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The effect of crop species on DNase-producing bacteria in two soils

The effect of crop species on DNase-producing bacteria in two soils Purpose: Extracellular deoxyribonucleases (exDNases) from microbial origin contribute substantially to the restriction of extracellular DNA (exDNA) in the soil. Hence, it is imperative to understand the diversity of bacterial species capable of performing this important soil function and how crop species influence their dynamics in the soil. The present study investigates the occurrence of DNase-producing bacteria (DPB) in leachate samples obtained from soils in which the crop species of alfalfa (Medicago sativa L.), canola (Brassica napus L.), soybean (Glycine max [L.] Merr.) and wheat (Triticum aestivum L.) were raised in a growth room. Methods: Selective media containing methyl green indicator was used to screen for DPB from leachate samples, whereas the 16S rRNA sequence analysis was employed to identify the isolates. Results: The proportion of culturable DPB ranged between 5.72 and 40.01%; however, we did observe specific crop effects that shifted throughout the growing period. In general, higher proportions of exDNase producers were observed when the soils had lower nutrient levels. On using the 16S rRNA to classify the DPB isolates, most isolates were found to be members of the Bacillus genera, while other groups included Chryseobacterium, Fictibacillus, Flavobacterium, Microbacterium, Nubsella, Pseudomonas, Psychrobacillus, Rheinheimera, Serratia and Stenotrophomonas. Five candidate exDNase/nuclease-encoding proteins were also identified from Bacillus mycoides genomes using online databases. Conclusion: Results from this study showed that crop species, growth stage and soil properties were important factors shaping the populations of DPB in leachate samples; however, soil properties seemed to have a greater influence on the trends observed on these bacterial populations. It may be possible to target soil indigenous bacteria that produce exDNases through management to decrease potential unintended effects of transgenes originating from genetically modified organisms (GMOs) or other introduced nucleic acid sequences in the environment. Keywords: DNase-producing bacteria, exDNA, exDNAse(s), GMOs, Wheat, Canola, Soybean, Alfalfa Introduction plant species-specific microbial consortia (Berg and Plants and microbes are known to form complex and Smalla 2009; Hartmann et al. 2009). The structure and dynamic interactions within the soil matrix, and these functions of microbial communities in the soil are can have significant implications to the functioning of strongly influenced by the residing plant species (Burns the ecosystem (Hartmann et al. 2009). These series of et al. 2015). For instance, the microbial communities in complex interactions between the plant, microbes and the soil associated with wheat and canola differ substan- the soil environment result to increased microbial activ- tially (Hansen et al. 2019 Hansen et al. 2018; Lay et al. ity in the rhizosphere resulting to the selection of unique 2018). Because of the intimate association between plants and * Correspondence: Rob.Gulden@umanitoba.ca microbes, the release of genetically engineered (GE) Department of Plant Science, University of Manitoba, 222 Agriculture plants brought into question the ecological sustainability Building, 66 Dafoe Road, Winnipeg, MB R3T 2N2, Canada © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 2 of 18 of the technology due to the perceived non-targeted ef- extracellularly (Benedik and Strych 1998); however, stud- fects of transgenes to soil organisms such as natural ies have found that many bacterial species exude nucle- transformation of microbes through horizontal gene ases that are either anchored to the cell wall or exuded transfer mechanisms (HGT) (Tsatsakis et al. 2017). The into the growth medium (Eaves and Jeffries 1963; Nakai increased rhizosphere activity has also been documented et al. 1965; Rothberg and Swartz 1965; Greaves and for nuclease-producing microorganisms which could be Webley 1965; Jakubovics et al. 2013; Sheikh and Hos- exploited for transgenes mitigation in the environment. seini 2013). This makes it possible to detect exDNase ac- For instance, Greaves and Webley (1965) observed that tivities on agar plates containing indicators such as the total number of nuclease-producing microorganisms methyl green that are intercalated into the double helix were higher on the root surface and in the rhizosphere matrix, but become clear halos of enzyme activity soil of pasture grasses than in non-rhizosphere soil. The around the growing colonies as the double helix is being plethora of compounds secreted through the root cap degraded. mucilage including genetic material (Wen et al. 2009; The majority of studies on soil bacteria report single Knox et al. 2020; Ropitaux et al. 2020; Chambard et al. isolates that produce exDNases, whereas only a few 2021) provide a source of nutrients and energy that may studies have identified multiple isolates that produce result in differential growth of microbial communities exDNases. Pioneer studies on nuclease-producing bac- (Berg and Smalla 2009; Haichar et al. 2014). Plant DNA teria (Greaves et al. 1970) reported nuclease production enters the soil environment mainly through root exu- by Cytophaga johnsonii isolated from the soil which uti- dates, root cap sloughing, pollen dispersal and degrad- lized nucleic acids as a C and P source more efficiently ation of plant materials (Levy-Booth et al. 2007; than a N source. On the other hand, some bacterial spe- Monticolo et al. 2020). cies such as Escherichia coli, Serratia marcescens, Myxo- One major fate of extracellular DNA (exDNA) in the coccus virescens, Myxococcus fulvus and Chondrococcus soil environment is degradation by indigenous soil mi- coralloides can thrive solely on nucleic acids as a C crobial extracellular deoxyribonucleases (exDNases) into source for their growth (Norén 1955; Redfield 1993; smaller fragments resulting to the loss of genetic infor- Benedik and Strych 1998). For instance, the proliferation mation (Blum et al. 1997; Levy-Booth et al. 2007; Niel- of a marine thriving Vibrio sp. increased up to 4 orders sen et al. 2007; Ibáñez de Aldecoa et al. 2017). The of magnitude in the presence of DNA, with rapid micro- presence of these restriction enzymes therefore serves as bial assimilation of a significant proportion of the deg- barriers to exDNA introgression into native soil bacteria radation products (Maeda and Taga 1974). Ten et al. through HGT (Dodd and Pemberton 1999; Wu et al. (2006) isolated and characterized a novel DNase- 2001) and its subsequent long-term persistence in the producing isolate Pedobacter ginsengisoli sp. nov. be- soil environment (Kunadiya et al. 2021). For instance, longing to the Bacteroidetes phyla from field soils grow- Stewart and Sinigalliano (1990) reported a decrease in ing ginseng (Panax ginseng) in South Korea. Strong natural transformation frequency in bacteria after incu- exDNase activity was also observed in Frankia strains bating marine and artificial sediments with DNase 1. Mi- which are known to form symbiotic relationships with crobial exDNases contribute to soil functions and have many dicot plant species (Tavares and Sellstedt 1997). largely been associated with nutrient scavenging activ- Extracellular DNase production has been reported in ities (Benedik and Strych 1998; Desai and Shankar 2003; several marine bacterial isolates with the majority be- Levy-Booth et al. 2007; Ibáñez de Aldecoa et al. 2017) longing to the genera Bacillus (Al-Wahaibi et al. 2019; and virulence of pathogens (Park et al. 2019; Monticolo Asha and Krishnaveni 2020). Moreover, several soil bac- et al. 2020). For example, an increase of up to 35-fold in terial isolates belonging to different phyla groups were viable bacterial counts was observed 3 days after spiking observed to express exDNases whose activities were soils with nucleic acids, thereby implying that microbes mostly optimal at neutral pH and at temperatures be- use nucleic acids as substrates for growth (Greaves and tween 30 and 40 °C (Kamble et al. 2011). Greaves and Wilson 1970). Blum et al. (1997) also observed an in- Wilson (1970) also recorded large numbers of DPB from crease in the number of soil microbes 12 h after inject- different soil types growing grassy vegetation with vary- ing DNA into soils, with rapid degradation occurring to ing proportions of DPBs at 17% in kaolinite, 86% in the unbound DNA spike. montmorillonite, 58% in peat and 47% in sandy soils. In Some bacteria and fungi closely associated with plant an indoor study carried out by Balestrazzi et al. (2007) roots have been reported to exhibit exDNase activities using transgenic white poplars with the bar gene insert, (Greaves and Webley 1965; Bertagnolli et al. 1996; 62.5 to 100% of the total culturable bacterial populations Tavares and Sellstedt 2001; Klosterman et al. 2001; were observed to express exDNase activities. Moreover, Balestrazzi et al. 2007). It was thought that only a limited bacterial isolates cultured and identified as DNase pro- number of bacterial species produce nucleases ducers in their study belonged to five genera: Bacillus, Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 3 of 18 Brevibacillus, Microbacterium, Pseudomonas and Table 1 Parameters of the two soils used in this study Stenotrophomonas. Soil ID To date, no study has described DPB inhabiting agri- Parameters Soil A Soil B cultural soils nor has the effect of crop species on DPB −1 N, kg ha 77.6 172.4 been investigated. Thus, the current study was carried −1 S, kg ha 19.1 23.6 out to quantify and identify bacterial species that express −1 P, kg ha 31.4 56.0 DNase activity extracellularly in soils collected from an −1 K, kg ha 412.0 555.5 agricultural field planted to different crops. Since micro- −1 Mg, kg ha 788.0 822.1 bial exDNase activity is an important soil function and −1 can contribute significantly to ecosystem services such Ca, kg ha 4664.0 4715.2 as hindering the dissemination of transgenes in the en- −1 Na, kg ha 51.5 71.7 vironment, understanding the diversity of exDNase- −1 Zn, kg ha 4.9 11.3 releasing bacteria in the soil and how different crop spe- −1 Fe, kg ha 126.8 297.9 cies affect this diversity is important. To add on that, −1 Mn, kg ha 12.1 88.7 exDNase activity was used as a model function in the −1 B, kg ha 1.1 1.3 current study to understand how crop species and soil type influence soil functions which are mediated by soil pH 6.3 5.1 microbes and may be indirectly or directly affected by Cation exchange capacity (CEC), meq 13.9 19.9 management practices employed and/or new techno- Organic matter (OM), % 3.3 4.3 logical advances in agriculture. We hypothesized that a Sand, % 76.0 72.0 number of key DNase-producing bacteria inhabiting Silt, % 11.0 15.0 agricultural soils would be identified. Clay, % 13.0 13.0 Materials and methods Leaching study carbathiin) while the alfalfa seeds were scarified briefly Prior to the study, soils were collected at two different using an electric seed scarifier (Westinghouse Electric locations (A and B) within the University of Manitoba’s Corp AC Motor 317P044, USA). Ian N. Morrison Research Farm in Carman, MB, Canada Shortly after emergence, the pots were thinned to (49° 29′ 48″ N, 98° 2′ 26″ W, 267 m above sea level). three seedlings per pot which were watered as required Chemical and physical properties of these soils were de- from here on. Three weeks post emergence, pots were termined at a commercial laboratory (Agvise Laborator- fertilized with nitrogen-phosphorus-potassium (20:20:20) −1 ies Inc., Northwood, ND, USA). The soil parameters are at the rate of 5 g L of water. The plants were main- shown in Table 1, and the major difference between the tained at 25/20 °C and 16/8 h day/night at a relative hu- soils was macronutrients (N, P, K), micronutrients (Zn, midity of 75% throughout the study. To prevent water Fe, Mn) and pH. The experiments conducted in this from preferentially flowing between the soil and the pot study included a preliminary experimental run with soil during treatment leaching, at the time of seeding, the A to develop the methods and a full experiment with soil surface was shaped into a deep concave in each pot soil A and one with soil B. All experiments were con- to facilitate leaching through the soil profile and leach- ducted in the growth room in a randomized complete ing was done at least monthly with 200 mL of distilled block design. Six replicates each of four crop species, in- H O. The first 30 mL of the leachate from each pot were cluding, wheat (Triticum aestivum L.), canola (Brassica collected in 50 mL falcon tubes placed on ice during napus L.), alfalfa (Medicago sativa L.) and soybean (Gly- leaching to minimize enzymatic degradation of DNA by cine max [L.] Merr.) were used in the study. Unplanted enzymes with further analyses, and DNA purification pots were included as controls. Plants were grown in performed immediately after sampling. The crops’ devel- 1.5-L (10.5 cm diameter, 38 cm height) transparent, opmental stages at the time of leaching are shown in inverted plastic bottles each covered with aluminium foil Table 2. Coinciding with monthly leaching, the alumin- to exclude light and having a 2-cm diameter hole in ium foil was removed temporarily and a 5 × 5 cm square their bottoms. Two layers of fiberglass mesh (0.2 mm) grid with 1-cm grid gradations printed on transparent were placed at the bottom of each pot followed by 150 plastic sheets was placed on the exterior of each pot. mL of industrial quartz. One litre mixture of industrial The number of root-grid line intersections was counted −1 quartz and soil (1:1, v/v) fertilized with 40 kg N ha in in each square to determine root length density (RLD). the form of urea was added to the pots, and before At the end of the experiment, shoot and root dry matter planting, the canola seeds were treated with fungicide were determined for each plant after drying to equilib- (trifloxystrobin, metalaxyl) and insecticide (clothianidin, rium at 55 °C. Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 4 of 18 Table 2 Developmental stages of the four crops at different times of leaching during experimental runs Experiment 1 (soil A) Experiment 2 (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) Alfalfa early veg. Mid veg. Early budding Flowering 7th trifoliate Mid veg. Early budding Canola 4 leaf stage 5 leaf stage Flowering Phys. maturity 3 leaf stage 5 leaf stage Flowering Soybean Flowering Flowering Phys. maturity – 5th trifoliate Flowering Phys. maturity Wheat Bolting Heading Phys. maturity – Tillering Heading Phys. maturity Abbreviations: veg vegetative, phys physiological *Days after planting Screening for DNase activity Scientific, Ottawa, ON, Canada), 1 μL (10 pmol) of each of One milliliter of aliquot of each leachate sample was the universal primers 27F/1492R (Suzuki and Giovannoni transferred into a 2-mL centrifuge tube and each leach- 1996), 0.75 μL 100% dimethyl sulphoxide (DMSO), 2.5 μL ate was 10-fold serially diluted. A 100 μL aliquot of the of DNA and 7.25 μL distilled autoclaved water. The qPCR −3 10 dilution was plated onto two replicate plates con- conditions were initial denaturation for 30 s at 98 °C, TM taining the Difco DNase Test Agar with methyl green followed by 30 cycles of denaturation for 10 s at 98 °C, an- as a substrate for DNase enzyme activity (DGM nealing for 30 s at 55 °C, extension at 72 °C for 30 s and a medium, Becton, Dickinson and Company Sparks, USA) final extension step at 72 °C for 10 min. The two replicate prepared according to the manufacturer’s instructions. samples of the qPCR products were pooled and verified on Plates were incubated at 25 °C, and 48 h after plating, 1% agarose gel, and thereafter, the qPCR products were total culturable DNase-producing bacteria (TCDPB) and sent to Macrogen (Rockville, Maryland, USA) for Sanger all the total colony-forming units (TCFU) with and with- sequencing using the universal primers used in this study. out DNA degradation halos were enumerated and used to estimate the proportion of culturable DNase- Genomic DNA extraction from leachates producing bacteria (%CDPB). Finally, single DNase- Total DNA was extracted from each leachate sample forming colonies were picked randomly from the treat- using the PowerSoil® total DNA isolation kit (MoBio, La- ments and sub-cultured on DGM medium to obtain boratories, Solana Beach, CA, USA) with adjustments single isolated colonies for identification purposes. made to adapt the manufacturer’s protocol to our ex- periment. Briefly, 10 mL aliquot of each leachate was pi- Bacterial DNA extraction petted into a 50-mL centrifuge tube and centrifuged at Genomic DNA of bacterial single colonies were ex- 5000g for 30 min at 4 °C to recover DNA and bacterial tracted using the InstaGene Matrix (IM) (Bio-Rad, cells from the leachates. The pellets were washed with Mississauga, ON, Canada), according to the manufac- cold 70% ethanol and centrifuged at 5000g for 10 min at turer’s protocol. In brief, picked isolated single colonies 4 °C followed by drying and resuspension in 1.5 mL of were suspended in 1 mL of distilled autoclaved water sterile Milli Q H O. The rest of the protocol followed and vortexed briefly before centrifuging at 15,294×g for the manufacturer’s instructions except for the solution 1 min. The resulting pellet was suspended in 200 μLof volumes which were optimized for leachate samples (500 InstaGene Matrix and incubated at 37 °C for 15 min μL bead solution buffer, 15 μL C1 solution, 100 μLC2 using a water bath. Samples were vortexed at high speed solution and 50 μL C3 solution per extraction). DNA for 10 s and placed in a 100 °C water bath for 8 min was eluted from the column with 100 μL of Milli Q after which samples were vortexed for 10 s at high speed H O. The quantity and purity of DNA was assessed on a and centrifuged for 3 min at 15,294×g. DNA quantity microplate spectrophotometer (Epoch Biotek, Winooski, and quality were assessed using a microplate spectro- VT, USA) at 260 and 280 nm. photometer (Epoch Biotek, Winooski, VT, USA) and samples were stored in the freezer at − 20 °C until fur- Quantitative real-time PCR amplifications (qPCR) ther analyses. Quantitative PCR for total bacterial load (TBL) was per- formed on DNA from leachate samples using a Bio-Rad Target amplification for sequencing CFX Real-time system (Bio-Rad, Hercules, CA, USA). Amplification of the partial 16S rRNA gene in DNA The amplifications were performed in two replicates on from bacterial single colonies was done in two replicate 96-well reaction plates (Bio-Rad, Hercules, CA, USA) reactions in a total volume of 25 μL containing 12.5 μL with a final volume of 20 μL reaction mixture containing of the 2x Phusion High Fidelity PCR Master Mix (Fisher 10 μL iTaq SYBR Green Supermix (Bio-Rad, Hercules, Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 5 of 18 CA, USA), 0.5 μL (10 pmol) of each of the eubacterial Statistical analyses primers 338F/518R (Fierer et al. 2005), 1 μL of genomic The SAS package 9.4 (SAS Institute, Inc., Cary, NC, DNA and 8 μL of distilled autoclaved water. The qPCR USA) was used to conduct analysis of variance amplification conditions were 3 min at 95 °C followed (ANOVA) using the mixed procedure. The preliminary by 35 cycles of 20 s at 95 °C, 20 s at 53 °C and 20 s at 72 experimental run with soil A which had fewer and in- °C. Following qPCR, a melt curve analysis was conducted compatible harvest dates was not included in this final with a temperature gradient from 65 to 95 °C in 0.5 °C analysis. Fixed factors in the ANOVA model were crop, increments for 5 s per cycle with continuous fluores- sampling date, experiment and their interactions. The cence monitoring performed after amplification to con- replication blocks nested within experimental run were firm amplification specificity to the target product. considered random. To satisfy the normality assump- Purified DNA products amplified from soil DNA using tions, log or square root transformations were applied to similar primers were pooled and 10-fold serially diluted the dataset and normality of residuals was examined by seven times to construct a standard curve to quantify using the Shapiro-Wilk test in the univariate procedure. the target DNA and evaluate primer efficiency. In addition, Lund’s test (Lund 1975) was used to identify and inspect potentially influential outliers, while the Akaike’s information criterion was used to examine and Phylogenetic analyses correct (when necessary) the homogeneity of variance Nucleotide sequences were examined and edited using prior to final data analysis. Following this, the REPEAT the Chromas software package (www.technelysium.com. ED statement was used to correct for heterogeneity of au) after which the forward and reverse strands of the variance among treatments when necessary. Fisher’s Pro- partial 16S rRNA sequences were aligned using the tected LSD (α = 0.05) difference was used to compare ClustalW multiple alignment option in the BioEdit pro- treatment means using the pdmix800 macro (Saxton gram (Hall 1999). The GenBank databases were used to 1998). The method=type3 option was used to determine determine close phylogenetic associations using the the partitioning of variance based on estimated type 3 Basic Local Alignment Tool (BLAST) at the National sums squares To determine co-linearity among the re- Center for Biotechnology Information (http://www-ncbi- sponse variables, correlation analysis was used. This ana- nlm-nih-gov.uml.idm.oclc.org). The BioEdit program lysis was conducted within experiment and sampling was used to assemble and align all sequences while max- dates to minimize confounding effects with date and imum likelihood phylogenetic analyses were conducted soil-specific effects. using the Kimura 2-parameter (K2P) model (Kimura 1980). The final tree was constructed from 1000 boot- Results for total culturable DNase-producing strap replicates in MEGA v7.0.18 (Kumar et al. 2016) bacteria (TCDPB), proportion of culturable DNase- after which edits were made using FigTree v1.4.3 (http:// producing bacteria (%CDPB), total colony-forming tree.bio.ed.ac.uk/software/figtree/). The partial 16S units (TCFU) and total bacterial load (TBL) rRNA nucleotide sequences of the isolates were depos- Experiment was the most important factor influencing ited in the GeneBank database under the accession num- the interpretation of the results among the bacterial re- bers (MN294613 to MN294681) (Table 9). sponse variables in these experiments. The behaviour of the response variables between the two experiments was Identification of putative exDNase/nuclease-encoding often quite different. As these response variables were genes determined from leachate samples, it was not unex- Bacterial genomes from the IMG/M database (Marko- pected that experiment played a major role in the parti- witz et al. 2012) were searched for genes encoding pos- tioning of variance components as soil physical and sible secreted DNases/nucleases. The protein sequences chemical properties can affect leachate composition and encoding the identified candidate exDNases/nucleases some of these parameters were different between the genes in Bacillus mycoides were retrieved from UNI- two soils used in this study (Table 1). Leachate samples PROT protein database (Apweiler et al. 2004). Finally, to were used in these experiments for several reasons. First, identify candidate secreted DNases/nucleases, the candi- they are non-destructive and allow for repeat sampling date proteins from Bacillus mycoides were screened for of the same experimental unit; second, they are integra- secretion signals using SignalP (Petersen et al. 2011) and tive over the entire volume of soil for each experimental SecretomeP (Bendtsen et al. 2004) which generate non- unit, and third, an exDNA disappearance assay (manu- classical neural network (NN) secretion scores for non- script in preparation) was developed which was more re- classical secreted proteins, whereas PSORTb 3.0.2 liable on leachate samples than soil samples, and these (http://www.psort.org/psortb/index.html) (Yu et al. experiments contributed to understanding the exDNA 2010) was used to predict the subcellular location. dynamics in leachate water and the effects of crop Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 6 of 18 species, sampling date and soil type on this process. In lowest TCDPB concentrations were observed in the can- the combined analyses, a relatively small, but significant ola leachates. Similar trends were also observed in the portion of the variance was partitioned to the plant spe- preliminary experiment (data not shown), and we are cies and sampling date effects. therefore relatively confident the observed differences All main effects except one and all but two interac- between the experiments were influenced strongly by tions were statistically significant among all bacterial re- soil type. In contrast, a different response was observed sponse variables (Table 3). The relative contribution of in experiment 2 with soil B where canola leachates con- sampling date and its interactions to total variation rela- tained greater densities of TCDPB compared with the tive to the crop species effect was not the same among UC at all sampling dates, while TCDPB in alfalfa, soy- the response variables. In specific, effects including sam- bean and wheat leachates were similar at most sampling pling date consumed less variation than all crop species dates except at 89 dap where the number of TCDPB effects in TCDPB and TCFU, whereas the opposite was were lower in soybean leachates than in alfalfa leachates. observed for %CDPB and 16S rRNA-based TBL. Overall, At 89 dap, soybean were at physiological maturity while the experimental factors and their interactions explained alfalfa was still at anthesis; thus, the difference in plant 53–71% of the total variation in these experiments indi- maturity was a probable factor contributing to the differ- cating a significant amount of unexplained variation in ence observed. TCDPB (43%), %CDPB (48%) and TBL (36%) suggesting The sampling date response (which signify plant devel- high variability in these measurements or that critical opment) in TCDPB was also unique to experiment, and factors that affect these bacterial parameters were not interestingly, this effect was most prominent in experi- included in the experiment. When analyzing TCDPB ment 1 and particularly in the alfalfa, canola and UC within each experiment, crop species was the main leachates. In canola leachates from experiment 1, a pro- source of variation in both experiments consuming 28% gressive increase in the population density of TCDPB and 36% of the total variation. Additionally, date was the was observed as this species developed and matured. On main source of variation in both experiments for TBL the other hand, a decrease in TCDPB occurred at the explaining about 16% and 42% of total variation in ex- mid-vegetative developmental stages in alfalfa leachates, periments 1 and 2, respectively. The same degree and while in the UC leachates, lower TCDPB were observed consistency of variance partitioning to crop species and at the first sampling date. Sampling date or its inter- sampling date within experiments was not observed in action with crop species had no effect on TCDPB in ex- the other bacterial response variables; however, either periment 2 with soil B. While similar in texture, soil B was significant depending on the experiment (data not was more nutrient rich, particularly in N and some of shown). This shift in variance partitioning when ana- the micronutrients, than soil A (Table 1). Soil B also had lyzed within experiments clearly showed the importance a lower pH, and a higher CEC and OM content than soil of crop species and sampling date on bacterial response A which likely contributed to the soil-specific observa- variables. tions. The nutrient profile of each soil was only assessed In experiment 1 with soil A, the number of TCDPB in at the beginning of each experiment. leachates from alfalfa and soybean were equal to or Culturable DNase-producing bacteria (%CDPB) expressed greater than TCDPB in leachates from the unplanted as a proportion of the TCFU ranged from 5.7 to 40.0% control (UC) (Table 4). The number of TCDPB in wheat among treatments in these experiments (Table 5). While the leachates was mostly intermediate, while generally the maximum proportions of %CDPB were similar between the Table 3 Percentage of total variance contributed by experimental factors and their interactions on measured bacterial parameters a a a a Source TCDPB P value %CDPB P value TCFU P value TBL P value Crop 7.66 < .0001 3.74 0.023 7.95 < .0001 2.86 0.022 Date 7.47 < .0001 10.78 < .0001 16.88 < .0001 22.68 < .0001 Crop x date 9.24 0.001 3.55 0.359 11.82 < .0001 5.03 0.030 Experiment 0.30 0.313 16.37 < .0001 10.99 < .0001 7.45 < .0001 Crop x experiment 21.24 < .0001 5.50 0.003 15.91 < .0001 8.22 < .0001 Date x experiment 0.22 0.693 2.91 0.012 2.33 0.003 10.21 < .0001 Crop x date x experiment 10.43 < .0001 9.65 0.001 5.43 0.001 8.09 0.0002 Error 43.44 – 47.5 – 28.69 – 35.46 – Column values are the proportions (%) of the variance component explained by the factor Abbreviations: TCDPB total culturable DNase-producing bacteria, %CDPB proportion of culturable DNase-producing bacteria, TCFU total colony-forming units, TBL total bacteria load Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 7 of 18 Table 4 Effect of crop species on TCDPB expressed in log CFU per mL of leachate during experimental runs TCDPB in experiment 1 TCDPB in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) c,B a,A a,AB a,A c b c UC 4.96 5.40 5.28 5.65 4.90 4.84 4.98 a,A ab,B a,B ab,A b a ab Alfalfa 5.70 5.20 5.35 5.54 5.13 5.36 5.46 d,C c,BC ab,AB b,A a a a Canola 4.42 4.79 5.12 5.33 5.49 5.42 5.53 ab ab a ab a c Soybean 5.41 5.35 5.53 – 5.36 5.38 4.99 bc b b ab ab bc Wheat 5.22 5.19 4.73 – 5.36 5.13 5.16 SEM 0.104 0.073 0.167 0.081 0.084 0.137 0.106 P value < .0001 < .0001 0.020 0.042 0.001 0.029 0.005 Days after planting Abbreviations: UC unplanted control, TCDPB total culturable DNase-producing bacteria Mean separation done for each sampling date within each experiment a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05. A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 experiments (40% and 36% in experiment 1 and 2, respect- Moreover, canola leachates consistently had greater %CDPB ively), the lowest %CDPB was 10% lower in experiment 2 than the UC at all sampling dates in this experiment. The than experiment 1 which again, is indicative of soil-specific %CDPB of all other crop species were similar to UC in ex- bacterial population dynamics. Generally, the effect of crop periment 2 except at 59 dap where alfalfa and soybean species was less consistent in this response variable as differ- leachates had greater %CDPB. ences among treatments were observed at all sampling dates Despite the observed differences in TCDPB and only in experiment 2. In experiment 1, alfalfa and wheat %CDPB among the experimental treatments, TCDPB leachates had the greatest %CDPB at the earlier sampling and TCFU were correlated at each sampling date in both times. Also, differences among treatments in %CDPB were experiments. The Pearson R values ranged from 0.57 to only observed at 63 dap and in particular, %CDPB in alfalfa, 0.94 (p value < 0.001). The relationship between TCFU, were about half of those observed in the UC. This was the culturable portion, and TBL based on 16S rRNA caused principally by lower TCDPB in the alfalfa treatment copy number was less clear. In experiment 2 and most (Table 4). In experiment 2, on the other hand, planted treat- sampling dates of experiment 1, no correlations were ments resulted in %CDPB that were quadruple those of the found between these bacterial measures. However, posi- UC at 59 dap (Table 5), which was probably caused by lower tive correlations between TCFU and TBL were observed TCDPB and TCFU in the UC treatment (Tables 4 and 6). at 63 dap (Pearson R = 0.40, p value = 0.0001) and 92 Table 5 Effect of crop species on %CDPB during experimental runs % CDPB in experiment 1 % CDPB in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) ab ab a a b,AB c,B bc,A UC 30.16 29.12 30.81 31.87 14.12 5.72 17.33 a,A c,C a,AB a,BC b a abc Alfalfa 40.01 15.47 29.05 22.17 15.27 20.67 25.19 b a a a a,A a,B a,A Canola 29.37 34.21 30.55 23.72 29.70 15.63 35.97 ab ab a ab ab c Soybean 36.29 28.31 31.42 – 21.09 14.40 14.14 ab,A bc,B a,B ab,A bc,B ab,A Wheat 38.29 18.09 21.53 – 20.26 9.88 29.00 SEM 0.308 0.393 0.505 0.372 0.372 0.261 0.477 P value 0.145 0.009 0.644 0.129 0.020 0.0001 0.022 Days after planting Abbreviations: UC unplanted control, %CDPB proportion of culturable DNase-producing bacteria Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05 A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 8 of 18 Table 6 Effect of crop species on TCFU expressed in log per milliliter of leachate during experimental runs TCFU in experiment 1 TCFU in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) c,C a,AB ab,B a,A b,B a,A bc,B UC 5.49 5.97 5.80 6.15 