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. 2021 Jun 11;11(7):326. doi: 10.1007/s13205-021-02867-9

Draft genome sequence and potential identification of a biosurfactant from Brevibacteriumcasei strain LS14 an isolate from fresh water Loktak Lake

Khushbu Kumari 1, Sudhanshu K Gouda 1, Ananta N Panda 1, Lopamudra Ray 1,4, Dinabandhu Sahoo 2,5, Tanmaya Nayak 1, Vipin Gupta 3, Vishakha Raina 1,✉
PMCID: PMC8196162  PMID: 34194910

Abstract

This study reports the whole-genome sequencing and sequence analysis of a bacterial isolate Brevibacterium casei strain LS14, isolated from Loktak Lake, Imphal, India. The de novo assembled genome reported in this paper featured a size of 3,809,532 bp, has GC content of 68% and contains 3602 genomic features, including 3551 protein-coding genes, 46 tRNA and 5rRNA. A biosurfactant biosynthesis gene cluster in the genome of the isolated strain was identified using AntiSMASH online tool V3.0.5 and KAAS (KEGG Automatic Annotation Server). The presence of biosurfactant was demonstrated by drop collapse, oil displacement and emulsification index. Subsequent chemical characterization using FTIR and LC–MS analyses revealed surfactin and terpene containing biosurfactant moieties. Also, the presence of genes involved in terpenoid synthesis pathway in the genome sequence may account for biosurfactant terpenoid backbone, but genes for later-stage conversion of terpenoid to biosurfactant were not ascertained.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-021-02867-9.

Keywords: Brevibacteriumcasei strain LS14, Whole genome sequencing, Comparative genomics, Biosurfactant

Introduction

Microbial biosurfactants are structurally and chemically diverse molecules which are amphiphilic in nature with the ability to reduce surface tension and interfacial tension between two insoluble phases (Gautam and Tyagi 2006). The extraordinary and environmentally friendly properties like low toxicity, stability and effectiveness at high pH and temperature and biodegradability make them favorable candidates for environmental bioremediation, pharmaceutical and cosmetic, food, agriculture, mining, heavy metal removal and enhanced oil recovery industries (Geys et al. 2014; Rebello et al. 2014). The presence of surface active hydrophilic and hydrophobic moieties, which may be chemical structures of glycolipids, lipopeptides, phospholipids, fatty acids or hydroxyl fatty acid chains linked to carbohydrates and peptides, polymeric and particulate lipids has been extensively studied (Marchant and Banat 2012; Satpute et al. 2016; Shekhar et al. 2015). Biosynthesis of biosurfactants (BSs) involves various metabolic and biosynthetic pathways (Santos et al. 2016), for example, a multi-modular protein complex non-ribosomal peptide synthetase (NRPS) is known for biosynthesis of lipopeptide-type biosurfactants like surfactin, lichenysin, iturin and arthrofactin (Santos et al. 2016; Shaligram et al. 2016) which have high similarity in structures even from different microbial species. The NRPSs modular enzymes in lipopeptide BSs catalyze synthesis of peptide products, such as siderophores, terpenes, antibiotics, pigments, etc., which are known for anti-microbial, anti-tumor and anti-inflammatory properties (Ansari et al. 2004; Satpute et al. 2010; Song et al. 2015). Terpene and terpenoid-based BSs have been reported from Actinobacteria with numerous pharmaceutical and industrial applications (Falquet et al. 2002; Kügler et al. 2015; Osawa et al. 2010).

BS producers have been reported from soil, sediments, fresh and marine water as well as extreme hypersaline environments and oil reservoirs (Cai et al. 2014; Das et al. 2015; Płaza et al. 2015). Although several discrete soil-isolated bacteria have been reported for BS production predominantly from several species of Pseudomonas, Bacillus, Burkholderia and yeasts (Kügler et al. 2015), the most dominant group of bacteria belonging to phylum Actinobacteria is known for playing major environmental roles and as producers of secondary metabolites, bioactive compounds, antibiotics have also been described for BS production (Falquet et al. 2002; Kügler et al. 2015; Osawa et al. 2010). Many strains from genus Brevibacterium (order Brevibacteriales) (Salam et al. 2020) are known to be BS producers, such as Brevibacterium aureum MSA13 (Kiran et al. 2010), Brevibacterium luteolum (Vilela et al. 2014), which are genetically diverse and found in various environments; however, they are less explored from freshwater. It is notable that microbial BSs from freshwater are reported for their low toxicity and easy biodegradability (Poremba et al. 1991a, b). With changes in methods of microbial research from culture-dependent to culture-independent, the new-generation sequencing technology facilitates to provide valuable genomic insights into genetics, evolution, metabolic pathways for BS production and several biological functions (Edwards and Holt 2013). As of now, whole-genome sequencing and annotation is widely used for analysis of microbial BS (Kamada et al. 2014).

