Metagenomic analysis of the dynamical conversion of photosynthetic bacterial communities in different crop fields over different growth periods.

Photosynthetic bacteria are beneficial to plants, but knowledge of photosynthetic bacterial community dynamics in field crops during different growth stages is scarce. The factors controlling the changes in the photosynthetic bacterial community during plant growth require further investigation. In this study, 35 microbial community samples were collected from the seedling, flowering, and mature stages of tomato, cucumber, and soybean plants. 35 microbial community samples were assessed using Illumina sequencing of the photosynthetic reaction center subunit M (pufM) gene. The results revealed significant alpha diversity and community structure differences among the three crops at the different growth stages. Proteobacteria was the dominant bacterial phylum, and Methylobacterium, Roseateles, and Thiorhodococcus were the dominant genera at all growth stages. PCoA revealed clear differences in the structure of the microbial populations isolated from leaf samples collected from different crops at different growth stages. In addition, a dissimilarity test revealed significant differences in the photosynthetic bacterial community among crops and growth stages (P<0.05). The photosynthetic bacterial communities changed during crop growth. OTUs assigned to Methylobacterium were present in varying abundances among different sample types, which we speculated was related to the function of different Methylobacterium species in promoting plant growth development and enhancing plant photosynthetic efficiency. In conclusion, the dynamics observed in this study provide new research ideas for the detailed assessments of the relationship between photosynthetic bacteria and different growth stages of plants.

Introduction

The plant phyllosphere is a complex habitat that provides a suitable environment for various bacteria, yeast, and fungi. The bacteria in the phyllosphere can promote plant growth and protect the plants from pathogens [1]. Bacteria are the most numerous colonizers in the phyllosphere (approximately 107 cells per cm2) [2]. Various bacterial taxa are commonly found in this habitat, and some studies indicated that α- and γ-Proteobacteria and Bacteroidetes are the dominant bacterial colonists of the phyllosphere [1, 3–6]. Photosynthetic bacteria are present in the phyllosphere, where they positively impact plant growth and disease control [7-9]. Indeed, photosynthetic phyllosphere bacteria play important roles in nitrogen and carbon dioxide fixation and desulfurization [9-11]. In addition, these bacteria produce a variety of chemicals that can induce systemic resistance in the plant hosts [9-11]. These bacteria are common microorganisms in nature but are mostly found in marine ecosystems [12, 13], river estuaries [14], freshwater lakes [15], saline lakes [16], and soil crusts [17, 18].

Photosynthetic bacteria conduct photosynthesis through photosynthetic reaction centers containing bacterial chlorophyll [19]. The most common photosynthetic bacteria used in agricultural applications are Rhodopseudomonas palustris, Methylobacterium spp., and Sphingomonas spp. [9, 10, 20, 21]. In a previous study by the authors’ group, R. palustris improved plant growth and development, enhanced plant resistance against biotic and abiotic stresses, and improved soil fertility [10]. Various Methylobacterium isolates can enhance seed germination [22] and inhibit plant pathogens, improving plant health [23]. Sphingomonas spp. are capable of suppressing disease development and inhibiting pathogen growth [24]. Methylobacterium spp., the first reported plant photosynthetic bacteria, we found to have important functions on plant leaf surfaces [25]. The genera Methylobacterium and Sphingomonas are consistently detected in different plant species and on different plant organs [26], especially in the plant phyllosphere, implying their intimate relationship with plants and their significance in plant health. In tomato, R. palustris [27], Methylobacterium spp. [28], and Sphingomonas spp. promote plant growth [29]. The same has been observed in cucumber and soybean [30-32]. Regardless, it is reasonable to believe that many photosynthetic bacteria and their community structure have yet to be discovered.

The photosynthetic reaction center subunit M (pufM) gene located in the puf operon can be used to identify anoxygenic photosynthetic bacteria in environmental samples [13, 33]. Furthermore, compared to 16S rRNA gene sequences, distinct pufM gene region sequences include more phylogenetic diversity and resolve anoxygenic photosynthetic bacteria community composition in the phyllosphere with a better resolution than 16S RNA sequencing or culture [12, 34].

We hypothesized that the photosynthetic bacteria are common in the phyllosphere and that the growth period of crops will affect the composition of the photosynthetic bacteria communities. Therefore, in this study, we selected representative crops from Solanaceae (tomato), Cucurbitaceae (cucumber), and Leguminosae (soybean) to study the distribution of the photosynthetic bacterial communities in different crops and at different growth stages using Illumina sequencing. The results presented in this paper help to identify the dynamic changes in photosynthetic bacterial communities during crop growth and development and increase the application potential of photosynthetic bacteria in agricultural production.

