IntroductionBacteroidota is the third most abundant type of bacterial phylum in the ocean, after Pseudomonadota and Cyanobacteria1,2. This phylum consists of six classes, among which the class Flavobacteriia contains a single order Flavobacteriales. The Flavobacteriales order includes eight families, with Flavobacteriaceae being the largest family3. The family Flavobacteriaceae consists of 155 validly published genera, among which Capnocytophaga, Flavobacterium, Tenacibaculum-Polaribacter, and Chryseobacterium are the major marine clades4. Some genera of Flavobacteriaceae are also found in terrestrial and freshwater environments5. Marine clades can exist freely in water, attach to particles, or form symbiotic relationships with algae6. They can also be associated with invertebrates such as corals, sponges7, and echinoderms8. Extensive novel taxa have recently been added to the family Flavobacteriaceae9,10. The genus Pontimicrobium, recently added to the Flavobacteriaceae family, initially contained only one species, P. aquaticum, which was isolated from seawater11.The members of the family Flavobacteriaceae are Gram-stain-negative, bacilli, non-spore forming, and aerobic bacteria4. They play a crucial role in carbon turnover in marine environments by degrading complex polysaccharides and proteins12,13. The genomes of members of Flavobacteriaceae are affluent in CAZymes and peptidases, enabling them to act as specialized degraders of macromolecules14,15. Additionally, they exhibit gliding motility, which aims to search for and prey on bacteria or nutrients16,17. Their genomes are also enriched with secondary metabolites, including carotenoids, alkaloids, terpenes, and antibiotics3,18.In a study of microbial diversity, we isolated a novel strain, SW4T, from surface seawater in the tidal flat of the West Sea in Korea. This strain, belonging to the genus Pontimicrobium, underwent taxonomic characterization. We performed a comparative genomic analysis between strain SW4T and P. aquaticum to identify key genes associated with a marine-adapted lifestyle and ecological functions. Genome analysis revealed that strain SW4T is well adapted to tidal flats, which are characterized by heavy metal inflow from land, sunlight exposure, and fluctuating salinity due to freshwater input and rainfall, by possessing key genetic determinants for marine adaptation, including genes for carotenoid synthesis and osmoregulation, which help mitigate oxidative and osmotic stress. In addition, the genus Pontimicrobium contained a high number of carbohydrate-active enzymes (CAZymes) that facilitate the breakdown and utilization of algal polysaccharides in marine environments. Overall, the taxonomic characterization and genome analysis emphasize the significant role of the genus Pontimicrobium in contributing to the health and functioning of marine ecosystems.Materials and methodsMarine samples collection and culturingA seawater sample collected from a tidal flat of the West Sea, Korea, was promptly transferred to the laboratory for processing. The 100 μl seawater sample was inoculated onto the low-nutrient medium, which was made of seawater and 50 mg/L (w/v) antifungal cycloheximide and 1.5% (w/v) agar. The culture plates were incubated at 20 °C for 1 week and then examined using a stereoscopic microscope (ZEISS Stemi 508). A pure culture was obtained by subculturing on marine agar (BD). The isolated colonies were preserved in 20% glycerol marine broth (MB) at − 80 °C for long-term storage. The novel isolates were deposited in the Indonesian Culture Collection (InaCC) and Korean Collection for Type Cultures (KCTC).Sequencing of 16S rRNA geneThe genomic DNA of the isolated strain was extracted using DNA extraction kit19. The 16S rRNA genes were first amplified using the universal primers, including 27F and 1492R. Sequencing was carried out with these primers along with two additional primers, 518R and 518F. The complete 16S rRNA gene sequences were assembled using Vector NTI software and then searched in the EzBioCloud database to identify matching sequences20. The sequences of the related strains downloaded from EzBioCloud were first aligned and trimmed using BioEdit software. Subsequently, three types of phylogenetic trees were constructed utilizing the Molecular Evolutionary Genetics Analysis (MEGA X) software21: neighbor-joining (NJ)22, maximum-likelihood algorithms (ML)23, and the maximum parsimony (MP) method24. All the phylogenetic trees were evaluated using 1,000 bootstrap iterations, with Capnocytophaga ochracea ATCC 27872T (U41350) serving as the outgroup.Physical and biochemical analysisTo determine colonial characteristics, strain SW4T was cultivated on MA. Gram reaction was performed using the BBL™ Gram Stain Kit (BD, USA). The morphology of the isolates was examined with a scanning electron microscope (SEM) (Regulus 8100, Hitachi). Salt tolerance was determined by preparing mimic marine broth that was changed with various concentrations of NaCl from 0, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10% (w/v). The range and optimal temperature for growth were tested at a temperature range from 4, 10, 15, 20, 25, 30, 37 and 45 °C on marine agar (MA). To determine the pH range and optimal pH, marine broth was adjusted across a pH range of 4.5 to 10.0 at 0.5-unit intervals using 20 mM buffer systems: phosphate buffer for pH 4.5 to 8.0, and carbonate buffer for pH 8.5 to 10.025. The gliding activity was determined by using a low nutrient soft agar26. The growth under anaerobic culture condition was determined using an anaerobic jar (BD GasPak Systems). The antibiotic susceptibility was tested on marine agar (BD) using various antibiotic discs (μg/disc) with ampicillin (10), chloramphenicol (30), carbenicillin (30), erythromycin (15), gentamicin (10), kanamycin (30), lincomycin (30), neomycin (30), nalidixic acid (30), novobiocin (30), penicillin (10 IU), streptomycin (10), tetracycline (30), and vancomycin (30)27. Catalase activity was tested using 3% (v/v) hydrogen peroxide, and oxidase activity was examined with 1% (w/v) tetramethyl-p-phenylenediamine dihydrochloride, respectively. The flexirubin type pigments were determined using a 20% (w/v) KOH solution28. Additional biochemical tests were performed using API ZYM, API 20E, and API 50CH (bioMérieux).Chemotaxonomic characterizationFor cellular fatty acid analysis, cells from strain SW4T and P. aquaticum KCTC 72003T were harvested from MA after 3 days of cultivation at 30 °C. Bacterial biomass at the same physiological stage was used, and fatty acid analysis was performed using the standard protocol of the Sherlock Microbial Identification System. The fatty acids were extracted according to the MIDI protocol (Sherlock Microbial Identification System version 6.0) and then analyzed using GC system (8890 GC system, Agilent)29. The polar lipids and respiratory quinone were examined using the Komagata and Suzuki protocols30. For polar lipid determination, compounds were spotted on a TLC plate (10 × 10 cm, silica gel 60 F254 plate, Merck) and then sprayed with various reagents: 0.2% ninhydrin, α-naphthol, molybdenum blue, and