AEM Accepted Manuscript Posted Online 30 October 2015 Appl. Environ. Microbiol. doi:10.1128/AEM.02662-15 Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Ali et al, Appl. Environ. Microbiol. 1
Ex vivo application of secr eted metabolites pr oduced by soil-inhabiting Bacillus spp.
2
efficiently contr ols foliar diseases caused by Alternaria spp
3 4
Gul Shad Ali#, Ashraf El-Sayed, Jaimin S. Patel*, Kari B. Green¶, Mohammad Ali, Mary
5
Brennan and David Norman
6 7
Mid-Florida Research and Education Center and Department of Plant Pathology, University of
8
Florida/Institute of Food and Agricultural Sciences, Apopka, Florida, USA
9
¶ Department of Chemistry, University of Florida, Gainesville, Florida 32611, USA
10 11
Running Head: Control of Alternaria by Bacillus metabolites
12 13
#
Address correspondence to: Gul Shad Ali, E-mail:
[email protected]
14 15
*
16
Food and Agricultural Sciences, Homestead, Florida, USA
Present address: Tropical Research and Education Center, University of Florida/Institute of
17
1
Ali et al, Appl. Environ. Microbiol. 18
Abstr act
19
Bacterial biological control agents (BCA) are largely used as live products to control plant
20
pathogens. However, due to variable environmental and ecological factors, live BCA usually fail
21
to produce desirable results against foliar pathogens. In this study, we investigated the potential
22
of cell-free culture filtrates of 12 different bacterial BCA isolated from flower beds for
23
controlling foliar diseases caused by Alternaria spp. In vitro studies showed that culture filtrates
24
from two isolates belonging to Bacillus subtilis and B. amyloliquefaciens displayed strong
25
efficacy and potencies against Alternaria spp. The antimicrobial activity of the culture filtrate of
26
these two biological control agents was effective over a wider range of pH (3.0 – 9.0), and was
27
not affected by autoclaving or proteolysis. Comparative LC–MS analyses showed that a
28
complex mixture of cyclic lipopeptides, primarily of the fengycin A and fengycin B families
29
were significantly higher in these two BCAs compared to inactive Bacillus spp. Interaction
30
studies with mixtures of culture filtrates of these two species revealed additive activity
31
suggesting that they produce similar products, which were confirmed by LC–MS/MS analyses.
32
In in planta pre- and post-inoculation trials, foliar application of culture filtrates of B. subtilis
33
reduced lesion sizes and lesion frequencies caused by A. alternata by 68 – 81%. Taken together,
34
our studies suggest that instead of live bacteria, culture filtrates of B. subtilis and B.
35
amyloliquefaciens can be applied either individually or in combination for controlling foliar
36
diseases caused by Alternaria species.
37
Keywor ds: Antifungal activity, BCA, fengycin, antimicrobial peptides, LC-MS.
38 39
2
Ali et al, Appl. Environ. Microbiol. 40
Intr oduction
41
Many species in the genus Alternaria cause significant yield and quality losses in food and
42
ornamental crops (1). These species primarily attack aerial plant parts including foliage, fruits
43
and stems, and cause a variety of symptoms ranging from necrotic leaf spots to enlarged blighted
44
shoots eventually resulting in defoliation, and loss in yield and quality. Alternaria diseases could
45
be managed with a combination of cultural practices, fungicides and, if available, genetic
46
resistance. Since many crop cultivars lack sufficient resistance to Alternaria spp., fungicide
47
sprays are the primary means of controlling Alternaria diseases (1). However, loss in the
48
efficacy of several commonly used fungicides for controlling Alternaria spp. has been reported
49
(2-6). Loss of effective fungicides requires discovery and development of new and safe
50
alternative chemicals. Although fungicides with newer chemistry are promising, their
51
introduction into crop production systems is slow and resistant field isolates of the pathogen
52
usually appear very quickly within a few seasons of the introduction of a new fungicide (5, 7, 8).