Loktak Lake, a freshwater floating lake located in south of Imphal valley in northeast of India possesses a unique disposition and is notable for large floating masses of heterogeneous vegetation and decomposing organic matter called “phumdi”. The region is considered endemic for several plant and animal species making it a microbial biodiversity hotspot with distinct physiological and metabolic attributes for bioprospecting of enzymes and metabolites like biosurfactants. Due to its biodiversity value and ecological status, the lake is a designated Ramsar site and is listed in Montreux record (Das Kangabam and Govindaraju 2019).

Here, we report the whole-genome sequencing and functional feature analysis of a BS producing Brevibacterium casei strain LS14 from Loktak Lake using integrated approach of genomics and chemical characterization for analysis of surfactin and terpene-based biosurfactants.

Materials and methods

Chemicals, glasswares, and reagents

All the plastic wares and glasswares (DURAN, Wertheim, Germany) used were washed and rinsed with MilliQ (RiOs 16 Century, Millipore, USA) water. The analytical-grade reagents used for the chemical analyses of sediment samples were mostly from Merck chemicals (Merck Millipore, Darmstadt, Germany) and HiMedia (HiMedia Labs, Mumbai, India).

Sample collection and isolation of bacterial strain

The sediment samples were collected from Loktak Lake (24.5593 °N, 93.8147 °E), through a Van Veen type of grab sampler (KC Denmark) and hollow bamboo sticks. Samples were then carried to the research laboratory for analysis and were stored at 4 °C and − 20 °C for extended storage. For physicochemical characterization and microbial analysis, sediments were homogenized using autoclaved mortar and pestle. The homogenates obtained were then serially diluted in normal saline (0.9% NaCl), plated on different selective growth media and incubated under the aerobic condition at 30 °C until noticeable bacterial colony growth. Standard bacteriological media (HiMedia) like Lysogeny Broth (LB), Zobell Marine Agar (ZMA), Starch Casein Agar (SCA), Actinomycetes Agar have been used for bacterial isolation. Only consistent morphotypes were chosen from subsequent cultures for further screening.

Morphological and biochemical characterization

Microscopic morphology of the strain was observed during growth LB Agar and the bacterial size and shape were noted using Scanning Electron Microscopy (Nova™ Nanosem 450). The biochemical characterization including enzyme assays and other phenotypic assays of the strain LS 14 was performed and compared with Brevibacterium casei (Kim et al. 2013).

DNA isolation, library preparation, and genome sequencing

The genomic DNA extraction from the bacterial culture of LS14 was done using PureLink® Invitrogen Genomic DNA Mini Kit using the protocol provided with the Mini Kit. The DNA isolated was checked for its integrity by resolving it on agarose gel (1% w/v). The quality and quantity of the DNA were determined by measuring UV absorbance at 260 nm (Agilent Cary 60 UV–Vis). DNA samples with an absorbance ratio of ~ 1.8 at 260 nm and 280 nm were further used for sequencing. The whole-genome sequence of strain LS14 was performed at AgriGenome Labs Private Limited (Kochi, India). DNA paired-end libraries construction was performed using NEBNext Ultra DNA Library Prep Kit following the manual provided. The whole-genome sequencing for the strain LS14 was performed using Illumina HiSeq 2500 paired-end technology. To obtain high-quality reads, the sequenced raw data were pre-processed using CutAdapt v.1.11 (Martin 2011) (v1.33; available at https://github.com/najoshi/sickle) to filter out any adaptor sequences, ambiguous reads, and reads having average quality score lower than 30 in paired-end reads.

Genomic data assembly and annotation

The de novo assembler was used to assemble the quality-filtered reads using ABySS v.2.0.1, Velvet v.1.2.10 and SPAdes v.3.13.0 assembler (Zerbino 2010). The default k-mer sizes were used for the SPAdes assembly. The Kmergenie predicted k-mer value 91 is used for both Velvet and ABySS assembly. However, we used ABySS assembly for all further downstream analyses since the statistics generated were better than Velvet and SPAdes (Supplementary Table 1). Quality control assessment was performed using QUAST version 4.6. (Gurevich et al. 2013). Automated annotation service, such as Rapid Annotation Using Subsystem Technology (RAST) (Brettin et al. 2015) and NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP) (Pruitt et al. 2011), was used for gene annotation. Default parameters were used for all the bioinformatics studies. The tRNA screening was done using tRNA scan-SE version 2.0.2. (Lowe and Chan 2016). The functional annotation of LS14 strain was performed using the evolutionary genealogy of genes: Non-supervised Orthologous Groups (EggNOG-mapper 4.5) (Huerta-Cepas et al. 2015) and KEGG Automatic Annotation Server (KAAS) (Moriya et al. 2007).