phosphomolybdic acid for aminolipids, glycolipids, phospholipids, and total lipids, respectively30. For quinone determination, compounds were extracted from cell biomass using a chloroform–methanol mixture (2:1, v/v), separated on TLC plates, and analyzed with an HPLC system.Genome sequencing and phylogenyThe genome sequencing of strain SW4T was carried out using the nanopore sequencing platform from Oxford Nanopore Technologies (United Kingdom). The process utilized SQK-LSK112 ligation sequencing kit, SQK-NBD112.24 barcoding kit (SQK-NBD112.24), an R10.4 flow cell, and a MinION device. The Flye version 2.9.1 was used to assemble the genome31. The CheckM version 1.2.2 and Busco version 5.4.4 were used to check the completeness and assess the quality of the genome31,32, respectively. The genome of strain SW4T was deposited to the NCBI with the GenBank accession number CP157199. The ANI and dDDH values were calculated using the ANI and genome-to-genome distance calculator33. A phylogenetic tree based on the whole genome of strain SW4T and its closest strain was constructed using the UBCG pipeline34.Genome functional analysisThe genomes of strain SW4T were first annotated using NCBI’s prokaryotic genome annotation pipeline (PGAP)35. A circular genome view was generated using the CGview server (https://stothardresearch.ca/cgview/). The KEGG pathways in the genome of strain SW4T were identified through the BlastKOALA database. Initially, the identification of KEGG pathways was performed using the BlastKOALA server36,37. Subsequently, the KEGG-decoder was used to proceed with the KEGG pathways obtained from BlastKOALA38. The RAST annotation was additionally used to identify the metabolic pathway and functional potential of both species in the genus Pontimicrobium39. The Comprehensive Antibiotic Resistance Database (CARD) was used to identify the antibiotic-resistant genes40. The genomes were annotated for CAZymes using the dbCAN2 server41. Additionally, a genome-wide comparative analysis of orthologous gene clusters or homologous proteins was conducted through the OrthoVenn3 server42.Phenotypic characterization: heavy metal tolerance and polysaccharide degradationMinimum inhibitory concentration (MIC) was determined as the lowest concentration of heavy metals that inhibited bacterial growth. Strain SW4T and the reference strain P. aquaticum KCTC 72003T were tested for tolerance to heavy metals, including Cu2⁺, Co2⁺, Ni2⁺, Mn2⁺, and Hg2⁺. Metal salts (CuSO₄·5H₂O, CoCl₂·6H₂O, NiCl₂·6H₂O, MnCl₂·4H₂O, and HgCl₂) were used in MA medium at the following concentrations: Cu2⁺ (0.1–1 mM), Co2⁺ (1–7 mM), Ni2⁺ (1–5 mM), Mn2⁺ (10–50 mM), and Hg2⁺ (0.05–0.5 mM)43,44. Cultures were inoculated in duplicate and incubated at 30 °C for 1 week.The polysaccharide degradation abilities of the strain SW4T and the reference strain P. aquaticum KCTC 72003T were assessed using two methods. First, the strains were grown on solid media containing 60% (v/v) seawater, 0.01% (w/v) peptone, and 1% (w/v) of each test polysaccharide (cellulose, chitin, κ-carrageenan, sodium alginate, starch, and xylan)45. Polysaccharide degradation was indicated by clear zones around colonies. In second method, liquid cultures with 0.2% (w/v) of each polysaccharide were used, and strains were incubated at 30 °C in a shaking incubator19. Samples were collected on days 0 and 7, and reducing sugars were detected in broth using 3,5-dinitrosalicylic acid (DNS) reagent46, with absorbance measured at 570 nm using a microplate reader (Synergy H1, BioTek).ResultsNovel strain isolation and morphologyAs a part of the Korean West Sea microbial diversity project, strain SW4T was isolated from seawater. The isolate grew optimally on MA, producing yellow, round colonies. SEM images revealed that the cells of strain SW4T are long rods with a cell length of 1.5–1.9 μm and a diameter ranging from 0.2 to 0.3 μm (Fig. S1).16S rRNA gene-based phylogenyThe phylogenetic analysis using 16S rRNA gene sequence confirmed that strain SW4T was affiliated to the genus Pontimicrobium within the phylum Bacteroidota with the closest strain P. aquaticum KCTC 72003T, with a similarity of 97.0%. The 16S rRNA gene similarity values among strain SW4T and reference strain P. aquaticum KCTC 72003T were below the cutoff value of species discrimination (98.7%)47. The phylogenetic trees based on 16S rRNA gene sequences showed monophyletic clustering of strain SW4T with reference strain P. aquaticum KCTC 72003T (Fig. 1), which implies that strain SW4T is a member of the genus Pontimicrobium. Finally, from 16S rRNA gene similarity values and the phylogenetic trees clustering, the strain P. aquaticum KCTC 72003T was chosen as a reference strain. The 16S rRNA genes sequence of SW4T was submitted to NCBI with the gene bank accession number PP818627.Fig. 1Maximum likelihood tree based on 16S rRNA gene sequences showing the phylogenetic relationship of strain SW4T and closely related species in the genus Pontimicrobium and other genus in the family Flavobacteriaceae. Bootstrap values (> 70%) in the order of ML/NJ/MP are shown at the branch points based on 1000 replications. Capnocytophaga ochracea ATCC 27872 Twere used as an outgroup. Bar 0.10 substitutions per nucleotide position.Full size imagePhysical and biochemical characterizationStrain SW4T was Gram-negative bacilli, aerobic, and possessed gliding motility. The strain grew in the temperature range of 10–30 °C (optimum 25–30 °C), at pH range 6.5–8.0 (optimum 7.5), and in presence of NaCl range 1–3% (w/v) (optimum 2%, w/v). The strain was sensitive to carbenicillin, chloramphenicol, erythromycin, lincomycin, novobiocin, neomycin, and tetracycline while resistant to ampicillin, gentamicin, kanamycin, nalidixic acid, penicillin, and streptomycin. The differential physiological properties of the isolated strain and P. aquaticum KCTC 72003T are presented in the Table 1.Table 1 Differential physiological properties of strain SW4T and Pontimicrobium aquaticum KCTC 72003T.Full size tableStrain SW4T was oxidase and catalase positive. P. aquaticum KCTC 72003T and strain SW4T did not produce flexirubin-type pigments. The biochemical characteristics were further examined utilizing API kits. In API ZYM, the cells of strain SW4T were positive for the activities of acid phosphatase, alkaline phosphatase, esterase (C4), esterase lipase (C8), leucine arylamidase, and naphthol-AS-BI-phosphohydrolase, while negative for the activities of β-glucuronidase, α-fucosidase, α-mannosidase, and trypsin. In the API 20E tests, the strain tested positive for gelatin hydrolysis and acid formation from amygdalin, arabinose, d-glucose, and sucrose. The API 50CH strip showed acid production from l-arabinose, N-acetylglucosamine, d-cellobiose, d-galactose, d-glucose, gentiobiose, glycogen, d-fructose, d-maltose, d-mannose, d-sucrose, starch, d-trehalose, d-turanose, and d-xylose. The differential biochemical characteristics of strain SW4T and P. aquaticum KCTC 72003T are presented in the Table 1.Chemotaxonomic characterizationThe fatty acid profile of strain SW4T and P. aquaticum KCTC 72003T shared a similar feature. The predominant fatty