53
As with many other plant pathogens, in most cases fungicide resistance in Alternaria spp. has
54
been attributed to single site mutations in the target genes (e.g. 9, 10, 11). Therefore, finding
55
multisite-acting fungicides that are difficult to break down and are relatively stable might
56
provide a sustainable mean of control. Biological control agents (BCAs) or the products derived
57
thereof could be used as a sustainable alternative or as a complement to fungicides in integrated
58
pest management programs.
59
Many bacterial BCAs are currently being used for controlling plant pests and diseases
60
(reviewed in 12, 13). Several Bacillus species have been developed into commercial products
61
for controlling a wide range of diseases caused by fungi and oomycetes (13-16). Biological
62
control activities of most bacterial BCAs have been attributed to cell wall degrading enzymes,
3
Ali et al, Appl. Environ. Microbiol. 63
antimicrobial peptides, cyclic lipopeptides such as iturins, fengycins, surfactins, low molecular
64
weight metabolites, volatile organic compounds and induction of systemic resistance in host
65
plants (13, 17-25). Iturins, surfactin and fengycins are extensively studied and using knock out
66
mutants and purified extracts have been associated with antimicrobial activities. These peptides
67
are distinguished from each other by the types and number of amino acids, and in the length of
68
fatty acid side chains. A combination of ring amino acids and fatty acid side chains provide
69
tremendous structural diversity, which likely accounts for the broad spectrum antimicrobial
70
activity of culture filtrates of Bacillus spp. Mass spectrometry of iturins and surfactins display
71
masses in the m/z range of 1000 – 1200, whereas fengycins are in the m/z range of 1400 – 1600
72
(18, 24, 26-28). Fengycins, surfactins and iturins also display differential activity against
73
different plant fungal pathogens, most likely due to differences in lipid composition of the target
74
fungi (29). Different Bacillus spp. produce a complex mixture of these peptides, and depending
75
the target fungal pathogen, it is suggested that these peptides act together in compromising
76
membrane permeability (30).
77
Bacterial BCAs differ in their genetic make up, ecological and adaptation characteristics,
78
which define their biological potential and antimicrobial activities. Previously we have isolated
79
and characterized 129 different isolates of soil-inhabiting bacteria from diverse bedding plants
80
(31). Based on fatty acid analyses, these isolates were classified into fourteen different species
81
in six different genera. Since they were isolated from diverse host plants, it is possible that they
82
might display antimicrobial activity against different plant pathogens.
83
Most research on biological control agents has focused on using live bacteria. However,
84
success and survival of BCAs depends on establishment, proliferation and colonization, and
85
persistence in the plant and soil environment (32). These survival factors are in turn dependent
4
Ali et al, Appl. Environ. Microbiol. 86
on temperature, humidity, physical characteristics of soil such as pH, soil porosity and
87
composition, and light quality and intensity (33, 34). Dependence on these environmental
88
factors is often cited as one of the major reasons for inconsistency in the performance of BCAs
89
(35). To circumvent these issues, it would be highly useful if the bioactive compound(s) were
90
extracted, characterized and used directly as soil drenches or sprays instead of live bacteria. In
91
this report, we showed that the extracellular culture filtrate of some of these bacteria contain
92
substantial quantities of bioactive ingredient(s). We found that the active ingredient(s) maintains
93
fungicidal activity after exposure to high temperature and proteolysis indicating that after
94
production they could be easily stored, transported and marketed with less concerns about their
95
shelf-life. Mixtures of fungicides have several advantages including extended control spectrum,
96
reduced fungicide resistance, and potential synergism. Antimicrobial compounds when mixed
97
may display synergistic (greater than expected), additive (one compound could be replaced by
98
another with similar effects) or antagonistic (lesser than expected) activities (36, 37). The effect
99
of interaction of cell-free culture filtrates of BCAs has not been studied extensively. These
100
studies are important for extending the biological control spectrum of rhizosphere BCAs to
101
above ground plant parts. In addition, such investigations are also essential for discovering new
102
antimicrobials with higher potencies and efficacies. In this study, we tested the hypothesis that
103
the culture filtrates of soil-inhabiting BCAs can be used for controlling foliar diseases. The
104
objectives of this research were: 1) To screen culture filtrates of different bacterial species for
105
antimicrobial activity against Alternaria spp. in vitro and in planta. 2) To determine the stability
106
of culture filtrates to heat, proteolysis and pH. 3) To determine level of synergism in the culture
107
filtrates of different BCAs. 4) To identify bioactive lipopeptides in the culture filtrates of BCAs
108
using LC-MS and LC-MS/MS analyses.
