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Research Article
Open Access Peer-reviewed

Effect of Jhum Cycles on Acidobacteria and Burkholderia Community in the Rhizosphere of Mixed Crops of Different Jhum Fields

Alarisa Khyllep , Dwipendra Thakuria, Mamtaj S. Dkhar
Applied Ecology and Environmental Sciences. 2021, 9(11), 919-930. DOI: 10.12691/aees-9-11-2
Received September 17, 2021; Revised October 22, 2021; Accepted November 01, 2021

Abstract

In the present study, culture-dependent and independent [Denaturing gradient gel electrophoresis (DGGE)] approach were used to analyze the effect of fallow cycle on bacterial populations associated with mixed crops selected from three different jhum fallow cycles (5-, 10- and 20- years) of Changki village, Nagaland. Two important bacterial phyla viz. Acidobacteria and Burkholderia were selected for DGGE analysis. According to the DGGE banding profile, Acidobacteria showed more richness compared Burkholderia. The presence and absence of few of the bands in the profile indicate the community shifts in the selected jhum fields. Shannon diversity index was higher in Acidobacteria than Burkholderia. Multivariate analysis showed that Acidobacteria community structure was similar among the crop plants of the same fallow cycle. Burkholderia community did not show clear separation among fallow cycles although crop of same fallow cycle tend to group together. ANOSIM and PERMANOVA showed significant differences in rhizosphere community pattern among fallow cycles and the crop plants of same fallow cycles indicated that both fallow cycle and crop plants are factors determining the Acidobacteria and Burkholderia community composition in jhum soils which was also confirmed by the culture-dependent analysis. Culturable bacterial counts were dependent on media used and significantly different at different fallow cycles. Bacterial communities (both culturable and DGGE patterns) were correlated with soil nutrients suggesting their importance in stability of jhum soil. The present study revealed that both fallow cycle and host plant may be the key factors in shaping many bacterial communities in jhum soils.

1. Introduction

Jhum or shifting cultivation is a traditional form of agriculture in which a piece of land or forest is cleared through slashing and then burning of dried biomass, cultivated for a short period of time, then leaving the land abandoned (fallow) allowing the soil to restore its fertility, while the cultivator moves on to another plot. The nutrients lost during cultivation are approximately replaced during fallowing period 1. The process of shifting cultivation from slashing to burning has shown to have detrimental effects on soil properties and on the diversity and abundance of different microbial populations in the soil. Microbial diversity of soil is important to sustainable agriculture because microbes mediate many processes that support agricultural productions and even may indicate disturbances or beneficial effects of amendments or management strategies 2.

Shifting cultivation in India is mostly practiced in the hilly areas by the tribal groups of the North Eastern states of India like Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, and Nagaland, Sikkim and Tripura 3. Mixed cropping system is mostly practiced in these jhum fields. In our study we have selected four crop plants viz. rice (Oryza sativa), colocasia (Colocasia esculenta), maize (Zea mays) and Perilla (Perilla frutescens), that were grown and common to all the fields (5-, 10- and 20- years), except for P.frutescens which is absent in 10 years fallow field.

The rhizosphere is a “hot spot” of intense microbial activity in the soil surrounding the roots, and is the focus in the field of plant stress response 4. These microbes in the rhizosphere play crucial roles in the rhizosphere ecosystem which includes metabolic processes such as nutrient cycling and organic matter decomposition which exert positive effects on plant health and growth 5 and they also play a crucial role in helping plant to adapt to various environmental stresses 6. Plant roots produce various exudates that help in shaping variety of microbes such as bacteria, fungi, algae, and protozoa 4. Although products released by roots comprise an important pool of organic compounds for soil microorganisms, their composition and quality can vary according to the plant species, soil type and plant developmental stage 7. Acidobacteria is one of the most abundantly distributed bacterial groups in the environment 8. The abundance of Acidobacteria in soils and their ability to withstand extreme and polluted environments suggest that they serve functions that are important in the environment and that are potentially quite varied 9. The phylum Burkholderia is also among the most abundant bacteria in the environment. The plasticity of their genomes and their capacity to adapt to changing conditions allow them to colonize diverse environmental niches. Some Burkholderia interact with host plants, resulting in beneficial effects and can also be used as biofertilizers, either by fixing nitrogen or by releasing iron or phosphorus from rock phosphates, to benefit crops cultivated in low-fertility soils, while other scan potentially be utilized as powerful pesticides in control of soil borne diseases, thus, becoming ecologically important 10. Since there is capability of Acidobacteria and Burkholderia for maintaining environment and agricultural stability purposes (such as nitrogen fixation, plant growth stimulation, biological control) we therefore investigate Acidobacteria and Burkholderia communities which may play major role in sustaining crop plants in jhum soils.

Plant associated microbial communities, such as Acidobacteria and Burkholderia, and their effects on plant growth and development in many disturbed, undisturbed, extreme and even stressed environments, have been done by many researchers around the world, however it has not been studied in jhum soil. Since plant and their surrounding microbes are living in association with each other, it is crucial to understand how these microbes are affected by the land use pattern. In a disturbed or stressed environment, soil nutrients and soil physical and biochemical properties also changes which will directly or indirectly affect plant growth and development. Therefore, this study aimed at analyzing the Acidobacteria and Burkholderia community associated with mixed crops under jhum soils using molecular approaches. DGGE fingerprints of 16S rRNA gene fragment were generated so as to investigate the two phylum community structures in the selected plant microsites (rhizosphere, loosely adhered soil and bulk) and to gain information as to whether these communities were altered or affected by different jhum fallow cycles (in this case 5-, 10- and 20- years). The study may help us to understand the effect of fallow length and crop plant on the recruitment of rhizosphere community in jhum soils.