acids found in strain SW4T and reference strain P. aquaticum KCTC 72003T were iso-C15:1 G, iso-C15:0, and iso-C17:0 3-OH ranged from 20.0–22.9, 18.4–24.1, and 14.6–17.0%, respectively. The minor fatty acids were C16:0, anteiso-C15:0, and iso-C14:0, ranging from 1.7–2.7, 1.5–1.7, and 1.2–2.8%, respectively (Table 2). Both strains in the genus Pontimicrobium have menaquinone 6 (MK-6) as a respiratory quinone. The polar lipid composition of strain SW4T included phosphatidylethanolamine (PE), an unknown lipid (L1), and two aminolipids (AL1-AL2) (Fig. S2).Table 2 Cellular fatty acid composition of strain SW4T and the Pontimicrobium aquaticum KCTC 72003T.Full size tableGenome analysis and phylogenyThe CheckM value of the genome of strain SW4T was 99.23%, showing the completeness and high quality of the genome. The genomes of strain SW4T consisted of two contigs, in which contig one was a circular chromosome with a size of 3,431,248 bp, while the contig two was a plasmid with a size of 6,997 bp. The NCBI PGAP annotation of the genomes of strain SW4T and P. aquaticum KCTC 72003T provided details on the number of genes, coding sequences (CDSs), rRNAs, and tRNAs, as presented in Table 3. Additionally, circular genomic feature maps were made through CGView server, providing the complete view of the genomes of both Pontimicrobium strains (Fig. 2). The ANI and dDDH values between strain SW4T and P. aquaticum KCTC 72003T were 81.0 and 24.40%, respectively. Both values are lower than the cutoff values of species differentiation, which range from 95–96% for ANI while below 70% for dDDH33,48. Thus, the ANI and dDDH values confirm the novelty of strain SW4T. A genome-based phylogenetic tree further showed monophyletic clustering of strain SW4T with P. aquaticum KCTC 72003T, consistent with the 16S rRNA gene-based phylogenetic trees (Fig. 3).Table 3 Genome features of strain SW4T and the Pontimicrobium aquaticum KCTC 72003T.Full size tableFig. 2Graphical circular maps of the genomes of the novel Pontimicrobium strain SW4T and the reference strain, generated by using the CGView server. (A) P. maritimus SW4T; (B) P. aquaticum CAU1491T.Full size imageFig. 3Genome-based phylogenetic tree of Pontimicrobium strain SW4T and other related type strains using UBCGs (concatenated alignment of 92 core genes). Bootstrap values are indicated at nodes. Scale bar, 0.05 substitutions per position.Full size imageComparative genomes analysisMetabolic pathways analysis using KEGG databaseThe genomes of strain SW4T and P. aquaticum KCTC 72003T were examined for metabolic pathways through KEGG databases, and the results were visualized in the heatmap (Fig. 4). The KEGG analysis detected the important metabolic pathways that are commonly involved in cellular respiration and carbohydrate metabolism. Both strains also harbored complete biosynthetic pathways for a wide range of amino acids, including arginine, alanine, aspartate, asparagine, cysteine, glycine, glutamate, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, tyrosine, tryptophan, threonine, and valine. The biosynthesis of these amino acids plays a crucial role in microbial survival and adaptation to diverse environmental conditions49.Fig. 4Heatmap showing the distribution of various metabolic pathways identified through KEGG analysis among the genus Pontimicrobium and other type strains of family Flavobacteriaceae. Strains: 1,SW4T; 2, P. aquaticum KCTC 72003T; 3, Aurantibacter aestuarii KCTC 32269T; 4, Bizionia algoritergicola; 5, Olleya_sp; 6, Lacinutrix venerupis_DOK2_8; 7, Olleya aquimaris DSM 24464; 8, Psychroserpens damuponensis JCM17632; 9, Lacinutrix mariniflava AKS432; 10, Yeosuana marina JLT21; 11, Bizionia psychrotolerans PBM7; 12, Bizionia_echini ERR599366; 13, Lacinutrix algicola AKS293; 14, Ichthyenterobacterium magnum DSM 26283; 15, Olleya sediminilitoris YSTF M6 1; 16, Lacinutrix jangbogonensis PAMC 27,137; 17, Siansivirga zeaxanthinifaciens CCSAMT ; 18, Capnocytophaga ochracea DSM7271; 19, Winogradskyella litoriviva KMM6491T; 20, Lacinutrix venerupis DSM 28755T.Full size imageMetabolic pathways analysis using RAST serverThe genomes of strain SW4T and P. aquaticum KCTC 72003T were annotated through the RAST database. Based on the RAST annotation, the genome of strain SW4T revealed the presence of 3,166 coding sequences (CDSs) and 46 RNAs (Fig. 5A). Meanwhile, P. aquaticum KCTC 72003T contained 3,108 CDSs and 36 RNAs (Fig. 5B). Strain SW4T exhibited 223 annotated subsystem features classified into 23 categories, whereas P. aquaticum KCTC 72003T exhibited 158 annotated subsystem features classified into 21 categories. However, more than 81% of CDSs in both strains of the genus Pontimicrobium were not assigned to any defined categories.Fig. 5RAST subsystem category distributions of novel Pontimicrobium strain SW4T and the reference strain. (A) P. maritimus SW4T; (B) P. aquaticum CAU1491T.Full size imageIn strain SW4T, the most significant number of genes were assigned to amino acids and their derivatives (199 genes), followed by cofactors, vitamins, prosthetic groups, and pigments (135 genes), and protein metabolism (100 genes). Similarly, in P. aquaticum KCTC 72003T, the highest number of genes were assigned to amino acids and their derivatives (150 genes), followed by cofactors, vitamins, prosthetic groups, and pigments (107 genes), and carbohydrate metabolism (74 genes).Genomic features related to the metabolism of heavy metalsThe KEGG pathways analysis showed that strain SW4T and P. aquaticum KCTC 72003T possess significant metabolic pathways involved in the transport and metabolism of heavy metals. Strain SW4T and P. aquaticum KCTC 72003T carried a complete pathway for arsenic reduction (Fig. 4). Additionally, both strains possess transporter genes responsible for the uptake of cobalt copper, iron, and manganese, including CorA, CopA, FeoB, and MntH, respectively. Among these transporter proteins, CorA exhibits notable diversity, as it facilitates the transport of magnesium, cobalt, and nickel50. For the transport of ferrous and ferric iron, the strains utilize FeoB, along with AfuA, an ABC-type transporter protein. Furthermore, RAST analysis also revealed that the strains carry genes involved in the homeostasis of copper, cobalt, zinc, and cadmium (Fig. 5A). Overall, the KEGG and RAST analyses of strain SW4T and P. aquaticum KCTC 72003T highlight their bioremediation potential by facilitating the transport and homeostasis of toxic metals, including arsenic, cobalt, copper, cadmium, iron, and zinc.The genome-based predictions were further validated through phenotypic assays assessing heavy metal tolerance using minimum inhibitory concentration (MIC) tests. Strain SW4T exhibited growth in the presence of 0.1 mM Cu2⁺, 2 mM Co2⁺, 3 mM Ni2⁺, and 20 mM Mn2⁺ but was unable to grow in the presence of Hg2⁺. Similarly, the reference strain P. aquaticum KCTC 72003T showed tolerance to 0.2 mM Cu2⁺, 5 mM Co2⁺, 5 mM Ni2⁺, and 20 mM Mn2⁺, with no growth observed under Hg2⁺ exposure (Table S1). These results are consistent with metal resistance profiles reported for deep-sea isolates such as Dietzia maris and Pseudoalteromonas