Sampling and Selection Factors that Enhance the Diversity of Microbial Collections: Application to Biopesticide Development

Media and storage conditions

Isolates were cultivated on solid and liquid media of four different recipes in this study. 1/3 × King’s Media B medium (KB) consisted of proteose peptone 6.7 g (Bacto, USA) monopotassium phosphate 0.4 g (Sigma Life Sciences Inc., USA), magnesium sulfate heptahydrate (Sigma life science Inc.) and 3.3 ml of glycerol (Junsei chemical Inc., Japan) per liter. 1/10 × tryptic soya medium (TS) was made with 3 g of Tryptic soil broth (Difco, USA) per liter. R2 medium consisted of proteose peptone 0.5 g (Bacto, USA) casamino acids 0.5 g (Difco, USA), yeast extract 0.5 g (Duchefa Inc., The Netherlands), glucose 0.5 g (Junsei Chemical Inc., Japan), soluble starch 0.5 g (Yoneyama Chemical Inc., Japan), dipotassium phosphate 0.3 g (Junsei Chemical Inc., Japan), magnesium sulfate heptahydrate 0.05 g (Duchefa Inc., The Netherlands), sodium pyruvate 0.3 g (Sigma Life Sciences Inc., USA), per liter, with a final pH of 7.2. L medium (LM) included peptone 5 g (Becton Dickinson Inc., USA), magnesium sulfate heptahydrate 0.2 g (Duchefa Inc., The Netherlands), ammonium iron(III) citrate 0.15 g (Daejung Chemical Inc., Korea), calcium chloride 0.05 g (Sigma Life Sciences Inc., USA), anhydrous ferric chloride 0.01 g (Aldrich Chemical Inc., USA), manganese sulfate monohydrate 0.01 g (Sigma life science Inc., USA) per liter. For soild medium, 1.5% agarose (Duchefa Inc., The Netherlands) was added prior to autoclaving. Strains were stored at −80°C on 1/10 TS with 17.5% glycerol added.

Sampling regimes and isolation methods

For the 1^st collection, representing a mixture of 24 samples from 16 different species, approximately 1 g of material was recovered from either the roots or leaves of plants grown on the research farm, arboretum, or landscape of the Chonnam National University campus on Oct 6, 2009. Individual plant samples were classified to genus, and, where possible species. Samples were placed in 10 ml of sterile water and incubated overnight at room temperature. Samples were then vortexed, and, for subcollection 1A plated directly onto 1/10× Tryptic Soya Agar (TSA) or 1/3× King’s Media B Agar (KBA) or inoculated into liquid media of the same composition. For subcollection 1B, the washes were serially diluted 3.5 times × 6 dilutions in distilled water and either plated directly onto TSA or KBA or inoculated into liquid media of the same composition. After 24 hrs, 20 microliters of the liquid cultures were plated from each dilution onto the corresponding solid media. After 2 days of incubation on solid media, individual colonies were picked and stored for further analysis.

For the 2^nd collection, representing the phyllosphere, individual leaves were sampled from the landscape around Agriculture Building IV on the campus of Chonnam National University (Gwangju, Korea) on Oct 10, 2009. Individual samples from different plants that were readily classified to genus. Individual leaves were pressed both onto 1/10 × Tryptic Soya Agar (TSA; top) and 1/3 × King’s Media B Agar (KBA; bottom). They were then dropped into a 50 ml tube containing 15 ml of sterile water, briefly vortexed and left to incubate at room temperature in the dark. After 12 hr and 120 hr, the tubes were vortexed for 60 sec, and 20 microliters of each wash were plated onto TSA or KBA and incubated for 2 days prior to colony picking.