Nucleotide sequence submission accession number

The 16S rRNA sequence (1364 bp) of the strain LS14 was submitted in GenBank database with accession number MK811188. This whole-genome shotgun sequencing project has been submitted in GenBank under accession number SJXG00000000.

Phylogenetic and comparative genomic analysis

Phylogenetic identification of the strain LS14 and its evolutionary relationships among closely related species were determined by 16S rRNA gene sequence analysis against prokaryotic type strain database (Yoon et al. 2017). These strains were aligned against the corresponding sequences using ClustalW (Larkin et al. 2007). The top 15 sequences of Brevibacterium species were then selected and aligned using EzTaxon database (http://eztaxone.ezbiocloud.net/) (Yoon et al. 2017). The phylogenetic tree was constructed using these aligned sequences with the help of Neighbor-joining method (Saitou and Nei 1987) in MEGA X (Kumar et al. 2018) Dermabacter hominis DSM 7083T used as an outgroup (Bhadra et al. 2008). The Kimura’s two-parameter model was used to calculate the evolutionary distance matrix (Kimura 1980). The bootstrap resampling method (Felsenstein 1985) with 1000 replicates was used to evaluate the topology of the phylogenetic tree.

Multilocus sequence typing (MLST) was performed to predict the taxonomic similarity in the genetic loci of seven housekeeping genes (dnaK, gyrA, recF, secA, dnaB, rpoD, recA), in the genome of strain LS14. For MLST analysis, above-mentioned housekeeping gene sequences of closely related type strains of genus Brevibacterium, namely (Brevibacterium casei CIP 10211T, Brevibacterium celere CIP 108809T, Brevibacterium sanguinis 2b_TX, Brevibacterium siliguriense DSM 23676T, Brevibacterium epidermis NBRC 14811T), were retrieved from NCBI Database, concatenated using MEGA X (Kumar et al. 2018) and further aligned using ClustalW (Larkin et al. 2007).

For the comparative genomic study, whole genomes of five closely related type strains belonging to Brevibacterium sp. as mentioned above (NCBI database) were compared with the strain LS14 using online tool GGDC v.2.1(Genome–Genome Distance Calculator) (http://ggdc.dsmz.de/ggdc.php#) (Meier-Kolthoff et al. 2013) and CGview (http://cgview.ca/) a comparative genomic tool (Grant and Stothard 2008).

Core genomic analysis was performed using ClustAGE online server V0.3.1 (http://vfsmspineagent.fsm.northwestern.edu/index_age.html) (PMID: 25,168,460) (Ozer 2018). FASTA files of 6 strains were uploaded at default parameters. The output tree file was processed on iTOL (Interactive Tree of Life) (https://itol.embl.de/upload.cgi) server for generating core genome phylogeny (Letunic and Bork 2019).

The ANI (average nucleotide identity) and tetranucleotide correlation index of strain LS14 were calculated using JSpeciesWS (https://www.ribocon.com/jspeciesws.html) (Richter et al. 2015) software against Brevibacterium casei CIP102111 and Brevibacterium celere CIP108809. Ortho Venn platform (http://www.bioinfogenome.net/OrthoVenn/) (Wang et al. 2015) for comparing and interpreting the orthologous gene cluster was applied.

Genomic feature analysis of strain LS14

The assembled draft genome was analyzed for secondary metabolite gene clusters using specialized pipelines, such as antibiotics and Secondary Metabolite Analysis Shell (antiSMASH V.3.0.4) (https://antismash.secondarymetabolites.org) (Weber et al. 2015) as default parameters. Genomic islands for RAST annotated genes were predicted using an integrated method combing all three IslandPick, SIGI-HMM & IslandPath-DIMOB methods available in the IslandViewer4 tool (http://www.pathogenomics.sfu.ca/islandviewer/) (Bertelli et al. 2017). The presence of any phage and insertion sequence was screened in the genome using PHASTER (PHAge Search Tool Enhanced Release) (https://phaster.ca/) (Arndt et al. 2016) and IS Semi-Automatic Genetic Annotation (IS-saga) (http://issaga.biotoul.fr/issaga_index.php) (Varani et al. 2011). Also, RGI (Resistance gene identifier) CARD database was used to predict antibiotic-resistant coding sequences (https://card.mcmaster.ca/) (Jia et al. 2016).