shioyasakiensis51,52. For instance, D. maris exhibited MICs of Cu2⁺ (2.8–5.7 mM), Co2⁺ (0.6 mM), Ni2⁺ (3.0 mM), and Mn2⁺ (14.3 mM), supporting the ecological relevance of the observed resistance traits (Table S1).Genomic features related to nitrogen and sulfur cyclingKEGG analysis revealed that strain SW4T and P. aquaticum KCTC 72003T harbor key pathways essential for the nitrogen cycle. Specifically, KEGG analysis showed that strain SW4T possesses pathways for nitrite, nitric oxide, and nitrous oxide reduction (Fig. 4). Additionally, RAST annotation identified 27 genes involved in nitrogen metabolism, including those associated with nitrite, nitrate ammonification, and ammonia assimilation (Fig. 5). RAST analysis also revealed the most significant differences in nitrogen metabolism between strain SW4T and P. aquaticum KCTC 72003T. The primary distinction is that P. aquaticum KCTC 72003T possesses a great number of denitrification genes (24 genes), whereas these genes are absent in strain SW4T. In contrast, strain SW4T harbors a significantly higher number of genes related to ammonia assimilation, nitrate, and nitrite ammonification (12 genes) compared to only three such genes in P. aquaticum KCTC 72003T.Nitrite reduction contributes to ammonia production, aiding nitrogen conservation in the ecosystem53. Denitrification, through the sequential reduction of nitric oxide to nitrous oxide and ultimately to nitrogen gas, mitigates nitrous oxide emissions, a potent greenhouse gas, and supports global nitrogen cycling54,55. These pathways are essential for mitigating the release of nitrous oxide, a potent greenhouse gas, into the atmosphere, playing a crucial role in maintaining marine ecosystems and supporting global nitrogen cycling56. Additionally, nitrate reduction can generate ammonia, which microbes assimilate into organic compounds like amino acids and nucleic acids, essential for growth and reproduction57,58.Beyond nitrogen cycling, KEGG and RAST analyses also identified pathways related to sulfur cycling in strain SW4T. KEGG analysis highlighted pathways for sulfide oxidation and sulfur assimilation, while RAST analysis revealed pathways for thioredoxin-disulfide reductase and galactosylceramide metabolism. Interestingly, comparative analysis of sulfur metabolism between strain SW4T and P. aquaticum KCTC 72003T showed that both possess highly similar thioredoxin-disulfide reductase genes. Thioredoxin-disulfide reductase is particularly crucial for bacterial survival in marine environments, enabling rapid adaptation to changing redox conditions59,60. However, P. aquaticum KCTC 72003T carries genes for galactosylceramide and sulfatide metabolism, which are absent in strain SW4T (Fig. 5A, B). Sulfatide metabolism plays a key role not only in marine adaptation but also in the degradation and transformation of organic sulfur compounds, contributing to sulfur cycling in marine ecosystems61.To complement these genomic insights, further phenotypic experiments are needed to confirm whether these metabolic pathways are functionally expressed under laboratory conditions. Such validation will provide deeper insights into the ecological roles and biogeochemical capabilities of these strains.Genomic insights into stress response and marine adaptationTo investigate the stress response mechanisms of Pontimicrobium strains in tidal flat environments, functional gene categories related to environmental adaptation were analyzed. RAST analysis revealed that strain SW4T and P. aquaticum KCTC 72003T harbor between 14 and 17 stress response genes, with the highest proportion associated with oxidative stress, followed by periplasmic and osmotic stress. The abundance of these genes underscores their crucial role in the adaptation and survival of Pontimicrobium strains in the marine environment62. RAST annotation identified a total of nine clusters related to oxidative stress, including those involved in the glutathione redox cycle. Glutathione acts as a vital antioxidant that neutralizes reactive oxygen species (ROS), thus protecting the cells from oxidative damage63. The presence of multiple oxidative stress genes indicates a robust system for dealing with oxidative stress, which is critical in shallow seawater in the tidal flat62,64.The second category included periplasmic stress response genes, which contribute to maintaining the integrity and functionality of the cell envelope under harsh marine conditions, such as severe fluctuations in temperature, pH, salinity, and pressure65. The stress genes against pressure stress consisted of osmotic stress-related cluster genes, which enabled strain SW4T to regulate their internal osmotic pressure, preventing cell lysis or shrinkage due to osmotic imbalances in marine salinity66. Moreover, RAST detected two gene clusters related to dimethylarginine metabolism, categorized under stress response. The dimethylarginine metabolism plays an important role in providing energy and nitrogen sources, contributing to the nitrogen cycle67.Additionally, Prokka annotation was employed to identify specific antioxidant-related genes involved in the antioxidant system for marine adaptation. Strain SW4T harbored genes for superoxide dismutase and catalase, including sodA and katG, which protect the cells from ROS by detoxifying them68,69. It also carried thioredoxin-related genes, such as trxA and trxB, which help maintain cellular redox balance and further bolster oxidative stress resistance70,71. Furthermore, strain SW4T also carried essential heat shock protein genes, including ibpB and dnaK72 and cold shock protein cspA, which are crucial for survival in both cold and hot marine environments73,74. These proteins ensure proper protein folding and repair under stress conditions, thereby supporting cellular functions and enhancing survival in the challenging environmental conditions typical of the tidal flat ecosystems75,76.Genomic features related to antibiotic-resistant and virulenceRAST annotation of the genomes of strain SW4T and P. aquaticum KCTC 72003T revealed significant differences in the virulence, disease, and defense subsystems. The most prominent distinction was observed in the number of coding sequences (CDSs) associated with these functions. Strain SW4T contained only 22 coding sequences related to virulence, disease, and defense, whereas P. aquaticum KCTC 72003T has three times as many corresponding genes. Specifically, strain SW4T carried 11 CDSs related to antibiotic resistance and the handling of toxic compounds, along with 11 CDSs associated with invasion and intracellular resistance. In contrast, P. aquaticum KCTC 72003T contained 51 CDSs linked to antibiotics and toxic compounds, including arsenic and zinc resistance, as well as resistance to vancomycin, which were absent in strain SW4T. Notably, copper tolerance was unique to strain SW4T (Fig. 5A, B).The identified antibiotic resistance genes include those conferring resistance to fluoroquinolones, as well as genes associated with multidrug-resistant efflux pumps and β-lactamase production. Additionally, the CARD also detected the presence of the vanT gene in the genome of strain