Introduction
The
government of the Kingdom of Saudi Arabia is taking considerable steps toward
the support of more environmental-friendly farming systems. One such system is
organic farming, which the Saudi government is actively encouraging the private
sector to adopt for the production of safe and healthy foods (Hartmann et al. 2012). The total area of organically
farmed land is approximately 35,000 ha, and future increases are expected
(Hartmann et al. 2012). Tomato (Lycopersicon esculentum
Mill.) is one of the
most important organic crops in Saudi Arabia, with an annual production of
approximately 306,000 tons (FAO 2017). However, Fusarium wilt, a
devastating disease caused by Fusarium oxysporum f. spp. lycopersici
(FOL), leads to extensive losses in tomato yield under both greenhouse and
open field conditions (El_Komy et al. 2016). Under optimal infection
conditions, yield losses can reach 90% (Hibar
et al. 2006). Controlling
tomato wilt disease using standard chemical methods is challenging;
furthermore, this mode of control is restricted in
organic farming (Finckh et
al. 2015). Biological
control with antagonistic microorganisms offers a promising and alternative
strategy to manage tomato wilt disease without the deleterious environmental
effects of chemical treatments (El_Komy et al.
2016). Inoculation
with certain strains of plant growth-promoting rhizobacteria (PGPR), such as Bacillus subtilis, can
protect plants from damaging soil-borne pathogens and promote plant growth via different mechanisms, including
competition for nutrients and space, production of antifungal
volatile organic compounds, antibiotics and fungal cell wall-degrading enzymes,
and enhancement of plant resistance to pathogens (Kloepper et al. 2004; Bouizgarne 2013; Jangir et al. 2018).
Despite the proven
effectiveness of certain rhizobacterial inoculants for the control of plant
diseases and improvement of productivity, their successful application in
commercial agricultural has been hampered by multiple constraints. Indeed, the
efficiency of rhizobacteria is influenced by environmental conditions (Shirinbayan et al. 2019). Saudi Arabia is one of the
world’s arid regions. The cultivated soils in such regions are characterized by
harsh environmental conditions, including lack of soil moisture and poor
fertility represented in the lower contents of organic matter, as well as the
higher contents of calcium carbonate and salinity (Hussain et al. 2010).
However, such ecosystems have a diversity of microbes that are adapted to harsh
environmental conditions (Soussi et al. 2016).
Thus, identification of native rhizobacterial strains that are naturally
adapted to harsh arid ecosystems may further lead to development of effective
and sustainable cropping systems (Shirinbayan et
al. 2019).
Root colonization by rhizobacteria
and their persistence in the rhizosphere are
major challenges in the implementation of biocontrol strategies (Abdallah et
al. 2018). Poor root colonization and inadequate antagonistic metabolite
production can account for some of the variations in the activity of antagonistic inoculants during the crop growing
season (Bouizgarne 2013; Abdallah et al. 2018). Amendment of
soil with organic substrates in combination with biocontrol strains can
increase both the survival of rhizobacterial strains and
their colonization of the soil near plant roots (Gava and Pinto 2016). Moreover, certain types of compost can naturally
suppress disease. Therefore, the use of compost as a substrate for biocontrol
applications would offer additional advantages (Termorshuizen et al.
2006; Gava and Pinto 2016).
Biological control may
be an effective strategy to protect tomato plants against FOL (Jangir et al.
2018); however, novel microbial control agents that are native to specific arid
conditions need to be identified. In fact, the application of exotic biocontrol
agents might disrupt the local ecosystem and have detrimental ecological
effects on the native rhizospheric microbial
populations (Figueroa-López et
al. 2016). In addition, exotic biocontrol agents might not remain active
under all soil environments and in all agricultural ecosystems (Schmidt et al.
2004). Hence, this study aimed to select a native
rhizobacterial strain against FOL in vitro and evaluate its
effectiveness, either alone or in combination with organic compost, in reducing
tomato wilt disease and inducing plant defense responses in vivo. This
study was designed to develop an approach using a native rhizobacterial strain
to control FOL and improve organic farming practices in arid regions.
Materials and
Methods
Fungal
pathogen
In
this study, a pathogenic strain of F. oxysporum
f. spp. lycopersici (FOL-30) was obtained from
the collection of the Department of
Plant Protection, College of Food and Agricultural Sciences, King Saud University.
The pathogen was isolated from roots of tomato plants
showing typical symptoms of Fusarium wilt. Koch’s postulates were performed to confirm the
pathogenicity. The pathogen was further identified
morphologically and microscopically according to the criteria of Leslie and Summerell (2006), as well as molecularly by sequencing
translation elongation factor 1 α (tef1α) and ITS-rRNA genes
(Saleh et al. 2017). The fungal culture
was revived on potato dextrose agar (PDA; Difco
Laboratories, Detroit, MI, USA) at 28°C after
incubation for 7 days and maintained on PDA by subculturing
at regular intervals.
