Limits...
Unexpected diversity during community succession in the apple flower microbiome.

Shade A, McManus PS, Handelsman J - MBio (2013)

Bottom Line: Yet fundamental knowledge of flower-associated microbiotas remains largely unknown.We found unexpected diversity on apple flowers, including a preponderance of taxa affiliated with Deinococcus-Thermus and TM7, phyla that are understudied but thought to be tolerant to an array of environmental stresses.Our results also suggest that changes in microbial community structure on the apple flower may be predictable over the life of the flower, providing the basis for ecological understanding and disease management.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, USA.

ABSTRACT

Unlabelled: Despite its importance to the host, the flower microbiome is poorly understood. We report a culture-independent, community-level assessment of apple flower microbial diversity and dynamics. We collected flowers from six apple trees at five time points, starting before flowers opened and ending at petal fall. We applied streptomycin to half of the trees when flowers opened. Assessment of microbial diversity using tag pyrosequencing of 16S rRNA genes revealed that the apple flower communities were rich and diverse and dominated by members of TM7 and Deinococcus-Thermus, phyla about which relatively little is known. From thousands of taxa, we identified six successional groups with coherent dynamics whose abundances peaked at different times before and after bud opening. We designated the groups Pioneer, Early, Mid, Late, Climax, and Generalist communities. The successional pattern was attributed to a set of prevalent taxa that were persistent and gradually changing in abundance. These taxa had significant associations with other community members, as demonstrated with a cooccurrence network based on local similarity analysis. We also detected a set of less-abundant, transient taxa that contributed to general tree-to-tree variability but not to the successional pattern. Communities on trees sprayed with streptomycin had slightly lower phylogenetic diversity than those on unsprayed trees but did not differ in structure or succession. Our results suggest that changes in apple flower microbial community structure are predictable over the life of the flower, providing a basis for ecological understanding and disease management.

Importance: Flowering plants (angiosperms) represent a diverse group of an estimated 400,000 species, and their successful cultivation is essential to agriculture. Yet fundamental knowledge of flower-associated microbiotas remains largely unknown. Even less well understood are the changes that flower microbial communities experience through time. Flowers are particularly conducive to comprehensive temporal studies because they are, by nature, ephemeral organs. Here, we present the first culture-independent time series of bacterial and archaeal communities associated with the flowers of apple, an economically important crop. We found unexpected diversity on apple flowers, including a preponderance of taxa affiliated with Deinococcus-Thermus and TM7, phyla that are understudied but thought to be tolerant to an array of environmental stresses. Our results also suggest that changes in microbial community structure on the apple flower may be predictable over the life of the flower, providing the basis for ecological understanding and disease management.

Show MeSH

Related in: MedlinePlus

Characteristics of community structure that contribute to changes in beta diversity though time. (a) Prevalent members of the community are detected often (persistent through time and prevalent across trees), while rare members are detected infrequently (transient). Each OTU is a point, the blue line is the log-linear model (adjusted r2 = 0.68, slope = 6.49, P < 0.001), and gray shading represents the standard error. Percent occurrence is out of 30 total observations (six trees and five sampling times). (b) Partition of temporal beta diversity (measured as Sørenson’s similarity [Sor]; blue) into components that represent taxa replacement (Simpson’s similarity [Sim]; green) and nestedness (Nes; red). Each point is multivariate community similarity calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less prevalent OTUs. The line is an average across the trees; gray shading represents the standard error. (c) Prevalent members of the community are detected often (persistent), while rare members are detected infrequently (transient). Each OTU is a point, the color shows the tree in which the OTU was detected, and the lines are the log-linear models for each tree (all adjusted r2 values are >0.45, slopes range between 3.99 and 5.01, all P values are <0.001). Percent occurrence is out of five time points per tree. (d) Nestedness metric based on overlap and decreasing fill (NODF). Each point is calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less-prevalent members. The line is an average across the trees; gray shading represents the standard error.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3585449&req=5

