DOI: 10.5061/dryad.wwpzgmsvr
title: Nectar peroxide: Assessing variation among plant species, microbial tolerance and effects on microbial community assembly

description: Nectar contains antimicrobial constituents including hydrogen peroxide,
 yet it is unclear how widespread nectar hydrogen peroxide might be among
 plant species or how effective against common nectar
 microbes. Here, we surveyed 45 flowering plant species across 23
 families and reviewed the literature to assess the field-realistic range
 of nectar hydrogen peroxide (Aim 1). We experimentally explored whether
 plant defense hormones increase nectar hydrogen peroxide (Aim 2). Further,
 we tested the hypotheses that variation in microbial tolerance to peroxide
 is predicted by microbe isolation environment (Aim 3); increasing hydrogen
 peroxide in flowers alters microbial abundance and community assembly (Aim
 4), and that microbial community context affects microbial tolerance to
 peroxide (Aim 5). Peroxide in sampled plants ranged from
 undetectable to ~3000 µM, with 50% of species containing less than 100 µM.
 Plant defensive hormones did not affect hydrogen peroxide in floral
 nectar, but enzymatically upregulated hydrogen peroxide significantly
 reduced microbial growth. Together, our results suggest that
 nectar peroxide is a common but not pervasive antimicrobial defense among
 nectar-producing plants. Microbes vary in tolerance and detoxification
 ability, and co-growth can facilitate the survival and growth of less
 tolerant species, suggesting a key role for community dynamics in
 microbial colonization of nectar.
description: <strong>Aim 1: Assessing natural levels of hydrogen
 peroxide in floral nectar</strong> We sampled the
 floral nectar of 45 flowering plant species (Plantae: Angiospermae) (in
 addition to four cultivars of <em>Epilobium canum</em>)
 growing on the campus of University of California, Davis (38.540 °N,
 121.756 °W, USA: California: Yolo County) and in the Sierra Nevada
 Mountain Range (Incline Lake, USA: Nevada: Washoe County) between
 March-July 2023 & 2024. We selected plant species that were in
 flower in spring/summer (2023 & 2024), produced nectar in volumes
 high enough to be extracted using glass microcapillary tubes (VWR
 International, Drummond Scientific Company, 50 μL) and have been
 previously studied with interest in microbial community inoculation ] (J. Cecala et al., 2024).
 Nectar was always extracted, protected from UV light under aluminum foil,
 kept at room temperature and processed with 3 hours of flower collection
 to reduce potential peroxide degradation. To determine
 the concentration of nectar peroxide, we used one of two lab assays (Table
 1, *for Amplex Red). For the first method, 5 μL of floral nectar was
 assayed using the colorometric Amplex<sup>TM</sup> Red
 Hydrogen Peroxide/Peroxidase Assay Kit (ThermoFisher, Waltham, MA), and
 measured at an absorbance of 560 nm on a spectrophotometer microplate
 reader to determine hydrogen peroxide concentration (SYNERGY HTX, Agilent,
 Santa Clara, CA) (See supplemental methods).  A hydrogen peroxide
 calibration curve was run for each Amplex<sup> </sup>Red assay
 performed in addition to blanks and peroxidase-free negative controls. For
 the Amplex Red assay the limit of detection (LOD) is 50 nM, while our
 limit of quantification (LOQ) is 1 μM. Any absorbance values below our LOQ
 we reported as &lt; 1 μM. Alternatively, we used colorometric mid
 range peroxide test strips with 0.5-2 μL of nectar
 (WaterWorks<sup>TM</sup> Mid Range Peroxide Check, Industrial
 Test Systems Inc., Rock Hill, SC) to determine peroxide concentration for
 some samples. We used a standard hydrogen peroxide curve to assess the
 performance of the peroxide test strips, which have discrete color changes
 for &lt;0.5, 2, 5, 10, 25, 50, and 100 ppm. For the test strip assay
 the LOD and LOQ are 0.5 ppm (15 μM). Any color change that matched
 &lt;0.5 ppm we reported as 0.5 ppm, and for those that were fainter
 than &lt;0.5 ppm we reported as &lt;15 μM.  Despite having lower
 precision, test strips exhibited a linear response to peroxide which the
 Amplex<sup>TM</sup> Red kit did not (due to oversaturation and
 the reversal of the colorometric reaction), so the test strips gave us
