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Article

Characterization of Antagonist Potential of Selected Compost Bacterial Isolates (CBI) against Plant and Human Pathogens

by
Abdo Tannouri
1,2,*,
Ziad Rizk
1,
Marina Al Daccache
3,
Chantal Ghanem
1,
Valérie Azzi
1,
Rami Haddad
2,
Richard G. Maroun
2,
Zeina Hobaika
2,
Rebecca Badra
4 and
Dominique Salameh
2
1
Lebanese Agricultural Research Institute (LARI), El Metn P.O. Box 90-1965, Lebanon
2
Faculté des Sciences, Université Saint Joseph Beyrouth, Campus des Sciences et Technologies, Mar Roukos, Beirut P.O. Box 17-5208, Lebanon
3
Ecole Supérieure d’Ingénieurs de Beyrouth (ESIB), Saint-Joseph University, CST Mkalles Mar Roukos, Beirut P.O. Box 11-514, Lebanon
4
Human Link-Research Advancing Knowledge, Hazmieh P.O. Box 21211, Lebanon
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(12), 2977; https://doi.org/10.3390/agronomy12122977
Submission received: 29 October 2022 / Revised: 21 November 2022 / Accepted: 22 November 2022 / Published: 27 November 2022
(This article belongs to the Special Issue Aerobic and Anaerobic Digestion of Agro-Industrial and Livestock Wastes: A Green and Sustainable Way toward the Future)
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Abstract

:
Several fecal and enteric pathogens are present within the primary organic raw materials that are introduced to compost piles. These pathogens may compete with the existing microbiota and limit their efficiency, yielding only partial decomposition of the final compost. These pathogens also affect the process kinetics and persist in the final compost or may even regrow as a result of the declining effect of indigenous antagonistic micro-organisms. In this work, 11 indigenous bacterial isolates were selected from compost piles that were constructed from different percentages of comingled primary organic raw materials. Enzymatic, biochemical, and genetic characterization profiling of these strains was fulfilled. The top hits supplied by GenBank proved the genetic diversity of these strains, which belonged to 6 different families. This diversity, applied also at enzymatic and biochemical levels, showed the different degradation patterns of amino acids, carbohydrates, hormones, and proteins. CBI2 has been shown to be the most active isolate in the degradation of the different types of hormones and proteins from dairy products but lacks the enzymes needed for the degradation of ammonia into nitrogen. The antagonistic potential of recuperated secondary metabolites proved the total inhibition of all strains against Fusarium oxysporum and no growth limitation against Botrytis cinerea. Only the secondary metabolites of CBI1, CBI5, and CBI9 isolates showed inhibitory activity against Salmonella Typhimurium and Escherichia coli, whereas only those of CBI6 and CBI8 inhibited the growth of Salmonella Typhimurium and Listeria monocytogenes accordingly. From that finding, these strains are considered pioneering, with high potential to ensure both the efficient degradation of organic matter and the elimination of existing pathogens when applied to compost piles.

1. Introduction

Solid waste management (SWM) is a challenge in many developing countries that have gone through rapid changes over the last few decades. As a general trend, municipal solid waste (MSW) composition in developing and transition countries contains larger fractions of organic waste, which are collected in a commingled form [1]. As an example, Lebanon generates around 2.04 million tons of solid municipal waste yearly, collected as commingled waste; 52.5% of this is organic waste, of which only 15% is composted [2]. Composting is a self-heating, dynamic, and complex biochemical process, during which the successful biotransformation of organic substrates is completed by different microorganisms including bacteria and fungi [3] under controlled conditions, such as pH, air, moisture content, particle size, C:N ratio, etc. [4]. Organic compound mineralization, water evaporation, and the modification of the porosity of the medium during the composting process reduce the mass and the volume of the initial organic waste by 50% [5]. Being dynamic and complex, several factors complicate the decomposition of organic matter in the composting process. A previously published study [6] enumerated more than 20 factors affecting the length and time of the process, among which are the existing pathogens that can regrow after having diminished in number below the detectable limits. The regrowth of Salmonella sp. and Escherichia coli is as a result of the declining effect of indigenous antagonistic micro-organisms [7]. In this context, most composting facilities rely on the existing microorganisms, such as Bacillota, Pseudomonadota, Actinomycetota, and Bacteroidota, which are commonly found in the primary organic raw materials without being active in the decomposing process and with a low antagonistic potential regarding their secondary metabolites [8,9,10,11,12]. This fact puts them in severe competition with the existing pathogens, such as Listeria monocytogenes [13] and Salmonella Typhimurium [14], which are present in animal manure, and Fusarium oxysporum [15], Botrytis cinerea [16] and Alternaria solani, which persist on plant residues. The combined action of the high temperatures reached in the composting process, as well as the release of secondary metabolites with antagonistic activity, synthesized hydrolytic enzymes, and volatile organic compounds by beneficial microbiota adapted to decomposition, allow the inhibition of pathogens present in the waste and the degradation of weed seeds that were present in the original raw material waste [17]. Moreover, when eradication temperatures and durations are not reached in compost piles, these pathogens may be present in the final product [18].
In this work, 11 indigenous CBIs were selected from various composting piles that differed in their raw material composition. The aim was to prove, under laboratory testing, the diversity of responses regarding the degradation of proteins, amino acids, and hormones on the one hand, and the produced secondary metabolites and their inhibitory potential against several pathogens that affect humans, animals, and plants on the other hand. These substances and pathogens are usually present within the primary used organic raw materials in compost piles and represent the main factors affecting the kinetics of the composting process. For that purpose, these indigenous CBIs are considered “pioneers”, since they have the potential, when formulated in a robust inoculum and applied to compost piles, to gain an advantage over the existing microbiota. This advantage will allow them to ensure stable kinetics during the composting process, allowing efficient decomposition of the organic matter and offering, through their secondary metabolites, a double sanitation potential against the existing pathogens and thereby delivering a high-grade compost suitable for agricultural use.