2. Material and Methods

2.1. Collection of Soil Samples

The crop plants and soil samples were collected at their growing stage from 5-, 10- and 20-years fallow cycles in triplicates. Rhizospheric soil was collected by gently brushing the soil attached to the roots. Loosely adhered soil was removed by shaking the roots. The replicate soil sample of each plant (separately for rhizosphere, loosely adhered and bulk soil) were then mixed together to make composite sample. The resulting soil samples were stored at -20°C for soil DNA extraction.

2.2. Bacterial Counts

Isolation of bacteria from rhizosphere soil was done using serial dilution method on Tryptic Soy Agar (TSA) and Reasoner’s 2Agar (R2A) culture media in triplicates. For isolation of root endophytes, fresh roots of the selected crop plants were washed in running tap water to remove any remaining soil attaching to the root surface and air dried for 3 to 4 hours. Dry weight per gram root sample was also taken.1 g of root was weighed and cut to 1 cm length. The roots were subjected to surface sterilization using 70% Ethanol and 2% Sodium hypochlorite solution. The roots were treated in 70% Ethanol for 1 minute followed by 2% Sodium Hypochlorite for 5 minutes. The roots were then treated in 70% Ethanol for about 30 seconds and finally followed by three rinses in sterile distilled water. The roots were transferred to sterile mortar pestle and grinded in 1X Phosphate buffer saline. The resulting suspension (both rhizosphere soil and root tissue) was serially diluted upto 10-5 dilution. Dilutions 10-3, 10-4 and 10-5 were plated onto TSA and R2A agar media in triplicates. Plates were then incubated at 30±1˚C, observed at 24, 48 and 72 hours and counted. Colonies Forming Units (CFU) g-1 fresh soil or root was calculated. Two-way analysis of variance (ANOVA) was also performed using SPSS 16 software to compare the effects of crop plant and fallow cycles as well as their interaction effects on the rhizobacteria and root endophytes CFU. CFU was also correlated with soil properties using Pearson’s correlation.

2.3. Soil DNA Extraction

DNA extraction was done using PowerSoiltm DNA Isolation Kit (MoBio Laboratories Inc., Carlsbad, CA) with a modification of additional incubation at 65°C for 10 minutes at the cell lysis step. DNA quality was checked at A260/280 under NanoDrop 2000 spectrophotometer.

2.4. 16SrRNA Gene Amplification and DGGE Fingerprinting

The primers used in this study are listed in Table 1. Optimization of PCR primers was done using gradient PCR. Amplification of Acidobacteria and Burkholderia 16S rRNA gene fragment was done using PCR-DGGE approach. The first round PCR primer pair for Acidobacteria used was 31F and 1378R and for second round PCR was F984GC and 1378R. Primer pair of Burkholderia used in first round PCR was Burk3 and 1378R and Burk3-GC and BurkR for the second round (Table 1). Approximately, 20 ng (1 μl) aliquot of each sample DNA was used for a 25 μl PCR reaction. The PCR reaction contained 1X PCR buffer (New England Biolabs, NEB), 1.5 mM MgCl2, 200 μM dNTPs, 0.2 μM forward and reverse Primer, 0.1 μg-1 μl BSA (Bovine serum albumin), and 3U Taq Polymerase (New England Biolabs). The PCR parameters were as follows: initial melt at 94°C for 3 min followed by 35 cycles of 94°C for 45 sec, annealing at 52°C (Acidobacteria)/ 58°C (Burkholderia) for 45 sec and 72°C for 1 min and a final hold at 72°C for 7 min. For PCR amplification, a blank was also loaded along with the samples. The PCR amplified products were analysed using agarose (0.8%) gel electrophoresis. The same PCR condition was run for the second round PCR at annealing temperature of 62.2°C.

2.5. Denaturing Gradient Gel Electrophoresis (DGGE)

DGGE was performed with the IngenyPhorU mutation detection system. PCR products were loaded onto polyacrylamide gel 6% (wt/vol) Acrylamide/Bisacrylamide (ratio of Acrylamide to bisacrylamide is 37.5:1) in 0.5X TAE buffer (pH 8) with a denaturant gradient (100% denaturant consist of 7M Urea and 40% (wt/vol) deionized formamide) of 35% to 70%and 30% 65% for Acidobacteria and Burkholderia. The stacking gel consists of 6% Acrylamide/Bisacrylamide (37.5:1) and 0.5X TAE buffer, pH 8.0. The wells were loaded with roughly equal amounts of DNA and electrophoresis was carried out in 0.5X TAE buffer at 90V for 16 hours at 60°C. The gels were silver stained as follows and photographed.

2.6. Silver Staining of DGGE Gel

Briefly, silver staining was carried out by soaking the gel in fixing solution (10% ethanol and 1% acetic acid) for 10 minutes and washed using distilled water. The gel was pre-treated using the pre-treatment solution (1.5% Nitric acid) for about 3 minutes under constant shaking and rinsed. The gel was stained using 0.2% silver nitrate impregnation solution for about 20 minutes and under constant shaking and rinsed. The gel was developed by applying initially 250 ml of pre-cold (12°C) developing solution (30 g of Sodium carbonate and 0.54 ml of 37% formaldehyde. The solution was kept at 12°C before use) and gently shaking until the solution became dark. The solution was drained and the tray was again filled with 750 ml fresh cold solution for 4-7 minutes until the bands appeared with desirable intensity. The gel was transferred to new tray containing stop solution (5% acetic acid) to stop the reaction and kept for 5 minutes. The gel was washed in distilled water. The gel was air-dried and photograph.