Materials and methods

Experimental design and sample collection

A total of 35 samples were collected from leaves of three crops at different growth stages for subsequent microbe isolation and high throughput sequencing process. The experiment was conducted from May to August 2018 at the experimental farm of the Hunan Academy of Agricultural Sciences, Changsha, Hunan Province, China (28.22°N, 113.26°E). Tomato cv. Zuan-hong-meili (XinShu Seed Co., Ltd., Beijing, China), cucumber cv. Shuyan 10 (XinShu Seed Co., Ltd., Beijing, China), and soybean cv. Su-qing III (Nanjing Ideal Seedings Co., Ltd., Nanjing, China) were selected for the study. First, a large piece was randomly picked from the experimental farm. Then it was divided into nine small blocks. The size of each block was approximately 40–50 m2, and the nutrients were consistent (the organic matter content of soil was 1.92%, total nitrogen 0.078%, whole phosphorus 0.023%, whole potassium 2.32%, quick acting phosphorus 1.4 mg/kg and fast acting potassium 93 mg/kg). Then, 300 plants were planted in each block of cucumber, tomato, and soybean separately. Each crop was planted in three randomly selected blocks on May 15, 2018, and sampled at the seedling (June 15, 2018), flowering (July 15, 2018), and mature (August 25, 2018) growth stages. At each growth stage, fully expanded leaves were collected from six randomly selected plants per crop per block. The leaves collected from a specific block were pooled to produce three biological replicates per crop at a specific growth stage. Each collected leaf sample was approximately 10 g and stored at 4°C until further use. Phyllosphere microorganisms were collected from each leaf sample as previously described [35], with specific modifications. Briefly, each collected leaf sample was placed inside a 500-mL sterile conical flask containing 200 mL of 0.1 M phosphate-buffered saline (PBS). The flask was shaken at 150 rpm for 10 min at 28°C and sonicated for 20 min using an Ultrasonic Cleaning Machine (Ningbo Scientz Biotechnology Co., Ltd., Ningbo, China). The solution was transferred into four 50-mL centrifuge tubes and centrifuged for 10 min at 12,000 rpm. The resulting phyllosphere microorganism pellets were collected and stored at -80°C until DNA extraction.

DNA extraction and purification

The DNA of the phyllosphere microorganisms was extracted using the MP FastDNA® SPIN Kit for Soil (MP Biochemicals, Solon, OH, USA). The PufM gene forward primer PufMF (5’-TAC GGS AAC CTG TWC TAC-3’) and reverse primer PufM-WAW (5’-AYN GCR AAC CAC CAN GCC CA-3’) were constructed according to earlier reports [12, 36]. Each primer was added with a unique 6-nt barcode. The DNA isolated from the individual samples was used for PCR amplification under the following conditions: initial denaturation at 94°C for 5 min, followed by 35 cycles of 94°C for 30 s, 60°C for 30 s, and 72°C for 30 s. The final extension step was 10 min at 72°C. Each PCR reaction was 50 μL in volume. The quality of the PCR products was checked using 2% agarose gel by electrophoresis. The correctly sized PCR products were purified using a Novogene Gel Extraction Kit (Novogene Bioinformatics Technology Co., Ltd., Beijing, China). Equal amounts of purified PCR products representing the three crops at three different growth stages were mixed and sequenced by Novogene Bioinformatics Technology Co. Ltd. (Beijing, China) on an Illumina HiSeq X Ten (2 × 250 bp paired-end reads), according to the literature [12, 19, 37].

Processing and analysis of sequence data

Paired-end reads were assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence. The paired-end reads were combined using the FLASH software [38]. Quality filtering of the raw tags was performed under specific filtering conditions to obtain high-quality clean tags [39] according to the QIIME 1.7.0 software [40] quality control process. The UPARSE software [41] was used to cluster all the effective tags to generate an operational taxonomic unit (OTU) table based on 97% sequence similarity. The photosynthetic bacteria database constructed by Novogene Bioinformatics Technology Co., Ltd. (Beijing, China) was used to annotate the tags at different taxonomic levels. The data were normalized based on the sample with 68,550 sequences to generate an OTU table. Alpha and beta diversity analyses were performed using the normalized data.

Statistical analysis

Statistical differences in alpha diversity indices (i.e., the Shannon index, the inverse (Inv-) Simpson index, observed richness, Chao’s estimated richness (chao1), and the relative abundance of the different taxonomic groups) were calculated using QIIME (version 1.7.0). The alpha diversity indices were analyzed using one-way analysis of variance (ANOVA) followed by Duncan’s multiple range test (P<0.05) in SPSS 21.0 (IBM, Armonk, NY, USA). The tests for microbial community composition dissimilarity between pairs of groups were performed using nonparametric multi-response permutation procedures (MRPPs), analysis of similarities (ANOSIM), and nonparametric permutational multivariate ANOVA with the adonis function (Adonis) [42, 43] in R (version 2.15.3). Principal coordinate analysis (PCoA) was performed in R (version 2.15.3). A t-test was performed to identify OTUs with significant variation between groups (P<0.05) using R. Annotation of Prokaryotic Taxa (FAPROTAX) was used to predict the ecological functions of photosynthetic bacterial communities [44, 45].