2. Materials and Methods

All culture media components used in the isolation process, the biochemical and molecular reagents, and the DNA extraction kits were supplied by Sigma-Aldrich (Taufkirchen, Germany), except for the yeast extract and the peptone, which were supplied by Oxoid (Hampshire, England).
Four compost piles (Piles A, B, C, and D) of approximately 300 kg each were constructed, containing different percentages and types of primary raw materials: Pile A, comprising 30% wood remnants (90 kg), 70% diapers, and organic household waste (210 kg); Pile B, comprising 30% wood remnants (90 kg) and 70% organic household waste (210 kg); Pile C, comprising 30% wood remnants (90 kg), 50% organic household waste (150 kg), and 20% cow manure (60 kg); Pile D, comprising 30% wood remnants (90 kg), 50% diapers and organic household waste (150 kg), and 20% cow manure (60 kg). The windrow composting system was adopted in all piles, whereby both temperature and moisture were monitored on a daily basis [19]. From each compost pile, three samples of 1 kg each were homogenously collected on the 7th, 45th, and 85th days from the initiation of the composting process, representing the three phases of composting [20], in the presence of a soil sample from the site as a control.
The dilution-spreading technique was used for the isolation of bacteria from 1 g of a sample previously suspended in a saline solution of 9‰ wt. NaCl at several dilutions. From each dilution, a volume of 0.1 mL was streaked onto International Streptomyces Project-2 (ISP2) medium and complex agar medium and then incubated in a Biosan incubator ES-20/60 (Riga, Latvia)) at 30 °C for 24 h, according to the methods used by the authors of [21]. The 11 most prominent compost bacterial isolates (CBI) were selected, purified, and maintained on nutrient agar (NA) at 4 °C for further analyses. Microbial diversity during the composting of different pile compositions was assessed, using the same technique as for strain isolation, but different culture media were adopted, including nutrient agar (NA), ISP2, peptone yeast extract iron agar (ISP6), and tyrosine agar (ISP7), as recommended by the International Streptomyces Project for culturing Actinobacteria and mycelial organisms, and were incubated at 30 °C for 24 h. Potato dextrose agar medium (PDA) was used for the yeasts and fungi growth assessment (ISO 21527-1:2008), and the plates were incubated at 25 °C for 5 days. The enumeration was performed with a colony counter (Boeco CC-1, Hamburg, Germany) and the results were expressed as colony-forming units (CFU)/mL.
Several biochemical and enzymatic tests were conducted to elaborate and identify the profiles of each of the 11 preserved CBIs. The production of melanoid pigmentations was tested on ISP6 and ISP7 [21]. The capacity of the CBIs to assimilate various carbohydrates and amino acids as the main source of carbon and nitrogen, and the ability to decarboxylate and hydrolyze organic salts and other organic compounds, were determined as described by the authors of [22]. Incubation was conducted at 30 °C for 15 days for all the performed tests. The ability of the CBIs to grow at different temperatures (30 °C, 37 °C, 40 °C, 45 °C, 50 °C, 55 °C, and 60 °C) was also examined, wherein a visible growth was recorded as a positive result. Growth at different pH levels (5, 7, and 9) was noted after 14 days of incubation on NA [22]. Nutrient and complex agar media, supplemented with different NaCl concentrations (3, 7, 10, 15, and 20% (w/v)), were used for determining the NaCl tolerance of the CBIs. Casein proteolysis, gelatin liquefaction, starch hydrolysis, and Tween 80 lipolysis were performed, as recommended by the authors of [22]. Growth tests in the presence of lysozyme, the triple sugar iron test, catalase test, H2S production, indole, and nitrate reduction tests were also carried out [22,23]. These analyses were performed for the biochemical profiling of isolated strains and their biodegradation potential.
A loop of each CBI, grown on NA for 8 days, was collected and inoculated in a solution of 10 mL peptone water, then incubated in an incubator shaker (Biosan, Riga, Latvia) at 30 °C and 150 rpm agitation speed for 48 h. Then, 20 colonies of each of the pathogens Listeria monocytogenes, Salmonella Typhimurium, and Escherichia coli (Microbiologics, St Cloud, MN, USA) were added separately to 5 mL of peptone water and incubated in a shaker incubator at 30 °C at 120 rpm for 24 h. Regarding the pathogenic fungi, recovered from the mycology laboratory of the Lebanese Institute of Agricultural Research (LARI), pure hypha cultures of Botrytis cinerea, Alternaria solani, and Fusarium oxysporum were transferred to the surface of the PDA medium and incubated at 24 °C until the plates were completely covered.
A volume of 97 mL of Bennett liquid media was introduced to a 500 mL Erlenmeyer flask and then inoculated with 3 mL (3% (v/v)) of bacterial pre-culture, with an initial population biomass of 0.1 to 0.2 g/L. The biomass increase was checked by measuring the absorbance at 600 nm with a spectrophotometer (Shimadzu, Japan). The inoculated media were incubated at 30 °C and 150 rpm. Bacterial growth was monitored for 10 days to detect the timing of the release of secondary metabolites for every CBI. A volume of 5 mL was aseptically recuperated every 24 h and centrifuged at 4500 rpm (Hermley, Wehingen, Germany) for 15 min. The proteinaceous compounds content in the supernatant was determined according to the Lowry procedure [24].
The culture of CBI was carried in Bennett broth medium until the maximum time for the release of secondary metabolites of peptidic origin from each of them. The supernatant was collected and fractionated by ultrafiltration to the corresponding 5–10 kDa peptidic fraction, to study whether the microbial byproducts are of protein origin and what their effects are on the pathogenic bacteria. First, the sample was distributed into centrifugal filter units, presenting a cut-off of 10 kDa (Amicon® Ultra-15 with an Ultracel-10 membrane). Ultrafiltration was performed at 3500× g for 45 min at 4 °C. Each unit can initially contain a volume of 15 mL. Four units were filled, and at the end of the ultrafiltration process, a volume of 0.2 mL was retained by the membrane of each unit. A total retentate of 0.8 mL, with a molecular weight (MW) ≥ 10 kDa (75 (X) concentrated), was obtained. The filtrate ≤ 10 kDa was then recovered and ultrafiltered using the centrifugal filter units, presenting a cut-off of 5 kDa (Corning® Spin-X UF 20, Sigma-Aldrich). The principle was the same and 0.8 mL of a fraction with an MW between 5 and 10 kDa (75 (X) concentrated) was obtained [25,26].
Nutrient agar media that was inoculated with 5% peptone water containing each of the pathogenic bacteria was prepared and poured into Petri plates. At the same time, sterile microbial disks (Sigma-Aldrich) were soaked for 20 min in the concentrated extracts of each CBI. The sterile disks were then transferred to the surfaces of the solidified agar plates and kept for 2 h at 4 °C to allow the diffusion of the secondary metabolites into the agar. Finally, the disks were removed, and the agar plates were incubated at 30 °C for 72 h, after which the inhibition zone was estimated [27,28]. In the case of the three pathogenic fungi, a volume of 0.8 mL of the 5–10 kDa (75X) was added to every plate. A hyphal disk of every pathogenic fungus was transferred to the surface of the solidified PDA using a hole puncher of 10 mm diameter and monitored until the control plates were fully covered [29]. Each antagonistic testing procedure was performed in three independent replicates for all fungi and bacterial pathogens while preserving the control.
One loop of each CBI was inoculated separately into 200 mL of nutrient broth medium. A volume of 15 mL was aseptically collected every 24 h and centrifuged at 4500 rpm for 15 min. The supernatant was used for pH measurement (pH meter, Ohaus, Kettering, UK). The pellet concentration was measured using a moisture analyzer (Ohaus, Kettering, UK) and the results were expressed as the dry weight in g/L.
A volume of 1.5 mL of an overnight broth bacterial culture was pelleted for DNA extraction, which was performed using the GenEluteTM Bacterial Genomic DNA Kit (Sigma, Taufkirchen, Germany). The 16S Metagenomic sequencing was performed at Macrogen Inc., Seoul (Korea), using the Illumina platform. The workflow consisted of four basic steps; the first was sample preparation for quality-control testing of the extracted DNA/RNA, DNA quantification, size, and impurities, revealed using high-sensitivity chips (2100 Bioanalyzer, Agilent Technologies, Santa Calara- California, USA). The second step covered library construction via random fragmentation, followed by 5′ and 3′ adapter ligation. The third step was represented by sequencing via bridge amplification to generate ready cluster templates for sequencing. Finally, the Illumina SBS technology allowed highly accurate base-by-base sequencing that virtually eliminates sequence context-specific errors, even within repetitive sequence regions and homopolymers. The sequencing data were converted into raw data to be analyzed. The Illumina sequencer (Seoul, South Korea)) generates raw images, utilizing sequencing control software for system control and base-calling using Real Time Analysis (RTA), an integrated primary analysis software. The BCL (base calls) binary file was converted into the FASTQ format, utilizing the Illumina package, bcl2fastq. Adapters have not been trimmed from the reads. The sequence was compared for similarity with the reference species of bacteria that are contained in genomic data banks, using the NCBI BLAST data available at http://www.ncbi.nlm.nih.gov/ (accessed on 3 May 2019). Phylogenetic analyses were conducted using the software included in the MEGA Version 3.0 package.
All the data reported represent an average of three triplicates with standard deviation. The XL-STAT software (version 2014.5.03) was used to handle the data. A two-way Analysis of Variance (ANOVA) (generalized linear model) was performed at p < 0.05, and the Tukey multiple range test (α = 0.05) was performed to assess the statistical significance of the microbial counts within the three phases of composting, on different culture media. The observations and correlations between the pile mix and the culture media were tested using a Pearson (n) type.