For the 3^rd collection, representing the rhizosphere, soils were collected from around Korea between November 16 and December 14, 2009. With the exception of sample 1 which was from a rice field, all other soils were taken from vinyl houses where various vegetables had been grown and harvested approximately one month prior to sampling. Approximately 3 kg of soil from the top 20 cm was mixed in situ at each location prior to being bagged and shipped to Gwangju. Soils were stored at room temperature in the dark prior to analyses. Soil chemical analyses were conducted by Jeonnam Agricultural Research and Extension Services (Naju, Korea) in December 2009. Tomato (Lycopersicon esculentum) and wheat (Triticum aestivum) were planted in small pots prefilled with 200 ml of each soil and grown in a greenhouse under standard growing conditions. Plants were harvested four and five weeks after planting. Roots were carefully removed and weighed, with 2 g (fresh weight) then being placed in 10 ml of sterile distilled water in 50 ml tubes for washing. These roots were vortexed for 60 sec to dislodge adhering bacteria, and 20 microliters was plated onto 1/3 × KBA, LMA, R2A, and 1/10 × TSA. In all cases, plates were incubated at room temperature for 2 days, following which individual colonies were picked and inoculated into 200 microliters of the same media in 96-well plates. After 24 hrs of incubation, 100 microliters of each culture was mixed into an equal volume of 35% glycerol and stored at −80°C. The remaining culture was frozen at −20°C prior to use as whole cell template for genotyping.

Genotyping isolate using amplified rDNA restriction analyses (ARDRA)

Individual isolates were recovered from glycerol stocks and plated onto the same media. After 2 to 4 days of growth, individual colonies were picked and used as whole cell templates for PCR amplification of the 16S rRNA gene using the eubacterial primers 8F and 1492R as described previously (Benitez and McSpadden Gardener, 2009). Briefly, master mixes contained 1 × PCR buffer 1.7 mM MgCl₂, 0.2 mM dNTP, 2 pmol of each primer, 0.04 mg RNAse A, and 0.06 U GoTaq Flexi. Into 20 microliter aliquots the master mix, individual colonies were added and reactions incubated at 95°C for 5 min. Reactions were cycled 28 times at 94°C for 1 min, 54°C for 1 min, and 70°C for 2 min, with a final extension at 70°C for 8 min Restriction analysis was performed on 6.5 microliters of amplified products from each PCR reaction diluted with sterile water to a total volume of 16.5 microliters. To this, 10 U of MspI was added and products were digested for 2 hr at 37°C. Eight microliters of digested products were loaded onto 1.7% agarose gels in 0.5 × TBE and separated using electrophoresis. DNA bands were stained with ethidium bromide and visualized on a UV light box. Image capture relied on a GelLogic112 system, with images being exported to PowerPoint (Microsoft Inc., USA) for labeling. Sizes of individual bands were estimated using 100 bp ladder that was added to adjoining lanes, and sizing is accurate to ± 20 bp. Genotypes were scored individually by two different people and reconciled by consensus with a third. All primers, 100 bp ladder, agarose, and TBE were purchased from Bioneer Inc. (Korea); restriction enzymes were obtained from Fermantas Inc., (USA); and all other molecular biology supplies were obtained from Promega Company (USA).

High-throughput bioassay for biocontrol activity

One-day protective activities of the fermentation broths were evaluated against the six plant pathogens: Magnaporthe oryzae and Rhizoctonia solani on rice plants, Botrytis cinerea and Phytophthora infestans on tomato plants, Puccinia recondita on wheat plants, and Colletotrichum coccodes on red pepper plants. The in vivo antifungal bioassays were conducted as previously described (Cho et al., 2000; Kim et al., 2001). Briefly, plants were grown in vinyl pots (4.5 cm diameter) for 1 to 4 weeks. The 3-day old fermentation broths of the test isolates were diluted three-fold with distilled water and then Tween-20 was added to a concentration of 250 mg/l. Serenade, a microbial biopesticide produced by Agraquest (Davis, CA), was diluted to the 1X application rate according to the manufacturer’s instructions and then applied as a positive control. Untreated control plants were treated with a Tween-20 solution alone. Plant seedlings were sprayed until run-off with each of the solutions. After 24 hr, the treated plant seedlings were inoculated with spores or mycelial suspensions of one of the six plant pathogens. Disease symptoms were rated from 3 to 7 days after inoculation, depending on the pathogen. The pots were arranged in a randomized complete-block design, with two replicates per treatment. The 24 isolates displaying the greatest biopesticide potential were retested and the four estimates for each treatment converted into a control percentage compared with the control treatments by the equation: % control = 100[(A – B)/A, where A = the area of infection (%) on leaves or sheaths sprayed with a Tween-20 solution alone and B = the area of infection (%) on treated leaves or sheaths.