Primary screening for biosurfactant production

Bacterial isolates for biosurfactant producing abilities were screened using three different methods, such as Drop collapse assay, Oil displacement assay, and Emulsification index assay. For further characterization, isolates with positive biosurfactant activity were selected.

(a) Drop collapse assay

The drop collapse assay was conducted following the protocol reported in Jain et al. (1991) with a slight modification in the protocol. 10 µl of crude oil was added to the glass slide and 10 µl of cell-free supernatant on top of the crude oil drop was added. The shape of the culture drop on the oil surface was observed. Microorganisms producing biosurfactants gave a flat drop. Triton X-100 (HiMedia) was used as a positive control and deionized water was taken as a negative control.

(b) Oil displacement test

Oil displacement assay was conducted using the protocol described by Hassanshahian et al. (2014). 200 µl of crude oil was added upon 50 ml distilled water in Petri dishes. Then, 20 µl of cell-free supernatant was gently placed on the surface of oil drop. The diameter of oil displaced and the clear halo zone formed on the oil surface was measured. As a positive control, Triton X-100 was used and deionized water which showed no clear zone was taken as a negative control.

(c) Emulsification index

To measure the Emulsification activity, the Emulsification index (E24) was calculated at 25 °C following the protocol described by Wang et al. (2014). To the cell-free supernatant, crude oil was added in an equal proportion of 1:1 and vigorously vortexed for 3 min and kept still for 24 h. After 24 h incubation, the height of emulsification was measured. The emulsification index (E24) was measured as the percent height of its emulsion layer (mm) by the overall height of the liquid inside the column (mm).

Biosurfactant extraction

Biosurfactant production was performed by growing the culture aerobically in 1-L conical flask holding 200 ml of actinomycetes broth (HiMedia) for 72 h at 30 °C in a shaking incubator (120 rpm). Cell-free supernatant was extracted from culture broth through centrifugation (Eppendorf) at 4 °C for 20 min at 12,000×g. The extraction was carried out using the protocol of Aparna et al. (2012). The culture supernatant was acidified (pH 2) and precipitated using concentrated HCl and incubating it overnight at 4 °C. Then, the precipitate was extracted with an equivalent volume of chloroform: methanol (2:1) mix. Following separation, the organic phase was collected and using rotary evaporator the solvent was evaporated at 50 °C, leaving behind the viscous brown color product, which was reconstituted in methanol for further use.

Antimicrobial assay

Gram-negative reference bacterial strains Shigella flexneri (ATCC 12022), Escherichia coli (ATCC 25922), Salmonella typhimurium (ATCC 14028), and Gram-positive reference strain Staphylococcus aureus (ATCC 6538) were used in this study. Bacterial inoculum was prepared following the recommendation guidelines of Clinical Laboratory Standards Institute (Wayne 2012).

Antimicrobial assay of the extracted biosurfactant compound was performed following Kirby–Bauer disk diffusion method. Bacterial inocula were swabbed on Mueller–Hinton agar plates. Whatman no.1 paper disks of 6 mm diameter were autoclaved and placed on the agar plate. Then, 10 µl of 14 mg/ml biosurfactant extract was applied onto the surface of the paper disk and incubated at 37 ℃ for 24 h. The experiment was performed in triplicate and zone of inhibition was calculated.

Characterization of biosurfactant

Fourier-transform infrared spectroscopy (FTIR) analysis

FTIR spectra of the extracted biosurfactant were recorded on a Spectrum Two (Perkin Elmer) spectrometer equipped with LiTaO3 (lithium tantalite) MIR detector. 500 µl of the extracted biosurfactant compound was analyzed by measuring the FTIR spectrum in the wavenumber range of 4000–450 cm−1.

Mass spectrometric (LCMS) analysis

Methanolic extract of the compound was diluted to 1:10 methanol/water (v/v) and injected into LC/MS (Agilent 6530B Accurate Mass Q-TOF LC/MS system (Agilent Technologies, USA) consisting of a binary pump, thermostat autosampler, and column compartment). The separation was carried out on a 2.1 × 150 mm, C18 column, at 45 °C. Formic acid and acetonitrile were used as mobile phase A and mobile phase B. The flow rate was 300 µL per minute with 5–95% linear gradient. The overall time of analysis was 36.51 min. Electrospray ionization mode (ESI) of Mass spectrometry was used. The molecular mass for the biosurfactant molecule was determined by operating the LC/MS in full-scan mode from 100 to 2000 m/z ratio.

