The present investigation focussed on the impact of different crop rotations on VBW incidence on solanaceous crops and population dynamics of R. solanacearum in the rhizospheres. Thirty different crop rotations (with crops from poaceae, malvaceae, brassicaceae, tilliaceae, leguminaceae and solanaceae families) were conducted in the present investigation for consecutively two years, i.e., 2017-18 and 2018-19 (Table 1 & 2). At the onset of the crop rotation programme (2016-17), the initial PDI of VBW in the sick plot across the individual plots ranged from 35.00 % to 60.00 % with a mean of 54.50 % (Table 2). No significant differences among mean PDI of the VBW existed across the experimental sick plots at the onset of the experiment.
At the end of the first year of crop rotation (2017-18), significant differences were observed between the mean PDI of VBW across the 30 different crop rotation systems (Table 2). Significantly low VBW incidence was observed for the crop rotation CaOB (27.5 %) followed by SMB (32.5 %), MMB (35.00 %), MOB (35.00 %), MCoB (35.00 %), OOB (37.5 %) and OMB (37.5 %). Conversely, moderate and significantly high level of VBW incidence was found in crop rotations viz., MJB, MRB, OJB, ORiB, CoMB, CoJB, CoRB, BRiB, SCoB, SJB and SRiB (50 % to 75 %); and BBB, TTB and CCB (72.50 % to 87.50 %), respectively. At the end of second year of crop rotation (2018-19), the PDI of VBW ranged from 15.00 % to 92.50 % with a mean PDI of 51.50 %. Significantly low bacterial wilt was observed in the crop rotation MMB (15 %) followed by SMB (17.50 %), OOB (17.5 %), OMB (22.50 %), CaOB (22.50 %), SSB (PDI = 25.00 %) and MCoB (PDI = 27.50 %). On the contrary, significantly high VBW wilt incidence was observed in the crop rotation BBB (92.50 %) followed by CCB (80.00 %), TTB (80.00 %), RiRiB (72.50 %) and BRiB (72.50 %) (Table 2).
Table 2: Effect of crop rotation on PDI of VBW in Y1 (2017-2018), Y2 (2018-2019) and percentage change of wilt incidence over initial PDI. Same alphabets represent no significant difference.
Crop Rotation
|
Mean Initial PDI
(2016-17)
|
Percent Disease Incidence (PDI)
|
Mean PDI change in Y2 over mean initial PDI (2016-17)
|
Percentage reduction of logarithmic bacterial population in YR2CR3 over Initial PDI
|
PDI (Y1:2017-2018)
|
PDI (Y2:2018-2019)
|
P1 (MMB)
|
57.50 (49.46)
|
35.00 (36.22) ab
|
15.00 (22.50) a
|
-73.91
|
28.74
|
P2 (MOB)
|
52.50 (46.48)
|
35.00 (36.07) ab
|
30.00 (33.14) bcde
|
-47.62
|
27.67
|
P3 (MCoB)
|
40.00 (38.67)
|
35.00 (36.22) ab
|
27.50 (31.61) abcd
|
-31.25
|
14.60
|
P4 (MJB)
|
55.00 (48.01)
|
62.50 (52.25) efg
|
65.00 (53.78) ij
|
18.18
|
-0.19
|
P5 (MRB)
|
60.00 (50.80)
|
62.50 (52.25) efg
|
62.50 (52.33) hij
|
4.17
|
1.07
|
P6 (OOB)
|
50.00 (45.00)
|
37.50 (37.75) abc
|
17.50 (24.68) ab
|
-65.00
|
27.89
|
P7 (OMB)
|
52.50 (46.53)
|
37.50 (37.67) abc
|
22.50 (28.28) abc
|
-57.14
|
25.19
|
P8 (OJB)
|
60.00 (50.77)
|
62.50 (52.25) efg
|
75.00 (60.11) jk
|
25.00
|
-1.27
|
P9 (ORiB)
|
57.50 (49.32)
|
65.00 (53.78) efg
|
67.50 (55.26) ijk
|
34.78
|
0.69
|
P10 (OCoB)
|
50.00 (45.00)
|
55.00 (47.88) cdefg
|
47.50 (43.55) fgh
|
-5.00
|
12.90
|
P11 (CoCoB)
|
55.00 (47.87)
|
47.50 (43.55) bcde
|
40.00 (39.20) defg
|
-22.73
|
14.05
|
P12 (CoOB)
|
52.50 (46.43)
|
50.00 (45.00) bcdef
|
45.00 (42.12) efg
|
-14.29
|
17.75
|