 greater confidence in the range of measurement without the need to measure
 multiple dilution points (See supplemental methods) . We note, however,
 that the peroxide strip test method may detect peroxides that include but
 are not limited to hydrogen peroxide, therefore, any values obtained from
 the test strips we refer to as peroxide, rather than hydrogen peroxide
 concentrations. We detected no significant degradation of prepared
 H<sub>2</sub>O<sub>2</sub> solutions (10 or 35 μM)
 after 3 hours (Supplemental Figure S1). In addition, we
 assessed the existing body of literature on hydrogen peroxide
 concentration in nectar, recording concentrations and detection methods
 used (Table 2, color coded by study). We used search terms including
 nectar, peroxide, hydrogen peroxide, nectar defense, and nectar
 antimicrobial compounds. <strong>Aim 2: Do plant
 defense hormones induce upregulation of floral nectar hydrogen
 peroxide?</strong>  To explore whether the
 production of nectar hydrogen peroxide may be induced by common plant
 hormones in living flowers, we tested the effects of methyl jasmonate and
 methyl salicylate. Jasmonic acid and salicylic acid upregulate defensive
 plant pathways associated with herbivory and microbial invasion (Bruinsma
 et al., 2008; Hernandez-Cumplido et al., 2016; Hoffmeister &
 Junker, 2017; Radhika et al., 2010). We were curious whether the methyl
 volatile conjugates of these plant hormones (the forms used in plant-plant
 signaling) could alter concentrations of hydrogen peroxide in the nectar
 of long-blooming <em>Peritoma</em> <em>arborea
 </em>(bladderpod). We performed these manipulative field experiments
 on the campus of the University of California, Davis.
 We selected two spatially separated (by 0.25 mi) patches of
 bladderpod. We treated recently opened flowers by spraying them with
 approximately 650 μL (350 mL spray bottle) of either a methyl jasmonate (1
 mM in 2% EtOH), methyl salicylate (1 mM in 2% EtOH), or 2% ethanol
 (control) spray solution (Thaler et al., 2001). We held a container under
 the sprayed flower to catch any excess liquid and prevent the treatment
 from impacting other parts of the plant. Care was also taken to avoid
 flooding the flowers with liquid (and diluting the nectar solution) by
 positioning flowers so they faced downward when spray was applied, such
 that the lower parts of the petals, as well as the tips of the stigma and
 anthers received treatment. We then placed mesh bags over the flowers to
 prevent pollinator visitation and removal of floral nectar.
 After 24 hours, we collected the individual treated flowers.
 Floral nectar was extracted using glass capillary tubes (VWR
 International, Drummond Scientific Company, 50 μL) and the nectar column’s
 length combined with a conversion factor based on the tube size was used
 to calculate the total volume of nectar extracted per flower. Peroxide
 concentrations were assessed using the Amplex<sup>TM</sup> Red
 Kit (Thermo Fisher Scientific) using 5 μL of nectar, as previously
 described in Experiment 1 (also, see supplemental methods).
 <strong>Aim 3: How does microbial identity and isolation
 source influence tolerance to hydrogen peroxide?</strong>
 To test how microbial identity and isolation source impacts
 tolerance to hydrogen peroxide, we selected fungi isolated from floral
 petal tissue, queen bumble bee regurgitant, bumble bee honey pot stores,
 and various floral nectars. For each assay, each strain was freshly
 streaked from freezer stocks (Table 2) onto yeast media (YM) agar
 containing 0.1% v/v of 100 mg/mL chloramphenicol (antibiotic) in methanol
 solution to inhibit bacterial growth. After at least 72 h of growth on
 agar at 25 °C, we created pure culture suspensions at 0.1 optical density
 at 600 nm (OD<sub>600</sub>) in sterile 20% sucrose solution
 (0.2 micron syringe filter). We prepared artificial nectar growth media
 (see Aim 3 recipe in supplemental methods) and sterilized it with a 0.2
 micron sterile filter. We prepared hydrogen peroxide stock solutions
 through a set of serial dilutions into artificial nectar using stabilized
 3% hydrogen peroxide (Thermo Scientific Chemicals) resulting in final
 in-plate concentrations of 0 μM, 100 μM, and 2000 μM.
