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Article

Antimicrobial Effects of Potential Probiotics of Bacillus spp. Isolated from Human Microbiota: In Vitro and In Silico Methods

by
Alfonso Torres-Sánchez
1,2,†,
Jesús Pardo-Cacho
1,†,
Ana López-Moreno
1,2,3,*,
Ángel Ruiz-Moreno
1,2,
Klara Cerk
1 and
Margarita Aguilera
1,2,3,*
1
Department of Microbiology, Faculty of Pharmacy, University of Granada, Campus of Cartuja, 18071 Granada, Spain
2
Institute of Nutrition and Food Technology “José Mataix”, CIBM, University of Granada, Armilla, 18016 Granada, Spain
3
Instituto de Investigación Biosanitaria ibs (IBS), 18012 Granada, Spain
*
Authors to whom correspondence should be addressed.
†
These authors have contributed equally to this manuscript.
Microorganisms 2021, 9(8), 1615; https://doi.org/10.3390/microorganisms9081615
Submission received: 29 June 2021 / Revised: 26 July 2021 / Accepted: 26 July 2021 / Published: 29 July 2021
(This article belongs to the Special Issue Probiotics and Antimicrobial Effect)
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Abstract

:
The variable taxa components of human gut microbiota seem to have an enormous biotechnological potential that is not yet well explored. To investigate the usefulness and applications of its biocompounds and/or bioactive substances would have a dual impact, allowing us to better understand the ecology of these microbiota consortia and to obtain resources for extended uses. Our research team has obtained a catalogue of isolated and typified strains from microbiota showing resistance to dietary contaminants and obesogens. Special attention was paid to cultivable Bacillus species as potential next-generation probiotics (NGP) together with their antimicrobial production and ecological impacts. The objective of the present work focused on bioinformatic genome data mining and phenotypic analyses for antimicrobial production. In silico methods were applied over the phylogenetically closest type strain genomes of the microbiota Bacillus spp. isolates and standardized antimicrobial production procedures were used. The main results showed partial and complete gene identification and presence of polyketide (PK) clusters on the whole genome sequences (WGS) analysed. Moreover, specific antimicrobial effects against B. cereus, B. circulans, Staphylococcus aureus, Streptococcus pyogenes, Escherichia coli, Serratia marcescens, Klebsiella spp., Pseudomonas spp., and Salmonella spp. confirmed their capacity of antimicrobial production. In conclusion, Bacillus strains isolated from human gut microbiota and taxonomic group, resistant to Bisphenols as xenobiotics type endocrine disruptors, showed parallel PKS biosynthesis and a phenotypic antimicrobial effect. This could modulate the composition of human gut microbiota and therefore its functionalities, becoming a predominant group when high contaminant exposure conditions are present.

Graphical Abstract

1. Introduction

The human gut microbiota could be considered as a new source for the identification and isolation of multiple microorganisms producing bioactive compounds and enzymes of interest such as biopolymers, antimicrobials notably demanded by the food, health, and several biotechnological industries [1,2]. Identifying the composition of cultivable gut microbiota has always been a challenge due mainly to the requested anaerobic conditions [3]. Efforts in simulating these harsh culture conditions allow isolating potential NGP [4] and even a variety of taxonomy bacterial groups which were also tolerant to xenobiotics or obesogens [5] followed by characterization through 16S rRNA gene sequencing.
Microbiome compositional consortia are variable in each individual [6,7]. Culturing methods and directed-culturomics for isolating specific microorganisms deserve special attention. Thus, the genus Bacillus belonging to a predominant microbiota phylum, Firmicutes, is differentially present and its species are capable of synthesizing a wide variety of bioactive compounds and enzymes of interest for their potential technological applications in health and the modern food biotechnological sectors [8]. Several Bacillus species have also been considered as probiotics [9,10]. Bacilli taxa, concretely Lactobacillus and Bacillus genera in microbiota seem to play a role on the ecology of predominant groups present on individual microbiota in obesity and metabolic disorders as compiled in human clinical trials (Table 1). The potential impact on the other circumscribed taxa groups could be driven by antimicrobial substances released by the Bacilli taxa, such as bacteriocins, PKs, lipopeptides, etc. [11,12].
Bisphenols are considered as microbiota disrupting chemicals (MDC) [5] and their presence in humans has been confirmed by detecting them in human biospecimens: feces, serum, urine, saliva, hair, tissue and blood [23,24]. Bisphenol A (BPA) is used in manufacturing polycarbonate and epoxy resins for food consumer products and packages. There is also cumulative exposure from contaminating soils, aquatic environments, drinking water, air and dust particles [25]. The estrogen activity alteration is the most widely studied effect of BPA and analogues, enhancing endocrine disruptor activities [26]. Moreover, some studies have shown obesogenic effects through microbiota dysbiosis [27], fat cell development, and lipid accumulation [28]. There are several regulations enforced concerning the hazards of Bisphenol A, as derivative of polycarbonates plastics and epoxy resins, used in food contact materials, toys, or other products. In order to protect the consumers from cumulative exposure, the tolerable daily intake (TDI) for BPA is permanently re-evaluated according to new toxicity data through specific international projects, such as U.S. National Toxicology Program (CLARITY-BPA program) [29] or European Food Safety Authority (EFSA) comprehensive re-evaluation of BPA exposure and toxicity [30].
Moreover, commensal microorganisms isolated from human microbiota could in general fulfill the criteria of safety assessment and the status of Qualified Presumption of Safety (QPS) [31,32]. Similarly, most Bacillus subtilis cluster species are considered QPS [33] and they are increasingly marketed as products [34]. Conversely, Bacillus cereus cluster species can be also present in the gut microbiota, but they are not considered as QPS [34,35].
Next-generation sequencing (NGS) platforms and WGS of microorganisms have enlarged the molecular comparison knowledge on the gene collection for encoding enzymes, and better taxonomy has supported appropriate classification. Moreover, specific WGS gene description is needed to consider the food and feed safety aspects of microbiota cultivated strains [35].
Genome mining tools and phenotypic analysis are complementary approaches to predict and demonstrate the production of active secondary metabolites such as antimicrobial products from Bacillus species [36]. Genome mining revealed the potential for known and novel PKs extensively in Bacillus (Figure 1). Moreover, based on the prediction of the general architecture, novel clusters were identified in novel Bacillus spp. variants. In addition, more recent in silico and bioinformatics approaches seem to be successful to find and verify the microbial potential to produce valuable enzymes for biotechnological applications [36].
The main objective of the present study was to determine the antimicrobial effects of catalogue of microorganisms isolated from human gut, by applying directed-culturing methods after the addition of endocrine disruptor chemicals. Taxa groups of isolated bisphenol A (BPA)-degrading Bacillus spp. will be analyzed by with in vitro assays to demonstrate the bioactive substances released against commensals and critical pathogens according to the World Health Organization (WHO). Moreover, genome mining and in silico tests will be used for disclosing the genes responsible for antimicrobial production and its enzymatic pathways.