5
Ali et al, Appl. Environ. Microbiol. 109
Mater ials and methods
110
Biological contr ol agents and pr epar ation of cell-fr ee cultur e extr act
111
Information about biological control agents used in this study is summarized in Table 1. All
112
bacterial strains were initially revived from glycerol stocks maintained at -80oC on NYG agar
113
(0.5% trypton peptone, 0.3% yeast extract, 2% glycerol, 1.5% Bacto-agar) at 28˚C. Single
114
colonies from each BCA strain were first grown in 5 ml LB medium in test tubes at 28oC in a
115
shaker incubator until OD600 reached approximately 0.6 – 0.8. One ml of this culture was added
116
to 50 mL LB media contained in a 250 mL flask and incubated at 28oC in a shaker incubator
117
(220 rpm) for 24 hours. At this point all cultures grew to early stationary phase (~OD600 = 3.0).
118
Cells were pelleted by centrifugation at 5000x g for 10 minutes at room temperature. Supernatant
119
was filtered through a 0.20 µm filter and stored at 4oC until further use.
120
Tar get fungi and their cultur e
121
Three major Alternaria spp., A. alternata, A. solani and A. brassicicola, which infect and cause
122
significant yield loss in many crops were used as target fungi. Isolates of A. alternata, A. solani
123
and A. brassicicola were recovered from infected impatiens, potato and Arabidopsis plants,
124
respectively. All isolates were cultured on PDA under continuous light at 25oC for four days.
125
Spores were resuspended in potato dextrose broth (PDB, Difco) to a final concentration of 3 x
126
104 spores mL-1.
127
Anti-fungal assays
128
In vitro fungal growth inhibition assays were performed in a 96-well microtiter plates as
129
described previously (38). Briefly, culture filtrates of BCAs were diluted appropriately (10% to
6
Ali et al, Appl. Environ. Microbiol. 130
0.01%) in LB according to the goals of an experiment, and added to the wells of a 96-well flat-
131
bottom microtiter plate (100 µL/well). One hundred µL of the conidial suspension (3 x104
132
spores mL-1 in PDB) was added to each well. Each treatment was replicated four times and each
133
experiment was repeated at least two times. Plates were wrapped with Parafilm and incubated at
134
25oC under continuous light. Absorbance (OD600) of each plate was read with the Synergy H1
135
Hybrid Multi-mode plate reader (BioTek®) at the beginning (0 hour) of an experiment and 24
136
hours after incubation. All plates were routinely checked at the beginning and end of
137
experiments for any bacterial contamination or turbidity with naked eye and under an inverted
138
microscope. Net mycelial growth was calculated by subtracting absorbance at the 0 hour from
139
absorbance at the 24-hr interval. Normalized net growth (percent of untreated control) was
140
determined by dividing net growth in each treatment by net growth in untreated control.
141
Dose-r esponse Cur ve fitting and statistical analyses
142
Dose-response analyses were conducted using 11 two-fold serial dilutions (10 to 0.01%) in a
143
microtiter plate using OD600 absorbance as described above. Dose-response data were fitted with
144
the following 4-paramerter logistic (4PL) curves using the Prism 6.0 software (GraphPad
145
Software, Inc.).
