Phyllosphere microbial associations improve plant reproductive success
Data files
Nov 17, 2023 version files 1.27 MB
Abstract
The above-ground (phyllosphere) plant microbiome is increasingly recognized as an important component of plant health. We hypothesized that phyllosphere bacterial recruitment may be disrupted in a greenhouse setting, and that adding a bacterial amendment would therefore benefit the health and growth of host plants. Using a newly developed synthetic phyllosphere bacterial microbiome for tomato (Solanum lycopersicum), we tested this hypothesis across multiple trials by manipulating microbial inoculation of leaves and measuring subsequent plant growth and reproductive success, comparing results from plants grown in both greenhouse and field settings. We confirmed that greenhouse-grown plants have a relatively depauperate phyllosphere bacterial microbiome, which both makes them an ideal system for testing the impact of phyllosphere communities on plant health and important targets for microbial amendments as we move towards increased agricultural sustainability. We find that the addition of the synthetic microbial community early in greenhouse growth leads to an increase in fruit production in this setting, implicating the phyllosphere microbiome as a key component of plant fitness and emphasizing the role that these bacterial microbiomes likely play in the ecology and evolution of plant communities.
README: Phyllosphere microbial associations improve plant reproductive success
These data represent the processed sequencing data (mostly in the form of phyloseq objects) and the greenhouse and field tomato plant harvest results associated with the study. Data includes sequencing results, with both bacterial absolute and relative abundance, as well as tomato number, and tomato weight, either as weight per tomato or weight harvested per plant.
Description of the data and file structure
Data is presented as one of two file types, either a .csv
or a .rds
. Most sequencing related data is presented as .rds
files, which must be loaded into R in order to be utilized. Further, these data are formatted as phyloseq
objects, and require the package phyloseq
in order to be processed. Some sequencing related data (ie. absolute, Trial_1_Greenhouse_Bacterial_Abundance.csv
, and relative abundance, Trial_3_Greenhouse_and_Field_Bacterial_Abundance.csv
) are .csv
files.
All of the greenhouse and field related data (tomato counts and weights) are presented as .csv
files.
Data can be cross referenced with the .html
R code provided with the paper as follows, with information on column naming included below:
- Trial_1_Greenhouse_Bacterial_Abundance.csv
Treatment
: Bacterial treatment applied; Control -> No bacteria, PhylloStart -> PhylloStart Community appliedSample_ID
: Unique sample ID per plantTotalAbundance
: Total calculated abundance from qPCR of bacterial reads
- Trial_3_Greenhouse_and_Field_Bacterial_Abundance.csv
Bacteria
: Bacterial treatment applied; Control -> No bacteria, Low -> PhylloStart Community applied at OD600=0.0002 density, High -> PhylloStart Community applied at OD600=0.02 densitySample
: Unique sample ID per plantLocation
: Whether plant was sampled from field or greenhouseTotalSynComAbundance
: Relative abundance of SynCom associated ASVs
- Trial_2_Greenhouse_Fruit_Count.csv
ID
: Unique sample ID per plantTreatment
: Bacterial and Azomite treatment applied (somewhat redundant with next two columns)Bacteria
: Bacterial treatment; Control -> No bacteria, Bacteria -> PhylloStart Community appliedAzomite
: Azomite treatment (concentration applied in grams)Total_Fruit
: Number of fruit produced per plant
- Trial_3_Greenhouse_Fruit_Count.csv
Plant_ID
: Unique sample ID per plantID
: Bacterial and Azomite treatment appliedTreatment
: Bacterial density applied; Control -> No bacteria, Phyllostart Low -> PhylloStart Community applied at OD600=0.0002 density, Phyllostart High -> PhylloStart Community applied at OD600=0.02 densityAzomite_g
: Azomite treatment (concentration applied in grams)Total_Fruit