P13 (CoMB)
|
60.00 (51.07)
|
67.50 (55.26) fg
|
70.00 (56.86) jk
|
16.67
|
0.05
|
P14 (CoJB)
|
55.00 (47.93)
|
62.50 (52.33) efg
|
75.00 (60.11) jk
|
36.36
|
-0.27
|
P15 (CoRiB)
|
60.00 (51.07)
|
62.50 (52.25) efg
|
52.50 (46.43) ghi
|
-12.50
|
13.61
|
P16 (SSB)
|
55.00 (47.88)
|
42.50 (40.68) abcd
|
25.00 (30.00) abcd
|
-54.55
|
15.49
|
P17 (SCoB)
|
60.00 (50.77)
|
50.00 (45.00) bcdef
|
47.50 (43.57) fgh
|
-20.83
|
17.20
|
P18 (SJB)
|
57.50 (49.32)
|
62.50 (52.25) efg
|
72.50 (58.58) jk
|
26.09
|
-0.46
|
P19 (SRB)
|
55.00 (47.87)
|
60.00 (50.80) defg
|
67.50 (55.26) ijk
|
22.73
|
1.99
|
P20 (SMB)
|
50.00 (45.00)
|
32.50 (34.74) ab
|
17.50 (24.68) ab
|
-65.00
|
25.81
|
P21 (CaSB)
|
55.00 (47.88)
|
50.00 (45.00) bcdef
|
40.00 (39.20) defg
|
-27.27
|
15.32
|
P22 (CaMB)
|
55.00 (47.87)
|
42.50 (40.68) abcd
|
35.00 (36.27) cdef
|
-36.36
|
2.20
|
P23 (CaOB)
|
35.00 (36.22)
|
27.50 (31.61) a
|
22.50 (28.28) abc
|
-35.71
|
14.38
|
P24 (CaCoB)
|
60.00 (50.77)
|
57.50 (49.36) defg
|
67.50 (55.38) ijk
|
12.50
|
2.37
|
P25 (CaCaB)
|
55.00 (47.87)
|
47.50 (43.57) bcde
|
40.00 (39.20) defg
|
-27.27
|
15.32
|
P26 (RiRiB)
|
55.00 (47.88)
|
70.00 (56.86) g
|
72.50 (58.39) jk
|
31.82
|
0.16
|
P27 (TTB)
|
55.00 (47.87)
|
72.50 (58.39) g
|
80.00 (63.61) k
|
45.45
|
-0.51
|
P28 (BBB)
|
55.00 (47.88)
|
87.50 (69.39) h
|
92.50 (74.32) l
|
68.18
|
-2.79
|
P29 (CCB)
|
60.00 (50.80)
|
72.50 (58.99) g
|
80.00 (63.61) k
|
33.33
|
-2.89
|
P30 (BRB)
|
55.00 (47.88)
|
60.00 (50.80) defg
|
72.50 (58.39) jk
|
31.82
|
1.45
|
SE(m)±
|
5.07
|
5.12
|
4.42
|
|
|
CD (5% level of significance)
|
NS
|
14.79
|
12.70
|
|
|
Hence, per cent reduction in PDI of VBW over the initial PDI ranged from 12.5 % to 73.91 % in 2018-19 among 30 different crop rotation systems. At the end of the second year of crop rotation (2018-19), significant reduction of the incidence of VBW in the final brinjal crop over initial year was observed in the rotations viz., MMB (73.91 %), OOB (65.00 %), SMB (65.00 %), OMB (57.14 %), SSB (54.55 %) and MOB (47.62 %); and moderate reduction was observed in the crop rotations viz., CaMB (36.36 %), CaOB (35.71 %), MCoB (31.25 %), CaSB and CoCoB (each 27.27 %), SCoB (20.83 %) and CoRiB (12.5 %) (Table 2; Figure 1). Thus, progressive decline in the incidence of VBW of brinjal was observed in the two years of cropping sequence in these crop rotations. On the contrary, increase in VBW incidence was recorded to be highest in crop rotations BBB (68.18 %) followed by TTB (45.50 %), CoJB (36.36 %), ORiB (34.78 %), CCB (33.33 %), RiRiB (31.82 %), BRiB (31.82 %), SJB (26.09 %), OJB (25.00 %), SRiB (22.73 %), MJB (18.18 %), CoMB (16.67 %), CaCoB (12.5 %) and MRB (4.17 %) compared to the initial VBW incidence of brinjal. Hence the crop rotation systems viz., MMB, OOB, SMB, OMB, SSB and MOB were found to significantly lower the incidence of VBW in sick plot after two years of consecutive crop rotations. In an earlier study (Adhikari and Basnyat, 1998), maize, okra, cowpea, and resistant tomato were observed to delay onset of VBW by 1-3 weeks and wilt severity was reduced by 20-26%. In another study, Ayana and Fininsa (2016) has reported cultivation of common bean and maize in the rotation after tomato resulted in reduction of VBW incidence by 6% and 16% after one year of crop rotation, respectively.