Isolation
and identification of bacterial antagonists
Rhizobacteria
were isolated from the rhizosphere of healthy tomato plants grown in the
Al-Kharj region of Saudi Arabia through serial dilution plating on nutrient
agar media (NA; Difco Laboratories). Colonies with
different characteristics were selected and grown separately. The isolated
bacteria were initially identified on the basis of their morphological and
physiological characteristics (Bergey
et al. 1974), as well as by using the Biolog
system (Biolog Inc., Hayward, C.A.). Molecular identification
of rhizobacterial cultures was performed by isolating genomic DNA using a standard
protocol (Sambrook et al. 1989). The 16S rRNA gene was
amplified using PCR and the 27F (5ʹ-AGAGTTTGATCMTGGCTCAG-3ʹ)
and 1492R (5'-TACGGYTACCTTGTTA CGACTT-3') universal primers (Heuer et al. 1997). The PCR
conditions were as follows: 10 min at 95°C,
followed by 35 cycles of 30 s at 95°C, 1
min at 55°C and 1.5 min at 72°C, with a
final extension of 10 min at 72°C. The
amplified products were sequenced by the Advanced Genetic Technologies Center
(AGTC), College of Agricultural Sciences of the University of Kentucky
(http://www.uky.edu/Centers/AGTC/). These DNA sequences were identified by
comparison with nucleotide sequences deposited in GenBank
using Bioedit software (Hall 1999;
http://www.mbio.ncsu.edu/Bioedit/bioedit.html).
The
In vitro antagonistic activity
Dual culture assay: The
bacterial strains were screened for antifungal activity against FOL-30 by using
the dual culture assay of Müller et al. (2018), with some
modifications. Briefly, two straight lines, 5 cm long and 2 cm from the edge of
a PDA plate, were streaked using a loop full of cells from a freshly growing
bacterial culture (24 h old). The plates were incubated at 28°C
for 48 h before fungal inoculation. A 4 mm diameter mycelial disc from a
7-day-old fungal culture was placed in the central position between the two
lines, 1.5 cm from the streaks. Plates without bacterial antagonists served as
controls. Five replicates were prepared for each treatment. Plates were
incubated at 28°C and observed daily for 7 days. The percentage of fungal
growth inhibition was determined by [(R1 − R2)/R1]
× 100, where R1 and R2 are the radii of the
pathogen colonies in the control and dual-culture plates, respectively. Signs
of stress in pathogen hyphae because of the antagonistic effects of
rhizobacterial strains were evaluated microscopically.
Bacterial
culture filtrate assay: Rhizobacterial strains were grown in NA at 28°C
for 48 h. A single colony of bacterial cultures was incubated in 100 mL of
nutrient broth with continuous shaking for 72 h at 28°C. The cultures were
centrifuged at
5000 × g for 10 min at 4°C and the
supernatant was vacuum-filtered through a 0.22 μm sterile membrane
(Millipore, Bedford, MA; Li et al. 2008). The resulting culture filtrate
was added at the concentration of 15% (v/v) to molten PDA media containing
the appropriate amount of agar to ensure the plates gelled properly. Plates containing the medium mixed
with sterile water only were used as controls. The plates were
inoculated in the center with a 0.5 cm plug from the leading edge of a
5-day-old PDA culture of FOL-30. Five replicates were prepared for each
treatment, and the plates were incubated at 28°C and observed daily for 7 days.
Mycelial growth was measured, and the percentage of growth inhibition was
calculated as described
above (Jangir et al. 2018).
Greenhouse
experiments
The
results of antagonistic experiments suggested that Bacillus subtilis
KSU-110 was the most promising strain and it was selected for further testing
of its biocontrol potential, both individually and/or in combination with
organic compost, against Fusarium wilt disease under greenhouse conditions.
Plant
growth conditions
Seeds
of Farah tomatoes, a common FOL-susceptible greenhouse cultivar in Saudi
Arabia, were surface-sterilized by immersion in 1% sodium hypochlorite for 30 s
and then washed thrice with sterile distilled water. The seeds were
pre-germinated for 3 days in Petri dishes containing sterile distilled water at
28°C. Germinated seeds were then sown in 15 cm pots containing an autoclaved
mixture of potting soil, peat moss, and perlite (2:1:1, v/v/v). Plants were
grown in a growth chamber with 70% relative humidity and a photoperiod of 12 h
light at 26°C and 12 h dark at 20°C. Plants were fertilized weekly with a
20-20-20 (N-P-K) soluble fertilizer (1 g/L) and the seedlings were irrigated
with tap water as needed. Subsequent experiments were performed
when four leaves had completely expanded (6
weeks old).
Microbial inoculum preparation
Fungal inocula were
prepared by culturing FOL-30 on PDA plates for 2 weeks at 28°C in
the dark. Fungal colonies were subsequently scraped from PDA
plates using a sterile glass rod to dislodge spores into sterile distilled
water. Fungal hyphae and residue were removed by filtering the suspension
through four layers of gauze. Spores were counted using
a hemocytometer, and the conidial suspension
was adjusted to 1 × 107 conidia per milliliter. For
antagonistic bacterial inocula, a suspension of the
KSU-110 strain was obtained from overnight cultures incubated on NA at 28°C.
Bacterial cells were scraped off the agar plate into 10 mM magnesium
sulfate buffer, centrifuged at 3000 × g for 10 min, and resuspended in
sterile distilled water. The bacterial cell concentration was adjusted to 1 ×
l07 colony forming units (cfus) per
milliliter by measuring the OD660 (optical density at 660 nm)
spectrophotometrically (Youssef et al. 2016).
