Odriozola Iñaki, Abrego Nerea, Tláskal Vojtěch, Zrůstová Petra, Morais Daniel, Větrovský Tomáš, Ovaskainen Otso, Baldrian Petr
Laboratory of Environmental Microbiology, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic
Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland.
mSystems. 2021 Jan 5;6(1):e01017-20. doi: 10.1128/mSystems.01017-20.
Fungal-bacterial interactions play a key role in the functioning of many ecosystems. Thus, understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. However, it is challenging to disentangle the mechanisms behind species associations from observed co-occurrence patterns, and little is known about the directionality of such interactions. Here, we applied joint species distribution modeling to high-throughput sequencing data on co-occurring fungal and bacterial communities in deadwood to ask whether fungal and bacterial co-occurrences result from shared habitat use (i.e., deadwood's properties) or whether there are fungal-bacterial interactive associations after habitat characteristics are taken into account. Moreover, we tested the hypothesis that the interactions are mainly modulated through fungal communities influencing bacterial communities. For that, we quantified how much the predictive power of the joint species distribution models for bacterial and fungal community improved when accounting for the other community. Our results show that fungi and bacteria form tight association networks (i.e., some species pairs co-occur more frequently and other species pairs co-occur less frequently than expected by chance) in deadwood that include common (or opposite) responses to the environment as well as (potentially) biotic interactions. Additionally, we show that information about the fungal occurrences and abundances increased the power to predict the bacterial abundances substantially, whereas information about the bacterial occurrences and abundances increased the power to predict the fungal abundances much less. Our results suggest that fungal communities may mainly affect bacteria in deadwood. Understanding the interactive dynamics between fungal and bacterial communities is important to gain predictive knowledge on ecosystem functioning. However, little is known about the mechanisms behind fungal-bacterial associations and the directionality of species interactions. Applying joint species distribution modeling to high-throughput sequencing data on co-occurring fungal-bacterial communities in deadwood, we found evidence that nonrandom fungal-bacterial associations derive from shared habitat use as well as (potentially) biotic interactions. Importantly, the combination of cross-validations and conditional cross-validations helped us to answer the question about the directionality of the biotic interactions, providing evidence that suggests that fungal communities may mainly affect bacteria in deadwood. Our modeling approach may help gain insight into the directionality of interactions between different components of the microbiome in other environments.
真菌与细菌的相互作用在许多生态系统的功能发挥中起着关键作用。因此，了解它们的相互作用动态对于获取有关生态系统功能的预测性知识至关重要。然而，从观察到的共现模式中理清物种关联背后的机制具有挑战性，而且对于这种相互作用的方向性知之甚少。在这里，我们将联合物种分布模型应用于枯木中共存的真菌和细菌群落的高通量测序数据，以探究真菌和细菌的共现是源于共享栖息地利用（即枯木的特性），还是在考虑栖息地特征后存在真菌与细菌的相互作用关联。此外，我们检验了这样一个假设，即相互作用主要通过真菌群落影响细菌群落来调节。为此，我们量化了在考虑另一个群落时，联合物种分布模型对细菌和真菌群落的预测能力提高了多少。我们的结果表明，真菌和细菌在枯木中形成了紧密的关联网络（即一些物种对的共现频率高于偶然预期，而其他物种对的共现频率低于偶然预期），其中包括对环境的共同（或相反）反应以及（潜在的）生物相互作用。此外，我们表明，关于真菌出现情况和丰度的信息大幅提高了预测细菌丰度的能力，而关于细菌出现情况和丰度的信息对预测真菌丰度的能力提升则少得多。我们的结果表明，真菌群落可能主要影响枯木中的细菌。了解真菌和细菌群落之间的相互作用动态对于获取有关生态系统功能的预测性知识很重要。然而，对于真菌与细菌关联背后的机制以及物种相互作用的方向性知之甚少。将联合物种分布模型应用于枯木中共存的真菌 - 细菌群落的高通量测序数据，我们发现有证据表明非随机的真菌 - 细菌关联源于共享栖息地利用以及（潜在的）生物相互作用。重要的是，交叉验证和条件交叉验证的结合帮助我们回答了关于生物相互作用方向性的问题，提供了表明真菌群落可能主要影响枯木中细菌的证据。我们的建模方法可能有助于深入了解其他环境中微生物群落不同组成部分之间相互作用的方向性。