 Microbial growth was assayed by monitoring optical density at 600
 nm (OD<sub>600</sub>)<sub> </sub>within 96 well
 growth plates. Each well contained 120 μL of the artificial nectar growth
 media, 10 μL of appropriate hydrogen peroxide stock solution, and 20 μL of
 microbial culture suspension. Each treatment combination was replicated in
 triplicate, and negative controls lacking microbe inoculum were run at
 each hydrogen peroxide concentration to ensure lack of microbial
 contamination. We incubated the microplates at room temperature in the
 dark and used a spectrophotometric microplate reader (SYNERGY HTX, BioTek
 Gen5 Software) to measure optical density at 600 nm every 2 hours for 24
 hours. Before each read the plates were shaken linearly for 30 seconds. We
 scaled the OD<sub>600</sub> measurements for each microbial
 taxon relative to their control (0 μM
 H<sub>2</sub>O<sub>2</sub>) because microbial
 growth varied among species depending on the media type. This allowed us
 to better visualize the impact of hydrogen peroxide treatments on each
 microbe type relative to one another. <strong>Aim
 4:  How does hydrogen peroxide concentration shape microbial assembly in
 the nectar of living flowers?</strong> To assess
 whether artificially elevated hydrogen peroxide in nectar affects the
 composition and growth of an inoculated microbial community, we performed
 manipulative field experiments with <em>Epilobium canum
 </em>(Greene) P.H.Raven (Myrtales: Onagraceae) on The University of
 California, Davis campus from June to August 2023. <em>Epilobium
 canum </em>was selected because of its harvestable nectar volume and
 floral phenology and longevity, typically 3-5 days. We
 prepared synthetic microbial communities and enzyme solutions for floral
 inoculation experiments. We selected microbial species isolated from
 flowers or pollinators that were morphologically distinguishable when
 grown on media (Table 2: recipe in supplemental methods) (J. M. Cecala
 & Vannette, 2024). Each microbe was plated from freezer stock onto
 agar and incubated for at least 72 h of growth at 25 ℃.  Then suspensions
 of each of the five species were adjusted to approximately
 10<sup>6</sup> cells using a hemocytometer and aliquots stored
 at -80 ℃ (Cecala & Vannette, 2024). To create inocula the day of
 the field experiment, aliquots from each of the five species were thawed,
 combined, and brought up to ~100µL with the freezer stock solution to
 yield an inoculum containing roughly 10<sup>4</sup>
 cells/µL<sup> </sup>of each of the five species, or
 equivalently 5 x 10<sup>4</sup> total cells/µL. The microbial
 inoculum was kept on ice. Each of the species was proven to be
 successfully culturable from the individually aliquoted inocula on media
 plates prior to use in experiments. To manipulate the concentration of
 hydrogen peroxide in living flowers, we prepared a solution of the
 hydrogen peroxide-generating enzyme, glucose oxidase (GOX) (isolated from
 <em>Aspergillus niger</em>, Type VII, ≥1000,000 units/g,
 Sigma-Aldrich) at a concentration of 0.32 units of enzyme/μL in 40% sugar
 solution (80% glucose: 20% sucrose), immediately prior to beginning the
 experiment. This solution, as well as a boiled (inactive, boiled for 2 hr)
 glucose oxidase (B-GOX) solution at an equivalent concentration to act as
 a negative control, were kept on ice. This strategy was advantageous
 because (1) the nectar redox cycle nectarin protein NEC5 identified in
 <em>Nicotiana</em> is a glucose oxidase and produces hydrogen
 peroxide via the same mechanism (C. Carter & Thornburg, 2004), (2)
 hydrogen peroxide can rapidly degrade, so this enzymatic method allows for
 a renewal of hydrogen peroxide through the activity of the GOX, and (3) a
 previous study showed success of this method and enzyme concentration in
 living <em>Nicotiana </em>nectar (Bezzi et al.,
 2010). The day prior to our field experiment, we
 covered closed flowers of <em>Epilobium canum</em> in two
 discrete patches with mesh bags to exclude pollinator visitation and
 microbial deposition (Francis et a,l 2023). Once all microbial inocula and
 enzyme solutions were prepared fresh each day, we identified bagged
 flowers that had opened and could be used in our experiment. For the first
 experimental treatment, we inoculated flowers with 10 μL (3.2 units) of
 active glucose oxidase enzyme and 1 μL of microbial inocula (n = 10, split
 between two clumps). Control flowers were inoculated with 10 μL of 40%
 sucrose solution and 1 μL of microbial inocula while additional flowers
 were inoculated with 10 μL boiled glucose oxidase solution and 1 μL of
 microbial inocula. Solutions were delivered into flowers using a
