bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
1 Experimental evidence pointing to rain as a reservoir of tomato phyllosphere microbiota
2
3 Marco E. Mechan-Llontop1,2, Long Tian1, Parul Sharma1, Logan Heflin1, Vivian Bernal-
4 Galeano1, David C. Haak1, Christopher R. Clarke3 & Boris A. Vinatzer1
5
6 1 School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA.
7 2 Current Address: Department of Microbiology and Molecular Genetics and DOE Great Lakes
8 Bioenergy Research Center, Michigan State University, East Lansing, MI 48824, USA.
9 3 Genetic Improvement for Fruits and Vegetables Laboratory, Beltsville Agricultural Research
10 Center, U.S. Department of Agriculture-Agricultural Research Service, Beltsville, MD 20705,
11 USA.
12
13 Corresponding author: B. A. Vinatzer; [email protected]
14
15 Keywords: bacteriology, genomics, microbiome, plant pathology, rhizosphere and phyllosphere,
16 plants, metagenomics
17
18
1 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
19 ABSTRACT
20 Plant microbiota play essential roles in plant health and crop productivity. Comparisons of
21 community composition have suggested seeds, soil, and the atmosphere as reservoirs of
22 phyllosphere microbiota. After finding that leaves of tomato (Solanum lycopersicum) plants
23 exposed to rain carried a higher microbial population size than leaves of tomato plants not exposed
24 to rain, we experimentally tested the hypothesis that rain is a so far neglected reservoir of
25 phyllosphere microbiota. Rain microbiota were thus compared with phyllosphere microbiota of
26 tomato plants either treated with concentrated rain microbiota, filter-sterilized rain, or sterile water.
27 Based on 16S rRNA amplicon sequencing, one-hundred and four operational taxonomic units
28 (OTUs) significantly increased in relative abundance after inoculation with concentrated rain
29 microbiota but no OTU significantly increased after treatment with either sterile water or filter-
30 sterilized rain. Some of the genera to which these 104 OTUs belonged were also found at higher
31 relative abundance on tomatoes exposed to rain outdoors than on tomatoes grown protected from
32 rain in a commercial greenhouse. Taken together, these results point to precipitation as a reservoir
33 of phyllosphere microbiota and show the potential of controlled experiments to investigate the role
34 of different reservoirs in the assembly of phyllosphere microbiota.
35
36
2 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
37 INTRODUCTION
38
39 Microbial communities associated with plants, often referred to as plant-associated microbiota and
40 as constituents of the plant microbiome, influence a remarkable number of processes of plant
41 biology and affect plant health and crop yield (Goh et al., 2013, Badri et al., 2013, Hacquard et al.,
42 2015, Lu et al., 2018, Torres-Cortés et al., 2018, Durán et al., 2018, Ritpitakphong et al., 2016,
43 Berg & Koskella, 2018). The phyllosphere, considered here as the plant compartment that extends
44 from the outside to the inside of the leaf (Morris, 2002, Vacher et al., 2016), harbors a high
45 diversity of microorganisms, with bacteria being the most abundant domain (Lindow & Brandl,
46 2003, Vorholt, 2012).
47 Phyllosphere microbiota are exposed to fluctuating environmental stresses, including
48 changes in UV exposure, temperature, water availability, osmotic stress, and humidity (Hirano &
49 Upper, 2000, Jacobs & Sundin, 2001, Lindow & Brandl, 2003, Vacher et al., 2016). The core
50 bacterial phyla that can withstand these environmental stressors include Proteobacteria,
51 Actinobacteria, Bacteroidetes, and Firmicutes (Vorholt, 2012, Bulgarelli et al., 2013). However,
52 at lower taxonomic ranks, the phyllosphere microbiome greatly varies with changing biotic and
53 abiotic factors (Lindemann & Upper, 1985, Rastogi et al., 2012, Copeland et al., 2015, Wagner et
54 al., 2016).
55 Culture-independent 16S rRNA amplicon analyses have expanded our knowledge of the
56 composition of the phyllosphere microbiome of several plant species (Knief et al., 2012, Williams
57 et al., 2013, Kembel et al., 2014, Copeland et al., 2015, Grady et al., 2019), including tomato
58 (Solanum lycopersicum) (Ottesen et al., 2013, Ottesen et al., 2016). The bacterial genera
59 Pseudomonas, Erwinia, Sphingomonas, Janthinobacterium, Curtobacterium, Agrobacterium,
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60 Stenotrophomonas, Aurantimonas, Thermomonas, Buchnera, Enterococcus, Rubrobacter,
61 Methylobacterium, Deinococcus, and Acidovorax have all been observed to be associated with the
62 phyllosphere of tomatoes grown in the field (Ottesen et al., 2013, Ottesen et al., 2016, Toju et al.,
63 2019).
64 Microbes constantly cycle across interconnected habitats maintaining healthy ecosystems
65 (van Bruggen et al., 2019). Importantly for this study, it has been shown that plants represent an
66 important source of microbes that are released as aerosols into the atmosphere (Lindemann et al.,
67 1982, Constantinidou, 1990, Lighthart & Shaffer, 1995, Šantl-Temkiv et al., 2013, Bowers et al.,
68 2011, Vaïtilingom et al., 2012). The atmosphere then serves as a vehicle for microbial dispersal
69 not only locally, but also globally (Bovallius et al., 1978, Brown & Hovmøller, 2002, Schmale &
70 Ross, 2015) and air-borne microbial communities are deposited back to earth surfaces as
71 precipitation. The atmosphere thus represents a crucial route for the dissemination of beneficial
72 and pathogenic species (Polymenakou, 2012, Monteil et al., 2014, Monteil et al., 2016). There is
73 even some evidence that air-borne microbes contribute to the formation of precipitation itself
74 (Christner et al., 2008, Morris et al., 2014, Amato et al., 2015, Amato et al., 2017, Failor et al.,
75 2017). Proteobacteria followed by Bacteroidetes, Actinobacteria, and Firmicutes have been
76 identified as the most common phyla both in the atmosphere (Peter et al., 2014, Hiraoka et al.,
77 2017, Cáliz et al., 2018) as in precipitation (Cáliz et al., 2018, Aho et al., 2020), notable largely
78 the same as the core phyla of the phyllosphere microbiome mentioned earlier.
79 Microbial community assembly is largely influenced by deterministic (selection) and
80 stochastic (dispersal) processes that determine the complex structure and function of microbiomes
81 (Powell et al., 2015, Zhou & Ning, 2017, Graham & Stegen, 2017). This assembly process has
82 been extensively studied in roots, which recruit microbial communities from the surrounding soil
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83 (Fitzpatrick et al., 2018, Pérez-Jaramillo et al., 2019). However, sources that drive the phyllosphere
84 microbiome assembly are still under debate. It has been suggested that soil is the major reservoir
85 of the phyllosphere microbiome (Zarraonaindia et al., 2015, Wagner et al., 2016, Grady et al.,
86 2019). In fact, it has been observed that the leaf microbiome reflects soil bacterial diversity at an
87 early stage of growth but significantly differs as plants grow and mature (Copeland et al., 2015).
88 On the contrary, (Maignien et al., 2014, Ottesen et al., 2016) found evidence that dry deposition
89 of air-borne microbes constitutes an important source of phyllosphere microbiota.
90 A few studies have also explored wet deposition of air-borne microbes in precipitation as
91 a potential reservoir of phyllosphere microbiota. For example, (Morris et al., 2008) concluded that
92 the plant pathogen Pseudomonas syringae is disseminated through the water cycle because of its
93 ubiquitous presence in compartments of the water cycle and plants. Using whole genome
94 sequencing, (Monteil et al., 2016) confirmed these conclusions by finding that P. syringae bacteria
95 isolated from diseased cantaloupe plants and P. syringae isolates from rain, snow, and irrigation
96 water were members of the same population. Recently, rain was also found to affect the overall
97 composition of plant phyllosphere microbiota but it was not determined if rain-borne bacteria were
98 the source of the observed shifts (Allard et al., 2020). Moreover, it is well known that fungal spores
99 are released from plants, travel long distances through the atmosphere, and can be deposited back
100 on plants with rain (Woo et al., 2018).
101 After finding that the phyllosphere of tomato plants exposed to rain contained a higher
102 bacterial population size than the phyllosphere of tomato plants not exposed to rain, we
103 hypothesized that rain-borne bacteria might contribute to the assembly of phyllosphere microbiota
104 beyond pathogenic bacteria and fungi. Putative rain-borne tomato phyllosphere colonizers were
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105 identified in a series of controlled laboratory experiments and by comparing the composition of
106 tomato phyllosphere microbiota of plants naturally exposed to rain with those not exposed to rain.
107
108 MATERIALS AND METHODS
109
110 Determination of the population size of tomato phyllosphere microbiota. Store-bought
111 tomato seeds of the cultivar ‘Rio Grande’ were germinated in autoclaved soil (60 min/ fast cycle).
112 For growth under laboratory conditions, plants were kept for 4 weeks on shelves under 14 h of
113 light and 10 h of dark. For exposure to outdoor conditions, 4-week-old tomato plants were
114 transplanted into large plastic pots. Pots were then either transported to a research farm and placed
115 on gravel near a maintained lawn (Kentland Farm, Blacksburg, VA, USA) or put on the flat roof
116 of the 3-story Latham Hall research building at Virginia Tech (Blacksburg, VA, USA) several
117 meters above and away from soil and vegetation.
118 Culture-dependent analysis of phyllosphere microbiota. Leaf disks were aseptically
119 collected with a #1 cork borer and placed in a tube containing 200 µL of sterile 10 mM MgSO4
120 solution and 3 glass beads. Tubes were placed in a mini bead beater (Biospec Products, Inc.,
121 Bartlesville, OK, USA) and shaken for 2 min to release bacterial cells. Serial dilutions were plated
122 on R2A plates supplemented with cycloheximide to inhibit fungal growth. Plates were incubated
123 at room temperature and colony-forming units were counted 4 days later.
124 Rain collection. Rain was collected as described in (Failor et al., 2017). In short,
125 autoclavable bags were wrapped in aluminum foil and autoclaved for 40 min/fast cycle. Trash cans
126 were arranged away from structures on the roof of the Latham Hall research building. Surfaces of
127 containers were sprayed with 75% ethanol to prevent contamination. Sterile bags were placed in
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128 the cans and the lid placed back on top until the beginning of a rainfall event, at which point they
129 were removed. The lids of three cans were then removed but one can was kept closed during the
130 precipitation event as a negative control. After the end of precipitation events, 1 liter (L) of sterile
131 water was poured into the negative control can, simulating the precipitation event. After rainfall
132 events ended, bags containing rain water were removed and placed at 4°C until processing.
133 For DNA extraction, three L of rainwater were vacuum filtrated (reusable filter holders
134 from Thermo Scientific Nalgene, USA) through a 0.2 µm pore filter membrane (Supor® 200 PES
135 membrane Disc Filter, PALL, USA). Filters were removed using sterile tweezers, placed into a 15
136 mL Eppendorf tube and stored at -80°C until processing.
137 Rain as bacterial inoculum and plant treatments. Tomato plants were grown in the
138 laboratory for four weeks as described above for the culture-dependent analysis of phyllosphere
139 microbiota. Two L of rainwater were vacuum-filtered as described under rain collection. To
140 concentrate the bacterial microbiota present in rain hundred fold, the filter membranes were
141 incubated for 10 min with shaking in 20 mL of sterile water, which was then used as inoculum
142 (referred to as concentrated rain microbiota or 100X-rain from now on). The rain that passed
143 through the filter was used as bacterial-free inoculum (referred to as filtered rain or filter-sterilized
144 rain). Autoclaved double-distilled water was used as sterile water treatment. Groups of four plants
145 placed together into 13 inch x 16 inch plastic bags were sprayed until run off. The bags were left
146 open for two hours to let the plants dry before the day 0 time point DNA extraction from two of
147 the four tomato plants. Bags were then closed for 2 days to create a high humidity environment
148 favorable to plant colonization after which they were kept open for 5 days until the day 7 time
149 point DNA extraction from the remaining two tomato plants.
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150 Growth of outdoor and greenhouse tomatoes. Tomato plants were purchased at Home
151 Depot at the beginning of June 2019 and transplanted into pots and placed on the flat roof of the
152 Latham Hall building on the Virginia tech campus by setting them on a large, clean sheet of plastic
153 to reduce contamination from the roof floor. Plants were regularly waters without touching leaves.
154 One set of plants were brought indoors before each rainfall event while the other set of plants were
155 kept outside to be exposed to rainfall. Each rainfall event was collected and DNA extracted as
156 described above and leaves from both sets of plants were harvested and DNA extracted as
157 described below.
158 Harvesting plants leaves. All plant leaves were removed and collected in a ziplock plastic
159 bag. Sterile distilled water was added (300 mL) and samples were sonicated for 10 minutes using
160 a 1510 BRANSON sonicator (Brandsonic, Mexico) (Ottesen et al., 2013). The leaf wash was
161 vacuum-filtered on to the same kind of 0.22 µm pore filter described above to collect microbial
162 cells dislodged from leaf tissue during sonication, as described above. Filter membranes were
163 placed into a 15 mL Eppendorf tube and stored at -80ºC until processing.
164 Plant leaves were also collected using the same procedure inside a commercial greenhouse
165 where tomatoes were grown either hydroponically or in non-sterilized soil under an organic
166 production regiment.
167 DNA extraction. DNA extraction from all the 0.22 µm filter membranes was performed
168 using the Power Water DNA isolation kit (Qiagen, USA) according to the manufacturer’s protocol
169 with minor modifications. DNA concentration and quality were assessed by UV
170 spectrophotometry (NanoDrop 1000, Thermo, USA) and visualized on a 1 % agarose gel.
171 Library preparation and sequencing. For the 16S rRNA amplicon sequencing we used
172 the barcoded primers a799wF (5’AMCVGGATTAGATACCCBG3’) and new1193R
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173 (5’ACGTCATCCCCACCTTCC3’). A 28 cycle PCR was performed using the HotStarTaq Plus
174 Master Mix Kit (Qiagen, USA) under the following conditions: 94°C for 3 minutes, followed by
175 28 cycles of 94°C for 30 seconds, 53°C for 40 seconds and 72°C for 1 minute, after which a final
176 elongation step at 72°C for 5 minutes was performed. After amplification, PCR products obtained
177 from the various samples were mixed in equal concentrations and purified using Agencourt
178 Ampure beads (Agencourt Bioscience Corporation, Beverly, MA, USA). All steps from PCR to
179 paired-end (2 × 300 bp) amplicon sequencing on the Illumina MiSeq platform were performed at
180 Molecular Research LP (MR DNA™, Shallowater, TX, USA).
181 For metagenomic sequencing using the Illumina platform, total DNA was sequenced using
182 150 bp paired-end reads on the HiSeq 4000 Illumina platform, Duke University Sequencing and
183 Genomic Technologies Shared Resource, Durham, NC, USA. For metagenomic sequencing using
184 the Nanopore platform, DNA libraries were prepared following the ‘1D Native barcoding genomic
185 DNA protocols (SQK-LSK109 and EXP-NBD104) provided by Oxford Nanopore Technologies
186 (ONT).
187 Bioinformatic analysis. Raw 16S rRNA paired-end sequences were processed by
188 Molecular Research LP (MR DNA™, Shallowater, TX, USA) as follows: 1) reads were joined
189 together after q25 trimming of the ends and reoriented in the 5’-3’ direction, 2) barcodes and
190 primer sequences were removed, and 3) sequences shorter than 200bp, sequences with ambiguous
191 base calls, and sequences with homopolymer runs exceeding 6 bp were removed. Operational
192 taxonomic units (OTU) were assigned using the open source Quantitative Insights into Microbial
193 Ecology (QIIME) version 1.9.1bioinformatic pipeline (Caporaso et al., 2010), using the open-
194 reference protocol at 97% sequence identity with UCLUST as the clustering tool and SILVA
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195 release 128 (Quast et al., 2013) as the database. All OTUs annotated as mitochondria, chloroplasts,
196 cyanobacteria, unassigned, and OTUs with fewer than five reads were removed from the dataset.
197 The QIIME-generated output file in the Biological Observation Matrix (BIOM) format was
198 used for downstream data analysis and visualization in R version 3.3 using the Vegan (Oksanen
199 J., 2020), Phyloseq 1.26.1 and ggplot2 3.3.2 packages (McMurdie & Holmes, 2013, Hadley, 2009).
200 Samples were rarefied to the lowest sample depth to compute diversity analysis. The rain
201 core microbiome analysis was performed with the microbiome R package (Lahti L., 2020) using
202 a detection threshold of 0.1% and 100% as a prevalence threshold. Alpha diversity was assessed
203 using observed OTUs, Shannon, and Simpson indices. Differences in alpha diversity were
204 determined by pairwise Wilcoxon rank sum test with the Holm correction method. Beta diversity
205 was analyzed based on unweighted UniFrac distance, weighted UniFrac distance, and Bray-Curtis
206 dissimilarity. Differences in beta diversity were determined using PERMANOVA as implemented
207 in adonis2 (from vegan 2.5-6 using models with 999 permutations, adonis2(dist.matrix
208 ~Treatment*TimePoint + DateExperiment, permutations = 999). Dissimilarity matrices were
209 visualized using the Principal Coordinates Analysis (PCoA) ordination method as implemented in
210 the Phyloseq package. DESeq2 (Love et al., 2014) was used to identify OTUs that were
211 differentially abundant across treatment groups and time points. OTUs were filtered using a False
212 Discovery Rate (FDR) cutoff of 0.01.
213 For metagenomic data analysis, raw 150 bp paired-end reads from Illumina were processed
214 to remove short and low quality reads using Trimmomatic (version 0.38) (Bolger et al., 2014).