3. Results

3.1. Microbial Counts at Different Composting Times

The microbial concentrations in the control (soil) and in p iles A, B, C, and D during the three different phases of composting are shown in Figure 1. During each of these phases, a microbial count was carried out on different culture media, such as ISP2, ISP6, ISP7, PDA, and NA. For the first phase of composting, the microbial count was low in the soil, as well as in pile A and pile B, without showing any significant differences (Figure 1a). In addition, the number of bacteria was higher in the soil than in pile A and pile B for the culture media used, with the exception of ISP6 and PDA media from pile B. A significant increase in microbial counts in pile C and pile D was observed, compared to the soil, and in piles A and B due to the decomposing of the existing sugar by the mesophilic bacteria. The highest microbial count was observed in the ISP6 media for pile C and in the PDA media in pile D and reached 1.8 × 109 CFU/mL and 1.5 × 109 CFU/mL respectively (Figure 1a). A positive correlation between pile C and ISP2, NA, and ISP6 was observed (an R-value between 0.956 and 0.902). Likewise, a correlation between pile D and ISP7 and PDA media was shown (an R-value between 0.943 and 0.779). Moreover, a positive correlation within the same medium samples was also achieved (Table 1).
In the second phase, in terms of microbial count in the soil, pile C and pile D were the lowest in all the media, without showing significant differences (Figure 1b). However, this concentration was higher than the one shown in the first phase. It may be due to the activities of thermophilic bacteria that decompose more complex raw materials (Figure 1a,b). In piles A and B, a significant increase in microbial counts was observed in all the media compared to the control, in piles C and D. It reached a maximum of 11 × 109 CFU/mL in pile A on ISP2 media, and a maximum of 10 × 109 CFU/mL in pile B on NA and ISP7 media (Figure 1b). Unlike the first phase, positive correlations were observed between pile A and ISP2, ISP6 and PDA media (an R-value between 0.940 and 0.821), between pile B and NA and ISP7 media (an R-value between 0.967 and 0.903), and even within the same medium (Table 1).
In the third phase of composting, yeast and fungus-counting was predominant in piles B and C, with a concentration of 1 × 109 CFU/mL and 1.6 × 109 CFU/mL, respectively (Figure 1c). The existence of simple sugar in the first phase launched an active fermentation process, leading to final population growth in the third phase. This was higher in pile C on the PDA than in pile B on the same media. Differences in cell concentrations were shown on the ISP7 medium for piles A, B, and C compared to the control (soil). However, no significant differences were shown for pile D. Furthermore, positive correlations were found between pile B and the NA, ISP7, and PDA media (R between 0.979 and 0.877), between pile C and the medium, specifically for ISP2, ISP6, and PDA media (an R-value between 0.998 and 0.996) (Table 1).