Year wise effect of crop rotation on rhizospheric culturable R. solanacearum population
Population of culturable R. solanacearum was measured by serial dilution plating in SMSA-E media (Elphinstone, 1995) after each crop in the two years of consecutive crop rotation experiments (2017-2018 and 2018-2019) (Supplementary figure 1; Table 3). The VBW incidence of brinjal in the sick experimental plot recorded during 2016-17 was 54.5 % and the culturable population of R. solanacearum ranged from 74.67 × 106 cfu g-1 (log value 7.87) to 91.6 × 106 cfu g-1 (log value 7.96) with no significant difference with mean of 74.13× 106 cfu g-1 (log value 7.91).
Significant mean logarithmic difference of R. solanacearum population over the initial population (culturable R. solanacearum population in soil before experiment, year 2016-17) was started to be noticed after two seasons of cropping, i.e., from YR1CR2 and the difference continued to deviate in most of the treatments up to YR2CR3. At the end of two years of crop rotation (YR2CR3) the rate of reduction of logarithmic population of R. solanacearum per season was maximum in the rhizosphere of OOB (-0.405), SMB (-0.402), MMB (-0.395), MOB (-0.387) and OMB (-0.369) (Table 2). Moderate reduction of R. solanacearum logarithmic population per season was observed in MCoB (-0.243) and CaCaB (-0.242) followed by SCoB (-0.215), CaSB (-0.205) and CaOB (-0.195). A low rate of logarithmic reduction of population per season was observed in the rhizosphere of SSB (-0.17), CoRiB (-0.17), CoOB (-0.15), CoCoB (-0.19), OCoB (-0.14), CaMB (-0.02), MRB (-0.019), ORiB (-0.015), CoJB (-0.01) and SJB (-0.006). In terms of percentage reduction of logarithmic population in the final season of YR2CR3 over the initial population, the highest percentage reduction of R. solanacearum was observed in the rhizosphere of MMB (28.74 %) followed by OOB (27.88 %), MOB (27.67 %), SMB (25.81 %) and OMB (25.19 %).
On the contrary, significant increase in rate of culturable population of R. solanacearum were observed in CCB (0.035) followed by BBB (0.025), BRiB (0.009), TTB (0.007), RiRiB (0.0013), CaCoB (0.0007), SRiB (0.0017), OJB (0.0037) and MJB (0.00023) rotations (Table 2). In terms of percentage increase of logarithmic population over the initial population in the final year (YR2CR3), the maximum percentage increase was observed in the rhizosphere of CCB (2.89 %) followed by BBB (2.79 %), OJB (1.27 %) and TTB (0.51 %).
Thus, after two years of crop rotations, MMB, OOB, OMB, MOB, and SMB were found to significantly reduce the population of R. solanacearum in the rhizospheres and significantly reduce the incidence of VBW of brinjal. In another experiment, okra-maize-radish, ragi-french bean-okra and maize-carrot-cucumber have significantly reduced primary inoculum of R. solanacearum in soil and either maize or ragi has been recommended to include in crop rotation for VBW reduction of tomato (Sharma and Kumar, 2004).
Thus, it indicates that crops viz., maize, okra and sorghum might have significant suppressive effect on survival of R. solanacearum when incorporated in crop rotation whereas brinjal and chilli has conducive effect which increases R. solanacearum population in soil.
Table 3. Rate of logarithmic population change of R. solanacearum after various cropping seasons and rate of change in two-year crop rotation period [2017-2018 (YR1) and 2018-2019 (YR2)].
Plot No.
|
Crop Rotation
|
Initial
|
YR1CR1 (2017-18)