215 Reads with an average per base quality below 30 and read length below 150bp were filtered out.
216 Filtered reads were then classified taxonomically using Centrifuge (version 1.0.4) (Kim et al.,
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217 2016) and Sourmash version 2.0.0 (Brown, 2016) only retaining species that were identified by
218 both classifiers.
219 For Oxford Nanopore Technologies sequencing, the fast5 files containing the raw reads
220 obtained from the MinION sequencer were base-called using Guppy (v3.3.2). The ONT workflow
221 What is in my pot (WIMP v2019.7.9) was used for bacterial identification and a classification
222 (Juul et al., 2015).
223
224 RESULTS
225
226 The bacterial population size on tomato plants exposed to rain is larger than that of
227 tomato plants not exposed to rain. Our investigation into the role of rain in shaping the
228 phyllosphere microbiome started by comparing the bacterial population size on tomato plants
229 grown indoors under controlled conditions with that of plants grown outside exposed to
230 environmental disturbances including rainfall. We observed that tomato plants grown over four
231 weeks outdoors in plastic pots at the Virginia Tech Kentland research farm harbored bacterial
232 populations of significantly larger size compared to plants grown under laboratory conditions for
233 the same period (Figure 1A). Interestingly, even plants grown on the roof of a campus research
234 building, which minimized microbial dispersal from soil and plants compared to the farm
235 environment, had bacterial populations that were significantly larger compared to those of plants
236 grown indoors (Figure 1B). These results suggest that air-borne and rain-borne bacteria through
237 dry and/or wet deposition had colonized the tomato plants grown outside.
238 To test the effect of rain on the bacterial population size in the tomato phyllosphere under
239 controlled conditions, we collected rain and used it as an inoculum to treat 4-week old tomato
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240 plants that had been grown under laboratory conditions. Seven days after plants were treated with
241 rain, they carried a significantly larger bacterial population count compared to plants that had been
242 treated with autoclaved rain (Figure 1C). This result suggested that at least some rain-borne
243 bacteria are able to colonize plant leaves efficiently and may thus impact bacterial population
244 composition in the phyllosphere.
245 Rain-borne microbiota in Blacksburg, Virginia, are highly variable. As a first step
246 towards identifying which bacterial taxa present in rainfall may efficiently colonize the tomato
247 phyllosphere, we characterized the bacterial diversity associated with nine rainfall events during
248 2015 and 2016. Rainfall was collected in sterile plastic bags on the same roof of the research
249 building previously used to grow tomatoes, DNA was extracted, and the 16S rRNA gene was
250 amplified and sequenced (Table 1). In total, 1,186,365 short reads were obtained. After 97% OTU
251 clustering and removal of all non-bacterial and unassigned reads, a total of 892,142 reads
252 remained. All samples were rarefied to 6419 reads per sample and 5958 OTUs overall were
253 identified. Rarefaction curves (Supplementary Figure 1) show that this is an underestimate of the
254 total number of OTUs since not all samples were sequenced to saturation. The number of OTUs
255 per rarefied sample ranged from 541 (June 2019) to 1782 (April 2016).
256 Taxonomic diversity analysis revealed Proteobacteria, Actinobacteria, Bacteroidetes,
257 Acidobacteria, and Firmicutes to be the dominant taxa at the phylum level. At the class level,
258 Alphaproteobacteria followed by Gammaproteobacteria, Actinobacteria, Acidobacteria, and
259 Bacilli were most abundant. However, there were considerable differences among samples. For
260 example, Chlamydiae represented the most abundant taxon in the rain sample collected in August
261 2015 at 36% relative abundance, represented only 0.4% in the sample collected in July 2016, and
262 were less than 0.1% in all other samples. Deltaproteobacteria were only present in August 2015,
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263 May 2016 and July 2016 at 12.79%, 1.42%, and 17.03% relative abundance, respectively.
264 Actinobacteria were most abundant in rain samples collected in April 2016 (25.56%) and
265 December 2016 (16.29%) while they only represented 2.18% of the October 2016 sample.
266 Gammaproteobacteria represented 80% of relative abundance in June 2019 but only averaged
267 28.41% in the other samples (Figure 2A).
268 Even more dramatic differences in relative abundance between samples were observed at
269 the genus level (Figure 2B). However, seventeen OTUs were identified across all nine samples
270 when setting a detection threshold of 0.1%. These OTUs belong to the following genera (listed in
271 order of decreasing relative abundance): Acidiphilium, Bryocella, Beijerinckiaceae 1174-901-12,
272 Methylobacterium, Massilia, Burkholderiaceae DQ787673.1.1527, Pantoea, Pseudomonas and
273 Sphingomonas (Supplementary Figure 2).
274 Concentrated rain microbiota, filter-sterilized rain, and sterile water all affect the
275 phyllosphere of lab-grown tomato plants. Next, we decided to determine if inoculation with rain
276 microbiota would not only increase the size of the tomato phyllosphere microbiota as seen in
277 Figure 1 but also change its composition because of colonization of tomato leaves by rain-borne
278 bacteria. In six independent experiments, 100-fold concentrated rain microbiota (100X-rain)
279 derived from six out of the nine collected rainfall events described above (April 2015, August
280 2015, March 2016, April 2016, May 2016, July 2016) were used to inoculate tomato plants. In
281 parallel, a separate set of tomato plants were treated each time with filter-sterilized rain obtained
282 from the concentration step above. For each of the 2016 experiments, additional tomato plants
283 were treated with sterile water. 16S rRNA amplicons were prepared and sequenced from DNA
284 extracted from leaf washes of tomato plants two hours after treatments (day-0) and seven days
285 later (day-7). For the March 2016 and May 2016 experiments enough rain and enough plants were
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286 available so that each treatment was done in duplicate. For the April 2016 experiment, two day-7
287 100X-rain samples were taken. For the other three experiments, only one sample per treatment and
288 time point was processed.
289 In total, 3,291,016 reads were obtained from 45 phyllosphere samples (Supplementary
290 Table 1). After 97% OTU clustering and removing all non-bacterial and unassigned reads, a total
291 of 3,118,320 reads remained in the data set. Rarefaction curves show that most of the samples were
292 deeply sequenced (Supplementary Figure 1).
293 After subsampling to 6,670 reads per sample, we identified a total of 9,923 OTUs and
294 measured the alpha diversity based on the total number of observed species and by Shannon and
295 Simpson diversity indices. Figure 3 shows the alpha diversity values for rain compared to treated
296 plants at day 0 and day 7. Although alpha diversity of rain microbiota was highly variable, the
297 number of observed OTUs in rain was significantly higher than day-7 samples for all three
298 treatments (p-values of 0.020, 0.050, and 0.028 respectively as determined by the pairwise
299 Wilcoxon rank sum test with the Holm correction method) (Supplementary Table 2). Also, the
300 number of observed OTUs significantly decreased in plants treated with 100X-rain from day 0 to
301 day 7 (p-value 0.027). Comparing Shannon’s index, we observed a depletion in richness from day
302 0 to day 7 for plants treated with 100X-rain (p-value 0.049) as well as for plants treated with
303 filtered-rain (p-value 0.023). No significant differences in alpha diversity were observed between
304 day 0 and day 7 for plants treated with sterile-water.
305 Principal coordinate analysis (PCoA) derived from weighted and unweighted UniFrac
306 distance metrics and from Bray-Curtis dissimilarity (Figure 4) revealed that most rain samples
307 clustered together while phyllosphere samples did not. While PCoA derived from weighted
308 Unifrac distances only separated phyllosphere samples along the second coordinate, PCoA derived
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309 from unweighted Unifrac distances and Bray-Curtis dissimilarity separated phyllosphere samples
310 along both axes. Therefore, bacterial communities on lab-grown tomato plants were even more
311 dissimilar from each other than the dissimilarity between rain communities. A permutational
312 multivariate analysis of variance (PERMANOVA) for Bray-Curtis dissimilarity revealed that date
313 of experiment, day of sampling (day 0 versus day 7), and treatment (100X-rain, filter-sterilized
314 rain, and sterile water) were all significantly associated with bacterial community composition.
315 (Supplementary Table 3). In regard to the date of experiment, it can be seen in panels 4B and 4C
316 how samples clearly cluster by date of experiment along the X axis. Since this clustering is
317 independent of treatment and day of sampling, the starting tomato phyllosphere population appears
318 to have been different between experiment dates. Secondly, day 7 samples differed from day 0
319 samples on the Y axis independently of which treatment was applied revealing that inoculation
320 and incubation under high humidity of plants by itself shifted the composition of the tomato
321 phyllosphere population. Thirdly, although treatment was significant, there was interaction
322 between treatment and date of experiment. Therefore, the effect of 100X-rain was not significantly
323 different compared to the effect of filter-sterilized rain or sterile water. In other words, beta
324 diversity analysis was unable to reveal if rain-borne bacteria present in the 100X-rain treatments
325 affected the tomato phyllosphere community, possibly because of the differences in the
326 composition of the microbial rain and phyllosphere communities between experiments.
327 After finding that beta diversity analysis was inconclusive, we decided to compare the
328 actual taxonomic diversity between samples. We observed an enrichment in Proteobacteria in the
329 tomato phyllosphere on day 7 compared to the day 0 regardless of treatment. In contrast, relative
330 abundance of Actinobacteria and Firmicutes was dramatically reduced 7 days post-treatment in all
331 plants treated with 100X-rain but not after treatment with filter-sterilized rain or sterile water
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332 (Figure 5). At the class level, Gammaproteobacteria were significantly enriched in all tomato
333 phyllosphere day 7 samples. Actinobacteria and Bacilli were reduced on day 7 in plants treated
334 with 100X rain compared with filter-sterilized rain or sterile water. Unexpectedly, no consistent
335 increase of any taxon at either phylum, class, or genus level was observed from day 0 to day 7 for
336 plants treated with 100X-rain alone.
337 One-hundred and four rain-borne OTUs increased significantly in relative
338 abundance in the tomato phyllosphere exclusively after treatment with concentrated rain
339 microbiota. Since we did not find any taxon between genus and phylum level that exclusively
340 increased from day 0 to day 7 on tomato plants treated with 100X-rain, we wanted to determine if
341 we could find any individual rain-borne OTUs that did so. To do this we used DESeq2 (Love et
342 al., 2014) as it is relatively robust to small and unequal sample sizes as in the present study..
343 First, we directly compared day-0 and day-7 phyllosphere microbiota treated with 100X-
344 rain and found that one-hundred and four OTUs (out of a total of 7,994 OTUs) significantly
345 increased (Supplementary Table 4). These OTUs belonged to the genera Massilia (27 OTUs),
346 Pantoea (18 OTUs), Duganella (13 OTUs), Pseudomonas (11 OTUs), Enterobacter (5 OTUs),
347 Flavobacterium (3 OTUs), Janthinobacterium (2 OTUs), and Curtobacterium (1 OTUs). 16
348 unknown OTUs from the Burkholderiaceae and 5 unknown OTUs from the Enterobacteriaceae
349 families significantly increased in relative abundance as well (Figure 6A). Importantly, not a
350 single OTU significantly differed in abundance between day 0 and day 7 on tomato plants treated
351 with either filtered-rain or dd-water. This suggests that the OTUs which increased in relative
352 abundance from day 0 to day 7 on tomatoes after treatment with 100X-rain originated from rain
353 and were not members of the bacterial community present in the tomato phyllosphere prior to
354 inoculation.
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355 We then complemented the previous comparison with a slightly different analysis
356 comparing the bacterial composition of rain microbiota with phyllosphere microbiota seven days
357 after treatment with 100X-rain. We observed that thirty-five rain-borne OTUs out of a total of
358 5,958 OTUs had a significantly higher relative abundance on tomatoes at day-7 compared to their
359 relative abundance in rain (Figure 6B). These OTUs (in order of decreasing differential
360 abundance) mostly belonged to the same genera as the genera identified in the day-0 to day-7
361 comparison : Massilia, Pseudomonas, Pandoraea, Streptomyces, and Pantoea. The genus Pantoea
362 was the genus that most consistently increased in relative abundance. In fact, Pantoea was detected
363 in all rain collections (Figure 7A) and reached a high relative abundance (between 4% - 44%) in
364 the tomato phyllosphere after 7 days each time its abundance in rain was above 1% (observed 4
365 out of 6 times). Genus-level abundance in rain and phyllosphere samples are also shown for
366 Flavobacterium, Janthinobacterium, Pseudomonas, Methylobacterium, and Massilia, which all
367 successfully colonized the tomato phyllosphere each time they were detected in rain (Figure 7B-
368 E).
369 In contrast, 61 OTUs found in rain samples significantly decreased in relative abundance
370 by day 7 suggesting that these rain-borne taxa were definitely not able to colonize tomato leaves.
371 These OTUs belonged to the following genera (list of the first 10 bacterial genera in order of
372 decreasing differential abundance): Acidiphilium, Beijerinckiaceae-1174-901-12, Bryocella,
373 Actinomycetospora, Methylobacterium, Methylocella, Granulicella, Belnapia, Modestobacter,
374 and Blastococcus. The genus Acidiphilium best exemplifies this group of taxa. It was detected at
375 high relative abundance in most rain samples, it was observed on plants treated with 100X-rain on
376 day 0, but it was never found on plants treated with 100X-rain on day 7 (Figure 7G). This clearly
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377 shows that Acidiphilium is a common rain-borne bacterial genus that does not include any
378 members able to colonize the tomato phyllosphere.
379 Several other pairwise comparisons were made to gain additional insights into differences
380 in composition between microbiota at the OTU level. For example, we determined which OTUs
381 were present in significantly higher abundance in rain compared to tomatoes treated with sterile
382 water on day 0 to identify OTUs that are commonly present in rain but present in low abundance
383 (or not at all) on laboratory-grown tomato plants (Supplementary Figure 3A). One hundred
384 seventy-four such OTUs (out of a total of 5,958 OTUs present in rain) were identified. Most of
385 these OTUs belonged to the following genera (list of the first 10 bacterial genera in order of
386 decreasing differential abundance in rain): Caedibacter, Tumebacillus, Acidiphilium,
387 Methylobacterium, Rhodovastum, Belnapia, Sphingomonas, Methylocella, Bacillus and Pantoea.
388 On the other hand, 109 OTUs had significantly higher relative abundance in laboratory-
389 grown tomatoes (tomatoes at day 0 after being treated with sterile water) than in rain
390 (Supplementary Figure 3A). These taxa are thus common inhabitants of tomatoes grown under
391 our laboratory conditions in the absence of rain. They mostly belonged to the following genera
392 (list of the first 10 bacterial genera in order of decreasing differential abundance):
393 Hyphomicrobium, Rhodanobacter, Chryseobacterium, Burkholderia, Paenibacillus,
394 Nocardioides, Pandoraea, Bacillus, Novosphingobium, and Streptomyces.
395 One genus that did not fall into any of the above categories was the genus Bacillus: Bacillus
396 OTUs were observed at high relative abundance in rain samples as well as in the tomato
397 phyllosphere at day 0 independent of treatment and on day 7 after sterile-rain and dd-water
398 treatments but not after 100X-rain treatments (Figure 7H). This suggests that Bacillus OTUs were
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399 present in rain as well as on lab-grown tomatoes but were outcompeted by other rain-borne bacteria
400 added with the 100X-rain treatments.
401 To more precisely identify the OTUs that represented the most efficient tomato colonizers,
402 we used metagenome shotgun sequencing to re-sequence the microbiota associated with rain
403 samples and with plants treated with 100X-rain on day 0 and day 7. The metagenome shotgun
404 sequencing approach generated 260,035,170 short-reads. After quality control, 7,543,305 reads
405 remained, of which 98.26% were identified as bacterial reads. Table 2 summarizes the results
406 listing the bacterial species present in rain that numerically increased in abundance from day 0 to
407 day 7 and ranked from high to low based on their relative abundance on day 7. Based on this
408 analysis, rain-borne species Pantoea vagans and Pantoea agglomerans were the most effective
409 tomato phyllosphere colonizers followed by Pseudomonas citronellolis, Novosphingobium
410 resinovorum, an unnamed Buttiauxella species, Erwinia gerundensis, Pseudomonas fluorescens,
411 Cedecea neteri, and an unnamed Massilia species. Additional Pantoea, Massilia, Pseudomonas,
412 Janthinobacterium, and Enterobacter species ranked highly as well. The metagenomic analysis
413 thus mostly confirmed and refined our 16S rRNA results of which rain-borne taxa are the most
414 effective colonizers of the tomato phyllosphere.
415 There are consistent differences between phyllosphere microbiota of tomato plants
416 never exposed to rain and naturally exposed to rain outdoors. After identifying bacterial taxa
417 present in rain that efficiently colonized tomato leaves under laboratory conditions, we tested the
418 hypothesis that these taxa would be abundant in tomato plants grown outdoors in pots containing
419 autoclaved soil on the roof of the same research building where we had collected rain samples
420 earlier (7 samples) but be missing, or at least be underrepresented, in phyllosphere microbiota of
421 greenhouse-grown tomatoes that had never been exposed to rain. This second set of plants included
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422 tomato plants grown in a hydroponic system (29 samples) and tomato plants grown in soil (18
423 samples), both in a commercial greenhouse (Supplementary Table 5). In total, we obtained
424 4,166,519 reads. After 97% OTU clustering and removing all non-bacterial and unassigned reads,
425 a total of 3,080,204 reads remained. Samples were rarefied to 2,546 reads per sample and 10,525
426 OTUs overall were identified. Taxonomic diversity analysis revealed Proteobacteria, Firmicutes,
427 Actinobacteria and Bacteroidetes to be the dominant bacterial taxa (Figure 8A), the same phyla
428 identified on the lab-grown tomatoes. Alpha diversity analysis supported by the total number of
429 observed species, and by the Shannon and Simpson diversity indices (Figure 8B) together with a
430 pairwise comparisons using the Wilcoxon rank sum test showed significant differences in the
431 number of OTUs between the hydroponic and the soil system (Supplementary Table 6).