Results

The alpha diversity of the photosynthetic bacterial communities changes with the growth stage

In this study, a total of 3,150,689 quality-filtered reads representing the photosynthetic bacterial communities in different crops were obtained through high-throughput sequencing. These sequences represented 35 leaf samples collected from three different crops at three different growth stages (quality filtering is shown in S1 Table). One sample (cucumber seedling sample) had to be removed due to the low quality of the sequences. Following the initial analysis, 6725 OTUs were found to share a 97% sequence similarity. According to the rarefaction curves, most obtained samples reached a sufficient sequencing depth (Fig 1A).

Fig 1

(A) Rarefaction curves of the reaction center protein M chain (pufM) gene fragment amplicons. Photosynthetic bacteria were isolated from tomato, cucumber, and soybean plants at different growth stages. The isolated photosynthetic bacterial samples were combined and sequenced with the Illumina HiSeq X Ten platform. (B-E) Alpha diversity of the three crops at three different growth stages. The alpha diversity indices include (B) the observed species, (C) Chao1, (D) Shannon index, and (E) Inv-Simpson index of photosynthetic bacterial communities. The data were analyzed using a one-way ANOVA followed by Duncan’s multiple range test at P<0.05. a,b,c Groups with different superscript letters are significantly different. aP = 0.001; bP = 0.008; cP = 0.049. n = 4. Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage. Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage. Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

The alpha diversity indices are shown in Fig 1B–1E and Table 1, including observed species, chao1, Shannon, and Inv-Simpson. The greater the alpha diversity index, the higher the diversity of the photosynthetic bacteria in the samples. For the alpha diversity indices of the tomato phyllosphere photosynthetic bacteria, all alpha diversity indices increased after the seedling stage and then decreased following the flowering stage. The highest diversity of phyllosphere photosynthetic bacteria was observed in the flowering period. For the alpha diversity indices of the cucumber phyllosphere photosynthetic bacteria, the Shannon index decreased from the seedling stage until the mature stage, while the Inv-Simpson index, the observed richness, and Chao1 increased in the seedling stage and then decreased after the flowering stage, the highest diversity of phyllosphere photosynthetic bacteria was in the flowering period. For the alpha diversity indices of the soybean phyllosphere photosynthetic bacteria, all assessed diversity indices decreased from the seedling stage until the mature stage. The highest diversity of phyllosphere photosynthetic bacteria was in the seedling period.

Table 1

Alpha diversity of three vegetable crops at three different growth stages.

Sample group		Observed species	Shannon	Inv-Simpson	Chao1
Tomato	Ta	956.25±26.75b	5.36±0.19b	0.92±0.01a	1136.96±31.52b
	Tb	1350.25±72.74a	6.25±0.12a	0.95±0a	1501.3±84.28a
	Tc	1170.25±90.22ab	5.16±0.17b	0.88±0.01b	1389.63±106.74ab
Cucumber	Ca	711.33±37.88b	5.06±0.4a	0.89±0.05ab	821.97±56.61b
	Cb	1126.5±70.07a	4.96±0.13a	0.92±0.01a	1277.17±91.16a
	Cc	860.25±28.61b	4±0.09b	0.83±0.01b	983.46±34.7b
Soybean	Sa	1052.75±29.49a	5.24±0.06a	0.94±0a	1190.22±41.69a
	Sb	857.75±37.23b	4.42±0.09b	0.88±0.01b	952.48±51.9b
	Sc	781.75±30.27b	4.28±0.06b	0.85±0c	920.75±47.46b

The alpha diversity indices include the observed species, Chao1, inverse (Inv-) Simpson, and Shannon indices of photosynthetic bacterial communities. The data were analyzed using a one-way ANOVA followed by Duncan’s multiple range test at P<0.05. a,b,c Groups with different superscript letters are significantly different (P<0.05).

Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage. Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage. Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

The photosynthetic bacterial communities are dissimilar among crop species and growth stages

The weighted UniFrac distance was used to calculate the pairwise distances among the phyllosphere photosynthetic bacterial communities on tomato, cucumber, and soybean at different growth stages (seedling, flowering, and maturing stages). The two axes of the PCoA explained 61.76% and 14.07% of the total variation, respectively (Fig 2). The ANOSIM, MRPP, and Adonis test results showed that all variables (i.e., different growth stages of tomato, cucumber, and soybean) examined in this study explained the variation in photosynthetic bacterial community structure among tomato, cucumber, and soybean at different growth stages (Table 2). The MRPP, ANOSIM, and Adonis results also suggested that the differences in the phyllosphere photosynthetic bacterial community among different crop species at different growth stages were significant (P<0.05).

Fig 2

Principal coordinate analysis (PCoA) of photosynthetic bacterial communities.

Each point represents one sample, plotted by a principal component on the X-axis and another on the Y-axis, which is colored by group. The percentage on each axis indicates its contribution to the discrepancy among samples. Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage. Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage. Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

Table 2

Beta diversity of three different vegetable crops at three different growth stages.

Group	MRPP		Anosim		Adonis
	delta	P	R	P	F	P
Ta-Tb	0.3642	0.033	1	0.031	15.97	0.025
Ta-Tc	0.3326	0.033	1	0.023	18.864	0.001
Tb-Tc	0.2493	0.024	1	0.041	13.129	0.025
Ca-Cb	0.3068	0.035	1	0.024	19.417	0.001
Ca-Cc	0.2893	0.034	1	0.022	20.756	0.04
Cb-Cc	0.1472	0.03	1	0.044	71.614	0.033
Sa-Sb	0.1072	0.026	1	0.025	93.007	0.041
Sa-Sc	0.1229	0.032	1	0.037	102.85	0.035
Sb-Sc	0.1078	0.025	1	0.026	86.631	0.001

MRPP, Multi-response permutation procedure analysis; Anosim, Analysis of similarity; Adonis, A method of nonparametric multivariate variance test according to the distance matrix. P<0.05 indicated a statistically significant difference.

Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage. Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage. Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

The photosynthetic bacterial communities were different among crops and growth stages

Proteobacteria were the major photosynthetic bacteria in the phyllosphere. The phylum accounted for 50.21%-96.87% of the sequences obtained from the three crops at the three growth stages (Fig 3A). The abundances of photosynthetic bacterial genera found in this study were Methylobacterium (25.56%-94.07%), Halorhodospira (0.15%-22.31%), Rhodopseudomonas (0.06%-8.85%), Ectothiorhodospira (0.18%-20.51%), Sphingomonas (0.001%-5.26%), Thiorhodococcus (0.22%-5.33%), Rhodobacter (0.09%-3.78%), Rhodocyclus (0%-5.92%), Roseateles (0.05%-2.78%), and Marichromatium (0.03%-1.41%) (Fig 3B).

Fig 3

Relative abundance of photosynthetic bacteria in tomato, cucumber, and soybean.

(A) Phyla. (B) Genera. (C) Species. Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage. Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage. Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

At the species level, photosynthetic bacteria were also found in the phyllosphere and included Methylobacterium extorquens (15.80%-75.99%), Methylobacterium radiotolerans (5.74%-65.94%), Halorhodospira halophila (0.04%-28.50%), Rhodopseudomonas palustris (0.06%-8.85%), Ectoth- iorhodospira shaposhnikovii (0.18%-20.51%), Sphingomonas ursincola (0–8.33%), Thiorhodococcus minor (0.17%-5.21%), Rhodobacter veldkampii (0.05%-3.32%), and Rhodocyclus tenuis (0–5.92%), and Roseateles depolymerans (0.06%-2.78%) (0.02%-3.67%) (Fig 3C). At this level, there were significant differences among crops at three different growth stages.

The photosynthetic bacteria populations change with growth stages in the three crops

The species showing significant differences at the three growth stages are shown in Figs 4–6. The bacterial strains showing a relative abundance of over 1% were selected and analyzed. During tomato growth, M. extorquens and M. radiotolerans increased in the seedling stage and then decreased after the flowering stage. R. depolymerans decreased from the seedling stage until the mature stage. Sphingomonas ursincola and T. minor decreased beginning in the seedling stage and then remained low after that (Table 3).

Fig 4

Photosynthetic bacterial populations showing significant changes among tomato samples collected at different growth stages.

Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage.

Fig 6

Photosynthetic bacterial populations showing significant changes among soybean samples collected at different growth stages.

Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

Table 3

Photosynthetic bacterial populations showing significant changes among tomato samples collected at three different growth stages.

Group	M. extorquens	M. radiotolerans	R. depolymerans	S. ursincola
Ta	0.1763±0.0379b	0.0759±0.0084c	0.0116±0.0017a	0.0526±0.013a
Tb	0.3026±0.0058a	0.2119±0.0095a	0.0036±0.0005b	0.0003±0.0003b
Tc	0.267±0.0129a	0.1646±0.0176b	0.0017±0.0002b	0±0b

The data were analyzed using one-way ANOVA followed by Duncan’s multiple range test (P<0.05). a,b,c Groups with different superscript letters are significantly different (P<0.05).