Results and discussion

Isolation and general features of strain LS14 genome sequence

Physiochemical parameters were measured for the sediment sample collected from Loktak Lake (Supplementary Table 2A). Among 50 bacterial isolates, strain LS14 was chosen for showing positive biosurfactant activity (Supplementary Fig. 1) and was considered for further biochemical characterization and 16 s rRNA sequencing to ascertain the phylogeny, which revealed its close relatedness to genus Brevibacterium (Supplementary Table 2B). Scanning electron microscopy (SEM) of strain LS14 on LB media showed bacterial cell morphology as rod-shaped, with a size of 1.36 µm length and 0.105 µm width (Supplementary Fig. 1). Genome sequencing of the strain LS14 using Illumina HiSeq 2500 sequencing platform generated a total of 32,049,507 paired-end reads with a length of 100 bp. The quality reads (> 30) from the raw data reads were filtered by excluding contaminants, such as adapters, the ambiguous “N” nucleotides, and low-quality sequences. The trimming of raw data reads, provided us a total of 24,653,050 filtered reads resulting in 2442.55 bases. These high-quality filtered reads were further used for analysis. ABySS assembler generated 60 contigs with an average coverage of 1281 X and a genome size of 3,809,532, with a G + C content of 68%. PGAAP analysis revealed 3421 genes (3368 CDS), and 53 RNAs in the genome while, RAST annotation and manual inspection revealed 3602 genomic features (RAST ID 6666666.429293), 3551 protein-coding genes and 51 RNAs in this strain. The general features of the strain LS14 have been summarized in Table 1, following the Minimal Information about any (X) sequence (MIxS) standard checklist (Chun et al. 2018).

Table 1.

General information of strain LS14, according to recommendations of Minimal Information about any (X) sequence (MIxS) standard checklist

Item Description
Classification Kingdom Bacteria
Phylum Actinobacteria
Class Actinomycetia
Order Brevibacteriales
Family Brevibacteriaceae
Genus Brevibacterium
Species Brevibacterium casei
Strain LS14
General features
 Shape Rod
 Gram staining Positive
 Motility Non motile
MIxS data investigation
 Submitted to insdc SJXG00000000.1 (GenBank)
 Investigation type Bacteria
 Project name Brevibacterium sp. LS14, whole-genome shotgun sequencing project
 Bioproject PRJNA523920
 Biosample SAMN10992559
 Geographic location India: Manipur, Imphal, Loktak Lake
 Collection date September-17
 Environment (biome) Fresh water
 Environment material Sediment
 Depth 0-5 m
 Relationship to oxygen Aerobic
 Isolation and growth condition Lysogeny Broth (LB)
 Sequencing method Illumina HiSeq
 Assembly ABySS v. 2.0.1
 Finishing strategy Draft, over 1281.0 × coverage, 60 contigs
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Biosurfactant activity

The biosurfactant production potential of strain LS14 was tested with three different assays. A positive drop collapse was observed for strain LS14 (Sari et al. 2014) in primary screening for BSs. Previous report of Morikawa et al. (2000), showed oil displacement assay to be relative to the biosurfactant produced by microorganisms. Oil displacement assay with cell-free supernatant of strain LS14 displaced oil layer completely to the circumference of the Petri dish compared to the control (Supplementary Fig. 1), indicating biosurfactant production. The emulsification test showed an emulsification index of 70% as compared to 80% in positive control (Triton X-100). Based on these results, strain LS14 was selected for further genomic analysis.

Antimicrobial activity

The antimicrobial activity of the extracted BS performed against several bacterial test strains showed positive antimicrobial activity against both Gram-positive and Gram-negative bacteria (Supplementary Table 3). The minimum zone of inhibition of 8.0 ± 1 mm against Staphylococcus aureus and highest zone inhibition of 9.3 ± 0.5 mm against Shigella flexenri (Supplementary Table 3) was observed. The antimicrobial activity of the strain LS14 describes its possible application in biomedical field.

Phylogenetic analysis, comparative genomics, and functional genome annotation

The near-complete 16S rRNA gene sequence of 1364 bp was obtained and used for phylogenetic analysis. Using this sequence, phylogenetic dendrogram was constructed which showed the strain LS14 relatedness with Brevibacterium casei NCDO 2048T (99.12%), followed by Brevibacterium ammoniilyticum A1T (98.01%), Brevibacterium celere KMM 3637T (97.71%), Brevibacterium siliguriense DSM 23676T (97.58%), Brevibacterium permense VKM Ac-2280T (97.5%) (Fig. 1a). MLST analysis with the concatenated dataset for seven housekeeping genes showed relatedness of strain LS14 with Brevibacterium casei CIP 102111T (Fig. 1b). Total 980 core genes were predicted from phylogenomic analysis among 6 strains of Brevibacterium based on core genome pool. Core genome was constituted of 335 Kb length and close phylogenetic relationship was predicted between strain LS14 and Brevibacterium casei CIP102111 genomes (Fig. 1c).