432 To identify any OTUs present at significantly higher relative abundance in tomato plants
433 grown outside exposed to rain compared to the tomato plants grown in the greenhouse
434 hydroponically in the absence of rain, DESeq2 was used again. Forty OTUs from the genera
435 Pandoraea, Curtobacterium, Massilia, Gemmatirosa, Kineococcus, Methylobacterium,
436 Sphingomonas, Buchnera, Alloiococcus, Pseudomonas, and Streptococcus were found (Figure
437 9A). Similarly, 58 OTUs from the genera Pantoea, Pelomonas, Kineococcus, Methylobacterium,
438 Massilia, Aureimonas, Buchnera, Alloiococcus, Pseudomonas, Streptococcus, and Sphingomonas
439 were of significantly higher relative abundance on the tomato plants grown outside exposed to rain
440 compared to the tomato plants growing in soil never exposed to rain in the greenhouse (Figure
441 9B). Note that, as we hypothesized, OTUs in the genera Massilia, Curtobacterium, Pseudomonas,
442 and Pantoea, were among the same genera as the OTUs identified to significantly increase in
443 relative abundance in the phyllosphere of tomato plants treated with concentrated rain microbiota
444 7 days post inoculation. However, unexpectedly, the actual OTUs of these genera identified in this
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445 comparison were not the same as those identified in the controlled laboratory experiments (see
446 discussion section for possible explanations).
447 Finally, we performed another small experiment collecting rain on the same roof as in the
448 previous experiments and exposing one set of tomato plants to all rain events while taking another
449 set of plants inside before each rain event. From one rain event (June 10, 2019), phyllosphere
450 communities from a single tomato plant exposed to rain (collected on June 21, 2019), and another
451 tomato plant not exposed to rain (collected on the same date) were sequenced together with a
452 sample of the corresponding rainfall using ONT’ MinION platform. A total of 194,591 long reads
453 were analyzed using the ONT taxonomic classifier WIMP. Table 3 shows the most abundant
454 species present in the three samples ranked by relative abundance on the tomato plant exposed to
455 rain. Yet again, species of the genera Massilia, Pantoea, Methylobacterium, Pseudomonas, and
456 Janthinobacterium (and some additional species outside of these genera) were present in the rain
457 sample as well as in the tomato sample exposed to rain but absent (or almost absent) in the tomato
458 sample not exposed to rain. While this experiment was too small for any statistical analysis, the
459 result is consistent with the laboratory results as well as the comparison of tomatoes grown outside
460 exposed to rain with those grown in a greenhouse not exposed to rain.
461
462 DISCUSSION
463
464 While our general understanding of the plant microbiome has increased dramatically over the last
465 few years, the basic question of where the bacteria that colonize and inhabit the phyllosphere
466 originate from has remained unanswered. The main approach in trying to answer this question has
467 been to make comparisons of the composition of the phyllosphere microbiome with the
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468 microbiomes of putative reservoirs (Maignien et al., 2014, Zarraonaindia et al., 2015, Ottesen et
469 al., 2016, Wagner et al., 2016, Grady et al., 2019). To complement this approach, here we used
470 controlled laboratory experiments.
471 We decided to focus on rain since previous studies provided evidence that at least the
472 bacterial leaf pathogen, Pseudomonas syringae, may be disseminated by precipitation and
473 efficiently colonize the plant phyllosphere (Monteil et al., 2016, Morris et al., 2008). Moreover, at
474 least temporary shifts in the composition of phyllosphere communities after rain events were
475 observed (Allard et al., 2020). In a first step, we found that tomato plants naturally exposed to rain
476 outdoors, or simply sprayed with rainfall when grown in the lab, carried significantly higher
477 bacterial populations sizes compared to lab-grown plants that had not been treated with rainfall or
478 that were treated with sterilized rainfall. While plants grown outside may have also been colonized
479 by airborne bacteria through dry-deposition or by soil-borne bacteria after being splashed during
480 rainfall events, the observation that treating lab-grown plants with rain caused the bacterial
481 population size to increase more than spraying lab-grown plants with sterilized rain was a strong
482 indication that the observed increase in population size was due to the colonization and growth of
483 rain-borne bacteria.
484 To dig deeper into the possibility that rain harbors bacteria that can effectively colonize
485 and grow on tomato leaves, we decided to characterize the taxonomic composition of rainfall
486 events and then determine if any of the identified members of the rain microbiota would increase
487 in relative abundance on tomato plants treated with concentrated rain microbiota (100X-rain) but
488 not on tomato plants treated with filter-sterilized rain or sterile water. We decided on using
489 concentrated rain microbiota instead of rain since we had previously found that rain contained as
490 few as 4 x 103 CFU l-1 (Failor et al., 2017) and the maximum volume that we can spray on a tomato
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491 plant before water runs off the leaves is only 10 mL. Therefore, as few as 40 bacteria may get
492 inoculated on an entire plant using rain as inoculum in a lab experiment, which we deemed not to
493 be enough to lead to a bacterial population size that could be analyzed using 16S rRNA amplicon
494 sequencing. We thus used 100X-rain concentrate, acknowledging that we artificially aided rain-
495 borne bacteria in our experiment.
496 The most important observation from the characterization of the rainfall microbiota was
497 that each collected rainfall event harbored a very different bacterial community. This is in line with
498 other recent results on rainfall collected in the USA, Europe, and Asia (Aho et al., 2020, Cáliz et
499 al., 2018, Woo & Yamamoto, 2020) that showed that the taxonomic composition of microbiota in
500 rain changes with origin of air masses and season. This meant for our experiment that we could
501 not expect to find the same taxa to colonize and grow on tomatoes in each inoculation experiment.
502 It was also important to use appropriate controls when inoculating lab-grown tomato plants
503 with 100X-rain. Importantly, tomato plants were not grown in sterile conditions. Therefore, they
504 already carried microbiota at the time of inoculation and simply spraying these plants with water
505 and incubating them at high humidity (as we did to favor plant colonization) could be expected to
506 lead to changes in relative abundance of the pre-existing microbiota. Moreover, rain contains
507 nutrients and bacteriophages that are not removed by filtering and that will also affect pre-existing
508 microbiota. Therefore, we used both, filter-sterilized rain (including nutrients and possibly
509 bacteriophages but no bacteria) and autoclaved double-distilled water (expected to contain neither
510 nutrients nor bacteriophages nor bacteria) as controls.
511 Comparison of rain microbiota with phyllosphere microbiota on day-0 and day-7 for the
512 three different treatments yielded some results confirming our hypothesis that rain contains
513 effective colonizers of tomato leaves while other results were ambiguous. Firstly, the observed
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514 drop in alpha diversity for phyllosphere microbiota from day-0 to day-7 after treatment with 100X-
515 rain is in agreement with the expected increase in relative abundance of some effective tomato leaf
516 colonizers accompanied by a decrease in relative abundance of many rain-borne bacteria that are
517 not adapted to tomato leaves and that are thus not effective tomato colonizers. The observed
518 decrease in alpha diversity from day-0 to day-7 for the sterile rain treatment may have been due to
519 growth of some pre-existing tomato phyllosphere members that thrived under the high humidity
520 conditions applied for two days after inoculation and the nutrients added with the rain water, which
521 helped them outcompete other members of the pre-existing microbiota. It is also possible that
522 bacteriophages present in the filter-sterilized rain reduced the relative abundance of some
523 phyllosphere members to below the detection limit.
524 In regard to beta diversity, we had expected the composition of the day 0 microbiota to be
525 similar to each other because tomato plants of the same cultivar were grown in autoclaved soil in
526 relatively stable laboratory conditions. Therefore, it was surprising to find phyllosphere samples
527 to differ more from each other (even on day-0 after sterile water treatments) compared to the
528 differences among rain samples. This was the case for weighted UniFrac distances, unweighted
529 UniFrac distances, and the Bray-Curtis dissimilarity static. A possible explanation is that the
530 composition of the phyllosphere microbiota of our lab-grown tomatoes was determined by
531 stochastic processes because of the low concentration of plant-associated bacteria present in the
532 indoor air and the autoclaved soil that was used for growing.
533 Another unexpected result was that beta diversity significantly changed from day-0 to day-
534 7 for all three treatments. Although the high humidity maintained for two days after inoculation
535 was expected to have some effect on the phyllosphere community, we still expected 100X-rain to
536 have a stronger effect on beta diversity than sterile water. Similarly unexpected, the taxonomic
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537 composition at the phylum, class, and genus level on day-0 and day-7 did not reveal any consistent
538 change unique to the treatment with 100X-rain compared to filter-sterilized rain or sterile water.
539 Taken together, these results suggested that, if they existed, tomato leaf colonizers present in rain
540 were individual species and changes in abundance of these individual species were not evident
541 from the overall comparison of beta diversity or taxonomic composition at higher taxonomic ranks.
542 Therefore, we decided to look at changes at the OTU level. To do this, we used DESeq2
543 (Love et al., 2014) a tool originally developed to identify significant changes in gene expression
544 in RNA-seq experiments, which have similar challenges to OTU tables, and which has been shown
545 to be effective for smaller OTU datasets like ours (Weiss et al., 2017). We made several
546 comparisons. Most importantly, not a single OTU significantly increased from day 0 to day 7 after
547 treatment with filter-sterilized rain or sterile water but 104 OTUs increased significantly after
548 treatment with 100X-rain. Since none of these OTUs significantly increased from day-0 to day-7
549 after treatment with filter-sterilized rain or sterile water, they were most likely rain-borne.
550 The 104 OTUs belong to 10 genera with one of them being the genus Pantoea. The DeSeq2
551 analysis identified 18 OTUs of this genus that significantly increased in relative abundance from
552 day 0 to day 7 after being treated with 100X-rain. Importantly, Pantoea OTUs were also present
553 in all rain samples (including the one sequenced with ONT’s MinION). Moreover, the species P.
554 agglomerans and P. vagans were identified as the most abundant species in several of the tomato
555 phyllosphere day 7 samples after being treated with 100X-rain based on metagenomic sequencing.
556 Also, two Pantoea OTUs were present in significantly higher relative abundance in tomatoes
557 grown outside compared to tomato grown organically inside a commercial greenhouse, and P.
558 agglomerans and P. vagans were both identified in the rain metagenome as well as in the
559 metagenome of a tomato plant exposed to rain but not in a tomato plant not exposed to rain using
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560 ONT MinION sequencing. Moreover, the genus Pantoea is well known to include plant pathogenic
561 bacteria and beneficial plant-associated bacteria (Coutnho & Venter, 2009, Walterson &
562 Stavrinides, 2015, Mechan Llontop et al., 2020), we previously identified 192 Pantoea isolates in
563 a culture-dependent study of precipitation samples (Failor et al., 2017), and Pantoea species were
564 recently identified both in rainfall before and after falling through a forest canopy, with higher
565 relative abundance in the throughfall samples (Ladin et al., 2021). Therefore, based on the results
566 obtained here and data in previous literature, members of the genus Pantoea are likely
567 phyllosphere inhabitants that originate from rainfall.
568 Another rain-borne genus that includes species that appear to successfully colonize tomato
569 plants is Massilia. Members of this genus were found in all rain samples (those analyzed by 16S
570 rRNA amplicon sequencing and the one sequenced with ONT’s Minion). Twenty-seven OTUs of
571 this genus significantly increased between day-0 phyllosphere samples and day-7 samples for
572 100X-rain treated plants. Two Massilia species were also found among the species with the highest
573 relative abundance in the metagenomic sequences of the 100X-treated tomato samples on day 7.
574 One Massilia OTU each was more abundant in tomatoes grown outdoors compared to
575 hydroponically or organically grown tomatoes in the commercial greenhouse, respectively. Four
576 Massilia species were found in the rain sample and tomato sample grown outdoors but not in the
577 tomato plant not exposed to rain when using ONT MinION sequencing. As with Pantoea, Massilia
578 species were cultured out of precipitation by us previously (Failor et al., 2017) and were recently
579 found in rain and rain that had fallen through a forest canopy (Ladin et al., 2021). Finally, OTUs
580 and named species belonging to the genus Massilia have been found in plants, soil, and even
581 extreme environments (Ofek et al., 2012, Rastogi et al., 2012, Bodenhausen et al., 2013, Purahong
582 et al., 2018, Singh et al., 2019, Holochová et al., 2020). Therefore, members of the genus Massilia
26 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
583 may cycle through multiple environments and some of them may be transported by rain to leaf
584 surfaces where they colonize the phyllosphere.
585 Other rain-borne genera likely to colonize the tomato phyllosphere based on our data
586 include Janthinobacterium, which, as the genus Massilia, is a member of the Burkholderiaceae
587 family. Four Janthinobacterium species were also found in rain and in the rain-exposed tomato
588 plant but not in the tomato plant protected from rain in the ONT MinION experiment. However,
589 Janthinobacterium was not found at significantly higher relative abundance in tomato plants
590 grown outside compared to greenhouse-grown tomatoes. Its inconsistent presence in rain may
591 explain this result.
592 Finally, we found evidence for OTUs and named species of the genus Pseudomonas to
593 colonize tomato plants. Unexpectedly though, we did not find a single member of the
594 Pseudomonas syringae species complex (P. syringae sensu lato), which includes many plant
595 pathogenic and commensal lineages (Vinatzer et al., 2016, Monteil et al., 2016). We do not have
596 any good explanation why we neither found P. syringae at relatively high abundance in the
597 analyzed rain samples nor in our phyllosphere samples treated with 100X-rain although we had
598 previously cultured P. syringae from rain (Failor et al., 2017) and from plants in our geographic
599 area (Clarke et al., 2010). We conclude that while P. syringae pathogens are present in rain and
600 disseminated by precipitation, they may not be a major component of precipitation microbiota, at
601 least not in the geographic area where the experiments here described were performed.
602 Importantly though, while our data and the literature suggest that members of some
603 common phyllosphere genera are rain-borne, the fact that we found different enrichment of OTUs
604 from these genera across experimental conditions, lab versus greenhouse, precluded the
605 identification of likely rain-borne tomato phyllosphere colonizers at the species level. One possible
27 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
606 explanation for this is that each rain event harbored such different taxa and this increased variation
607 coupled with low replication meant that OTUs with higher relative abundance on tomatoes grown
608 outside were simply missed in the lab experiments. Conversely, the small number of analyzed
609 tomato plants grown outside exposed to rain made it difficult to find significant differences
610 compared to the tomatoes grown inside not exposed to rain. Finally, laboratory conditions may
611 not have allowed some of the OTUs found outside to effectively grow on tomato plants inside the
612 laboratory. On the other hand, artificial light and almost constant temperature and humidity may
613 have favored tomato colonization of related, but different, species compared to the most effective
614 colonizers of tomato plants grown outside, where plants are exposed to natural sunlight, including
615 UV radiation and dramatic temperature and humidity changes. These differences in environmental
616 conditions may explain why members of the genera Sphingomonas and Methylobacterium were
617 consistently found in rain and in significantly higher abundance on tomato plants grown outside
618 than in greenhouse-grown tomatoes but OTUs of these genera did not significantly increase in our
619 controlled laboratory experiments after 100X-rain treatments. Finally, the use of concentrated rain
620 microbiota instead of rain may have led to increased competition between rain-borne bacteria and
621 suppressed the colonization efficiency and growth of some while favoring the growth of others.
622 To follow up on the results reported here and to gain further insight into the relative
623 importance of seeds, soil, the atmosphere, and precipitation as reservoirs of phyllosphere
624 microbiota, we propose to expand the kind of controlled experiments we performed here but
625 growing tomatoes outdoors from either sterilized seeds or non-sterilized seeds, either not limiting
626 exposure to precipitation or limiting exposure to precipitation (for example, through the use of
627 mobile rain-out shelters), and growing plants in native versus sterile soil. Moreover, strain-level
628 metagenomics (Olm et al., 2021) of all reservoir microbiota and phyllosphere microbiota could
28 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
629 provide the necessary strain-level resolution to identify which strains from which reservoirs are
630 the most important colonizers of the phyllosphere.
