al analysis revealed a more complex structure (particularly for the saline network) with the presence of six modules (Figure 7c), that is, clusters of OTUs that are highly connected within the module but with very few connections outside the module. In agreement with previous works (Freilich et al, 2010;Chaffron et al, 2010;Faust and Raes, 2012), modules could be considered as ecological and/or functional niches as suggested by modules 4, 5 and 6, which represented freshwater, hypersaline and salinemethanogen sub-networks, respectively. MCG were present in four of the six modules and, interestingly, they systematically co-occurred more often with members of the Thermoplasmata as indicated by the high number of interconnections (that is, indicated by higher degree values; Figure 7d).…”

“…The sediment archaeal network (Figure 7a Insights in the ecology and evolutionary history of MCG M Fillol et al the typical topology for microbial network (Chaffron et al, 2010;Steele et al, 2011;Barberan et al, 2012;Deng et al, 2012): scale-free (that is, node connectivity distribution not different from a power law model, see Supplementary Figure 1), small-world (clustering coefficient of 0.56 and average path length of 3.66) and modular (modularity of 0.55).…”

“…As illustrated by recent studies, microbial co-occurrence patterns can help to unveil ecologically meaningful interactions between species (Horner- Devine et al, 2007;Steele et al, 2011). Network approaches also showed that co-occurring species are often organized into groups, or modules, of functional significance (Chaffron et al, 2010;Barberan et al, 2012;Vick-Majors et al, 2014). After OTU clustering at 90% identity and filtering the data set for optimizing network sensitivity and specificity, network inference was calculated on 99 OTUs distributed across 205 studies.…”

Cross-depth analysis of marine bacterial networks suggests downward propagation of temporal changes

“…Given the complexity of marine microbial networks and our need to quantitatively compare multiple networks, particularly those describing associations at different depths, we leverage various network statistics that are common in social, biological (Albert and Barabási, 2002) and ecological networks (Dunne et al, 2002;Montoya et al, 2006;Olesen et al, 2007;Suweis and D'Odorico, 2014), including microbial ecological ones (Chaffron et al, 2010;Zhou et al, 2010;Kara et al, 2012), but less common in marine microbial ecology. Network topological statistics are used to describe 'global' network properties, and we utilize three related properties to comparatively and globally describe networks: network density, average clustering coefficients and average path length.…”

“…Pairwise association analysis techniques (reviewed in Cram et al, 2014b) have proven to be valuable tools in looking at trends in the many statistical associations in microbial communities in a variety of environments including lake systems (Eiler et al, 2012;Kara et al, 2012), soil (Zhou et al, 2010;Barberán et al, 2011), the human microbiome (Arumugam et al, 2011; and globally through metaanalysis across diverse sampling sites (Chaffron et al, 2010;Freilich et al, 2010). In marine surface waters, studies using pairwise association analysis over time have suggested that the abundance of particular bacteria tend to be best predicted by the abundance of other microorganisms, rather than variability of measured parameters (Fuhrman and Steele, 2008;Steele et al, 2011;Chow et al, 2013Chow et al, , 2014.…”