Abstract
Introduction:
Endophytes are crucial partners that contribute to the plants’ health and overall wellbeing. Apart from the elucidation of the relationship between plants and their microbiota, the metabolic potential of endophytes is also of a special interest. Therefore, it is crucial to isolate and taxonomically identify endophytes, as well as to investigate their genomic potential to determine their significance in plant health and potential as bioactive metabolite producers for industrial application.
Methods:
In this study, we isolated ten endophytic bacterial strains from different tissues of medicinal plant Galium aparine L. and performed de novo assembly of their genomes using short and long reads. Comparative genomic analysis was conducted to assess the accurate taxonomic identification of the strains. The investigation also focused on the presence of mobile genetic elements and their significance concerning endophytic lifestyles. We performed functional annotation of coding sequences, particularly targeted genes that encode carbohydrate enzymes and secondary metabolites within gene clusters.
Results:
Through sequencing using two complementary methods, we obtained 10 bacterial genomes, ranging in size, coding density and number of mobile genetic elements. Our findings provide a first insight into the cultivable bacterial community of the medicinal plant Galium aparine L., their genome biology, and potential for producing valuable bioactive metabolites. Obtained whole genome sequences allowed for complete phylogenetic analysis, which revealed crucial insights into the taxonomic status of bacteria and resulted in the discovery of two putatively novel bacterial species from the Bacillus and Priestia genera, suggesting that plants are hiding a reservoir of novel species with potentially useful properties and unknown mechanisms related to their relationship with plant host.
Introduction
Plants have developed complex and diverse relationships with microorganisms in their neighborhood as they co-exist in the same ecological niche, constantly subjected to selection pressures. Endophytic microorganisms are an exceptional group of plant-associated microorganisms, as they thrive inside their tissues without causing any detrimental effect or disease to the host (). The relationship between plants and their endophytes is mutually beneficial. The plant provides a safe niche less disturbed by fluctuating conditions (e.g., temperature amplitude) and a constant supply of nutrients, while the endophytes provide positive effects on plant health and fitness, therefore ensuring their own survival (). Among the beneficial traits exhibited by endophytes, the most common ones are nitrogen fixation and phosphorus solubilization, which enhance the uptake of these crucial nutrients by a plant. Additionally, endophytes produce various bioactive substances such as plant hormones (indole-3-acetic acid, gibberellins, abscisic acid, etc.) siderophores, antibiotics, and insecticides (; ; ). Medicinal plants are particularly intriguing for the identification of their endophytes, especially bacteria, due to the abundant production of various chemicals with therapeutic qualities. However, the investigation of these bacterial endophytes has been limited (Sharma et al., 2023). Existing evidence proves that endophytes are capable of producing ex planta bioactive compounds that are identical or very similar to those of their host plants; therefore, this concept may 1 day be applied as technology of their large-scale production (; ).
A broad group of endophytes, classified as “facultative,” enters the plant via root or stem cracks, previously being rhizospheric or epiphytic microorganisms, respectively. Another type, known as “obligate,” maintains an intrinsic bond with its host throughout its entire life cycle and typically transmits itself vertically through seeds (). Seed microbiota is transmitted by plants across generations, being the starting point for community assembly in the new seedling (Semenzato et al., 2022a; Truyens et al., 2015). Obligate endophytes are recalcitrant or even impossible to grow outside plants in laboratory conditions; thus, cultivable endophytes are considered to be mostly facultative (; ). Members of the Bacillaceae family, especially Bacillus species, are among the most commonly encountered cultivable endophytic bacteria. Their plant growth-promoting activities and versatility for industrial use have led to extensive research in recent decades (; ; , ; ; Zhou et al., 2021).
Apart from ex planta studies of isolated endophytes, modern omics approaches conjoining different aspects of single endophyte interaction with the host plant and other inhabitants are crucial to deciphering not only their role in host plant ecology, but also the impact of it on endophytes’ functioning. As the plant itself represents a peculiar niche that requires specific adaptations from its inhabitants, endophytes influence the plant environment and contribute to its secondary metabolism as well. broadly discussed methodologies essential for resolving some of the issues, including genomics, transcriptomics, and proteomics. Comparative genomics provides insights into mechanisms steering the endophytic lifestyle, such as colonization patterns, plant growth promotion, induced resistance, interactions with other associated microorganisms, as well as the secondary metabolism of an endophyte (; ). The conventional approach to screening for novel compounds relies on biological assays based on their putative activity; however, this approach is time- and cost-consuming and often results in rediscovery of known compounds (). Therefore, in the last years, there has been a shift toward a genome mining approach, which takes advantage of recent advancements in DNA sequencing technologies and bioinformatics. This reveals the hidden potential of cultivable endophytes to produce specific compounds (enzymes, non-ribosomal peptides, polyketides), which are often not expressed under standard laboratory conditions. This knowledge could guide future cultivation methods and approaches to activate genes responsible for their synthesis (). All of those endophytic bioactive compounds can be successfully used in pharmaceutical and other industrial applications, as detergents (), biofuels (Zhang et al., 2014), biopesticides () or pigments (), as well as in agriculture and crop production (; ).
To our knowledge, this is the first report on endophytic bacteria isolated from Galium aparine L., a medicinal herb widely growing in Europe, North America and Asia; known for its beneficial effects on kidneys, skin disorders, wounds, high blood pressure, and insomnia (; ). While there is no prior published record on endophytes, both bacterial and fungal, a research by reported the presence of rhizospheric fungi belonging to the genera Aspergillus, Mucor, Penicillium, and Rhizophus (). All plants developed close associations with surrounding microorganisms, as their support is crucial for plants as sessile organisms to adapt effectively to changing environmental conditions. However, many plant have yet to be studied in terms of their microbiome (). The study aimed to (1) isolate cultivable endophytic bacteria from the tissues of Galium aparine L., (2) obtain their genomic sequences and identify them taxonomically, (3) study the presence of mobile genetic elements as drivers of evolution and (4) mine their genomes for encoded bioactive compounds with beneficial uses in agriculture and other industries.