Induced systemic resistance bioassay

Pepper (Capsicum annuum) seeds were sown in a tray including autoclaved nursery soil. The tray was placed in a greenhouse maintained at 25°C during the daytime. After 10 days, young pepper plants were transplanted into pots (9 cm × 8 cm) which contained autoclaved nursery soil and vermiculite 5:1 (v:v). The bacteria used in these assays were recovered from glycerols and incubated on TSA at room temperature for 48 hr prior to inocula preparation. Pure colonies were of the test isolates were resuspended in sterile water and cell density adjusted to ~3 × 10⁸ CFU/ml based on optical density at 600 nm prior to inoculation (see below). Inocula of Xanthomonas campestris pv. vesicatoria consisted of cells resuspended in 0.85% NaCl + 0.02 % Silwet L-77 (Lehle Seeds, USA). When the plants reached the 3 to 4 leaf stage, 5ml of the selected isolates (~3 × 10⁸ CFU/ml) were drenched onto each root system. Five days later, leaves were spray inoculated with 2 ml of X. campestris pv. vesicatoria (~1 × 10⁸ CFU/ml). The pathogen treated plants were placed in a growth chamber (dark, 25°C, 100% relative humidity) for 24 hr and replaced in greenhouse. Five days later, disease ratings for each of the upper four leaves, excluding newly emerged leaves were made, and the average disease rating per plant used for analysis. Three plants per treatment were evaluated relative to a negative control. Disease reduction was calculated as percent control = 100[(A – B)/A, where A = the disease rating of the negative control and B = the disease rating of the root drenched plants from each treatment.

Statistical analysis

Data were organized and sorted in Excel 2007 (Microsoft, Inc., USA). Statistical tests were performed using Minitab v. 15.1.3 (Minitab Inc., USA). Evaluation of frequency data was performed using the Tally Individual Variables and Chi-squared Goodness of Fit functions where individual sample sizes for each varied depending on the variable tested, with n > 44 for all classes. Evaluation of bioassay data (n = 3 or 4 for all tests) was performed using General Linear Models with comparisons to the controls being performed using Dunnet’s test. The obtained P-values are noted in the text.

General description and genotyping of bacterial collections

In order to determine which sampling variables might provide access to the greatest spectrum of bacterial diversity and novelty, we developed and analyzed three different bacterial strain collections. Collection 1 (mixed collection) consisted of 1032 isolates obtained from 24 plant samples (representing leaves and/or roots of 16 different plant species) grown on liquid or solid states of two different media. This collection was asymmetrically divided to assess the effects of different selection intensities (i.e. the number of colony picks per sample) and reproducibility of different independent samples coming from the same or different plant species. Collection 2 (phyllosphere collection) consisted of a total of 1080 isolates obtained from individual leaves of 12 different plant species, incubated 3 different ways, and plated onto 2 different media. Collection 3 (rhizosphere collection) consisted of a total of 1120 isolates obtained from rhizosphere of 2 different plant species, planted in 10 different soils, and plated onto 4 different media.

The genotypic diversity of each collection was assessed by amplified ribosomal DNA restriction analysis (ARDRA) using MspI and the occurrence of different banding patterns was noted. In this way, we identified 62, 88 and 132 distinct genotypes in Collection 1 (N = 1032 isolates), Collection 2 (N = 691 isolates) and Collection 3 (N = 657 isolates). Across all 3 collections, a total of 237 distinct genotypes were noted, indicating that there was substantial collection to collection variation. Additional genotypes may be present in these collections, as nearly 40% of initial isolates were determined to be mixed cultures, based on the number and collective size of bands revealed by ARDRA. However, most of these colony picks displayed banding patterns consistent with at least one or more previously identified genotypes. Therefore, we made the strategic decision to increase throughput and not further purify those additional colony picks.

Effects of sampling design on the distribution of common and rare genotypes in the different collections

The genotypic structures of the each of the collections were analyzed to assess the overall effect of using different combinations of sampling and selection factors (Table 1). Overall, we observed that collection designs with more independent samples (initial factor) and fewer isolate per sample (last factor in design) were the most diverse. This was shown by the fact that Collections 1B, 2, and 3 yielded 2 to 3 times as many genotypes per 100 isolates. Those same collections also had much more even distribution of genotypes, with the greatest balance occurring in Collections 2 and 3 where the five most common genotypes represented < 50% of the collection.