5.78 6.10 5.77 a,AB a,BC ab,C a,A ab a a Alfalfa 6.10 6.02 5.89 6.21 5.96 6.05 6.09 d,D b,C bc,B b,A a,B a,A ab,B Canola 4.96 5.26 5.68 5.97 6.02 6.24 5.98 ab a a a a bc Soybean 5.86 5.91 6.04 – 6.04 6.23 5.85 bc,B a,A c,B a,A a,A c,B Wheat 5.64 5.95 5.43 – 6.07 6.15 5.71 SEM 0.085 0.053 0.107 0.052 0.068 0.141 0.079 P value < .0001 < .0001 < .0001 0.015 0.055 0.825 0.011 Days after planting Abbreviations: UC unplanted control, TCFU total colony-forming units Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05 A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 dap (Pearson R = 0.56, p value < 0.0001) in experiment 1 TBL, on the other hand, decreased in alfalfa at the (data not shown). These results not only indicate soil- last sampling date in both experiments. The same specific microbial dynamics, but as expected, also an trend was observed for most other plant species as important temporal component to soil microbial commu- well, where TBL was lowest at the last sampling date nity dynamics. Furthermore, these findings also highlight in experiment 2, and for canola in experiment 1. Dif- the differences between culturable and unculturable tech- ferences among treatments within sampling date were niques for bacterial studies. sporadic and inconsistent. In many cases, the ob- In experiment 1, the range in TCDPB and TCFU served differences were less than 10-fold and there- (Tables 4 and 6) among the treatments diminished fore likely of limited biological significance. over the duration of the experiments showing a clear trend in the temporal dynamics in these response var- Shoot and root growth iables. More specific, the largest differences (greater Root length density measurements are a non-destructive than 10-fold among treatments) were observed at 49 two-dimensional method for estimating the density of dap in experiment 1, and by the end of the experi- ments, this range in differences diminished to about Table 7 Effect of crop species on TBL using 16S rRNA gene copies expressed in log per mL of leachate during 0.32 and 0.24 log units for TCDPB and TCFU, re- 10 experimental runs spectively. The same was not observed in experiment TBL in experiment 1 TBL in experiment 2 2where therange in thedifferenceamong crop spe- (soil A) (soil B) cies was more consistent throughout the development Sampling date Sampling date of the plants (0.55–0.59 log units in TCDPB and * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) 0.19–0.39 log units in TCFU). Differences among a,AB a,A b,C a,BC a b a UC 6.93 7.19 6.66 6.86 7.27 6.76 6.68 treatments were less common for TCFU in experi- a,A ab,A b,AB ab,B a,A a,A a,B ment 2 and TBL in experiment 1 (Tables 6 and 7). Alfalfa 6.84 6.83 6.64 6.43 7.61 7.59 6.51 Nevertheless, a few plant species-specific trends were a,A b,A ab,A b,B a,A a,A a,B Canola 6.86 6.54 6.70 5.96 7.52 7.68 6.80 observed in these response variables, particularly in a ab a a,A b,A b,B Soybean 6.91 6.96 6.94 – 7.65 7.13 5.65 experiment 1. For example, canola consistently had a,B a,A ab,B a,A a,A a,B Wheat 6.73 7.09 6.70 – 7.75 7.71 7.04 the lowest TCFU densities at each sampling date in SEM 0.076 0.160 0.089 0.205 0.172 0.153 0.254 experiment 1 and the concentration increased at each P value 0.333 0.049 0.157 0.047 0.372 0.002 0.013 subsequent sampling date in this species. In experi- ment 2, TCFU in canola leachates were not different *Days after planting Abbreviations: UC unplanted control, TBL total bacteria load from those in the other crop species and the greatest Mean separation done for each sampling date within each experimental run a,b,c bacterial densities were observed at 59 dap. In experi- Means with different letters within columns indicate statistical differences between treatments at P < 0.05 ment 1, alfalfa had among the highest TCFU dens- A,B,C Means with different letters between columns indicate statistical ities, but these were lower during the mid-vegetative differences between sampling dates at P < 0.05 stages and increased again at the final sampling date. P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 9 of 18 root proliferation in a volume of soil. In experiment 1, biomass are more important at influencing soil microbial no relationship between RLD and soil bacterial response function. variables were found, whereas in experiment 2, root length density correlated with TCFU at all sampling DNase-producing bacterial isolates dates (Pearson R = 0.39 to 0.42, p values 0.0008 to Some of the DPB were isolated and picked for identification 0.0027). At 32 dap in experiment 2, RLD also was corre- using Sanger sequencing. Bacterial isolates identified in the lated with %CDPB (Pearson R = 0.49, p value < 0.0001) current study were classified into four phyla groups includ- and TBL (Pearson R = 0.38, p value = 0.003), and at 59 ing the Firmicutes (37 isolates), Actinobacteria (14 isolates), dap, RLD was correlated positively with TCDPB (Pear- Proteobacteria (10 isolates) and Bacteroides (8 isolates) with son R = 0.39, p value = 0.0019) and negatively with TBL a total of 11 genera groups (Table 9). The genera groups of (Pearson R = − 0.40, p value = 0.0014). Moreover, at the DPB isolates identified in this study included Bacillus, later sampling dates in experiment 1, RLD correlated Chryseobacterium, Fictibacillus, Flavobacterium, Microbac- well with per plant shoot and per plant root biomass terium, Nubsella, Pseudomonas, Psychrobacillus, Rheinhei- (Pearson R = 0.46–0.72, p value < 0.0001). These results mera, Serratia and Stenotrophomonas.The largest indicate that root length density alone may not be as im- proportion of culturable DPB (54%) was identified as Firmi- portant as other crop species-specific effects for the ob- cutes with 6 different Bacillus species. Theidentityof the served treatment differences among the crop species and DPB isolates to sequences in the NCBI gene bank database soil type clearly modified these effects. ranged between 94 and 100% with the exception of isolates As expected, differences in shoot and root biomass identified as Microbacterium paraoxydans (57-15C) and were observed among the crop species (Table 8) and Pseudomonas baetica (24-14A) whose identities were 85% these also were influenced by experiment. At the end of (Table 9). the experiment, alfalfa had produced the greatest Of the total 69 DPB isolates identified, about one-third amount of root biomass in both experiments. The great- (23 isolates) were isolated from the canola leachates (Fig. 1) est shoot biomass was observed in alfalfa in experiment and were mostly from the phyla Firmicutes.Noisolatesin 1and in canola in experiment 2. Among the crop species, the Bacteroides phyla were identified from alfalfa leachates, shoot dry weight was related to root dry weight only ex- while few members in the Bacteroides phyla were isolated periment 1 with Pearson R ranging from 0.52 to 0.74 (p from wheat leachate. The number of Proteobacteria isolates value = < 0.001 to 0.0001). At the last sampling date, dry was the same among all the treatments, whereas the lowest weights were related to TCDPB (Pearson R = 0.51, p number of Actinobacteria was isolated from the UC and value = 0.0016 for shoot; Pearson R = 0.67, p value < soybean leachates. Leachates from experiment 1 using soil 0.0001 for root) and TCFU (Pearson R = 0.70, p value < A contained mostly Firmicutes and proteobacteria,withthe 0.0001 for shoot; Pearson R = 0.80, p value < 0.0001 for canola treatment culturing only Firmicutes, while alfalfa root) in experiment 1. In experiment 2, neither shoot leachates contained the lowest number of Proteobacteria. nor root biomass was related to any of the soil bacterial Theidentitystructureof the isolates was different in response variables further confirming observations above experiment 2 using soil B, where Firmicutes were only that crop species-specific factors other than plant cultured from canola and UC leachates with the Table 8 RLD at different sampling dates and biomass components at the end of experimental runs expressed on per plant basis Experiment 1 (soil A) Experiment 2 (soil B) Sampling date Sampling date * * * * * * 1 (49) 2 (63) 3 (92) 1 (32) 2 (59) 3 (89) Crop RLD SBPP RBPP RLD SBPP RBPP b a a a a b b a c a Alfalfa 0.83 1.05 1.12 3.96 4.40 0.36 0.52 2.03 2.06 1.75 b b a bc b a a b ab a Canola 0.78 0.70 1.03 1.96 0.80 0.87 1.30 1.24 2.72 1.93 a b a b b a a b bc b Soybean 1.16 0.71 0.89 2.37 0.88 0.94 1.22 1.16 2.34 0.93 b c b c b a b c a b Wheat 0.73 0.33 0.54 1.64 1.02 0.67 0.51 0.43 3.11 1.00 SEM 0.097 0.089 0.097 0.181 0.278 0.116 0.113 0.147 0.197 0.211 P value 0.027 0.0004 0.001 < .0001 0.0002 0.003 < .0001 < .0001 0.011 0.012 Days after planting Abbreviations: RLD root length density, SBPP shoot biomass per plant, RBPP root biomass per plant Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05. P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 10 of 18 Table 9 Identified DPB isolates from leachates grown with different crops using partial 16S rRNA sequences b d Phylum DPB Isolate Genus Species Identity GenBank Closest NCBI GenBank Treatment Exp ID (%) database match Accession no. (Accession no.) Actinobacteria (20%) 49-15SL Microbacterium M. azadirachtae 97 LC177121.1 MN294656 Soil 2 50-15SL M. azadirachtae 100 MH489019.1 MN294657 Soil 2 52-15A M. azadirachtae 98 MH489019.1 MN294659 Alfalfa 2 53-15A M. azadirachtae 98 MH489019.1 MN294660 Alfalfa 2 66-15SY M. azadirachtae 99 MH489019.1 MN294673 Soybean 2 70-15SY M. azadirachtae 97 MH489019.1 MN294677 Soybean 2 71-15W M. azadirachtae 97 MH489019.2 MN294678 Wheat 2 58-15C M. foliorum 99 CP041040.1 MN294665 Canola 2 73-15W M. foliorum 97 KF803585.1 MN294680 Wheat 2 74-15W M. foliorum 99 MG195155.1 MN294681 Wheat 2 51-15A M. oxydans 97 MF767919.1 MN294658 Alfalfa 2 55-15A M. oxydans 99 MF767919.1 MN294662 Alfalfa 2 56-15C M. oxydans 99 MF767919.1 MN294663 Canola 2 57-15C M. paraoxydans 85 KX280770.1 MN294664 Canola 2 Bacteroidetes (12%) 62-15C Chryseobacterium C. lathyri 99 KU924001.1 MN294669 Canola 2 67-15SY C. oranimense 99 NR_044168.1 MN294674 Soybean 2 68-15SY C. oranimense 96 NR_044168.1 MN294675 Soybean 2 72-15W C. oranimense 98 NR_044168.1 MN294679 Wheat 2 48-15SL C. taihuense 95 KT719933.1 MN294655 Soil 2 69-15SY Flavobacterium F. ginsengiterrae 96 NR_132661.1 MN294676 Soybean 2 65-15C Nubsella N. zeaxanthinifaciens 98 NR_114146.1 MN294672 Canola 2 46-15SL N. zeaxanthinifaciens 96 NR_114146.1 MN294653 Soil 2 Firmicutes (54%) 5-14SY Bacillus B. cereus 97 MG205787.1 MN294616 Soybean 1 12-14W B. cereus 97 KU721999.1 MN294622 Wheat 1 14-14W B. cereus 99 MG205902.1 MN294623 Wheat 1 21-14A B. cereus 100 MN232174.1 MN294630 Alfalfa 1 22-14A B. cereus 98 KF725719.1 MN294631 Alfalfa 1 41-14C B. cereus 96 KX350001.1 MN294648 Canola 1 42-14C B. cereus 94 KF500919.1 MN294649 Canola 1 43-14C B. cereus 98 KJ473716.1 MN294650 Canola 1 44-14C B. cereus 99 MF988724.1 MN294651 Canola 1 59-15C B. muralis 99 EU977778.1 MN294666 Canola 3 1-14SY B. mycoides 97 KU160370.1 MN294613 Soybean 1 4-14SY B. mycoides 99 KU160370.1 MN294615 Soybean 1 9-14SY B. mycoides 97 KU160370.1 MN294619 Soybean 1 11-14W B. mycoides 97 MK217082.1 MN294621 Wheat 1 17-14W B. mycoides 94 CP020743.1 MN294626 Wheat 1 18-14W B. mycoides 100 KU160370.1 MN294627 Wheat 1 20-14A B. mycoides 100 MK883205.1 MN294629 Alfalfa 1 26-14A B. mycoides 100 KU160370.1 MN294634 Alfalfa 1 33-14C B. mycoides 95 KU160370.1 MN294640 Canola 1 34-14C B. mycoides 100 KJ528876.1 MN294641 Canola 1 36-14C B. mycoides 100 KU160370.1 MN294643 Canola 1 37-14C B. mycoides 100 KU160370.1 MN294644 Canola 1 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 11 of 18 Table 9 Identified DPB isolates from leachates grown with different crops using partial 16S rRNA sequences (Continued) b d Phylum DPB Isolate Genus Species Identity GenBank Closest NCBI GenBank Treatment Exp ID (%) database match Accession no. (Accession no.) 39-14C B. mycoides 97 KU160370.1 MN294646 Canola 1 40-14C B. mycoides 99 KJ528876.1 MN294647 Canola 1 45-14C B. pumilus 96 MK491041.1 MN294652 Canola 1 32-14SL B. simplex 97 KX866680.1 MN294639 Soil 1 47-15SL B. simplex 98 FN435888.1 MN294654 Soil 2 60-15C B. simplex 96 FN435888.1 MN294667 Canola 2 61-15C B. simplex 97 KM817231.1 MN294668 Canola 2 16-14W B. thuringiensis 97 CP004870.1 MN294625 Wheat 1 19-14A B. thuringiensis 99 KX592862.1 MN294628 Alfalfa 1 25-14A B. thuringiensis 97 KU179338.1 MN294633 Alfalfa 1 38-14C B. thuringiensis 95 JF895480.1 MN294645 Canola 1 28-14SL Fictibacillus F. arsenicus 98 CP016761.1 MN294636 Soil 1 2-14SY Psychrobacillus P. psychrodurans 95 KC618486.1 MN294614 Soybean 1 27-14SL P. psychrodurans 95 KP334978.1 MN294635 Soil 1 35-14C P. soli 100 MH934924.1 MN294642 Canola 1 Proteobacteria (14%) 24-14A Pseudomonas P. baetica 85 KY963434.1 MN294632 Alfalfa 1 6-14SY P. fluorescens 99 CP015225.1 MN294617 Soybean 1 8-14SY P. moorei 96 FM955889.1 MN294618 Soybean 1 29-14SL P. mosselii 98 CP024159.1 MN294637 Soil 1 15-14W P. putida 96 KJ819580.1 MN294624 Wheat 1 10-14W Rheinheimera R. soli strain 99 KU597256.1 MN294620 Wheat 1 31-14SL Serratia S. fonticola 96 CP013913.1 MN294638 Soil 1 54-15A Stenotrophomonas S. maltophilia 96 MK641655.1 MN294661 Alfalfa 2 63-15C S. maltophilia 99 JN705917.1 MN294670 Canola 2 64-15C S. maltophilia 98 CP033829.1 MN294671 Canola 2 Proportions of Phyla groups DPB DNase-producing bacteria Percent identity match of sequence based on the NCBI database Experiment largest number cultured from canola leachates. ginsengiterrae was strongly distinct as indicated by a DNase-producing Proteobacteria were found only in bootstrap value of 71.1%. Moreover, the Firmicutes were alfalfa and canola leachates in experiment 2. Further- separated from the Actinobacteria and Proteobacteria more, Bacteroides were cultured from leachates of all moderately with a 55.5% bootstrap value, while the bac- treatments except from alfalfa leachates with the most terial species in the Actinobacteria phylum clustered cultured from soybean leachates and the least cul- tightly together with a strong bootstrap value of 99.9%. tured from wheat leachates. DNase-producing Actino- Within the Proteobacteria phylum, bacterial species bacteria were cultured from all leachates; however, seemed to have some variation from each other with the their numbers were greatest in alfalfa leachates. These Pseudomonas genus separating more from the other spe- results further support the observations in this study cies in this phylum than the different genera in the other that soil type is an important factor in shaping the phylum groups. At the same time, the Strenotrophomo- soil bacterial community. nas species clustered tightly together with a 100% boot- On clustering the DPB isolates using the maximum strap value. likelihood method, all isolates clustered close to their re- spective phyla groups (Fig. 2). The Bacteroides group Putative exDNase/nuclease-encoding genes clustered separately from all other bacterial groups, and When the genomes for the sequenced bacterial isolates this was strongly supported by the high bootstrap value in the IMG/M database were queried, a total of 9 pos- of 100%. Among the Bacteroides cluster, Flavobacterium sible secreted exDNases/nucleases were identified Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 12 of 18 The crop species and developmental stage strongly in- fluenced the TBL and DPB in leachates from the growth room study. The results observed in this study suggest that crop species exert specific selection pressures to the soil total bacterial population and DPB in the form of soil nutrient depletion and species-specific compounds released by plant roots which change the proportion of the selected bacterial groups during the crop’s develop- mental stages. This observation is well documented in other studies (Miethling et al. 2000; Smalla et al. 2001; Dunfield and Germida 2003; Costa et al. 2006; Berg and Smalla 2009; Hartmann et al. 2009). In contrast to our Fig. 1 The number of culturable DNase-producing bacteria isolates results, an indoor study using transgenic poplars grow- within each Phyla group identified from two experiments using ing on loamy sand over a duration of 26 months did not different soils (a and b) growing four different crop species and observe shifts in the proportion of the culturable DPB unplanted control (UC) based on partial 16S rRNA gene sequences (Balestrazzi et al. 2007). In addition, they did observe higher proportions of DPB (62.5 to 100%) in bulk soils (Additional file 1: Table S1). These enzymes included associated with poplar, whereas the current study re- TatD-related DNase (COG0084/KOG3020/pfam01026), ports an overall lower proportion of DPB (5.72 to Deoxyribonuclease NucA/NucB (pfam14040), Staphylo- 40.01%) from leachates. It is important to bear in mind coccal nuclease homologue (pfam00565), Bacterial EndoU that poplars are woody tree species, while in the current nuclease (pfam14436), DNase/tRNase domain of colicin- study annual and herbaceous perennial crops species like bacteriocin (pfam12639), Endonuclease/Exonuclease/ were used thus a probable factor contributing to the dif- phosphatase family (pfam03372), endA-deoxyribonuclease ferences in the DPB populations observed. I (K01150), EndA-DNA-entry nuclease (K15051) and a The DPB constitute a large proportion (> 50%) of cul- predicted extracellular nuclease (K15051 (COG2374). A turable organisms in soil and aquatic environments total of five possibly secreted exDNases/nucleases were (Greaves and Wilson 1970; Maeda and Taga 1973, predicted in Bacillus mycoides (Table 10). Only the TatD- 1974). Furthermore, DPB have been reported in soils related DNase which was predicted to be localized in the grown to pasture grasses where they constituted up to cytoplasm did not possess a signal peptide nor predicted 42% of the total culturable isolates in the rhizosphere to be non-classically secreted whereas the colicin-like bac- and bulk soils that were preferentially stimulated de- teriocin DNase did not map to a specific location. pending on the species and age of the grasses (Greaves and Webley 1965) which agrees with our findings. The sampling strategy of leaching experimental pots used in Discussion the current study may have contributed to the lower In the present study, both culture-dependent and mo- proportions of DPB observed from those of previous lecular techniques were employed to quantify and iden- studies. Leaching of the soil may however present some tify DPB inhabiting soils planted to different agricultural advantages compared to using rhizosphere and bulk soils plant species in a greenhouse study. In addition, the because it is less destructive, covers a larger volume of TBL was enumerated on selective culture medium soil and integrates the effects from both the rhizosphere coupled with commonly used universal bacterial and bulk soils. primers. Soil bacteria that release DNases extracellularly It is also interesting to note that experiment 2 had are an important component in the chain for assessing lower proportions of %CDPB than experiment 1, and the avenues to mitigate the unintended effects of GMOs in UC in experiment 2 consistently cultured lower TCDPB the environment. Moreover, soil enzyme activities medi- and %CDPB than experiment 1. The possible explan- ated by soil microbes are important as they perform ation to this is that under high nutrient levels as in the beneficial ecosystem functions, and thus, understanding case of experiment 2 (soil B), the soil bacteria had less the dynamics of these microbes in the soil will help shed need to breakdown DNA as a nutrient source. Moreover, more light on the untargeted effects of evolving agro- this effect was masked in the presence of plants as they nomic practices. To the best of our knowledge, no stud- release extra nutrients that can be utilized by the mi- ies have reported DPB inhabiting soils cultivated to crobes. Under low nutrient levels in experiment 1 (soil annual and perennial crop species and more specifically A), bacteria use exDNase enzyme activity as an alternate in the Canadian prairie region, which accounts for most nutrient acquisition mechanism which progressively de- of the arable agricultural land in Canada. creases in the presence of plants. Degradation of exDNA Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 13 of 18 Fig. 2 Maximum likelihood tree showing relatedness of 70 DNase-producing bacterial isolates recovered from leachates based on partial 16S rRNA gene sequences. Bootstrap values are shown when > 50% based on 1000 replicates Table 10 Candidate exDNase/nuclease-encoding proteins in Bacillus mycoides a b IMG/M database annotation Uniprot entry Pfam SignalP NN scores Localization (score) TatD-related DNase A0A084ITC0 Pfam01026 No 0.058 Cytoplasmic (9.97) Endonuclease/Exonuclease/phosphatase family A0A0A0WPY9 Pfam03372 Yes 0.931 Cytoplasmic membrane (4.60) Deoxyribonuclease NucA/NucB A0A090YLN6 Pfam14040 Yes 0.500 Cytoplasmic membrane (9.81) Staphylococcal nuclease homologue (SNase) C2Y446 Pfam00565 No 0.941 Extracellular (10) DNase/tRNase domain of colicin-like bacteriocin A0A0B5S5U9 pfam12639 No 0.698 All locations (2.5) Protein families Neural network prediction of signal peptides Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 14 of 18 by microbial nucleases contributes large proportions of season were also observed in fields planted with soybean the daily requirement of N and P for microbial growth (Sugiyama et al. 2014). Thus, it seems the soil bacterial in pelagic environments (Jørgensen and Jacobsen 1996). population shifts more frequently under the influence of Other studies also have hypothesized that microbial extra- crop species in their surroundings and are highly transi- cellular nuclease activities are involved in scavenging for ent over time which we also observed. Canola and other nutrients such as C, N and P from their environment (Blum Brassica species are known to produce glucosinolates et al. 1997; Benedik and Strych 1998;Dell’Anno 2005;Bais through their root exudates which when hydrolyzed to et al. 2006; Levy-Booth et al. 2007; Nielsen et al. 2007;Ibá- isothiocyanates act as biofumigants that actively sup- ñez de Aldecoa et al. 2017). Studies supporting this sugges- press soil-borne pathogens consequently affecting the tion include those of Greaves et al. (1970) who reported composition of rhizosphere microbial communities that the production of nucleases in Cytophaga johnsonii (Rumberger and Marschner 2003; Smith et al. 2004; was greatest in low-nutrient media, Salikhova et al. (2000) Matthiessen and Kirkegaard 2006; Hansen et al. 2018). who observed an increase in the production of nuclease For example, soybean root colonization by arbuscular from Proteus mirabilis which exhibits both DNase and mycorrhizal fungi was reduced up to 30% when the pre- RNase activity when grown in low P conditions, Turk et al. ceding crop was canola in the rotation (Valetti et al. (1992) who reported that the rate of DNA decomposition 2016). Similarly, in our study, we did observe a suppress- was 10-fold greater in P-limiting compared with N-limiting ing effect of canola on the total bacterial biomass and marine environments and Mulcahy et al. (2010) who ob- DPB in experiment 1 using the low nutrient soil (A). served that Pseudomonas aeruginosa highly expressed Soil properties such as pH, nutrients, organic matter, exDNase under P-limiting conditions to restrict DNA and texture and structure are known to act singly or in com- use its constituents as a source of nutrients. bination to influence the structure and functions of soil Sampling date-specific effects of crops on soil bacteria microbes (Garbeva et al. 2004). According to Reese et al. were observed on both the culturable and the 16S rRNA (2018), the soil factor having the most dominant effect gene copies. We did not observe any particular trends on the soil microbes varies according to the environ- consistently among the crop species over the growing ment. For instance, some studies have reported a reduc- period; however, alfalfa and soybean plants seemed to tion in microbial biomass as a result of N application favour higher numbers of bacteria according to the cul- (Treseder 2008; Janssens et al. 2010; Ramirez et al. ture technique while canola plants suppressed the prolif- 2012), while others reported an increase (Frey et al. eration of culturable bacteria in experiment 1 (the lower 2004; Leff et al. 2015). Our present findings support the nutrient soil). Altogether these results imply that crops suggestion that soil factors influence microbes differ- have dynamic and temporal effects on soil bacterial pop- ently. Specifically, we observed that TCDPB and %CDPB ulations which are dependent on the growth stage, soil were higher in leachates from UC of experiment 1 than nutrient levels and the plant species. Both plant species in UC of experiment 2, which may be associated with and soil properties largely influence the structure and the lower pH of the soil used in the latter experiment functions of soil microbial communities as previously compared with the former. In addition, we also observed reviewed (Berg and Smalla 2009). The growing season that compared with the UC, the TCDPB of crops has previously been shown to influence the abundance planted in experiment 1 was either reduced or did not of microbes associated with canola roots when frag- change, whereas TCDPB of all crops grown in experi- ments of the 16S rRNA were analyzed on denaturing ment 2 were increased, suggesting that the differences in gradient gel electrophoresis (Smalla et al. 2001). Studies soil properties between the two soils imposed a strong by Dunfield and Germida (2003) revealed similar trends selective pressure in favour of the growth of DNase- where they observed seasonal variability in the microbial producing bacteria. Additionally, with less need to community using the fatty acid methyl ester (FAME) breakdown DNA in experiment using soil B, coupled profiles and community-level physiological profiles tech- with the absence of plants in the UC which eliminated niques on soils planted to genetically modified canola. microbial competition for nutrients, the DPB population Moreover, Germida et al. (1998) observed a plant- was reduced significantly. However, due to competition dependent effect on the diversity of rhizoplane bacteria in the presence of plants, DPB still needed to utilize associated with canola and wheat based on their FAME DNA as a source of nutrient hence their increased popu- profiles. Differences in the microbial community associ- lation in the crop treatments compared to the UC. ated with Arabidopsis shifted with the development Similarly, it is noteworthy that canola had reduced stage and were highly correlated with the root exudates, TCDPB and TCFU than the control treatment in experi- and the seedling microbiome were observed to be dis- ment 1, whereas the opposite was true in experiment 2. tinct from the other stages (Chaparro et al. 2014). The differences in pH between the two soils could have Changes in soil bacterial abundance over the growing been a possible contributing factor to these observed Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 15 of 18 differences. As canola is known to acidify the rhizosphere Out of the of 9 possible secreted exDNases/nucleases for P acquisition (Hedley et al. 1982), the already strongly identified in the genomes of bacterial isolates in the acidic environment in soil B could have presented an ad- present study, five of them were present in Bacillus vantage for its uptake by this plant creating a P-limiting mycoides. The prediction of signal peptides in endo- environment and hence the switch to the alternate mech- nuclease/exonuclease/phosphatase family and deoxyribo- anism of acquiring this nutrient by microbes. A more in- nuclease NucA/NucB indicate that they may translocate teresting observation was that although alfalfa did not do across the bacterial membrane (Petersen et al. 2011). well in experiment 2 (as reflected by lower root and shoot Moreover, tatD-related DNases, endonuclease/exonucle- biomass production in this experiment compared with ex- ase/phosphatases and deoxyribonuclease NucA/NucB, periment 1), a factor directly associated with the low pH have previously been shown to be important for viru- of soil B, the TBL count from alfalfa leachates was higher lence in some plant pathogens (Tran et al. 2016; Hawes in experiment 2 than in experiment 1 suggesting that the et al. 2016; Park et al. 2019). The staphylococcal nucle- plant-soil-microbe interaction is complex and not only a ase is a well-characterized nuclease from Staphylococcus function of plant biomass or species. The microbial popu- aureus, in which this enzyme is secreted to degrade lations were highly responsive to the presence of wheat extracellular nucleic acids (Kiedrowski et al. 2014). On and canola throughout the experiments as reflected by the the other hand, colicin-DNases are secreted nucleases shifts among sampling dates, while the least responses and have been observed to kill non-self-target cells and were observed in the presence of soybean and those in al- enhance survival under stress in E. coli (Yang 2011; falfa were intermediate. Sharma et al. 2019). In the current study, we isolated DNase-producing soil To the best of our knowledge, this is the first study bacteria belonging to Bacillus, Chryseobacterium, Fictiba- reporting Bacillus mycoides as an exDNase producer in cillus, Flavobacterium, Microbacterium, Nubsella, Pseudo- the soil. This observation may be of interest in under- monas, Psychrobacillus, Rheinheimera, Serratia and standing the documented plant growth promotion activ- Stenotrophomonas genera. This observation is in agree- ities by this bacterium which is abundant in the soil and ment with the findings of Farmer et al. (2014)who rhizosphere and endosphere of some plants (Neher et al. isolated soil DPB belonging to the Bacillus, Pseudo- 2009; Stefan et al. 2013; Bach et al. 2016; Ambrosini monas, Serratia and Strenotrophomonas genera; Bales- et al. 2016). trazzi et al. (2007) who isolated DPB belonging to the genera Bacillus, Microbacterium, Pseudomonas and Conclusion Stenotrophomonas and Aparna and Sarada (2012)who The results presented in this study show that plants have isolated several DPB belonging to Serratia genera. Al- influence on total culturable soil bacteria communities, though we only identified six Bacillus species (B. ce- and this influence is variable depending on the crop spe- reus, B. muralis, B. mycoides, B. pumilus, B. simplex cies, soil abiotic properties and the stage of development and B. thuringiensis) that produce exDNase, several of the plant. This observation is also true for culturable other Bacillus species have been reported to exhibit DNase-producing bacteria as we observed changes over extracellular nuclease activity including B. subtilis time in the proportions cultured by individual crop spe- (Akrigg and Mandelstam 1978;Morenoet al. 2012); B. cies during the development of the plant and also among licheniformis (Nijland et al. 2010); B. fusiformis, B. the species at the different sampling dates. In addition, megaterium, B. sphericus, B. brevis (Balestrazzi et al. our findings suggest that different soils exert variable se- 2007); and B. seohaeanensis, B. stratosphericus, B. lective pressure with potential to influence the compos- oceanisediminis, B. mojavensis (Moreno et al. 2012). A ition, structure and possibly the functions of microbes study by Al-Wahaibi et al. (2019)reportedthe Bacillus inhabiting them. Furthermore, we also observed a com- genera group to constitute the largest proportion of plex interaction between the crop species and soil type culturable exDNase-producing bacterial isolates from suggesting that crop performance may not be a good in- different marine habitats. However, their findings that dicator of microbial richness and diversity in the soil; Proteobacteria (57%) and Firmicutes (34%) dominated hence, the focus should be directed onto the specific culturable exDNase-producing bacterial isolates con- properties of the soil and crop with potential to exert se- trasts our results as the largest proportion belonged to lective pressure on to the resident microbial populations. Firmicutes (54%) while Actinobacteria were the second Moreover, this study provided evidence suggesting that largest group (20%). The results of these studies, to- there seems to be large numbers of soil bacteria that gether with ours, indicate that a large proportion of produce exDNase into their surroundings. In this study, culturable bacteria in the Bacillus group may be re- the DNase producers were identified as members of sponsible for extracellular nuclease activities in the eleven different genera with a majority of the isolates be- soil. longing to the Firmicutes. 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Curr Microbiol 42: 168–172. https://doi.org/10.1007/s002840010198 Ten LN, Liu QM, Im WT et al (2006) Pedobacter ginsengisoli sp. nov., a DNase- producing bacterium isolated from soil of a ginseng field in South Korea. Int J Syst Evol Microbiol 56:2565–2570. https://doi.org/10.1099/ijs.0.64414-0 Tran TM, MacIntyre A, Hawes M, Allen C (2016) Escaping underground nets: extracellular DNases degrade plant extracellular traps and contribute to http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Microbiology Springer Journals