Results and discussion
Isolation of endophytic bacteria
From the surface-sterilized fragments of leaves, stems and roots of Galium aparine L., a total of 10 bacterial isolates were isolated and purified by subsequent streak plating. The effectiveness of the surface sterilization method was confirmed by the lack of microbial growth on the control plates containing water from the plant’s last rinsing after 7 days of incubation. Obtained strains were named as G followed by R, S, or L for roots, stem and leaves, respectively.
Genome sequencing and assembly
Whole genome sequencing (WGS) was performed, followed by de novo hybrid assembly and annotation (Table 1). The assembly size of 10 isolated strains ranges from 4.17 (GS2) to 6.10 Mbp (GL1). The average genome-wide GC content varies between 34.9% and 40.5%. The number of assembled contigs varied from sample to sample, but of all the datasets, only the GR2 genome is assembled to the complete chromosome level. The strains differ in the number of genes. The obtained results ensure good quality assembly without contamination.
TABLE 1
| Feature | Strain name | |||||||||
| GR1 | GR2 | GR3 | GR4 | GS1 | GS2 | GS3 | GL1 | GL2 | GL3 | |
| Size (Mbp) | 5.66 | 5.63 | 5.97 | 5.69 | 5.94 | 4.17 | 5.70 | 6.10 | 5.70 | 5.99 |
| GC content (%) | 35.23 | 40.48 | 34.87 | 37.70 | 34.86 | 37.69 | 35.05 | 35.03 | 35.12 | 35.11 |
| Contigs | 18 | 1 | 10 | 45 | 58 | 9 | 26 | 19 | 21 | 8 |
| N50 (Mbp) | 4.99 | 5.63 | 3.13 | 0.91 | 0.61 | 3.77 | 2.92 | 2.13 | 3.78 | 5.29 |
| L50 | 1 | 1 | 1 | 3 | 4 | 1 | 1 | 2 | 1 | 1 |
| Genes (all) | 5,840 | 5,392 | 6,085 | 5,937 | 6,061 | 4,285 | 5,803 | 6,307 | 5,808 | 6,132 |
| CDSs* | 5,716 | 5,261 | 5,941 | 5,842 | 5,986 | 4,157 | 5,676 | 6,173 | 5,659 | 5,982 |
| rRNAs* | 19 | 42 | 34 | 11 | 10 | 27 | 28 | 27 | 38 | 39 |
| tRNAs* | 100 | 83 | 105 | 76 | 60 | 96 | 94 | 102 | 106 | 106 |
| ncRNAs* | 5 | 6 | 5 | 8 | 5 | 5 | 5 | 5 | 5 | 5 |
| Completeness (%) | 99.41 | 99.35 | 99.11 | 99.27 | 99.27 | 99.35 | 99.22 | 98.24 | 99.22 | 98.82 |
| Contamination (%) | 0.00 | 0.32 | 0.06 | 0.65 | 0.97 | 0.00 | 0.43 | 0.10 | 0.43 | 0.25 |
| Complete BUSCOs (%) | 99.8 | 99.8 | 99.5 | 100.0 | 99.8 | 99.6 | 99.8 | 99.3 | 99.8 | 99.8 |
Genome assembly statistics and annotation features of endophytic bacteria from Galium aparine L.
*CDS, coding sequence; ncRNA, non-coding RNA; rRNA, ribosomal RNA, tRNA, transfer RNA.
The genome sequences are deposited in the National Center for Biotechnology Information (NCBI, United States) database under the BioProject number PRJNA1068863.
Taxonomic identification
The initial attempt at identification was conducted by manually extracting 16S rDNA and gyrA sequences from annotated genomes, followed by their comparison against the NCBI database using BLASTN (data not shown). However, for most of the strains, this approach was highly inconclusive as the percentage of identity in gene sequences was the same for several species, a common occurrence within the Bacillus genus (). What is more, many members of Bacillus cereus group members are identified solely based on their 16S rDNA sequences, leading to further misidentifications in the NCBI database. As a consequence, taxonomic identification of isolated strains was based on whole genome sequence analysis using Type (Strain) Genome Server (TYGS), which calculates digital DNA:DNA hybridization (dDDH) parameter values for in silico species delineation, considering only verified type strains from the List of Prokaryotic names with Standing in Nomenclature (LPSN) (; Tindall et al., 2010). So-called “reference” or “representative” strains are not reliable and their use in identification may lead to further taxonomic misidentification (). Also, the Average Nucleotide Identity (ANI) values, the second parameter for species delineation, were calculated. The proposed identification of the isolates with ANI and dDDH is presented in Table 2.