 micropipette and sterilized 10 μL tip. The inoculated flowers were marked
 with permanent marker, tagged, and mesh bags replaced. Each treatment had
 10 replicates per trial, and two separate trials were conducted. The
 prepared microbial inoculum, the active glucose oxidase, boiled GOX, and
 control solution (sugar substrate) were all kept on ice while out in the
 field. After 24 hours, flowers were harvested and
 brought back to the laboratory where microbial growth and composition were
 assessed. Occasionally, we would find that thrips and ants had made it
 inside of some bagged flowers and their presence noted. Nectar was
 extracted in a hood using glass capillary tubes, total nectar volume of
 each flower quantified (VWR International, Drummond Scientific Company, 50
 μL), and diluted for plating. We also noted any bleached corolla or pistil
 tissue, likely caused by oxidative tissue damage from reactive oxygen
 derivatives of hydrogen peroxide. For floral nectar samples with greater
 than 5 μL extracted volume, we added 5 μL of nectar into 45 μL of DPBS
 buffer. For extracted nectar samples of less than 5 μL, 50 μL DPBS buffer
 was added to the full amount of nectar sample. We vortexed and centrifuged
 the diluted samples, then plated 15 μL of each sample on YM, TSA, and MRS
 plates and spread using sterile glass beads. Plates were incubated at 28 ℃
 for 7 days. CFUs were identified by microbial taxa based on morphological
 features and counted for each plate (Cecala & Vannette, 2024). For
 plates where the CFUs were too numerous/dense to count with confidence, we
 overlaid a transparent grid and tallied CFU subsamples in at least six 0.1
 or 1.0 cm<sup>2</sup> squares, which we used to estimate the
 total CFUs per plate for a given microbe. If CFU’s were too dense for even
 this method, having formed a lawn, we assigned it the highest countable
 density from another plate of the same microbe type.
 Using 5 μL undiluted aliquots of extracted nectar above, we
 quantified peroxide concentrations with mid (previously used) and high
 range (0, 100, 200, 400 ppm) peroxide test strips
 (WaterWorks<sup>TM</sup> Mid Range Peroxide Check, Industrial
 Test Systems Inc., Rock Hill, SC), (Bartovation Peroxide Test Strips 0-400
 ppm, Bartovation, Queens, NY) to validate enzyme effects on peroxide
 concentration. For some of the samples we also used a
 handheld refractometer (Bellingham + Stanley, Kent, UK) to measure
 Brix (Supplemental Figure S2). <strong>Aim 5: How
 does community vs individual growth context impact microbial
 growth?</strong> To explore whether co-growth of
 microbes influences microbial tolerance to hydrogen peroxide, we compared
 the growth of microbe isolates individually and in communities at
 different concentrations of hydrogen peroxide, in sterile artificial
 nectar solution to mimic floral nectar conditions (see Aim 5 recipe in
 supplemental methods). Using the same microbial isolates previously used
 in the field experiment of Aim 4 (Table 2), we created a community
 suspension of all five taxa as well as suspensions for each individual
 taxa. To create a community inoculum the day of the in vitro lab
 experiment, we combined aliquots from each of the five species as
 described previously. To make microbial isolate suspensions, an aliquot
 from a given species containing roughly 10<sup>4</sup>
 cells/µL<sup> </sup>was brought up to a volume of 100 μL with
 freezer stock solution. We prepared hydrogen peroxide stock solutions
 through a set of serial dilutions into the artificial nectar media with
 final concentrations of 0, 10, 50, 100, and 2000 μM.
 For each replicate, we added 39 μL of artificial nectar, 10 μL of
 hydrogen peroxide treatment and 1 μL of microbial suspension for a total
 volume of 50 μL in PCR tubes, which we selected based on nectar volumes
 often extracted from <em>Epilobium canum </em>during prior
 field trials. Each treatment combination--six different microbial inocula
 (community of all five microbes and each microbe individually) x five
 hydrogen peroxide treatment concentrations--was performed in triplicate.
 We vortexed and centrifuged the tubes and then incubated at 28 ℃ for 24
 hours, protected from UV light with aluminum foil. After the 24 hours, we
 assessed microbial growth as described in Aim 4 above. We also determined
 the concentration of hydrogen peroxide using 5 μL of each solution applied
 to mid-range peroxide colorimetric test strips. By comparing control,
 individual, and community samples we assessed how peroxide degradation
 (Supplemental Figure S3) and if microbial growth and community membership
 altered hydrogen peroxide concentration.