2. Materials and Methods

2.1. Microbiota Sampling Bank and Directed Culturing Approach

Ten isolates from fecal human microbiota collections of 0–1 year old infants (Isolates B-Project INFABIO) appropriately maintained at −80 °C underwent a directed culturing approach using 0.5 g of the fecal specimen in 1.5 mL of Brain Heart Infusion or Man Rogosa and Sharpe (BHI/MRS) broths, adding different concentrations of BPA (0.5, 10, 20, and 50 ppm), in order to search tolerant and/or potentially BPA biodegrading microorganisms, incubation for 72 h. Further serial dilutions and spreading onto BHI/MRS solid media plus incubation under aerobic and anaerobic conditions (anaerobic jars anaerocult®) at 37 °C over 72 h were applied. BPA-tolerant colonies with distinguishing features were isolated as pure culture for subsequent morphological, phenotypic, and genotypic identifications: bacterial cell counts, gram staining, spore staining, capsule staining, catalase activity, oxidase, and motility tests.

2.2. BPA Microbiota Tolerance Testing

BPA biodegradation microbiota capacity was tested directly adding BPA to the human fecal samples. The specimens were exposed to 25 ppm concentration of BPA at 30 °C during 72 h. BPA was measured in the extracts and supernatants through Liquid chromatography–mass spectrometry (LC-MS/MS) system for BPA quantification. Chemicals, reagents, instrumentation, and software for bisphenols determination were provided by CIC services under validated procedures previously described by García-Córcoles et al. [38].

2.3. Culturing- Isolation of Bacillus Catalogue

A common approach to isolate Bacillus strains from microbiota has been pursued in our research team [39]. For this study, ten isolates from fecal human microbiota collections of 0 to 1 year old infants (Isolates B-Project INFABIO) and 6–8 year-old children (Isolates C-Project OBEMIRISK) were obtained by a serial dilution method, with exposure to different BPA concentrations (0.5, 10, 20, and 50 ppm) over 72 h and further spreading in BHI/MRS media incubated under aerobic and anaerobic conditions (anaerobic jars anaerocult®) at 37 °C. The BPA-tolerant bacterial colonies with distinguishing features were isolated as pure culture for subsequent morphological, phenotypic, and genotypic identifications: bacterial cell counts, gram staining, spore staining, capsule staining, catalase activity, oxidase, and motility tests.

2.4. Genomic DNA Extraction, Taxonomy Identification and Phylogenetic Analysis

Genomic DNA was extracted using DNeasy columns (Qiagen®, Hilden, Germany) following the manufacturing instructions. The isolated DNA was quantified using Nanodrop (Thermo Scientific® Waltham, MA, USA) and biophotometer (Eppendorf® D30). The quality of DNA was monitored through gel electrophoreses. Complete 16S RNA gene sequencing of selected bacterial strains was done by Sanger method (Institute of Parasitology and Biomedicine “López-Neyra” IPBLN Service). Forward and reverse sequences were provided separately. Reverse sequence was converted to complementary sequence with Chromas Pro 2.0 software (Technelysium Pty Ltd., Tewantin, Australia). Sequences were examined for maximum homology against GenBank using National Center for Biotechnology Information NCBI’s BLASTn program. The collection and comparison of complete 16S rRNA gene sequences were performed using the Ezbiocloud platform [40].