Compost
material
The
sterilized organic compost (Al-Reef Organic Fertilizers Factory, Co., Kingdom
of Saudi Arabia, Riyadh) used in this study consisted of cow
manure and vegetable material, with the former being the major component and
the latter representing only 20% of the amendment. The compost had the
following major physicochemical characteristics: pH 6.3, 1% nitrogen, 91.8%
organic matter, 78.3% carbon and a 37.3 C: N ratio. It is commercially
available in Saudi Arabia.
Control of fusarium wilt in tomatoes using the combination
of the KSU-110 strain and compost
A
pot experiment was conducted in the greenhouse of the Plant Protection
Department, College of Food and Agricultural Sciences, King Saud University.
Pots were arranged in a completely randomized design with eight treatments:
(T1) non-infested soil (healthy control), (T2) non-infested soil amended with
KSU-110, (T3) non-infested soil with compost, (T4) non-infested soil with
KSU-110 and compost, (T5) soil infested with FOL-30, (T6) soil infested with
FOL-30 amended with compost, (T7) soil infested with FOL-30 and amended with
KSU-110, and (T8) soil infested with FOL-30 and amended with KSU-110 and compost.
Each treatment consisted of 30 replicates, with one plant per replicate (pot).
Plastic pots (15 cm in diameter) were filled
with a sterilized mixture of sand, clay and soil (1:1:1, v/v). The compost
treatments were incorporated into the potting mixture at a rate of 25% (v/v).
The conidial suspensions of the wilt pathogen were incorporated into each pot
to ensure a final concentration of 1 × 103 conidia per gram of soil
to promote disease development. Pots inoculated with an equal volume of
distilled water served as controls. One week after soil infestation with FOL-30
inocula, tomato seedling roots were dipped into a
bacterial suspension (1 × 107 cfu mL−1)
for 30 min and then transferred to pots, with one tomato seedling per pot. The
seedlings were placed in a greenhouse maintained at 28°C with 50–70% relative
humidity and a 12:12 h light-dark photoperiod. At 45 days after transplanting (DAT), 15
plants from each treatment were arbitrarily selected for biomass analysis and
disease scoring. The experiment was repeated twice.
Incidence and severity of fusarium wilt disease
Plants were examined for the incidence and severity of
Fusarium wilt after 45 DAT. Disease incidence (DI) was calculated as DI =
(number of diseased plants/total number of plants) × 100. Disease severity (DS)
was evaluated using two different disease rating scales (1–5); one was based on
foliar symptoms as proposed by (Hibar et al. 2006) and the other was based on
vascular browning (Horinouchi et al. 2008).
Disease scores were converted to DS using the following formula: DS = [(A × 1) + (B × 2) + (C ×
3) + (D ×
4) + (E
× 5) ]/(total number of plants) × 100, where, A, B, C, D,
and E are the number of plants
corresponding to 1, 2, 3, 4, and 5 disease rating scores, respectively. Control
efficiency (%CE) for each treatment was calculated using
the estimates of DI and DS in control and treated plants (D1
and D2, respectively) using the following formula:
CE = [(D1 – D2)/D1] ×
100.
The synergistic
interaction of KSU-110 + compost in controlling wilt disease was estimated
according to Abbott’s formulae (Levy et al. 1986). The expected control
efficiency (Pexp12) for the combined application was
calculated using
the formula: Pexp12
= (P1 + P2) – (P1 × P2)/100,
where P1 and P2 are the P data observed for
the single application of KSU-110 and compost, respectively. The observed protection efficiency
(Pobs) was estimated from the P data for the combined
application. The synergism factor (SF) was estimated using the formula:
SF = (Pobs/Pexp12). As a decision rule, SF
> 1 indicated the interaction was synergistic, SF = 1 indicated the
interaction was additive, and SF < 1 indicated the interaction was
antagonistic (Levy et al. 1986).
Plant
growth measurements
At the end of the experiment, length (cm) and
dry weight (g; oven dried at 80°C for 72 h) of the root and shoot systems of
each plant were measured separately. The improvement efficiency (%IM) was calculated using the following formula: [(C -
T)/C] × 100; where, C and T are the growth
parameters of control and treated plants, respectively. The synergistic interaction of KSU-110 + compost in
promoting plant growth was estimated, as described above.
Assay
of defense enzymes
Root
samples of three plants from each treatment were collected at 15, 30, and 45 DAT
(three replicates per time interval for each treatment). The roots were washed,
briefly dried, snap frozen in liquid nitrogen, stored at −80°C, and
maintained separately for biochemical analysis representing three biological
replications. Plant tissues were ground into a fine powder under liquid
nitrogen using a mortar and pestle. The fine powder was suspended in 100 mM
sodium phosphate buffer (pH 7.0) at 4°C (1 mL g-1 leaf tissue). The
solution was centrifuged at 10,000 × g for 20 min. The supernatant was
collected and used as a crude enzyme extract to assay peroxidase (POD)
spectrophotometrically by measuring the oxidation of pyrogallol in the presence
of H2O2 as OD425 and polyphenol oxidase (PPO)
as OD575 (Tuzun et al. 1989).