631
632 DATA DEPOSITION
633
634 Sequences and metadata are being deposited at NCBI under BioProject DPRJNA719680. All
635 read processing steps, bioinformatic workflows, and scripts used in this research are available on
636 GitHub (https://github.com/marcoeml/VinatzerLab-Mechan-rain-phyllosphere-microbiota-2020).
637
638 FUNDING
639
640 This research was supported by the National Science Foundation (DEB-1241068 and IOS-
641 1754721). Funding to BAV was also provided in part by the Virginia Agricultural Experiment
642 Station and the Hatch Program of the National Institute of Food and Agriculture, United States
643 Department of Agriculture.
644
645 LITERATURE CITED
646
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39 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
866 TABLES
867 Table 1. Metadata for analyzed rain samples. 868 Rain # raw used for plant Month Year collection ID reads inoculations VTP049 April 2015 7,133 Yes VTP050-1 August 2015 75,555 Yes VTP050-2 August 2015 68,612 Yes VTP061 March 2016 75,166 Yes VTP062 April 2016 7,533 Yes VTP063 May 2016 27,729 Yes VTP064 July 2016 142,736 Yes VTP065 October 2016 35,216 No VTP066 December 2016 32,866 No VTP2019 June 2019 419,596 No 869 870
40 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
871 Table 2. Species with highest relative abundance on tomato plants on day-7 after treatment with 872 100X-rain based on metagenomic sequencing. 873 # average average average highest positive species abundance abundance abundance abundance day 7 in rain2 on day 02 on day 72 on day 7 samples1 Pantoea vagans 4 0.09 0.01 2.86 8.69 Pantoea agglomerans 3 0.03 0.01 2.12 4.25 Novosphingobium resinovorum 1 0.00 0.00 1.54 1.54 Pseudomonas citronellolis 2 0.01 0.08 1.21 1.98 Buttiauxella sp. 2 0.01 0.03 0.79 1.49 Janthinobacterium sp. 1 0.01 0.01 0.77 0.77 Pseudomonas fluorescens 4 0.03 0.02 0.75 1.16 Erwinia gerundensis 2 0.01 0.01 0.75 1.31 Massilia putida 3 0.01 0.01 0.63 0.76 Janthinobacterium agaricidamnosum 1 0.01 0.00 0.62 0.62 Cedecea neteri 2 0.01 0.02 0.53 1.00 Pseudomonas orientalis 2 0.00 0.00 0.53 0.79 Massilia sp. 4 0.01 0.02 0.45 0.90 Flavobacterium sp. HYN0086 1 0.06 0.02 0.41 0.41 Flavobacterium anhuiense 1 0.08 0.04 0.40 0.40 Flavobacterium sp. 1 0.04 0.02 0.33 0.33 Pseudomonas azotoformans 4 0.01 0.00 0.31 0.48 Pseudomonas sp. 2 0.00 0.00 0.27 0.33 Pseudomonas putida 1 0.02 0.01 0.27 0.27 Enterobacter sp. 1 0.00 0.01 0.26 0.26 Klebsiella michiganensis 1 0.00 0.01 0.25 0.25 Pseudomonas protegens 1 0.00 0.02 0.25 0.25 Pantoea ananatis 1 0.00 0.00 0.24 0.24 Pseudomonas trivialis 1 0.00 0.00 0.24 0.24 Pseudomonas rhizosphaerae 2 0.01 0.01 0.23 0.27 Brevundimonas sp. 1 0.01 0.00 0.23 0.23 Pseudomonas veronii 1 0.00 0.00 0.23 0.23 Pseudomonas syringae 1 0.01 0.02 0.22 0.22 Enterobacter cloacae 2 0.02 0.01 0.15 0.24 Escherichia coli 3 0.14 0.12 0.15 0.22 Sphingobium sp. 1 0.00 0.00 0.15 0.15 Hyphomicrobium sp. 1 0.01 0.00 0.13 0.13 Paraburkholderia fungorum 1 0.00 0.00 0.11 0.11
41 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
Staphylococcus aureus 1 0.11 0.10 0.11 0.11 Pseudomonas sp. 1 0.00 0.00 0.10 0.10 Pseudomonas sp. 1 0.01 0.00 0.10 0.10 1 out of 5 2 only considering experiments for which the species was present on day 7 874
875
42 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
876 Table 3. Taxonomic classification of ONT MinION reads using WIMP of a rain sample, a 877 tomato plant exposed to rain, and a tomato plant not exposed to rain. 878 tomato exposed tomato not Taxon1 rain to rain exposed to rain Massilia putida 2,461 165 0 Massilia sp. WG5 2,794 119 0 Deinococcus gobiensis 0 67 1 Deinococcus actinosclerus 0 56 2 Roseateles depolymerans 33 55 0 Pantoea agglomerans 659 45 1 Methylobacterium sp. PR1016A 37 32 0 Acidovorax sp. KKS102 17 32 0 Pseudomonas oryzihabitans 25 25 2 Variovorax paradoxus 98 22 0 Phycomyces blakesleeanus 15 22 29 Mitsuaria sp. 7 50 19 1 Pantoea vagans 18 18 1 Methylobacterium phyllosphaerae 75 18 1 Methylobacterium aquaticum 42 17 0 Microbacterium testaceum 0 16 0 Deinococcus soli Cha et al. 2016 0 15 0 Rubrivivax gelatinosus 47 15 0 Massilia sp. B2 826 14 1 Rhizobacter gummiphilus 53 13 0 Microbacterium sp. BH-3-3-3 12 12 1 Methylobacterium extorquens 1,102 11 2 Pantoea sp. PSNIH1 0 10 1 Massilia sp. NR 4-1 550 9 1 Janthinobacterium sp. 1_2014MBL_MicDiv 384 9 0 Janthinobacterium sp. LM6 350 9 1 Ralstonia solanacearum 150 9 0 Janthinobacterium agaricidamnosum 338 8 0 Sphingomonas taxi 627 7 0 Janthinobacterium svalbardensis 265 6 0 Modestobacter marinus 162 5 3 Herbaspirillum frisingense 199 4 0 Pseudomonas syringae 165 4 0 Pseudomonas fluorescens 10,173 3 0 Geodermatophilus obscurus 163 3 0
43 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
Pseudomonas protegens 906 2 1 Pseudomonas putida 289 2 1 879 1Only species with at least two reads in either the tomato plant exposed to rain or the tomato 880 plant not exposed to rain are listed ranked from high to low by the number of reads in the tomato 881 plant exposed to rain. Species with a higher number of reads in the tomato plant exposed to rain 882 are in bold. 883
884
885 FIGURE LEGENDS
886
887 Figure 1. Bacterial population size in the phyllosphere of tomato plants A) grown exposed to rain
888 in plastic pots at the Virginia Tech Kentland Farm compared to plants grown inside the laboratory
889 B) grown on the roof of the Latham Hall research building exposed to rain compared to plants
890 grown under laboratory conditions, and C) grown inside the laboratory seven days after being
891 either treated with rain or autoclaved rain. T-test, P < 0.001.
892
893 Figure 2. Relative abundance (RA) of bacterial taxa in rainfall collected in Blacksburg, VA, on 9
894 different days in 2015, 2016, and 2019. Samples were rarefied to 6,419 sequences. A) RA at the
895 class level (only classes with a RA above 1% are shown), B) RA at the genus level (only generated
896 with RA above 2% are shown). For August 15, results are based on two technical replicates (see
897 also Table 1).
898
899 Figure 3. Alpha diversity measurements for rain compared to treated plants at day-0 vs day-7.
900 Three measures of alpha diversity (observed OTUs, Shannon diversity index, and Simpson
901 diversity index) were used. For rain, only samples used for plant inoculations were included.
902
44 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
903 Figure 4. Principal coordinates analysis (PCoA) derived from weighted UniFrac distances (A),
904 unweighted UniFrac distances (B), and the dissimilarity matrix of Bray-Curtis (C). Only rain
905 samples used for plant inoculation were included. For experiments for which replicates were
906 available, the replicate samples are labeled as “monthyear.1” and “monthyear.2”.
907
908 Figure 5. Relative abundance (RA) of bacterial taxa of plants treated with either 100X-rain,
909 filtered rain, or sterile water, at day-0 and day-7. Experiments are listed by dates from left to
910 right (April ‘15, August ‘15, March ‘16, April ‘16, May ‘16, and July ‘16). A) RA at the phylum
911 level (abundance > 1%), B) . RA at the genus level (abundance > 3%). For experiments for
912 which replicates were available relative abundance is based on all replicates.
913
914 Figure 6: Differential abundance analysis at the level of Operational Taxonomic Unit (OTU) using
915 DESeq2 (Love et al., 2014). The fold change is shown on the X axis and genera are listed on the
916 Y axis. Each colored dot represents a separate OTU. A) Comparison of phyllosphere microbiota
917 of plants treated with 100X-rain between day-0 and day-7, B) Comparison between rain microbiota
918 and phyllosphere microbiota 7 days after treatment with the respective 100X-rain sample.
919
920 Figure 7. Relative abundance of a representative selection of rain-borne genera that either failed
921 or succeeded in colonizing the tomato phyllosphere. Dates of experiments are listed on the X axis
922 of panels G and H. Relative abundance is shown on the Y axis for rain, tomato plants on day-0 and
923 day-7 after being treated with 100X-rain (Rain), filtered rain, or sterile water (see panel B for
924 figure legend). A) Pantoea, B) Flavobacterium, C) Janthinobacterium, D) Pseudomonas, E)
925 Massilia, F) Methylobacterium, G) Acidiphilium, and H) Bacillus.
45 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
926
927 Figure 8. Taxonomic composition and Alpha diversity of phyllosphere microbiota of tomato
928 plants grown hydroponically or in soil (both in a commercial greenhouse) and of tomato plants
929 grown outside (on the roof of the Latham Hall research building). A) Relative abundance at the
930 phylum level (only phyla with a RA above 1% are shown), B) Alpha diversity (observed OTUs,
931 Shannon diversity index, and Simpson diversity index).
932
933 Figure 9. Differential abundance analysis at the level of Operational Taxonomic Unit (OTU)
934 using DESeq2 (Love et al., 2014). The fold change is shown on the X axis and genera are listed
935 on the Y axis. Each colored dot represents a separate OTU. A) Plants grown hydroponically in a
936 greenhouse compared with plants grown on the roof of the Latham Hall research building, B)
937 Plants grown in soil in a greenhouse compared with plants grown on the roof of the Latham Hall
938 research building.
939
940 Supplementary Figures
941
942 Supplementary Figure 1. Rarefaction curves of rain microbiota and tomato phyllosphere
943 microbiota treated with 100X-rain, filtered rain, or sterile water on day-0 and day-7.
944
945 Supplementary Figure 2. The core rain microbiome. Rain-associated OTUs at a detection
946 threshold of 0.1% and 100% as a prevalence threshold.
947
46 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
948 Supplementary Figure 3. Differential abundance analysis at the OTU level usingDESeq2 (Love
949 et al., 2014). A) Comparison of rain microbiota with the tomato phyllosphere treated with sterile
950 water at day-0 during the same experiment, B) Comparison of rain microbiota with the tomato
951 phyllosphere microbiota on the day there were treated with 100X-rain (day-0).
952
47 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
A Colony count using standard error B Colony count using standard error 6 6 6 6 *
* 4 4 4 4 Population_Size Population_Size
2 2 2 2 Bacterial population size Bacterial population size
0 0 0 0
Kentland Laboratory Roof Laboratory Kentland Farm Plants Laboratory Roof building Plants Laboratory
C Colony count using standard error 3 3
*
2 2 Population_Size
1 1 Bacterial population size
0 0
Rain sterile Rain inoculation Treatment Sterile-rain inoculation
Figure 1. Bacterial population size in the phyllosphere of tomato plants A) grown exposed to rain in plastic pots at the Virginia Tech Kentland Farm compared to plants grown inside the laboratory B) grown on the roof of the Latham Hall research building exposed to rain compared to plants grown under laboratory conditions, and C) grown inside the laboratory seven days after being either treated with rain or autoclaved rain. T-test, P < 0.001. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Class Composition 100% A Class Composition Class100% Composition 100% A Class Composition 100%
75% 75% Class ClassD_2__Acidimicrobiia 75% 75% D_2__AcidobacteriiaD_2__AcidimicrobiiaAcidimicrobiia ClassD_2__Actinobacteria ClassD_2__AcidobacteriiaAcidobacteria D_2__AlphaproteobacteriaActinobacteriaD_2__Acidimicrobiia D_2__BacilliD_2__ActinobacteriaD_2__AcidobacteriiaAcidimicrobiia AlphaproteobacteriaD_2__Acidimicrobiia D_2__BacteroidiaD_2__AlphaproteobacteriaD_2__ActinobacteriaD_2__AcidobacteriiaAcidobacteria D_2__BlastocatelliaD_2__BacilliBacilliD_2__AlphaproteobacteriaActinobacteria (Subgroup 4) 50% D_2__BacilliD_2__Actinobacteria D_2__ChlamydiaeD_2__BacteroidiaBacteroidiaD_2__AlphaproteobacteriaAlphaproteobacteria D_2__ClostridiaD_2__BlastocatelliaBlastocatelliaD_2__Bacteroidia(Subgroup (Subgroup 4) 4) 50% D_2__BlastocatelliaD_2__BacilliBacilli (Subgroup 4) 50% D_2__DeinococciChlamydiae D_2__DeltaproteobacteriaD_2__ChlamydiaeD_2__BacteroidiaBacteroidia D_2__ClostridiaClostridiaBlastocatellia (Subgroup 4) 50% D_2__GammaproteobacteriaD_2__Blastocatellia (Subgroup 4) D_2__GemmatimonadetesD_2__DeinococciDeinococciD_2__ChlamydiaeChlamydiae D_2__ThermoleophiliaD_2__Deltaproteobacteria D_2__DeltaproteobacteriaDeltaproteobacteriaD_2__GammaproteobacteriaD_2__ClostridiaClostridia D_2__VerrucomicrobiaeD_2__GammaproteobacteriaGammaproteobacteriaD_2__GemmatimonadetesD_2__DeinococciDeinococci 25% D_2__GemmatimonadetesGemmatimonadetesD_2__ThermoleophiliaD_2__DeltaproteobacteriaDeltaproteobacteria Relative Abundance (Class > 1%) Relative Abundance D_2__ThermoleophiliaThermoleophiliaD_2__VerrucomicrobiaeD_2__GammaproteobacteriaGammaproteobacteria 25% D_2__VerrucomicrobiaeVerrucomicrobiaeD_2__GemmatimonadetesGemmatimonadetes Relative Abundance (Class > 1%) Relative Abundance D_2__ThermoleophiliaThermoleophilia 25% D_2__VerrucomicrobiaeVerrucomicrobiae Relative Abundance (Class > 1%) Relative Abundance 25% Relative Abundance (Class > 1%) Relative Abundance 0% Apr15Apr Aug15Aug Mar16Mar Apr16Apr May16May Jul16Jul Oct16Oct Dec16Dec Jun19Jun 0%2015 2015 2016 2016 2016 2016 2016 2016 2019
GenusGenus Composition CompositionApr15 Aug15 Mar16 Apr16 May16 Jul16Jul16 Oct16 Dec16 Jun19 Apr15 Apr16 Oct16 Jun19 Mar16 Aug15 Dec16 Rain collectionMay16 100%100% Rain collection event
GenusGenus Composition Composition Rain Colection Jul16 Apr15 Apr16 Oct16 Jun19 Mar16 Aug15 Dec16 Rain collectionMay16 100%100% Rain Colection B0% B0%Apr15GenusAug15 Mar16CompositionApr16 May16 Jul16 Oct16 Dec16 Jun19 B 100%Apr15GenusAug15 Mar16CompositionRainApr16 ColectionMay16 Jul16 Oct16 Dec16 Jun19 100% Rain Colection