TABLE 2
| Strain | Proposed identification (NCBI GenBank Assembly Accession no.) | Closest type-strain match (NCBI GenBank Assembly Accession no.) | ANI (%)* | dDDH (%)* |
| GR1 | Bacillus pretiosus GR1 (GCA_036408975.1) | Bacillus pretiosus SAIUCEU11T(GCA_025916425.1) | 97.14 | 78.20 |
| GR2 | Peribacillus frigoritolerans GR2 (GCA_036352075.1) | Peribacillus frigoritolerans DSM 8801 (GCA_024169475.1) | 97.24 | 80.30 |
| GR3 | Bacillus cereus GR3 (GCA_036408805.1) | Bacillus cereus ATCC 14579 (GCA_006094295.1) | 97.16 | 74.10 |
| GR4 | Priestia megaterium GR4 (GCA_036350305.1) | Priestia megaterium ATCC 14581 (GCA_017086525.1) | 96.91 | 72.80 |
| GS1 | Bacillus thuringiensis GS1 (GCA_036350635.1) | Bacillus thuringiensis ATCC 10792 (GCA_000161615.1) | 96.52 | 69.10 |
| GS2 | Priestia sp. GS2 (GCA_036409025.1) | Priestia flexa NBRC 15715 (GCA_001591565.1) | 92.40 | 47.40 |
| GS3 | Bacillus cereus GS3 (GCA_036408815.1) | Bacillus cereus ATCC 14579 (GCA_006094295.1) | 98.30 | 83.40 |
| GL1 | Bacillus sp. GL1 (GCA_039680825.1) | Bacillus wiedmannii FSL W8-0169 (GCA_001583695.1) | 95.06 | 59.80 |
| GL2 | Bacillus cereus GL2 (GCA_036408835.1) | Bacillus cereus ATCC 14579 (GCA_006094295.1) | 98.30 | 83.50 |
| GL3 | Bacillus wiedmannii GL3 (GCA_036350675.1) | Bacillus wiedmannii FSL W8-0169 (GCA_001583695.1) | 96.63 | 70.00 |
Whole genome sequencing (WGS)-based identification of isolated strains.
*ANI, Average Nucleotide Identity; dDDH, digital DNA-DNA hybridization.
The majority of the isolates surpassed thresholds recognized as the cut-offs for species delineation, ≥ 95%–96% for ANI and ≥ 70% for dDDH (; ). As stated in Table 2, most of the isolated species belong to the Bacillus genus or are closely related. Strains can be divided into three groups (Figure 1): (1) Priestia spp. – Priestia sp. GS2, Priestia megaterium GR4, (2) Peribacillus frigoritolerans GR2 and (3) Bacillus cereus group – Bacillus thuringiensis GS1, Bacillus cereus GS3, GL2, and GR3, Bacillus wiedmannii GL3, Bacillus pretiosus GR1, and Bacillus sp. GL1.
FIGURE 1
Among the strains isolated from Galium aparine L., two strains, GS2 and GL1, showed the possibility of being novel strains, as ANI and dDDH values are too low to classify them into known species (Table 2). Their taxonomic identification was determined to be Priestia sp. and Bacillus sp., respectively. Surprisingly, based on manual comparisons of the two strains, Priestia sp. GS2 displayed high similarity to Bacillus sp. 1708r2a1 (NCBI GenBank assembly no. GCA_024134725.1), which was isolated from the clean room of NASA Center with ANI and dDDH values reaching 99.48% and 95.70%, respectively. In contrast, these parameters are below threshold established for the closest type strain Priestia flexa NBRC 15715 (NCBI GenBank assembly no. GCA_001591565.1).
Firmicutes, with Bacillus as the most representative genus, is one of the most prevalent phyla among culturable endophytic bacteria. Bacillus spp. endophytes are known for their plant growth potential and often demonstrate antibacterial and antifungal activities (
Although the Bacillus subtilis and Bacillus cereus clades are not phylogenetically related, the Bacillus genus is restricted only to members of these two clades. The subtilis clade is actually Bacillus sensu stricto, as it contains the type strain Bacillus subtilis. On the other hand, however, the cereus clade cannot be named a separate genus as it contains multiple human pathogens according to Rule 56a of the International Code of Nomenclature of Prokaryotes (
To validate the taxonomic identification of Bacillus cereus group members, the BTyper3 tool was used (
FIGURE 2

Average Nucleotide Identity (ANI) and digital DNA:DNA hybridization (dDDH) values between isolated bacterial endophytes’ genomes. ANI (%; ANIm results) values are indicated in the upper triangle and dDDH (%; formula d4 results) in the lower triangle.
Researchers have investigated few medicinal plants for the presence of beneficial endophytes, most of which contain Bacillus-related species with multiple plant growth-promoting activities. For instance, 65% of bacteria isolated from licorice (Glycyrrhiza uralensis F.) were found to belong to the Bacillus spp. based on 16S rDNA sequences, and most of them were able to produce indole-3-acetic acid (IAA) and siderophores, fix nitrogen, and solubilize phosphate (
Also, Bacillus-related bacterial species are often identified as the main endophytic species enhancing plant stress tolerance in extremophilic conditions, which emphasizes the importance of the plant microbiome for its survival and fitness.
Numerous novel Bacillus-related strains are of endophytic origin, including for example Bacillus endophyticus (2002), Bacillus graminis (2011), Bacillus endoradicis (2012), Bacillus lycopersici (2015), Bacillus cabrialesi (2019), Bacillus taxi (2020), Bacillus mexicanus (2023), Bacillus dicomae (2023) (
Functional annotation
Genes associated with plant growth promotion
A substantial amount of genes is significant to the formation and maintenance of an endophytic lifestyle, as well as indirectly for plant growth promotion, adaptation and protection (Figure 3).
FIGURE 3

Presence of genes associated with plant growth promotion according to SEED functions from The Rapid Annotation using Subsystem Technology (RAST).
Endophytic bacteria enhance the metabolism of essential nutrients in their plant hosts, such as phosphorus, nitrogen, and sulfur, mostly by increasing the bioavailability of these elements, which later serve for amino acids and protein synthesis (
A pivotal plant growth-promoting trait of many bacterial endophytes is their ability to synthesize indole-3-acetic acid (IAA), primarily by tryptophan-dependent pathway (Tang et al., 2023). As a member of the auxin family of indole derivatives, IAA regulates almost every aspect of plant development, including cell division, roots and stem elongation, as well as responses to environmental cues (
While a single endophytic species alone is not able to drastically improve plant fitness and life conditions, a whole group of them can significantly contribute. Notably, certain species demonstrate “specialization” in specific plant growth-promoting traits, as exemplified by Peribacillus frigoritolerans GR2, which possesses almost two times more enzymes connected to degradation (especially n-phenylalkanoic acids) than Bacillus wiedmannii GL3 with its heightened amount of reductatases for organic sulfur mineralization and assimilation. Given their well-studied plant growth-enhancing properties, Bacillus spp. stand out as exemplars for future research on the cruciality of endophytes for plant metabolism and the development of sustainable agriculture agents.