Monitoring FOL-30 and KSU-110
in the tomato rhizosphere
KSU-110 and FOL-30 populations in the soil were monitored by collecting
rhizosphere samples at 15, 30, and 45 DAT. A 1 g rhizosphere soil sample (four
replicates per time interval for each treatment) was suspended in 9 mL of
sterilized/ distilled water and vortexed at the maximum speed for 5 min. Next,
a 1:200 soil dilution was spread onto plates containing Komada’s
selective medium for FOL-30 (Komada, 1975) and NA
medium for KSU-110. After incubation at 28°C for 48 h, the number of cfus of FOL-30 and KSU-110 per gram of rhizosphere soil was
recorded. Re-isolated bacteria showing morphological
similarities to KSU-110 were identified using the Biolog
system to confirm the association of the applied strain with the rhizosphere
samples. The pathogen
reduction efficiency (%RE) was calculated using the following formula: [(C
- T)/C] × 100; where, C and T are the FOL
populations in infected control and treated rhizosphere soils, respectively.
The synergistic interaction of KSU-110 + compost in the reduction of the FOL
population was estimated at intervals, as described above.
Field experiments
Experiments
were conducted in a field naturally
infested with FOL at the Experimental
Farm of the College of Food and Agriculture Sciences, King Saud University. This field was
naturally highly infested with the wilt pathogen
during the previous season. The experiment was arranged in a completely
randomized block design with four treatments (T5, T6, T7 and
T8) and was replicated six times, with 15 plants per replicate. For the experimental treatments, tomato plants were
treated with KSU-110 and compost as described above. At the
end of the experiment (45 DAT), ten plants were arbitrarily
selected
from each replicate and used to evaluate the % DI and % DS. Furthermore, the
dry weight and length of the root and shoot systems for each plant were recorded at 45 DAT as described
above. The synergistic interactions of KSU-110 +
compost in promoting plant growth and controlling wilt disease were estimated,
as described above.
Statistical
analysis
All
experiments were repeated twice. The analyses did not indicate any significant
differences between the two repeats of the treatments; hence, the results from
the duplicate tests were combined for the final analysis. All the data are
presented as mean values (average of two experiments). All analysis of variance
tests were conducted using SAS Version 9.1 software (SAS Institute Inc 2003).
The data for disease
measurements were analyzed following an arcsine transformation. The
population data were transformed with a square-root [sqrt (x + 0.5)]
transformation before analysis to obtain homogeneity of variances (Gomez and
Gomez 1984). The least significant difference at P < 0.05 was applied
to detect differences between treatments (Gomez and Gomez 1984).
Table 1: List of rhizobacterial
strains identified on a molecular basis and their GenBank
accession numbers
Strain code |
Strain identified |
GenBank Accession No. |
KSU-18 |
Pseudomonas spp. |
MN208459 |
KSU-67 |
Pseudomonas spp. |
MN208458 |
KSU-25 |
Pseudomonas aeruginosa |
MN208460 |
KSU-87 |
Stenotrophomonas spp. |
MN208462 |
KSU-E3 |
Stenotrophomonas spp. |
MN208463 |
KSU-B3 |
Enterobacter spp. |
MN208461 |
KSU-191 |
Achromobacter spanius |
MN208464 |
KSU-B17 |
Bacillus spp. |
MN208475 |
KSU-XR |
Bacillus spp. |
KY123A56 |
KSU-06 |
B. cereus |
MN208465 |
KSU-103 |
B. megaterium |
MN208466 |
KSU-A7 |
B. pumilus |
MN208469 |
KSU-12 |
B. safensis |
MN208467 |
KSU-31 |
B. amyloliquefaciens |
MN208468 |
KSU-2.2 |
B. pumilus |
MN208474 |
KSU-Y1 |
B. subtilis |
MN208472 |
KSU-50 |
B. subtilis |
MN208470 |
KSU-110 |
B. subtilis |
MN208473 |
KSU-B2 |
B. subtilis |
MN208476 |
KSU-43 |
B. subtilis |
MN208471 |
Fig. 1: Percentage mean inhibition of FOL-30 growth by the rhizobacterial strains obtained using a dual culture plate assay (A) and bacterial culture filtrate (B) after six days of inoculation at 28 ± 1°C. Each bar represents the
average of two experiments with five replicates per treatment per experiment. Percentage inhibition data were analyzed
after arcsine transformation.
Bars with the same letter are not significantly different at P < 0.05
according to the LSD test
Results
Isolation
and identification of fungal pathogens and bacterial antagonists
The
results of culture morphology and microscopic examination revealed that the
FOL-30 strain was F. oxysporum. In addition,
the tef1α and rDNA-ITS sequences confirmed the identity of the FOL-30 strain.
The tef1α and rDNA-ITS sequences of FOL-30 were deposited in the GenBank
database under the accession numbers MN514860 and MN508482, respectively.
Twenty rhizobacterial strains were isolated from the rhizosphere of commercial tomato fields. The 16S rRNA gene-based analysis
showed that 13 rhizobacterial strains belonged
to the genus Bacillus (Table
1). Eleven were assigned to a species, whereas two were identified only to the
genus level. The remaining strains belonged to the genera Pseudomonas, Stenotrophomonas, Enterobacter,
and Achromobacter (Table 1).
In
vitro
antagonistic activity
All the strains were
significantly antagonistic to FOL-30 (P
< 0.05) and
inhibited its growth (Fig. 1).
However, these antagonistic responses
varied by strain (Fig. 1). In the dual culture
plate assay, the highest level of antagonistic activity against
FOL-30 was observed for B. subtilis strain KSU-110 (68%; Fig. 1–2). This strain induced distortions and deformations in FOL-30 mycelia, including increased
branching, hyphal swelling, and cytoplasm collapse. Moreover,
the KSU-110 culture filtrate had the
greatest inhibitory activity toward pathogen growth (46%) among all the rhizobacterial culture
filtrates (Fig. 1).