2.7. Analysis of DGGE Banding Pattern

The bacterial community profiles generated were transformed to a matrix based on the presence/absence of bands and further scored based on the intensity of the band. Scoring was made from 0 to 5. Strongest bands were scored 5, least intense band 1 and absence of band 0. The band intensity score matrix was further expressed as relative abundance matrix [(number of a specific band/ sum of all the bands in the sample) x 100]. The species richness from the DGGE banding profile was expressed as the total number of bands for both Acidobacteria and Burkholderia. Species diversity and evenness was calculated using the Shannon diversity index (H′) 17 using band intensity.

Where,

H = Shannon's diversity index

S = total number of species in the community (richness)

pi = proportion of S made up of the ith species

EH = equitability (evenness)

Multivariate analysis was performed using PAST3 software. Non-metric multidimensional scaling (nMDS) and Principal Component Analysis (PCA) was done for similarity community composition between samples, and cluster/dendrogram was constructed using the Unweighted pair group method with arithmetic mean (UPGMA) algorithm. ANOSIM (analysis of similarity) (100,000 permutations) and PERMANOVA (Permutational multivariate analysis of variance) (999 permutations) was done for test of similarity of community composition of different fallow cycles 18. SIMPER was also used to estimate the similarity or dissimilarity percent of community composition among the fallow cycles. All multivariate analysis was done based on the Bray-Curtis similarity indices. Pearson’s correlation was done SPSS16 to correlate soil properties and bacterial community. All statistical analysis was performed using the relative abundance matrix except for the Pearson’s correlation it was done using the presence and absence matrix.

2.8. Soil Physico-chemical and Biochemical Properties

Physicochemical properties of soil were determined as per the standard procedures described by Page et al. 19. Soil Moisture content (MC) was determined gravimetrically by oven drying fresh soil samples at 105°C to constant weight (wt.). Air dried soil samples (passed through 0.5 mm sieve) were used for determination of soil pH and soil organic carbon (SOC). Soil pH was measured in 1:2.5 soil: H2O suspension using a standard pH meter (Mettler Toledo, Switzerland). Air-dried and finely ground soil (<0.1 mm, 0.5 g) was used for determination of SOC by the potassium dichromate wet oxidation method 20.

Microbial biomass carbon (MBC), Microbial biomass nitrogen (MBN) and Microbial biomass phosphorus (MBP) were determined by chloroform-fumigation method 21. Available phosphorus (AvP) in soil was measured following Bray’s method 22. Available potassium (AvK) was extracted using neutral ammonium acetate 23. Soil available nitrogen (AvN) was determined by the method described by Subbiah and Asija 24. Exchangeable Ca+Mg (Ex Ca+Mg) were estimated using the EDTA method. Breifly, 10 g of air-dried soil was extracted using 50 ml of neutral ammonium acetate and shaken for 10 minutes. The extraction mixture was then filtered through Whatman No.1 filter paper.10 ml of aliquot was taken and 0.5 ml of ammonium chloride-ammonium hydroxide buffer was added. 3-4 drops of Erichrome black T indicator was added. This solution was titrated with 0.01N EDTA till the colour changes to bright blue or green and no tinge of wine-red colour remains behind.

Soil dehydrogenase activity (DHA) was measured in terms of the amount of triphenylformazan (TPF) produced during incubation of fresh soil sample with 2,3,5-triphenyltetrazolium chloride (TTC) at 37±1°C for 24 hours, and expressed as μg (TPF) g1 (dry weight) soil h1 25. Soil acid-phosphomonoesterase activity (PHA) was determined in terms of amount of p-nitrophenol (PNP) produced during incubation (37±1°C for 1 hour) of fresh soil sample with p-nitrophenyl phosphate (p-NPP) in the presence of a modified universal buffer (MUB, pH 6.5), and was expressed as mg PNP g1 (dry weight) soil h1 26. β-Glucosidase activity (GSA) of soil was determined based on the method described by Eivazi and Tabatabai 27. One gram soil was incubated with 0.25 ml Toluene, 4 ml MUB (pH 6) and 1ml of PNG (p-Nitrophenyl-β-D-glucoside) solution, pH 6. After 1 hour incubation, 0.5 M CaCl2, 4 ml of 0.1 M THAM (Tris (hydroxymethyl aminomethane) buffer, pH 12, were added, swirled and then filtered. The amount of p-nitrophenol released during incubation was expressed in µg p-nitrophenol g-1 dry wt. soil h-1.

3. Results

3.1. Bacterial Counts

Table 2 showed the bacterial CFU of rhizosphere (g-1 fresh soil) and root endophyte (g-1 root) of O.sativa, C.esculenta, Z.mays and P.frutescens from different jhum cycles (5-, 10- and 20- years). CFU g-1 soil and CFU g-1 root recorded was higher on R2A than TSA media. Highest CFU was seen in the 20 years and minimum in 5 years fallow cycle in all the rhizosphere samples. However, for root endophyte CFU was highest in 5 years and lowest in 20 years fallow cycle in all the root samples. Crop plant and fallow cycle effect on rhizosphere CFU were statistically significant at p<0.001 and p<0.05, respectively (Table 3). Crop plant effect on root endophyte CFU was statistically different at p<0.01. The main effect of crop plant on rhizosphere and root endophyte yielded an effect of 89% and 81.6%, respectively. The effect of fallow cycle on rhizosphere bacteria was 53%. The interaction of crop plant and fallow cycle was not statistically significant for both rhizosphere and root endophytes CFU.