Ta, tomato seedling stage; Tb, tomato flowering stage; Tc, tomato maturity stage.

Photosynthetic bacterial populations showing significant changes among cucumber samples collected at different growth stages.

During cucumber growth, Ectothiorhodospira shaposhnikovii and M. extorquens increased after the seedling stage and then decreased after the flowering stage. Halorhodospira halophila, Rhodobacter veldkampii, Rhodopseudomonas palustris, and R. depolymerans decreased beginning in the seedling stage and decreased again after the flowering stage. M. radiotolerans increased beginning in the seedling stage and increased again after the flowering stage. S. ursincola decreased beginning in the seedling stage and was maintained at a low level until the maturity stage (Table 4).

Table 4

Photosynthetic bacterial populations showing significant changes among the cucumber samples collected at the three different growth stages.

Group	E. shaposhnikovii	H. halophila	M. extorquens	M. radiotolerans	R. veldkampii	R. palustris	R. depolymerans	S. ursincola
Ca	0.0376±0.015b	0.285±0.0933a	0.1902±0.0257b	0.0925±0.0157c	0.0332±0.0248a	0.0382±0.0276a	0.0278±0.0042a	0.0833±0.0182a
Cb	0.2051±0.0106a	0.0014±0.0002b	0.3369±0.0067a	0.2231±0.0132b	0.0014±0.0002a	0.0021±0.0002a	0.0028±0.0002b	0.0002±0.0001b
Cc	0.0025±0.0004c	0.0004±0.0001b	0.158±0.0076b	0.6594±0.0082a	0.0005±0.0002a	0.0007±0.0002a	0.0006±0.0001b	0.0001±0b

The data were analyzed using one-way ANOVA followed by Duncan’s multiple range test (P<0.05). a,b,c Groups with different superscript letters are significantly different (P<0.05).

Ca, cucumber seedling stage; Cb, cucumber flowering stage; Cc, cucumber maturity stage.

During soybean growth, E. shaposhnikovii decreased beginning in the seedling stage and then increased after the flowering stage until the maturity stage. M. extorquens first increased beginning in the seedling stage and then decreased after the flowering stage. M. radiotolerans increased beginning in the seedling stage and increased again after the flowering stage (Table 5).

Table 5

Photosynthetic bacterial populations showing significant changes among soybean samples collected at three different growth stages.

Group	E. shaposhnikovii	M. extorquens	M. radiotolerans
Sa	0.0166±0.0006a	0.8267±0.0177b	0.0574±0.0032b
Sb	0.0018±0.0001b	0.8718±0.0086a	0.0671±0.0051b
Sc	0.0027±0.0005b	0.7599±0.0128c	0.1783±0.0116a

The data were analyzed using one-way ANOVA followed by Duncan’s multiple range test (P<0.05). a,b,c Groups with different superscript letters are significantly different (P<0.05).

Sa, soybean seedling stage; Sb, soybean flowering stage; Sc, soybean maturity stage.

Predicted photosynthetic bacteria community ecological functions using FAPROTAX

The predicted ecological functions of the phyllosphere photosynthetic bacteria communities were investigated using FAPROTAX (Fig 7). Among the putative functions, a total of 33 putative biogeochemical cycle functions were identified from the phyllosphere photosynthetic bacteria community. The results indicated that the photosynthetic bacteria community contained a high number of sequences assigned to phototrophy (14.4%), photoheterotrophy (14.0%), aerobic anoxygenic phototrophy (11.7%), chemoheterotrophy (11.9%), ureolysis (10.9%), methanol oxidation (10.9%), and methylotrophy (10.9%). In addition, many sequences were predicted to have ecological functions involved in photoautotrophy (3.2%), anoxygenic photoautotrophy (3.2%), anoxygenic photoautotrophy S oxidizing (3%), anoxygenic photoautotrophy H2 oxidizing (1.4%), and aerobic chemoheterotrophy (1%). Other ecological functions, including nitrogen fixation, nitrate reduction, dark iron oxidation, and sulfide oxidation, were also predicted to be present in the phyllosphere photosynthetic bacterial communities in relatively lower abundances (<1%).

Fig 7

Abundance of phyllosphere photosynthetic bacterial function groups predicted with the FAPROTAX tool relative to different groups.

Discussion

Numerous studies investigated the colonization, species, and abundance of plant phyllosphere microorganisms, but most studies focused on the roles of phyllosphere microorganisms in plant growth, development, and disease resistance [46-49]. The results showed that the photosynthetic bacterial community was common in the phyllosphere, and the composition of the photosynthetic bacterial community at the phylum and genus levels were similar among the growth stages of the three crops. In addition, the dissimilarity test revealed a significant difference in photosynthetic bacterial community composition among the crops at different growth stages.