Mobile genetic elements (MGEs)
As major drivers of horizontal gene transfer (HGT), bacterial mobile genetic elements (MGEs), also known as the “bacterial mobilome,” can move within the genome or transfer between bacterial species, ensuring their better adaptation to the occupied ecological niche. That broad term is represented not only by plasmids and phages but also by transposable elements, insertion, restriction and modification systems, integrative and conjugative elements (ICEs) among others (
Five different categories of MGEs provided by mobileOG-db database include integration and excision (IE; recombinases, transposases, etc.) replication, recombination or nucleic acid repair (RRR; repair and recombination systems, plasmid and phage replication initiators, etc.), phage-related biological processes (P; lysis and lysogeny-associated machinery, etc.) stability, transfer, or defense (STD; CRISPR proteins, etc.) and inter-organism transfer (T; conjugation machinery, etc.); each one corresponding to another key molecular machinery (
TABLE 3
| MGEs category | GR1 | GR2 | GR3 | GR4 | GS1 | GS2 | GS3 | GL1 | GL2 | GL3 |
| Integration/excision (IE)* | 51 | 40 | 70 | 24 | 68 | 14 | 61 | 73 | 61 | 86 |
| Replication/recombination/repair (RRR)* | 52 | 44 | 47 | 57 | 50 | 42 | 46 | 52 | 46 | 50 |
| Phage (P)* | 44 | 16 | 32 | 23 | 48 | 18 | 39 | 33 | 38 | 29 |
| Stability/transfer/defense (STD)* | 9 | 4 | 7 | 6 | 6 | 6 | 13 | 6 | 12 | 9 |
| Transfer (T)* | 27 | 16 | 35 | 29 | 30 | 14 | 28 | 34 | 28 | 32 |
| All | 183 | 120 | 191 | 139 | 202 | 94 | 187 | 198 | 185 | 206 |
Mobile genetic elements (MGEs) assigned to major mobileOG categories.
*IE, integration/excision; RRR, replication/recombination/repair; P, phage; STD, stability/transfer/defense; T, transfer.
These data suggest that the bacteria in question are not an exception in nature, as the movement of genetic material acts as a driving force in their adaptation and fitness by facilitating gene loss or gain, in further perspective contributing to evolution. The study of HGT in the context of endophytes and plants has been limited. However, accurate detection of its presence is essential for understanding the complex relationship between them and their mutual influences. This knowledge can directly help to enhance the application of bacteria in sustainable agriculture (
In an evolutionary context, a prime example of MGEs is bacteria’s acquisition of antibiotic resistance. The rise of antibiotic resistance is one of the most pressing problems in the modern world. According to the World Health Organization (WHO), 700,000 people die each year as a result of this phenomenon and that number is projected to increase to 10,000,000 by 2050 if no effective solutions are developed (
The resistomes of isolated strains were analyzed to obtain information related to antibiotic resistance genes, which resulted in identification of five antimicrobial resistance (AMR) gene families, each displaying four resistance mechanisms (Table 4).
TABLE 4
| AMR* gene family | ARO* term | Drug class | Antibiotic resistance mechanism | Number of hits | |||||||||
| GR1 | GR2 | GR3 | GR4 | GS1 | GS2 | GS3 | GL1 | GL2 | GL3 | ||||
| Glycopeptide resistance gene cluster | vanR/vanT/vanW/vanY | Glycopeptide antibiotic | Target alteration | 8 | 3 | 11 | 6 | 10 | 4 | 9 | 8 | 9 | 9 |
| Bacillus cereus Bc beta-lactamase | BcI/BcII/BcIII | Cephalosporin, penem | Inactivation | 4 | 1 | 4 | 1 | 4 | 1 | 2 | 5 | 2 | 5 |
| Fosfomycin thiol transferase | FosB | Phosphonic acid antibiotic | Inactivation | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 | 1 |
| SMR* antibiotic efflux pump | qacJ/qacG | Disinfecting agents and antiseptics | Efflux | 1 | 2 | 1 | 3 | 1 | 1 | 1 | 1 | 1 | 1 |
| Tetracycline-resistant ribosomal protection protein | tetB | Tetracycline antibiotics | Target protection | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |
| All | 15 | 7 | 18 | 12 | 18 | 7 | 14 | 17 | 14 | 18 | |||
Antimicrobial resistance (AMR) gene families predicted in Galium aparine L’s bacterial endophytes.
*ARO, antibiotic resistance ontology; AMR, antimicrobial resistance; SMR, small multidrug resistance.