3.2. Acidobacteria and Burkholderia Community Richness and Diversity

Figure 1 and Figure 2 depicts DGGE gel profile images of Acidobacteria and Burkholderia, respectively. Banding profile revealed varied banding pattern among the crop plant samples of the same and different fallow lengths. DGGE analysis revealed richness of 11-21 and 2-7 distinct bands in Acidobacteria and Burkholderia, respectively. Acidobacteria showed more number of bands compared Burkholderia indicated that Acidobacteria is highly diverse. Band A, B, C and D were some of the bands that showed Acidobacteria community shifts among the crop plants while band E was present only in bulk sample of 10 years fallow cycle (Fig.1). Burkholderia community pattern (Fig.2) showed few numbers of bands in all the samples. Band A was present in all the crop samples except in the 10 years Z.mays rhizosphere, whereas B to F were few of the bands (dominant) that are likely to be selectively present only in some of the samples. Example, band B was present in loosely adhered of 5 years O.sativa as well as in the rhizosphere and loosely adhered soil of 20 years Z.mays. Band C was seen in the 5 and 10 years bulk sample, 5 years loosely adhered O.sativa, 10 years rhizosphere of O.sativa and 20 years rhizosphere and loosely adhered soil of Z.mays.

Average Shannon diversity index was higher in Acidobacteria (H = 2.67±0.07) than Burkholderia (H = 1.23±0.34). Acidobacteria showed highest diversity at fallow cycle 20 and highest evenness at fallow cycle 5 in all the crop samples (Table 4). Burkholderia community showed highest diversity as well as evenness in 5 (O.sativa and Z.mays) and 10 (C.esculenta and P.frutescens) years fallow cycles (Figure 3).

3.3. Acidobacteria and Burkholderia Community Composition

Dendrogram was constructed based on the relative abundance matrix generated from the community pattern on the gel for both Acidobacteria and Burkholderia (Figure 4). The dendrogram of Acidobacteria community structure resulted in three clusters which separate the three fallow cycles. The three clusters showed similarity of ~65% to ~75%. The crop samples showed similarity of ~75% to ~95%. Acidobacteria as well as Burkholderia in the rhizosphere and loosely adhered soil of the same crop plant also tend to group together. Burkholderia community showed similarity of ~50 to ~90% among the crop samples but do not show clear separation between fallow cycles nor among rhizosphere, loosely adhered and bulk soil. Crops from 5 years and 10 years fallow cycle tend to group together. Rhizosphere of Z.mays 10 and 20 years group together. Rhizosphere and loosely adhered soil of C.esculenta of 5 and 10 years grouped together. On the other hand, rhizospheric soil of O.sativa, C.esculenta and P.frutescens of 20 years grouped together. Similarly, loosely adhered soil of O.sativa, C.esculenta and P.frutescens of 20 years grouped in the same cluster which indicates that rhizosphere and loosely adhered soil the fallow cycle 20 years are closely similar to each other.

The nMDS and PCA (Figure 5) plots showed grouping of fallow cycles 5-, 10- and 20 years separately for Acidobacteria. Burkholderia community structure did not show clear separation between fallow cycles although the crop plants of same fallow cycle tend to group together. nMDS plot for Acidobateria and Burkholderia was computed and shown in two co-ordinates with 2D stress value of 0.15 and 0.19 respectively.

The ANOSIM (Table 5) of Acidobacteria showed significant differences between fallow cycles of (R=1, p<0.01) and crop plants (R=0.67, p<0.01). Burkholderia community pattern also showed significant differences between fallow cycles (R=0.67, p<0.01) and crop plants (R=0.42, p<0.01). However, no significant differences were observed between rhizosphere, loosely adhered and bulk soil. PERMANOVA analysis (Table 5) indicated that fallow cycle was a determining factor of Acidobacteria (F=8.16, p<0.01) and Burkholderia (F=1.12, p<0.05). Crop plants were also found to be the determining factor for both Acidobacteria (F=1.82, p<0.01) and Burkholderia (F=2.07, p<0.01) communities. SIMPER analysis showed highest Acidobacteria dissimilarity between 5 and 20 years fallow cycle (37.77%) followed by 10 and 20 years (33.43%) and 5 and 10 years (33.15%). Similarly, in the case of Burkholderia, dissimilarity was highest between 10 and 20 years fallow cycles (61.90%) followed by 5 and 20 years (56.60 %) and least between 5 and 10 years fallow cycle (54.55%).

3.4. Correlation of CFU (Rhizobacteria and Bacterial Root Endophytes with Soil Physico-chemical and Biochemical Properties)

Physical, chemical and biochemical properties of soil were analysed (Supplementary Table S1). All soil parameters analyzed were found to be higher in 20 fallow cycles, except all the three soil enzymes were found to be higher in the 5 years fallow cycle. Pearson’s correlation (r) of soil properties, bacterial counts, Acidobacteria and Burkholderia community pattern which was based on the presence/absence of bands were analysed (Supplementary Table S2). CFU of rhizosphere soil was found to be positively correlated with soil pH (r=0.67; p<0.05), SOC (r=0.81; p<0.01), MBC (r=0.84; p<0.01), MBN (r=0.85; p<0.01), MBP (r=0.80; p<0.01), AvN (r=0.68; p<0.05), AvK (r=0.93; p<0.01) and ExCa+Mg (r=0.69; p<0.05) and negatively correlated with DHA (r=-0.66; p<0.05), PHA (r=-0.71; p<0.05), GSA (r=-0.67; p<0.05). CFU of root endophyte was found to be negatively correlated to pH (r=-0.97; p<0.01), SOC (r=-0.72; p<0.05), MBC (r=-0.63; p<0.05), MBN (r=-0.62; p<0.05), MBP (r=-0.88; p<0.01), AvK (r=-0.63; p<0.05) and CFU of rhizosphere soil (r=-0.75, p<0.01) and positively correlated with GSA (r=0.73; p<0.05).