75%75% 75%75% GenusGenus GenusGenus D_5__11741174D_5__1174-901−901-12−−12901−12 D_5__MethylobacteriumD_5__MethylobacteriumMethylobacterium 75% D_5__11741174D_5__1174-901−901-12−−12901−12 D_5__MethylobacteriumD_5__MethylobacteriumMethylobacterium 75% GenusD_5__AcidiphiliumAcidiphiliumD_5__Acidiphilium D_5__MethylocellaD_5__MethylocellaMethylocella GenusD_5__AcidiphiliumD_5__Acidiphilium D_5__MethylocellaD_5__Methylocella D_5__BacillusD_5__1174BacillusAcidiphiliumD_5__Bacillus−901−12 D_5__MethylobacteriumD_5__NakamurellaD_5__NakamurellaNakamurellaMethylocella D_5__AcidiphiliumD_5__BacillusD_5__1174D_5__Bacillus−901−12 D_5__MethylocellaD_5__MethylobacteriumD_5__NakamurellaD_5__Nakamurella D_5__BlastococcusBacillusD_5__Blastococcus D_5__NoviherbaspirillumD_5__NoviherbaspirillumNakamurella BlastococcusD_5__Acidiphilium D_5__MethylocellaNoviherbaspirillum D_5__BacillusD_5__BlastococcusBlastococcusD_5__Blastococcus D_5__NakamurellaD_5__NoviherbaspirillumD_5__NoviherbaspirillumNoviherbaspirillum D_5__BrevibacteriumD_5__BlastococcusD_5__BacillusD_5__Brevibacterium D_5__NoviherbaspirillumD_5__NakamurellaD_5__PantoeaD_5__Pantoea BrevibacteriumD_5__Brevibacterium D_5__PantoeaPantoea D_5__BlastococcusD_5__Brevibacterium D_5__NoviherbaspirillumD_5__PantoeaPantoea D_5__BrevundimonasD_5__BrevibacteriumBrevibacteriumD_5__Brevundimonas D_5__PantoeaD_5__ProteusD_5__ProteusProteus BrevundimonasD_5__BrevundimonasD_5__BrevibacteriumD_5__Brevundimonas D_5__PantoeaD_5__ProteusD_5__Proteus D_5__BryocellaD_5__BrevundimonasBrevundimonas D_5__ProteusD_5__PseudomonasProteus BryocellaD_5__BrevundimonasD_5__Bryocella D_5__Proteus D_5__PseudomonasPseudomonas D_5__BryocellaD_5__BryocellaBryocellaD_5__Bryocella D_5__PseudomonasD_5__PseudomonasD_5__PseudomonasPseudomonas 50% D_5__BuchneraD_5__BryocellaD_5__Buchnera D_5__PseudomonasD_5__RhodovastumD_5__Rhodovastum 50% 50% D_5__BuchneraBuchneraD_5__BuchneraD_5__Buchnera D_5__RhodovastumD_5__RhodovastumRhodovastumD_5__Rhodovastum 50%50% 50% D_5__BuchneraBuchnera D_5__RhodovastumRhodovastum D_5__CaedibacterD_5__Caedibacter D_5__SaccharibacillusD_5__SaccharibacillusSaccharibacillusD_5__Saccharibacillus CaedibacterD_5__CaedibacterCaedibacterD_5__Caedibacter D_5__SaccharibacillusD_5__SaccharibacillusSaccharibacillusD_5__Saccharibacillus D_5__CandidatusD_5__Candidatus Hamiltonella Hamiltonella HamiltonellaD_5__SphingomonasD_5__SphingomonasD_5__Sphingomonas CandidatusD_5__CandidatusD_5__Candidatus Hamiltonella Hamiltonella Hamiltonella HamiltonellaD_5__SphingomonasD_5__SphingomonasSphingomonasD_5__Sphingomonas D_5__FlavobacteriumCandidatus HamiltonellaD_5__Spirosoma Sphingomonas D_5__FlavobacteriumD_5__FlavobacteriumD_5__Flavobacterium D_5__SpirosomaD_5__SpirosomaD_5__Spirosoma D_5__GemmatirosaFlavobacteriumD_5__FlavobacteriumD_5__Flavobacterium D_5__TumebacillusD_5__SpirosomaSpirosomaD_5__Spirosoma D_5__GemmatirosaFlavobacterium D_5__TumebacillusSpirosoma D_5__GemmatirosaD_5__Gemmatirosa D_5__TumebacillusD_5__Tumebacillus D_5__GranulicellaGemmatirosaD_5__GemmatirosaD_5__GranulicellaGemmatirosaD_5__Gemmatirosa D_5__VitiosangiumD_5__VitiosangiumD_5__TumebacillusTumebacillusD_5__TumebacillusTumebacillus D_5__Hymenobacter D_5__uncultured D_5__GranulicellaGranulicellaD_5__GranulicellaD_5__HymenobacterGranulicellaD_5__GranulicellaD_5__Granulicella D_5__unculturedD_5__VitiosangiumD_5__VitiosangiumD_5__VitiosangiumD_5__VitiosangiumVitiosangium D_5__LimnobacterD_5__Limnobacter D_5__unculturedD_5__uncultured bacterium bacterium D_5__HymenobacterD_5__HymenobacterD_5__HymenobacterD_5__Hymenobacter D_5__unculturedD_5__unculturedD_5__unculturedD_5__uncultured D_5__MassiliaHymenobacterD_5__MassiliaHymenobacter Uncultured 25% 25% D_5__LimnobacterLimnobacterD_5__LimnobacterLimnobacterD_5__LimnobacterD_5__Limnobacter D_5__unculturedD_5__unculturedUnculturedD_5__unculturedUnculturedD_5__uncultured bacterium bacteriumbacterium D_5__MassiliaD_5__Massilia Relative Abundance (Genus) > 2%) (Genus) Relative Abundance Relative Abundance (Genus) > 2%) (Genus) Relative Abundance MassiliaMassiliaD_5__MassiliaD_5__Massilia 25%25%25%25% Relative Abundance (Genus) > 2%) (Genus) Relative Abundance Relative Abundance (Genus) > 2%) (Genus) Relative Abundance Relative Abundance (Genus) > 2%) (Genus) Relative Abundance Relative Abundance (Genus) > 2%) (Genus) Relative Abundance
0% 0% Apr Aug Mar Apr May Jul Oct16Oct Dec16Dec Jun19Jun Apr15 Apr15Aug15Aug15Mar16Mar16Apr16Apr16May16May16Jul16Jul16Oct16 Dec16 Jun19 2015 2015 2016 2016 2016 2016 2016 2016 2019 Jul16 Apr15 Apr16 Oct16 Jun19 Mar16 Aug15 Dec16 May16 Jul16 Apr15 Apr16 Oct16 Jun19 Mar16 Aug15 Dec16 Rain collectionMay16 RainRain collection Colection 0% RainRain collection Colection event 0%0% 0% Jul16 Jul16 Apr15 Apr16 Oct16 Jun19 Mar16 Apr15 Apr16 Oct16 Aug15 Jun19 FigureDec16 2 May16 Mar16 Aug15 Dec16 Figure 2. Relative abundance (RA) ofMay16 bacterial taxa in rainfall collected in Blacksburg, VA, on 9 different Jul16 Jul16 Apr15 Apr16 Oct16 Jun19 Mar16 Apr15 Apr16 Oct16 Aug15 Jun19 FigureDec16 2 May16 Mar16 Aug15 Dec16 RainRain Colection ColectionMay16 days in 2015, 2016, andRainRain2019 Colection .ColectionSamples were rarefied to 6,419 sequences. A) RA at the class level (only classes with a RA above 1% are shown), B) RA at the genus level (only generated with RA above 2% are shown). For August 15, results are based on two technical replicates (see also Table 1). bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
Observed Shannon Simpson
1.0
6
0.9
1500
5
0.8
4
1000 0.7 Alpha Diversity
3
0.6
500
2 0.5 d0 d7 d7 d0 d7 d0 d7 d0 d7 d0 d7 d0 rain rain rain - - - rain - - - rain - - - - rain - - - - - Rain Rain Rain - - - W.d0 W.d7 W.d0 W.d7 W.d0 W.d7 d7 d7 FR.d0 FR.d7 FR.d0 FR.d7 FR.d0 FR.d7 d7 CR.d0 CR.d7 CR.d0 CR.d7 CR.d0 CR.d7 d0 d0 d0 Atm.Rain Atm.Rain Atm.Rain Filtered Filtered Filtered Filtered Filtered Filtered rain rain rain rain rain rain Sterile Sterile Sterile Sterile Sterile Sterile 100X 100X 100X 100X 100X 100X water water water water water water
Figure 3. Alpha diversity measurements for rain compared to treated plants at day-0 vs day-7. Three measures of alpha diversity (observed OTUs, Shannon diversity index, and Simpson diversity index) were used. For rain, only samples used for plant inoculations were included. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. PCoA: Weighted Unifrac
A Jul 2016
Mar 2016.2
0.02
Jul 2016 TREATMENT Mar 2016.1 System Mar 2016.1 Aug 2015.1 RainAtm.Rain Mar 2016.2 Aug 2015.2 100XCR.d0-rain-d0 Jul 2016 100XCR.d7-rain-d7 Filtered Rain-d0 Apr 2016 FR.d0 0.01 Mar 2016.1 FilteredFR.d7 Rain-d7 Mar 2016.2 SterileW.d0 water-d0 Mar 2016.1 Mar 2016.2 SterileW.d7 water-d7
ExperimentEXPERIMENT Jul 2016 AprVTP049 2015 Axis.2 [14.9%] Apr 2015 Mar 2016.2 AugVTP050 2015 Apr 2015 0.00 Mar 2016.2 Jul 2016 MarVTP061 2016 Apr 2016 Apr 2016 Apr 2016 VTP062 Apr 2016.2 MayVTP063 2016 May 2016.1 Apr 2016 May 2016.2 Apr 2016.1 VTP064Jul 2016 May 2016.1 Mar 2016.1 May 2016.2 Jul 2016 May 2016.1 Aug 2015 May 2016.1 Aug 2015 May 2016.2 May 2016.1 May 2016.2 Aug 2015 Mar 2016 Apr 2015 Apr 2016.1 Mar 2016.1 Apr 2015 May 2016.2 −0.01 Aug 2015 Apr 2016 Apr 2015 May 2016.2 May 2016 May 2016.1 Jul 2016 0.00 0.03 0.09 0.06 0.03 − − − Axis.1 [56.5%]
B PCoA: Unweighted Unifrac Mar 2016.2 Mar 2016.1 Mar 2016.2
Mar 2016.1 Mar 2016.2 20% Jul 2016 May 2016.2 Mar 2016.1
May 2016.1 May 2016.2 Jul 2016 May 2016.1 Apr 2016.1 Apr 2016.2 SystemTREATMENT Jul 2016 May 2016.2 Apr 2015 RainAtm.Rain May 2016.1 Apr 2016 Apr 2016 100XCR.d0-rain-d0 100XCR.d7-rain-d7 Mar 2016.1 FilteredFR.d0 Rain-d0 May 2016.1 May 2016.1 Mar 2016.2 FilteredFR.d7 Rain-d7 0% May 2016.2 May 2016.2 SterileW.d0 water-d0 Jul 2016 Mar 2016.2 May 2016.1 Mar 2016.1 SterileW.d7 water-d7 Aug 2015 Jul 2016 Apr 2015 Mar 2016.1 ExperimentEXPERIMENT Apr 2015 Mar 2016.2 Jul 2016 May 2016.2 AprVTP049 2015 Axis.2 [6.1%] Apr 2016 Apr 2016 AugVTP050 2015 Apr 2015 VTP061 Mar 2016 Mar 2016 AprVTP062 2016 Aug 2015 MayVTP063 2016 −20% VTP064Jul 2016 Apr 2016 May 2016 Apr 2016 Aug 2015 Apr 2015 Jul 2016 Aug 2015
Aug 2015.1 Aug 2015.2 −0.2 0.0 0.2 Axis.1 [7.4%]
C PCoA: Bray−Curtis
Mar 2016.1 Mar 2016.2 Mar 2016.2 Mar 2016.1 Mar 2016.1 Jul 2016 Mar 2016.2
20% Jul 2016 May 2016.1 Apr 2016.1 May 2016.2 Apr 2016.2 Jul 2016 May 2016.2 TREATMENTSystem RainAtm.Rain May 2016.1 100X-rain-d0 May 2016.2 CR.d0 Aug 2015 100XCR.d7-rain-d7 Apr 2015 May 2016 Apr 2016 FilteredFR.d0 Rain-d0 Apr 2016 Aug 2015 May 2016.1 Mar 2016 FilteredFR.d7 Rain-d7 Apr 2016 Mar 2016.1 Apr 2015 Jul 2016 0% Mar 2016.2 SterileW.d0 water-d0 Aug 2015.1 Aug 2015.2 SterileW.d7 water-d7 Jul 2016 Jul 2016 May 2016.1 ExperimentEXPERIMENT Mar 2016.2 Jul 2016 Apr 2015 Axis.2 [10.4%] VTP049 Mar 2016.1 AugVTP050 2015 May 2016.1 MarVTP061 2016 May 2016.2 −20% Apr 2015 AprVTP062 2016 Aug 2015 Mar 2016.2 MayVTP063 2016 May 2016.2 Apr 2015 Aug 2015 JulVTP064 2016 May 2016.1 Mar 2016.1 May 2016.2 Apr 2015
Apr 2016
Apr 2016 −40%
Apr 2016 −0.4 −0.2 0.0 0.2 Axis.1 [17.3%]
Figure 4. Principal coordinates analysis (PCoA) derived from weighted UniFrac distances (A), unweighted UniFrac distances (B), and the dissimilarity matrix of Bray-Curtis (C). Only rain samples used for plant inoculation were included. For experiments for which replicates were available, the replicate samples are labeled as “monthyear.1” and “monthyear.2”. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. PhylumPhylum Composition Composition 100% 100%PhylumPhylumPhylum Composition Composition Composition 100%A 100%100% Phylum Composition 100%
75% 75% 75% 75% 75% 75% Phylum Phylum
D_1__AcidobacteriaPhylum D_1__AcidobacteriaPhylum D_1__Actinobacteria D_1__ActinobacteriaD_1__AcidobacteriaD_1__ActinobacteriaD_1__Acidobacteria D_1__BacteroidetesD_1__Bacteroidetes D_1__ActinobacteriaD_1__ChloroflexiD_1__Actinobacteria D_1__ChloroflexiD_1__BacteroidetesD_1__ChloroflexiD_1__Bacteroidetes 50% 50% 50% D_1__FirmicutesD_1__Firmicutes D_1__ChloroflexiD_1__GemmatimonadetesD_1__Chloroflexi 50% 50% 50% D_1__GemmatimonadetesD_1__FirmicutesD_1__PatescibacteriaD_1__GemmatimonadetesD_1__Firmicutes D_1__Gemmatimonadetes D_1__PatescibacteriaD_1__GemmatimonadetesD_1__PlanctomycetesD_1__PatescibacteriaD_1__Gemmatimonadetes D_1__PlanctomycetesD_1__ProteobacteriaD_1__PlanctomycetesD_1__Patescibacteria D_1__PatescibacteriaD_1__PlanctomycetesD_1__Patescibacteria D_1__ProteobacteriaD_1__PlanctomycetesD_1__VerrucomicrobiaD_1__ProteobacteriaD_1__Planctomycetes D_1__VerrucomicrobiaD_1__VerrucomicrobiaD_1__Proteobacteria D_1__ProteobacteriaD_1__VerrucomicrobiaD_1__Proteobacteria D_1__Verrucomicrobia 25% D_1__Verrucomicrobia 25% 25% 25% 25% 25% > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance
0% 100X.d0 100X.d7 FR.d0 FR.d7 dd.W.d0 dd.W.d7 0%100X-rain 100X-rain Filtered rain Filtered rain Sterile Sterile 0% 0% d0100X.d0 d7100X.d7 d0FR.d0 d7FR.d7 waterdd.W.d0d0 waterdd.W.d7d7 0% 0% Jul16.W.d0 Jul16.W.d7 Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7
Genus CompositionGenus CompositionApr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Genus May16.CR.d0 CompositionMay16.CR.d7 100% Jul16.W.d0 Jul16.W.d7
100% Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 B May16.W.d0 May16.W.d7
Genus CompositionGenus CompositionApr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7
100% Mar16.FR.d0 Mar16.FR.d7 Rain TreatmentAug15.FR.d0 Aug15.FR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Jul16.W.d0 Jul16.W.d7 May16.CR.d0 May16.CR.d7 Genus Composition Jul16.W.d0 Jul16.W.d7 Apr16.W.d0 Apr16.W.d7 Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 100% Jul16.CR.d0 Jul16.CR.d7 100% May16.W.d0 May16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 May16.CR.d0 May16.CR.d7 100% May16.CR.d0 May16.CR.d7 Rain Treatment Jul16.W.d0 Jul16.W.d7 Jul16.W.d0 Jul16.W.d7 Apr16.W.d0 Apr16.W.d7 Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 RainAug15.CR.d7 Treatment May16.CR.d0 May16.CR.d7 Rain Treatment May16.CR.d0 May16.CR.d7 Rain RainTreatment Treatment