Incidence and severity of fusarium
wilt disease
The highest mean DI and DS values (P < 0.05) were
detected in tomato plants grown in the presence of FOL alone (Table 2).
Application of
KSU-110 and compost, either separately or in combination, significantly
(P <
0.05) reduced
disease development compared to that of
infected control plants (Table 2). Indeed, compared to the infected control, the
combined rhizobacteria + organic compost treatment resulted in
the largest reduction
in DI (71%), DS based on foliar symptoms
(63%), and stem discoloration (69%; Table 2).
However, the control efficiency for the tomato plants treated with KSU-110 was
higher than that of plants treated with organic compost (Table
2).
According to Abbott’s formulae, the interaction of KSU-110 with compost was
synergistic (SF > 1) in the reduction of tomato wilt disease (Table
2).
Plant
growth measurements
Plant
growth parameters were significantly (P < 0.05) reduced in tomato plants infected with FOL-30 compared with those of non-infected controls (Table 3). In FOL-30-infested soil, tomato
plants treated with the antagonistic bacteria along with organic compost showed
the greatest increase in root and shoot length (68 and 58%, respectively), as
well as
root and shoot dry weight (50 and 66%,
respectively) compared to those of the infected control plants (Table 3). However,
treatment with KSU-110
or compost alone also significantly (P
< 0.05) improved the growth of pathogen-infected
plants (Table
3). Regardless of
the presence or absence of FOL-30, the combined effect of KSU-110 + organic was
synergistic (SF > 1) in most plant growth measurements (Table
3).
Table 2: The effects of Bacillus subtilis
strain KSU-110 and organic compost applied alone or in combination on tomato wilt incidence, foliar symptoms, and discoloration severity
caused by the Fusarium wilt pathogen under greenhouse
conditions
Treatments |
Wilt
incidence (%)a |
(%CE)b |
Foliar
symptoms (%)a |
(%CE)b |
Discoloration
(%)a |
(%CE)b |
FOL
(infected control) |
92.4
a |
- |
50.0
a |
- |
48.2 a |
- |
FOL
+ compost |
75.8
b |
17.9 |
38.0
b |
24.0 |
29.5
b |
38.8 |
FOL+
KSU-110 |
56.1
c |
39.3 |
24.8
c |
50.4 |
26.7
b |
44.6 |
FOL+
compost + KSU-110 |
26.4
d |
71.4 |
18.3 c |
63.4 |
15.2
c |
68.5 |
Synergism
factor c |
1.43 |
1.02 |
1.05 |
a
Each value represents the average of two experiments with 15 replicates for
each treatment per experiment
b The control efficiency (%CE) was calculated
according to the following formula: [(D1 – D2)/D1]
× 100; where, D1 and D2 are the disease measurements
of the control and treated plants, respectively
c The synergism
factor (SF) was estimated using the following formula: SF = (Pobs /Pexp);
where, Pobs and Pexp
are the observed and expected protection efficiency achieved by the
combined application, respectively
- Values
in each
column followed by the same letter are not significantly different at P < 0.05 according to the LSD test
Activity of defense
enzymes
Infection of tomato
plants with the wilt pathogen resulted in significant increases in POD and PPO
enzyme activities (Fig. 3). The activities of POD (1.5- to 2.2-fold increases in
absorbance per minute per gram of root tissue) and PPO (2.4- to 2.8-fold increases in absorbance per min per gram of root tissue) significantly (P < 0.05)
increased in infected plants (Fig. 3). The activities of both enzymes were greater in KSU-110-
and/or compost-treated tomato plants than
in the non-treated, infected plants (Fig. 3). Treating tomato plants with KSU-110 + compost resulted in significantly
(P < 0.05) higher
POD (1.3- to 1.45-fold increases in absorbance) and
PPO (1.1- to 1.26-fold increases in absorbance) activities
than those in
plants treated with FOL-30 only (Fig. 3).
Monitoring
of FOL-30 and KSU-110 in the tomato rhizosphere
Fig. 2:
Dual culture assay of B. subtilis strain
KSU-110 and FOL-30 on PDA after
6 days of incubation at 28 ± 1°C (B). The control B-1 plate was inoculated only
with FOL-30.
Plate B-2 shows the antagonistic action of KSU-110
against FOL-30
Fig.
3: Changes in peroxidase (POD) (A) and polyphenol oxidase
(PPO) (B) activities
in root tissues of FOL-infected tomato plants treated with Bacillus subtilis strain KSU-110 and
organic compost, applied either singly or in combination at 15, 30, and 45 days
after transplanting. Each bar represents the average of two
experiments with three replicates per treatment per experiment. Bars with the same letter are
not significantly different at P < 0.05 according to the LSD
test. Error bars represent the standard deviations of the mean
KSU-110
efficiently colonized the tomato rhizosphere and persisted at high levels for
up to 45 DAT (range
from 9.7 × 104
to 12.3 × 104 cfu g−1 of
rhizosphere soil at 45 DAT; Table 4).
However, the highest level of KSU-110 colonization occurred in the composted
soil (Table 4). The pathogen population increased over time in the FOL-30-only infested
(control) soil (from 2.2 × 105 to 5.0 × 105 cfu
g−1 of rhizosphere soil; Table 4).