3.2. pH and Biomass Variations

The pH decreased during the first 24 to 48 h of incubation (Figure 2a). The pH decreased sharply for CBI1, CBI3, CBI4, CBI5, CBI6, CBI7, CBI8, and CBI9, from a pH value of around 7.2 to reach a pH range between 3.5 and 4.4. It also decreased in CBI2 and CBI10 but in a less marked way, reaching a pH of 5.58 and 6.21, respectively. After 48 h, the pH increased again to reach values between 9 and 9.5 after 100 h of incubation, except for CBI1, which maintained a pH value of 4.14 until after 120 h of incubation, before it increased again. The biomass measurement showed a slow increase in population growth, especially for CBI2, CBI3, CBI6, CBI8, CBI9, and CBI10, where the values ranged between 0.002 g and 0.02 g. On the other hand, the population growth in CBI1, CBI4, CBI5, and CBI7 was higher and ranged between 0.04 g and 0.07 g (Figure 2b). pH and population growth varied with time and reached their maximum level at the end of the process.

3.3. Antagonist Activity—Fungal Pathogens

The potential of the secondary metabolites of the different CBIs to inhibit the mycelial development of the three fungal plant pathogens, Alternaria solani, Botrytis cinerea, and Fusarium oxysporum, in the presence of a control is represented in Figure 3. Mycelial growth was followed until day 7 for the first two pathogens and for 11 days for the third one. The inhibition potential of the secondary metabolites against Alternaria solani, when compared to the control, showed that the secondary metabolites of CBI4 had partial mycelial growth limitation on day 3 that did not persist, and normal growth was resumed by day 5. Conversely, CBI7 showed a higher potential of limiting the mycelial growth than the control and persisted until the 7th day (Figure 3a). The inhibition potential of the remaining CBI is negligible. Furthermore, the secondary metabolites of all CBI had no effect on the inhibition of Botrytis cinerea (Figure 3b). Finally, and in contrast to the other fungal pathogens, all secondary metabolites of CBI showed an important limitation of the mycelial growth of the Fusarium oxysporum pathogen after the first day, and persisted until day 11 (Figure 3c).

3.4. Antagonist Activity—Pathogenic Bacteria

The conducted antagonistic activity tests showed that the concentrated peptidic fractions of the CBI1, CBI5, and CBI9 samples had inhibitory activity against both Salmonella Typhimurium and Escherichia coli. In the case of CBI6, it only acted on Salmonella Typhimurium but showed a high inhibition zone in comparison to the control (Table 2). Only the secondary metabolites of the CBI8 showed inhibitory activity against Listeria monocytogenes, in comparison with the control.

3.5. Physiological and Biochemical Testing

In total, 49 tests were conducted on the 11 CBIs, allowing the elaboration of a full profile for each (Table S1 in the Supplementary Materials). These bacteria could be classified into two groups according to their ability to grow at different temperature ranges, as follow:
Group I: CBI1, CBI3, CBI6, CBI9, and CBI11 have the best growth rate at temperatures ranging between 40 and 50 °C, reaching even 55 °C for CBI1 and CBI6. Therefore, these strains are classified as thermophilic bacteria.
Group II: CBI2, CBI4, and CBI10 have the best growth rate at temperatures ranging between 30 and 40 °C and can grow at temperatures reaching 45 °C. CBI5, CBI7, and CBI8 have the best growth rate at temperatures ranging between 37 and 45 °C. Therefore, these strains are considered to be mesophilic bacteria.
All strains can grow in a wide pH range between 5 and 9. They can develop under anaerobic conditions through the fermentation of simple sugars (sucrose, lactose, and glucose) as the source of energy for their physiological persistence. As for their growth at different NaCl concentrations, CBI2 is considered slightly halotolerant since it was able to grow at NaCl concentrations ranging between 1 and 3% only, while all the other strains are moderately halotolerant since they grow at concentrations ranging between 5 and 20%.
CBI2 is the most active strain in terms of the degradation of different types of hormones and proteins from dairy products (milk and its byproducts), but it lacks the enzymes needed for the degradation of ammonia into nitrogen. CBI1, CBI5, and CBI9 are more active in the degradation of starch and proteins into simple sugars and in the degradation of fats. All the studied strains can degrade one or several amino acids, carbohydrates, hormones, starches, and proteins. They are also able to decarboxylate organic sodium salts and hydrolyze other organic compounds to use them as the main source of carbon for their survival.