fig7: Characteristics of community structure that contribute to changes in beta diversity though time. (a) Prevalent members of the community are detected often (persistent through time and prevalent across trees), while rare members are detected infrequently (transient). Each OTU is a point, the blue line is the log-linear model (adjusted r2 = 0.68, slope = 6.49, P < 0.001), and gray shading represents the standard error. Percent occurrence is out of 30 total observations (six trees and five sampling times). (b) Partition of temporal beta diversity (measured as Sørenson’s similarity [Sor]; blue) into components that represent taxa replacement (Simpson’s similarity [Sim]; green) and nestedness (Nes; red). Each point is multivariate community similarity calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less prevalent OTUs. The line is an average across the trees; gray shading represents the standard error. (c) Prevalent members of the community are detected often (persistent), while rare members are detected infrequently (transient). Each OTU is a point, the color shows the tree in which the OTU was detected, and the lines are the log-linear models for each tree (all adjusted r2 values are >0.45, slopes range between 3.99 and 5.01, all P values are <0.001). Percent occurrence is out of five time points per tree. (d) Nestedness metric based on overlap and decreasing fill (NODF). Each point is calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less-prevalent members. The line is an average across the trees; gray shading represents the standard error.

Mentions: Because community structure varied over time (Fig. 3b) and 90% of the OTUs were represented by fewer than 50 sequences (Fig. 2), we hypothesized that the less-abundant OTUs were also transient, or detected at relatively few points in the series. Transient organisms may be those that arrive on flowers but do not successfully colonize. We found a relationship between persistence (the consistency in detecting a taxon through time) and prevalence (the abundance of a taxon) such that transient OTUs also tended to have low abundance (Fig. 7a and c). This suggests that at each time point, rare, transient OTUs were replaced in the community by other transient OTUs, indicating high community turnover. Prevalent OTUs were more often persistent (Fig. 7a and c) and increased and decreased in abundance gradually (Fig. 5). Therefore, the persistent and prevalent OTUs changed over time, contributing to successional patterns (Fig. 5). Many prevalent OTUs were affiliated with Deinococcus-Thermus, TM7, and Bacteriodetes, and many rare OTUs were affiliated with Proteobacteria and Actinobacteria (Fig. 6).


Unexpected diversity during community succession in the apple flower microbiome.

Shade A, McManus PS, Handelsman J - MBio (2013)

Characteristics of community structure that contribute to changes in beta diversity though time. (a) Prevalent members of the community are detected often (persistent through time and prevalent across trees), while rare members are detected infrequently (transient). Each OTU is a point, the blue line is the log-linear model (adjusted r2 = 0.68, slope = 6.49, P < 0.001), and gray shading represents the standard error. Percent occurrence is out of 30 total observations (six trees and five sampling times). (b) Partition of temporal beta diversity (measured as Sørenson’s similarity [Sor]; blue) into components that represent taxa replacement (Simpson’s similarity [Sim]; green) and nestedness (Nes; red). Each point is multivariate community similarity calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less prevalent OTUs. The line is an average across the trees; gray shading represents the standard error. (c) Prevalent members of the community are detected often (persistent), while rare members are detected infrequently (transient). Each OTU is a point, the color shows the tree in which the OTU was detected, and the lines are the log-linear models for each tree (all adjusted r2 values are >0.45, slopes range between 3.99 and 5.01, all P values are <0.001). Percent occurrence is out of five time points per tree. (d) Nestedness metric based on overlap and decreasing fill (NODF). Each point is calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less-prevalent members. The line is an average across the trees; gray shading represents the standard error.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3585449&req=5