SW4T, which confers resistance to glycopeptide antibiotics such as vancomycin.The antibiotic susceptibility of strain SW4T was assessed using the disc diffusion method. The strain exhibited resistance to ampicillin, gentamicin, kanamycin, nalidixic acid, penicillin, and streptomycin while remaining sensitive to chloramphenicol, carbenicillin, erythromycin, lincomycin, neomycin, novobiocin, tetracycline, and vancomycin. These phenotypic observations were largely consistent with genome-based predictions. Specifically, resistance to fluoroquinolones (e.g., nalidixic acid) and β-lactam antibiotics (e.g., ampicillin, penicillin) correlates with the presence of corresponding resistance genes. Resistance to aminoglycosides, such as gentamicin and kanamycin, is likely associated with the presence of multidrug efflux pump genes. Interestingly, although the vanT gene was identified in the genome, strain SW4T remained sensitive to vancomycin. Suggesting that vanT may be unexpressed or nonfunctional under the tested conditions.Beyond antibiotic resistance, RAST annotation also revealed that both Pontimicrobium strains carry virulence genes associated with invasion and intracellular resistance. Notably, both genomes encode a Mycobacterium-like virulence operon, comprising small (SSU) and large (LSU) ribosomal subunit proteins implicated in protein synthesis and pathogenesisp77, as well as a Mycobacterium virulence operon linked to DNA transcription regulation. In addition, the strains possess Listeria internalin-like surface proteins, which facilitate bacterial adhesion and host cell entry cell78. These genes further enhance the bacterium’s ability to acquire nutrients, form protective biofilms, and protect itself from a wide range of environmental stresses.Annotation of carbohydrate-active enzymes (CAZymes) through dbCAN meta serverThe genomes of strain SW4T and P. aquaticum KCTC 72003T were annotated for CAZyme gene clusters (CGCs) utilizing the dbCAN meta server. The dbCAN analysis of strain SW4T genome identified 57 CAZymes, including 36 glycosyltransferases (GTs), 13 glycoside hydrolases (GHs), two auxiliary activities (AAs), three carbohydrate esterases (CEs), and one carbohydrate binding module (CBM). In comparison, the genome of P. aquaticum KCTC 72003T harbored 55 CAZymes, including 39 GTs, 8 GHs, 3 CEs, 3 AAs, and 2 CBMs (Table 4).Table 4 Distribution of carbohydrate-active enzyme (CAZyme) in the genomes of strain SW4T and Pontimicrobium aquaticum KCTC 72003T.Full size tableThe abundance of CAZymes reflects the ecological adaptability and potential biotechnological applications of strains in the genus Pontimicrobium79. The annotation results highlight their significant role in polysaccharide degradation within tidal flat ecosystems. As shown in Table 4, the most abundant CAZymes were GTs, followed by GHs. GTs catalyze the formation of glycosidic linkages, while GHs hydrolyze glycosidic bonds in polysaccharides such as starch and cellulose.The presence of a high number of CAZymes was further supported by in vitro polysaccharide degradation tests. The degradation of various polysaccharides, including cellulose, chitin, κ-carrageenan, sodium alginate, starch, and xylan, was evaluated in both solid and liquid media. On solid media, clear zones around the colonies indicated enzymatic degradation activity. Specifically, strain SW4T demonstrated the capacity to degrade cellulose, chitin, starch, and xylan. This was further confirmed by the DNS assay, which demonstrated the breakdown of these polysaccharides along with the production of reducing sugars.The abundance of CAZymes, particularly glycoside hydrolases (GHs, 13 genes) and glycosyltransferases (GTs, 36 genes), supports the strain’s capacity to degrade complex carbohydrates. Overall, these findings suggest that strain SW4T plays an important role in the carbon cycle of the ecosystem. Furthermore, the enzymatic breakdown of polysaccharides may produce oligosaccharides with promising applications in biomedicine, cosmetics, and the food industry.Detection of orthologous gene clusters using OrthoVenn3 serverUsing the OrthoVenn3 server, a comparative orthologous gene cluster analysis between strain SW4T and P. aquaticum KCTC 72003T revealed 2,330 shared orthologous gene clusters. In addition, strain SW4T possessed 45 unique gene clusters, while P. aquaticum KCTC 72003T contained 51 unique clusters (Fig. 6). The unique gene clusters in strain SW4T were predominantly associated with fundamental biological processes (14.10%), metabolic processes (11.53%), and cellular processes (11.53%). At the molecular function level, these unique clusters were primarily linked to hydrolase activity (33.00%) and nucleic acid binding (16.6%). In terms of cellular component classification, the associated genes were mostly related to cell parts and membranes, each accounting for 50% of the annotations.Fig. 6Analysis of orthologous protein clusters among the genus Pontimicrobium, using the OrthoVenn3 server.Full size imageConclusionStrain SW4T, isolated from tidal flat seawater, is a novel species in the Pontimicrobium genus within the family Flavobacteriaceae and the phylum Bacteroidota. Comparative genomic analysis between strain SW4T and P. aquaticum KCTC 72003T revealed key ecological roles of SW4T in tidal flat ecosystems, including involvement in nitrogen and sulfur cycles. The strain also possesses pathways for sulfide oxidation and thioredoxin-disulfide reductase activity, contributing to redox balance in coastal sediments. Additionally, its ability to tolerate and metabolize heavy metals like copper, cobalt, zinc, and cadmium suggests bioremediation potential. The presence of a high number of carbohydrate-active enzymes (CAZymes) supports the degradation of algal polysaccharides, contributing significantly to carbon cycling. The strain is also equipped with genes related to stress responses, including heat, cold, oxidative, and osmotic stress, virulence, and antibiotic resistance. These features highlight SW4T’s adaptability to fluctuating conditions and its role in ecological balance. In conclusion, strain SW4T is vital for carbon and nitrogen cycling, ecosystem productivity, and biodiversity maintenance in tidal flat environments. This study not only identifies a novel Pontimicrobium species but also deepens our understanding of the genus’s ecological significance.Description Pontimicrobium maritimus sp. nov.Pontimicrobium maritimus (mari’timus, referring to the source of isolation sea water).The cells are Gram-negative bacilli, strictly aerobic, and have gliding motility. The strain produces a light yellow, circular, smooth colony on MA. The optimum growth occurs at temperatures 25–30 °C, pH 6.5–7.5, and NaCl 1–3% (w/v). The strain is positive for the activities of acid phosphatase, alkaline phosphatase, esterase (C4), esterase lipase (C8), leucine arylamidase, and naphthol-AS-BI-phosphohydrolase, while negative for the activities of β-glucuronidase, α-fucosidase, α-mannosidase, and trypsin. In the API 20E tests, the strains tested positive for gelatin hydrolysis and for acid formation from amygdalin, arabinose, d-glucose, and