Strains belonging to Bacillus spp. species (GR1, GR3, GS1, GS3, GL1, GL2, GL3) exhibit a comparable number and distribution of AMR genes, suggesting similar resistance to antibiotics among them. Conversely, strains from Priestia (GS2, GR4) and Peribacillus (GR2) genera have significantly lower numbers of AMR genes. The major family in all bacterial genomes encodes the glycopeptide antibiotic resistance proteins (vanW, vanY, vanR and vanT genotypes), which function through the antibiotic inactivation resistance mechanism. Glycopeptide antibiotics, such as vancomycin and teicoplanin, are commonly used to treat life-threatening community-acquired infections caused by methicillin-resistant Staphylococcus aureus (MRSA) (
One of the other key factors shaping the ecological balance and evolution of bacteria are phages, the most abundant biological entities on Earth. As predators, they kill bacterial hosts by lysis, causing selective pressure for bacteria resistant to phage infection, which further results in the emergence of different adaptation systems, such as the CRISPR-Cas immune system, leading to co-evolution of phages and bacteria (
TABLE 5
| Strain | Identified phage (GenBank Accession no.) | Region length (kbp) | Start | End | No. of total proteins | GC (%) |
| Bacillus pretiosus GR1 | Bacillus phage phIS3501 (NC_019502) | 58.5 | 3,173,596 | 3,232,186 | 68 | 36.78 |
| Bacillus phage IEBH (NC_011167) | 50.8 | 779 | 51,609 | 90 | 36.40 | |
| Bacillus cereus GR3 | Bacillus phage phi4J1 (NC_029008) | 29.5 | 2,859,647 | 2,889,205 | 42 | 36.47 |
| Brevibacillus phage Jenst (NC_028805) | 65.0 | 565730 | 630,753 | 59 | 33.45 | |
| Priestia megaterium GR4 | Bacillus phage PM1 (NC_020833) | 71.5 | 786,539 | 858,040 | 88 | 37.05 |
| Bacillus thuringiensis GS1 | Geobacillus phage GBSV1 (NC_008376) | 58.3 | 671,230 | 725,088 | 50 | 34.83 |
| Bacillus phage phIS3501 (NC_019502) | 41.0 | 1 | 41,007 | 61 | 35.17 | |
| Bacillus cereus GS3 | Bacillus phage Vb_BhaS_171 (NC_03090) | 19.9 | 4,150 | 24,136 | 32 | 35.86 |
Phages identified in endophytic genomes.
As a result, the strains Bacillus pretiosus GR1, Bacillus cereus GR3 and Bacillus thuringiensis GS1 were found to harbor two copies of complete phage regions across their genomes, while Priestia megaterium GR4 and Bacillus cereus GS3 each contained one. Bacillus spp. are highly ubiquitous in many ecological niches, making them ideal subjects for studying host-phage interactions (
Lastly, we searched for putative plasmid sequences within our genomic data, as plasmids represent the largest and most commonly encountered examples of MGEs. First, we used PlasmidSPAdes to find plasmid sequences from short-reads (
TABLE 6
| Strain | Contig no. | Length (kbp) | GC (%) | CDSs* | MGEs* | ARGs* | CRISPR/Cas* | PLSDB (NCBI accession no.) | ||
| Best match | Cover (%) | Identity (%) | ||||||||
| Bacillus pretiosus GR1 | 2 | 383.181 | 32.59 | 365 | 43 | 1 | 0 | Bacillus wiedmannii bv. thuringiensis strain FCC41 plasmid pFCC41-1-490K (CP024685.1) | 62 | 99.48 |
| 5 | 54.381 | 36.3 | 94 | 15 | 0 | 0 | – | – | – | |
| Bacillus cereus GR3 | 3 | 637.249 | 32.03 | 579 | 71 | 2 | 0 | Bacillus thuringiensis strain B13 plasmid pBt13367-1 (NZ_CP074713.1) | 41 | 98.93 |
| Priestia megaterium GR4 | 22 | 7.738 | 35.38 | 8 | 3 | 0 | 0 | Priestia megaterium QM B1551 plasmid pBM200 (NC_010009.2) | 79 | 92.51 |
| Bacillus sp. GL1 | 4 | 213.927 | 32.83 | 188 | 26 | 1 | 1 | Bacillus tropicus strain EMB20 plasmid pBEMB20-2 (NZ_CP078083.1) | 47 | 96.56 |
| 6 | 72.347 | 31.66 | 96 | 11 | 0 | 0 | Bacillus mycoides strain BPN43/2 plasmid p75 (NZ_CP036011.1) | 74 | 90.88 | |
| 9 | 3.965 | 34.91 | 4 | 1 | 0 | 0 | Bacillus mycoides plasmid pBMY1 (NC_005703.1) | 55 | 86.41 | |
| Bacillus wiedmannii GL3 | 2 | 464.727 | 32.40 | 409 | 41 | 2 | 0 | Bacillus wiedmannii strain EPS29 plasmid ppl557 (NZ_CP133558.1) | 70 | 99.49 |
| 3 | 226.263 | 32.72 | 231 | 30 | 0 | 0 | Bacillus thuringiensis HD-771 plasmid p02 (NC_018501.1) | 44 | 89.89 | |
| 4 | 6.402 | 30.55 | 7 | 2 | 0 | 0 | – | – | – | |
Putative plasmid sequences in Galium aparine L’s bacterial endophytes.
*CDSs, coding sequences; MGEs, mobile genetic elements; ARGs, antibiotic resistance genes; CRISPR/Cas, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas).