2.5. Enzymes Tests

Relevant enzymatic production assays were carried out to verify the potential of gut microbiota strains to synthetize relevant enzymes in the biotechnological and industrial context. Starch, carboxymethylcellulose, inulin, tween 20 and 80, and DNase supplemented media were used to determine the degradation of different substrates according to complementary methodologies [41,42,43,44,45,46].

2.6. Antimicrobial In Vitro Tests

Antimicrobial activity was tested by agar well diffusion method. Under Joint FAO/WHO Expert Committee on Food (JECFA) procedures [47] and the study carried out by Powthong & Suntornthiticharoen [48], nine different bacteria were used as indicators to verify the antimicrobial capacity of the Bacillus spp. isolated from the gut microbiota. To determine the synthesis of antimicrobial compounds, several isolated strains were selected according to preliminary antimicrobial tests and the main taxonomy groups: strains close/represented by rB1 (Bacillus sp. AM1), strains close/represented by rB3 (Bacillus siamensis (KCTC 13613)), strains close/represented by rB7 (Bacillus cereus (AFS039342)). Plates with 20 mL of Müller-Hinton agar were prepared and test microorganisms used as indicators: Bacillus cereus, Bacillus circulans, Staphylococcus aureus, Streptococcus pyogenes, Escherichia coli, Serratia marcescens, Klebsiella spp., Pseudomonas spp., and Salmonella spp., were adjusted to a cell density of 0.5 on the McFarland scale in sterile 0.85% NaCl solution. The data were expressed as mean of the three replicates. Tests were done spreading the indicator microbial strains over the surface of the Müller-Hinton agar using sterile cotton swab. Inside six mm diameter oxford wells generated in agar, 20 µL of antibiotic producing bacteria extract was added. Standards appropriate positive controls (ampicillin, gentamycin, and streptomycin at 10 µg) and negative/blank (sterile media/ethanol) were used. The plates were incubated at 37 °C for 24 h and the inhibition zones were measured.

2.7. Genome Data Mining and Analysis –PKs Genes and Clusters

2.7.1. Genome Mining Tools for PKs Gene Searching

In order to discover the presence of secondary metabolites, several bioinformatics tools were used to perform genome mining. A data retrieving software has been specifically computed using Pascal programming language to obtain the PKs enzymes ID and the corresponding Loci from the genomes.
Type strain genomes from the closest species isolated were retrieved from NCBI Genome Data Bank in GenBank file format in order to list the proteins that they were able to potentially produce.
A more detailed prediction of the clusters was performed by checking the downstream and upstream genes of those involved in PKs synthesis using NCBI genome map viewer [49].

2.7.2. Prediction of Polyketides in WGS of Bacillus sp. AM1 Isolated from Microbiota

The identification of PKs gene cluster was carried out by the analysis of the WGS of Bacillus sp. AM1, GenBank CP047644.1, following the same approach explained above.

3. Results and Discussion

3.1. BPA-Tolerant Microorganisms Isolated from Human Gut Microbiota

3.1.1. BPA Microbiota Metabolization Capacities

The microbiota composition of each fecal sample was specific and contributed differentially to the biodegradation of BPA exposure levels (Figure 2). Each fecal sample (340, 349, and 437) showed a differential ability to eliminate BPA due to its taxa compositional and functional characteristics, showing sample 340 a maximum percentage of BPA degradation of 89.3% while sample 349 degraded 76% and 437 was able to eliminate 21% of the BPA concentration. Previous studies have shown the same effects in the environment [50], where they observed that different microbial communities presented a specific elimination rate dependent on their composition.
Cumulative exposure to a wide range of xenobiotics, such as BPA and its analogues, affects the microbiota diversity possessed by each individual, causing a selection of bacteria strains to populate the gut, and consequently modify its equilibrium through MDC [5]. This dysbiosis has been proven to be responsible for well-known diseases, such as obesity, diabetes, and even some hormonal-related cancers. Therefore, identification of the triggered main taxa variations and their functions remains a challenge. Moreover, the appropriate use of probiotics [50,51,52] or search for NGP to mitigate or reverse these dysbiosis are crucial [53,54]. A directed culturing approach allow us to select tolerant bacteria and mimic an ecological environment to understand better the impact of the specific enriched communities and their capacities to impact the taxa microbiota colonization.

3.1.2. Catalogue of BPA-Tolerant Bacillus spp. Isolated from Human Microbiota

Isolation and identification of BPA-tolerant Bacillus spp. strains from microbiota samples were successfully performed with the different BPA concentrations plates (0.5; 10; 20 and 50 ppm). Out of these 11 isolates analyzed, the closest species by complete gene 16S rRNA sequence were B. amyloliquefaciens, B. siamensis, B. velezensis, B. nematocida, B. cereus, and B. pacificus (Table 2).
Data obtained by parallel experimental work showed a BPA directed human fecal culturing catalogue that contained different BPA tolerant species from the following genera and percentages: Enterococcus 28%, Bacillus 27%, Staphylococcus 10%, Escherichia 8%, Clostridium 5%, and Lactobacillus 4% (data not shown). Representing Bacilli taxa (Bacillus and Lactobacillus) was a major taxa with approximately a 30% of BPA tolerant isolated strains from microbiota samples, which corroborates the predominant presence of these genera being able to overcome the impact of xenobiotics, such as BPA, as previous assays showed [39].
In line with these results, interesting properties and uses are specifically described for Bacillus spp. Recently, several Bacilli strains have been extensively proposed for use as human and animal probiotics [55,56]. Most of the species used belong to Bacillus subtilis and Bacillus amyloliquefaciens groups and special attention should be paid to the food and clinical studies with strains that showed special enzyme capacities [57] or those able to modulate and mitigate pathophysiological disorders [58].