Table 1

General description of the genotypic diversity observed in different collections of plant-associated bacteriaa

Histograms of the data revealed that all collections were skewed in their distribution of genotypes, though the degree of skew varied by sampling regime, selection intensity, and environment. In mixed collection (Collection 1), the sub-collection defined by a relatively deep selection criteria of n = 90 per sample per media, had just 17 genotypes, with the 5 most commonly recovered genotypes (27, 26, 51, 4 and 52) represented 88% of the isolates (Fig. 1). This was the most skewed collection as just three genotypes (27, 26, and 51). In contrast, a much wider sampling (23 samples, n = 7 per sample per media) was more diverse, with the 5 most commonly recovered ARDRA-defined genotypes (20, 26, 44, 45 and 50) representing only 67% of the isolates (Fig. 1B). Using a sample size of 15 isolates per media per sample gave even more diverse collections (Table 1). In the phyllosphere (Collection 2), 47% of the isolates belonged to just 5 commonly recovered ARDRA-defined genotypes (37, 61, 59, 71 and 50). In the rhizosphere collection (Collection 3), the 5 most common genotypes (75, 60, 77, 124, and 122) accounted for only 38% of the 657 cleanly genotyped isolates. In both cases where n = 15 per sample per media, the single most commonly recovered genotypes (numbered 37 and 70, respectively) constituted just about 15% of each collection. Each collection also had a good number of rare genotypes, defined as those patterns observed to occur just once or twice (i.e. < 0.5% of the total). For comparable sampling and selection regimes, the rhizosphere provided nearly twice as many rare genotypes (45 singlets and 58 doublets) than the phyllosphere (31 singlets and 20 doublets). This was due to the fact that there was relatively little commonality of the genotypes recovered from different samples or media. Overall, these data indicate that relatively balanced multifactor sampling and selection designs can provide substantially more diverse collections than those using more unbalanced designs.

Fig. 1

Distribution of unique genotypes in Collection 1. Genotypes were determined using MspI digestion of amplified ribosomal DNA amplified from each isolate. The y-axis represents the number of times each genotype was observed in Collection 1A (2 samples, n = 90 for each) or 1B (23 samples, n = 7 for each).

Determination of appropriate selection intensity per sample

With Collection 1, we set out to specifically determine an appropriate selection intensity (i.e. number of colony picks per sample) that would lead to an optimal recovery of diverse genotypes with clear capacity to colonize plant tissues. Previous reports have indicated skewed distributions of bacterial counts on both above and below ground plant parts, and it is well established that bacteria aggregate in biofilms of various sizes on plant tissues. We found that the mean number of genotypes per sample (across all tested media) was 2.2, 4.1, 5.7, and 6.3 for n = 7, 14, 21, and 90, respectively. And, the total number of genotypes ranged from 1–6, 2–9, 3–10, and 5–8 per media over the same four sampling intensities, with the only significant difference being the lower number of genotypes for n = 7, as compared to the other sample sizes. These data indicate that an optimal number of distinct isolates is recovered with just 14 and 21 colony picks per sample. Beyond that sampling intensity, the recovery of new genotypes is very rare. Such a selection intensity is further indicated by the observation that there was very little overlap in the genotypes detected between samples on the same media, or between media for the same samples with n = 7. And similar observations were made with n = 15 in Collections 2 and 3 (see below). Nonetheless, the discovery of new genotypes followed a pattern of diminishing returns with increasing the number of samples. Specifically, the average number of genotypes per sample ranged from 1.4 to 2.7 on the different media, but the use of 23 samples only increased the number genotypes recovered by just 7- to 11-fold depending on the media used. From these data, we concluded that a rather shallow selection (e.g. n = 15 colony picks per sample) across a rather wide sample based (e.g. 10 to 12 different samples) provided the lowest degree of redundancy within our collection. These values were then used to develop and further assess the factors affecting the diversity recovered in Collection 2 (phyllosphere) and Collection 3 (rhizosphere).

Factors affecting the recovery of novel genotypes from the phyllosphere.

With Collection 2, we set out to determine whether media, sample incubation condition, or plant species had the greatest effect on the number of novel genotypes recovered from the phyllosphere. While different rare genotypes were recovered on the two media tested, the number of these did not vary significantly (P > 0.5). In contrast, the ex situ factor of incubation condition did have a marginal effect on the recovery of rare genotypes (P = 0.07), with the leaf press tending to provide more novel genotypes than the 12 hr and 120 hr incubations in water. These two additional incubation conditions were intended to model natural processes of extended precipitation and/or leaf deposition in puddles, natural conditions that are expected to lead to the recovery of previously uncultured genotypes. The recovery of rare genotypes from leaves was most strongly influenced by the in situ selection factor of plant species (P = 0.01; Table 2). For every 15 isolates, the number of genotypes isolated per plant species ranged from 1 to 9, averaging from 3.2 to 5.3 per media. Using our tiered sampling regime, most individual leaf samples provided 2 to 8 rare genotypes, with only the Magnolia sample providing no unique genotypes.