sucrose. The API 50CH strip showed acid production from l-arabinose, N-acetylglucosamine, d-cellobiose, d-galactose, d-glucose, gentiobiose, glycogen, d-fructose, d-maltose, d-mannose, d-sucrose, starch, d-trehalose, d-turanose, and d-xylose. The major fatty acids identified were iso-C15:0, iso-C15:1 G, and iso-C17:0 3-OH. The polar lipids of strain SW4T included phosphatidylethanolamine (PE), and MK-6 was identified as the only respiratory quinone. The genomic DNA G + C content of the type strain is 32%.The type strain, SW4T (= KCTC 42599T = InaCC B1659T), was isolated from the sea water collected from the West Sea, Republic of Korea. The 16S rRNA genes sequence of strain SW4T was submitted to NCBI with the gene bank accession number PP818627. The complete genome of the novel strain SW4T was deposited with the gene bank accession number CP157199.Data availabilityThe datasets generated and/or analysed during the current study are available with the gene bank accession number PP818627 and CP157199. https://www.ncbi.nlm.nih.gov/nuccore/PP818627.1/. https://www.ncbi.nlm.nih.gov/nuccore/CP157199.1/.ReferencesGómez-Pereira, P. R. et al. Distinct flavobacterial communities in contrasting water masses of the north Atlantic Ocean. ISME J. 4, 472–487. https://doi.org/10.1038/ismej.2009.142 (2010).Article CAS PubMed Google Scholar Fernández-Gómez, B. et al. Ecology of marine Bacteroidetes: a comparative genomics approach. ISME J. 7, 1026–1037. https://doi.org/10.1038/ismej.2012.169 (2013).Article CAS PubMed PubMed Central Google Scholar Gavriilidou, A. et al. Comparative genomic analysis of Flavobacteriaceae: Insights into carbohydrate metabolism, gliding motility and secondary metabolite biosynthesis. BMC Genomics 21, 569. https://doi.org/10.1186/s12864-020-06971-7 (2020).Article CAS PubMed PubMed Central Google Scholar McBride, M. J. in The Prokaryotes: Other Major Lineages of Bacteria and the Archaea (eds Rosenberg, E. et al.) 643–676 (Springer, Berlin, 2014).Kirchman, D. L. The ecology of Cytophaga–Flavobacteria in aquatic environments. FEMS Microbiol. Ecol. 39, 91–100 (2002).CAS PubMed Google Scholar Mann, A. J. et al. The genome of the alga-associated marine flavobacterium Formosa agariphila KMM 3901T reveals a broad potential for degradation of algal polysaccharides. Appl. Environ. Microbiol. 79, 6813–6822 (2013).Article ADS CAS PubMed PubMed Central Google Scholar Yoon, B.-J. & Oh, D.-C. Spongiibacterium flavum gen. nov., sp. Nov., a member of the family Flavobacteriaceae isolated from the marine sponge Halichondria oshoro, and emended descriptions of the genera Croceitalea and Flagellimonas. Int. J. Syst. Evolut. Microbiol. 62, 1158–1164 (2012).Article CAS Google Scholar Sweet, M., Croquer, A. & Bythell, J. Bacterial assemblages differ between compartments within the coral holobiont. Coral Reefs 30, 39–52 (2011).Article ADS Google Scholar Fu, Z.-Y. et al. Marixanthotalea marina gen. nov., sp. Nov., a bacterium in the family Flavobacteriaceae isolated from seawater. Int. J. Syst. Evol. Microbiol. 73, 006107 (2023).Article CAS Google Scholar Wang, Y. W., Wang, X. H., Zhang, J., Du, Z. J. & Mu, D. S. Cerina litoralis gen. nov., sp. nov., a novel potential polysaccharide degrading bacterium of the family Flavobacteriaceae, isolated from marine sediment. Antonie Van Leeuwenhoek 116, 1447–1455. https://doi.org/10.1007/s10482-023-01888-z (2023).Article CAS PubMed Google Scholar Janthra, T. et al. Pontimicrobium aquaticum gen. nov., sp. nov., a bacterium in the family Flavobacteriaceae isolated from seawater. Int. J. Syst. Evol. Microbiol. 70, 4562–4568. https://doi.org/10.1099/ijsem.0.004314 (2020).Article CAS PubMed Google Scholar Bennke, C. M. et al. Polysaccharide utilisation loci of Bacteroidetes from two contrasting open ocean sites in the North Atlantic. Environ. Microbiol. 18, 4456–4470. https://doi.org/10.1111/1462-2920.13429 (2016).Article CAS PubMed Google Scholar McKee, L. S. et al. Polysaccharide degradation by the Bacteroidetes: Mechanisms and nomenclature. Environ. Microbiol. Rep. 13, 559–581. https://doi.org/10.1111/1758-2229.12980 (2021).Article CAS PubMed Google Scholar Chen, B. et al. Discovery of a novel marine Bacteroidetes with a rich repertoire of carbohydrate-active enzymes. Comput. Struct. Biotechnol. J. 23, 406–416. https://doi.org/10.1016/j.csbj.2023.12.025 (2024).Article CAS PubMed Google Scholar Beidler, I. et al. Marine bacteroidetes use a conserved enzymatic cascade to digest diatom β-mannan. ISME J. 17, 276–285. https://doi.org/10.1038/s41396-022-01342-4 (2023).Article CAS PubMed Google Scholar McBride, M. J. & Nakane, D. Flavobacterium gliding motility and the type IX secretion system. Curr. Opin. Microbiol.. 28, 72–77. https://doi.org/10.1016/j.mib.2015.07.016 (2015).Article CAS PubMed Google Scholar Sato, K. et al. Colony spreading of the gliding bacterium Flavobacterium johnsoniae in the absence of the motility adhesin SprB. Sci. Rep. 11, 967. https://doi.org/10.1038/s41598-020-79762-5 (2021).Article CAS PubMed PubMed Central Google Scholar Cooper, R. et al. Two new monobactam antibiotics produced by a Flexibacter sp. I. Taxonomy, fermentation, isolation and biological properties. J. Antibiot. (Tokyo) 36, 1252–1257. https://doi.org/10.7164/antibiotics.36.1252 (1983).Article CAS PubMed Google Scholar Muhammad, N., Avila, F., Nedashkovskaya, O. I. & Kim, S.-G. Three novel marine species of the genus Reichenbachiella exhibiting degradation of complex polysaccharides. Front. Microbiol. 14, 1265676 (2023).Article PubMed PubMed Central Google Scholar Yoon, S. H. et al. Introducing EzBioCloud: A taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int. J. Syst. Evol. Microbiol. 67, 1613–1617. https://doi.org/10.1099/ijsem.0.001755 (2017).Article CAS PubMed PubMed Central Google Scholar Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. https://doi.org/10.1093/molbev/msy096 (2018).Article CAS PubMed PubMed Central Google Scholar Saitou, N. & Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425. https://doi.org/10.1093/oxfordjournals.molbev.a040454 (1987).Article CAS PubMed Google Scholar Felsenstein, J. Evolutionary trees from DNA sequences: A maximum likelihood approach. J. Mol. Evol. 17, 368–376. https://doi.org/10.1007/bf01734359 (1981).Article ADS CAS PubMed Google Scholar Fitch, W. M. Toward defining the course of evolution: Minimum change for a specific tree topology. Syst. Biol. 20, 406–416 (1971).Article Google Scholar Muhammad, N. et al. Flavobacterium litorale sp. nov., isolated from red alga. Int. J. Syst. Evol. Microbiol. https://doi.org/10.1099/ijsem.0.005458 (2022).Article PubMed Google Scholar Tittsler, R. P. & Sandholzer, L. A. The use of semi-solid agar for the detection of bacterial motility. J. Bacteriol. 31, 575–580. https://doi.org/10.1128/jb.31.6.575-580.1936 (1936).Article CAS PubMed PubMed Central Google Scholar Muhammad, N. et al. Vibrio ostreae sp. nov., a novel gut bacterium isolated from a Yellow Sea oyster. Int. J. Syst. Evol. Microbiol. https://doi.org/10.1099/ijsem.0.005586 (2022).Article PubMed Google Scholar Vila, E., Hornero-Méndez, D., Azziz, G., Lareo, C. & Saravia, V. Carotenoids from heterotrophic bacteria isolated from Fildes Peninsula, King George Island, Antartica. Biotechnol. Rep. Amst. 21, e00306. https://doi.org/10.1016/j.btre.2019.e00306 (2019).Article PubMed PubMed Central Google Scholar Sasser, M. C. Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids Technical Note # 101. (1990).Komagata, K. & Suzuki, K.-I. 4 Lipid and cell-wall analysis in bacterial systematics. Methods Microbiol. 19, 161–207 (1988).Article Google Scholar Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 37, 540–546. https://doi.org/10.1038/s41587-019-0072-8 (2019).Article CAS PubMed Google Scholar Manni, M., Berkeley, M. R., Seppey, M. & Zdobnov, E. M. BUSCO: Assessing genomic data quality and beyond. Curr. Protoc. 1, e323. https://doi.org/10.1002/cpz1.323 (2021).Article PubMed Google Scholar Meier-Kolthoff, J. P., Auch, A. F., Klenk, H. P. & Goker, M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinform. 14, 60. https://doi.org/10.1186/1471-2105-14-60 (2013).Article Google Scholar Na, S. I. et al. UBCG: Up-to-date bacterial core gene set and pipeline for phylogenomic tree reconstruction. J. Microbiol. 56, 280–285. https://doi.org/10.1007/s12275-018-8014-6 (2018).Article CAS PubMed Google Scholar Li, W. et al. RefSeq: Expanding the prokaryotic genome annotation pipeline reach with protein family model curation. Nucleic Acids Res. 49, D1020-d1028. https://doi.org/10.1093/nar/gkaa1105 (2021).Article ADS CAS PubMed Google Scholar Kanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. & Ishiguro-Watanabe, M. KEGG: Biological systems database as a model of the real world. Nucleic Acids Res. 53, D672-d677. https://doi.org/10.1093/nar/gkae909 (2025).Article PubMed Google Scholar Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30. https://doi.org/10.1093/nar/28.1.27 (2000).Article CAS PubMed PubMed Central Google Scholar Graham, E. D., Heidelberg, J. F. & Tully, B. J. Potential for primary productivity in a globally-distributed bacterial phototroph. ISME J. 12, 1861–1866. https://doi.org/10.1038/s41396-018-0091-3 (2018).Article CAS PubMed PubMed Central Google Scholar Aziz, R. K. et al. The RAST Server: Rapid annotations using subsystems technology. BMC Genomics 9, 75. https://doi.org/10.1186/1471-2164-9-75 (2008).Article CAS PubMed PubMed Central Google Scholar McArthur, A. G. et al. The comprehensive antibiotic resistance database. Antimicrob. Agents Chemother. 57, 3348–3357. https://doi.org/10.1128/aac.00419-13 (2013).Article CAS PubMed PubMed Central Google Scholar Ausland, C. et al. dbCAN-PUL: A database of experimentally characterized CAZyme gene clusters and their substrates. Nucleic Acids Res. 49, D523-d528. https://doi.org/10.1093/nar/gkaa742 (2021).Article CAS PubMed Google Scholar Sun, J. et al. OrthoVenn3: An integrated platform for exploring and visualizing orthologous data across genomes. Nucleic Acids Res. 51, W397-w403. https://doi.org/10.1093/nar/gkad313 (2023).Article CAS PubMed PubMed Central Google Scholar Noisangiam, R. et al. Heavy metal tolerant Metalliresistens boonkerdii gen. nov., sp. nov., a new genus in the family Bradyrhizobiaceae isolated from soil in Thailand. Syst. Appl. Microbiol. 33, 374–382. https://doi.org/10.1016/j.syapm.2010.06.002 (2010).Article CAS PubMed Google Scholar Muhammad, N., Avila, F. & Kim, S.-G. Comparative genome analysis of the genus Marivirga and proposal of two novel marine species: Marivirga arenosa sp. nov., and Marivirga salinae sp. nov.. BMC Microbiol. 24, 245. https://doi.org/10.1186/s12866-024-03393-3 (2024).Article CAS PubMed PubMed Central Google Scholar Gao, B., Jin, M., Li, L., Qu, W. & Zeng, R. Genome sequencing reveals the complex polysaccharide-degrading ability of novel deep-sea bacterium Flammeovirga pacifica WPAGA1. Front. Microbiol. https://doi.org/10.3389/fmicb.2017.00600 (2017).Article PubMed PubMed Central Google Scholar Deshavath, N. N., Mukherjee, G., Goud, V. V., Veeranki, V. D. & Sastri, C. V. Pitfalls in the 3, 5-dinitrosalicylic acid (DNS) assay for the reducing sugars: Interference of furfural and 5-hydroxymethylfurfural. Int. J. Biol. Macromol. 156, 180–185. https://doi.org/10.1016/j.ijbiomac.2020.04.045 (2020).Article CAS PubMed Google Scholar Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645. https://doi.org/10.1038/nrmicro3330 (2014).Article CAS PubMed Google Scholar Yoon, S. H., Ha, S. M., Lim, J., Kwon, S. & Chun, J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110, 1281–1286. https://doi.org/10.1007/s10482-017-0844-4 (2017).Article CAS PubMed Google Scholar Ramoneda, J., Jensen, T. B. N., Price, M. N., Casamayor, E. O. & Fierer, N. Taxonomic and environmental distribution of bacterial amino acid auxotrophies. Nat. Commun. 14, 7608. https://doi.org/10.1038/s41467-023-43435-4 (2023).Article ADS CAS PubMed PubMed Central Google Scholar Zhang, Y., Rodionov, D. A., Gelfand, M. S. & Gladyshev, V. N. Comparative genomic analyses of nickel, cobalt and vitamin B12 utilization. BMC Genomics 10, 78. https://doi.org/10.1186/1471-2164-10-78 (2009).Article CAS PubMed PubMed Central Google Scholar Rojas, L. A. et al. Characterization of the metabolically modified heavy metal-resistant Cupriavidus metallidurans strain MSR33 generated for mercury bioremediation. PLoS ONE 6, e17555. https://doi.org/10.1371/journal.pone.0017555 (2011).Article ADS PubMed PubMed Central Google Scholar Gillard, B., Chatzievangelou, D., Thomsen, L. & Ullrich, M. S. Heavy-metal-resistant microorganisms in deep-sea sediments disturbed by mining activity: An application toward the development of experimental in vitro systems. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00462 (2019).Article Google Scholar Liu, Y. et al. Spatial and temporal conversion of nitrogen using Arthrobacter sp. 24S4-2, a strain obtained from Antarctica. Front. Microbiol. 14, 1040201. https://doi.org/10.3389/fmicb.2023.1040201 (2023).Article PubMed PubMed Central Google Scholar Schreiber, F., Wunderlin, P., Udert, K. M. & Wells, G. F. Nitric oxide and nitrous oxide turnover in natural and engineered microbial communities: Biological pathways, chemical reactions, and novel technologies. Front. Microbiol. 3, 372. https://doi.org/10.3389/fmicb.2012.00372 (2012).Article PubMed PubMed Central Google Scholar Pajares, S. & Ramos, R. Processes and microorganisms involved in the marine nitrogen cycle: Knowledge and gaps. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00739 (2019).Article Google Scholar Zhang, M., Li, A., Yao, Q., Wu, Q. & Zhu, H. Nitrogen removal characteristics of a versatile heterotrophic nitrifying-aerobic denitrifying bacterium, Pseudomonas bauzanensis DN13-1, isolated from deep-sea sediment. Bioresour. Technol. 305, 122626. https://doi.org/10.1016/j.biortech.2019.122626 (2020).Article CAS PubMed Google Scholar Han, F. et al. Self-assembly of ammonium assimilation microbiomes regulated by COD/N ratio. Chem. Eng. J. https://doi.org/10.1016/j.cej.2022.140782 (2023).Article Google Scholar Brown, C. M. & Dilworth, M. J. Ammonia assimilation by rhizobium cultures and bacteroids. J. Gen. Microbiol. 