Genus Genus Genus GenusD_5__Allorhizobium−Neorhizobium−PararhizobiumAllorhizobiumD_5__Allorhizobium−Rhizobium−NeorhizobiumMethylobacteriumD_5__Methylobacterium−Pararhizobium−Rhizobium D_5__Methylobacterium 75% 75% GenusD_5__Allorhizobium−Neorhizobium−Pararhizobium−Rhizobium D_5__Methylobacterium 75% D_5__Ammoniphilus AmmoniphilusGenusD_5__Ammoniphilus MycobacteriumD_5__Mycobacterium D_5__Mycobacterium 75% 75% D_5__Allorhizobium−NeorhizobiumD_5__Ammoniphilus−PararhizobiumAllorhizobiumD_5__Allorhizobium−Rhizobium−NeorhizobiumMethylobacteriumD_5__Methylobacterium−Pararhizobium−Rhizobium D_5__MycobacteriumD_5__Methylobacterium D_5__Bacillus BacillusD_5__BacillusD_5__Allorhizobium−NeorhizobiumNocardiaD_5__Nocardia−Pararhizobium−Rhizobium D_5__NocardiaD_5__Methylobacterium 75% D_5__Ammoniphilus D_5__BacillusAmmoniphilusD_5__Ammoniphilus MycobacteriumD_5__Mycobacterium D_5__NocardiaD_5__Mycobacterium D_5__Brevundimonas BrevundimonasD_5__BrevundimonasD_5__Ammoniphilus NocardioidesD_5__Nocardioides D_5__NocardioidesD_5__Mycobacterium D_5__Bacillus D_5__BrevundimonasBacillusD_5__Bacillus NocardiaD_5__Nocardia D_5__NocardioidesD_5__Nocardia D_5__Buchnera BuchneraD_5__BuchneraD_5__Bacillus NoviherbaspirillumD_5__Noviherbaspirillum D_5__NoviherbaspirillumD_5__Nocardia D_5__Brevundimonas D_5__BuchneraBrevundimonasD_5__Brevundimonas NocardioidesD_5__Nocardioides D_5__NoviherbaspirillumD_5__Nocardioides D_5__Burkholderia−Caballeronia−ParaburkholderiaBurkholderiaD_5__BurkholderiaD_5__Brevundimonas−CaballeroniaNovosphingobiumD_5__Novosphingobium−Paraburkholderia D_5__NovosphingobiumD_5__Nocardioides D_5__Buchnera D_5__BurkholderiaBuchneraD_5__Buchnera−Caballeronia−NoviherbaspirillumD_5__NoviherbaspirillumParaburkholderia D_5__NovosphingobiumD_5__Noviherbaspirillum D_5__Castellaniella CastellaniellaD_5__CastellaniellaD_5__Buchnera PaenibacillusD_5__Paenibacillus D_5__PaenibacillusD_5__Noviherbaspirillum D_5__Burkholderia−Caballeronia−D_5__CastellaniellaParaburkholderiaBurkholderiaD_5__Burkholderia−CaballeroniaNovosphingobiumD_5__Novosphingobium−Paraburkholderia D_5__PaenibacillusD_5__Novosphingobium D_5__Chryseobacterium ChryseobacteriumD_5__ChryseobacteriumD_5__Burkholderia−CaballeroniaPandoraeaD_5__Pandoraea−Paraburkholderia D_5__PandoraeaD_5__Novosphingobium D_5__Castellaniella D_5__ChryseobacteriumCastellaniellaD_5__Castellaniella PaenibacillusD_5__Paenibacillus D_5__PandoraeaD_5__Paenibacillus D_5__Curtobacterium CurtobacteriumD_5__CurtobacteriumD_5__Castellaniella PantoeaD_5__Pantoea D_5__PantoeaD_5__Paenibacillus 50% 50% D_5__Chryseobacterium D_5__CurtobacteriumChryseobacteriumD_5__Chryseobacterium PandoraeaD_5__Pandoraea D_5__PantoeaD_5__Pandoraea 50% D_5__Delftia DelftiaD_5__DelftiaD_5__ChryseobacteriumPseudomonasD_5__Pseudomonas D_5__PseudomonasD_5__Pandoraea D_5__Curtobacterium D_5__DelftiaCurtobacteriumD_5__Curtobacterium PantoeaD_5__Pantoea D_5__PseudomonasD_5__Pantoea 50% 50% D_5__Duganella DuganellaD_5__DuganellaD_5__Curtobacterium PusillimonasD_5__Pusillimonas D_5__PusillimonasD_5__Pantoea 50% D_5__Delftia D_5__DuganellaDelftiaD_5__Delftia PseudomonasD_5__Pseudomonas D_5__PusillimonasD_5__Pseudomonas D_5__Enterobacter EnterobacterD_5__EnterobacterD_5__Delftia RhodanobacterD_5__Rhodanobacter D_5__RhodanobacterD_5__Pseudomonas D_5__Duganella D_5__EnterobacterDuganellaD_5__Duganella PusillimonasD_5__Pusillimonas D_5__RhodanobacterD_5__Pusillimonas D_5__Escherichia−Shigella EscherichiaD_5__EscherichiaD_5__Duganella-Shigella−Shigella SolimonasD_5__Solimonas D_5__SolimonasD_5__Pusillimonas D_5__Enterobacter D_5__EscherichiaEnterobacterD_5__Enterobacter−Shigella RhodanobacterD_5__Rhodanobacter D_5__SolimonasD_5__Rhodanobacter D_5__Flavobacterium FlavobacteriumD_5__FlavobacteriumD_5__Enterobacter SphingobiumD_5__Sphingobium D_5__SphingobiumD_5__Rhodanobacter D_5__Escherichia−Shigella D_5__FlavobacteriumEscherichiaD_5__Escherichia-Shigella−Shigella SolimonasD_5__Solimonas D_5__SphingobiumD_5__Solimonas D_5__Gordonia GordoniaD_5__GordoniaD_5__Escherichia−ShigellaSphingomonasD_5__Sphingomonas D_5__SphingomonasD_5__Solimonas D_5__Flavobacterium D_5__GordoniaFlavobacteriumD_5__Flavobacterium SphingobiumD_5__Sphingobium D_5__SphingomonasD_5__Sphingobium D_5__Hyphomicrobium HyphomicrobiumD_5__HyphomicrobiumD_5__Flavobacterium StreptomycesD_5__Streptomyces D_5__StreptomycesD_5__Sphingobium D_5__Gordonia D_5__HyphomicrobiumGordoniaD_5__Gordonia SphingomonasD_5__Sphingomonas D_5__StreptomycesD_5__Sphingomonas D_5__Janthinobacterium JanthinobacteriumD_5__JanthinobacteriumD_5__Gordonia TumebacillusD_5__Tumebacillus D_5__TumebacillusD_5__Sphingomonas D_5__Hyphomicrobium D_5__JanthinobacteriumHyphomicrobiumD_5__Hyphomicrobium StreptomycesD_5__Streptomyces D_5__TumebacillusD_5__Streptomyces 25% 25% D_5__Limnobacter LimnobacterD_5__LimnobacterD_5__Hyphomicrobium UnculturedD_5__uncultured bacterium bacterium D_5__unculturedD_5__Streptomyces bacterium Relative Abundance (Genus > 3%) (Genus Relative Abundance Relative Abundance (Genus > 3%) (Genus Relative Abundance 25% D_5__Janthinobacterium D_5__LimnobacterJanthinobacteriumD_5__Janthinobacterium TumebacillusD_5__Tumebacillus D_5__unculturedD_5__Tumebacillus bacterium Relative Abundance (Genus > 3%) (Genus Relative Abundance D_5__Massilia MassiliaD_5__MassiliaD_5__Janthinobacterium D_5__Tumebacillus 25% 25% D_5__Limnobacter D_5__MassiliaLimnobacterD_5__Limnobacter UnculturedD_5__uncultured bacterium bacterium D_5__uncultured bacterium Relative Abundance (Genus > 3%) (Genus Relative Abundance Relative Abundance (Genus > 3%) (Genus Relative Abundance 25% D_5__Limnobacter D_5__uncultured bacterium Relative Abundance (Genus > 3%) (Genus Relative Abundance D_5__Massilia MassiliaD_5__Massilia D_5__Massilia
0% 0% 0% 0% 0%100X.d0 100X.d7 FR.d0 FR.d7 dd.W.d0 dd.W.d7 0% 100X100X.d0-rain 100X100X.d7Rain-rain collectionFilteredFR.d0 rain FilteredFR.d7 rain dd.W.d0Sterile dd.W.d7Sterile Jul16.W.d0 Jul16.W.d7
d0 d7 d0 d7 waterJul16.W.d0 d0 waterJul16.W.d7 d7 Apr16.W.d0 Apr16.W.d7 Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Jul16.W.d0 Jul16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Rain collection Aug15.FR.d0 Aug15.FR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Apr16.W.d0 Apr16.W.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 May16.CR.d0 May16.CR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 May16.CR.d0 May16.CR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Jul16.W.d0 Jul16.W.d7 Aug15.FR.d0 Aug15.FR.d7 Jul16.W.d0 Jul16.W.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 May16.CR.d0 May16.CR.d7 Apr16.W.d0 Apr16.W.d7 Apr16.W.d0 Apr16.W.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Jul16.W.d0 Jul16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7
Rain Treatment Mar16.FR.d0 Mar16.FR.d7 Aug15.FR.d0 Aug15.FR.d7 Apr16.W.d0 Apr16.W.d7
Mar16.CR.d0 Mar16.CR.d7 Rain Treatment May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 May16.CR.d0 May16.CR.d7 Mar16.W.d0 Mar16.W.d7 Jul16.FR.d0 Jul16.FR.d7 May16.CR.d0 May16.CR.d7 Jul16.CR.d0 Jul16.CR.d7 May16.W.d0 May16.W.d7 Apr15.FR.d0 Apr16.FR.d0 Apr15.FR.d7 Apr16.FR.d7 Apr15.CR.d0 Apr16.CR.d0 Apr15.CR.d7 Apr16.CR.d7 Mar16.FR.d0 Mar16.FR.d7 Rain TreatmentAug15.FR.d0 FigureAug15.FR.d7 5 Mar16.CR.d0 Mar16.CR.d7 May16.FR.d0 May16.FR.d7 Aug15.CR.d0 Aug15.CR.d7 Rain TreatmentMay16.CR.d0 RainMay16.CR.d7 Treatment Figure 5. Relative abundance (RA) ofRainbacterial TreatmenttaxaFigureof plants 5 treated with either 100X-rain, filtered rain, or sterile water, at day-0 and day-7. Experiments are listed by dates from left to right (April ‘15, August ‘15, March ‘16, April ‘16, May ‘16, and July ‘16). A) RA at the phylum level (abundance > 1%), B) . RA at the genus level (abundance > 3%). For experiments for which replicates were available relative abundance is based on all replicates. A RainRain vs vstomato Tomato treated treated with with 100X.rain.d7 CR.d7 RainRain vs Tomato vs Tomato treated treated with withCR.d7 CR.d7 BlastocadellaD_5__Blastocatella D_5__BlastocatellaD_5__Blastocatella CandidatusD_5__Candidatus Paracaedibacter Paracaedibacter D_5__CandidatusD_5__Candidatus Paracaedibacter Paracaedibacter D_5__SpirosomaSpirosoma D_5__SpirosomaD_5__Spirosoma D_5__BelnapiaBelnapia D_5__BelnapiaD_5__Belnapia D_5__CaedibacterCaedibacter D_5__CaedibacterD_5__Caedibacter D_5__BlastococcusBlastococcus D_5__BlastococcusD_5__Blastococcus ChthonomonasD_5__Chthonomonas D_5__ChthonomonasD_5__Chthonomonas ModestobacterD_5__Modestobacter D_5__ModestobacterD_5__Modestobacter D_5__RhodopilaRhodopila D_5__RhodopilaD_5__Rhodopila FriedmanniellaD_5__Friedmanniella D_5__FriedmanniellaD_5__Friedmanniella D_5__BacillusBacillus D_5__BacillusD_5__Bacillus Phylum RhodovastumD_5__Rhodovastum Phylum Phylum D_5__RhodovastumD_5__Rhodovastum D_1__Proteobacteria D_5__BryocellaBryocella D_1__ProteobacteriaD_1__Proteobacteria D_5__BryocellaD_5__Bryocella D_1__Actinobacteria D_5__GranulicellaGranulicella D_1__ActinobacteriaD_1__Actinobacteria D_5__GranulicellaD_5__Granulicella D_1__Firmicutes ChthoniobacterD_5__Chthoniobacter D_1__FirmicutesD_1__Firmicutes D_5__ChthoniobacterD_5__Chthoniobacter D_1__Gemmatimonadetes ActinomycetosporaD_5__Actinomycetospora D_1__GemmatimonadetesD_1__Gemmatimonadetes
TAXA TAXA D_5__ActinomycetosporaD_5__Actinomycetospora D_1__Verrucomicrobia MethylocellaD_5__Methylocella TAXA TAXA TAXA TAXA D_1__VerrucomicrobiaD_1__Verrucomicrobia D_5__MethylocellaD_5__Methylocella D_1__Acidobacteria GemmatirosaD_5__Gemmatirosa D_1__AcidobacteriaD_1__Acidobacteria D_5__GemmatirosaD_5__Gemmatirosa D_1__Armatimonadetes UnculturedD_5__uncultured D_1__ArmatimonadetesD_1__Armatimonadetes D_5__unculturedD_5__uncultured D_1__Bacteroidetes D_5__RomboutsiaRomboutsia D_1__BacteroidetesD_1__Bacteroidetes D_5__RomboutsiaD_5__Romboutsia AcidiphiliumD_5__Acidiphilium D_5__AcidiphiliumD_5__Acidiphilium D_5__11741174-901−901-12−12 D_5__1174D_5__1174−901−12 −901−12 UnculturedD_5__uncultured bacterium bacterium D_5__unculturedD_5__uncultured bacterium bacterium MethylobacteriumD_5__Methylobacterium D_5__MethylobacteriumD_5__Methylobacterium D_5__DuganellaDuganella D_5__DuganellaD_5__Duganella StreptomycesD_5__Streptomyces D_5__StreptomycesD_5__Streptomyces PseudomonasD_5__Pseudomonas D_5__PseudomonasD_5__Pseudomonas D_5__PantoeaPantoea bioRxiv preprintD_5__Pantoea doi: https://doi.org/10.1101/2021.04.08.438997D_5__Pantoea ; this version posted April 9, 2021. The copyright holder for this preprint (which D_5__MassiliaMassilia was not certifiedD_5__Massilia byD_5__Massilia peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made D_5__PandoraeaPandoraea D_5__PandoraeaD_5__Pandoraea available under aCC-BY-ND 4.0 International license. −5 0 5 −5 −5 Log2FoldChange0 0 5 5 TomatoTomato treatedLog2FoldChange treated Log2FoldChangewith withCR d0CR vs d0 d7 vs d7 D_5__RB41D_5__RB41 TomatoTomato treated treated with 100X.rain.d0 with CR d0 vs 100X.rain.d7d7 BD_5__MesorhizobiumA D_5__Mesorhizobium D_5__SphingomonasD_5__SphingomonasD_5__RB41RB41 D_5__MesorhizobiumMesorhizobium D_5__BradyrhizobiumD_5__Bradyrhizobium D_5__SphingomonasSphingomonas D_5__MicrobisporaD_5__Microbispora D_5__BradyrhizobiumBradyrhizobium D_5__PseudolabrysD_5__PseudolabrysD_5__MicrobisporaMicrobispora D_5__unculturedD_5__uncultured bacterium bacteriumD_5__PseudolabrysPseudolabrys D_5__JatrophihabitansD_5__JatrophihabitansD_5__unculturedUncultured bacterium bacterium Phylum PhylumPhylum D_5__unculturedD_5__unculturedD_5__JatrophihabitansJatrophihabitans D_1__BacteroidetesPhylumD_1__Bacteroidetes D_5__unculturedUncultured D_5__HerbaspirillumD_5__Herbaspirillum D_1__ProteobacteriaD_1__BacteroidetesD_1__Proteobacteria
TAXA TAXA D_1__Proteobacteria TAXA TAXA D_5__HerbaspirillumHerbaspirillum D_1__ActinobacteriaD_1__Actinobacteria D_5__Curtobacterium D_5__Curtobacterium TAXA D_1__AcidobacteriaD_1__ActinobacteriaD_1__Acidobacteria D_5__CurtobacteriumCurtobacterium D_1__Acidobacteria D_5__JanthinobacteriumD_5__Janthinobacterium D_5__JanthinobacteriumJanthinobacterium D_5__LimnobacterD_5__LimnobacterD_5__LimnobacterLimnobacter D_5__DuganellaD_5__DuganellaD_5__DuganellaDuganella D_5__MassiliaD_5__MassiliaD_5__MassiliaMassilia D_5__EnterobacterD_5__EnterobacterD_5__EnterobacterEnterobacter D_5__PseudomonasPseudomonas D_5__PseudomonasD_5__Pseudomonas D_5__PantoeaPantoea D_5__PantoeaD_5__Pantoea D_5__FlavobacteriumFlavobacterium D_5__Flavobacterium D_5__Flavobacterium 0 10 20 0 0 10 Log2FoldChange10 20 20 Log2FoldChangeLog2FoldChange
B A RainRain vs vstomato TomatoFigure treated treated 6 with with 100X.rain.d7 CR.d7 RainRain vs Tomato vs Tomato treated treated with withCR.d7 CR.d7 BlastocadellaD_5__Blastocatella D_5__BlastocatellaD_5__Blastocatella CandidatusD_5__Candidatus Paracaedibacter Paracaedibacter D_5__CandidatusD_5__Candidatus Paracaedibacter Paracaedibacter D_5__SpirosomaSpirosoma D_5__SpirosomaD_5__Spirosoma D_5__BelnapiaBelnapia D_5__BelnapiaD_5__Belnapia D_5__CaedibacterCaedibacter D_5__CaedibacterD_5__Caedibacter D_5__BlastococcusBlastococcus D_5__BlastococcusD_5__Blastococcus ChthonomonasD_5__Chthonomonas D_5__ChthonomonasD_5__Chthonomonas ModestobacterD_5__Modestobacter D_5__ModestobacterD_5__Modestobacter D_5__RhodopilaRhodopila D_5__RhodopilaD_5__Rhodopila FriedmanniellaD_5__Friedmanniella D_5__FriedmanniellaD_5__Friedmanniella D_5__BacillusBacillus D_5__BacillusD_5__Bacillus Phylum RhodovastumD_5__Rhodovastum Phylum Phylum D_5__RhodovastumD_5__Rhodovastum D_1__Proteobacteria D_5__BryocellaBryocella D_1__ProteobacteriaD_1__Proteobacteria D_5__BryocellaD_5__Bryocella D_1__Actinobacteria D_5__GranulicellaGranulicella D_1__ActinobacteriaD_1__Actinobacteria D_5__GranulicellaD_5__Granulicella D_1__Firmicutes ChthoniobacterD_5__Chthoniobacter D_1__FirmicutesD_1__Firmicutes D_5__ChthoniobacterD_5__Chthoniobacter D_1__Gemmatimonadetes ActinomycetosporaD_5__Actinomycetospora D_1__GemmatimonadetesD_1__Gemmatimonadetes
TAXA TAXA D_5__ActinomycetosporaD_5__Actinomycetospora D_1__Verrucomicrobia MethylocellaD_5__Methylocella TAXA TAXA TAXA TAXA D_1__VerrucomicrobiaD_1__Verrucomicrobia D_5__MethylocellaD_5__Methylocella D_1__Acidobacteria GemmatirosaD_5__Gemmatirosa D_1__AcidobacteriaD_1__Acidobacteria D_5__GemmatirosaD_5__Gemmatirosa D_1__Armatimonadetes UnculturedD_5__uncultured D_1__ArmatimonadetesD_1__Armatimonadetes D_5__unculturedD_5__uncultured D_1__Bacteroidetes D_5__RomboutsiaRomboutsia D_1__BacteroidetesD_1__Bacteroidetes D_5__RomboutsiaD_5__Romboutsia AcidiphiliumD_5__Acidiphilium D_5__AcidiphiliumD_5__Acidiphilium D_5__11741174-901−901-12−12 D_5__1174D_5__1174−901−12 −901−12 UnculturedD_5__uncultured bacterium bacterium D_5__unculturedD_5__uncultured bacterium bacterium MethylobacteriumD_5__Methylobacterium D_5__MethylobacteriumD_5__Methylobacterium D_5__DuganellaDuganella D_5__DuganellaD_5__Duganella StreptomycesD_5__Streptomyces D_5__StreptomycesD_5__Streptomyces PseudomonasD_5__Pseudomonas D_5__PseudomonasD_5__Pseudomonas D_5__PantoeaPantoea D_5__PantoeaD_5__Pantoea D_5__MassiliaMassilia D_5__MassiliaD_5__Massilia D_5__PandoraeaPandoraea D_5__PandoraeaD_5__Pandoraea −5 0 5 −5 −5 Log2FoldChange0 0 5 5 TomatoTomato treatedLog2FoldChange treated Log2FoldChangewith withCR d0CR vs d0 d7 vs d7 D_5__RB41D_5__RB41 Figure 6: Differential abundance analysisTomatoat treatedthe levelwith 100X.rain.d0of Operational vs 100X.rain.d7Taxonomic Unit (OTU) using D_5__Mesorhizobium Tomato treated with CR d0 vs d7 DESeq2 (Love etBD_5__Mesorhizobiumal., 2014). The fold change is shown on the X axis and genera are listed on the Y axis. D_5__SphingomonasD_5__SphingomonasD_5__RB41RB41 Each colored dot representsD_5__MesorhizobiumaMesorhizobiumseparate OTU. A) Comparison of phyllosphere microbiota of plants D_5__BradyrhizobiumD_5__Bradyrhizobium treated with 100X-rain betweenD_5__SphingomonasSphingomonasday-0 and day-7, B) Comparison between rain microbiota and D_5__MicrobisporaD_5__Microbispora phyllosphere microbiota 7 daysD_5__BradyrhizobiumBradyrhizobiumafter treatment with the respective 100X-rain sample. D_5__PseudolabrysD_5__PseudolabrysD_5__MicrobisporaMicrobispora D_5__unculturedD_5__uncultured bacterium bacteriumD_5__PseudolabrysPseudolabrys D_5__JatrophihabitansD_5__JatrophihabitansD_5__unculturedUncultured bacterium bacterium Phylum PhylumPhylum D_5__unculturedD_5__unculturedD_5__JatrophihabitansJatrophihabitans D_1__BacteroidetesPhylumD_1__Bacteroidetes D_5__unculturedUncultured D_5__HerbaspirillumD_5__Herbaspirillum D_1__ProteobacteriaD_1__BacteroidetesD_1__Proteobacteria