At 45 DAT, the FOL-30 populations were significantly reduced (P < 0.05) by
94–99.6% in the tomato rhizosphere treated with KSU-110 and/or organic compost compared to that in soil treated only with FOL-30 (Table
4). The FOL-30 population
decreased in the
soil of plants treated with KSU-110, the population of which increased markedly over time (Table
4). In terms of FOL
reduction efficiency, the mean synergy factor calculated over study
intervals was 0.98 (Table 4). This value did not significantly differ according to the one-tailed t
test (P > 0.05).
Field
experiments
The
greatest protection against wilt disease was noted in tomato plants treated
with a combination of KSU-110 and organic compost, for which the disease incidence, foliar
symptom severity, and internal stem discoloration were reduced by 60, 67 and
56%, respectively (Table 5). The same application led to significant increases (P < 0.05) in root
and shoot length
(44 and 55%,
respectively), as well as root and shoot dry weight (66 and 84%, respectively),
compared to those of the non-treated control (Table 6). Application of either KSU-110
or compost alone
was next in degree of effectiveness, significantly suppressing wilt disease and
improving plant growth (P < 0.05; Tables
5 and 6). In
general, the combined KSU-110 + organic compost treatment resulted in
synergistic effects (SF > 1) in the control of wilt disease and promotion of
tomato growth (Table 5 and 6).
Discussion
Selecting
native PGPR strains that are well adapted to Saudi ecosystems is a requisite step towards improving the efficacy of managing tomato wilt
disease under organic farming conditions. In the present study, we identified 20 rhizobacterial strains from the tomato rhizosphere and screened them
for their antagonistic potential against FOL-30 in vitro. All
rhizobacterial strains had significant antifungal activity against
the wilt pathogen and inhibited
its growth. B. subtilis strain KSU-110 had the highest antagonistic activity against FOL-30. This strain also induced distortions
and deformations in the mycelia of the pathogen, including increased hyphal
branching, swelling, and cytoplasm collapse. The antagonistic responses observed in the in vitro
tests suggested that the selected KSU-110 strain could release antifungal
substances that restricted pathogen growth. Direct antagonism of pathogenic
fungi because of antibiosis (e.g., antibiotics, lytic enzymes, and
volatile organic compounds) is one of the biocontrol mechanisms used by the
soil Bacillus strains (Ahemad and Kibret 2014; Grobelak et al.
2015). This could provide a potential basis for selecting antagonistic strains
for biological control under field conditions (Bubici
et al. 2019).
Table 5: The effects of Bacillus subtilis
strain KSU-110 and organic compost applied alone or in combination on tomato wilt incidence, foliar symptoms, and discoloration severity
caused by the Fusarium wilt pathogen under field
conditions
Treatments |
Wilt incidence (%)a |
(%CE)b |
Foliar symptoms (%)a |
(%CE)b |
Discoloration (%)a |
(%CE)b |
FOL (infected control) |
66.0
a |
- |
32.6
a |
- |
25.5
a |
- |
FOL + compost |
50.5
b |
23.4 |
20.0 b |
38.7 |
19.3
b |
24.3 |
FOL+ KSU-110 |
39.6
c |
40.0 |
19.0 c |
42.0 |
16.4 c |
36.0 |
FOL+ compost + KSU-110 |
26.7
c |
59.5 |
10.7
d |
67.2 |
11.3
d |
55.7 |
Synergism factorc |
1.1 |
1.05 |
1.1 |
a Each
value represents the average of two experiments with 15 replicates for each
treatment per experiment
b The control efficiency (%CE) was calculated
according to the following formula: [(D1 – D2)/D1]
× 100; where, D1 and D2 are the disease measurements
of the control and treated plants, respectively
c The
synergism factor (SF) was estimated using the following formula: SF = (Pobs /Pexp);
where, Pobs and Pexp
are the observed and expected protection efficiency achieved by the
combined application, respectively
- Values in each column followed by the
same letter are not significantly different at P < 0.05
according to the LSD test
Table 6: The
effects of Bacillus
subtilis strain KSU-110 and organic compost applied
alone or in combination on the length
and dry weights of both root and shoot systems of
tomato plants infected with the Fusarium wilt
pathogen under field conditions
Treatments |
Length (cm)a |