Acidobacteria was positively correlated with soil pH (r=0.67; p<0.05), SOC (r=0.863; p<0.01), MBC (r=0.74; p<0.01), MBN (r=0.74; p<0.01), MBP (r=0.78; p<0.01), AvN (r=0.71; p<0.05), AvK (r=0.66; p<0.05) and Ex Ca+Mg (r=0.61; p<0.05) and negatively correlated to soil PHA (r=-0.61; p<0.05). Burkholderia was positively correlated to soil DHA (r=0.61; p<0.05) and negatively correlated with soil MBC (r=-0.63; p<0.05). Acidobacteria was positively correlated with CFU of both rhizosphere (r= 0.65; p<0.01) and negatively correlated with root endophyte (r=-0.78; p<0.01).

4. Discussion

In this study, we have used both culture-dependent and culture-independent technique for studying the effect of fallow cycle and crop plants on bacterial communities in soil. We used conventional method of isolation and enumeration of bacterial population in the rhizosphere and root tissue. PCR-DGGE has been used in molecular microbial ecology for about a decade 28. DGGE fingerprinting is the most widely used and appropriate method for analysis of multiple samples. Since its introduction into microbial ecology, it has been adapted in many laboratories for assessment of microbial diversity in natural samples and is reproducible and sensitive 29. Numerous samples can be analyzed simultaneously allowing the monitoring of microbial communities and whether they are affected by any environmental parameter 30. The first silver staining of polyacrylamide gels was introduced by Switzer et al. 31. We have used this technique as it offers sensitivity, is rapid and easy to use for identification of nucleic acids. Silver staining also reduced the cost of testing by reducing the PCR mixture volume and provides a permanent record of result 32. Different statistical strategies have been applied for analyzing DGGE fingerprinting data and multivariate analyses of DGGE patterns were confirmed by Muylaert et al. 33 and incorporation of both the methods (DGGE and multivariate analyses) has become a powerful tool in molecular microbial community’s studies.

The choice of matrix between presence/absence and relative abundance depends on whether the specific aim of the study is quantitative (presence/absence) or quantitative (relative abundance) and that relative abundance is recommended over presence/absence matrix to investigate complex bacterial community composition and to reveal the full extent of the changes in microbial community composition 18. In our study, we have analyzed all the data based on the relative abundance matrix except for correlation we have used the presence/absence matrix.

Number of CFU (both rhizosphere and root tissue) of O.sativa, C.esculenta, Z.mays and P.frutescens from different jhum cycles (5-, 10- and 20- years) were comparatively higher on R2A than TSA media indicating the ability of R2A media to provide nutritional requirements and support microbial growth 34. 89% and 53% effect size were attributed to individual crop plant and fallow cycle indicating that crop plant and fallow cycle are likely the factors affecting the culturable bacteria in the rhizosphere of selected crop plants. 81.6% of the variance in culturable endophytic bacterial population was explained by crop plant pointing to the ability of plant species to attract and recruit special bacterial endophytes that may help them cope with the surrounding environment. However, there is no combine effect of crop plant and fallow cycle on rhizobacteria and root endophytes indicating their effect were independent of each other. Endophytic community of a plant is strongly influenced by host plant and different plant species growing in the same soil can have different endophytic communities and same plant species growing in different agricultural soil can have different endophytic bacteria 36.

The community composition of soil Acidobacteria and Burkholderia was altered in shifting cultivation system as revealed by the DGGE finger printing. In this study, both the DGGE banding patterns were complex and showed higher number of species especially with Acidobacteria community. This was also seen from the Shannon diversity index where Acidobacteria had the higher average diversity index which was due to higher number of bands present. Thus, indicating the dominating nature of this group in the selected jhum plots. Community shifts as seen by presence and absence of bands between crop plants of same and different fallow were most likely due to changes of root exudation patterns at different fallow cycles due to abiotic and biotic stresses at different fallow cycles suggesting selection of different species in this environment. Many biotic and abiotic stresses can alter rhizosphere microbial community structures because some microbial communities can sense plant signal molecules under stresses which can trigger some microbial populations to increase or decrease 37, 38. In this study, Shannon evenness was variable yet higher in all the rhizosphere of the selected crop plants reflecting to functional resistant of dominant species to any environmental change. Cluster analysis showed that there was similarity in the Acidobacteria community associated with crop plants of the same fallow cycle. There were similarities in few crop species and also among fallow cycles in the case of Burkholderia population. The effects of both plant microsites (rhizosphere and loosely adhered soil) and fallow cycle seemed to be stronger on Acidobacteria compared to Burkholderia. Our results have also showed significant differences in Acidobacteria and Burkholderia population at different fallow cycles and among the selected crop plants within the same fallow cycle indicating that both fallow cycle and plant species are determining factor in shaping the community structure of both bacterial groups. For Acidobacteria, fallow cycle had a stronger effect than crop species and plant microsites, whereas in the case of Burkholderia, the effect of crop species is slightly higher than fallow cycles but the difference is low, pointing that may be both these factors were having equal effect on shaping Burkholderia community. This was also confirmed by our culture-dependent analysis which showed the effect of crop plant and fallow cycle on bacterial population. Site dependent community analysis of bacteria was also studied by Costa et al. 39 which showed that the effects of plant and site on bacterial communities using PCR-DGGE approach. His study showed that plant roots played a more important role than the sampling site for determining the rhizospheric microbial community. Plant effects on soil microbial communities have been frequently observed in the rhizosphere, which refers to the soil directly influenced by root exudates 40, 41. However, the composition of root exudates varies from plant to plant and affects the relative abundance of microorganisms in the vicinity of the roots [2004]. According to Marschner 43, the interaction between plant species, soil type and root zone affect the bacterial community composition.