3.1.3. Taxonomical and Phylogenetic Clustering

The phylogenetic tree based on complete 16S rRNA gene of Bacillus strains isolated from microbiota treated with BPA grouped the clusters to B. subtilis, B. amyloliquefaciens, B. velezensis, B. siamensis, B.cereus, and B. pacificus (Figure 3). The two main clustering of closely related Bacillus strains belong to B. subtilis and B.amyloliquefaciens taxonomic group (green) and B. cereus group (yellow). Three representative strains (rB1, rB3, and rB7) were further processed by bioactive compounds production tests. They were organized as follows: rB1 represented B1, B4, B5, B6, B7, B8, B9, and B9.2; rB3 represented B2 and B3; rB7 represented B7 and B12.
The strains isolated in the present work were clustered in the two main groups: B. subtilis–like (non-pathogenic) [59] and B. cereus-like (pathogenic) [60], as shown in Figure 3, however the pathogenicity features are strain-specific dependent. The work approach is based on potential uses and predictive data analysis, but for further commercial uses, a safety assessment should be performed for each strain, to demonstrate that they do not pose any safety and/or pathogenicity concerns. The battery of tests usually requested is: antibiotic resistance test no greater than existing regulatory cutoffs against clinically important antibiotics, incapacity to induce hemolysis or produce surfactant factors, and the absence of virulence or toxigenic activity in vitro.

3.2. Analysis of Bioactive Compounds Production Capacities

3.2.1. Enzymatic Activity Tests

B. subtilis, B. amyloliquefaciens, and B. licheniformis have been used as bacterial resources in the industrial context for the production of a wide range of enzymes and bioactive compounds for decades. Bacillus sp. AM1 and other strains belonging to Bacillus genus have shown remarkable hydrolytic enzyme capacity (Table 3), being related to the performance of key roles in several biotechnological and many manufacturing processes [61,62,63].

3.2.2. Antimicrobial Activity Tests

The results obtained from antimicrobial experimental tests carried out with the representative isolated microorganisms from different taxonomic clusters confirmed the ability of the strains B1 and B3 to inhibit Gram-negative and Gram-positive bacteria (Table 4).
Preliminary results grouped the strains according to their capacity of antibiotic production with very similar inhibiting zone value, which were also in agreement with the main taxonomic clusters. rB1 represented B1, B4, B5, B6, B7, B8, B9, and B9.2; rB3 represented B2 and B3; rB7 represented B7 and B12.
rB1 and rB3 strains were found to be antagonistic against Gram-positive Bacillus cereus, Bacillus circulans, Staphylococcus aureus, Streptococcus pyogenes (diameter of zone of growth inhibition 10–17 mm) and also against Gram-negative food-borne pathogenic bacteria Serratia marcescens, Escherichia coli, Salmonella, and Klebsiella pneumoniae (diameter of zone of growth inhibition 10–20 mm). Conversely, the strains rB7 did not show any production of antimicrobial effects.
Minimum inhibitory concentration (MIC) values were similar to those resultant of other polyketides antimicrobial effects previously described, being significant differential and higher the effects found against Klebsiella [64]. Therefore, the search for a putative biosynthetic pathway of the pks gene product proceeded after the validated molecular antimicrobial attributions.

3.3. WGS Data Mining and In Silico Analysis

3.3.1. WGS Mining in Type Strains

The bioinformatics analysis carried out on the type strains of closest species identified as cultivable Bacillus species from microbiota showed specific enzymes involved in PKs biosynthesis (Table 5). The genome mining identified the clusters with the genomes from closest homologue type strains available in the database. Bioinformatic tools and Pascal ad hoc software allowed the exhaustive analysis of genomes making it a powerful prediction tool.
According to the results, Bacillus amyloliquefaciens, B. siamenensis, B. velezensis, B. subtilis and B. atrophaeus harbor almost complete pks genetic macroclusters for the production of polyketides. While B. licheniformis, B. cereus, B. pacificus, and the probiotics B. clausii, B. coagulans did not contained the PKs loci. The antimicrobial effects of polyketides are site colonization specific and the strains are scarcely used for health biotechnological interests [65]. Moreover, the ecological impact of these antimicrobial substances on the gut microbiota composition may have a huge impact, beyond the modification and control of the colonization of commensals and pathogenic bacteria, e.g., to cause weight gain effects in humans as well as in animals [66].