TAXA TAXA D_1__Proteobacteria TAXA TAXA D_5__HerbaspirillumHerbaspirillum D_1__ActinobacteriaD_1__Actinobacteria D_5__Curtobacterium D_5__Curtobacterium TAXA D_1__AcidobacteriaD_1__ActinobacteriaD_1__Acidobacteria D_5__CurtobacteriumCurtobacterium D_1__Acidobacteria D_5__JanthinobacteriumD_5__Janthinobacterium D_5__JanthinobacteriumJanthinobacterium D_5__LimnobacterD_5__LimnobacterD_5__LimnobacterLimnobacter D_5__DuganellaD_5__DuganellaD_5__DuganellaDuganella D_5__MassiliaD_5__MassiliaD_5__MassiliaMassilia D_5__EnterobacterD_5__EnterobacterD_5__EnterobacterEnterobacter D_5__PseudomonasPseudomonas D_5__PseudomonasD_5__Pseudomonas D_5__PantoeaPantoea D_5__PantoeaD_5__Pantoea D_5__FlavobacteriumFlavobacterium D_5__Flavobacterium D_5__Flavobacterium 0 10 20 0 0 10 Log2FoldChange10 20 20 Log2FoldChangeLog2FoldChange Figure 6 30% Acidiphilium bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. A B Pantoea Flavobacterium 50% 20% 30% Rain Rain -d0100X day0 40% Rain -d7100X day7 20% FilteredRain Rainrain d0day0 Rain Rain d0 30% Rain d0 FilteredFilteredRain Rain rain d7 d7day7 Rain d7 Filtered Rain d0 Filtered Rain d0 Sterile waterwaterFiltered Rain d0day0 d7 Filtered Rain d7 Sterile water d0 20% 10% Sterile water d0 Sterile waterwater d7day7 10% Sterile water d7
10%
0% 0% 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 0% C Janthinobacterium0 1 2 D3 4 5 Pseudomonas6 7 20% 90% 80%
70% Rain 60% Rain d0 Rain Rain d0 Rain50% d7 Rain d7 10% Filtered Rain d0 Filtered Rain d0 Filtered40% Rain d7 Filtered Rain d7 Sterile water d0 Sterile water d0 30% Sterile water d7 Sterile water d7 20% 10%
0% 0% 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7
Massilia F 30% Methylobacterium E 50%
40%
Rain 20% Rain 30% Rain d0 Rain d0 Rain d7 Rain d7 Filtered Rain d0 Filtered Rain d0 Filtered Rain d7 Filtered Rain d7 20% Sterile water d0 Sterile water d0 Sterile water10% d7
10%
0% 0 1 2 3 4 5 6 7 0% 0 1 2 3 4 5 6 7
G H Bacillus 30% Acidiphilium 30%
20% Rain 20% Rain Rain d0 Rain d0 Rain d7 Rain d7 Filtered Rain d0 Filtered Rain d0 Filtered Rain d7 Filtered Rain d7 Sterile water d0 Sterile water d0 Sterile water d7 10% Sterile water10% d7
0% 0% 0 1 2 3 4 5 6 7 0 Apr151 Aug152 Mar163 Apr164 May165 Jul166 7 Apr15 Aug15 Mar16 Apr16 May16 Jul16
Figure 7. Relative abundance of a representative selection of rain-borne genera that either failed or succeeded in colonizing the tomato phyllosphere. Dates of experiments are listed on the X axis of panels G and H. Relative abundance is shown on the Y axis for rain, tomato plants on day-0 and day-7 after being treated with 100X-rain, filtered rain, or sterile water (see panel B for figure legend). A) Pantoea, B) Flavobacterium, C) Janthinobacterium, D) Pseudomonas, E) Massilia, F) Methylobacterium, G) Acidiphilium, and H) Bacillus. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. PhylumPhylum Composition Composition 100%100% A Phylum Composition 100%
PhylumPhylum Phylum 75% 75% 75% D_1__AcidobacteriaD_1__AcidobacteriaD_1__Acidobacteria D_1__ActinobacteriaD_1__ActinobacteriaD_1__Actinobacteria D_1__ArmatimonadetesD_1__ArmatimonadetesD_1__Armatimonadetes D_1__BRC1D_1__BRC1D_1__BRC1 D_1__BacteroidetesD_1__BacteroidetesD_1__Bacteroidetes D_1__Chlamydiae D_1__ChlamydiaeD_1__Chlamydiae D_1__Chloroflexi D_1__ChloroflexiD_1__DeinococcusD_1__Chloroflexi−Thermus 50% D_1__DeinococcusD_1__FBPD_1__Deinococcus−Thermus−Thermus 50% 50% D_1__FBPD_1__FCPU426D_1__FBP D_1__FCPU426D_1__FirmicutesD_1__FCPU426 D_1__FirmicutesD_1__FusobacteriaD_1__Firmicutes D_1__Gemmatimonadetes D_1__FusobacteriaD_1__Fusobacteria D_1__Nitrospirae D_1__GemmatimonadetesD_1__Gemmatimonadetes D_1__Patescibacteria D_1__NitrospiraeD_1__PlanctomycetesD_1__Nitrospirae 25% D_1__PatescibacteriaD_1__ProteobacteriaD_1__Patescibacteria
Relative Abundance (Phylum > 1%) (Phylum Relative Abundance D_1__PlanctomycetesD_1__VerrucomicrobiaD_1__Planctomycetes 25% 25% D_1__ProteobacteriaD_1__Proteobacteria Relative Abundance (Phylum > 1%) (Phylum Relative Abundance Relative Abundance (Phylum > 1%) (Phylum Relative Abundance D_1__VerrucomicrobiaD_1__Verrucomicrobia
0% Exposed Hydroponic system Soil (organic system) to rain RSF3.S.1 RSF3.S.2 RSF3.S.3 RSF3.S.4 RSF4.S.1 RSF4.S.2 RSF4.S.3 RSF4.S.4 RSF3.H.1 RSF3.H.2 RSF3.H.3 RSF4.H.1 RSF4.H.2 RSF4.H.3 RSF4.H.4 Kom.Roof RSF1.S.T1 RSF2.S.T1 RSF2.S.T2 RSF2.S.T3 RSF1.H.T1 RSF1.H.T2 RSF1.H.T3 RSF2.H.T1 RSF2.H.T2 RSF2.H.T3 0% 0% RSF5.SK.1 RSF5.SK.2 RSF5.SK.3 RSF1.H.B1 RSF1.H.B2 RSF1.H.B3 RSF5.HK.1 RSF5.HK.2 RSF5.HK.3 RSF6.HK.1 RSF6.HK.2 RSF6.HK.3 RSF6.HK.4 RSF5.HQ.1 RSF5.HQ.2 RSF5.HQ.3 RSF6.HQ.1 RSF6.HQ.2 RSF6.HQ.3 RioG.Roof.1 RioG.Roof.2 RSF2.SK.T1 RSF2.SK.T2 RSF2.SK.T3 TR.7.15.AREC TR.7.25.AREC TR.6.17.Latham TR.6.21.Latham B Sample RSF3.S.1 RSF3.S.2 RSF3.S.3 RSF3.S.4 RSF4.S.1 RSF4.S.2 RSF4.S.3 RSF4.S.4 RSF3.S.1 RSF3.S.2 RSF3.S.3 RSF3.S.4 RSF4.S.1 RSF4.S.2 RSF4.S.3 RSF4.S.4 RSF3.H.1 RSF3.H.2 RSF3.H.3 RSF4.H.1 RSF4.H.2 RSF4.H.3 RSF4.H.4 RSF3.H.1 RSF3.H.2 RSF3.H.3 RSF4.H.1 RSF4.H.2 RSF4.H.3 RSF4.H.4 Kom.Roof Kom.Roof RSF1.S.T1 RSF2.S.T1 RSF2.S.T2 RSF2.S.T3 Observed RSF1.S.T1 ShannonRSF2.S.T1 RSF2.S.T2 RSF2.S.T3 Simpson RSF1.H.T1 RSF1.H.T2 RSF1.H.T3 RSF2.H.T1 RSF2.H.T2 RSF2.H.T3 RSF5.SK.1 RSF5.SK.2 RSF5.SK.3 RSF1.H.T1 RSF1.H.T2 RSF1.H.T3 RSF2.H.T1 RSF2.H.T2 RSF2.H.T3 RSF5.SK.1 RSF5.SK.2 RSF5.SK.3 RSF1.H.B1 RSF1.H.B2 RSF1.H.B3 RSF5.HK.1 RSF5.HK.2 RSF5.HK.3 RSF6.HK.1 RSF6.HK.2 RSF6.HK.3 RSF6.HK.4 RSF1.H.B1 RSF1.H.B2 RSF1.H.B3 RSF5.HK.1 RSF5.HK.2 RSF5.HK.3 RSF6.HK.1 RSF6.HK.2 RSF6.HK.3 RSF6.HK.4 RSF5.HQ.1 RSF5.HQ.2 RSF5.HQ.3 RSF6.HQ.1 RSF6.HQ.2 RSF6.HQ.3 RSF5.HQ.1 RSF5.HQ.2 RSF5.HQ.3 RSF6.HQ.1 RSF6.HQ.2 RSF6.HQ.3 RioG.Roof.1 RioG.Roof.2 RioG.Roof.1 RioG.Roof.2 RSF2.SK.T1 RSF2.SK.T2 RSF2.SK.T3 RSF2.SK.T1 RSF2.SK.T2 RSF2.SK.T3 TR.7.15.AREC TR.7.25.AREC 1.0 TR.7.15.AREC TR.7.25.AREC TR.6.17.Latham TR.6.21.Latham TR.6.17.Latham TR.6.21.Latham 1000 Sample6 Sample
0.8
750
4
0.6
500 Alpha Diversity
0.4 2 250
0.2 Exposed Exposed Exposed Hydroponic Soil to rain Hydroponic Soil to rain Hydroponic Soil to rain Organic Organic Organic Out.Rain Out.Rain Out.Rain Hydroponic Hydroponic Hydroponic
Figure 8. Taxonomic composition and Alpha diversity of phyllosphere microbiota of tomato plants grown hydroponically or in soil (both in a commercial greenhouse) and of tomato plants grown outside (on the roof of the Latham Hall research building). A) Relative abundance at the phylum level (only phyla with a RA above 1% are shown), B) Alpha diversity (observed OTUs, Shannon diversity index, and Simpson diversity index). bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. A Tomato DEseqplantsDEseq grownHydroponic Hydroponic hydroponically vs Outside_Rain vs Outside_Rain vs plants grown outside A D_5__AlcanivoraxD_5__AlcanivoraxAlcanivorax D_5__CandidatusD_5__CandidatusCandidatus Hamiltonella Hamiltonella Hamiltonella D_5__AnoxybacillusD_5__AnoxybacillusAnoxybacillus D_5__SnodgrassellaD_5__SnodgrassellaSnodgrassella D_5__unculturedUnculturedD_5__uncultured bacterium bacterium bacterium D_5__ParacoccusD_5__ParacoccusParacoccus D_5__EndobacterD_5__EndobacterEndobacter D_5__GranulicellaD_5__GranulicellaGranulicella D_5__RubritepidaD_5__RubritepidaRubritepida D_5__ThermoactinomycesD_5__ThermoactinomycesThermoactinomyces D_5__BacillusD_5__BacillusBacillus D_5__ChthoniobacterD_5__ChthoniobacterChthoniobacter D_5__RoseomonasD_5__RoseomonasRoseomonas Phylum Phylum D_5__TuricibacterD_5__TuricibacterTuricibacter D_1__FirmicutesD_1__Firmicutes D_5__CutibacteriumD_5__CutibacteriumCutibacterium D_1__ProteobacteriaD_1__Proteobacteria D_5__ArthrobacterD_5__ArthrobacterArthrobacter D_1__ActinobacteriaD_1__Actinobacteria D_5__KnoelliaD_5__KnoelliaKnoellia D_1__GemmatimonadetesD_1__Gemmatimonadetes Genus Genus Genus Genus D_5__PseudarthrobacterD_5__PseudarthrobacterPseudarthrobacter D_1__VerrucomicrobiaD_1__Verrucomicrobia D_5__StaphylococcusD_5__StaphylococcusStaphylococcus D_1__AcidobacteriaD_1__Acidobacteria D_5__GeodermatophilusD_5__GeodermatophilusGeodermatophilus D_1__ChloroflexiD_1__Chloroflexi D_5__DelftiaD_5__DelftiaDelftia D_5__PandoraeaD_5__PandoraeaPandoraea D_5__CurtobacteriumD_5__CurtobacteriumCurtobacterium D_5__MassiliaD_5__MassiliaMassilia D_5__GemmatirosaD_5__GemmatirosaGemmatirosa D_5__KineococcusD_5__KineococcusKineococcus D_5__MethylobacteriumD_5__MethylobacteriumMethylobacterium D_5__SphingomonasD_5__SphingomonasSphingomonas D_5__BuchneraD_5__BuchneraBuchnera D_5__AlloiococcusD_5__AlloiococcusAlloiococcus D_5__PseudomonasD_5__PseudomonasPseudomonas D_5__StreptococcusD_5__StreptococcusStreptococcus −20 −20 −10 −10 0 0 10 10 20 20 30 30 Log2FoldChangeLog2FoldChange
B TomatoDEseqDEseq plants Organic Organic grown vs Outside_Rain vsin soilOutside_Rainvs plants grown outside D_5__HalomonasD_5__HalomonasHalomonas D_5__CandidatusD_5__CandidatusCandidatus Hamiltonella Hamiltonella Hamiltonella B D_5__NovibacillusD_5__NovibacillusNovibacillus D_5__ThermoactinomycesD_5__ThermoactinomycesThermoactinomyces D_5__BifidobacteriumD_5__BifidobacteriumBifidobacterium D_5__LeucobacterD_5__LeucobacterLeucobacter D_5__PlanifilumD_5__PlanifilumPlanifilum D_5__unculturedD_5__unculturedUncultured bacterium bacterium bacterium D_5__ActinomaduraD_5__ActinomaduraActinomadura D_5__PaenochrobactrumD_5__PaenochrobactrumPaenochrobacterum D_5__OceanobacillusD_5__OceanobacillusOceanobacillus D_5__LongisporaD_5__LongisporaLongispora D_5__UreibacillusD_5__UreibacillusUreibacillus D_5__PlanomicrobiumD_5__PlanomicrobiumPlanomicrobium D_5__CutibacteriumD_5__CutibacteriumCutibacterium D_5__ThermobifidaD_5__ThermobifidaThermobifida D_5__AnoxybacillusD_5__AnoxybacillusAnoxybacillus D_5__JanibacterD_5__JanibacterJanibacter D_5__ArthrobacterD_5__ArthrobacterArthrobacter D_5__AneurinibacillusD_5__AneurinibacillusAneurinibacillus D_5__SaccharopolysporaD_5__SaccharopolysporaSaccharopolyspora D_5__RhodococcusD_5__RhodococcusRhodococcus D_5__TerribacillusD_5__TerribacillusTerribacillus Phylum Phylum D_5__PaenarthrobacterD_5__PaenarthrobacterPaenarthrobacter D_5__DomibacillusD_5__DomibacillusDomibacillus D_1__ProteobacteriaD_1__Proteobacteria D_5__GracilibacillusD_5__GracilibacillusGracilibacillus D_1__FirmicutesD_1__Firmicutes D_5__unculturedD_5__unculturedUncultured compost compost compost bacterium bacterium bacterium D_5__NocardiopsisD_5__Nocardiopsis D_1__ActinobacteriaD_1__Actinobacteria Genus Genus
Genus Genus Nocardiopsis D_5__ParacoccusD_5__ParacoccusParacoccus D_5__VariovoraxD_5__VariovoraxVariovorax D_1__ChloroflexiD_1__Chloroflexi D_5__PlanococcusD_5__PlanococcusPlanococcus D_5__StaphylococcusD_5__StaphylococcusStaphylococcus D_5__PseudogracilibacillusD_5__PseudogracilibacillusPseudogracilibacillus UnculturedD_5__unculturedD_5__uncultured bacterium D_5__RoseomonasD_5__RoseomonasRoseomonas D_5__GlutamicibacterD_5__GlutamicibacterGlutamicibacter D_5__BacillusD_5__BacillusBacillus D_5__BrachybacteriumD_5__BrachybacteriumBrachybacterium D_5__BrevibacteriumD_5__BrevibacteriumBrevibacterium D_5__EnterobacterD_5__EnterobacterEnterobacter D_5__BrevundimonasD_5__BrevundimonasBrevundimonas D_5__PantoeaD_5__PantoeaPantoea D_5__PelomonasD_5__PelomonasPelomonas D_5__KineococcusD_5__KineococcusKineococcus D_5__MethylobacteriumD_5__MethylobacteriumMethylobacterium D_5__MassiliaD_5__MassiliaMassilia D_5__AureimonasD_5__AureimonasAureimonas D_5__BuchneraD_5__BuchneraBuchnera D_5__AlloiococcusD_5__AlloiococcusAlloiococcus D_5__PseudomonasD_5__PseudomonasPseudomonas D_5__StreptococcusD_5__StreptococcusStreptococcus D_5__SphingomonasD_5__SphingomonasSphingomonas −20 −20 −10 −10 0 0 10 10 20 20 30 30 Log2FoldChangeLog2FoldChange Figure 9. Differential abundance analysis at the level of Operational Taxonomic Unit (OTU) using DESeq2 (Love et al., 2014). The fold change is shownFigureon 9 the X axis and genera are listed on the Y axis. Each colored dot represents a separate OTU. A) Plants grown hydroponically in a greenhouse compared with plants grown on the roof of the Latham Hall research building, B) Plants grown in soil in a greenhouse compared with plants grown on the roof of the Latham Hall research building. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
Rarefaction Curves Rain−Tomato Rarefaction Curves Rain−Tomato
3000 3000
SystemSystem RainAtm.Rain Concent.Rain.d0CR.d0 2000 2000 Concent.Rain.d7CR.d7 Filtered.Rain.d0FR.d0 Filtered.Rain.d7FR.d7 Sterile.Water.d0W.d0 Observed OTU Observed OTU Sterile.Water.d0W.d7
1000 1000
0 0 0 25000 50000 75000 100000 0 25000 Sequences50000 per sample 75000 100000 Sequences per sample
Supplementary Figure 1. Rarefaction curves of rain microbiota and tomato phyllosphere microbiota treated with 100X-rain, filtered rain, or sterile water on day-0 and day-7. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license.