|
YR1CR2 (2017-18)
|
YR1CR3 (2017-18)
|
YR2CR1 (2018-19)
|
YR2CR2 (2018-19)
|
YR2CR3 (2018-19)
|
Logarithmic rate of population change per cropping season
|
Percentage change of logarithmic population over initial
|
P1
|
MMBα
|
7.89
|
7.51
|
6.98 a β
|
6.86 b
|
6.08 a
|
5.84 b
|
5.62 a
|
-0.39483 a
|
-28.74
|
P2
|
MOB
|
7.89
|
7.73
|
7.17 h
|
6.91 bcd
|
6.58 d
|
5.88 b
|
5.71 b
|
-0.38717 a
|
-27.67
|
P3
|
MCoB
|
7.91
|
7.94
|
7.96 a
|
7.78 ghi
|
7.04 f
|
6.73 ef
|
6.75 fg
|
-0.24330 b
|
-14.60
|
P4
|
MJB
|
7.94
|
7.92
|
7.93 hi
|
7.93 mn
|
7.92 mno
|
7.91 n
|
7.95 no
|
0.00023 fgh
|
0.19
|
P5
|
MRB
|
7.92
|
7.96
|
7.93 g
|
7.83 ijk
|
7.75 jk
|
7.90 n
|
7.83 l
|
-0.01943 fg
|
-1.07
|
P6
|
OOB
|
7.96
|
7.65
|
7.56 lm
|
6.96 d
|
6.43 c
|
5.87 b
|
5.74 b
|
-0.40493 a
|
-27.89
|
P7
|
OMB
|
7.90
|
7.73
|
7.45 d
|
6.86 b
|
6.63 d
|
5.96 c
|
5.91 c
|
-0.36867 a
|
-25.19
|
P8
|
OJB
|
7.93
|
7.98
|
7.80 c
|
7.86 kl
|
7.75 jk
|
7.91 n
|
8.03 p
|
0.00370 fgh
|
1.27
|
P9
|
ORiB
|
7.92
|
8.00
|
7.93 n
|
7.89 lm
|
7.81 jklm
|
7.93 n
|
7.87 lm
|
-0.01550 fg
|
-0.69
|
P10
|
OCoB
|
7.93
|
7.96
|
7.91 jkl
|
7.83 ijk
|
7.18 g
|
7.93 n
|
6.91 i
|
-0.13797 e
|
-12.90
|
P11
|
CoCoB
|
7.91
|
7.97
|
7.91 klm
|
7.97 n
|
7.95 no
|
6.84 g
|
6.80 gh
|
-0.19870 cd
|
-14.05
|
P12
|
CoOB
|
7.93
|
7.72
|
7.91 b
|
6.94 cd
|
7.71 ijk
|
7.41 h
|
6.52 d
|
-0.14703 e
|
-17.75
|
P13
|
CoMB
|
7.92
|
7.75
|
7.88 hi
|
7.86 kl
|
7.73 jk
|
7.49 i
|
7.92 n
|
-0.02400 f
|
-0.04
|
P14
|
CoJB
|
7.90
|
7.92
|
7.90 lm
|
7.80 hij
|
7.69 ij
|
7.82 m
|
7.92 n
|
-0.01243 fg
|
0.27
|
P15
|
CoRB
|
7.91
|
7.97
|
6.88 klm
|
7.84 jkl
|
7.52 h
|
6.84 g
|
6.83 h
|
-0.17313 cde
|
-13.61
|
P16
|
SSB
|
7.94
|
7.53
|
6.96 e
|
6.90 bc
|
7.52 h
|
6.72 ef
|
6.71 ef
|
-0.16930 de
|
-15.49
|
P17
|
SCoB
|
7.92
|
7.93
|
6.87 klm
|
8.07 o
|
7.59 hi
|
6.60 d
|
6.56 d
|
-0.21517 bc
|
-17.20
|
P18
|
SJB
|
7.94
|
7.95
|
7.88 f
|
7.92 mn
|
7.92 mno
|
7.79 lm
|
7.97 o
|
-0.00610 fgh
|
0.46
|
P19
|
SRiB
|
7.89
|
7.55
|
7.77 lm
|
7.95 n
|
7.88 lmno
|
7.76 kl
|
7.73 jk
|
0.00170 fgh
|
-1.99
|
P20
|
SMB
|
7.94
|
7.71
|
7.14 hij
|
6.61 a
|
6.19 b
|
5.63 a
|
5.89 c
|
-0.40260 a
|
-25.81
|
P21
|
CaSB
|
7.93
|
7.81
|
7.79 jkl
|
7.74 fg
|
7.78 jkl
|
6.77 f
|
6.72 ef
|
-0.20457 bcd
|
-15.32
|
P22
|
CaMB
|
7.93
|
7.83
|
7.82 b
|
7.85 jkl
|
7.83 klmn
|
7.77 kl
|
7.75 k
|
-0.02212 f
|
-2.20
|
P23
|
CaOB
|
7.91
|
7.86
|
7.84 ijk
|
7.86 jkl
|
7.97 o
|
6.76 f
|
6.78 g
|
-0.19580 cd
|
-14.38
|
P24
|
CaCoB
|
7.88
|
7.51
|
7.39 lm
|
7.70 ef
|
7.70 ij
|
7.65 j
|
7.70 j
|
0.00070 fgh
|
-2.37
|
P25
|
CaCaB
|
7.9
|
7.79
|
7.91 c
|
7.76 gh
|
6.91 e
|
6.71 e
|
6.69 e
|
-0.24213 b
|
-15.32
|
P26
|
RiRiB
|
7.91
|
7.93
|
7.88 m
|
7.89 lm
|
7.92 mno
|
7.95 n
|
7.90 mn
|
0.00130 fgh
|
-0.16
|
P27
|
TTB
|
7.94
|
7.91
|
7.94 lm
|
7.94 mn
|
7.95 no
|
7.95 n
|
7.99 op
|
0.00737 fgh
|
0.51
|
P28
|
BBB
|
7.9
|
8.04
|
8.07 jkl
|
8.08 o
|
8.10 p
|
8.05 o
|
8.12 q
|
0.02547 gh
|
2.79
|
P29
|
CCB
|
7.87
|
7.9
|
7.90 lm
|
7.92 mn
|
7.92 mno
|
8.05 o
|
8.10 q
|
0.03553 h
|
2.89
|
P30
|
BRiB
|
7.9
|
7.71
|
7.68 klm
|
7.68 e
|
7.72 jk
|
7.73 k
|
7.78 k
|
-0.00957 fgh
|
-1.45
|
Mean (season)
|
7.92 f
|
7.82 e
|
7.67 d
|
7.63 d
|
7.49 c
|
7.21 b
|
7.16 a
|
|
|
SE(m)±
|
0.02
|
0.16
|
0.02
|
0.02
|
0.04
|
0.02
|
0.02
|
0.014
|
|
CD
|
NS
|
NS
|
0.06
|
0.05
|
0.11
|
0.05
|
0.05
|
0.039
|
|
α Alphabetic abbreviations represent various crop names represented in Table 1. β Alphabets in smaller case represent DMRT values (from YR1CR1 to YR2CR3).