3.3.2. WGS Representative Bacillus sp. AM1 from Microbiota: Genome Mining Data

From the analysis of the specific Bacillus sp. AM1 WGS, the cluster genes and enzymes related to PKs biosynthesis were identified (bae, mln, and dfn) and they were related to the production of bacillaene, and two other polyketides macrolactin and difficidin.
This complex microbial ecosystem seems to be enriched in new bacterial strains belonging to Bacillus genus that produce PKs with a wide range of applications in the current biotechnological context. Among these applications, PKs stand out for their antimicrobial capacity against certain bacterial species. Therefore, further identification through bioinformatics tools and experimental data will confirm the functionality of these bioactive substances.
Advances in NGS and in silico tools allow to perform an appropriate screening of genes of concern or interest in microbiota, such as antimicrobial resistance genes and the capacity of antimicrobial production of cultivable isolates WGS. A better understanding of the microbiota ecology, driven by the bioactive compounds released by its components, will lead to better clinical interventions. Antimicrobials naturally synthetized by gut microorganisms are mainly described as bacteriocins [12]. However, it is important to consider other molecules acting as antimicrobial as polyketides. Isolation and elucidation of PKs structures by nuclear magnetic resonance (NMR) methods are limited by the concentration needed for analysis [67]. Thus, it is possible to predict the types of PKs and their variants, as showed for Bacillales [37]. Genome mining performed in the present study allowed BLAST driven search for predicted PKs clusters. Pascal ad hoc software analysed the type strain genomes making it a powerful prediction tool. Similarly, another useful prediction tool could be used as nonribosomal peptide-synthetase NRPS/PKs substrate predictor [68].
Importantly, Bacillus and specific WGS genes description is needed to verify the safety assessment of different strains if they are proposed to be used in food or feed chain [70]. Moreover, the safety of a beneficial microbe or probiotic strain must be sufficiently characterized by high-throughput technologies, safe for the intended use, and assessed through pathogenicity, immunotoxicity, and colonization, in addition to its antibiotic resistance profile [71]. However currently, there is no consensus or standardization for the interventional use of probiotics [72]. In addition to general guidelines for the qualification of the QPS, European Food Safety Authority (EFSA) made a supplementary requirement for Bacillus species other than the Bacillus cereus group, where a cytotoxicity test should be performed to determine whether the strain produces high levels of non-ribosomal synthesised peptides. One of the criteria for strains to fulfill and meet the requirements for QPS and generally recognized as safe (GRAS) standards is antimicrobial activity and the absence of antimicrobial resistance genes as a possible safety concern against critically important antimicrobials (CIAs) or highly important antimicrobials (HIAs), which might eventually be transferred via horizontal gene transfer to pathogenic bacteria during food manufacture or after consumption [33,73]. According to the general guidelines for the qualifications of the QPS, unless the strain qualifies for the QPS approach or belongs to a taxonomic unit, known not to produce antimicrobials relevant to use in humans and animals, assessment should be made to determine the inhibitory activity of culture supernatants against reference strains, known to be susceptible to a range of antibiotics and the inhibitory substance [47]. A slight adjustment has been made for the production strains, which have to demonstrate the absence of carry-over into the final product together with the exact phase of the industrial scale manufacturing process, and whether any CIAs or HIAs are used during the manufacturing of the product, to determine compatibility with other additives showing antimicrobial activity and, furthermore, possible co-/cross-resistance [35].

4. Conclusions

Bacillus strains isolated from human gut microbiota, and taxonomically closest to the safely qualified B. subtilis and B. amyloliquefaciens groups, became cultivable predominant taxa when high bisphenol exposure conditions were tested. In parallel, these strains harbored PKS molecular gene biosynthetic loci and showed phenotypic antimicrobial effects. Therefore, they might be proposed as beneficial microorganisms with molecular features that would contribute to modulate the ecological taxa composition and functionality of human gut microbiota. Intervention studies will be further needed to demonstrate the ability to recover from microbiota dysbiosis, triggered by high MDC exposure diets and lifestyles, towards eubiosis and healthier status.

5. Patents

IPR-823 Application in progress.

Author Contributions

Conceptualization, M.A.; methodology, A.T.-S. and J.P.-C.; writing—original draft preparation, A.T.-S., A.L.-M., and J.P.-C.; writing—review and editing: A.T.-S., J.P.-C., A.L.-M., Á.R.-M., K.C. and M.A.; supervision, M.A.; project administration, M.A.; funding acquisition, M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This work was carried out within the frame of FEDER-Infrastructure Project: IE_2019-198 and OBEMIRISK EFSA-Partnering Grant Project GP/EFSA/ENCO/2018/03-GA04. A.T.-S. and Á.R.-M. “Colaboración Investigación—Master”. J.P.-C. “ICARO-Extracurriculares Prácticas”. A.L.-M. “Incentivación de la Investigación”. Plan Propio-UGR. K.C. is collaborating with UGR under the EU-FORA Programme (2020/2021).