CoreRain core microbiome
D_4__Sphingomonadaceae_;D_5__Sphingomonas_;FPLS01046173.19.1488Sphingomonas, FPLS01046173.19.1488
D_4__Sphingomonadaceae_;D_5__Sphingomonas_;ATTI01000001.185818.187289Sphingomonas, ATTI01000001.185818.187289
D_4__Pseudomonadaceae_;D_5__Pseudomonas_;KJ161326.1.1708Pseudomonas, KJ161326.1.1708
D_4__Pseudomonadaceae_;D_5__Pseudomonas_;FJ375389.1.1657Pseudomonas, FJ375389.1.1657
D_4__Pseudomonadaceae_;D_5__Pseudomonas_;ALXA01000013.88221.89768Pseudomonas, ALXA0100013.88221.89768
D_4__Enterobacteriaceae_;D_5__Pantoea_;KF906837.1.1529Pantoea, KF906837.1.1529
D_4__Burkholderiaceae_;D_5__uncultured_;DQ787673.1.1527Burkholderiaceae, uncultured, DQ787673.1.1527 Prevalence 1.0 D_4__Burkholderiaceae_;D_5__Massilia_;JF970594.1.1526Massilia, JF970594.1.1526 0.9 0.8 0.7 D_4__Burkholderiaceae_;D_5__Massilia_;FLTE01001368.534.2052 0.6 Massilia, FLTE01001368.534.2052 0.5
Taxa 0.4 0.3 D_4__Burkholderiaceae_;D_5__Massilia_;FJ375388.1.1726Massilia, FJ375388.1.1726 0.2 0.1 0.0 D_4__Beijerinckiaceae_;D_5__Methylobacterium_;New.ReferenceOTU549Methylobacterium, New Reference OTU549
D_4__Beijerinckiaceae_;D_5__Methylobacterium_;JN695907.1.1533Methylobacterium, JN695907.1.1533
D_4__Beijerinckiaceae_;D_5__1174Beijerinckiaceae, 1174−901-901−-12_;New.ReferenceOTU101412, New Reference OTU1014
D_4__Beijerinckiaceae_;D_5__1174Beijerinckiaceae, 1174−901-901−12_;KX508279.1.1446-12, KX508279.1.1446
D_4__Beijerinckiaceae_;D_5__1174Beijerinckiaceae, 1174−901-901−12_;KF037267.1.1456-12, KF037267.1.1456
D_4__Acidobacteriaceae (Subgroup 1)_;D_5__Bryocella_;EU861913.1.1468Bryocella, EU861913.1.1468
D_4__Acetobacteraceae_;D_5__Acidiphilium_;KF037545.1.1475Acidiphilium, KF037545.1.1475
0.1 1.0 10.0 DetectionDetection thresholdthreshold (Relative (Relative abundance abundance %) %)
Supplementary Figure 2. The core rain microbiome. Rain-associated OTUs at a detection threshold of 0.1% and 100% as a prevalence threshold. bioRxiv preprint doi: https://doi.org/10.1101/2021.04.08.438997; this version posted April 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. A Rain Rainvs tomato vs treatedTomato with treated sterile water.d0 with W.d0 D_5__TumebacillusTumebacillus D_5__CandidatusCandidatus Protochlamydia Protochlamydia D_5__VitiosangiumVitiosangium D_5__BelnapiaBelnapia D_5__BlastocatellaBlastocatella D_5__CandidatusCandidatus Paracaedibacter Paracaedibacter D_5__CaenimonasCaenimonas RainRain vs Tomato vs Tomato treated treated with withW.d0 W.d0 D_5__CandidatusCandidatus Finniella Finniella D_5__TumebacillusD_5__Tumebacillus D_5__AmnibacteriumAmnibacteriumD_5__CandidatusD_5__Candidatus Protochlamydia Protochlamydia D_5__VitiosangiumD_5__Vitiosangium D_5__BlastococcusBlastococcus D_5__BelnapiaD_5__Belnapia D_5__VariovoraxVariovorax D_5__BlastocatellaD_5__Blastocatella D_5__CaedibacterCaedibacterD_5__CandidatusD_5__Candidatus Paracaedibacter Paracaedibacter D_5__CaenimonasD_5__Caenimonas D_5__ChthonomonasChthonomonasD_5__CandidatusD_5__Candidatus Finniella Finniella D_5__ChthoniobacterChthoniobacterD_5__AmnibacteriumD_5__Amnibacterium D_5__RhodovastumRhodovastum D_5__BlastococcusD_5__Blastococcus D_5__VariovoraxD_5__Variovorax D_5__RhodococcusRhodococcus D_5__CaedibacterD_5__Caedibacter D_5__RhodopilaRhodopilaD_5__ChthonomonasD_5__Chthonomonas D_5__SpirosomaSpirosomaD_5__ChthoniobacterD_5__Chthoniobacter D_5__RhodovastumD_5__Rhodovastum D_5__RomboutsiaRomboutsiaD_5__RhodococcusD_5__Rhodococcus D_5__ClostridiumClostridium sensu sensu stricto stricto 11 D_5__RhodopilaD_5__Rhodopila D_5__RickettsiaRickettsia D_5__SpirosomaD_5__Spirosoma D_5__RomboutsiaD_5__Romboutsia D_5__GemmatirosaGemmatirosaD_5__ClostridiumD_5__Clostridium sensu stricto sensu 1 stricto 1 D_5__RhodopseudomonasRhodopseudomonas D_5__RickettsiaD_5__Rickettsia Phylum D_5__BryocellaBryocella D_5__GemmatirosaD_5__Gemmatirosa Phylum Phylum D_5__ActinomycetosporaD_5__RhodopseudomonasD_5__Rhodopseudomonas Actinomycetospora D_5__BryocellaD_5__Bryocella D_1__Patescibacteria D_5__KineococcusKineococcusD_5__ActinomycetosporaD_5__Actinomycetospora D_1__Patescibacteria D_5__Granulicella D_5__KineococcusD_5__Kineococcus D_1__Patescibacteria Granulicella D_5__GranulicellaD_5__Granulicella D_5__unculturedUncultured actinobacterium actinobacteriumD_5__unculturedD_5__uncultured actinobacterium actinobacterium D_1__ProteobacteriaD_1__ProteobacteriaD_1__Proteobacteria D_5__PseudomonasPseudomonasD_5__PseudomonasD_5__Pseudomonas D_5__Aureimonas D_5__AureimonasD_5__Aureimonas D_1__BacteroidetesD_1__Bacteroidetes AureimonasD_5__FriedmanniellaD_5__Friedmanniella D_1__Bacteroidetes D_5__FriedmanniellaFriedmanniella D_5__RoseomonasD_5__Roseomonas D_1__ActinobacteriaD_1__Actinobacteria D_5__RoseomonasRoseomonasD_5__HymenobacterD_5__Hymenobacter D_5__HymenobacterD_5__CandidatusD_5__Candidatus Udaeobacter Udaeobacter D_1__Actinobacteria HymenobacterD_5__PseudonocardiaD_5__Pseudonocardia D_1__FirmicutesD_1__Firmicutes D_5__CandidatusCandidatus Udaeobacter UdaeobacterD_5__CurtobacteriumD_5__Curtobacterium D_5__PseudonocardiaPseudonocardia D_5__AcidiphiliumD_5__Acidiphilium D_1__VerrucomicrobiaD_1__VerrucomicrobiaD_1__Firmicutes D_5__Curtobacterium D_5__EndobacterD_5__Endobacter CurtobacteriumD_5__GeodermatophilusD_5__Geodermatophilus TAXA TAXA TAXA TAXA D_5__AcidiphiliumAcidiphiliumD_5__ModestobacterD_5__Modestobacter D_1__FBPD_1__FBPD_1__Verrucomicrobia D_5__EndobacterEndobacter D_5__1174−D_5__1174901−12 −901−12 D_5__Geodermatophilus D_5__PantoeaD_5__Pantoea D_1__ChloroflexiD_1__Chloroflexi Geodermatophilus D_5__MethylocellaD_5__Methylocella TAXA TAXA D_1__FBP D_5__ModestobacterModestobacterD_5__SphingomonasD_5__Sphingomonas D_1__ArmatimonadetesD_1__Armatimonadetes D_5__11741174-−901901-−1212 D_5__DuganellaD_5__Duganella D_5__Pantoea D_5__MassiliaD_5__Massilia Pantoea D_5__NocardiaD_5__Nocardia D_1__AcidobacteriaD_1__AcidobacteriaD_1__Chloroflexi D_5__MethylocellaMethylocella D_5__DevosiaD_5__Devosia D_5__SphingomonasSphingomonas D_5__unculturedD_5__uncultured D_1__GemmatimonadetesD_1__GemmatimonadetesD_1__Armatimonadetes D_5__DuganellaD_5__MethylobacteriumD_5__Methylobacterium Duganella D_5__AmmoniphilusD_5__Ammoniphilus D_1__ChlamydiaeD_1__Chlamydiae D_5__MassiliaMassiliaD_5__MicrobacteriumD_5__Microbacterium D_5__NocardiaD_5__ThermosporothrixD_5__Thermosporothrix D_1__Acidobacteria NocardiaD_5__PseudaminobacterD_5__Pseudaminobacter D_5__DevosiaDevosia D_5__StreptomycesD_5__Streptomyces D_5__unculturedUnculturedD_5__NovosphingobiumD_5__Novosphingobium D_1__Gemmatimonadetes D_5__MethylobacteriumMethylobacteriumD_5__NoviherbaspirillumD_5__Noviherbaspirillum D_5__Ammoniphilus D_5__BacillusD_5__Bacillus Ammoniphilus D_5__MicrobisporaD_5__Microbispora D_1__Chlamydiae D_5__MicrobacteriumMicrobacteriumD_5__ActinomaduraD_5__Actinomadura D_5__ThermosporothrixThermosporothrix D_5__PseudolabrysD_5__Pseudolabrys D_5__PandoraeaD_5__Pandoraea D_5__PseudaminobacterPseudaminobacter D_5__LD29D_5__LD29 D_5__StreptomycesStreptomycesD_5__MesorhizobiumD_5__Mesorhizobium D_5__Novosphingobium D_5__PaenibacillusD_5__Paenibacillus Novosphingobium D_5__NocardioidesD_5__Nocardioides D_5__NoviherbaspirillumD_5__BurkholderiaNoviherbaspirillumD_5__Burkholderia−Caballeronia−Caballeronia−Paraburkholderia−Paraburkholderia D_5__AllorhizobiumD_5__Allorhizobium−NeorhizobiumD_5__BacillusBacillus−Neorhizobium−Pararhizobium−Pararhizobium−Rhizobium−Rhizobium D_5__MicrobisporaD_5__BrevundimonasD_5__Brevundimonas MicrobisporaD_5__ChryseobacteriumD_5__Chryseobacterium D_5__ActinomaduraActinomaduraD_5__RhodanobacterD_5__Rhodanobacter D_5__PseudolabrysPseudolabrysD_5__HyphomicrobiumD_5__Hyphomicrobium D_5__PandoraeaPandoraeaD_5__unculturedD_5__uncultured bacterium bacterium D_5__LD29LD29 D_5__MesorhizobiumMesorhizobium −20 −20−10 −10 0 010 1020 20 D_5__PaenibacillusPaenibacillus Log2FoldChangeLog2FoldChange D_5__NocardioidesNocardioides D_5__BurkholderiaBurkholderia−Caballeronia-Paraburkholderia−Paraburkholderia D_5__Allorhizobium−NeorhizobiumPararhizobium−Pararhizobium-Rhizobium−Rhizobium D_5__BrevundimonasBrevundimonas D_5__ChryseobacteriumChryseobacterium D_5__RhodanobacterRhodanobacter D_5__HyphomicrobiumHyphomicrobium D_5__unculturedUncultured bacterium bacterium −20 −10 0 10 20 Log2FoldChange
Rain vs tomato treated with 100X rain.d0 B RainRain vsvs TomatoTomato treatedtreated withwith CR.d0CR.d0 D_5__CandidatusCandidatus Paracaedibacter ParacaedibacterRain vs Tomato treated with CR.d0 D_5__Candidatus Paracaedibacter D_5__Candidatus D_5__BlastocatellaParacaedibacterBlastocatella D_5__Blastocatella D_5__CandidatusD_5__BlastocatellaCandidatus Finniella D_5__Candidatus Finniella D_5__CandidatusD_5__Rhodopila FinniellaRhodopila D_5__Rhodopila D_5__RhodopilaD_5__KineococcusKineococcus D_5__Kineococcus D_5__MethylobacteriumD_5__KineococcusMethylobacterium D_5__MethylobacteriumD_5__Methylobacterium D_5__AcidiphiliumAcidiphilium D_5__AcidiphiliumD_5__Acidiphilium D_5__SphingomonasSphingomonas D_5__SphingomonasD_5__Sphingomonas D_5__11741174−-901901−-1212 D_5__1174D_5__1174−901−−90112−12 D_5__RhodanobacterRhodanobacter D_5__RhodanobacterD_5__Rhodanobacter Phylum Phylum Phylum D_5__NovosphingobiumNovosphingobium D_1__Actinobacteria D_5__NovosphingobiumD_5__Novosphingobium D_1__ActinobacteriaD_1__Actinobacteria D_5__DevosiaDevosia D_1__Firmicutes D_5__DevosiaD_5__Devosia D_1__FirmicutesD_1__Firmicutes TAXA TAXA Bacillus D_1__Proteobacteria TAXA TAXA D_5__Bacillus D_1__Proteobacteria TAXA TAXA D_1__Proteobacteria D_5__BacillusD_5__Bacillus D_1__Acidobacteria D_5__Ellin6055Ellin6055 D_1__AcidobacteriaD_1__Acidobacteria D_5__Ellin6055D_5__Ellin6055 D_5__AmmoniphilusAmmoniphilus D_5__AmmoniphilusD_5__Ammoniphilus D_5__PseudaminobacterPseudaminobacter D_5__PseudaminobacterD_5__Pseudaminobacter D_5__PseudolabrysPseudolabrys D_5__PseudolabrysD_5__Pseudolabrys D_5__StreptomycesStreptomyces D_5__StreptomycesD_5__Streptomyces D_5__MesorhizobiumMesorhizobium D_5__MesorhizobiumD_5__Mesorhizobium D_5__SolimonasD_5__SolimonasSolimonas D_5__Solimonas D_5__NocardiaD_5__NocardiaNocardia D_5__Nocardia D_5__PaenibacillusD_5__PaenibacillusPaenibacillus D_5__Paenibacillus D_5__MicrobisporaD_5__MicrobisporaMicrobispora D_5__Microbispora −5 −5 0 0 5 5 −Log2FoldChange5 Log2FoldChange0 5 Log2FoldChange Supplementary Figure 3. DifferentialSupplementaryabundance analysis Figureat the OTU 3 level usingDESeq2 (Love et al., 2014). A) Comparison of rain microbiota with the tomato phyllosphere treated with sterile water at day-0 during the same experiment, B) Comparison of rain microbiota with the tomato phyllosphere microbiota on the day there were treated with 100X-rain (day-0).