Dataset Information

FusionDB: assessing microbial diversity and environmental preferences via functional similarity networks.

ABSTRACT: Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same environmental niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ more across environments than across taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly link microbial functions to the environment. We previously developed a method for comparing microbial functional similarities on the basis of proteins translated from their sequenced genomes. Here, we describe fusionDB, a novel database that uses our functional data to represent 1374 taxonomically distinct bacteria annotated with available metadata: habitat/niche, preferred temperature, and oxygen use. Each microbe is encoded as a set of functions represented by its proteome and individual microbes are connected via common functions. Users can search fusionDB via combinations of organism names and metadata. Moreover, the web interface allows mapping new microbial genomes to the functional spectrum of reference bacteria, rendering interactive similarity networks that highlight shared functionality. fusionDB provides a fast means of comparing microbes, identifying potential horizontal gene transfer events, and highlighting key environment-specific functionality.

SUBMITTER: Zhu C

PROVIDER: S-EPMC5753390 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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fusionDB: assessing microbial diversity and environmental preferences via functional similarity networks.

Zhu Chengsheng C Mahlich Yannick Y Miller Maximilian M Bromberg Yana Y

Nucleic acids research 20180101 D1

Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same environmental niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ more across environments than across taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly link microbial functions to the environment. We previously dev ...[more]

PMID: 29112720

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Project description:BackgroundEcological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not.ResultsWe present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges-87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors.ConclusionsTo reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses. Video abstract.

Project description:It is a central ecological goal to explore the effects of global change factors on soil microbial communities. The vast functional gene repertoire of soil microbial communities is composed of both core and accessory genes, which may be governed by distinct drivers. This intuitive hypothesis, however, remains largely unexplored. We conducted a 5-year nitrogen and water addition experiment in the Eurasian steppe and quantified microbial gene diversity via shotgun metagenomics. Nitrogen addition led to an 11-fold increase in the abundance (based on quantitative PCR [qPCR]) of ammonia-oxidizing bacteria, which have mainly core community genes and few accessory community genes. Thus, nitrogen addition substantially increased the relative abundance of many core genes at the whole-community level. Water addition stimulated both plant diversity and microbial respiration; however, increased carbon/energy resources from plants did not counteract increased respiration, so soil carbon/energy resources became more limited. Thus, water addition selected for microorganisms with genes responsible for degrading recalcitrant soil organic matter. Accordingly, many other microorganisms without these genes (but likely with other accessory community genes due to relatively stable average microbial genome size) were selected against, leading to the decrease in the diversity of accessory community genes. In summary, nitrogen addition primarily affected core community genes through nitrogen-cycling processes, and water addition primarily regulated accessory community genes through carbon-cycling processes. Although both gene components may significantly respond as the intensity of nitrogen/water addition increases, our results demonstrated how these common global change factors distinctly impact each component.IMPORTANCE Our results demonstrated increased ecosystem nitrogen and water content as the primary drivers of the core and accessory components of soil microbial community functional diversity, respectively. Our findings suggested that more attention should be paid to certain components of community functional diversity under specific global change conditions. Our findings also indicated that microbial communities have adapted to nitrogen addition by strengthening the function of ammonia oxidization to deplete the excess nitrogen, thus maintaining ecosystem homeostasis. Because community gene richness is primarily determined by the presence/absence of accessory community genes, our findings further implied that strategies such as maintaining the amount of soil organic matter could be adopted to effectively improve the functional gene diversity of soil microbial communities subject to global change factors.

Dataset Information

FusionDB: assessing microbial diversity and environmental preferences via functional similarity networks.

Publications

fusionDB: assessing microbial diversity and environmental preferences via functional similarity networks.

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