Dry weight (g)a |
||||||
Root |
(%IM)b |
Shoot |
(%IM)b |
Root |
(%IM)b |
Shoot |
(%IM)b |
|
FOL (infected control) |
10.7
c |
- |
37.8
c |
- |
3.7
b |
- |
12.5
d |
- |
FOL + compost |
14.5
ab |
35.4 |
50.8 b |
34.4 |
5.9 b |
60.5 |
19.9
b |
37.3 |
FOL+ KSU-110 |
13.4
b |
24.9 |
48.5
b |
28.2 |
4.8ab |
29.7 |
16.2
c |
29.6 |
FOL+ compost + KSU-110 |
15.5
a |
44.2 |
58.5
a |
54.7 |
6.1
a |
65.7 |
23.0
a |
83.6 |
Synergism factorc |
0.86 |
1.04 |
0.92 |
1.49 |
a
Each value represents the average of two experiments with 15 replicates for
each treatment per experiment
b The calculation of improvement
efficiency (%IM) was according to the following formula: [(C -
T)/C] × 100, where C and T are the growth parameters of control
and treated plants, respectively
c The
synergism factor (SF) was estimated using the following formula: SF = (IMobs /IMexp);
where, IMobs and IMexp are the observed and
expected improvement
efficiency achieved by the combined application, respectively
- Values in each column followed
by the same letter are not significantly different
at P < 0.05 according to the LSD test
The addition of
organic compost to the soil provided an environment-friendly method of managing
soil-borne diseases, including FOL (Dukare et al. 2011; Hadar
and Papadopoulou 2012; Bahramisharif
et al. 2013; Gava and Pinto 2016). In the present study, we evaluated the hypothesis that the integrated combination of
KSU-110 with compost could enhance the biological control efficacy against FOL
because of additive or synergistic interactions. Our results showed that the
application of KSU-110 and organic compost applied alone or in combination,
significantly
(P < 0.05) reduced
disease development under greenhouse and field
conditions. This suggested that the suppressive effects of KSU-110
detected in the in
vitro antagonistic assays were linked to the management of Fusarium wilt
disease in tomatoes in vivo. Interestingly, mixing
KSU-110 with organic compost caused the highest reduction in DI and DS compared
to that of the individual applications even under field conditions. Moreover, the
observed control efficiency in tomato plants treated with KSU-100 + compost was
higher than that expected (SF > 1), indicating a synergistic
effect. This
suggests that the application of KSU-110 + compost represents a promising option
for organic growers of tomatoes. The synergistic disease suppression elicited by this
combination could result from nutrients in the compost that enhance rhizobacterial
competitive ability,
or from the presence of specific agents that evoke an antibiosis effect or
induce resistance against pathogen infection (Abbasi et al. 2002; Huang et al. 2011).
Moreover, volatiles
released during manure decomposition, such as sulfur-containing compounds,
organic acids, and ammonia, may increase disease suppression (Coventry et al.
2006).
Table 3: The effects of Bacillus subtilis strain KSU-110 and organic compost applied
alone or in combination on the length
and dry weights of both root and shoot systems in
tomato plants regardless of the presence or absence of the Fusarium
wilt pathogen under greenhouse conditions
Treatments |
Length (cm)a |
Dry weight (g)a |
||||||
Root |
(%IM)b |
Shoot |
(%IM)b |
Root |
(%IM)b |
Shoot |
(%IM)b |
|
Healthy control |
7.1
bc |
- |
22.6
c |
- |
1.30
bc |
- |
3.90
cd |
- |
Compost |
8.7
a |
22.5 |
28.2
b |
24.8 |
1.60
a |
23.0 |
5.10
b |
30.8 |
KSU-110 |
8.0
a |
12.7 |
26.4 b |
16.8 |
1.40
ab |
07.7 |
4.70
bc |
20.5 |
KSU-110 + compost |
9.1
a |
28.2 |
31.4
a |
38.9 |
1.70
a |
30.8 |
6.11
a |
56.7 |
Synergism factorc |
0.89 |
1.05 |
1.1 |
1.26 |
||||
FOL (infected control) |
3.7
e |
- |
10.3
f |
- |
0.68
e |
- |
1.93
g |
- |
FOL + compost |
5.0
d |
35.1 |
13.6 e |
32.0 |
0.97 d |
42.6 |
2.78
ef |
44.0 |
FOL+ KSU-110 |
4.9
d |
32.4 |
13.0
e |
26.2 |
0.88
de |
29.4 |
2.20
fg |
14.0 |
FOL+ compost + KSU-110 |
6.2
c |
67.6 |
16.3
d |
58.3 |
1.02
cd |
50.0 |
3.20
cd |
65.8 |
Synergism factorc |
1.21 |
1.17 |
0.85 |
1.27 |
a Each
value represents the average of two experiments with 15 replicates for each
treatment per experiment
b The improvement efficiency (%IM)
was calculated using the following formula: [(C - T)/C] ×
100; where, C and T are the growth parameters of control and treated
plants, respectively.