: Number of fruit produced per plant
- Trial_3_Field_Fruit_Count.csv
Plant Number
: Unique sample ID per plantBacteria
: Bacterial density applied; No_Bac -> No bacteria, B_low -> PhylloStart Community applied at OD600=0.0002 density, B -> PhylloStart Community applied at OD600=0.02 densityAzomite_con
: Azomite treatment (concentration applied in grams)Total_Fruit
: Number of fruit produced per plant
- Pathogen_Invasion_Experiment_CFU_Counts.csv
fertilizer
: Nutrient treatment; Low -> No fertilizer applied, High -> Fertilizer appliedinocula
: PhylloStart/SynCom treatment; Buffer -> No bacteria applied, Syncom -> PhylloStart appliedCFU_1
: First replicate CFU countCFU_2
: Second replicate CFU countCFU_avg
: Average of both counts
- Trial_2_Greenhouse_Fruit_Weights.csv
ID
: Unique sample ID per plantTreatment
: Bacterial and Azomite treatment applied (somewhat redundant with next two columns)Bacteria
: Bacterial treatment; Control -> No bacteria, Bacteria -> PhylloStart Community appliedAzomite
: Azomite treatment (concentration applied in grams)Average_Weight
: Average weight of individual fruit produced per plant in grams
- Trial_3_Greenhouse_Fruit_Weights.csv
Plant_ID
: Unique sample ID per plantID
: Bacterial and Azomite treatment appliedTreatment
: Bacterial density applied; Control -> No bacteria, Phyllostart Low -> PhylloStart Community applied at OD600=0.0002 density, Phyllostart High -> PhylloStart Community applied at OD600=0.02 densityAzomite_g
: Azomite treatment (concentration applied in grams)Average_Weight
: Average weight of individual fruit produced per plant in grams
- Trial_3_Field_Fruit_Weights.csv
Plant Number
: Unique sample ID per plantTomatoes
: Total number of fruit produced per plantFull_ID
: All treatments concatenatedBacteria
: Bacterial density applied; No_Bac -> No bacteria, B_low -> PhylloStart Community applied at OD600=0.0002 density, B -> PhylloStart Community applied at OD600=0.02 densityAzomite
: Was Azomite applied or not?; Azo -> Yes, Control -> NoAzomite_con
: Azomite treatment (concentration applied in grams)Row
: Row in the field plant was located atTotal_Weight_kg
: Total weight of harvest per plant in kgTotal_Fruit
: Number of fruit produced per plant
- Supplemental_Trial_Fruit_Weight.csv
Plant_ID
: Unique sample ID per plantBacteria
: Bacterial treatment, PhylloStart or ControlAzomite
: Was Azomite applied or not?; Azo -> Yes, Control -> NoWeight
: Weight in kg harvested per plant
- Trial_1_AllSamples.rds (All samples from trial one, including other Azomite concentrations not used in main figure)
X
: Formatting artifact, please ignoresamples.out
: Sequencing IDSample_Type
: Is this a sample or a sequencing control? All data included are for samples.Sample_ID
: Sample treatment info; G -> Granular PhylloStart, GU -> Granular + Ultrafine Azomite, U -> Ultrafine Azomite, C -> No Azomite, any samples with a B have the same as described above, but were inoculated with the PhylloStart Community at OD600=0.02 densityProject
: Location, for these data, all are from the greenhouseTreatment
: Expanded treatment information, see above
- Trial_1_Greenhouse_DataFrame_AbsAbund.rds (Absolute abundance, used in figures section)
Treatment
: Treatment, either Control or Bacteria (PhylloStart)Sample_ID
: Unique ID per SampleTotalAbundance
: Total absolute bacterial 16s rRNA abundance per sample, as calculated by qPCR
- Trial_1_Greenhouse_PhyloseqObject_absAbund_stats.rds (Absolute abundance, used in statistics section)
X
: Formatting artifact, please ignoresamples.out
: Sequencing IDSample_Type
: Is this a sample or a sequencing control? All data included are for samples.Sample_ID
: Sample treatment info; G -> Granular PhylloStart, GU -> Granular + Ultrafine Azomite, U -> Ultrafine Azomite, C -> No Azomite, any samples with a B have the same as described above, but were inoculated with the PhylloStart Community at OD600=0.02 densityProject
: Location, for these data, all are from the greenhouseTreatment
: Expanded treatment information, see above
- Trial_1_Greenhouse_PhyloseqObject_relAbund.rds (Relative abundance)