The alpha diversity results revealed that the phyllosphere photosynthetic bacterial communities of cucumber and soybean decreased as the season progressed, while the phyllosphere photosynthetic bacterial community of tomato increased from the seedling stage to the flowering stage and then decreased after the flowering stage. Copeland et al. [37] found that the leaf microbiome had the highest diversity at the beginning of the growing season and then became significantly less diverse as the season progressed. Redford et al. [50] reported that the composition of the phyllosphere bacterial community varied greatly throughout the growing season, and the diversity of early- and late-season communities was greater than that of mid-season communities. The results for the cucumber and soybean phyllosphere photosynthetic bacteria obtained here agreed with those of Copeland et al. [37] but were inconsistent with the results of Redford et al. [50]. Copeland et al. [37] reported that the soil microbiome strongly influenced the leaf microbiome’s diversity in common beans and soybean at the beginning of the growing season. In contrast, Redford et al. [50] reported that diversity was the lowest at the mid-season, probably due to adverse growth conditions (e.g., UV exposure, moisture conditions, resource availability, or leaf cuticle properties) and affecting phyllosphere microbiome colonization. There have been no studies on the phyllosphere microbial changes in cucumber, and the soybean material examined in this study was the same as that examined by Copeland et al. [37]. The photosynthetic bacterial community changes in cucumber and soybean might also be due to soil microorganisms’ influence on the phyllosphere of crop seedlings. In addition, the results for tomatoes were inconsistent with those reported by Copeland et al. [37] and Redford et al. [50], as the highest community diversity of phyllosphere photosynthetic bacteria was observed during tomato flowering. A possible reason for the discrepancy is that the colonization of phyllosphere microorganisms varies among crops. Additional studies examining various crops cultured under the same conditions and analyzed using the same methods within the same study are necessary to compare the phyllosphere diversity among crops.

Indeed, there were significant differences in photosynthetic bacterial community composition among the crops and growth stages in the present study. The results of the PCoA showed clear differences among the three crops and the three growth stages. In addition, the dissimilarity test revealed significant differences in photosynthetic bacterial community composition among the three crops and three growth stages. A previous study reported that bacterial communities were plant species-specific [5]. Redford et al. [50] showed that the phyllosphere bacterial community’s composition was significantly affected by the growing season. In the present study, the colonization of plant leaf surfaces by photosynthetic bacteria might also have been affected by crop species, plant growth, and development. Potential functions of the photosynthetic bacteria community determined by FAPROTAX included phototrophy, photoheterotrophy, aerobic anoxygenic phototrophy, chemoheterotrophy, ureolysis, methanol oxidation, and methylotrophy, which were abundant among all samples. For the three crops, the functional diversity of photosynthetic bacteria at the seedling stage was higher than in other growth periods. Abundant phototrophy in the phyllosphere indicated that many microorganisms can fix carbon and must obtain carbon and energy from the oxidation of organic compounds.

Methylobacterium was the most abundant bacteria in the phyllosphere of tomato, cucumber, and soybean during their respective growing seasons. Methylobacterium has been identified in many crop species [51] and can promote plant growth and development [52]. Knief et al. [53] reported that the distribution of Methylobacterium is not plant-specific, supporting the present study. M. extorquens and M. radiotolerans were found in the photosynthetic bacterial community at different crop growth periods. M. extorquens was reported to promote the germination of seeds and plant growth [25, 54]. M. radiotolerans was shown to be able to degrade 2,2-bis-(p-chlorophenyl)-1,1-dichloroethylene (DDE) and promote plant growth [55]. Thus, these two bacteria might play an important role in the growth and development of the three plants. Sphingomonas differed significantly between the tomato and cucumber growth periods, and the relative abundance at the seedling stage was much higher than in the flowering and mature periods. Sphingomonas have unique abilities to degrade refractory contaminants, serve as bacterial antagonists to phytopathogenic fungi, and secrete valuable exopolysaccharides [56]. This study suggests that Sphingomonas might play a positive role in the tomato and cucumber seedling periods. These observations are also supported by various studies showing that Sphingomonas promote plant growth [57, 58] and protect against pathogens [24].