=
+ ( 1 + 10 (
−
)
)∗
146
In the equation, Y is normalized net growth, Basal and Maximal are the basal and maximal
147
growths expressed in units of Y, respectively, X is the log [culture filtrate (CF) dilutions].
148
Statistical analyses of goodness-of-fit of curves and comparison of curves in response to
149
different treatments were performed using Prism 6.0. IC50 values, define as CF dilution required
150
for 50% growth inhibition, were calculated from the fitted 4PL curves.
7
Ali et al, Appl. Environ. Microbiol. 151
Inter action of cultur e filtr ates of B. subtilis (B11-128) and B. amyloliquefaciens (B11-144)
152
To determine if B11-128 and B11-144 interact with each other additively, synergistically or
153
antagonistically in inhibiting A. alternata, CFs of these two isolates were tested alone and in 1:1
154
(v/v) mixtures at seven different concentrations: Concentrations for B11-128 and B11-144 alone
155
were 2, 1, 0.3, 0.2, 0.14, 0.1 and 0.02%. A corresponding 1:1 mixture series consisted of B11-
156
128+B11-144 at 1%+1%, 0.5%+0.5%, 0.15%+0.15%, 0.1%+0.1%, 0.07%+0.07%,
157
0.05%+0.05% and 0.01%+0.01%. The expected percent mycelial growth inhibitions (Iexp) were
158
determined using the following formula according to Abbott (39): Iexp =X+Y-(XY/100), where X
159
and Y are the percent inhibitions provided by B. subtilis (B11-128) and B. amyloliquefaciens
160
(B11-144), respectively, when used alone. Levels of interactions were determined as IR =
161
Iobs/Iexp, where Iobs is the experimentally-determined observed inhibition provided by mixtures of
162
B. subtilis (B11-128) and B. amyloliquefaciens (B11-144) culture filtrates. IR ratios of 0.5 – 1.5
163
were considered as additive, >1.5 as synergistic and 10
–
Bacillus subtilis
B11-128
Impatiens sp.
0.21b
2.14
(0.15 – 0.29)
(1.16 – 3.95)
B11-144
Bacillus
Lantana sp.
amyloliquefaciens
b
MIC c
0.33
1.40
(0.21 – 0.51)
(0.63 – 3.21)
Bacillus mycoids
B156
Salvia sp.
9.12
–
Bacillus pumilus
B182
Coleus
8.87
–
Bacillus circulans
B9
Impatiens sp.
>10
–
Lycinibacillus spaericus
B65
Impatiens sp.
9.34
–
Bacillus freudenreichii
B68
Lantana sp.
>10
–
Bacillus cereus
B147
Marigold
>10
–
Brevibacillus
B173
Salvia sp. >10
laterosporus Bacillus brevis
–
B194
Pentas sp.
Azoxystrobin R d
(Heritage ) a
>10
–
0.023
0.09
(0.017 – 0.032)
(0.053 – 0.21)
identification of BCA (biological control agent) strains has been reported before (31). IC50 values, expressed as percent amount of bacterial culture filtrates in the assay solution (v/v), were predicted from logistic curves fitted to the dose-response data of B11-128 and B11-144 culture filtrate tested against A. alternata in vitro; IC50 values for the remaining isolates were estimated from the data of Figure 1. c MIC (Minimum inhibitory concentrations) were considered minimum concentrations that completely inhibited growth. These values roughly corresponded to IC90 values, which were predicted from the logistic curves. d Heritage, a broad spectrum fungicide consisting of 50% Azoxystrobin as active ingredient was used as a positive control. b
670
29
Ali et al, Appl. Environ. Microbiol. 671 Table 2: Effect of heat and proteinase treatment on the antifungal activity 672 (IC50) of culture filtrates of B11-128 and B11-144 Cultur e
Pr oteinase
filtr ate
Contr ol
Autoclaved
tr eated
B11-128
0.22a
0.26
0.36
(0.19 – 0.24)
(0.22 – 0.31) b
B11-144
(p>0.48)
(p >0.51)b
0.39
0.44
0.41
(0.24 – 0.52)
(0.30 – 0.68) b
(0.31 – 0.52) (p>0.98)b
(p>0.67) a
(0.26 – 0.51)
Data shown are IC50 means (95% confidence intervals are in
parentheses), expressed as percent concentration of bacterial culture filtrates in the assay solution (v/v), which were predicted from logistic curves fitted to the dose-response data of each culture filtrate tested against A. alternata in vitro. b
p values are for comparing means of heat or proteinase treatments to
untreated control means.