3.6. Raw Data Statistics of 16S Sequencing

The total number of bases and reads, in addition to the percentage of GC (%), Q20 (%), and Q30 (%), were studied for the 11 strains (Table S2 in the Supplementary Materials). CBI 8 shows the highest percentage of GC (57.202%). It belongs to the Actinobacteria phylum, as one of a group of Gram-positive bacteria with high levels of guanine and cytosine (greater than 55%). The GC percentage within the DNA of CBI1, CBI2, and CBI7 oscillates around 55%, which indicates that they are three different clones within the same species, Bacillus subtilis.

3.7. Taxonomic Classification and Abundance Ratio (%)

The taxonomic abundance ratio led to the identification of four phyla, five classes, six orders, six families, six genera, and eight different species represented in Table 3 and Table S3 in the Supplementary Materials.
CBI1, CBI2, and CBI7 were identified as potential Bacillus subtilis, as per the top hits, when compared to the accession codes within the GenBank, isolated from different ecological niches within the soil. Since all accession codes represent the partial sequencing of isolated strains and not the whole genomes and do show variabilities with isolated strains within this study, this allows us to identify three different clones of Bacillus subtilis.
CBI3 and CBI11 were identified as potential Providencia sp., as per the top hits of the accession codes, representing the partial sequences of an uncultured bacterium isolated from the environment of the Chaerhan Lake ecosystem in China [30].
For the CBI6 strain, the top hits show 97.73% similarity with the Bacillus pseudomycoides strain, 219298, identified by the accession code CP007626 in the NCBI, where the whole genome is sequenced. The authors of [31] proposed the genome analysis-based reclassification of Bacillus weihenstephanensis as a later heterotypic synonym of Bacillus mycoides, along with the correction of erroneous species identifications for several strains. It is of note that the GC percentage in all studied species in [31] was equal to 35%, while the isolated CBI6 strain’s percentage of GC is equal to 53%.
For the CBI5 strain, the top hits show 78.41% similarity with Pseudomonas sp. 20_BN strain or Pseudomonas saudiphocaensis, identified by the accession code CCSF01000001 in GenBank. The bacteria were isolated from a partial solid waste digester fed with methanol. Other isolated strains were noted for their similarity to strains found at Makkah, in Saudi Arabia [32]. Members of the genus Pseudomonas are mostly environmental bacteria that are widely distributed in soil, water, and air [33].
For the CBI4 strain, the top hits show 62.40% similarity with the Alcaligenes strains, identified by two accession codes for a partial sequence of an uncultured bacterium in GenBank, JF 692663.1, isolated from a coastal urban watershed, and AB205631, isolated from a denitrification system of saline industrial wastewater [34]. A third accession code, KM251257, isolated from aerobic granular biomass from sewage sludge, was identified as Alcaligenes faecalis via partial sequencing [35].
For the CBI8 strain, the top hits show 95.66% similarity with Arthrobacter strains identified by three accession codes, JF218251, JF218331, and JF218225, isolated from the skin and volar forearm [36]. The bacteria studied in all accession codes were uncultured, had a partial sequence in the GenBank, and were related to atopic dermatitis.
For the CBI9 strain, top hits show 99.51% similarity with the Myroides injenensis M0-0166 strain, identified by two accession codes of partial sequences, JX966100.1, isolated from human urine, and HQ671078.1, isolated from human blood [37]. A third accession code, FJ649673.1, isolated through a partial sequence from activated sludge, was also noted and identified as Flavobacterium sp. CESNVD 3 [38].
For the CBI10 strain, the top hits show 54.01% similarity with Pseudomonas sp. strains, identified by two accession codes of the uncultured bacterium, FJ672787.1, isolated from feedlot surface material from Meat Animal Research Center (MARC) beef [39] and representing the clones Ll142-7H2 and LN565711. The second accession code was that of an uncultured bacterium isolated from the refuse dump Nest 12 layer 2″ [40], representing the clone SIBG1279_N12D2_16S_B. A third accession code, AB673200.1, was also noted and was obtained from a partially sequenced uncultured gamma proteobacterium gene taken from a desulfurization bioreactor [41] and identified as the clone DSCIR13.