Several of the photosynthetic bacteria observed in this study have also been reported as having industrial applications. For example, R. depolymerans was originally identified as a degrader of poly-hexamethylene carbonate (PHC), and it was later found to have the ability to use not only PHC but also some other biodegradable plastics [59]. E. shaposhnikovii is a phototrophic sulfur bacterium belonging to the Gram-negative subgroup of purple bacteria [60], and it was shown to be able to remove H2S from wastewater, industrial gases, and biogases [61]. Most of the research on H. halophila focused on the photoactive yellow protein [62, 63], but the interactions of these bacteria with plants have not been studied. The role of these strains in plant growth and disease resistance will be interesting. On the other hand, the effects of different photosynthetic bacterial strains on plant growth and development need to be further investigated.

Conclusion

This study provides ecological insights into the photosynthetic bacterial communities in the tomato, cucumber, and soybean phyllosphere at different growth stages. We have demonstrated that photosynthetic bacterial communities are dynamic and change with different growth stages. Still, the molecular mechanisms controlling the changes in photosynthetic bacterial community composition during different plant growth stages require further investigation.

Quality filtering of the 35 samples.

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Title: Dynamical conversion of photosynthetic bacterial communities in tomato, cucumber, and soybean fields over different growth periods characterized by high-throughput sequencing

Journal: PLOS ONE

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Response: We thank the Journal. The manuscript was revised accordingly.

2. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Response: It was corrected.

3. We note that you are reporting an analysis of a microarray, next-generation sequencing, or deep sequencing data set. PLOS requires that authors comply with field-specific standards for preparation, recording, and deposition of data in repositories appropriate to their field. Please upload these data to a stable, public repository (such as ArrayExpress, Gene Expression Omnibus (GEO), DNA Data Bank of Japan (DDBJ), NCBI GenBank, NCBI Sequence Read Archive, or EMBL Nucleotide Sequence Database (ENA)). In your revised cover letter, please provide the relevant accession numbers that may be used to access these data. For a full list of recommended repositories, see http://journals.plos.org/plosone/s/data-availability#loc-omics or http://journals.plos.org/plosone/s/data-availability#loc-sequencing

Response: We thank the Journal. In this study, all fastq files are available from the NCBI database (bacterial sequences SRA: SRP193589; BioProject: PRJNA533201; BioSample: SAMN11444424-SAMN11444390; URL: https://www.ncbi.nlm.nih.gov/bioproject/533201).

4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

Response: We provided the ORCID numbers.

5. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Response: The reference list was verified.

Reviewer #1

1. Summary: Photosynthetic bacteria are an important component of the phyllosphere, as they play roles in plant health, plant function, and disease suppression. Though there are potential applications for agricultural production, many photosynthetic bacterial communities in the phyllosphere have not been characterized. The authors hypothesize that photosynthetic bacteria are common in the phyllosphere and that the growth period of crops will affect community composition. The results are in support of this hypothesis, as 3,150,689 quality-filtered reads were found in 6725 identified OTUs across 35 pooled samples, alpha diversity changed throughout the growth stages of tomato, cucumber, and soybean, and community dissimilarity was affected by plant growth stage. The reviewer finds the manuscript to be technically sound and that the data supports the authors' conclusions.

2. Figures, tables, and captions: The figures are clear and easy to understand, as are the captions.

Response: We thank the Reviewer for taking the time to review our work and for the comments.

4. There are no issues with the writing that would detract from understanding the work, save for one instance where clarity is needed.

Lines 50 - 51: This sentence could be reworded; it reads like it is missing a phrase. As written, this sentence implies that photosynthetic bacteria have only been in the phyllosphere as of recently. Is the sentence meant to convey that the existence of photosynthetic bacteria in the phyllosphere was recently confirmed?

Line 54: The phrase "trigger inducible" seems redundant. For example, the literature cited uses the phrase "induces systemic resistance" in the title.

Response: We thank the Reviewer. The entire manuscript was proofread, including the two statements mentioned above.

Reviewer #2

The title of the manuscript is not very clear, it should be like “Metagenomic analysis of dynamical conversion of photosynthetic bacterial communities in different crop fields over different growth periods”.

Response: We thank the Reviewer for the comment. The title was revised as suggested.

Page 2, line 33. Please consider to remove “and” from sentence. different 33 crop species and at different growth stages.

Response: It was corrected.

Page 2, line 38. Consider to remove “and” among plant growth and development.

Response: It was corrected.

Page 3, line 49. “proteobacteria” Be consistent with the use of bacterial name in italic and with the use of capital letters. Check throughout the manuscript.

Response: It was corrected. The names were verified.

Page 4, line 82. Add “help to identify” instead of “help reveal”.

Response: It was corrected.

Page 5, line 88 and 89. These two sentences are useless in the start, adjust it in the last before DNA isolation and consider it like “a total of 35 samples were collected from leaves of three crops at different growth stages for subsequent microbe isolation and high throughput sequencing process.

Response: It was corrected as suggested.