Institutional Review Board Statement

Ethical review and approval were waived for this specific study, due to the specimens collection belonged to our previous approved project INFABIO.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Part of the results are from Alfonso Torres-Sánchez doctoral thesis, Nutrition and Food Technology Doctorate Program of the University of Granada and Ana López-Moreno doctoral thesis, Biomedicine Doctorate Program.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

ANAnorexia Nervosa
BHIBrain-Hearth Infusion
BPABisphenol A
CIAsCritically Important Antimicrobials
CICCentro de Instrumentación Científica
ECEnzyme Commission number
EFSAEuropean Food Safety Authority
GRASGenerally Recognized as Safe
HCHealthy control
HIAsHighly Important Antimicrobials
IPBLNInstitute of Parasitology and Biomedicine “López-Neyra”
JECFAJoint FAO/WHO Expert Committee on Food AdditivesLiquid
LC-MS/MSLiquid Chromatography-Mass Spectrometry
MCLMaximum Composite Likelihood
MDCMicrobiota Disrupting Chemicals
MetSMetabolic syndrome
MICMinimum Inhibitory Concentration
MRSMan-Rogosa-Sharpe
NAFLDNonalcoholic fatty liver disease
NCBINational Center for Biotechnology Information
NGPNext Generation Probiotics
NGSNext Generation Sequencing
NMRNuclear Magnetic Resonance
NRPSNonribosomal Peptide-synthetase
OBObesity
OWOver-weigth
PKsPoliketides
QPSQualified Presumption of Safety
SNSupernatant
T1DType 1 Diabetes
T2DType 2 Diabetes
WGSWhole Genome Sequences
WHOWorld Health Organization