Values in normal font are the effects of different bio-organic treatments on
plant growth parameters compared with those in the healthy control (no FOL
stress). Values in bold font are the effects of different bio-organic
treatments on plant growth parameters compared with those in the infected
control (under FOL stress)
c The synergism
factor (SF) was estimated using the following formula: SF = (IMobs /IMexp);
where, IMobs and IMexp are the observed and
expected improvement
efficiency achieved by the combined application, respectively
- Values in each column followed
by the same letter are not significantly different
at P < 0.05 according to the LSD test
Table 4: Rhizosphere soil populations
of Bacillus subtilis strain KSU-110 and Fusarium
wilt pathogen strain FOL-30 (cfu g−1 of rhizosphere
soil) sampled in the vicinity of tomato plants at 15,
30, 45 days after transplantation (DAT) under greenhouse conditions
Treatments |
Population of KSU-110a |
Population of FOL-30a |
|||||||
15 DAT |
30 DAT |
45 DAT |
15 DAT |
(%RE)b |
30 DAT |
(%RE)b |
45 DAT |
(%RE)b |
|
KSU-110 |
6.0 ×
104 e |
7.7 × 104 d |
9.8 × 104 c |
- |
|
- |
|
- |
|
KSU-110 + compost |
7.7 × 104 d |
10.0× 104 c |
12.3 × 104 a |
- |
|
- |
|
- |
|
FOL |
- |
- |
- |
2.2 × 105 C |
- |
3.3
× 105 B |
- |
5.1
× 105 A |
- |
FOL + compost |
- |
- |
- |
3.1
× 104 D |
85.9 |
3.5
× 104 D |
89.4 |
3.2
× 104 D |
93.7 |
FOL + KSU-110 |
4.5 × 104 f |
6.5× 104 e |
9.7× 104 c |
3.0
× 104 D |
86.4 |
3.2
× 104 D |
90.3 |
3.4
× 104 D |
93.3 |
FOL + compost + KSU-110 |
6.2
× 104 e |
9.6
× 104 c |
11.4
× 104 b |
1.8
× 104 E |
91.8 |
2.3
× 103 F |
99.3 |
2.0
× 103 F |
99.6 |
Synergism factorc |
0.98 |
a
Each value represents the average of two experiments with four replicates for
each time point
per experiment
b The pathogen reduction efficiency (%RE) was calculated
using the following formula: [(C - T)/C] × 100; where, C
and T are the FOL populations in infected control and treated rhizosphere soils, respectively
c The mean synergism factor (SF) was estimated
using the following formula: SF = (Robs /Rexp);
where, Robs and Rexp
are the observed and expected FOL reduction efficiency achieved by the combined
application at 15, 30, and 45 DAT
- Values followed by the same
lowercase or uppercase letters are not significantly different at P < 0.05 according to the LSD test
In addition to
suppressing wilt disease, the application of KSU-110 and
compost, either separately or in combination, had a positive growth-promoting effect on tomato
seedlings under both greenhouse and field conditions. Application of KSU-110
and organic compost
led to the highest (P < 0.05) increase in tomato growth parameters,
irrespective of the presence or absence of the wilt pathogen. These effects may
be attributed to the ability of Bacillus strains to promote plant growth and health by enhancing nutrient uptake
from the soil by plant roots, as well as the synthesis of plant hormones (Grobelak et al. 2015). Moreover, the addition of
organic compost to the soil probably improves the nutritional status of the
plants and contributes to soil health through increased soil microbial activity
(Abbasi et al. 2002). Together, these factors could explain the
remarkably synergetic effects of the combined treatment on the growth
parameters of tomato plants. In fact, improved growth enhances the resistance
of plants to the detrimental effects of infection-related stress while
promoting plant health and decreasing harvest losses (Ahemad and Kibret 2014; Grobelak et al. 2015).
Our results showed
that POD
and PPO activities were higher in tomato plants treated with
different bioorganic compounds than that in the non-treated infected plants.
Furthermore, their activities were remarkably higher in plants treated with
KSU-110 + organic compost than in those receiving either treatment alone. In
fact, POD is a key enzyme that participates in lignin biosynthesis. It also catalyzes
reactive oxygen species generated in plant tissues caused by pathogen attack (Caverzan et al. 2012). Furthermore, PPO is
another plant defense enzyme responsible
for the oxidation of phenolic compounds into anti-microbial quinones in plant
tissues attacked by plant pathogens, thereby inducing disease resistance (Arora
and Bajaj 1985). Therefore, integrated application of KSU-110 + compost had
likely induced defense responses of POD and PPO that might have increased
tomato plant tolerance against FOL stress. These results are consistent with those of Krause et al.
(2003) and Kloepper et al.
(2004) who revealed that the application of Bacillus
strains and
compost amendments induced systemic disease resistance in affected plants.
Determining the
population density of both biocontrol agents and pathogens in the plant
rhizosphere is important in predicting the success of biological control
(Leandro et al. 2007). Notably, KSU-110 could efficiently colonize the
tomato rhizosphere and persist at a high level in the treated soils. In fact, extensive colonization of the
plant rhizosphere by inoculant rhizobacteria was essential for its biocontrol
and growth-promoting activities (Bouizgarne 2013; Abdallah et
al. 2018). We showed that plants with reduced wilt disease
incidence had an increased KSU-110 population and decreased
FOL-30 population. Importantly,
mixing KSU-110 + organic compost resulted in additive activity in the reduction
of the FOL-30 population compared with that of their separate application. Moreover,
the KSU-110 could be was attributed to the additional nutrients supplied by the
amended compost. This suggests that competition for nutrients
and space may be the key mechanism for biocontrol of
the pathogen by KSU-110. The additional organic
substrates enhanced the
competitive action of KSU-110 and its survival in the tomato
rhizosphere. Taken together, these findings may explain why the combined
treatment was more effective in decreasing wilt disease than the application of
KSU-110 alone. The
results are consistent with those of previous studies showing that compost
amendments positively enhanced microbial biomass and activity in the plant
rhizosphere and resulted in a deleterious competitive environment for pathogens
(Hadar and Papadopoulou
2012; Bahramisharif et al. 2013).
Conclusion
Our findings highlight the
advantages of deploying native antagonistic bacteria for crop health and
management in arid regions. The application of KSU-110
decreased the FOL-30 population in the tomato rhizosphere and hence
could be a potential biological control agent against FOL.
Furthermore, the combination
of KSU-110 and compost greatly enhanced disease suppression and enhanced tomato
growth under both greenhouse and field conditions. Further evaluations are needed
to verify the efficacy of combining KSU-110 with compost
against diverse soil-borne pathogens under a wider range of field conditions, before
commencing any large-scale application.
Acknowledgments
We thank the Deanship of
Scientific Research at King Saud University for funding this work through
research group no. RG-1440-029.
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