Secretion of suppressive exudates or secondary metabolites from crop roots and complex interaction of rhizospheric microorganisms in soil – plant ecology might direct the soil towards suppressiveness against R. solanacearum. Gu et al. (2016) illustrated hydroxyamic acid DIMBOA (2,4-dihydroxy-7-methoxy-1,4-benzoxazine-3-one) secreted by maize roots possess strong antibacterial activity against R. solanacearum at minimum inhibitory concentrations (MIC) of 200 mg/L. Besides antibacterial activity, DIMBOA have been reported to reduce the swarming motility of R. solanacearum within 24 hours.
Proteins like β-1,3-glucanases, chitinases and lipid transferase present in root exudates of cowpea have been proved to be antimicrobial towards Fusarium oxysporum. But no report is available for its antimicrobial activity against R. solanacearum. Similarly, no knowledge is currently available regarding how R. solanacearum population is reduced in the rhizospheres of okra, sorghum, radish, and cauliflower. In order to further investigate the reasons underlying the reduction in population of R. solanacearum in the rhizospheric system of the crop rotations, rhizospheric microbial population dynamics has been studied through metagenomics of rhizospheric soils of MMB, MOB, SMB, and BBB crop rotations, collected at the end of two years of crop rotation (YR2CR3).
Changes in the microbial diversity in the rhizospheric system of the suppressive and conducive crop rotations
Plants belonging to different genotypes harbour different microbiomes in their rhizosphere owing to the influence of their secretion of root exudates with characteristic organic compounds (Sasse et al., 2018). Next Generation Sequencing (NGS) of the V3-V4 regions with Illumina HiSeq 2500 sequencing platform was used to decipher the microbial community changes in the rhizospheric systems of the last brinjal crop (YR2CR3) of the identified suppressive (MMB, MOB and SMB) and conducive (BBB) crop rotations after two years of rotation experiments against VBW. Base quality for all samples is shown in Supplementary figure 2. The x-axis represents positions in read (bp) and y-axis represents percentage of total reads. More than 90% of the total reads have phred score greater than 30 (>Q30; error-probability >=0.001). Overall base compositions of these samples are provided in Supplementary Table 1. The GC ratio of the test samples ranged from 30 – 60 % with mean of 56.13 %. The percentage of contig length plot showed that contig lengths of 410 and 440 bp were more than 40 per cent, while contig lengths of 390 were obtained for around 10 percent (Supplementary figure 3).
The Illumina sequencing generated a total paired end reads of 2217965 with a mean Phred score of 36.72. A total of 1138083 consensus reads were obtained by merging the paired end reads (Supplementary Table 2). Among them, 1137883 pre-processed consensus sequences were finally obtained by discarding 508824 chimeric sequences. Pre-processed reads from all the samples were pooled and clustered into OTUs based on their sequence similarity using Uclust program (similarity cuto. = 0.97) administered in QIIME software. A total of 163299 OTUs were identified from 1137883 reads of which 146518 OTUs with less than 5 reads were removed and 16781 OTUs were selected for further analysis (Supplementary Table 2). Bar plot representing reads and OTUs have been shown in Supplementary figure 4. All these figures suggest the data set obtained from Illumina sequencing are acceptable in standards.
Effect of crop rotation on resident bacterial community
Phylum level comparison
Among phyla, the well reported biocontrol agents comprising phylum Actinobacteria increased up to 23.79 % in OOB followed by SMB (20.44 %) and MMB (22.31 %) as compared to BBB (Figure 2). The Krona plots constructed also depicted that the share of phylum Actinobacteria was maximum in rhizosphere of OOB (56 % of total population) followed by MMB (16 % of total population), SMB (17 % of total population) and the least i.e., 6 per cent of the bacterial community in the rhizosphere of BBB (Figure 3). Firmicutes also shared higher relative abundances in the communities of OOB (17.32 %), SMB (14.64 %) and MMB (11.26 %) as compared to BBB. On the contrary, relative abundance of Proteobacteria was observed to decrease in MMB (8.70 %), SMB (8.63 %) and OOB (4.96 %) with respect to high population in BBB after two years of crop rotation (Figure 2). The reason is supported by the reduced population of Ralstonia which in turn is a Betaproteobacteria. Hence, a reliable increase in Actinobacteria and Firmicutes took place in the ecological niche of the rhizosphere of MMB, OMB and SMB in comparison to BBB.