The effect of crop species on DNase-producing bacteria in two soils

Annals of Microbiology , Volume 71 (1) – Mar 12, 2021

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Abstract

Purpose: Extracellular deoxyribonucleases (exDNases) from microbial origin contribute substantially to the restriction of extracellular DNA (exDNA) in the soil. Hence, it is imperative to understand the diversity of bacterial species capable of performing this important soil function and how crop species influence their dynamics in the soil. The present study investigates the occurrence of DNase-producing bacteria (DPB) in leachate samples obtained from soils in which the crop species of alfalfa (Medicago sativa L.), canola (Brassica napus L.), soybean (Glycine max [L.] Merr.) and wheat (Triticum aestivum L.) were raised in a growth room. Methods: Selective media containing methyl green indicator was used to screen for DPB from leachate samples, whereas the 16S rRNA sequence analysis was employed to identify the isolates. Results: The proportion of culturable DPB ranged between 5.72 and 40.01%; however, we did observe specific crop effects that shifted throughout the growing period. In general, higher proportions of exDNase producers were observed when the soils had lower nutrient levels. On using the 16S rRNA to classify the DPB isolates, most isolates were found to be members of the Bacillus genera, while other groups included Chryseobacterium, Fictibacillus, Flavobacterium, Microbacterium, Nubsella, Pseudomonas, Psychrobacillus, Rheinheimera, Serratia and Stenotrophomonas. Five candidate exDNase/nuclease-encoding proteins were also identified from Bacillus mycoides genomes using online databases. Conclusion: Results from this study showed that crop species, growth stage and soil properties were important factors shaping the populations of DPB in leachate samples; however, soil properties seemed to have a greater influence on the trends observed on these bacterial populations. It may be possible to target soil indigenous bacteria that produce exDNases through management to decrease potential unintended effects of transgenes originating from genetically modified organisms (GMOs) or other introduced nucleic acid sequences in the environment. Keywords: DNase-producing bacteria, exDNA, exDNAse(s), GMOs, Wheat, Canola, Soybean, Alfalfa Introduction plant species-specific microbial consortia (Berg and Plants and microbes are known to form complex and Smalla 2009; Hartmann et al. 2009). The structure and dynamic interactions within the soil matrix, and these functions of microbial communities in the soil are can have significant implications to the functioning of strongly influenced by the residing plant species (Burns the ecosystem (Hartmann et al. 2009). These series of et al. 2015). For instance, the microbial communities in complex interactions between the plant, microbes and the soil associated with wheat and canola differ substan- the soil environment result to increased microbial activ- tially (Hansen et al. 2019 Hansen et al. 2018; Lay et al. ity in the rhizosphere resulting to the selection of unique 2018). Because of the intimate association between plants and * Correspondence: Rob.Gulden@umanitoba.ca microbes, the release of genetically engineered (GE) Department of Plant Science, University of Manitoba, 222 Agriculture plants brought into question the ecological sustainability Building, 66 Dafoe Road, Winnipeg, MB R3T 2N2, Canada © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 2 of 18 of the technology due to the perceived non-targeted ef- extracellularly (Benedik and Strych 1998); however, stud- fects of transgenes to soil organisms such as natural ies have found that many bacterial species exude nucle- transformation of microbes through horizontal gene ases that are either anchored to the cell wall or exuded transfer mechanisms (HGT) (Tsatsakis et al. 2017). The into the growth medium (Eaves and Jeffries 1963; Nakai increased rhizosphere activity has also been documented et al. 1965; Rothberg and Swartz 1965; Greaves and for nuclease-producing microorganisms which could be Webley 1965; Jakubovics et al. 2013; Sheikh and Hos- exploited for transgenes mitigation in the environment. seini 2013). This makes it possible to detect exDNase ac- For instance, Greaves and Webley (1965) observed that tivities on agar plates containing indicators such as the total number of nuclease-producing microorganisms methyl green that are intercalated into the double helix were higher on the root surface and in the rhizosphere matrix, but become clear halos of enzyme activity soil of pasture grasses than in non-rhizosphere soil. The around the growing colonies as the double helix is being plethora of compounds secreted through the root cap degraded. mucilage including genetic material (Wen et al. 2009; The majority of studies on soil bacteria report single Knox et al. 2020; Ropitaux et al. 2020; Chambard et al. isolates that produce exDNases, whereas only a few 2021) provide a source of nutrients and energy that may studies have identified multiple isolates that produce result in differential growth of microbial communities exDNases. Pioneer studies on nuclease-producing bac- (Berg and Smalla 2009; Haichar et al. 2014). Plant DNA teria (Greaves et al. 1970) reported nuclease production enters the soil environment mainly through root exu- by Cytophaga johnsonii isolated from the soil which uti- dates, root cap sloughing, pollen dispersal and degrad- lized nucleic acids as a C and P source more efficiently ation of plant materials (Levy-Booth et al. 2007; than a N source. On the other hand, some bacterial spe- Monticolo et al. 2020). cies such as Escherichia coli, Serratia marcescens, Myxo- One major fate of extracellular DNA (exDNA) in the coccus virescens, Myxococcus fulvus and Chondrococcus soil environment is degradation by indigenous soil mi- coralloides can thrive solely on nucleic acids as a C crobial extracellular deoxyribonucleases (exDNases) into source for their growth (Norén 1955; Redfield 1993; smaller fragments resulting to the loss of genetic infor- Benedik and Strych 1998). For instance, the proliferation mation (Blum et al. 1997; Levy-Booth et al. 2007; Niel- of a marine thriving Vibrio sp. increased up to 4 orders sen et al. 2007; Ibáñez de Aldecoa et al. 2017). The of magnitude in the presence of DNA, with rapid micro- presence of these restriction enzymes therefore serves as bial assimilation of a significant proportion of the deg- barriers to exDNA introgression into native soil bacteria radation products (Maeda and Taga 1974). Ten et al. through HGT (Dodd and Pemberton 1999; Wu et al. (2006) isolated and characterized a novel DNase- 2001) and its subsequent long-term persistence in the producing isolate Pedobacter ginsengisoli sp. nov. be- soil environment (Kunadiya et al. 2021). For instance, longing to the Bacteroidetes phyla from field soils grow- Stewart and Sinigalliano (1990) reported a decrease in ing ginseng (Panax ginseng) in South Korea. Strong natural transformation frequency in bacteria after incu- exDNase activity was also observed in Frankia strains bating marine and artificial sediments with DNase 1. Mi- which are known to form symbiotic relationships with crobial exDNases contribute to soil functions and have many dicot plant species (Tavares and Sellstedt 1997). largely been associated with nutrient scavenging activ- Extracellular DNase production has been reported in ities (Benedik and Strych 1998; Desai and Shankar 2003; several marine bacterial isolates with the majority be- Levy-Booth et al. 2007; Ibáñez de Aldecoa et al. 2017) longing to the genera Bacillus (Al-Wahaibi et al. 2019; and virulence of pathogens (Park et al. 2019; Monticolo Asha and Krishnaveni 2020). Moreover, several soil bac- et al. 2020). For example, an increase of up to 35-fold in terial isolates belonging to different phyla groups were viable bacterial counts was observed 3 days after spiking observed to express exDNases whose activities were soils with nucleic acids, thereby implying that microbes mostly optimal at neutral pH and at temperatures be- use nucleic acids as substrates for growth (Greaves and tween 30 and 40 °C (Kamble et al. 2011). Greaves and Wilson 1970). Blum et al. (1997) also observed an in- Wilson (1970) also recorded large numbers of DPB from crease in the number of soil microbes 12 h after inject- different soil types growing grassy vegetation with vary- ing DNA into soils, with rapid degradation occurring to ing proportions of DPBs at 17% in kaolinite, 86% in the unbound DNA spike. montmorillonite, 58% in peat and 47% in sandy soils. In Some bacteria and fungi closely associated with plant an indoor study carried out by Balestrazzi et al. (2007) roots have been reported to exhibit exDNase activities using transgenic white poplars with the bar gene insert, (Greaves and Webley 1965; Bertagnolli et al. 1996; 62.5 to 100% of the total culturable bacterial populations Tavares and Sellstedt 2001; Klosterman et al. 2001; were observed to express exDNase activities. Moreover, Balestrazzi et al. 2007). It was thought that only a limited bacterial isolates cultured and identified as DNase pro- number of bacterial species produce nucleases ducers in their study belonged to five genera: Bacillus, Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 3 of 18 Brevibacillus, Microbacterium, Pseudomonas and Table 1 Parameters of the two soils used in this study Stenotrophomonas. Soil ID To date, no study has described DPB inhabiting agri- Parameters Soil A Soil B cultural soils nor has the effect of crop species on DPB −1 N, kg ha 77.6 172.4 been investigated. Thus, the current study was carried −1 S, kg ha 19.1 23.6 out to quantify and identify bacterial species that express −1 P, kg ha 31.4 56.0 DNase activity extracellularly in soils collected from an −1 K, kg ha 412.0 555.5 agricultural field planted to different crops. Since micro- −1 Mg, kg ha 788.0 822.1 bial exDNase activity is an important soil function and −1 can contribute significantly to ecosystem services such Ca, kg ha 4664.0 4715.2 as hindering the dissemination of transgenes in the en- −1 Na, kg ha 51.5 71.7 vironment, understanding the diversity of exDNase- −1 Zn, kg ha 4.9 11.3 releasing bacteria in the soil and how different crop spe- −1 Fe, kg ha 126.8 297.9 cies affect this diversity is important. To add on that, −1 Mn, kg ha 12.1 88.7 exDNase activity was used as a model function in the −1 B, kg ha 1.1 1.3 current study to understand how crop species and soil type influence soil functions which are mediated by soil pH 6.3 5.1 microbes and may be indirectly or directly affected by Cation exchange capacity (CEC), meq 13.9 19.9 management practices employed and/or new techno- Organic matter (OM), % 3.3 4.3 logical advances in agriculture. We hypothesized that a Sand, % 76.0 72.0 number of key DNase-producing bacteria inhabiting Silt, % 11.0 15.0 agricultural soils would be identified. Clay, % 13.0 13.0 Materials and methods Leaching study carbathiin) while the alfalfa seeds were scarified briefly Prior to the study, soils were collected at two different using an electric seed scarifier (Westinghouse Electric locations (A and B) within the University of Manitoba’s Corp AC Motor 317P044, USA). Ian N. Morrison Research Farm in Carman, MB, Canada Shortly after emergence, the pots were thinned to (49° 29′ 48″ N, 98° 2′ 26″ W, 267 m above sea level). three seedlings per pot which were watered as required Chemical and physical properties of these soils were de- from here on. Three weeks post emergence, pots were termined at a commercial laboratory (Agvise Laborator- fertilized with nitrogen-phosphorus-potassium (20:20:20) −1 ies Inc., Northwood, ND, USA). The soil parameters are at the rate of 5 g L of water. The plants were main- shown in Table 1, and the major difference between the tained at 25/20 °C and 16/8 h day/night at a relative hu- soils was macronutrients (N, P, K), micronutrients (Zn, midity of 75% throughout the study. To prevent water Fe, Mn) and pH. The experiments conducted in this from preferentially flowing between the soil and the pot study included a preliminary experimental run with soil during treatment leaching, at the time of seeding, the A to develop the methods and a full experiment with soil surface was shaped into a deep concave in each pot soil A and one with soil B. All experiments were con- to facilitate leaching through the soil profile and leach- ducted in the growth room in a randomized complete ing was done at least monthly with 200 mL of distilled block design. Six replicates each of four crop species, in- H O. The first 30 mL of the leachate from each pot were cluding, wheat (Triticum aestivum L.), canola (Brassica collected in 50 mL falcon tubes placed on ice during napus L.), alfalfa (Medicago sativa L.) and soybean (Gly- leaching to minimize enzymatic degradation of DNA by cine max [L.] Merr.) were used in the study. Unplanted enzymes with further analyses, and DNA purification pots were included as controls. Plants were grown in performed immediately after sampling. The crops’ devel- 1.5-L (10.5 cm diameter, 38 cm height) transparent, opmental stages at the time of leaching are shown in inverted plastic bottles each covered with aluminium foil Table 2. Coinciding with monthly leaching, the alumin- to exclude light and having a 2-cm diameter hole in ium foil was removed temporarily and a 5 × 5 cm square their bottoms. Two layers of fiberglass mesh (0.2 mm) grid with 1-cm grid gradations printed on transparent were placed at the bottom of each pot followed by 150 plastic sheets was placed on the exterior of each pot. mL of industrial quartz. One litre mixture of industrial The number of root-grid line intersections was counted −1 quartz and soil (1:1, v/v) fertilized with 40 kg N ha in in each square to determine root length density (RLD). the form of urea was added to the pots, and before At the end of the experiment, shoot and root dry matter planting, the canola seeds were treated with fungicide were determined for each plant after drying to equilib- (trifloxystrobin, metalaxyl) and insecticide (clothianidin, rium at 55 °C. Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 4 of 18 Table 2 Developmental stages of the four crops at different times of leaching during experimental runs Experiment 1 (soil A) Experiment 2 (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) Alfalfa early veg. Mid veg. Early budding Flowering 7th trifoliate Mid veg. Early budding Canola 4 leaf stage 5 leaf stage Flowering Phys. maturity 3 leaf stage 5 leaf stage Flowering Soybean Flowering Flowering Phys. maturity – 5th trifoliate Flowering Phys. maturity Wheat Bolting Heading Phys. maturity – Tillering Heading Phys. maturity Abbreviations: veg vegetative, phys physiological *Days after planting Screening for DNase activity Scientific, Ottawa, ON, Canada), 1 μL (10 pmol) of each of One milliliter of aliquot of each leachate sample was the universal primers 27F/1492R (Suzuki and Giovannoni transferred into a 2-mL centrifuge tube and each leach- 1996), 0.75 μL 100% dimethyl sulphoxide (DMSO), 2.5 μL ate was 10-fold serially diluted. A 100 μL aliquot of the of DNA and 7.25 μL distilled autoclaved water. The qPCR −3 10 dilution was plated onto two replicate plates con- conditions were initial denaturation for 30 s at 98 °C, TM taining the Difco DNase Test Agar with methyl green followed by 30 cycles of denaturation for 10 s at 98 °C, an- as a substrate for DNase enzyme activity (DGM nealing for 30 s at 55 °C, extension at 72 °C for 30 s and a medium, Becton, Dickinson and Company Sparks, USA) final extension step at 72 °C for 10 min. The two replicate prepared according to the manufacturer’s instructions. samples of the qPCR products were pooled and verified on Plates were incubated at 25 °C, and 48 h after plating, 1% agarose gel, and thereafter, the qPCR products were total culturable DNase-producing bacteria (TCDPB) and sent to Macrogen (Rockville, Maryland, USA) for Sanger all the total colony-forming units (TCFU) with and with- sequencing using the universal primers used in this study. out DNA degradation halos were enumerated and used to estimate the proportion of culturable DNase- Genomic DNA extraction from leachates producing bacteria (%CDPB). Finally, single DNase- Total DNA was extracted from each leachate sample forming colonies were picked randomly from the treat- using the PowerSoil® total DNA isolation kit (MoBio, La- ments and sub-cultured on DGM medium to obtain boratories, Solana Beach, CA, USA) with adjustments single isolated colonies for identification purposes. made to adapt the manufacturer’s protocol to our ex- periment. Briefly, 10 mL aliquot of each leachate was pi- Bacterial DNA extraction petted into a 50-mL centrifuge tube and centrifuged at Genomic DNA of bacterial single colonies were ex- 5000g for 30 min at 4 °C to recover DNA and bacterial tracted using the InstaGene Matrix (IM) (Bio-Rad, cells from the leachates. The pellets were washed with Mississauga, ON, Canada), according to the manufac- cold 70% ethanol and centrifuged at 5000g for 10 min at turer’s protocol. In brief, picked isolated single colonies 4 °C followed by drying and resuspension in 1.5 mL of were suspended in 1 mL of distilled autoclaved water sterile Milli Q H O. The rest of the protocol followed and vortexed briefly before centrifuging at 15,294×g for the manufacturer’s instructions except for the solution 1 min. The resulting pellet was suspended in 200 μLof volumes which were optimized for leachate samples (500 InstaGene Matrix and incubated at 37 °C for 15 min μL bead solution buffer, 15 μL C1 solution, 100 μLC2 using a water bath. Samples were vortexed at high speed solution and 50 μL C3 solution per extraction). DNA for 10 s and placed in a 100 °C water bath for 8 min was eluted from the column with 100 μL of Milli Q after which samples were vortexed for 10 s at high speed H O. The quantity and purity of DNA was assessed on a and centrifuged for 3 min at 15,294×g. DNA quantity microplate spectrophotometer (Epoch Biotek, Winooski, and quality were assessed using a microplate spectro- VT, USA) at 260 and 280 nm. photometer (Epoch Biotek, Winooski, VT, USA) and samples were stored in the freezer at − 20 °C until fur- Quantitative real-time PCR amplifications (qPCR) ther analyses. Quantitative PCR for total bacterial load (TBL) was per- formed on DNA from leachate samples using a Bio-Rad Target amplification for sequencing CFX Real-time system (Bio-Rad, Hercules, CA, USA). Amplification of the partial 16S rRNA gene in DNA The amplifications were performed in two replicates on from bacterial single colonies was done in two replicate 96-well reaction plates (Bio-Rad, Hercules, CA, USA) reactions in a total volume of 25 μL containing 12.5 μL with a final volume of 20 μL reaction mixture containing of the 2x Phusion High Fidelity PCR Master Mix (Fisher 10 μL iTaq SYBR Green Supermix (Bio-Rad, Hercules, Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 5 of 18 CA, USA), 0.5 μL (10 pmol) of each of the eubacterial Statistical analyses primers 338F/518R (Fierer et al. 2005), 1 μL of genomic The SAS package 9.4 (SAS Institute, Inc., Cary, NC, DNA and 8 μL of distilled autoclaved water. The qPCR USA) was used to conduct analysis of variance amplification conditions were 3 min at 95 °C followed (ANOVA) using the mixed procedure. The preliminary by 35 cycles of 20 s at 95 °C, 20 s at 53 °C and 20 s at 72 experimental run with soil A which had fewer and in- °C. Following qPCR, a melt curve analysis was conducted compatible harvest dates was not included in this final with a temperature gradient from 65 to 95 °C in 0.5 °C analysis. Fixed factors in the ANOVA model were crop, increments for 5 s per cycle with continuous fluores- sampling date, experiment and their interactions. The cence monitoring performed after amplification to con- replication blocks nested within experimental run were firm amplification specificity to the target product. considered random. To satisfy the normality assump- Purified DNA products amplified from soil DNA using tions, log or square root transformations were applied to similar primers were pooled and 10-fold serially diluted the dataset and normality of residuals was examined by seven times to construct a standard curve to quantify using the Shapiro-Wilk test in the univariate procedure. the target DNA and evaluate primer efficiency. In addition, Lund’s test (Lund 1975) was used to identify and inspect potentially influential outliers, while the Akaike’s information criterion was used to examine and Phylogenetic analyses correct (when necessary) the homogeneity of variance Nucleotide sequences were examined and edited using prior to final data analysis. Following this, the REPEAT the Chromas software package (www.technelysium.com. ED statement was used to correct for heterogeneity of au) after which the forward and reverse strands of the variance among treatments when necessary. Fisher’s Pro- partial 16S rRNA sequences were aligned using the tected LSD (α = 0.05) difference was used to compare ClustalW multiple alignment option in the BioEdit pro- treatment means using the pdmix800 macro (Saxton gram (Hall 1999). The GenBank databases were used to 1998). The method=type3 option was used to determine determine close phylogenetic associations using the the partitioning of variance based on estimated type 3 Basic Local Alignment Tool (BLAST) at the National sums squares To determine co-linearity among the re- Center for Biotechnology Information (http://www-ncbi- sponse variables, correlation analysis was used. This ana- nlm-nih-gov.uml.idm.oclc.org). The BioEdit program lysis was conducted within experiment and sampling was used to assemble and align all sequences while max- dates to minimize confounding effects with date and imum likelihood phylogenetic analyses were conducted soil-specific effects. using the Kimura 2-parameter (K2P) model (Kimura 1980). The final tree was constructed from 1000 boot- Results for total culturable DNase-producing strap replicates in MEGA v7.0.18 (Kumar et al. 2016) bacteria (TCDPB), proportion of culturable DNase- after which edits were made using FigTree v1.4.3 (http:// producing bacteria (%CDPB), total colony-forming tree.bio.ed.ac.uk/software/figtree/). The partial 16S units (TCFU) and total bacterial load (TBL) rRNA nucleotide sequences of the isolates were depos- Experiment was the most important factor influencing ited in the GeneBank database under the accession num- the interpretation of the results among the bacterial re- bers (MN294613 to MN294681) (Table 9). sponse variables in these experiments. The behaviour of the response variables between the two experiments was Identification of putative exDNase/nuclease-encoding often quite different. As these response variables were genes determined from leachate samples, it was not unex- Bacterial genomes from the IMG/M database (Marko- pected that experiment played a major role in the parti- witz et al. 2012) were searched for genes encoding pos- tioning of variance components as soil physical and sible secreted DNases/nucleases. The protein sequences chemical properties can affect leachate composition and encoding the identified candidate exDNases/nucleases some of these parameters were different between the genes in Bacillus mycoides were retrieved from UNI- two soils used in this study (Table 1). Leachate samples PROT protein database (Apweiler et al. 2004). Finally, to were used in these experiments for several reasons. First, identify candidate secreted DNases/nucleases, the candi- they are non-destructive and allow for repeat sampling date proteins from Bacillus mycoides were screened for of the same experimental unit; second, they are integra- secretion signals using SignalP (Petersen et al. 2011) and tive over the entire volume of soil for each experimental SecretomeP (Bendtsen et al. 2004) which generate non- unit, and third, an exDNA disappearance assay (manu- classical neural network (NN) secretion scores for non- script in preparation) was developed which was more re- classical secreted proteins, whereas PSORTb 3.0.2 liable on leachate samples than soil samples, and these (http://www.psort.org/psortb/index.html) (Yu et al. experiments contributed to understanding the exDNA 2010) was used to predict the subcellular location. dynamics in leachate water and the effects of crop Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 6 of 18 species, sampling date and soil type on this process. In lowest TCDPB concentrations were observed in the can- the combined analyses, a relatively small, but significant ola leachates. Similar trends were also observed in the portion of the variance was partitioned to the plant spe- preliminary experiment (data not shown), and we are cies and sampling date effects. therefore relatively confident the observed differences All main effects except one and all but two interac- between the experiments were influenced strongly by tions were statistically significant among all bacterial re- soil type. In contrast, a different response was observed sponse variables (Table 3). The relative contribution of in experiment 2 with soil B where canola leachates con- sampling date and its interactions to total variation rela- tained greater densities of TCDPB compared with the tive to the crop species effect was not the same among UC at all sampling dates, while TCDPB in alfalfa, soy- the response variables. In specific, effects including sam- bean and wheat leachates were similar at most sampling pling date consumed less variation than all crop species dates except at 89 dap where the number of TCDPB effects in TCDPB and TCFU, whereas the opposite was were lower in soybean leachates than in alfalfa leachates. observed for %CDPB and 16S rRNA-based TBL. Overall, At 89 dap, soybean were at physiological maturity while the experimental factors and their interactions explained alfalfa was still at anthesis; thus, the difference in plant 53–71% of the total variation in these experiments indi- maturity was a probable factor contributing to the differ- cating a significant amount of unexplained variation in ence observed. TCDPB (43%), %CDPB (48%) and TBL (36%) suggesting The sampling date response (which signify plant devel- high variability in these measurements or that critical opment) in TCDPB was also unique to experiment, and factors that affect these bacterial parameters were not interestingly, this effect was most prominent in experi- included in the experiment. When analyzing TCDPB ment 1 and particularly in the alfalfa, canola and UC within each experiment, crop species was the main leachates. In canola leachates from experiment 1, a pro- source of variation in both experiments consuming 28% gressive increase in the population density of TCDPB and 36% of the total variation. Additionally, date was the was observed as this species developed and matured. On main source of variation in both experiments for TBL the other hand, a decrease in TCDPB occurred at the explaining about 16% and 42% of total variation in ex- mid-vegetative developmental stages in alfalfa leachates, periments 1 and 2, respectively. The same degree and while in the UC leachates, lower TCDPB were observed consistency of variance partitioning to crop species and at the first sampling date. Sampling date or its inter- sampling date within experiments was not observed in action with crop species had no effect on TCDPB in ex- the other bacterial response variables; however, either periment 2 with soil B. While similar in texture, soil B was significant depending on the experiment (data not was more nutrient rich, particularly in N and some of shown). This shift in variance partitioning when ana- the micronutrients, than soil A (Table 1). Soil B also had lyzed within experiments clearly showed the importance a lower pH, and a higher CEC and OM content than soil of crop species and sampling date on bacterial response A which likely contributed to the soil-specific observa- variables. tions. The nutrient profile of each soil was only assessed In experiment 1 with soil A, the number of TCDPB in at the beginning of each experiment. leachates from alfalfa and soybean were equal to or Culturable DNase-producing bacteria (%CDPB) expressed greater than TCDPB in leachates from the unplanted as a proportion of the TCFU ranged from 5.7 to 40.0% control (UC) (Table 4). The number of TCDPB in wheat among treatments in these experiments (Table 5). While the leachates was mostly intermediate, while generally the maximum proportions of %CDPB were similar between the Table 3 Percentage of total variance contributed by experimental factors and their interactions on measured bacterial parameters a a a a Source TCDPB P value %CDPB P value TCFU P value TBL P value Crop 7.66 < .0001 3.74 0.023 7.95 < .0001 2.86 0.022 Date 7.47 < .0001 10.78 < .0001 16.88 < .0001 22.68 < .0001 Crop x date 9.24 0.001 3.55 0.359 11.82 < .0001 5.03 0.030 Experiment 0.30 0.313 16.37 < .0001 10.99 < .0001 7.45 < .0001 Crop x experiment 21.24 < .0001 5.50 0.003 15.91 < .0001 8.22 < .0001 Date x experiment 0.22 0.693 2.91 0.012 2.33 0.003 10.21 < .0001 Crop x date x experiment 10.43 < .0001 9.65 0.001 5.43 0.001 8.09 0.0002 Error 43.44 – 47.5 – 28.69 – 35.46 – Column values are the proportions (%) of the variance component explained by the factor Abbreviations: TCDPB total culturable DNase-producing bacteria, %CDPB proportion of culturable DNase-producing bacteria, TCFU total colony-forming units, TBL total bacteria load Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 7 of 18 Table 4 Effect of crop species on TCDPB expressed in log CFU per mL of leachate during experimental runs TCDPB in experiment 1 TCDPB in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) c,B a,A a,AB a,A c b c UC 4.96 5.40 5.28 5.65 4.90 4.84 4.98 a,A ab,B a,B ab,A b a ab Alfalfa 5.70 5.20 5.35 5.54 5.13 5.36 5.46 d,C c,BC ab,AB b,A a a a Canola 4.42 4.79 5.12 5.33 5.49 5.42 5.53 ab ab a ab a c Soybean 5.41 5.35 5.53 – 5.36 5.38 4.99 bc b b ab ab bc Wheat 5.22 5.19 4.73 – 5.36 5.13 5.16 SEM 0.104 0.073 0.167 0.081 0.084 0.137 0.106 P value < .0001 < .0001 0.020 0.042 0.001 0.029 0.005 Days after planting Abbreviations: UC unplanted control, TCDPB total culturable DNase-producing bacteria Mean separation done for each sampling date within each experiment a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05. A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 experiments (40% and 36% in experiment 1 and 2, respect- Moreover, canola leachates consistently had greater %CDPB ively), the lowest %CDPB was 10% lower in experiment 2 than the UC at all sampling dates in this experiment. The than experiment 1 which again, is indicative of soil-specific %CDPB of all other crop species were similar to UC in ex- bacterial population dynamics. Generally, the effect of crop periment 2 except at 59 dap where alfalfa and soybean species was less consistent in this response variable as differ- leachates had greater %CDPB. ences among treatments were observed at all sampling dates Despite the observed differences in TCDPB and only in experiment 2. In experiment 1, alfalfa and wheat %CDPB among the experimental treatments, TCDPB leachates had the greatest %CDPB at the earlier sampling and TCFU were correlated at each sampling date in both times. Also, differences among treatments in %CDPB were experiments. The Pearson R values ranged from 0.57 to only observed at 63 dap and in particular, %CDPB in alfalfa, 0.94 (p value < 0.001). The relationship between TCFU, were about half of those observed in the UC. This was the culturable portion, and TBL based on 16S rRNA caused principally by lower TCDPB in the alfalfa treatment copy number was less clear. In experiment 2 and most (Table 4). In experiment 2, on the other hand, planted treat- sampling dates of experiment 1, no correlations were ments resulted in %CDPB that were quadruple those of the found between these bacterial measures. However, posi- UC at 59 dap (Table 5), which was probably caused by lower tive correlations between TCFU and TBL were observed TCDPB and TCFU in the UC treatment (Tables 4 and 6). at 63 dap (Pearson R = 0.40, p value = 0.0001) and 92 Table 5 Effect of crop species on %CDPB during experimental runs % CDPB in experiment 1 % CDPB in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) ab ab a a b,AB c,B bc,A UC 30.16 29.12 30.81 31.87 14.12 5.72 17.33 a,A c,C a,AB a,BC b a abc Alfalfa 40.01 15.47 29.05 22.17 15.27 20.67 25.19 b a a a a,A a,B a,A Canola 29.37 34.21 30.55 23.72 29.70 15.63 35.97 ab ab a ab ab c Soybean 36.29 28.31 31.42 – 21.09 14.40 14.14 ab,A bc,B a,B ab,A bc,B ab,A Wheat 38.29 18.09 21.53 – 20.26 9.88 29.00 SEM 0.308 0.393 0.505 0.372 0.372 0.261 0.477 P value 0.145 0.009 0.644 0.129 0.020 0.0001 0.022 Days after planting Abbreviations: UC unplanted control, %CDPB proportion of culturable DNase-producing bacteria Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05 A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 8 of 18 Table 6 Effect of crop species on TCFU expressed in log per milliliter of leachate during experimental runs TCFU in experiment 1 TCFU in experiment 2 (soil A) (soil B) Sampling date