Network modules and hubs in plant-root fungal biomes

Abstract

Terrestrial plants host phylogenetically and functionally diverse groups of below-ground microbes, whose community structure controls plant growth/ survival in both natural and agricultural ecosystems. Therefore, understanding the processes by which whole root-associated microbiomes are organized is one of the major challenges in ecology and plant science. We here report that diverse root-associated fungi can form highly compartmentalized networks of coexistence within host roots and that the structure of the fungal symbiont communities can be partitioned into semi-discrete types even within a single host plant population. Illumina sequencing of root-associated fungi in a monodominant south beech forest revealed that the network representing symbiont -symbiont co-occurrence patterns was compartmentalized into clear modules, which consisted of diverse functional groups of mycorrhizal and endophytic fungi. Consequently, terminal roots of the plant were colonized by either of the two largest fungal species sets (represented by Oidiodendron or Cenococcum). Thus, species-rich root microbiomes can have alternative community structures, as recently shown in the relationships between human gut microbiome type (i.e. 'enterotype') and host individual health. This study also shows an analytical framework for pinpointing network hubs in symbiont-symbiont networks, leading to the working hypothesis that a small number of microbial species organize the overall root-microbiome dynamics.

Networks Depicting the Fine-Scale Co-Occurrences of Fungi in Soil Horizons

“…The 3,862,747 reads that passed the filtering processes were clustered with a cutoff sequence similarity of 97% in a parallelized process of the Minimus for accurate assembling/clustering [54] as implemented in Claident and the obtained consensus sequences were then used as operational taxonomic units (OTUs) in the following statistical analyses. In the clustering process, reads of each sample were clustered beforehand with a 98% cutoff similarity: the results of the within-sample dereplication was used as guide information in order only to accelerate the 97% clustering process [35, 43]. OTUs whose sequencing reads were less than ten in all the samples were removed because their sequences could contain PCR/sequencing errors [55].…”

“…Those microbiome studies focus on “co-occurrence” patterns of species across sequenced samples: i.e., pairs of species sharing niches and those in positive interactions are expected to co-occur more frequently than expected by chance in the same host (or environmental) samples [31–33]. These co-occurrence analyses have been applied also to community ecological analyses of fungi in plant root systems, highlighting importance of interspecific interactions in the fine-scale assembly processes of fungi [34, 35] (but see [36]). Furthermore, such community-scale analyses allow us to infer how diverse taxonomic/functional groups of fungi structure networks [37, 38] of potential interactions and how those networks are compartmentalized into “modules” [30, 39] of closely associated fungi [35].…”

“…These co-occurrence analyses have been applied also to community ecological analyses of fungi in plant root systems, highlighting importance of interspecific interactions in the fine-scale assembly processes of fungi [34, 35] (but see [36]). Furthermore, such community-scale analyses allow us to infer how diverse taxonomic/functional groups of fungi structure networks [37, 38] of potential interactions and how those networks are compartmentalized into “modules” [30, 39] of closely associated fungi [35]. Although pioneering studies have examined co-occurrence network structure of soil fungal communities [40, 41], it remains a major challenge to understand how functionally diverse fungi are grouped into those co-occurrence network modules.…”

Controls of nitrogen cycling evaluated along a well‐characterized climate gradient

“…While the most parsimonious explanation for these taxonomic patterns likely arise from shared environmental preferences, given the strong gradient here, they may also be driven by positive interactions, such as niche-complementarity or facilitation (Toju et al 2016). Better functional characterization of soil fungi and bacteria (Martiny et al 2015, Treseder and would aid in distinguishing between these different ecological mechanisms.…”

Next-Generation Sequencing in Primate Molecular Ecology

“…。こうした PCR 産物の塩基長をベースとした解析はフラグメント 解析(fragment analysis)と呼ばれ，ゲル電気泳動の代 わりに一塩基レベルまで精度よく自動分離できるキャ ピラリー電気泳動もよく用いられている (Andersen et al, 2003) Lindblad-Toh et al, 2011;Locke et al, 2011;Perry et al, 2012;Prüfer et al, 2012;Scally et al, 2012) (Ley et al, 2008;Muegge et al, 2011;Human Microbiome Project Consortium, 2012;Srivathsan et al, 2015) 。糞以外でも，例 えば口腔スワブ試料に含まれている口腔細菌や，土壌や 水圏に含まれている DNA からその生態系に属する生物 種の同定などで応用されている (Bohmann et al, 2014) (Folmer et al, 1994;CBOL Plant Working Group, 2009;Pompanon et al, 2012;Toju et al, 2016) (Moeller et al, 2012) 。 他にも，菌叢パターンにはホストの系統によって制約 があること (Sanders et al, 2014;Moeller et al, 2016a) ，季 節によって利用できる食物が変動するような環境に生息 している霊長類では，腸内細菌叢も変動するということ Sun et al, 2016;Smits et al, 2017) や， 前胃を持つ葉食性のコロブスは飼育下で消化管疾患にか か り， 腸 内 細 菌 叢 に も 影 響 が 出 る こ と ，群れの中で親和的な関係にある個体間では腸内 細菌叢も類似してくるというネットワークとの関係 (Tung et al, 2015;Moeller et al, 2016b;Perofsky et al, 2017) ， そして飼育下の霊長類は野生とは離れ，西洋食的になっ てしまうことから，菌構成もヒトのようになってしまう こと (Eckburg et al, 2005) Weisburg et al, 1991) (Choo et al, 2015;Flores et al, 2015;Gorzelak et al, 2015;Hale et al, 2015;Song et al, 2016) …”