Class level comparison
In class level, the relative abundance of Actinobacteria was maximum in the rhizosphere of OOB (48.11 %) followed by MMB (33.78%), SMB (33.18 %) in comparison to BBB (Figure 4). This figure is well in line with the relative changes in phyla level as stated above. The relative abundance of OTU’s of the well reported class of biocontrol agent, Bacilli was also observed to increase in the rhizosphere of OOB (25.91 %), SMB (19.17 %) and MMB (13.47 %) after two consecutive years of crop rotation, as compared to the rhizosphere of BBB. The Krona plots constructed from the metagenomics study (Figure 5) also revealed maximum share of Bacilli in bacterial rhizospheric community of MMB (7 %), followed by OOB (3 %), SMB (3 %) and least in case of BBB (1 %). Hence, number of different genera belonging to the class Bacilli increased in the rhizospheres where crop rotation with Maize, Okra and Sorghum was followed in the sick plot of VBW. The OTU’s of prokaryotic class Gamma-proteobacteria was higher in rhizosphere of OOB (6.79 %) and SMB (2.34 %) and lower in MMB (-2.22 %) as compared to that of BBB (Figure 4). The OTU abundance of Delta-proteobacteria was also higher in the rhizospheric prokaryotic community of SMB (13.82 %), followed by OOB (10.56 %); but the OTU abundance was lower in MMB (-11.52 %) as compared to that of BBB. The overall OTU’s of Alpha-proteobacteria were increased in the rhizosphere of OOB (1.23 %) and reduced in the rhizosphere of MMB (-9.50 %) and SMB (-9.97 %) as compared to that of population in BBB rhizosphere (Figure 4).
Order level comparison
Five bacterial orders containing important biocontrol agents were compared to understand the relationship of them with the suppression of VBW in sick soil. Considering Silva taxonomy, the number of OTUs of the order Beta-proteobacteriales belonging to class Gammaproteobacteria was found to be higher in the rhizosphere of SMB (9.76 %) followed by OOB (7.14 %) and MMB (4.53 %) as compared to that of BBB (Figure 6). It was observed that the number of OTU’s of order Streptomycetales was strikingly higher in the rhizosphere of OOB (92.45 %), SMB (90.57 %) and MMB (67.92 %) as compared to that of BBB. The Krona Plots (Figure 3) also clearly illustrated that the share of the order Streptomycetales was 3 per cent of the entire rhizospheric bacterial population of SMB, followed by 2 per cent of the total rhizospheric bacterial population of MMB and OOB each and 0.5 % of BBB rhizosphere. Again, the members of order Rhizobiales, a well reported order that imparts plant growth promotion and biocontrol activity, were comparatively higher in the rhizosphere of OOB (8.83 %) followed by MMB (5.36 %) and SMB (3.47 %) as compared to that of BBB (Figure 6). Additionally, after two consecutive years of crop rotation, members of Bacillales increased in the rhizospheres of OOB (25.93 %), MMB (20.63 %) and SMB (12.17 %) as compared to that in the rhizosphere of BBB (Figure 6). This supports the reason behind the increase in abundance of the class Bacilli in the VBW suppressive rhizospheres of MMB, OOB and SMB rotated plots.
On the contrary, the number of OTUs of members of order Pseudomonadales were found to be lower in the rhizospheric bacterial community of SMB (-22.22%) and MMB (-22.22%) (Figure 6) as compared to BBB. Further, the number of OTUs of Azospirillales were found to be higher (16.67 %) in the rhizosphere of MMB as compared to that of BBB. Hence, after two years of crop rotation, the members of order Streptomycetales, Bacillales, Beta-proteobacteriales and Rhizobiales ramped up predominantly in the rhizospheres of plots involving two years of continuous rotation with the crops like maize, okra and sorghum as compared to Brinjal.
Genus level comparison
The relative abundance of the genus Ralstonia was higher in the prokaryotic community of BBB rhizosphere as compared to the other three VBW suppressive rhizospheres (MMB, OOB and SMB). The reads of Ralstonia sp. in BBB rhizospheric prokaryotic community was 21.5 times higher than MMB, 5 times higher than OOB and 365 times higher than SMB (Figure 7). The Krona plots (Figure 8) also illustrated the lower share of Ralstonia sp. in the bacterial rhizospheric community of experimental plots rotated with Maize, Okra and Sorghum. The plots show that the share of Ralstonia sp. and R. solanacearum was as few as 0.02% and 0.007%, respectively, in the rhizospheric prokaryotic population of MMB after the two years of continuous crop rotation. Similarly, the population of Ralstonia sp. and R. solanacearum was 0.06% and 0.02 %, respectively, of total rhizospheric prokaryotic population of OOB. In case of SMB, the population of Ralstonia sp. was as few as 0.001 % of the total population. On the contrary, after the two years of continuous cropping of brinjal in the VBW sick plot, the population of R. solanacearum was 0.2 per cent of the total bacterial population and the population of Ralstonia sp. was 0.3 per cent of the total population. Hence, the population of R. solanacearum and Ralstonia sp. were both strikingly higher in the rhizosphere of BBB.