4. Discussion

Composting is the microbial decomposition of biodegradable materials, and it is governed by physicochemical, physiological, and microbiological factors. The importance of microbial communities (bacteria, actinomycetes, and fungi) during composting is well established [42]. However, the microbial diversity during composting may vary with the variety of composting materials and nutrient supplements. Therefore, it is necessary to study the diversity of microorganisms during the composting of different agricultural byproducts, such as wood remnants or organic compounds, organic household waste (from secondary sortings), cow manure, and diapers. In this study, the high number of bacteria in the soil in the first phase of composting can be explained by the presence of diapers treated with sanitizers in pile A and the un-respected ratio of C/N (carbon content out of range) in pile B, which can lead to a delay in the adaptation and growth of the existing bacteria. Nitrogen and carbon are major sources of microbial activity; carbon constitutes the primary source of energy and cell development, while nitrogen is essential for protein synthesis [43]. The adoption of a primary C/N ratio mix between 25/1 and 30/1, in addition to the quality of primary raw materials, which, when collected and comingled with other wastes, represents a high risk of contamination with pollutants (e.g., pesticides, heavy metals, etc.) and impurities, having a major impact on the microbial activity, the composting process, and the end-product quality. In this study, the best mix of chosen raw materials is the one adopted in pile C. The mixture allows for the launch of a robust bio-stabilization process and to reach the highest microbial population rates in a short period, especially in phase 1, continuing through the other phases and on most of the plated culture media [20,44,45].
Nevertheless, the changes in pH and biomass variations go in parallel, highlighting an acidification phase within the substrate during the first 48 h, due to the degradation of different existent glucidic and lipidic substances and the production of organic acids. Under aqueous conditions, these organic acids dissociate and accumulate in the substrate, and, in the presence of carbon dioxide, lead to the formation of carbonic acids. This phase is followed by an alkaline phase, which is due to the production of amines from proteins within the first phase, followed by the production of ammonia and other metabolites. This trend of pH is similar to one of the composting procedures [46].
Compost is close to soil, a source of infinite life that promotes the bacterial consortium. To gain an advantage in this process, bacterial populations play an important role in the decomposition of organic materials, especially in the early stages when moisture levels are high, while fungi tend to dominate during the later stages of decomposition. The obtained results in this study provide a better understanding of bacterial communities and their interaction during composting [47]. Nevertheless, existing pollutants, such as fertilizers and pesticide residues within compost when it is added to the soil, contribute to the contamination and deterioration of the environment, affect soil fertility, and cause a loss of productivity, which underlines the importance of adopting sustainable farming practices [42]. On the other hand, microbial contamination is also a matter of major concern that can challenge human health directly, through the presence of pathogenic bacteria, such as coliforms, Vibrio, Listeria, Salmonella, and many others [48].
Bacillus subtilis and Pseudomonas sp. are examples of decomposer bacteria. Bacillus subtilis was one of the most abundant isolated strains in our study, in CBI1, CBI2, and CBI7 in the mesophilic, thermophilic, and last stage of composting and in the different pile mixtures at levels close to those described in the literature [49]. The isolates revealed a high metabolic activity but a variance in biochemical abilities [30]. The presence of B. subtilis promoted the maturation of compost, enhanced the total organic carbon and humic substances, and retained carbon due to the reduction of amino acid and carbohydrate metabolism, as previously reported in [50]. Bacillus were shown to be the proteolytic bacteria that were most frequently present [51]. They were always the most numerically dominant proteolytic bacteria isolated, on the basis of gelatin liquefaction and casein hydrolysis tests, except for strain 7, which shows lower proteolytic activity but inhibits the growth of both Alternaria solani and Fusarium oxysporium, verifying what was stated in a previous paper [52]. Showing high similarities with Bacillus cereus and Bacillus mycoides, the Bacillus pseudmycoides CBI6 strain was also detected in abundance. The growth profile reveals its high ability to withstand various pH, salinity, and temperature ranges; it metabolized many amino acids but showed lesser carbohydrate usage and did not exhibit any proteolytic activity. This strain exhibited an antibacterial effect against Salmonella typhimurium entericae [53].
Both the Pseudomonas and Bacillus species have hydrolytic potential and were able to decompose the organic waste efficiently. They are found in the microbiome of vermicompost [54] and are involved in the bioremediation of environmental xenobiotics [55], such as phthalate acid esters (PAEs), the most frequently occurring di-n-butyl phthalate (DBP) that aroused worldwide concern due to threats to the environment and human health [56]. Interestingly, Bacillus and Pseudomonas are prolific producers of secondary metabolites, which act against numerous co-existing phytopathogenic fungi and human pathogenic bacteria. Bacillus subtilis has been used to suppress seedling blight in sunflowers, caused by Alternaria helianthin, while Pseudomonas sp., was used to limit Rhizoctonia solani [57]. It is important to note that divergence in the responses of the inhibition potential of our strains could be due to the success of these chosen pathogens in developing resistance against these secondary metabolites within the primary niches of isolation. For that reason, additional investigations need to be carried out regarding the secondary metabolites’ characterization (activity, purification, peptides sequencing, and concentrations) for every strain, along with the identification of their lethal inhibitory doses. The patterns of the different secondary metabolites produced by the compost bacterial isolates showed that a unique or mixture of chemical substances exists.
Providencia sp., an Enterobacteria detected in this study, along with Pseudomonas, is involved in the biodegradation of DBP and contributes to bioremediation [58]. Two strains of Providencia, CBI3 and CBI11, which are abundant in the thermophilic stage, showed the same metabolic profile by degrading most of the amino acids and casein present in dairy products, and no antimicrobial effects were noted. Pseudomonas sp., detected in compost piles as CBI5 and CBI10 and abundant in the mesophilic stages, demonstrated similarities in growth patterns at different pH values and temperatures, with growth in the presence of a high percentage of sodium chloride. They also showed interesting proteolytic activity, carbohydrate utilization, and amino acid intake; in addition, CBI5 was able to stop the growth of both Salmonella Typhimurium and Escherichia coli.
Moreover, Actinobacteria help to slowly break down humates and humic acids in soils with a pH higher than 5 and secrete a wide range of extracellular enzymes to degrade lignin and recalcitrant molecules [59]. With flexible growth at different pH, salinity, and temperature ranges, the only identified Actinobacteria in this study was the genus Arthrobacter sp., CBI8. This genus is known for its industrial use to produce L-glutamate in biodegradation and bioremediation due to its ability to degrade sulfadiazine, a sulfamide antibiotic, as a sole carbon source [55,60], in addition to its implication in nitrogen nitrification [61]. It is also an efficient bacterium in atrazine degradation in wastewater treatments, enabling bioaugmentation [62]. Another important criterion is that Arthrobacter can degrade phenols that take a longer time to compost, due to their complex chemical structure [63]. The Alcaligenes sp. strain, CBI4, found in the compost of this study shares the same criteria as Arthrobacter in terms of degrading phenolic compounds but can also be found in the rhizosphere of many plants and can assist plants to survive high levels of arsenic content in soil [64]. This strain is relatively poor in terms of biochemical abilities and showed normal growth rates under high salinity and temperature and low pH. It is of note that in this study, Arthrobacter showed remarkable inhibition of Listeria monocetogenes, while Alcaligenes showed only a slight inhibition of Alternaria solani, but both strains completely inhibited Fusarium oxysporum.
Finally, Flavobacteriaceae were abundant in the curing phase and were identified as Myroïdes, CBI9; they seem to have a high affinity with amino acids, an exceptional ability to degrade proteins, and completely inhibit the growth of both Salmonella Typhimurium and Fusarium oxysporum. These bacteria can support the composting process in cold conditions and are used in wastewater treatments [65] but can also cause severe illnesses in humans, such as urinary tract infections [66].