It was already known that bacterial population in soil is greatly affected by soil properties. This study also pointed to the relationship between soil parameters and bacterial population in soil. It was seen that culturable rhizobacteria and root endophytes were correlated to a number of soil parameters such as pH, SOC, PHA, DHA, GSA, MBC, MBN, MBP, AvN, AvP, AvK and Ex Ca+Mg. Correlation was also found between CFU of rhizobacteria and CFU of root endophytes suggesting that the surrounding rhizobacteria may be controlling the endophyte population and diversity or vice versa by releasing root exudates. Acidobacteria community was correlated with rhizobacteria and root endophyte population suggesting that Acidobacteria may play a role in contributing or controlling the population of rhizobacteria and root endophytic bacteria through interaction with each other or with other organisms and also with the environment and hence shape the diversity. Among the soil properties that correlated with bacterial population in soils, pH was most prominent and also a strong predictor of Acidobacteria abundance and community composition in soil. The highest incidences of Acidobacteria were found in soils with the lowest pH 44 and phylogenetic clustering of Acidobacteria communities became stronger as soil pH departed from neutrality 45. Preference for an acidic pH has been found to be a trait of other subdivision Acidobacteria 46 but is probably not characteristic of the entire phylum 9, whereby, multiple members of the phylum Acidobacteria have been found to be abundant in alkaline soils 47, 48. Higher SOC in longer fallow cycle increase the microbial population, particularly Acidobacteria in this case, due to accumulation and build up of organic matter during the long fallow period. Yang et al. 49 also found that SOC was the main driving factor changing the bacterial communities. Higher MBC, MBN and MBP in the soil of 20 years fallow cycle indicates the high rate of decomposition of plant, animal and soil organic matter thus releasing carbon dioxide and plant available nutrients in these soil. Higher microbial biomass is an indication of higher abundance of bacterial population. PHA is involved in phosphorus cycle and has been reported to be governed by soil microclimate, SOC and AvP 50. The relative stress in younger fallow cycle may have caused the higher activity in soil enzymes which could be due to higher plant and microbial secretion in these soils. The high Ex Ca+Mg in the rhizosphere of selected crop plants revealed the soil ability to provide sufficient nutrients required by plants, although a wide range of other factors influence the exchange capacity.

Therefore, it was seen that the bacterial population in the soil and root can be greatly affected by plant species and fallow cycle and their dependent on soil nutrients as revealed by both culture-dependent and culture-independent technique. Due to this variation in exudation, different plant species growing in the same soil type are known to select divergent bacterial communities 2, 7, 51. However, when the microbial communities associated with the same plant species growing in different soil types are analyzed, the soil type may exert a large influence on microbial diversity 7, 52. Keeping in mind that several other factors like climate, plant genotypes, age, root exudates, etc. are also responsible for shaping the bacterial population. The changed microbial community composition during stress or during disturbance in jhum soil may have implications for plant survival and health. There is a need to identify root associated microbial communities that thrive under adverse environments and can confer stress tolerance and potentially be advantageous to the host.

5. Conclusion

This study reveals that under relative stressed environments like jhum ecosystem, along with other factors such as soil type, the factor determining the microbial community structure may likely be due to the length of fallow cycles which exert pressure to the plant to secrete root exudates that attract special microbial communities that can confer resistance and tolerance to the host plant from biotic and abiotic stresses. Plant species is also a determining factor for recruiting Acidobacteria and Burkholderia communities that may help the individual crop plant to survive in jhum soil especially in shorter fallow cycles. This study also revealed that community patterns of Acidobacteria and Burkholderia responds differently to the length of the fallow cycles. This study may also help in formulating ecorestoration strategies by targeting dominant strains (as revealed in DGGE fingerprinting) that may help in plant growth and their survive ability, and developing appropriate bio-inoculant that is confined to mixed crops under jhum agro-ecosystem for improving crop productivity and reduce the environmental impacts caused by chemical fertilizers. The symbiotic associations of microbes and plants if targeted can provide a lot more of information where we can improve the soil health status in jhum fields and improve crop productivity in these systems.

Acknowledgements

The authors acknowledge the College of Post Graduate Studies, Central Agricultural University, Imphal, Umiam, Meghalaya, for providing laboratory facilities. We also thank Dr. Sapu Changkija of Nagaland University for help during field trips and jhum cycle identification.

Funding

This work was funded by North Eastern Region Biotechnology Programme Management Cell (NER-BPMC), Department of Biotechnology (DBT), Government of India (GOI).

Conflict of Interest

The authors declare that there is no conflict of interest.

References

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In article      View Article
 
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Published with license by Science and Education Publishing, Copyright © 2021 Alarisa Khyllep, Dwipendra Thakuria and Mamtaj S. Dkhar

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Cite this article:

Normal Style
Alarisa Khyllep, Dwipendra Thakuria, Mamtaj S. Dkhar. Effect of Jhum Cycles on Acidobacteria and Burkholderia Community in the Rhizosphere of Mixed Crops of Different Jhum Fields. Applied Ecology and Environmental Sciences. Vol. 9, No. 11, 2021, pp 919-930. http://pubs.sciepub.com/aees/9/11/2
MLA Style
Khyllep, Alarisa, Dwipendra Thakuria, and Mamtaj S. Dkhar. "Effect of Jhum Cycles on Acidobacteria and Burkholderia Community in the Rhizosphere of Mixed Crops of Different Jhum Fields." Applied Ecology and Environmental Sciences 9.11 (2021): 919-930.
APA Style
Khyllep, A. , Thakuria, D. , & Dkhar, M. S. (2021). Effect of Jhum Cycles on Acidobacteria and Burkholderia Community in the Rhizosphere of Mixed Crops of Different Jhum Fields. Applied Ecology and Environmental Sciences, 9(11), 919-930.
Chicago Style
Khyllep, Alarisa, Dwipendra Thakuria, and Mamtaj S. Dkhar. "Effect of Jhum Cycles on Acidobacteria and Burkholderia Community in the Rhizosphere of Mixed Crops of Different Jhum Fields." Applied Ecology and Environmental Sciences 9, no. 11 (2021): 919-930.
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  • Figure 3. Shannon diversity index and evenness of Acidobacteria and Burkholderia in the rhizosphere of crop plants of the three fallow cycles. RR5/10/20 = rhizosphere of O.sativa of fallow cycle 5/10/20 years; RC5/10/20 = rhizosphere of C.esculenta of fallow cycle 5/10/20 years; RM5/10/20 = rhizosphere of Z.mays of fallow cycle 5/10/20 years; RP5/20 = = rhizosphere of P.frutescens of fallow cycle 5/20 years
  • Figure 4. Cluster analysis of (a) Acidobacteria and (b) Burkholderia community composition of the rhizosphere, loosely attached and bulk soil of selected crops of three fallow cycles generated from relative abundance matrix using UPGMA algorithm
  • Figure 5. nMDS plots (A) and PCA plots (B) of Acidobacteria and Burkholderia community composition of selected crop plants generated from relative abundance matrix
  • Table 2. Bacterial CFU g-1 rhizosphere soil (x106) and bacterial CFU g-1 root (x104) of selected crop plants
  • Table 3. ANOVA table for CFU of rhizobacteria and bacterial root endophyes of selected crop plants from different jhum cycles
  • Table 4. Shannon diversity index and evenness of rhizosphere soil of 5-, 10- and 20 years fallow cycles of selected crops
  • Table S2. Pearson’s correlation between soil properties, CFU of culturable bacteria and Acidobacteria and Burkholderia
[1]  Ramakrishnan, P.S. and Toky, O.P. “Soil nutrient status of hill agroecosystems and recovery pattern after slash and burn agriculture (jhum) in north-eastern India. Plant and Soil, 60: 41-64. 1981.
In article      View Article
 
[2]  Lupwayi, N.Z., Rice, W.A. and Clayton, G.W. “Soil microbial diversity and community structure under wheat as influenced by tillage and crop rotation”. Soil Biology and. Biochemistry, 30(13): 1733-1741. 1998.
In article      View Article
 
[3]  Nath, A.J., Brahma, B., Lal, R. and Das, A.K. “Soil and Jhum Cultivation. Encycloprdia of Soil Science, 3rd edition Taylor and Francis, 2016.
In article      
 
[4]  Mendes, R., Garbeva, P., Raaijmakers, J.M. “The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms”. FEMS Microbiology Reviews, 37(5): 634-663. 2013.
In article      View Article  PubMed
 
[5]  Dennis, P.G., Miller, A.J., Hirsch, P.R. “Are root exudates more important than other sources of rhizodeposits in structuring rhizosphere bacterial communities?” FEMS Microbiology Ecology, 72(3): 313-327. 2010.
In article      View Article  PubMed
 
[6]  Cui, J., Li, Y., Wang, C., Kim, K.S., Wang, T., Liu, S. "Characteristics of the rhizosphere bacterial community across different cultivation years in saline-alkaline paddy soils of Songnen Plain of China”. Canadian Journal of Microbiology, 64(12): 925-936. 2018.
In article      View Article  PubMed
 
[7]  Wieland, G., Neumann, R., and Backhaus, H. “Variation of microbial communities in soil, rhizosphere, and rhizoplane in response to crop species, soil type, and crop development”. Applied Environmental Microbiology, 67(12): 5849-5854. 2001.
In article      View Article  PubMed
 
[8]  Zimmermann, J., Gonzalez, J.M., Saiz-Jimenez, C. and Ludwig, W. “Detection and phylogenetic relationships of highly diverse uncultured acidobacterial communities in Altamira Cave using 23S rRNA sequence analysis”. Geomicrobiology Journal, 22(7-8): 379-388. 2005.
In article      View Article
 
[9]  Ward, N.L., Challacombe, J.F., Janssen, P.H., Henrissat, B. “Three Genomes from the Phylum Acidobacteria Provide Insight into the Lifestyles of These Microorganisms in Soil”. Applied and Environmental Microbiology, 75: 2046-2056. 2009.
In article      View Article  PubMed
 
[10]  Compant, S., Nowak, J., Coenye, T., Clement, C. and Barka, E.A. “Diversity and occurrence of Burkholderia spp. in the natural environment”. FEMS Microbiology Reviews, 32(4): 607-626. 2008.
In article      View Article  PubMed
 
[11]  Barns, S.M., Takala, S.L., Kuske, C.R. “Wide distribution and diversity of members of the bacterial kingdom Acidobacterium in the environment”. Applied and Environmental Microbiology, 65(4): 1731-1737. 1999.
In article      View Article  PubMed
 
[12]  Boon, N., Windt, De W., Verstraete, W., Top, M.E. “Evaluation of nested PCR-DGGE (denaturing gradient gel electrophoresis) with group-specific 16S rRNA primers for the analysis of bacterial communities from different wastewater treatment plants”. FEMS Microbial Ecology, 39(2): 101-112. 2002.
In article      View Article  PubMed
 
[13]  Salles, J.F., De Souza, F.A, van Elsas, J.D. “Molecular method to assess the diversity of Burkholderia species in environmental samples”. Applied and Environmental Microbiology, 68(4): 1595-1603. 2002.
In article      View Article  PubMed
 