Page 5, line 95. The methodology part is lack of crop plantation points, in which base the block were randomly selected? Fertilization/nutrients rate was same in every block? How many seed were cultivated in every block? Was the seed quantity was varied or same per block? After how much time the samples were collected?

Response: We thank the Reviewer for the comment. The experiment was conducted from May to August 2018 at the experimental farm of the Hunan Academy of Agricultural Sciences, Changsha, Hunan Province, China (28.22oN, 113.26oE). Tomato cv. Zuan-hong-meili (XinShu Seed Co., Ltd., Beijing, China), cucumber cv. Shuyan 10 (XinShu Seed Co., Ltd., Beijing, China), and soybean cv. Su-qing III (Nanjing Ideal Seedings Co., Ltd., Nanjing, China) were selected for the study. A large block was randomly picked from the experimental farm. Then it was divided into nine small blocks. The size of each block was approximately 40-50 m2, and the nutrients were consistent. Then, 300 plants were planted in each block of cucumber, tomato, and soybean. Each crop was planted in three randomly selected blocks on May 15, 2018 and sampled at the seedling (June 15, 2018), flowering (July 15, 2018), and mature (August 25, 2018) growth stages. This information was added to the Methods.

Page 5, line 104. This sentence is unclear, please consider to rewrite it.

Response: The sentence was revised.

Page 8, line 151. Consider to mention the quality filtration information of all the 35 samples as a supplementary table.

Response: We thank the Reviewer. We now present the quality filtration process in Supplementary Table S1.

Page 11, line 223-226. Fig 3C doesn’t representing the mentioned bacterium except few one.

Response: We thank the Reviewer. We revised the description.

Page 11, line 227. Explain all the significantly diverse bacterial species among different crop at different growth stages.

Response: We thank the Reviewer. We revised the description.

Page 15, line 269. Table 5, Consider to mentioned all the a, b, c (P-value) along with the tables. Check with every table showing statistical data.

Response: We thank the Reviewer. We verified all tables. Groups with different superscript letters are significantly different (P<0.05).

Page 17, line 294-296. The sentence should be like, the results showed that the photosynthetic bacterial community was common in the phyllosphere and the composition of photosynthetic bacterial community at the phylum and genus levels were similar among the growth stages of the three crops.

Response: We thank the Reviewer. The sentence was revised as suggested.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

28 Dec 2021

Metagenomic analysis of the dynamical conversion of photosynthetic bacterial communities in different crop fields over different growth periods

PONE-D-21-13677R1

Dear Dr. Zhang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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Kind regards,

Suzanne L. Ishaq, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: All previous comments were addressed. However, the additional information provided in the Materials and Methods section does raise additional questions about nutrient application rates and the experimental design.

Materials and methods:

Lines 101-105: More of the experimental design has been added, but the usage of "block" for two different levels is somewhat confusing. Replacing "block" where it appears in Line 101 (referring to the field picked for experimentation) with another term may be helpful.

Line 103: For the sake of experimental replication, the information on nutrient application could be included as supplemental information or be briefly described beyond "The nutrients were consistent."

Lines 103-104: Having this sentence come before the one detailing random assignment of crops to blocks is confusing. It is also not clear that each block is planted in a monoculture. It could help to combine sentences and clarify that each crop was randomly assigned to three replicate blocks and planted in a monoculture of 300 seedlings. Or, a simple diagram could be included.

The manuscript could also benefit from further proofreading and editing for clarity. The following comments are some suggestions along those lines.

Abstract:

Lines 27 - 28: As the sentence is currently written, the apostrophe is no longer needed. Alternatively, the phrase "the knowledge...in field crops" could be replaced with "knowledge of photosynthetic bacterial community dynamics in field crops" to make the first sentence of the abstract more concise.

Line 31: Consider restructuring this sentence to place the growth stages closer to the list of crops being sampled (ex: "...collected from the seedling, flowering, and mature stages of tomato, cucumber, and soybean plants.")

Line 32: Consider replacing "they" with the subject (samples) for clarity

Introduction:

Line 70: Consider moving the verb in this sentence and changing tense. As currently written, the sentence may imply the bacteria no longer have the properties described. (ex: "Methylobacterium spp., the first...bacteria, were found to have..."

Discussion:

In the second sentence, it would help to clarify that these are your results and not results from the aforementioned studies.

Figures:

The color palette may be difficult for people with color deficiencies to view.

Reviewer #2: (No Response)

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Reviewer #1: No

Reviewer #2: No

6 Jul 2022

PONE-D-21-13677R1

Metagenomic analysis of the dynamical conversion of photosynthetic bacterial communities in different crop fields over different growth periods

Dear Dr. Zhang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Suzanne L. Ishaq

Academic Editor

PLOS ONE