fig7: Characteristics of community structure that contribute to changes in beta diversity though time. (a) Prevalent members of the community are detected often (persistent through time and prevalent across trees), while rare members are detected infrequently (transient). Each OTU is a point, the blue line is the log-linear model (adjusted r2 = 0.68, slope = 6.49, P < 0.001), and gray shading represents the standard error. Percent occurrence is out of 30 total observations (six trees and five sampling times). (b) Partition of temporal beta diversity (measured as Sørenson’s similarity [Sor]; blue) into components that represent taxa replacement (Simpson’s similarity [Sim]; green) and nestedness (Nes; red). Each point is multivariate community similarity calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less prevalent OTUs. The line is an average across the trees; gray shading represents the standard error. (c) Prevalent members of the community are detected often (persistent), while rare members are detected infrequently (transient). Each OTU is a point, the color shows the tree in which the OTU was detected, and the lines are the log-linear models for each tree (all adjusted r2 values are >0.45, slopes range between 3.99 and 5.01, all P values are <0.001). Percent occurrence is out of five time points per tree. (d) Nestedness metric based on overlap and decreasing fill (NODF). Each point is calculated for a time series from one tree, and the analysis was repeated for each of six trees and at various levels of cutoff to remove less-prevalent members. The line is an average across the trees; gray shading represents the standard error.
Mentions: Because community structure varied over time (Fig. 3b) and 90% of the OTUs were represented by fewer than 50 sequences (Fig. 2), we hypothesized that the less-abundant OTUs were also transient, or detected at relatively few points in the series. Transient organisms may be those that arrive on flowers but do not successfully colonize. We found a relationship between persistence (the consistency in detecting a taxon through time) and prevalence (the abundance of a taxon) such that transient OTUs also tended to have low abundance (Fig. 7a and c). This suggests that at each time point, rare, transient OTUs were replaced in the community by other transient OTUs, indicating high community turnover. Prevalent OTUs were more often persistent (Fig. 7a and c) and increased and decreased in abundance gradually (Fig. 5). Therefore, the persistent and prevalent OTUs changed over time, contributing to successional patterns (Fig. 5). Many prevalent OTUs were affiliated with Deinococcus-Thermus, TM7, and Bacteriodetes, and many rare OTUs were affiliated with Proteobacteria and Actinobacteria (Fig. 6).

Bottom Line: Yet fundamental knowledge of flower-associated microbiotas remains largely unknown.We found unexpected diversity on apple flowers, including a preponderance of taxa affiliated with Deinococcus-Thermus and TM7, phyla that are understudied but thought to be tolerant to an array of environmental stresses.Our results also suggest that changes in microbial community structure on the apple flower may be predictable over the life of the flower, providing the basis for ecological understanding and disease management.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, USA.

ABSTRACT

Unlabelled: Despite its importance to the host, the flower microbiome is poorly understood. We report a culture-independent, community-level assessment of apple flower microbial diversity and dynamics. We collected flowers from six apple trees at five time points, starting before flowers opened and ending at petal fall. We applied streptomycin to half of the trees when flowers opened. Assessment of microbial diversity using tag pyrosequencing of 16S rRNA genes revealed that the apple flower communities were rich and diverse and dominated by members of TM7 and Deinococcus-Thermus, phyla about which relatively little is known. From thousands of taxa, we identified six successional groups with coherent dynamics whose abundances peaked at different times before and after bud opening. We designated the groups Pioneer, Early, Mid, Late, Climax, and Generalist communities. The successional pattern was attributed to a set of prevalent taxa that were persistent and gradually changing in abundance. These taxa had significant associations with other community members, as demonstrated with a cooccurrence network based on local similarity analysis. We also detected a set of less-abundant, transient taxa that contributed to general tree-to-tree variability but not to the successional pattern. Communities on trees sprayed with streptomycin had slightly lower phylogenetic diversity than those on unsprayed trees but did not differ in structure or succession. Our results suggest that changes in apple flower microbial community structure are predictable over the life of the flower, providing a basis for ecological understanding and disease management.

Importance: Flowering plants (angiosperms) represent a diverse group of an estimated 400,000 species, and their successful cultivation is essential to agriculture. Yet fundamental knowledge of flower-associated microbiotas remains largely unknown. Even less well understood are the changes that flower microbial communities experience through time. Flowers are particularly conducive to comprehensive temporal studies because they are, by nature, ephemeral organs. Here, we present the first culture-independent time series of bacterial and archaeal communities associated with the flowers of apple, an economically important crop. We found unexpected diversity on apple flowers, including a preponderance of taxa affiliated with Deinococcus-Thermus and TM7, phyla that are understudied but thought to be tolerant to an array of environmental stresses. Our results also suggest that changes in microbial community structure on the apple flower may be predictable over the life of the flower, providing the basis for ecological understanding and disease management.

Show MeSH
Related in: MedlinePlus