[14]  Salles, J.F., van Veen, J.A. and van Elsas, J.D. “Multivariate analyses of Burkholderia species in soil: effect of crop and land use history”. Applied Environmental Microbiology, 70(7): 4012-4020. 2004.
In article      View Article  PubMed
 
[15]  Heuer, H. and Smalla, K. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) for studying soil microbial communities. Modern Soil Microbiology (van Elsas J. D., Trevors J. T. and Wellington EMH, eds), Marcel Dekker, New York. pp. 353-373, 1997.
In article      
 
[16]  Nübel, U., Engelen, B., Felske, A., Snaidr, J., Wiesenhuber, A., Amann, R.I., Ludwig, W. and Backhaus, H. “Sequence heterogeneities of genes encoding 16S rRNAs in Paenibacilluspolymyxadetected by temperature gradient gel electrophoresis”. Journal of Bacteriology, 178: 5636-5643. 1996.
In article      View Article  PubMed
 
[17]  Shannon, C.E. A mathematical theory of communication. Bell System Technical Journal 27: 379-423. 1948.
In article      View Article
 
[18]  Blaud, A., Diouf, F., Herrmann, A.M. and Lerch, T.Z. “Analysing the effect of soil organic matter on bacterial communities using T-RFLP fingerprinting: different methods, different stories?” Biology and Fertility of soils, 51(8): 959-971. 2015.
In article      View Article
 
[19]  Page, A.L., Miller, R.L. and Keeny, D.R. Methods of soil analysis. Part-2 Chemical and microbiological properties, 2nd edition, Agronomy Monograph No. 9: 961-1010, American Society of Agronomy, Soil Science Society of America, CSSA, Madison,Wisconsin, USA. pp. 1159. 1982.
In article      
 
[20]  Walkley, A. “Critical examination of rapid method for determining organic carbon in soils: effect of variation in digestion conditions and of inorganic soil constituents”. Soil Science, 63: 251-257. 1947.
In article      View Article
 
[21]  Brookes, P.C. and Jeorgensen, R. “Microbial biomass measurements by fumigation extraction. Microbiological methods for assessing soil quality. 77-83. 2006.
In article      View Article
 
[22]  Jackson, M.L. Soil chemical analysis. Prentice hall of India Pvt. Ltd, New Delhi. 1973.
In article      
 
[23]  Metson, A.J. Methods of chemical analysis for soil survey samples. Department of scientific and industrial research, New Zealand. 1956.
In article      
 
[24]  Subbiah, B.V. and Asija, G.L. “A rapid procedure for determination of available nitrogen in soil”. Current Science, 25: 259-260. 1956.
In article      
 
[25]  Casida, L.E., Klein, Jr D.A., Santoro, T. “Soil dehydrogenase activity”. Soil Science, 98(6): 371-376. 1964.
In article      View Article
 
[26]  Tabatabai, M.A., Bremner, J.M. “Use of p-nitrophenyl phosphate for assay of soil phosphatase activity”. Soil Biology and Biochemistry, 1(4): 301-307. 1969.
In article      View Article
 
[27]  Eivazi, F. and Tabatabai, M.A. “Glucosidases and galactosidases in soils”. Soil Biology and Biochemistry, 20(5): 601-606. 1988.
In article      View Article
 
[28]  Muyzer, G., de Waal, E.C. and Uitterlinden A.G. “Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA”. Applied Environmental Microbiology, 59(3): 695-700.1993.
In article      View Article  PubMed
 
[29]  Schafer H, Muyzer G “Denaturing gradient gel electrophoresis in marine microbial ecology. Methods in Microbiology, 30:425-468. 2004.
In article      View Article
 
[30]  Fromin, N., Hamelin, J., Tarnawski, S., et al. “Statistical analysis of denaturing gel electrophoresis (DGE) fingerprinting patterns”. Environmental Microbiology, 4(11): 634-643. 2002.
In article      View Article  PubMed
 
[31]  Switzer, R.C., Meril, C.R. and Shifrin, S. “A highly sensitive stain for detecting proteins and peptides in polyacrylamide gels”. Analitical Biochemistry, 98(1): 231-237. 1979.
In article      View Article
 
[32]  Radojkovic, D. and Kusic, J. “Silverstaining of denaturing gradient gel electrophoresis gels”. Clinical Chemistry, 46(6):883-884. 2000.
In article      View Article  PubMed
 
[33]  Muylaert, K., Van der Gucht, K., Vloemans, N., Meester, L.D., Gillis, M., and Vyverman, W. “Relationship between bacterial community composition and bottom-up versus top-down variables in four eutrophic shallow lakes”. Applied Environmental Microbiology, 68(10): 4740-4750. 2002.
In article      View Article  PubMed
 
[34]  Taylor, J.P., Wilson, B., Willis, M.S., and Burns, R.G. “Comparison of microbial numbers and enzymatic activities in surface soils and subsoils various techniques”. Soil Biology and Biochemistry, 34(3): 387-401. 2002.
In article      View Article
 
[35]  Ding, T. and Melcher, U. “Influences of plant species, season and location on leaf endophytic bacterial communities of non-cultivated-plants”. PLoS One, 11(3). 2016.
In article      View Article  PubMed
 
[36]  Graner, G., Persson, P., Meijer, J., Alstorm, S. “A study on microbial diversity in different cultivars of Brassica napus in relation to its wilt pathogen, Verticillum longisporum”. FEMS Microbiology letters, 224(2): 269-76. 2003.
In article      View Article
 
[37]  Naylor, D., De Graaf, S., Purdom, E., Coleman-Derr, D. “Drought and host selection influence bacterial community dynamics in the grass root microbiome”. Multidisciplinary Journal of Microbial Ecology, 11, 2691-2704. 2017.
In article      View Article  PubMed
 
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