5. Conclusions

In this work, 11 indigenous CBI were first isolated from compost piles and were characterized enzymatically, biochemically, and genetically. Top hits provided by GenBank demonstrated the genetic diversity of these strains, belonging to these 6 different families: Bacillus, Providencia, Pseudomonas, Alcaligenes, Arthrobacter, Myroides spp. This diversity also applies at the enzymatic and biochemical level, with different degradation patterns of amino acids, carbohydrates, hormones, and proteins. CBI2 was found to be the most active strain in the degradation of different types of hormones and proteins from dairy products, but it lacks the enzymes necessary for the degradation of ammonia to nitrogen.
Afterward, the antagonistic potential of the recovered secondary metabolites was studied. The results showed the complete inhibition of all strains against Fusarium oxysporum, with no growth limitation against Botrytis cinerea. However, only the secondary metabolites of the isolates CBI1, CBI5, and CBI9 showed inhibitory activity against Salmonella Typhimurium and Escherichia coli, while only those of CBI6 and CBI8 inhibited the growth of Salmonella Typhimurium and Listeria monocytogenes.
Thus, the different tests that were performed proved the variability of the degradation potential of different organic substances, as well as the efficiency of their secondary metabolites against several pathogens affecting humans, animals, and plants.
The obtained results demonstrate the potential development of a robust inoculum, containing these pioneer strains, that is adapted to the composting of commingled organic household waste. This inoculum will be able to initiate and maintain robust kinetics throughout the composting process and ensure efficient decomposition, resulting in a final compost with high nutritive value. The secondary metabolites of this inoculum will suppress the existing pathogens during composting and thereby prevent their proliferation beyond the process. Therefore, agricultural producers will benefit from the production of high-quality compost for use in their agricultural fields at a lower cost, providing a safe agricultural product while generating additional income.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12122977/s1, Table S1: Biochemical tests for the 11 compost bacterial isolates; Table S2: Taxonomic classification of compost bacterial isolates (CBI); Table S3: The taxonomy of the different species.

Author Contributions

Conceptualization, A.T., R.G.M. and Z.H.; methodology, A.T., R.B., D.S. and Z.R.; formal analysis, A.T.; investigation, A.T., R.B., D.S. and Z.R.; resources, A.T.; data curation, C.G. and R.H.; writing—original draft preparation, A.T. and V.A.; writing—review and editing, A.T., Z.R., D.S., R.G.M., M.A.D., V.A. and Z.H.; supervision, D.S. and R.G.M.; Registration within GenBank, A.T. and R.B. All authors have read and agreed to the published version of the manuscript.

Funding

The financial support of the study by the Lebanese Agricultural Research Institute (LARI) and the Saint Joseph University Faculty of Sciences are gratefully acknowledged.

Data Availability Statement

All sequence data used for our analyses have been uploaded to the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) under BioProject number PRJNA662047. The nucleotide sequence data reported are made freely available in the SRA database, under the accession numbers SRX9104377 (Pseudomonas sp.), SRX9104376 (Myroïdes sp.), SRX9104375 (Arthrobacter sp.), SRX9104374 (Bacillus subtilis), SRX9104373 (Bacillus pseudomycoïdes), SRX9104372 (Pseudomonas sp. 20_BN), SRX9104371 (Alcaligenes sp.), SRX9104370 (Providencia sp. Clone 3), SRX9104369 (Providencia sp. Clone 11), SRX9104368 (Bacillus subtilis), and SRX9104367 (Bacillus subtilis).