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Microorganisms 09 01615 g001 550
Figure 1. Conserved PKs proteins and functions in Bacillus modified from Straight et al. [37].
Figure 1. Conserved PKs proteins and functions in Bacillus modified from Straight et al. [37].
Microorganisms 09 01615 g001
Microorganisms 09 01615 g002 550
Figure 2. BPA relative percentage of degradation by human fecal specimens. (LC-MS/MS) system was used for BPA quantification; SN: Supernatant.
Figure 2. BPA relative percentage of degradation by human fecal specimens. (LC-MS/MS) system was used for BPA quantification; SN: Supernatant.
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Microorganisms 09 01615 g003 550
Figure 3. Phylogenetic tree based on gene sequences of isolated gut microbiota strains. The tree was obtained by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach and Kimura 2-parameter model. The species and strain names are shown. Bootstrap values shown after 1000 resamplings. Main clusters are highlighted: in green close to B.subtilis group and yellow close to B.cereus group.
Figure 3. Phylogenetic tree based on gene sequences of isolated gut microbiota strains. The tree was obtained by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach and Kimura 2-parameter model. The species and strain names are shown. Bootstrap values shown after 1000 resamplings. Main clusters are highlighted: in green close to B.subtilis group and yellow close to B.cereus group.
Microorganisms 09 01615 g003
Table
Table 1. Bacilli taxa modifications from clinical trials of metabolic related diseases.
Table 1. Bacilli taxa modifications from clinical trials of metabolic related diseases.
ReferenceClinical Trials—Disease /Sample Size and Clinical TraitsTaxa Modifications
[13]OB; n = 192; HC n = 25; OW n = 22; OB n = 145↑ Bacillus in OW and OB
[14]OB, AN; n = 49; HC n = 20; OB n = 20; AN n = 9↑ Lactobacillus in OB
[15]T2D; n = 36; HC n = 18; T2D n = 18↑ Lactobacillus in T2D
[16]T2D, OB; n = 60; HC n = 20; Obese-T2D n = 40↑ Bacillus sporothermodurans in OB-T2D
[17]T1D, T2D; n = 110; HC n = 40; T2D n = 49; T1D n = 21↑ Lactobacillus in T1D and T2D
[18]NAFLD; n = 126; HC n = 83; NAFLD n = 43↓ Lactobacillus in NAFLD
[19]NAFLD; n = 67; HC n = 37; NAFLD n = 30↑ Lactobacillaceae in NAFLD
[20]NAFLD; n = 60; HC n = 30; NAFLD n = 30↑ Lactobacillus in NAFLD
[21]NAFLD, OB; n = 73; HC n = 20; OB-NAFLD n = 36; OB-non-NAFLD n = 17↑ Bacilli in OB-NAFLD
↑ Lactobacillus in non-NAFLD
[22]MetS; n = 655; Monozygotic twins n = 306; Dizygotic twins n = 74; Siblings n = 275↑ Lactobacillus in MetS
AN: anorexia nervosa; HC: healthy control; MetS: metabolic syndrome; NAFLD: non-alcoholic fatty liver disease; OB: obese; OW: overweight; T1D: type 1 diabetes; T2D: type 2 diabetes. ↑ Increasements.
Table
Table 2. Bacillus isolates from human microbiota and 16S rRNA complete gene homology description.
Table 2. Bacillus isolates from human microbiota and 16S rRNA complete gene homology description.
Microbiota IsolatesClosest Taxa—[Strain] Best Hitbp Position 16S rRNAQuery Cover (%)Identity (%)Accession Number
B1Bacillus siamensis [LRM10-3D]15,030100100MT645306.1
Bacillus velezensis [XC1] 100100MT649755.1
B2Bacillus velezensis [CR-502]148395.499.14AY603658
B3Bacillus siamensis [KCTC 13613]149010098.00AJVF01000043
B4Bacillus siamensis [KCTC 13613]151510099.66AJVF01000043
Bacillus nematocida [B-16] 10099.73AY820954
Bacillus amyloliquefaciens [DSM7] 10099.52FN597644
B5Bacillus siamensis [KCTC 13613]151610098.91AJVF01000043
Bacillus nematocida [B-16] 10098.98AY820954
Bacillus velezensis [CR-502] 95.499.22AY603658 FN597644
Bacillus amyloliquefaciens [DSM7] 10098.78
B6Bacillus velezensis [CR-502]150495.499.93AY603658
B7Bacillus cereus [AFS039342]151010099.39NUMR01000072
Bacillus pacificus [NCCP 15909] 10099.34CP041979.1
B8Bacillus velezensis [CR-502]152095.499.93AY603658
B9Bacillus velezensis [CR-502]149995.499.22AY603658
B9.2Bacillus siamensis [KCTC 13613]149910099.52AJVF01000043
Bacillus nematocida [B-16] 10099.59AY820954
Bacillus amyloliquefaciens [DSM 7] 10099.39FN597644
B12Bacillus cereus [AFS039342]154310099.39JMQC01000008
Bacillus pacificus [NCCP 15909] 99.099.35CP041979.1
Table
Table 3. Enzymatic activity in gut microbiota isolates.
Table 3. Enzymatic activity in gut microbiota isolates.
Enzyme TestMicrobiota Isolates
rB1rB3rB7
Starch+++++
Carboxymethylcellulose---
Inulin+-+
Tween 80---
DNase++--
Table
Table 4. Antimicrobial activity of BPA-tolerant human gut microbiota isolated strains.
Table 4. Antimicrobial activity of BPA-tolerant human gut microbiota isolated strains.
Target Indicator BacteriaStrains rB1Strains rB3Strains rB7
Diameter of inhibitory zone (mm) ± SD 1
Bacillus cereus15 ± 017 ± 0-
Bacillus circulans13 ± 014.3 ± 1.2-
Staphylococcus aureus11.7 ± 0.610 ± 0-
Streptococcus pyogenes15 ± 013.3 ± 0.6-
Serratia marcescens17 ± 015.3 ± 1.5-
E. coli15 ± 013.3 ± 0.6-
Salmonella11 ± 010 ± 0-
Klebsiella20 ± 0 *15 ± 0 *-
Pseudomonas---
1 Values are mean diameter of inhibitory zone (mm) ± SD of three replicates. The diameter of well (6 mm) was included. (-) Diameter of inhibitory zone <7 mm considered as no antimicrobial activity. * Significant values compared to theroretical values from B. subtilis polyketides [64].
Table
Table 5. Gene-encoding and corresponding enzymes involved in Polyketide biosynthesis in WGS of Type strain of Bacillus spp.
Table 5. Gene-encoding and corresponding enzymes involved in Polyketide biosynthesis in WGS of Type strain of Bacillus spp.
EnzymeEnzyme description EC numberB. amyloliquefaciens WF02T