86, 39–48. https://doi.org/10.1099/00221287-86-1-39 (1975).Article CAS PubMed Google Scholar He, J., Liu, S., Fang, Q., Gu, H. & Hu, Y. The thioredoxin system in Edwardsiella piscicida contributes to oxidative stress tolerance, motility, and virulence. Microorganisms https://doi.org/10.3390/microorganisms11040827 (2023).Article PubMed PubMed Central Google Scholar Wang, B. Y. et al. Thioredoxin H (TrxH) contributes to adversity adaptation and pathogenicity of Edwardsiella piscicida. Vet Res 50, 26. https://doi.org/10.1186/s13567-019-0645-z (2019).Article CAS PubMed PubMed Central Google Scholar Pomin, V. H. Phylogeny, structure, function, biosynthesis and evolution of sulfated galactose-containing glycans. Int. J. Biol. Macromol. 84, 372–379. https://doi.org/10.1016/j.ijbiomac.2015.12.035 (2016).Article CAS PubMed Google Scholar Wang, Y. et al. Peroxidase activity and involvement in the oxidative stress response of Roseobacter denitrificans truncated hemoglobin. PLoS ONE 10, e0117768 (2015).Article PubMed PubMed Central Google Scholar Kwon, D. H. et al. Protective effect of glutathione against oxidative stress-induced cytotoxicity in RAW 264.7 macrophages through activating the nuclear factor erythroid 2-related factor-2/heme oxygenase-1 pathway. Antioxidants (Basel) https://doi.org/10.3390/antiox8040082 (2019).Article PubMed Google Scholar Lesser, M. P. Oxidative stress in marine environments: Biochemistry and physiological ecology. Annu. Rev. Physiol. 68, 253–278 (2006).Article CAS PubMed Google Scholar Kim, H., Wu, K. & Lee, C. Stress-responsive periplasmic chaperones in bacteria. Front. Mol. Biosci. 8, 678697. https://doi.org/10.3389/fmolb.2021.678697 (2021).Article CAS PubMed PubMed Central Google Scholar Cho, B. C., Hardies, S. C., Jang, G. I. & Hwang, C. Y. Complete genome of streamlined marine actinobacterium Pontimonas salivibrio strain CL-TW6(T) adapted to coastal planktonic lifestyle. BMC Genomics 19, 625. https://doi.org/10.1186/s12864-018-5019-9 (2018).Article CAS PubMed PubMed Central Google Scholar Lundgren, B. R., Bailey, F. J., Moley, G. & Nomura, C. T. DdaR (PA1196) regulates expression of dimethylarginine dimethylaminohydrolase for the metabolism of methylarginines in Pseudomonas aeruginosa PAO1. J. Bacteriol. https://doi.org/10.1128/jb.00001-17 (2017).Article PubMed PubMed Central Google Scholar Ahn, J.-M., Mitchell, R. J. & Gu, M. B. Detection and classification of oxidative damaging stresses using recombinant bioluminescent bacteria harboring sodA∷, pqi∷, and katG∷ luxCDABE fusions. Enzyme Microb. Technol. 35, 540–544 (2004).Article CAS Google Scholar Dussurget, O., Rodriguez, M. & Smith, I. Protective role of the Mycobacterium smegmatis IdeR against reactive oxygen species and isoniazid toxicity. Tuber. Lung Dis. 79, 99–106. https://doi.org/10.1054/tuld.1998.0011 (1998).Article CAS PubMed Google Scholar Scharf, C. et al. Thioredoxin is an essential protein induced by multiple stresses in Bacillus subtilis. J. Bacteriol. 180, 1869–1877. https://doi.org/10.1128/jb.180.7.1869-1877.1998 (1998).Article CAS PubMed PubMed Central Google Scholar Mallén-Ponce, M. J., Huertas, M. J. & Florencio, F. J. Exploring the diversity of the thioredoxin systems in cyanobacteria. Antioxidants (Basel) https://doi.org/10.3390/antiox11040654 (2022).Article PubMed Google Scholar Klein, G., Laskowska, E., Taylor, A. & Lipińska, B. IbpA/B small heat-shock protein of marine bacterium Vibrio harveyi binds to proteins aggregated in a cell during heat shock. Mar. Biotechnol. 3, 346–354 (2001).Article CAS Google Scholar Muchaamba, F., Wambui, J., Stephan, R. & Tasara, T. Cold shock proteins promote nisin tolerance in listeria monocytogenes through modulation of cell envelope modification responses. Front. Microbiol. 12, 811939. https://doi.org/10.3389/fmicb.2021.811939 (2021).Article PubMed PubMed Central Google Scholar Ting, L. et al. Cold adaptation in the marine bacterium, Sphingopyxis alaskensis, assessed using quantitative proteomics. Environ. Microbiol. 12, 2658–2676. https://doi.org/10.1111/j.1462-2920.2010.02235.x (2010).Article CAS PubMed Google Scholar Hu, C. et al. Heat shock proteins: Biological functions, pathological roles, and therapeutic opportunities. MedComm (2020) 3, e161. https://doi.org/10.1002/mco2.161 (2022).Article CAS PubMed Google Scholar Zhou, Z. et al. A cold shock protein promotes high-temperature microbial growth through binding to diverse RNA species. Cell Discov. 7, 15. https://doi.org/10.1038/s41421-021-00246-5 (2021).Article CAS PubMed PubMed Central Google Scholar Rigottier-Gois, L. Dysbiosis in inflammatory bowel diseases: The oxygen hypothesis. ISME J. 7, 1256–1261. https://doi.org/10.1038/ismej.2013.80 (2013).Article CAS PubMed PubMed Central Google Scholar Bierne, H. & Cossart, P. Listeria monocytogenes surface proteins: From genome predictions to function. Microbiol. Mol. Biol. Rev. 71, 377–397. https://doi.org/10.1128/mmbr.00039-06 (2007).Article CAS PubMed PubMed Central Google Scholar Chettri, D. & Verma, A. K. Biological significance of carbohydrate active enzymes and searching their inhibitors for therapeutic applications. Carbohydr. Res. 529, 108853 (2023).Article CAS PubMed Google Scholar Download referencesFundingThe Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program (KGM1252511) supported this study. This research is funded by Funds for Science and Technology Development of the University of Danang under Project Number B2023-DN02-19.Author informationAuthors and AffiliationsBiological Resource Center/Korean Collection for Type Cultures (KCTC), Korea Research Institute of Bioscience and Biotechnology, Jeongeup, Jeonbuk, 56212, Republic of South KoreaNeak Muhammad & Song-Gun KimDepartment of Environmental Biotechnology, KRIBB School, University of Science and Technology (UST), Daejeon, 34113, Republic of South KoreaNeak Muhammad & Song-Gun KimGeneStory JSC, Hanoi, VietnamTien Q. VuongThe University of Danang, University of Science and Technology, Da Nang, VietnamHo Le HanAuthorsNeak MuhammadView author publicationsSearch author on:PubMed Google ScholarTien Q. VuongView author publicationsSearch author on:PubMed Google ScholarHo Le HanView author publicationsSearch author on:PubMed Google ScholarSong-Gun KimView author publicationsSearch author on:PubMed Google ScholarContributionsN.M. performed experiments of isolation, identification, and characterization of the bacterial strains including polar lipids, Whole-genome sequencing, physiological characteristics, and genome analysis. N.M also wrote the manuscript. T.Q.V did Whole-genome assemble, analyzed genomes, constructed a UBGC genome tree. H.L.H carried out fatty acid analysis, genome analysis for RAST subsystem, and wrote the paragraphs regarding antibiotics resistance, stress response and conclusions. S-G.K. supervised the experiments and finalized the manuscript. All authors reviewed the manuscript.Corresponding authorsCorrespondence to Ho Le Han or Song-Gun Kim.Ethics declarationsCompeting interestsThe authors declare no competing interests.Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary InformationSupplementary Information.Rights and permissionsOpen Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.Reprints and permissionsAbout this article