Acknowledgments

We thank the Domaine de Taanayel and Arcenciel for providing part of the raw materials for the trials.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Microbial counts on different media of different compost piles in the (a) first phase, (b) second phase, and (c) third phase. The averages within the graph that are followed by the same letter do not significantly differ, according to Tukey’s multiple range test (α = 0.05).
Figure 1. Microbial counts on different media of different compost piles in the (a) first phase, (b) second phase, and (c) third phase. The averages within the graph that are followed by the same letter do not significantly differ, according to Tukey’s multiple range test (α = 0.05).
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Figure 2. (a) Variations in pH of the different CBI samples in Bennett medium; (b) kinetics of population growth (biomass) of the different CBI samples.
Figure 2. (a) Variations in pH of the different CBI samples in Bennett medium; (b) kinetics of population growth (biomass) of the different CBI samples.
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Agronomy 12 02977 g003a 550Agronomy 12 02977 g003b 550
Figure 3. Inhibition potential of secondary metabolites against (a) Alternaria solani, (b) Botrytis cinerea, and (c) Fusarium oxysporum.
Figure 3. Inhibition potential of secondary metabolites against (a) Alternaria solani, (b) Botrytis cinerea, and (c) Fusarium oxysporum.
Agronomy 12 02977 g003aAgronomy 12 02977 g003b
Table
Table 1. Pearson correlation of all the pile mixes and culture media in phases 1, 2, and 3.
Table 1. Pearson correlation of all the pile mixes and culture media in phases 1, 2, and 3.
Phase 1
SoilPile APile BPile CPile DISP 2NAISP 6ISP7PDA
Soil1.000
Pile A−0.2501.000
Pile B−0.250−0.2501.000
Pile C−0.250−0.250−0.2501.000
Pile D−0.250−0.250−0.250−0.2501.000
ISP 2−0.332−0.336−0.3320.9560.0441.000
NA−0.339−0.341−0.3390.9480.0721.0001.000
ISP 6−0.365−0.365−0.3640.9020.1910.9890.9931.000
ISP7−0.396−0.398−0.3970.4130.7790.6610.6810.7651.000
PDA−0.343−0.343−0.3420.0870.9430.3740.4000.5070.9431.000
Phase 2
SoilPile APile BPile CPile DISP 2NAISP 6ISP7PDA
Soil1.000
Pile A−0.2501.000
Pile B−0.250−0.2501.000
Pile C−0.250−0.250−0.2501.000
Pile D−0.250−0.250−0.250−0.2501.000
ISP 2−0.3900.8210.347−0.390−0.3891.000
NA−0.4210.1780.903−0.268−0.3930.7041.000
ISP 6−0.4060.9400.062−0.200−0.3970.9470.4821.000
ISP7−0.3280.0040.967−0.320−0.3240.5740.9800.3121.000
PDA−0.3930.8280.335−0.390−0.3811.0000.6950.9510.5641.000
Phase 3
SoilPile APile BPile CPile DISP 2NAISP 6ISP7PDA
Soil1.000
Pile A−0.2501.000
Pile B−0.250−0.2501.000
Pile C−0.250−0.250−0.2501.000
Pile D−0.250−0.250−0.250−0.2501.000
ISP 2−0.291−0.168−0.2650.996−0.2721.000
NA−0.427−0.3100.8770.240−0.3800.2291.000
ISP 6−0.301−0.211−0.2590.998−0.2260.9980.2341.000
ISP7−0.475−0.2250.7960.362−0.4580.3600.9850.3591.000
PDA−0.298−0.2930.9790.998−0.298−0.1150.940−0.1080.8761.000
Note: The values in bold are different from 0, according to the Pearson correlation (α = 0.05).
Table
Table 2. Inhibition efficiency of the secondary metabolites against pathogenic bacteria.
Table 2. Inhibition efficiency of the secondary metabolites against pathogenic bacteria.
Pathogenic Bacteria Inhibition Halo (cm)
Salmonella TyphimuriumListeria monocytogenesEscherichia coli
5–10 K≥ 10 K5–10 K≥ 10 K5–10 K≥ 10 K
CBI110.8000.80.8
CBI2000001
CBI3000011
CBI4110000
CBI5110011
CBI6330000
CBI7000000
CBI8001100
CBI911.50011
CBI10000011
CBI11000000
Note. CBI: Compost bacteria isolate.
Table
Table 3. Taxonomic abundance ratio (%) of compost bacterial isolates.
Table 3. Taxonomic abundance ratio (%) of compost bacterial isolates.
Next Related Type Strain
Sample NameSample Accession NumberNumber of BasesAccession Code 1Accession Code 2Accession Code 3Highest 16S rRNA Sequence Similarity
CBI1SRX9104367467EU257444 (GenBank)FJ526332 (GenBank)FJ772081 (GenBank)Bacillus subtilis (70.83%)
CBI2SRX9104368466EU257444 (GenBank)FJ526332 (GenBank)FJ772081 (GenBank)Bacillus subtilis (66.68%)
CBI3SRX9104370440HM127153 (GenBank)HM127159 (GenBank)HM127158 (GenBank)Providencia sp. (41.13%)
CBI4SRX9104371440AB205631 (GenBank)JF692663 (GenBank)KM251257 (GenBank)Alcaligens sp. (62.40%)
CBI5SRX9104372440EF586016 (GenBank)LK021121 (GenBank)CCSF01000001 (GenBank)Pseudomonas sp. 20_BN (78.41%)
CBI6SRX9104373451FJ786044 (GenBank)HQ683838 (GenBank)CP007626 (NCBI)Bacillus pseudomycoides (97.73%)
CBI7SRX9104374466EU257444 (GenBank)FJ526332 (GenBank)FJ772081 (GenBank)Bacillus subtilis (95.09%)
CBI8SRX9104375451JF218251 (GenBank)Jf218331 (GenBank)JF218225 (GenBank)Arthrobacter sp. (95.66%)
CBI9SRX9104376440HQ671078 (GenBank)JX966100 (GenBank)FJ649673 (GenBank)Myroides sp. (99.51%)
CBI10SRX9104377440FJ672787 (GenBank)AB673200 (GenBank)LN565711 (GenBank)Pseudomonas sp. (54.01%)
CBI11SRX9104369440HM127153 (GenBank)HM127159 (GenBank)HM127158 (GenBank)Providencia sp. (48.98%)
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Tannouri, A.; Rizk, Z.; Al Daccache, M.; Ghanem, C.; Azzi, V.; Haddad, R.; Maroun, R.G.; Hobaika, Z.; Badra, R.; Salameh, D. Characterization of Antagonist Potential of Selected Compost Bacterial Isolates (CBI) against Plant and Human Pathogens. Agronomy 2022, 12, 2977. https://doi.org/10.3390/agronomy12122977

AMA Style

Tannouri A, Rizk Z, Al Daccache M, Ghanem C, Azzi V, Haddad R, Maroun RG, Hobaika Z, Badra R, Salameh D. Characterization of Antagonist Potential of Selected Compost Bacterial Isolates (CBI) against Plant and Human Pathogens. Agronomy. 2022; 12(12):2977. https://doi.org/10.3390/agronomy12122977

Chicago/Turabian Style

Tannouri, Abdo, Ziad Rizk, Marina Al Daccache, Chantal Ghanem, Valérie Azzi, Rami Haddad, Richard G. Maroun, Zeina Hobaika, Rebecca Badra, and Dominique Salameh. 2022. "Characterization of Antagonist Potential of Selected Compost Bacterial Isolates (CBI) against Plant and Human Pathogens" Agronomy 12, no. 12: 2977. https://doi.org/10.3390/agronomy12122977

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