Sampling date * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) c,C a,AB ab,B a,A b,B a,A bc,B UC 5.49 5.97 5.80 6.15 5.78 6.10 5.77 a,AB a,BC ab,C a,A ab a a Alfalfa 6.10 6.02 5.89 6.21 5.96 6.05 6.09 d,D b,C bc,B b,A a,B a,A ab,B Canola 4.96 5.26 5.68 5.97 6.02 6.24 5.98 ab a a a a bc Soybean 5.86 5.91 6.04 – 6.04 6.23 5.85 bc,B a,A c,B a,A a,A c,B Wheat 5.64 5.95 5.43 – 6.07 6.15 5.71 SEM 0.085 0.053 0.107 0.052 0.068 0.141 0.079 P value < .0001 < .0001 < .0001 0.015 0.055 0.825 0.011 Days after planting Abbreviations: UC unplanted control, TCFU total colony-forming units Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05 A,B,C Means with different letters between columns indicate statistical differences between sampling dates at P < 0.05 P values in bold indicate statistical significance at P < 0.05 dap (Pearson R = 0.56, p value < 0.0001) in experiment 1 TBL, on the other hand, decreased in alfalfa at the (data not shown). These results not only indicate soil- last sampling date in both experiments. The same specific microbial dynamics, but as expected, also an trend was observed for most other plant species as important temporal component to soil microbial commu- well, where TBL was lowest at the last sampling date nity dynamics. Furthermore, these findings also highlight in experiment 2, and for canola in experiment 1. Dif- the differences between culturable and unculturable tech- ferences among treatments within sampling date were niques for bacterial studies. sporadic and inconsistent. In many cases, the ob- In experiment 1, the range in TCDPB and TCFU served differences were less than 10-fold and there- (Tables 4 and 6) among the treatments diminished fore likely of limited biological significance. over the duration of the experiments showing a clear trend in the temporal dynamics in these response var- Shoot and root growth iables. More specific, the largest differences (greater Root length density measurements are a non-destructive than 10-fold among treatments) were observed at 49 two-dimensional method for estimating the density of dap in experiment 1, and by the end of the experi- ments, this range in differences diminished to about Table 7 Effect of crop species on TBL using 16S rRNA gene copies expressed in log per mL of leachate during 0.32 and 0.24 log units for TCDPB and TCFU, re- 10 experimental runs spectively. The same was not observed in experiment TBL in experiment 1 TBL in experiment 2 2where therange in thedifferenceamong crop spe- (soil A) (soil B) cies was more consistent throughout the development Sampling date Sampling date of the plants (0.55–0.59 log units in TCDPB and * * * * * * * Crop 1 (49) 2 (63) 3 (92) 4 (126) 1 (32) 2 (59) 3 (89) 0.19–0.39 log units in TCFU). Differences among a,AB a,A b,C a,BC a b a UC 6.93 7.19 6.66 6.86 7.27 6.76 6.68 treatments were less common for TCFU in experi- a,A ab,A b,AB ab,B a,A a,A a,B ment 2 and TBL in experiment 1 (Tables 6 and 7). Alfalfa 6.84 6.83 6.64 6.43 7.61 7.59 6.51 Nevertheless, a few plant species-specific trends were a,A b,A ab,A b,B a,A a,A a,B Canola 6.86 6.54 6.70 5.96 7.52 7.68 6.80 observed in these response variables, particularly in a ab a a,A b,A b,B Soybean 6.91 6.96 6.94 – 7.65 7.13 5.65 experiment 1. For example, canola consistently had a,B a,A ab,B a,A a,A a,B Wheat 6.73 7.09 6.70 – 7.75 7.71 7.04 the lowest TCFU densities at each sampling date in SEM 0.076 0.160 0.089 0.205 0.172 0.153 0.254 experiment 1 and the concentration increased at each P value 0.333 0.049 0.157 0.047 0.372 0.002 0.013 subsequent sampling date in this species. In experi- ment 2, TCFU in canola leachates were not different *Days after planting Abbreviations: UC unplanted control, TBL total bacteria load from those in the other crop species and the greatest Mean separation done for each sampling date within each experimental run a,b,c bacterial densities were observed at 59 dap. In experi- Means with different letters within columns indicate statistical differences between treatments at P < 0.05 ment 1, alfalfa had among the highest TCFU dens- A,B,C Means with different letters between columns indicate statistical ities, but these were lower during the mid-vegetative differences between sampling dates at P < 0.05 stages and increased again at the final sampling date. P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 9 of 18 root proliferation in a volume of soil. In experiment 1, biomass are more important at influencing soil microbial no relationship between RLD and soil bacterial response function. variables were found, whereas in experiment 2, root length density correlated with TCFU at all sampling DNase-producing bacterial isolates dates (Pearson R = 0.39 to 0.42, p values 0.0008 to Some of the DPB were isolated and picked for identification 0.0027). At 32 dap in experiment 2, RLD also was corre- using Sanger sequencing. Bacterial isolates identified in the lated with %CDPB (Pearson R = 0.49, p value < 0.0001) current study were classified into four phyla groups includ- and TBL (Pearson R = 0.38, p value = 0.003), and at 59 ing the Firmicutes (37 isolates), Actinobacteria (14 isolates), dap, RLD was correlated positively with TCDPB (Pear- Proteobacteria (10 isolates) and Bacteroides (8 isolates) with son R = 0.39, p value = 0.0019) and negatively with TBL a total of 11 genera groups (Table 9). The genera groups of (Pearson R = − 0.40, p value = 0.0014). Moreover, at the DPB isolates identified in this study included Bacillus, later sampling dates in experiment 1, RLD correlated Chryseobacterium, Fictibacillus, Flavobacterium, Microbac- well with per plant shoot and per plant root biomass terium, Nubsella, Pseudomonas, Psychrobacillus, Rheinhei- (Pearson R = 0.46–0.72, p value < 0.0001). These results mera, Serratia and Stenotrophomonas.The largest indicate that root length density alone may not be as im- proportion of culturable DPB (54%) was identified as Firmi- portant as other crop species-specific effects for the ob- cutes with 6 different Bacillus species. Theidentityof the served treatment differences among the crop species and DPB isolates to sequences in the NCBI gene bank database soil type clearly modified these effects. ranged between 94 and 100% with the exception of isolates As expected, differences in shoot and root biomass identified as Microbacterium paraoxydans (57-15C) and were observed among the crop species (Table 8) and Pseudomonas baetica (24-14A) whose identities were 85% these also were influenced by experiment. At the end of (Table 9). the experiment, alfalfa had produced the greatest Of the total 69 DPB isolates identified, about one-third amount of root biomass in both experiments. The great- (23 isolates) were isolated from the canola leachates (Fig. 1) est shoot biomass was observed in alfalfa in experiment and were mostly from the phyla Firmicutes.Noisolatesin 1and in canola in experiment 2. Among the crop species, the Bacteroides phyla were identified from alfalfa leachates, shoot dry weight was related to root dry weight only ex- while few members in the Bacteroides phyla were isolated periment 1 with Pearson R ranging from 0.52 to 0.74 (p from wheat leachate. The number of Proteobacteria isolates value = < 0.001 to 0.0001). At the last sampling date, dry was the same among all the treatments, whereas the lowest weights were related to TCDPB (Pearson R = 0.51, p number of Actinobacteria was isolated from the UC and value = 0.0016 for shoot; Pearson R = 0.67, p value < soybean leachates. Leachates from experiment 1 using soil 0.0001 for root) and TCFU (Pearson R = 0.70, p value < A contained mostly Firmicutes and proteobacteria,withthe 0.0001 for shoot; Pearson R = 0.80, p value < 0.0001 for canola treatment culturing only Firmicutes, while alfalfa root) in experiment 1. In experiment 2, neither shoot leachates contained the lowest number of Proteobacteria. nor root biomass was related to any of the soil bacterial Theidentitystructureof the isolates was different in response variables further confirming observations above experiment 2 using soil B, where Firmicutes were only that crop species-specific factors other than plant cultured from canola and UC leachates with the Table 8 RLD at different sampling dates and biomass components at the end of experimental runs expressed on per plant basis Experiment 1 (soil A) Experiment 2 (soil B) Sampling date Sampling date * * * * * * 1 (49) 2 (63) 3 (92) 1 (32) 2 (59) 3 (89) Crop RLD SBPP RBPP RLD SBPP RBPP b a a a a b b a c a Alfalfa 0.83 1.05 1.12 3.96 4.40 0.36 0.52 2.03 2.06 1.75 b b a bc b a a b ab a Canola 0.78 0.70 1.03 1.96 0.80 0.87 1.30 1.24 2.72 1.93 a b a b b a a b bc b Soybean 1.16 0.71 0.89 2.37 0.88 0.94 1.22 1.16 2.34 0.93 b c b c b a b c a b Wheat 0.73 0.33 0.54 1.64 1.02 0.67 0.51 0.43 3.11 1.00 SEM 0.097 0.089 0.097 0.181 0.278 0.116 0.113 0.147 0.197 0.211 P value 0.027 0.0004 0.001 < .0001 0.0002 0.003 < .0001 < .0001 0.011 0.012 Days after planting Abbreviations: RLD root length density, SBPP shoot biomass per plant, RBPP root biomass per plant Mean separation done for each sampling date within each experimental run a,b,c Means with different letters within columns indicate statistical differences between treatments at P < 0.05. P values in bold indicate statistical significance at P < 0.05 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 10 of 18 Table 9 Identified DPB isolates from leachates grown with different crops using partial 16S rRNA sequences b d Phylum DPB Isolate Genus Species Identity GenBank Closest NCBI GenBank Treatment Exp ID (%) database match Accession no. (Accession no.) Actinobacteria (20%) 49-15SL Microbacterium M. azadirachtae 97 LC177121.1 MN294656 Soil 2 50-15SL M. azadirachtae 100 MH489019.1 MN294657 Soil 2 52-15A M. azadirachtae 98 MH489019.1 MN294659 Alfalfa 2 53-15A M. azadirachtae 98 MH489019.1 MN294660 Alfalfa 2 66-15SY M. azadirachtae 99 MH489019.1 MN294673 Soybean 2 70-15SY M. azadirachtae 97 MH489019.1 MN294677 Soybean 2 71-15W M. azadirachtae 97 MH489019.2 MN294678 Wheat 2 58-15C M. foliorum 99 CP041040.1 MN294665 Canola 2 73-15W M. foliorum 97 KF803585.1 MN294680 Wheat 2 74-15W M. foliorum 99 MG195155.1 MN294681 Wheat 2 51-15A M. oxydans 97 MF767919.1 MN294658 Alfalfa 2 55-15A M. oxydans 99 MF767919.1 MN294662 Alfalfa 2 56-15C M. oxydans 99 MF767919.1 MN294663 Canola 2 57-15C M. paraoxydans 85 KX280770.1 MN294664 Canola 2 Bacteroidetes (12%) 62-15C Chryseobacterium C. lathyri 99 KU924001.1 MN294669 Canola 2 67-15SY C. oranimense 99 NR_044168.1 MN294674 Soybean 2 68-15SY C. oranimense 96 NR_044168.1 MN294675 Soybean 2 72-15W C. oranimense 98 NR_044168.1 MN294679 Wheat 2 48-15SL C. taihuense 95 KT719933.1 MN294655 Soil 2 69-15SY Flavobacterium F. ginsengiterrae 96 NR_132661.1 MN294676 Soybean 2 65-15C Nubsella N. zeaxanthinifaciens 98 NR_114146.1 MN294672 Canola 2 46-15SL N. zeaxanthinifaciens 96 NR_114146.1 MN294653 Soil 2 Firmicutes (54%) 5-14SY Bacillus B. cereus 97 MG205787.1 MN294616 Soybean 1 12-14W B. cereus 97 KU721999.1 MN294622 Wheat 1 14-14W B. cereus 99 MG205902.1 MN294623 Wheat 1 21-14A B. cereus 100 MN232174.1 MN294630 Alfalfa 1 22-14A B. cereus 98 KF725719.1 MN294631 Alfalfa 1 41-14C B. cereus 96 KX350001.1 MN294648 Canola 1 42-14C B. cereus 94 KF500919.1 MN294649 Canola 1 43-14C B. cereus 98 KJ473716.1 MN294650 Canola 1 44-14C B. cereus 99 MF988724.1 MN294651 Canola 1 59-15C B. muralis 99 EU977778.1 MN294666 Canola 3 1-14SY B. mycoides 97 KU160370.1 MN294613 Soybean 1 4-14SY B. mycoides 99 KU160370.1 MN294615 Soybean 1 9-14SY B. mycoides 97 KU160370.1 MN294619 Soybean 1 11-14W B. mycoides 97 MK217082.1 MN294621 Wheat 1 17-14W B. mycoides 94 CP020743.1 MN294626 Wheat 1 18-14W B. mycoides 100 KU160370.1 MN294627 Wheat 1 20-14A B. mycoides 100 MK883205.1 MN294629 Alfalfa 1 26-14A B. mycoides 100 KU160370.1 MN294634 Alfalfa 1 33-14C B. mycoides 95 KU160370.1 MN294640 Canola 1 34-14C B. mycoides 100 KJ528876.1 MN294641 Canola 1 36-14C B. mycoides 100 KU160370.1 MN294643 Canola 1 37-14C B. mycoides 100 KU160370.1 MN294644 Canola 1 Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 11 of 18 Table 9 Identified DPB isolates from leachates grown with different crops using partial 16S rRNA sequences (Continued) b d Phylum DPB Isolate Genus Species Identity GenBank Closest NCBI GenBank Treatment Exp ID (%) database match Accession no. (Accession no.) 39-14C B. mycoides 97 KU160370.1 MN294646 Canola 1 40-14C B. mycoides 99 KJ528876.1 MN294647 Canola 1 45-14C B. pumilus 96 MK491041.1 MN294652 Canola 1 32-14SL B. simplex 97 KX866680.1 MN294639 Soil 1 47-15SL B. simplex 98 FN435888.1 MN294654 Soil 2 60-15C B. simplex 96 FN435888.1 MN294667 Canola 2 61-15C B. simplex 97 KM817231.1 MN294668 Canola 2 16-14W B. thuringiensis 97 CP004870.1 MN294625 Wheat 1 19-14A B. thuringiensis 99 KX592862.1 MN294628 Alfalfa 1 25-14A B. thuringiensis 97 KU179338.1 MN294633 Alfalfa 1 38-14C B. thuringiensis 95 JF895480.1 MN294645 Canola 1 28-14SL Fictibacillus F. arsenicus 98 CP016761.1 MN294636 Soil 1 2-14SY Psychrobacillus P. psychrodurans 95 KC618486.1 MN294614 Soybean 1 27-14SL P. psychrodurans 95 KP334978.1 MN294635 Soil 1 35-14C P. soli 100 MH934924.1 MN294642 Canola 1 Proteobacteria (14%) 24-14A Pseudomonas P. baetica 85 KY963434.1 MN294632 Alfalfa 1 6-14SY P. fluorescens 99 CP015225.1 MN294617 Soybean 1 8-14SY P. moorei 96 FM955889.1 MN294618 Soybean 1 29-14SL P. mosselii 98 CP024159.1 MN294637 Soil 1 15-14W P. putida 96 KJ819580.1 MN294624 Wheat 1 10-14W Rheinheimera R. soli strain 99 KU597256.1 MN294620 Wheat 1 31-14SL Serratia S. fonticola 96 CP013913.1 MN294638 Soil 1 54-15A Stenotrophomonas S. maltophilia 96 MK641655.1 MN294661 Alfalfa 2 63-15C S. maltophilia 99 JN705917.1 MN294670 Canola 2 64-15C S. maltophilia 98 CP033829.1 MN294671 Canola 2 Proportions of Phyla groups DPB DNase-producing bacteria Percent identity match of sequence based on the NCBI database Experiment largest number cultured from canola leachates. ginsengiterrae was strongly distinct as indicated by a DNase-producing Proteobacteria were found only in bootstrap value of 71.1%. Moreover, the Firmicutes were alfalfa and canola leachates in experiment 2. Further- separated from the Actinobacteria and Proteobacteria more, Bacteroides were cultured from leachates of all moderately with a 55.5% bootstrap value, while the bac- treatments except from alfalfa leachates with the most terial species in the Actinobacteria phylum clustered cultured from soybean leachates and the least cul- tightly together with a strong bootstrap value of 99.9%. tured from wheat leachates. DNase-producing Actino- Within the Proteobacteria phylum, bacterial species bacteria were cultured from all leachates; however, seemed to have some variation from each other with the their numbers were greatest in alfalfa leachates. These Pseudomonas genus separating more from the other spe- results further support the observations in this study cies in this phylum than the different genera in the other that soil type is an important factor in shaping the phylum groups. At the same time, the Strenotrophomo- soil bacterial community. nas species clustered tightly together with a 100% boot- On clustering the DPB isolates using the maximum strap value. likelihood method, all isolates clustered close to their re- spective phyla groups (Fig. 2). The Bacteroides group Putative exDNase/nuclease-encoding genes clustered separately from all other bacterial groups, and When the genomes for the sequenced bacterial isolates this was strongly supported by the high bootstrap value in the IMG/M database were queried, a total of 9 pos- of 100%. Among the Bacteroides cluster, Flavobacterium sible secreted exDNases/nucleases were identified Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 12 of 18 The crop species and developmental stage strongly in- fluenced the TBL and DPB in leachates from the growth room study. The results observed in this study suggest that crop species exert specific selection pressures to the soil total bacterial population and DPB in the form of soil nutrient depletion and species-specific compounds released by plant roots which change the proportion of the selected bacterial groups during the crop’s develop- mental stages. This observation is well documented in other studies (Miethling et al. 2000; Smalla et al. 2001; Dunfield and Germida 2003; Costa et al. 2006; Berg and Smalla 2009; Hartmann et al. 2009). In contrast to our Fig. 1 The number of culturable DNase-producing bacteria isolates results, an indoor study using transgenic poplars grow- within each Phyla group identified from two experiments using ing on loamy sand over a duration of 26 months did not different soils (a and b) growing four different crop species and observe