X
: Formatting artifact, please ignoresamples.out
: Sequencing IDSample_Type
: Is this a sample or a sequencing control? All data included are for samples.Sample_ID
: Sample treatment info; G -> Granular PhylloStart, GU -> Granular + Ultrafine Azomite, U -> Ultrafine Azomite, C -> No Azomite, any samples with a B have the same as described above, but were inoculated with the PhylloStart Community at OD600=0.02 densityProject
: Location, for these data, all are from the greenhouseTreatment
: Expanded treatment information, see above
- Trial_3_Greenhouse_and_Field_PhyloseqObject_ForBeta.rds (Raw abundances)
X
: Formatting artifact, please ignoreSamples
: Sequencing IDSequence_ID
: Unique ID per plantTreatment
: Azomite treatment; Azo -> Azomite applied, Control -> No Azomite appliedConcentration
: Amount of Azomite applied in gramsBacteria
: PhylloStart treatment, Community applied at OD600=0.0002 (Low), or PhylloStart Community applied at OD600=0.02 density (High), or no PhylloStart applied (Control)Timepoint
: Timepoint for measurement (all are T1)Location
: Where the plant was grown, field or greenhousePlottingCoordinates
: Arbitrary numbers assigned for internal use to plot the figures
- Trial_3_Greenhouse_and_Field_PhyloseqObject.rds (Relative abundances)
X
: Formatting artifact, please ignoreSamples
: Sequencing IDSequence_ID
: Unique ID per plantTreatment
: Azomite treatment; Azo -> Azomite applied, Control -> No Azomite appliedConcentration
: Amount of Azomite applied in gramsBacteria
: PhylloStart treatment, Community applied at OD600=0.0002 (Low), or PhylloStart Community applied at OD600=0.02 density (High), or no PhylloStart applied (Control)Timepoint
: Timepoint for measurement (all are T1)Location
: Where the plant was grown, field or greenhousePlottingCoordinates
: Arbitrary numbers assigned for internal use to plot the figures
Sharing/Access information
Data was generated for the purpose of this study and is not available elsewhere.
Code/Software
All data was either processed through R as described in the methods of the paper or transferred from lab notebooks into .xlsx
files, which were then converted to .csv
s and processed in R. Data is made available as both .rds
files, and, when possible, as .csv
.
Methods
For 16s Sequencing related data, paired-end reads were filtered and trimmed to 230(F) and 160(R) base pairs (bps), using DADA2 with default parameters (Callahan et al., 2016). Following denoising, merging reads and removing chimeras, DADA2 was used to infer amplicon sequence variants (ASVs), which are analogous to operational taxonomic units (OTUs), and taxonomy was assigned using the DADA2-trained SILVA database. Using DNA extraction and PCR negative controls from 16S sequencing, the decontam package was implemented using default settings to identify and remove potential contamination from the samples (Davis et al., 2018). The assigned ASVs, read count data, and sample metadata were combined in a phyloseq object (McMurdie & Holmes, 2013) for downstream analyses. The phyloseq package was used to calculate beta diversity (using Bray-Curtis distance), and a permutational analysis (PERMANOVA) was performed on data rarified to 400 reads (Weiss et al., 2017) (to account for extraordinarily low read counts in untreated greenhouse samples) using the adonisfunction in the vegan package (Oksanen et al., 2022).
Tomatoes were harvested and their number and weight were recorded multiple times per plant from onset of fruit production to plant termination in the greenhouse, at weeks 17, 18 and 19 in the second trial, and weeks 18 and 24 in the third trial. These metrics were measured only once after harvest from each individual plant grown in the field, at week 24. Tomatoes were weighed individually in trial 2, and as total harvested weight per plant in trial 3, as described. Data was recorded initially in laboratory notebooks, then transferred to `.csv`s before being processed in R.
Usage notes
All data is provided as either `.csv` files, or as `.rds` files, which can be opened and processed in R.