Fig. 1.

Fig. 1

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a Neighbor Joining tree based on 16S rRNA gene sequence showing the phylogenetic relationship of strain LS14 within genus Brevibacterium. Bootstrap values (expressed as percentage of 1000 replicates) > 50% are shown at branch nodes. The asterisks indicate conserved branches recovered when maximum- parsimony (Fitch 1971), maximum-likelihood (Felsenstein 1985) and minimum-evolution (Kimura 1980) methods were used to reconstruct phylogenetic trees. b Phylogenetic relationship of the isolate strain LS14 with its closely related Brevibacterium taxa, based on MLST approach. Evolutionary analyses were conducted in MEGA7. c Neighbor Joining phylogenomic tree derived from genome data of strain LS14 and other strains of Brevibacterium which are publicly available online. Evolutionary analyses were performed using iTOL

Genome annotation from RAST revealed genes related to biosurfactant production, such as glycosyltransferase, phosphomannomutase, 3-oxoacyl-ACP reductase (Supplementary Table 4), which are considered vital for glycolipid synthesis. Fifteen genes were interpreted to be LuxR family transcriptional regulator which played a significant part in the regulation of glycolipid synthesis. Genes known to code for cell envelope biogenesis protein OmpA, which is an active constituent of emulsifier (Walzer et al. 2006) was also identified. The sfp gene is reported to be accountable for the stimulation of seven peptidyl protein domains of surfactin (lipopeptide) synthase (Jadeja et al. 2019). It works by transferring the 4-phosphopantetheinyl moiety of coenzymeA to a serine residue. Hence, sfp gene is considered important for the production of lipopeptides like plipastatin and surfactin. Genome annotation and analysis revealed 648 bp of sfp gene in strain LS14 (Fig. 2, Supplementary Table 4), also their function as per the RAST annotation was revealed as Fatty Acid Biosynthesis FASII (EC 2.7.8.-). The sfp gene arrangement of the strain LS14 is shown (Fig. 2) with the closest match available for sfp gene in RAST subsystem namely Brevibacterium linens.

Fig. 2.

Fig. 2

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Gene organization of sfp gene in strain LS14 with respect to closest match Brevibacterium linens available for sfp gene in RAST subsystem: 1. 4ʹ-phosphopantetheinyl transferase (EC 2.7.8.-), 2. Putative membrane protein, 3. Hypothetical protein, 4. Transcriptional regulator of pyridoxine metabolism/pyridoxamine phosphate aminotransferase (EC 2.6.1.54), 5. Isocitrate dehydrogenase [NADP] (EC 1.1.1.42); monomeric isocitrate dehydrogenase [NADP] (EC 1.1.1.42), 6. Pyridoxal 5ʹ-phosphate synthase (glutamine hydrolyzing), synthase subunit (EC 4.3.3.6), 7. Thymidine kinase (EC 2.7.1.21), 8. Pyridoxal 5ʹ-phosphate synthase (glutamine hydrolyzing), glutaminase subunit (EC 4.3.3.6), 9. Hydrolase, alpha/beta fold family, 10. Uncharacterized protein YjgR, 11. Sodium-dependent anion transporter family, 12. Hypothetical protein, 13. NADH:flavin oxidoreductases, Old Yellow Enzyme family, 14. hypothetical protein

Functional annotation of RAST annotated genes was carried out using EggNOG-mapper and KEGG KAAS. EggNOG analysis divided LS14 protein-coding sequences into four groups of, Metabolism (38%), Information storage and processing (20%), poorly characterized (29%) and cellular process and signaling (13%) (Supplementary Fig. 2). Summary of genes functional classification using EggNOG-mapper is shown in the (Supplementary Table 5).

KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotation was considered useful, annotating biological gene functions via interpreting proteins and different enzymes involved in biochemical processes (Kanehisa and Goto 2000). Protein sequences used for metabolic pathway annotation through KEGG-KAAS Functional annotation using KAAS (ID:1550662996) server revealed the existence of a biosynthetic gene cluster. This gene cluster consists of NRPS family, specific to the microbial surfactant group (Doroghazi et al. 2014). Genes, such as 4-phosphopantetheinyl transferase (sfp) and non-ribosomal peptide synthetase (dhbF) (May et al. 2001) involved in biosurfactant biosynthesis and regulations with high industrial value (Płaza et al. 2015), were recognized (Supplementary Table 6). In this study, eleven genes assigned to NRPS structure, generally associated with lipopetide synthesis and two srfA and pps genes, responsible for antibiotic lipopeptides like surfactin and fengycin production were identified in genome of LS14. The peptide synthase needed for the amino acid moiety of surfactin is encoded by four ORFs in the srfA operon, namely srfAA, srfAB, srfAC, and srfAD, which were found to be present (Płaza et al. 2015). The sfp gene encoding phosphopantetheniyl transferase needed for surfactin synthetase activation via post-translational modification (Nakano et al. 1992) was also present (Supplementary Table 6).

DNA–DNA Hybridization (DDH) of the strain LS14 was performed with the whole genome of five closest type strains of genus Brevibacterium retrieved from the NCBI database (Table 2). The highest DDH of 85% was obtained with Brevibacterium casei CIP 102111T and further confirmation based on the genome comparison approach using CGview (Fig. 3) and JSpeciesWS (Supplementary Table 7) tool was employed which supported these findings. Circular map of genome representing various coding regions, rRNA, tRNA, and other genes (Fig. 3) showed genome resemblance of strain LS14 to Brevibacterium casei CIP 102111T. Hence, strain LS14 was designated as Brevibacterium casei strain LS14.

Table 2.

Comparison of strain LS14 with the available whole-genome of members of genus Brevibacterium

Bacterial strain DDH Distance Prob. DDH* ≥ 70% G + C difference
Brevibacterium casei CIP 10211T (FXZ00000000) 85.5 0.086 94.3 0.06
Brevibacterium celere CIP 108809T(QNSB00000000) 27.3 0.46 0.01 0.31
Brevibacterium epidermis NBRC 14811T(BCSJ00000000) 24.9 0.492 0.003333 3.64
Brevibacterium sanguinis 2b_TX (QNRZ00000000) 27.3 0.461 0.01 0.31
Brevibacterium siliguriense DSM 23676T(LT629766) 23.7 0.507 0.003333 3.8
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DDH* DNA–DNA Hybridization

Fig. 3.

Fig. 3

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The circular genome maps of Brevibacterium casei strain LS14 and compared with the genome of closest type species of genus Brevibacterium based on BLAST results of B. casei, B. celere, B. epidermis, B. sanguinis, B. siliguriense. The feature rings subjects (starting with the outermost ring) as following. Rings 1&12: forward and reverse strand CDSs in reading frames. Ring 2 &11: forward and reverse strand ORFs in reading frames. Ring 3–7 BLAST results of B. casei, B. celere, B. epidermis, B. sanguinis, B. siliguriense, respectively. Rings 8: represents the contigs number, Rings 9 it represents GC skew. Ring 10: GC content. The sfp gene accountable for surfactin synthetase domain activation was shown based on Prokka annotation

Comparative genome analysis and identification of overlapping orthologous gene clusters (Ortho Venn) enabled was instrumental in elucidating the genome structure, predicting functions and evolution of proteins across different species. The existence of orthologous clusters was established on comparison of amino acid sequence of B. casei strain LS14 with five closely related genomes as mentioned earlier. A collaborative map (Supplementary Fig. 3, Supplementary Table 8) summarized the number of unique clusters that exist in strain LS14 as compared to other 5 Brevibacterium species. A total of 2140 proteins were found to be common in all these Brevibacterium species and B. casei strain LS14 was found to hold seven unique orthologous Clusters.

On examination of specific sequences of seven unique orthologous gene clusters including 31 protein-coding sequences, detected in genome of B. casei strain LS14, reveals the similarity of one of the clusters with transposase for insertion sequence (IS) element, while there was no sequence similarity for other six clusters in the Swiss-Prot database (Supplementary Table 9).

Screening of genomic islands and prophage

No prophage was found in the genome of strain LS14 as revealed by PHASTER (PHAge Search Tool Enhanced Release). Genomic islands are generally associated with horizontal gene transfer (HGT) and are acquired in the process of evolution (Juhas et al. 2009). 36 genomic islands containing 447 genes with their location were predicted by Island viewer4 (Supplementary Fig. 4). A list of predicted genes in these genomic islands of Brevibacterium casei strain LS14 is given in (Supplementary Table 10). Although the strain LS14 genome contains 36 genomic islands, the regions harboring terpene containing glycolipid pathway and lipopeptide surfactin genes were not found in these genomic islands, suggesting the strain’s inherent ability to synthesize them (Waghmode et al. 2019). IS Elements are known genomic regions capable of repositioning within or across the chromosomes and can likewise interrupt CDS and gene regulation (Griffiths et al. 2000). Overall, 35 IS elements (ISsaga web tool) were found in the genome of strain B. casei strain LS14. However, no positive antibiotic resistance gene was found.