shifts in the proportion of the culturable DPB unplanted control (UC) based on partial 16S rRNA gene sequences (Balestrazzi et al. 2007). In addition, they did observe higher proportions of DPB (62.5 to 100%) in bulk soils (Additional file 1: Table S1). These enzymes included associated with poplar, whereas the current study re- TatD-related DNase (COG0084/KOG3020/pfam01026), ports an overall lower proportion of DPB (5.72 to Deoxyribonuclease NucA/NucB (pfam14040), Staphylo- 40.01%) from leachates. It is important to bear in mind coccal nuclease homologue (pfam00565), Bacterial EndoU that poplars are woody tree species, while in the current nuclease (pfam14436), DNase/tRNase domain of colicin- study annual and herbaceous perennial crops species like bacteriocin (pfam12639), Endonuclease/Exonuclease/ were used thus a probable factor contributing to the dif- phosphatase family (pfam03372), endA-deoxyribonuclease ferences in the DPB populations observed. I (K01150), EndA-DNA-entry nuclease (K15051) and a The DPB constitute a large proportion (> 50%) of cul- predicted extracellular nuclease (K15051 (COG2374). A turable organisms in soil and aquatic environments total of five possibly secreted exDNases/nucleases were (Greaves and Wilson 1970; Maeda and Taga 1973, predicted in Bacillus mycoides (Table 10). Only the TatD- 1974). Furthermore, DPB have been reported in soils related DNase which was predicted to be localized in the grown to pasture grasses where they constituted up to cytoplasm did not possess a signal peptide nor predicted 42% of the total culturable isolates in the rhizosphere to be non-classically secreted whereas the colicin-like bac- and bulk soils that were preferentially stimulated de- teriocin DNase did not map to a specific location. pending on the species and age of the grasses (Greaves and Webley 1965) which agrees with our findings. The sampling strategy of leaching experimental pots used in Discussion the current study may have contributed to the lower In the present study, both culture-dependent and mo- proportions of DPB observed from those of previous lecular techniques were employed to quantify and iden- studies. Leaching of the soil may however present some tify DPB inhabiting soils planted to different agricultural advantages compared to using rhizosphere and bulk soils plant species in a greenhouse study. In addition, the because it is less destructive, covers a larger volume of TBL was enumerated on selective culture medium soil and integrates the effects from both the rhizosphere coupled with commonly used universal bacterial and bulk soils. primers. Soil bacteria that release DNases extracellularly It is also interesting to note that experiment 2 had are an important component in the chain for assessing lower proportions of %CDPB than experiment 1, and the avenues to mitigate the unintended effects of GMOs in UC in experiment 2 consistently cultured lower TCDPB the environment. Moreover, soil enzyme activities medi- and %CDPB than experiment 1. The possible explan- ated by soil microbes are important as they perform ation to this is that under high nutrient levels as in the beneficial ecosystem functions, and thus, understanding case of experiment 2 (soil B), the soil bacteria had less the dynamics of these microbes in the soil will help shed need to breakdown DNA as a nutrient source. Moreover, more light on the untargeted effects of evolving agro- this effect was masked in the presence of plants as they nomic practices. To the best of our knowledge, no stud- release extra nutrients that can be utilized by the mi- ies have reported DPB inhabiting soils cultivated to crobes. Under low nutrient levels in experiment 1 (soil annual and perennial crop species and more specifically A), bacteria use exDNase enzyme activity as an alternate in the Canadian prairie region, which accounts for most nutrient acquisition mechanism which progressively de- of the arable agricultural land in Canada. creases in the presence of plants. Degradation of exDNA Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 13 of 18 Fig. 2 Maximum likelihood tree showing relatedness of 70 DNase-producing bacterial isolates recovered from leachates based on partial 16S rRNA gene sequences. Bootstrap values are shown when > 50% based on 1000 replicates Table 10 Candidate exDNase/nuclease-encoding proteins in Bacillus mycoides a b IMG/M database annotation Uniprot entry Pfam SignalP NN scores Localization (score) TatD-related DNase A0A084ITC0 Pfam01026 No 0.058 Cytoplasmic (9.97) Endonuclease/Exonuclease/phosphatase family A0A0A0WPY9 Pfam03372 Yes 0.931 Cytoplasmic membrane (4.60) Deoxyribonuclease NucA/NucB A0A090YLN6 Pfam14040 Yes 0.500 Cytoplasmic membrane (9.81) Staphylococcal nuclease homologue (SNase) C2Y446 Pfam00565 No 0.941 Extracellular (10) DNase/tRNase domain of colicin-like bacteriocin A0A0B5S5U9 pfam12639 No 0.698 All locations (2.5) Protein families Neural network prediction of signal peptides Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 14 of 18 by microbial nucleases contributes large proportions of season were also observed in fields planted with soybean the daily requirement of N and P for microbial growth (Sugiyama et al. 2014). Thus, it seems the soil bacterial in pelagic environments (Jørgensen and Jacobsen 1996). population shifts more frequently under the influence of Other studies also have hypothesized that microbial extra- crop species in their surroundings and are highly transi- cellular nuclease activities are involved in scavenging for ent over time which we also observed. Canola and other nutrients such as C, N and P from their environment (Blum Brassica species are known to produce glucosinolates et al. 1997; Benedik and Strych 1998;Dell’Anno 2005;Bais through their root exudates which when hydrolyzed to et al. 2006; Levy-Booth et al. 2007; Nielsen et al. 2007;Ibá- isothiocyanates act as biofumigants that actively sup- ñez de Aldecoa et al. 2017). Studies supporting this sugges- press soil-borne pathogens consequently affecting the tion include those of Greaves et al. (1970) who reported composition of rhizosphere microbial communities that the production of nucleases in Cytophaga johnsonii (Rumberger and Marschner 2003; Smith et al. 2004; was greatest in low-nutrient media, Salikhova et al. (2000) Matthiessen and Kirkegaard 2006; Hansen et al. 2018). who observed an increase in the production of nuclease For example, soybean root colonization by arbuscular from Proteus mirabilis which exhibits both DNase and mycorrhizal fungi was reduced up to 30% when the pre- RNase activity when grown in low P conditions, Turk et al. ceding crop was canola in the rotation (Valetti et al. (1992) who reported that the rate of DNA decomposition 2016). Similarly, in our study, we did observe a suppress- was 10-fold greater in P-limiting compared with N-limiting ing effect of canola on the total bacterial biomass and marine environments and Mulcahy et al. (2010) who ob- DPB in experiment 1 using the low nutrient soil (A). served that Pseudomonas aeruginosa highly expressed Soil properties such as pH, nutrients, organic matter, exDNase under P-limiting conditions to restrict DNA and texture and structure are known to act singly or in com- use its constituents as a source of nutrients. bination to influence the structure and functions of soil Sampling date-specific effects of crops on soil bacteria microbes (Garbeva et al. 2004). According to Reese et al. were observed on both the culturable and the 16S rRNA (2018), the soil factor having the most dominant effect gene copies. We did not observe any particular trends on the soil microbes varies according to the environ- consistently among the crop species over the growing ment. For instance, some studies have reported a reduc- period; however, alfalfa and soybean plants seemed to tion in microbial biomass as a result of N application favour higher numbers of bacteria according to the cul- (Treseder 2008; Janssens et al. 2010; Ramirez et al. ture technique while canola plants suppressed the prolif- 2012), while others reported an increase (Frey et al. eration of culturable bacteria in experiment 1 (the lower 2004; Leff et al. 2015). Our present findings support the nutrient soil). Altogether these results imply that crops suggestion that soil factors influence microbes differ- have dynamic and temporal effects on soil bacterial pop- ently. Specifically, we observed that TCDPB and %CDPB ulations which are dependent on the growth stage, soil were higher in leachates from UC of experiment 1 than nutrient levels and the plant species. Both plant species in UC of experiment 2, which may be associated with and soil properties largely influence the structure and the lower pH of the soil used in the latter experiment functions of soil microbial communities as previously compared with the former. In addition, we also observed reviewed (Berg and Smalla 2009). The growing season that compared with the UC, the TCDPB of crops has previously been shown to influence the abundance planted in experiment 1 was either reduced or did not of microbes associated with canola roots when frag- change, whereas TCDPB of all crops grown in experi- ments of the 16S rRNA were analyzed on denaturing ment 2 were increased, suggesting that the differences in gradient gel electrophoresis (Smalla et al. 2001). Studies soil properties between the two soils imposed a strong by Dunfield and Germida (2003) revealed similar trends selective pressure in favour of the growth of DNase- where they observed seasonal variability in the microbial producing bacteria. Additionally, with less need to community using the fatty acid methyl ester (FAME) breakdown DNA in experiment using soil B, coupled profiles and community-level physiological profiles tech- with the absence of plants in the UC which eliminated niques on soils planted to genetically modified canola. microbial competition for nutrients, the DPB population Moreover, Germida et al. (1998) observed a plant- was reduced significantly. However, due to competition dependent effect on the diversity of rhizoplane bacteria in the presence of plants, DPB still needed to utilize associated with canola and wheat based on their FAME DNA as a source of nutrient hence their increased popu- profiles. Differences in the microbial community associ- lation in the crop treatments compared to the UC. ated with Arabidopsis shifted with the development Similarly, it is noteworthy that canola had reduced stage and were highly correlated with the root exudates, TCDPB and TCFU than the control treatment in experi- and the seedling microbiome were observed to be dis- ment 1, whereas the opposite was true in experiment 2. tinct from the other stages (Chaparro et al. 2014). The differences in pH between the two soils could have Changes in soil bacterial abundance over the growing been a possible contributing factor to these observed Kamino and Gulden Annals of Microbiology (2021) 71:14 Page 15 of 18 differences. As canola is known to acidify the rhizosphere Out of the of 9 possible secreted exDNases/nucleases for P acquisition (Hedley et al. 1982), the already strongly identified in the genomes of bacterial isolates in the acidic environment in soil B could have presented an ad- present study, five of them were present in Bacillus vantage for its uptake by this plant creating a P-limiting mycoides. The prediction of signal peptides in endo- environment and hence the switch to the alternate mech- nuclease/exonuclease/phosphatase family and deoxyribo- anism of acquiring this nutrient by microbes. A more in- nuclease NucA/NucB indicate that they may translocate teresting observation was that although alfalfa did not do across the bacterial membrane (Petersen et al. 2011). well in experiment 2 (as reflected by lower root and shoot Moreover, tatD-related DNases, endonuclease/exonucle- biomass production in this experiment compared with ex- ase/phosphatases and deoxyribonuclease NucA/NucB, periment 1), a factor directly associated with the low pH have previously been shown to be important for viru- of soil B, the TBL count from alfalfa leachates was higher lence in some plant pathogens (Tran et al. 2016; Hawes in experiment 2 than in experiment 1 suggesting that the et al. 2016; Park et al. 2019). The staphylococcal nucle- plant-soil-microbe interaction is complex and not only a ase is a well-characterized nuclease from Staphylococcus function of plant biomass or species. The microbial popu- aureus, in which this enzyme is secreted to degrade lations were highly responsive to the presence of wheat extracellular nucleic acids (Kiedrowski et al. 2014). On and canola throughout the experiments as reflected by the the other hand, colicin-DNases are secreted nucleases shifts among sampling dates, while the least responses and have been observed to kill non-self-target cells and were observed in the presence of soybean and those in al- enhance survival under stress in E. coli (Yang 2011; falfa were intermediate. Sharma et al. 2019). In the current study, we isolated DNase-producing soil To the best of our knowledge, this is the first study bacteria belonging to Bacillus, Chryseobacterium, Fictiba- reporting Bacillus mycoides as an exDNase producer in cillus, Flavobacterium, Microbacterium, Nubsella, Pseudo- the soil. This observation may be of interest in under- monas, Psychrobacillus, Rheinheimera, Serratia and standing the documented plant growth promotion activ- Stenotrophomonas genera. This observation is in agree- ities by this bacterium which is abundant in the soil and ment with the findings of Farmer et al. (2014)who rhizosphere and endosphere of some plants (Neher et al. isolated soil DPB belonging to the Bacillus, Pseudo- 2009; Stefan et al. 2013; Bach et al. 2016; Ambrosini monas, Serratia and Strenotrophomonas genera; Bales- et al. 2016). trazzi et al. (2007) who isolated DPB belonging to the genera Bacillus, Microbacterium, Pseudomonas and Conclusion Stenotrophomonas and Aparna and Sarada (2012)who The results presented in this study show that plants have isolated several DPB belonging to Serratia genera. Al- influence on total culturable soil bacteria communities, though we only identified six Bacillus species (B. ce- and this influence is variable depending on the crop spe- reus, B. muralis, B. mycoides, B. pumilus, B. simplex cies, soil abiotic properties and the stage of development and B. thuringiensis) that produce exDNase, several of the plant. This observation is also true for culturable other Bacillus species have been reported to exhibit DNase-producing bacteria as we observed changes over extracellular nuclease activity including B. subtilis time in the proportions cultured by individual crop spe- (Akrigg and Mandelstam 1978;Morenoet al. 2012); B. cies during the development of the plant and also among licheniformis (Nijland et al. 2010); B. fusiformis, B. the species at the different sampling dates. In addition, megaterium, B. sphericus, B. brevis (Balestrazzi et al. our findings suggest that different soils exert variable se- 2007); and B. seohaeanensis, B. stratosphericus, B. lective pressure with potential to influence the compos- oceanisediminis, B. mojavensis (Moreno et al. 2012). A ition, structure and possibly the functions of microbes study by Al-Wahaibi et al. (2019)reportedthe Bacillus inhabiting them. Furthermore, we also observed a com- genera group to constitute the largest proportion of plex interaction between the crop species and soil type culturable exDNase-producing bacterial isolates from suggesting that crop performance may not be a good in- different marine habitats. However, their findings that dicator of microbial richness and diversity in the soil; Proteobacteria (57%) and Firmicutes (34%) dominated hence, the focus should be directed onto the specific culturable exDNase-producing bacterial isolates con- properties of the soil and crop with potential to exert se- trasts our results as the largest proportion belonged to lective pressure on to the resident microbial populations. Firmicutes (54%) while Actinobacteria were the second Moreover, this study provided evidence suggesting that largest group (20%). The results of these studies, to- there seems to be large numbers of soil bacteria that gether with ours, indicate that a large proportion of produce exDNase into their surroundings. In this study, culturable bacteria in the Bacillus group may be re- the DNase producers were identified as members of sponsible for extracellular nuclease activities in the eleven different genera with a majority of the isolates be- soil. longing to the Firmicutes. 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