30
Ali et al, Appl. Environ. Microbiol. 673 Table 3: Interaction of culture filtrates of B. subtilis (B11-128) 674 and B. amyloliquefaciens (B11-144) in inhibiting A. alternata IRc
Ratios (B11-128+B11-144)a
b
1.0% + 1.0%
b
(Iobs/Iexp)
69.8
88.4±1.11
1.3
0.5%+0.5%
57.8
41.4±1.64
0.7
0.15%+0.15%
43.8
27.3±0.63
0.6
0.1%+0.1%
27.8
15.8±0.96
0.6
0.07%+0.07%
9.8
4.9±0.79
0.5
0.05%+0.05%
4.9
2.3±0.13
0.5
a
Iexp
Iobs
CFs were mixed in equal proportions at the indication
concentration (%). b
Iexp (Expected percent inhibition assuming an additive
interaction) was calculated according to the following equation (39): Iexp =X+Y-(XY/100), where X and Y are the percent inhibition provided by B. subtilis (B11-128) and B. amyloliquefaciens (B11-144) when used alone. Iobs is the observed inhibition provided by mixtures of B. subtilis (B11128) and B. amyloliquefaciens (B11-144) culture filtrates. c
IR (interaction ratios) > 1.5 represent synergistic, < 0.5
antagonistic and between 0.5 to 1.5 as additive (36, 42)
31
Ali et al, Appl. Environ. Microbiol. 675 676
Table 4: List of cyclic lipopeptides identified in B11-128 and B11-144 using LC-MS/MS.
Identified lipopeptide
B11-144 ESI/MS (m/z) Diagnostica B11-128 ESI/MS (m/z) RT:23-26 fragment RT:23-26 min min ions (m/z)
Types of fatty acids & amino acids at position 6
677
Fengycin A – 1450.94 966, 1082 (C15, 6-Ala) Fengycin A 1462.02 1462.17 966, 1082 (C16, 6-Ala) Fengycin A 1463.95 1464.15 966, 1082 (C16, 6-Ala) Fengycin A – 1465.89 966, 1082 (C16, 6-Ala) Fengycin A 1478.06 1478.26 966, 1082 (C17, 6-Ala) Fengycin A – 1480.77 966, 1082 (C17, 6-Ala) Fengycin B 1490 1490.06 995, 1109 (C16, 6-Val) Fengycin B 1491.86 1492.71 995, 1109 (C16, 6-Val) Fengycin B 1506.12 1506.25 995, 1109 (C17, 6-Val) Fengycin B 1507.8 1507.76 995, 1109 (C17, 6-Val) a Diagnostic fragments are based on published reports (21, 26).
678
Representative LC-MS/MS peaks are shown in Table S1 in supplemental file 1.
679
RT, retention time
32
Peak number according to Figure 6G a b b b c c d d e e
Ali et al, Appl. Environ. Microbiol. 680
FIGURE LEGENDS.