In the rhizospheric bacterial community of MMB, there was contrastingly higher reads of biocontrol agents viz., Streptomyces sp. (66.83 %), Burkholderia-Paraburkholderia sp. (64.3 %), Bacillus sp. (15.4 %) and Paenibacillus sp. (5.5 %) as compared to their abundance in the rhizosphere of BBB (Figure 7). Hence these organisms may have contributed towards suppression of the growth and population expansion of R. solanacearum in the experimental VBW sick plot by various possible principles of antagonism.
Bacterial species reported as biocontrol agents of R. solanacearum slightly differed in the rhizospheric community of OOB crop rotation. The relative abundance of Streptomyces sp. (75.44 %), Burkholderia-Paraburkholderia sp. (38.5 %) and Paenibacillus sp. (38.64 %) was higher as compared to that in the rhizosphere of BBB. In addition to them, the well reported biocontrol agents Stenotrophomonas sp. (35.49 %) and Acinetobacter sp. (35.49 %) was found to be higher. The population of Bacillus and Pseudomonas negligibly differed from that of BBB.
In case of rhizosphere of SMB crop rotation system, the per cent OTUs of Streptomyces sp. was 76.51 %, Paenibacillus sp. was 19.53 % and Bacillus sp. was 2.65 % higher than the rhizosphere of BBB. In addition to them, the percent OTUs of Brevibacillus sp. was 3.26 % higher than BBB. On the contrary the population of Burkholderia-Paraburkholderia sp., Stenotrophomonas sp. and Acinetobacter sp. were comparatively lower as compared to that of BBB, indicating absence of their role in suppressing R. solanacearum in SMB rhizosphere. Similarly, the colonisation of Planctomyces and Chloroflexi increased prominently in the rhizosphere of MMB, OOB and SMB. In contrast to them, abundance of Bacteroides was reduced in the rhizosphere of MMB, OOB and SMB as compared with higher colonisation in BBB. Hence, in the genus level comparison, eight reported biocontrol agents of R. solanacearum mentioned above were found to be relatively higher in terms of percentage abundance of OTU in the bacterial community of MMB, OOB and SMB as compared to BBB.
Exploring the Alpha diversity
The microbial diversity in terms of species richness within each rhizospheric soil sample was estimated by computing Shannon, Chao1 and observed species metrics with the help of QIIME (Quantitative Insights Into Microbial Ecology) software.
Shannon diversity index
The Shannon diversity index (SDI) gives us the picture of how many different species are present in a community (species richness) and the relative abundance of all the species in that community (species evenness). Rarefaction curve was drawn with random sub samples of increasing size in order to demonstrate how well the random sampling reflects the true diversity present in a bacterial community of an ecological niche. In our present investigation, the SDI rarefaction curve represents highest range of SDI for the rhizospheric bacterial community of suppressive crop rotation SMB (3.32 – 11.38) followed by, MMB (3.32 – 11.01) and OOB (3.28 – 11.14). The lowest SDI range was observed in the rhizosphere of BBB (3.26 to 10.69) (Table 4). Hence, relatively higher species richness and evenness was observed in the rhizosphere of suppressive crop rotations SMB, MMB and OOB as compared to the VBW conducive BBB rhizosphere.
Chao diversity index
In addition to the number of different species observed, the Chao index predicts the expected potential number of species that can be present in a bacterial community by taking into account the additional unobserved and unknown number of species. This calculation is done on the basis of the rarely present species in that bacterial community. The count of the rarely prevalent species is taken by considering singleton and doubleton reads. In our study, as compared to the Shannon diversity index, Chao diversity index predicted the possibility of thriving of more number of species in the rhizospheric bacterial community of OOB (48.60 - 13664.01) followed by MMB and SMB. On the contrary, the lowest Chao index of BBB crop rotation (45.4 - 12639.90) clearly indicates poor species richness (Figure 9; Table 4).
Observed species diversity index
The observed species index of alpha diversity only counts the number of different unique OTU or species present in a community. Among the four rhizospheres, the number of species was higher in the rhizospheric bacterial community of OOB, SMB followed by MMB (Figure 3). The least number of different species was observed in case of BBB (Table 4).