Secondary metabolite prediction and NRPS cluster analysis

Four gene zones were observed by AntiSMASH analysis for secondary metabolite gene prediction (Supplementary Table 11). One of the gene clusters was for biosynthesis of terpenes showing 57% gene similarity with known carotenoid cluster (Supplementary Fig. 5). Terpene-coding operon is located at position 1,410,757 to 1,431,668 bp of strain LS14 genome. Studying the homologous gene cluster of this operon on relative bacteria showed that this operon has the maximum similarity (85%) with its closest relative Brevibacterium casei. Moreover, ecotine gene zone showed 75% gene similarity with ecotine cluster, besides this, NRPS-like gene zone and siderophore gene zones were also predicted (Supplementary Table 11). NaPDoS proposed the predicted gene cluster belonged to the family FAS and NRPS. Besides, KAAS (KEGG Automatic Annotation Server) identified the entire set of genes involved in terpene synthesis. The entire Terpene gene cluster was further studied to find secondary metabolite genes comprising terpene-like molecule in the backbone as in the lipid synthesis pathway.

Characterization of biosurfactant

Characterization of extracted biosurfactant from strain LS14 using FTIR showed the existence of aliphatic C–H, O–H, and C–O functional groups which are the major structural functionality of surfactin and terpene. The biosurfactant molecular composition showed the promising peaks at 3351.12, 2840, 1644, 1233 cm−1 (Fig. 4a). The existence of an aliphatic hydrocarbon chain has been observed in previously reported biosurfactants derived from Brevibacterium sp. (Kiran et al. 2010). A broad band of the hydroxyl group (-OH) showing the presence of hydrogen bond was observed at 3351 cm−1. The absorption band at 2840 cm−1 verified C–H stretch of the alkyl hydrocarbon chain (CH2-CH3) group while the carbonyl stretching band at 1233 cm−1 showed the presence of ketone compound. Biosurfactant produced by the strain LS14 was additionally interpreted using mass spectrometry. The LC–MS analysis of the biosurfactant was executed in negative ion mode and the major ion peaks of molecular mass m/z 194.98, 1044.92, 1094.9, 994.9 were observed (Fig. 4b). The ions of m/z 194.98 were observed predominantly as the terpenes (Waghmode et al. 2019) and ions of m/z 1044.92, 1094.9 and 994.9 were observed showing its similarity with members of surfactin family (Ayed et al. 2014).

Fig. 4.

Fig. 4

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a An FTIR spectrum of biosurfactant from Brevibacterium casei strain LS14, b LC–MS spectrum of biosurfactant produced by Brevibacterium casei strain LS14

Conclusion

In the current study, a combined genomic and functional approach was used to describe the genome features and characterize the biosurfactant from strain LS14 isolated from a freshwater environment. Different integrative approaches, such as phylogenetic analysis of ribosomal RNA gene sequence (99%), GGDC, ANI, Tetra-nucleotide correlation index and seven MLST genes, and core genome phylogenomic analysis confirmed the designation of the strain as Brevibacterim casei LS14.

Genomic insights using KEGG revealed the presence of genes involved in glycolipid and lipopeptide surfactin synthesis. Secondary metabolite prediction with antiSMASH disclosed the existence of a terpene biosynthetic gene cluster. The genomic understanding of the biosurfactant biosynthetic pathway using KEGG-KAAS disclosed all the genes involved in the terpenoid biosynthesis pathway, which was the anticipated backbone molecule for biosurfactant production. Additionally, FTIR analysis exhibits functional groups with carbohydrate and lipid molecules and a lack of protein fraction concerning previous studies (Abdel-Mawgoud et al. 2011; Ebrahimipour et al. 2014). LC/MS analysis also revealed the prevalence of molecular mass peaks corresponding to the members of lipid and polysaccharides (Wang et al. 2014).

In conclusion, based on genomic and functional analyses, Brevibacterium casei strain LS14 can be represented for terpene and surfactin biosurfactant production which could have noteworthy industrial applications.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 689 KB) (689KB, doc)
Supplementary file2 (DOC 2746 KB) (2.7MB, doc)

Acknowledgements

This research work was funded by the Department of Biotechnology (DBT), Govt. of India.

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