Half of the isolated strains contain putative plasmid sequences, some even more than one. Except for two hypothetical plasmids (Bacillus pretiosus GR1, contig 5; Bacillus wiedmannii GL3, contig 4), all of them were matched to plasmids present in the PLSDB database; additionally, all even to those from taxonomically matching strains’ genera. Putative plasmid sequences have lower GC content than whole genomes (Table 1), and some of them are especially large (up to 10% of the whole genome as with Bacillus cereus GR3), which makes them so-called megaplasmids. Thresholds for minimum megaplasmid size vary as the overall genome size should be considered: however, ≥ 350 kbp proposed by
None of the identified plasmids were similar to those encoding toxins characteristic of Bacillus anthracis or thuringiensis from Bacillus cereus group, which further confirms that they are not members of those genera. However, there is a high possibility that strain GS1 is a member of Bacillus thuringiensis, but has lost its characteristic plasmid, making it difficult to differentiate from Bacillus cereus. Conversely, strain GR3 classified as Bacillus cereus member based on ANI and dDDH parameters surpassing thresholds in comparison to the type strain, does possess Bacillus thuringiensis plasmid, although it lacks cry gene encoding insecticidal crystal protein. In addition, the best match according to the PLSDB database is Bacillus thuringiensis strain B13 plasmid pBt13367-1, which also does not possess that gene. Interestingly, cry gene was found in the chromosome sequence within a genomic island, the same as in Bacillus thuringiensis HER1410 genome (
Carbohydrate-active enzymes (CAZymes)
Carbohydrate-active enzymes are families of enzymes intricately associated with the synthesis, degradation and modification of carbohydrates, divided into five classes based on their function within the CAZy database1. These classes comprise glycoside hydrolases (GHs), carbohydrate esterases (CEs), glycosyl transferases (GTs), polysaccharide lyases (PLs), and now also non-catalytic carbohydrate-binding modules (CBMs) and auxiliary activity enzymes (AAs) acting in collaboration with other CAZymes to enhance their activity (
As a result of CAZymes identification analysis, between 106 (Peribacillus frigoritolerans GR2) and 148 (Priestia megaterium GR4) genes were mapped to the CAZymes family. Figure 4 illustrates the distribution of predicted CAZymes’ families across the genomes. The number behind the bar indicates the total number of CAZymes, while the number in brackets represents the percentage of CAZymes to the total number of genes predicted by RAST.
FIGURE 4

Comparison of the distribution of carbohydrate-active enzyme (CAZyme) classes identified in Galium aparine L.’s bacterial endophytes. AA, auxiliary activity; CBM, carbohydrate-binding module; CE, carbohydrate esterase; GH, glycoside hydrolase; GT, glycosyltransferase; PL, polysaccharide lyase.
The proportions of CAZymes families differ slightly depending on the species represented. It was the glycosyl transferases (GTs) that were most common in Bacillus spp. strains, followed by glycoside hydrolases (GHs) and then by carbohydrate esterases (CEs) and carbohydrate-binding modules (CBMs). In comparison, in strains belonging to Priestia spp. and Peribacillus spp., the amount of GTs and GHs is similar and CBMs are more abundant than in Bacillus spp. CEs and AAs levels are similar in all strains. Comprehensive analysis showed the highest abundance of CBM50 (LysM domains binding to the N-acetylglucosamine residues in bacterial peptidoglycan and chitin), CE4 (esterases catalyzing the de-acylation of polysaccharides), GH13 (hydrolases acting on substrates with α-glucoside linkages), GT2 and GT4 (catalyzing glycoside synthesis) families (
We have used the number, type, and proportions of CAZymes an organism carries as a marker to assess its adaptation to a specific environment and gain insights into its lifestyle. Polysaccharides consist of diverse glycosyl units, often branched. Microorganisms can use these polysaccharides as sources of carbon and energy, acting as an adaptation mechanism to deal with temporary periods of starvation. The glucose units have to be released by specific enzymes – the key ones belonging to GHs (Wang et al., 2023). GHs and GTs are the most abundant across the genomes of many plant growth-promoting bacteria (PGPB) (Wang et al., 2023). GTs synthesize extracellular polysaccharides, which are crucial also for biofilm formation, resistance to environmental pressures, and other significant activities for endophytic bacteria (Wang et al., 2023). In Bacillus spp. strains there is no significant difference in the number and distribution of CAZymes between soil-, leaf- and other-associated PGPB, which is contrary to other common PGPB species (e.g., Pseudomonas, Burkholderia); thus, makes Bacillus spp. remarkably stable genus (Wang et al., 2023). Also, endophytic isolates from Galium aparine L. displayed a proportion of CAZymes to all predicted gene sequences ranging from 1.77% in Peribacillus frigoritolerans GR2 to 2.87% in Priestia sp. GS2 (Figure 4). Free-living organisms typically exhibit a CAZyme repertoire ranging from 1% to 5% of all predicted sequences. A significant reduction suggests a strict intracellular parasitic lifestyle (
Bacterial CAZymes are successfully applied for multiple biotechnological (e.g., food processing, detergent additives), medical (e.g., synthesis of pharmaceutical intermediates) and industrial (e.g., xenobiotics degradation, dye production) purposes as they are often more sustainable, cheaper and time efficient solution. Genome mining for CAZymes is a very useful tool for picking the right bacteria and planning more experiments to break down tough substrates like cellulose, starch, lignin, and others. Because those substrates possess unique complex structures, enzymes have to work in conjunction for that purpose. For instance, for effective and complete degradation of chitin, the polymer of (1→4)-β-linked N-acetyl-D-glucosamine (GlcNAc), and chitosan, its deacetylated form, not only chitinases and chitosanases are needed, but also deacetylases, aminidases and lytic monooxygenases (
The CAZyme repertoires from Galium aparine L. endophytes were manually screened for the presence of specific enzymes associated with the degradation of selected polysaccharides (Figure 5).
FIGURE 5

Genes associated with polysaccharide degradation.
All isolated strains display genomic potential for the degradation of polysaccharides, especially chitin, chitosan, cellulose and starch. Strains belonging to Bacillus spp. demonstrate a higher number of genes encoding enzymes associated with chitin and chitosan degradation, while strains from Priestia spp. those associated with starch hydrolysis, e.g., six copies of an α-amylase gene in Priestia megaterium GR4. Only a few genes associated with xylan, pectin and lignin degradation were found across the genomes of all isolates. However, the enzymes presented in Table 4 are only known enzymes with assigned EC number, other enzymes involved in the degradation process may be “hidden” on the family level.