Table 4. Various alpha diversity indices of the four rhizospheric soils
Sample ID
|
Shannon index
|
Chao Index
|
Observed species
|
YR2-CR3-P1 (MMB)
|
3.32 – 11.01
|
55.0 -13137.21
|
10 - 11269.1
|
YR2-CR2-P6 (OOB)
|
3.28 – 11.14
|
48.6 - 13664.01
|
9.7 - 12329.8
|
YR2-CR3-P20 (SMB)
|
3.32 – 11.38
|
55.0 - 12772.48
|
10 - 11923.3
|
YR2-CR3-P28 (BBB)
|
3.26 to 10.69
|
45.4 - 12639.90
|
9.8 - 11125.1
|
Beta diversity analysis
Beta diversity explores the species that are shared among different communities and that are different in communities (Lozupone et al., 2006). The relation between different communities has earlier been demonstrated by various beta diversity matrices, viz., Eucledian, Chi-square and Bray-Curtis. But these matrices do not consider how evolutionarily close or distant are the species between different communities under study. Hence, Unique fraction (UniFrac) approach was taken which states how phylogenetically different are the species present between different samples/communities under study. The UniFrac approach differentiates the samples based on the fraction or proportion of the phylogenetic tree that is unique to a sample, which in turn is computed by adding the branch length of the phylogenetic tree over which the species of a sample are spread over. Distance matrix between pairs of samples for branch length on phylogenetic tree was computed using both weighted and unweighted UniFrac approach. In case of weighted UniFrac method, the frequencies of each species present in a sample is taken into consideration, while in unweighted approach only presence or absence of a species is considered. Hence, the unweighted UniFrac approach is a non-parametric approach that considers even the rarest species.
Weighted and Unweighted UniFrac approach
In our study, the UPGMA cluster tree based on weighted UniFrac approach (Figure 10) revealed that the phylogenetic distance between the bacterial community of four rhizospheres ranged from 0.16 to 0.30. The minimum phylogenetic distance was observed between species in the bacterial community of rhizosphere of MMB – OOB (0.16) and MMB – SMB (0.16). On the contrary, higher phylogenetic distance was observed between species in the bacterial community of rhizosphere of BBB-MMB (0.30), BBB-SMB (0.27) and BBB-OOB (0.24) (Table 5). Also, the cluster tree produced from non-parametric unweighted UniFrac approach showed that the communities of OOB and SMB clustered closer to each with minimum phylogenetic distance of 0.21 (Table 6), whereas the community of BBB was distantly related to MMB (Figure 11).
Table 5. Phylogenetic distance matrix based on weighted UniFrac approach
Crop rotation
|
YR2-CR3-P1 (MMB)
|
YR2-CR3-P6 (OOB)
|
YR2-CR3-P20 (SMB)
|
YR2-CR3-P28 (BBB)
|
YR2-CR2-P1 (MMB)
|
0.00
|
0.16
|
0.16
|
0.30
|
YR2-CR2-P6 (OOB)
|
0.16
|
0.00
|
0.18
|
0.24
|
YR2-CR2-P20 (SMB)
|
0.16
|
0.18
|
0.00
|
0.27
|
YR2-CR2-P28 (BBB)
|
0.30
|
0.24
|
0.27
|
0.00
|
Table 6. Phylogenetic distance matrix based on unweighted UniFrac approach
Crop rotation
|
YR2-CR3-P1 (MMB)
|
YR2-CR3-P6 (OOB)
|
YR2-CR3-P20 (SMB)
|
YR2-CR3-P28 (BBB)
|
YR2-CR2-P1 (MMB)
|
0.00
|
0.22
|
0.25
|
0.28
|
YR2-CR2-P6 (OOB)
|
0.22
|
0.00
|
0.21
|
0.24
|
YR2-CR2-P20 (SMB)
|
0.25
|
0.21
|
0.00
|
0.24
|
YR2-CR2-P28 (BBB)
|
0.28
|
0.24
|
0.24
|
0.00
|
Few studies have been conducted to study effect of different crops or cropping patterns over rhizospheric prokaryotic diversity. Venter et al. (2016) reviewed 27 crop diversification studies whereas 17 studies showed average increase of 3.36 % of microbial SDI. Quadros et al (2012) illustrated higher SDI in archaeal and bacterial diversity in maize-based crop rotations compared to other crops in subtropical acrisols. Peralta et al. (2018) inferred that SDI of bacterial community was 4 % higher in corn monocropping as compared to diversified corn-based crop rotations (corn-soyabean-wheat). But interestingly, diversification with maize, soyabean and wheat increased abundance of diseases suppressive functional group prnD gene in rhizosphere as compared monocultures of maize.
In our study, all the alpha diversity indices suggested that diversity of the bacterial species was enriched in the rhizospheric bacterial community of the suppressive crop rotation system MMB, OOB and SMB. On the contrary, the alpha diversity indices documented poor species diversity in the rhizosphere of continuous brinjal cropping (BBB). Further, in Beta diversity analysis, the cluster trees based on weighted and unweighted approach together inferred that the bacterial species of BBB rhizosphere was phylogenetically distant and different (Table 5 & 6) from the closely aggregated bacterial communities of the MMB, OOB and SMB. This indicated that the root exudates of sorghum, maize and okra have surely promoted harbouring of diverse beneficial bacterial species in the rhizospheres after two years of continuous crop rotations which in turn have suppressed the population of R. solanacearum.