NZ_CP053376		B. siamenensis SCSIO 05746T
NZ_CP025001		B. velezensis
CBMB205T
NZ_CP011937		B. subtilis
168T
NC_000964		B. atrophaeus
BSST
NZ_CP007640		B. sp-AM1
B1T
CP047644.1)
PksAHypothetical protein/EC:3.1.2.6WP_024085315.1 174131..1741526WP_060962748.1 2494188..2494397WP_032874955.1 2222103..2222312NP_000389590.1 1782713..1783390WP_013390522.1
1165636..1167084		1787442..1787651
QHJ03379.1
-Hypothetical protein/EC:3.1.2.6WP_024085326.1 1816193..1816555WP_016936035.1 2419160..2419522WP_007410383.1 2146808..2147170YP_0009513956.1 1783500..1783766WP_003328852.1
1167393..1167932		-
RegulatorTetR family transcriptional regulator C terminal ---NP_000389589.1 1781906..1782523WP_003328851.1
1168054..1168644		-
PksBMBL fold metallo hydrolase/
EC: 2.3.1.39		WP_024085316.1 1742160..1742837WP_060962747.1 2492787..2493464WP_032874957.1 2220496..2221173YP_0009513956.1 1783500..1783766WP_003328850.1
1168942..1169619		1788295..1788972
QHJ03380.1
PksCACP S malonyltransferase/
EC:2.3.1.51		WP_014305029.1 1743152..1744021WP_060962746.1 2491603..2492472WP_032874959.1 2219312..2220181NP_000389591.1 1783763..1784629WP_003328849.1
1170013..1170879		1789287..1790156
QHJ03381.1
PksDAcyltransferase domain containing protein/EC: 2.3.1.39WP_003154101.1 1744158..1745132WP_060962745.1 2490494..2491468WP_032874961.1 2218201..2219175NP_000389592.2 1785133..1786107WP_003328847.1
1171417..1172382		1790293..1791267
QHJ03382.1
PksEACP S malonyltransferase/
EC:1.3.1.9 and 1.3.1.10		WP_003154100.1 1745134..1747374ID Not found
2488250..2490492		WP_032874963.1 2215959..2218199NP_000389593.3 1786104..1788407WP_003328846.1
1172389..1174752		1791269..1793509
QHJ03383.1
AcpKAcyl carrier protein/EC:2.3.3.10WP_003154099.1 1747440..1747688WP_060962743.1 2487934..2488182WP_012117592.1 2215645..2215893NP_00570904.1 1788469..1788717WP_003328845.1
1174891..1175139		1793575..1793823
QHJ03384.1
PksFPolyketide beta ketoacyl:ACP synthase/EC: 4.2.1.17---NP_000389594.2 1788695..1789942WP_003328844.1
1175117..1176364		-
PksGHydroxymethylglutaryl CoA synthase family/EC: 4.2.1.17WP_003154098.1 1747740..1749002WP_060962742.1 2486620..2487882WP_032874965.1 2214331..2215593NP_000389595.2 1789943..1791205WP_010788667.1
1176364..1177626		1793875..1795137
QHJ03385.1
PksHEnoyl CoA hydratase/isomeraseWP_024085319.1 1748999..1749772WP_060962741.1 2485850..2486623WP_032874967.1 2213561..2214334NP_000389596.1 1791193..1791972WP_087941777.1
1177614..1178390		1795134..1795907
QHJ03386.1
PksIenoyl CoA hydratase/isomerase family proteinWP_003154094.1 1749782..1750531WP_060962740.1 2485091..2485840WP_003154094.1 2212802..2213551NP_000389597.2 1792012..1792761WP_003328841.1
1178438..1179184		1795917..1796666
QHJ03387.1
PksJNon ribosomal peptide synthetaseWP_024085320.1 1750571..1765525WP_060962739.1 2470129..2485062WP_032874969.1 2197814..2212762NP_000389598.3 1792806..1807937WP_013390525.1
1179247..1194429		1796706..1811657
QHJ03388.1
PksMSDR family NAD(P) dependent oxidoreductase EC:1.6.5.2WP_165869029.1 1765509..1778951WP_167388675.1 2456724..2470145WP_162859398.1 2184400..2197830NP_000389601.3 1821553..1834341WP_013390526.1
1194431..1208248		1811659..1825086
QHJ03389.1
PksMSDR family NAD(P) dependent oxidoreductase/EC:1.6.5.2WP_024085322.1 1778969..1789513WP_101605493.1 2446202..2456707WP_032874973.1 2173847..2184382NP_000389602.3 1834409..1850875WP_013390527.1
1208267..1221238		1825104..1835639
QHJ03390.1
PksNNon ribosomal peptide synthetase-WP_101605492.1 2429908 2446212WP_032874975.1 2157559 2173857NP_000389604.2 1850890 1858521WP_087941783.1
1221318..1237793		1835629..1851930
QHJ03391.1
PksRPolyketide synthase dehydratase domain/EC:2.1.1.-WP_024085324.1 1805818..1813275WP_060962735.1 2422440..2429894WP_032874977.1 2150088..2157545NP_000389600.3 1807921..1821537WP_003328830.1
1237809..1245533		1851944..1859401
QHJ03392.1
PksSCytochrome P450/EC:1.14.14.-WP_024085325.1 1813410..1814621WP_060962734.1 2421090..2422301WP_032875233.1 2148742..2149953NP_000389605.2 1858566..1859783WP_003328829.1
1245647..1246888		1859536..1860747
QHJ03393.1
B. licheniformis (strain ATCC 14580)T; NC_006270 PKs Loci was not found; B. cereus (strain B4264) NC_011725 PKs Loci was not found; B. pacificus (strain R1) NC_NJQG01000001 Loci was not found; B. clausii (strain 7520-2 contig00001)T NZ_NPBN01000001 PKs Loci was not found; B. coagulans (B4099 NODE_1)T NZ_LQYI01000001 PKs Loci was not found; B. nematocida (strain B-16T) No WGS is available—Analysis PKS Loci was not applicable [69].
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Torres-Sánchez, A.; Pardo-Cacho, J.; López-Moreno, A.; Ruiz-Moreno, Á.; Cerk, K.; Aguilera, M. Antimicrobial Effects of Potential Probiotics of Bacillus spp. Isolated from Human Microbiota: In Vitro and In Silico Methods. Microorganisms 2021, 9, 1615. https://doi.org/10.3390/microorganisms9081615

AMA Style

Torres-Sánchez A, Pardo-Cacho J, López-Moreno A, Ruiz-Moreno Á, Cerk K, Aguilera M. Antimicrobial Effects of Potential Probiotics of Bacillus spp. Isolated from Human Microbiota: In Vitro and In Silico Methods. Microorganisms. 2021; 9(8):1615. https://doi.org/10.3390/microorganisms9081615

Chicago/Turabian Style

Torres-Sánchez, Alfonso, Jesús Pardo-Cacho, Ana López-Moreno, Ángel Ruiz-Moreno, Klara Cerk, and Margarita Aguilera. 2021. "Antimicrobial Effects of Potential Probiotics of Bacillus spp. Isolated from Human Microbiota: In Vitro and In Silico Methods" Microorganisms 9, no. 8: 1615. https://doi.org/10.3390/microorganisms9081615

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