Table 2

P-values from chi-squared analyses indicate the significance of different isolation factors on the diversity of recovered bacterial isolatesa

Factors affecting the recovery of novel genotypes from the rhizosphere

Having examined the phyllosphere of plants grown in a local area where colonizing bacteria are captured from a theoretically broad (i.e. airborne) pool of emigrating microbes, we next turned to examine the relative importance of various factors on the recovery of novel bacterial genotypes from root tissues which are typically exposed to large but relatively immobile pools of diversity. With Collection 3, we characterized the relative influence of media, plant species, and soil source on the diversity of recovered isolates.

In the rhizosphere, the choice of media, again, affected the type but not the number of rare genotypes recovered (Fig. 1). In contrast with the phyllosphere, the number of rare genotypes recovered from the rhizosphere did not vary by plant species (P > 0.4). In this study, the recovery of rare genotypes from the rhizosphere was most strongly influenced by soil source (P = 0.001, Table 2). Interestingly, no apparent correlation in the number or identity of genotypes was observed for the closely paired soils (3 and 4, 5 and 6, 7 and 8, and 9 and 10), which varied from < 5 to just under 250 m apart. This indicates that while substrate differences are important, they are perhaps not much more important than environmental differences in soil conditions occurring over relatively small spatial scales. For every 15 isolates, the number of genotypes per soil source ranged from 1 to 8, averaging just 2.4 to 3.9 genotypes per media depending on the crop. Using our tiered sampling regime, each soil provided between 6 and 15 rare genotypes, reflecting the greater number of media used to create this second collection. These data support the view that rhizosphere microbial communities, like those in the soils from which they are derived, are strongly influenced by the many complex and interacting factors that limit spread and enhance localized evolution of microbial populations (Garbeva et al., 2004). And these data highlight the benefit of sampling diverse matrices into which roots can productively grow to identify novel rhizosphere bacteria.

Screening of distinct genotypes for biocontrol activity

We next considered the question of whether or not the three collections might include novel biofungicidal or plant health promoting bacteria. In this study, we chose to screen 419 isolates in planta based primarily on genotypic differentiation. These included 176 mixed collection isolates representing 52 of the 62 identified genotypes, 129 phyllosphere isolates representing 80 of the 88 identified genotypes, and 82 rhizosphere isolates representing 67 of 132 genotypes. While not all genotypes were tested (due to limited resources), particular emphasis was placed on the rare genotypes because of our motivation to discover new biopesticide agents.

From this primary screen targeting 6 different plant diseases, 48 isolates displaying the greatest biopesticide potential were retested and also assayed for their ability to induce system resistance to disease caused by a phytobacterial pathogen. Of these, a diverse set of 20 isolates displayed remarkable biopesticide properties (Table 3). Putative identifications of these isolates were made using single-pass 16S rRNA gene sequencing (data not shown). Each of these 20 strains reduced disease relative to the negative control (P < 0.10) and did so as well or better than the commercial biofungicide Serenade (containing Bacillus subtilis strain QST713) for one or more pathosystems (bold values in Table 3). Additionally, 15 of these strains reduced the average disease severity rating of Xanthomonas campestris pv. vesicatoria infection on pepper; and such patterns were statistically significant (P < 0.10) for 9 of the isolates. Remarkably, 16 of these top performing isolates were rare in our collections, i.e. found to occur at a frequency of ≤ 1% of the selected isolates. For those five genotypes more commonly found in our collections, some significant variation in efficacy among isolates of the same genotypes was noted (data not shown), indicating that the ARDRA-genotype was not always predictive of biocontrol ability. Most of the selected genotypes were obtained from distinct combinations of sample variables, with all combinations of source, incubation, and media being represented. And, eight (38%) were classified as rare genotypes, i.e. singleton or doublets, in our collections.

Table 3

Biocontrol efficacy the most active genotypes recovered from plantsa