 <strong>Statistical Analysis:</strong>
 We conducted all statistical analyses in R (R Core Team, 2021)
 and used ggplot (Wickham, 2016). In Aim 1, to estimate plant phylogenetic
 relationships among the sampled plant species, we used the function
 ‘phylo.maker’ in package <em>V.PhyloMaker2</em> (Jin &
 Qian, 2022) using the reference vascular plant mega-phylogeny
 GBOTB.extended.TPL. Using this tree and the function ‘multiPhylosignal’ in
 the package <em>picante </em>(Kembel et al., 2010) we tested
 for a phylogenetic signal of nectar peroxide concentration.
 To test whether defensive growth hormones altered concentrations
 of hydrogen peroxide in <em>Peritoma arborea</em> nectar or
 nectar volume (Aim 2), we used one-way ANOVA in the package
 <em>car</em>. We obtained F- and P values using Kenward-Roger
 degrees of freedom. For Aim 3, we tested whether microbial growth
 (measured by OD<sub>600</sub>) differed among concentrations
 of hydrogen peroxide according to microbial identity or isolation source
 and their interaction using type III ANOVA and the drop1 function. We
 performed post-hoc analysis using the ‘TukeyHSD’ function to assess the
 source of variation in the predictor variable, microbial isolation source.
 For Aim 4, we compared how enzyme treatments influenced floral nectar
 peroxide concentration using an ordinal model (because test strip data are
 ordinal) implemented using the function ‘clm2’ in the ordinal R package,
 as well as effects on total microbial community composition, and growth of
 individual species using separate ANOVAs. We used the peroxide test strip
 designations per product instructions to assign different peroxide levels
 used in the analysis and visualization. To evaluate which enzyme
 treatments contributed to differences observed in total microbial
 community composition and individual microbe growth, we performed a
 post-hoc Tukey analysis. In Aim 5, we examined the
 impact of community vs isolate growth context, hydrogen peroxide
 concentration and their interaction on microbial growth using III ANOVAs,
 with separate models for each tested microbe. Additionally, we examined if
 measured peroxide concentration varied with microbial growth context,
 starting hydrogen peroxide treatment concentration and their interaction
 using ordinal models (clm2) as above, with significance assessed using
 c<sup>2</sup> tests. To evaluate which microbe taxa
 contributed to differences observed in the final environmental hydrogen
 peroxide concentration, we performed a post-hoc analysis using
 ‘TukeyHSD’.  Finally, to test if microbial community composition (as
 Bray-Curtis dissimilarity) that formed after 24 hours differed among
 hydrogen peroxide treatments, we used function ‘adonis’ in package
 <em>vegan</em> (Oksanen et al., 2007) to perform a
 multivariate analysis of variance (PERMANOVA). Microbial community
 composition was visualized using non-metric multidimensional scaling
 (NMDS) ordination (Supplemental Figure S4).
description: # Nectar Peroxide measurements and experiments
 [https://doi.org/10.5061/dryad.wwpzgmsvr](https://doi.org/10.5061/dryad.wwpzgmsvr) ## Description of the data and file structure Data are structured in tables containing metadata and measured variables for nectar and artificial nectar solutions, microbial growth in nectar and artificial nectar solutions, and measurements of hydrogen peroxide in solutions. Files are structured around the aims described in the accompanying manuscript. Aim 1: Comparing nectar peroxide values among plant species Phylogeny_Nectar_Peroxide_Signal.xlsx ``` This experiment compared measured nectar peroxide values among plant species using a phylogenetic context.   ``` Aim 2: Assessing effects of plant hormones on nectar traits MeSA_JA_Nectar_Peroxide-CLEAN.xlsx ``` This experiment assessed nectar traits of plants treated with plant hormones methyl salicylate (MeSA) or methyl jasmonate (MeJA).   ``` Aim 3: variation in microbial tolerance to peroxide is predicted by microbe isolation environment Isolation_Source-CLEAN.xlsx ``` This experiment assessed microbial growth in 96 well plates containing artificial nectar solution and measured microbial growth of individual strains using optical density (OD600). ``` Aim 4: hydrogen peroxide in flowers alters microbial abundance and community assembly GOX_Peroxide_Microbial_Growth-CLEAN.xlsx ``` This experiment assessed microbial growth in real floral nectar and quantified microbial growth (CFUs) and nectar traits in flowers treated with Glucose oxidase (GOX) or inactivated GOX. ``` Aim 5: microbial community context affects microbial tolerance to peroxide Growth_Context_Peroxide_Tolerance-CLEAN.xlsx ``` This experiment assessed microbial growth in artificial nectar solutions and quantified microbial growth (CFUs) and nectar traits. ``` ### Files and variables #### File: GOX\_Peroxide\_Microbial\_Growth-CLEAN.xlsx **Description:** This experiment assessed microbial growth in real floral nectar and quantified microbial growth (CFUs) and nectar traits in flowers treated with Glucose oxidase (GOX) or inactivated GOX. Cells containing "." represent unavailable information or data not applicable ##### Variables * Enzyme_treatment: experimental treatment with either sugar, boiled enzyme (B-GOX), or active enzyme (GOX) * Microbe_treatment: Microbial community added (Y) or not added (N) * ID: flower ID * Ppm: measured hydrogen peroxide (ppm) * uM_peroxide: measured hydrogen peroxide (uM) * peroxide_data: did the flower have measured peroxide data? Yes (Y) or no (N) * trial: trial number * vol_used_plating: nectar volume used for counting microbial density (colony forming units) via plating * vol_PBS_added: volume of PBS added for dilution and plating * dilution_factor: factor by which nectar was diluted for plating, used to calculate microbial density * Mreuk_CFU: colony forming units of Metschnikowia reukaufii * Apull_CFU: colony forming units of Aureobasidium pullulans * Nthail_CFU: colony forming units of Neokomagatea thailandica * Apoll_CFU: Estimate of colony forming units for Acinetobacter pollinis * Amich_CFU: colony forming units of Apilactobacillus michenerii * Other CFUs: Any other colonies that were not from focal microbes * Total CFUS: sum of all inoculated microbial colony forming units in a given sample #### File: Phylogeny\_Nectar\_Peroxide\_Signal.xlsx **Description:** This experiment compared measured nectar peroxide values among plant species using a phylogenetic context.   ##### Variables * Sheet 1: plant_trait_dataframe contains * label: Plant species name * value: mean peroxide measured in floral nectar  * Sheet 2 contains * species: Genus and species of each plant species sampled * genus: plant genus * family: plant family #### File: Growth\_Context\_Peroxide\_Tolerance-CLEAN.xlsx **Description:** This experiment assessed microbial growth in real floral nectar and quantified microbial growth (CFUs) and nectar traits in flowers treated with Glucose oxidase (GOX) or inactivated GOX. ##### Variables * * Trial: experimental trial number * Inocula_type: was the focal microbe part of a community or inoculated singly (isolate) * H2O2_concentration: manipulated nectar peroxide concentration (uM) * Replicate: replicate of that particular treatment * Microbe_name: microbial species counted * CFU_count: colony forming units in a nectar sample * Dilution factor: dilution factor for calculating density * CFU_corrected: total colony forming units in the sample when correcting for dilution factor. * Log-CFU: log10(colony forming units+1) #### File: MeSA\_JA\_Nectar\_Peroxide-CLEAN.xlsx **Description:** This experiment assessed nectar traits of plants treated with plant hormones methyl salicylate (MeSA) or methyl jasmonate (MeJA).   #### File: Isolation\_Source-CLEAN.xlsx **Description:** This experiment assessed microbial growth in 96 well plates containing artificial nectar solution and measured microbial growth of individual strains using optical density (OD600). ## Code/software The two R scripts were created in R version 4.4.1 (2024-06-14) -- "Race for Your Life". R Packages used are listed in the scripts themselves but include: growthcurver, readxl, dplyr, ggplot2, car, lme4, AICcmodavg, MuMIn, emmeans, magrittr, multcomp, scales, plyr, visreg, tidyr, ggpubr, summarytools, fitdistrplus, vegan, arm, glmmTMB, ggfortify, goeveg, corrplot, Hmisc. The R script " Manuscript_Aim1_Phylogeny_Peroxide_LL.R” analyzes “Phylogeny_Nectar_Peroxide_Signal.xlsx” . The R script " Manuscript_Aim2_MeSA_JA_LL.R” analyzes “MeSA_JA_Nectar_Peroxide.xlsx” The R script “Manuscript_Aim3_IsolationSource_LL.R” analyzes “Isolation_Source.xlsx” The R scripts “Manuscript_Aim4_GOX_CFU.R” and “Manuscript_Aim4_GOX_Peroxide-rlv” analyze “GOX_Peroxide_Microbial_Growth.xlsx” The R scripts “Manuscript_Aim5_Growth_context_peroxide_tolerance.R” and “Manuscript_Aim5_Microbial_peroxide_degradation-rlv.R” analyze “Growth_Context_Peroxide_Tolerance.xlsx” ## Access information Other publicly accessible locations of the data: * None Data was derived from the following sources: * The data contained here are original and not derived from any other source.