681
Figur e 1. Screening of soil-inhabiting bacterial species for controlling Alternaria alternata in
682
vitro
683
(A) Effect of different dilutions, 10%, 1% and 0.1%, of Culture Filtrates (CF) of bacterial
684
isolates indicated on the X-axis on the in vitro growth of A. alternata. Growth was normalized
685
to growth in no-CF control considered as 100 percent. Azoxystrobin (Heritage®), a broad
686
spectrum fungicide was used as a positive control, and its 10%, 1% and 0.1% levels correspond
687
to 5.0, 0.5 and 0.05 µg mL-1 active ingredient in the assay solution. ***, and ** indicate
688
statistically significant differences at p0.1). Data shown are means ± s.e.m (n = 4).
717 718
Figur e 4. Interaction of B. subtilis (B11-128) and B. amyloliquefaciens (B11-144) culture
719
filtrates in controlling A. alternata.
720
(A) Bar graphs comparing effect of combining culture filtrates of B11-128 and B11-144 on A.
721
alternata growth. CFs of B11-128 alone, B11-144 alone and B11-128+B11-144 combined were
722
used, respectively, at the following % dilutions: A (2, 2, 1+1), B (1, 1, 0.5+0.5), C (0.3,
34
Ali et al, Appl. Environ. Microbiol. 723
0.15+0.15), D (0.2, 0.1+0.1), E (0.14, 0.07+0.07), F(0.1, 0.05+0.05), G (0.02, 0.01+0.01) .
724
Growth data were normalized to the growth in untreated control. Error bars are s.e.m. (B)
725
Micrographs showing effects of B11-128 and B11-144 used individually or in mixtures at the
726
indicated dilutions. Bar= 100 µm.
727 728
Figur e 5. In vivo control of Alternaria spp. by culture filtrates from B. subtilis (B11-128) and B.
729
amyloliquefaciens (B11-144).
730
A – D show results of detached leaf assays, whereas E shows results of whole plant assays. (A,
731
C and D) Bar graphs showing average lesion sizes caused by Alternaria spp. on poinsettia (A),
732
dieffenbachia (C) and tomato (D). (B) Photographs showing control of A. alternata on poinsettia
733
leaves. Pictures were taken 7 days post-inoculation. Culture filtrates of B11-128 and B11-144
734
significantly reduced lesion sizes. (E) Bar graphs showing number of lesions per plant in
735
response to CFs from B11-128 and B11-144. H2O→Aa, water control application followed by
736
A. alternata inoculation; LB→Aa, 2% LB control application followed by A. alternata
737
inoculation; CF→Aa, 2% culture filtrate application followed by A. alternata inoculation;
738
Aa→CF, A. alternata inoculation followed by 2% culture filtrate application; CF→Aa→CF, 2%
739
culture filtrate was applied both pre- and post-inoculation with A. alternata; Azox→Aa,
740
Azoxystrobin (HeritageR) spray followed by A. alternata inoculation. Error bars indicate
741
standard errors of means.
742 743
Figur e 6. Total ion current chromatograms of water soluble (A, B, C) and methanol soluble (D,
744
E, F) fractions of acid-precipitated lytic peptides of B. subtilis (B11-128), B. amyloliquefaciens
35
Ali et al, Appl. Environ. Microbiol. 745
(B11-144) and B. thuringiensis (B11-48). Two distinct clusters of peaks were observed at
746
retention time 12 – 20 min (Cluster 1) and 23 – 26 min (Cluster 2). Cluster 1, which was
747
observed only in water soluble fractions, displayed similar peak patterns in the bioactive (B11-
748
128, B11-144) and inactive (B11-48) strains. In contrast, cluster 2 peaks were present in the
749
bioactive culture filtrate but not in the inactive culture filtrate. (G, H) Mass spectra (m/z)
750
displaying overall distribution of water soluble cyclic lipopeptides in CFs of B. subtilis (B11-128)
751
and B. amyloliquefaciens (B11-144). The mass spectra correspond to an average of cluster 2
752
(retention time: 23 – 26 min). Prominent peaks are labeled as a – e.
36