Biosynthetic gene clusters (BGCs)
Bacteria are capable of synthesizing diverse biologically active compounds during their secondary metabolism. Most of the secondary metabolites serve as traits bringing fitness advantages to the occupied ecological niche and microbial community, including cell-cell signaling or nutrient scavenging. However, their production also brings costs to the individual cell as it uses resources from primary metabolism (Santamaria et al., 2022). Apart from their ecological role, secondary metabolites have significant potential as therapeutics and agricultural agents. Traditional approaches for screening for their production by bacteria involved bioactivity-based assays of their culture supernatants, their extraction and fractionation with solvents and attempts at characterization by such techniques as mass spectroscopy (MS) and nuclear magnetic resonance spectroscopy (NMR). These processes are both expensive and labor-intensive and often lead to the rediscovery of known compounds. As a result of the greater affordability of DNA sequencing, genome mining approach has emerged. Through recognizing specific genetic sequences encoding highly conserved enzymes, biosynthetic gene clusters (BGCs) responsible for producing these metabolites can be identified in bacterial genomes (
Genomes of Galium aparine L.’s bacterial endophytes were analyzed using the antibiotics and secondary metabolite analysis shell (antiSMASH) 7.0 tool to explore their secondary metabolites BGCs (
FIGURE 6

Comparison of the distribution of biosynthetic gene clusters (BGCs) types. NRPS, non-ribosomal peptide synthetase; PKS, polyketide synthase; RiPP, ribosomally synthesized and post-translationally modified peptides.
Bacteria dedicate approximately 4%–8% of their genomes to the production of secondary metabolites, with Bacillus cereus (GR3, GS3, GL2) and Bacillus thuringiensis (GS1) species reaching the upper limit of this range. Strains belonging to Bacillus cereus species, both Bacillus cereus and thuringiensis and Bacillus wiedmannii (GL1, GL3, GR1) subgroups, overall exhibit a higher number of clusters (10–15) compared to those in Priestia spp. and Peribacillus frigoritolerans GR2 (7–8).
The diversity of BGCs types also demonstrates a genus-specific distribution pattern. NRPS and RiPP clusters are more prevalent in Bacillus spp. strains (
Strains of Priestia spp., Priestia sp. GS2, Priestia megaterium GR4, and Peribacillus frigoritolerans GR2 contain fewer BGCs in comparison to Bacillus spp. members. They lack NRPS clusters but have a greater number of terpene gene clusters. Both Priestia spp. strains harbor a carotenoid gene cluster (terpene; 50% with Halobacillus halophilus DSM 2266; MIBiG no. BGC0000645) and type III PKS cluster. Interestingly, Priestia sp. GS2 possesses gene cluster encoding bacillopaline (other; 100% similarity with Paenibacillus mucilaginosus KNP414; MIBiG no. BGC0002488), metallophore known for its zinc-binding ability (
As stated before, secondary metabolites are not essential for bacterial growth, but enhance their chances of survival in the occupied environment; a principle that applies also to endophytes. Many compounds, whose encoding clusters were found in Galium aparine L.’s endophytes, exhibit antibacterial and/or antifungal activities or metal-binding properties, directly influencing their ability to thrive inside the plant host. Although current knowledge about endophytic lifestyle is extensive, detailed comparative studies of BGCs in endophytic and non-endophytic bacterial genomes are needed to properly understand the importance of secondary metabolism in the establishment and maintenance of endophytism. Many of these clusters, especially those without any similarity to known compound genes remain silent, meaning they are not expressed under standard cultivation conditions (Zarins-Tutt et al., 2016). Therefore, finding a way to activate their synthesis, both by simply testing various cultivation conditions by One Strain Many Compounds (OSMAC) strategy or molecular biology techniques, is crucial for a comprehensive understanding of bacterial metabolism.
Conclusion
To our knowledge, this is the first research of the endophytic community of the medicinal plant Galium aparine L., and one of the few that thoroughly analyzes genomes of endophytic bacteria from the same plant host. We isolated ten strains of bacterial strains from different tissues of Galium aparine L. and performed high-quality de novo assembly of their genomes using both short and long reads. Taxonomic identification based on whole genome sequences showed that all of them are members of the Bacillaceae family with Priestia sp. GS2 and Bacillus sp. GL1 potentially representing new species. Additionally, Bacillus pretiosus GR1 was identified as the second member of its genus. We examined the distribution of mobile genetic elements, including phages and plasmids, as well as their repertoires of carbohydrate-active enzymes and secondary metabolites. Our findings show the rich biosynthetic capacity among the endophytes, which may not only play an important role in adaptation to the endophytic lifestyle but, moreover, offer potential for diverse biotechnological applications. Although Bacillus-related strains are well-known as plant growth promoters, their full metabolic capacities are yet to be explored. Further detailed genome-guided studies are needed as they can lead to the discovery of novel enzymes and metabolites. Medicinal plants are a particularly rich and valuable source of bioactive compounds, yet their bacterial endophytes are still highly. Therefore, research focused on isolating culturable endophytes and exploring their biotechnological potential is of high importance.
Materials and methods
Isolation of endophytic bacteria
Endophytic bacteria were isolated from healthy Galium aparine L. herb collected in spring 2022 from a neighboring area of a military airport in Łask, Poland (51°34′02.8″N 19°11′04.6″E). The plant was dug up and quickly transported to the laboratory. After cleaning with tap water to remove soil particles, healthy parts were subjected to surface sterilization (90% ethanol - 3 min, 6.25% sodium hypochlorite – 5 min, 90% ethanol – 30 s), followed by rinsing five times in sterile water (
DNA extraction, library preparation and sequencing
Genomic DNA of all strains was extracted from overnight cultures (LB medium, 30°C, 120 rpm) using both Gram Plus and Yeast Genomic DNA Purification Kit (Eurx, Poland), following the manufacturer protocol, as well as using phenol-chloroform method for Gram-positive bacteria (Wilson, 2001). Obtained genomic DNA was quantified with the Qubit dsDNA BR Assay Kit (Life Technologies), and its purity and integrity were assessed by spectrophotometric absorbance measurement and by agarose gel electrophoresis, respectively. For strains GS2, GS3, GL1, GL2, GR1, GR2, GR3 paired-end libraries (2 × 150 bp) were prepared from kit-extracted gDNA using MGIEasy FS PCR-Free DNA Library Prep Set and sequencing was performed at the BGI-TECH (Wuhan, China) on MGISEQ-2000 Sequencer (MGI, Shenzhen, China); for strains GS1, GL3 and GR4 TruSeq DNA PCR-Free Kit was used and sequencing was performed by Macrogen Europe on Illumina system sequencer. Phenol-chloroform extracted gDNA was subjected to library preparation by Native Barcoding Kit 24 V14 (Oxford Nanopore Technology) and NEBNext Companion Module (New England Biolabs) for subsequent sequencing on MinION Mk1b Nanopore sequencer (Oxford Nanopore Technology).
Genome de novo assembly
Short reads underwent quality filtering and trimming using Trimmomatic v0.36 (
Taxonomic identification
The Type Strain Genome Server (TYGS) was used for initial whole genome-based taxonomic analysis against type-strain species present in their database and calculation of dDDH values (
Annotation and functional analysis
Genomes were annotated using NCBI PGAP (Tatusova et al., 2016) and RASTtk v1.073 (
Statements
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1068863, PRJNA1068863.
Author contributions
NR: Software, Investigation, Conceptualization, Writing – original draft, Writing – review and editing, Data curation, Visualization, Formal Analysis, Methodology. MD: Software, Resources, Data curation, Writing – review and editing, Investigation, Methodology. OM-M: Conceptualization, Resources, Writing – review and editing, Supervision.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Acknowledgments
We thank Bartosz Sekuła and Maciej Nielipiński for their help with MinION software and computing resources, and Małgorzata Ryngajłło for contacting with Maurycy Daroch. This article has been completed while the first author was the Doctoral Candidate in the Interdisciplinary Doctoral School at the Lodz University of Technology, Poland.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2025.1612860/full#supplementary-material
Abbreviations
AA, auxiliary activity; AMR, antimicrobial resistance; ANI, Average Nucleotide Identity; antiSMASH, antibiotics and secondary metabolite analysis shell; ARGs, antibiotic resistance genes; ARO, antibiotic resistance ontology; BGCs, biosynthetic gene clusters; BUSCO, Benchmarking Universal Single-Copy Orthologs; CARD, Comprehensive Antibiotic Resistance Database; Cas, CRISPR-associated; CAZymes, carbohydrate-active enzymes; CBM, carbohydrate-binding module; CDPS, tRNA-dependent cyclodipeptide synthase; CDS – coding sequence; CE, carbohydrate esterase; CRISPR, clustered regularly interspaced short palindromic repeats; CSIs, conserved signature indels; dDDH, digital DNA:DNA hybridization; GH, glycoside hydrolase; GlcNAc, N-acetyl-D-glucosamine; GT, glycosyltransferase; HGT, horizontal gene transfer; HMMs, Hidden Markov Models; IAA, indole-3-acetic acid; IAAld, indole-3-acetaldehyde; ICEs, integrative and conjugative elements; IE, integration/excision; IPA, indole pyruvate; LAP, linear azol(in)e-containing peptides; LPSN, List of Prokaryotic names with Standing in Nomenclature; MGEs, mobile genetic elements; MIBiG, Minimum Information about a Biosynthetic Gene Cluster; MLST, multi-locus sequence typing; mobileOG-db, mobile orthologous groups database; MRSA, methicillin-resistant Staphylococcus aureus; MS, mass spectroscopy; NCBI, National Center for Biotechnology Information; ncRNA, non-coding RNA; NMR, nuclear magnetic resonance spectroscopy; NRPS, non-ribosomal peptide synthetases; ONT, Oxford Nanopore Technologies; OSMAC, One Strain Many Compounds; P, phage; PGAP, Prokaryotic Genome Annotation Pipeline; PGPB, plant growth-promoting bacteria; PHASTER, PHAge Search Enhanced Release; PKS, polyketide synthases; PL, polysaccharide lyase; QUAST, QUality ASsessment Tool for Genome Assemblies; RAST, The Rapid Annotation using Subsystem Technology; REALPHY, the Reference sequence Alignment based Phylogeny builder; RGI, Resistance Gene Identifier; RiPPs, ribosomally synthesized and post-translationally modified peptides; rRNA, ribosomal RNA; RRR, replication/recombination/repair; SMR, small multidrug resistance; SNPs, Single Nucleotide Polymorphisms; STD, stability/transfer/defense; T, transfer; TFBS, transcription factor binding sequences; tRNA, transfer RNA; TYGS, Type (Strain) Genome Server; WHO, World Health Organization.
Footnotes
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Summary
Keywords
bacterial endophytes, Galium aparine L., phylogenetics, genome mining, mobile genetic elements, secondary metabolites, plant microbiome
Citation
Rutkowska N, Daroch M and Marchut-Mikołajczyk O (2025) Exploring the diversity and genomics of cultivable Bacillus-related endophytic bacteria from the medicinal plant Galium aparine L.. Front. Microbiol. 16:1612860. doi: 10.3389/fmicb.2025.1612860
Received
16 April 2025
Accepted
03 June 2025
Published
30 June 2025
Volume
16 - 2025
Edited by
Muneer Ahmad Malla, German Centre for Integrative Biodiversity Research (iDiv), Germany
Reviewed by
Satheesh Sathianeson, King Abdulaziz University, Saudi Arabia
Liu Dong, Anqing Vocational and Technical College, China
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© 2025 Rutkowska, Daroch and Marchut-Mikołajczyk.
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*Correspondence: Natalia Rutkowska, natalia.rutkowska@dokt.p.lodz.pl
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