Skip to main content
NCBI home page
MicrobiologyOpen logoLink to MicrobiologyOpen
. 2026 Feb 19;15(1):e70239. doi: 10.1002/mbo3.70239

Genome Analysis Reveals Diversity and Functional Potential of Novel Janthinobacterium Species From Subarctic Soils

Anil Kumar 1,2, Minna K Männistö 3, Lee J Kerkhof 2, Max M Häggblom 1,✉
PMCID: PMC12917689  PMID: 41711050

ABSTRACT

The Arctic tundra and boreal forest regions are affected by ongoing climate change, leading to increased warming, increased plant production, and heightened microbial activity. Microbes play a key role in carbon release from stored soil organic matter, and characterizing their diversity and function in high‐latitude soils is thus of significant interest. The Pseudomonadota are abundant and diverse members of high‐latitude soils. Here, we describe two novel species of the genus Janthinobacterium, of the order Burkholderiales, isolated from tundra heath and northern boreal forest soils. The isolates are aerobic, chemoorganotrophic psychrophiles and are well‐adapted to the subarctic climate conditions. Phylogenomic analyses and ANI values confirmed the novelty of the strains, designated as Janthinobacterium silvisoli sp. nov. K2Li3 and Janthinobacterium saanense sp. nov. S3T4. Genome analysis revealed that the new species have the metabolic potential for degradation of complex carbon and polyphenols, which are abundant in tundra heath and lichen‐dominated, nutrient‐poor forest soils. The strains are well‐adapted to nitrogen‐limited soil ecosystems and can scavenge nitrogen from both organic and inorganic sources. Additionally, the strains harbor secondary metabolite gene clusters that encode antimicrobial compound production, potentially enhancing their competitiveness in the subarctic environment. The comparative pangenome analysis indicated that the strains have unique gene clusters for carbohydrate transport and metabolism, and energy generation and conservation. The genome‐based functional exploration enhances our understanding of this genus and how environmental conditions may shape the functionality and interactions of Janthinobacterium species in subarctic soil ecosystems.

Keywords: cold‐adapted, novel species, subarctic ecosystem

The Pseudomonadota are abundant and diverse members of high‐latitude soils. Here, we describe two novel species, Janthinobacterium silvisoli and Janthinobacterium saanense, of the order Burkholderiales, isolated from tundra heath and northern boreal forest soils. The isolates are aerobic, chemoorganotrophic psychrophiles and are well‐adapted to the subarctic climate conditions. Genome analysis elucidated their potential roles in carbon degradation and the release of stored carbon from subarctic tundra and forest soils.

graphic file with name MBO3-15-e70239-g002.jpg

1. Introduction

The Arctic is warming at a rapid rate due to global climate change, which increases the air temperature considerably, and it is expected that the warming rate will be up to four times more than the global mean temperature in the coming years (Stroeve et al. 2025). In many regions, such as Fennoscandia, the climate is warming, especially during winter months (Mikkonen et al. 2015), and in general, precipitation in the form of rain instead of snow is expected to increase (Mikkonen et al. 2015; Bintanja and Andry 2017). The Fennoscandian part of the Arctic region, which includes the Scandinavian Peninsula (Norway and Sweden) and Finland, is experiencing climate change‐driven alteration in the vegetation structure and nutrient dynamics. The rise in temperatures, increased rainfall, and a longer growing season are facilitating the northward extension of shrubs and tree species, leading to changes in ecosystem composition and functioning (Elmendorf et al. 2012; Bjorkman et al. 2018; Stark et al. 2023; Maliniemi et al. 2025). Changes in vegetation can affect both the quality and amount of organic matter that enters soils, leading to subsequent impacts on the diversity and abundance of microbial communities, carbon cycling processes, and the availability of nutrients (Vozzo et al. 2025). Moreover, variations in snow cover and the soil freeze–thaw dynamics are affecting microbial activity and the rates of nutrient mineralization (Sorensen et al. 2018; L. Liu et al. 2023). The ecological responses of microbial communities in this area appear to be strongly connected to the evolving interactions among plants, soil, and microbes. Therefore, understanding the behavioral and ecological roles of microbial species in the climate‐changing Fennoscandian environment is of utmost importance.

The Arctic tundra and forest soils are composed of diverse bacterial communities primarily from the phyla Pseudomonadota, Actinomycetota, Bacteroidota, Acidobacteriota, and Verrucomicrobiota (Malard et al. 2019). Within these phyla, Pseudomonadota comprises approximately 25%–30% of the overall bacterial abundance (Wong et al. 2023; Männistö et al. 2024). Members of the Pseudomonadota include phototrophs, heterotrophs, and lithotrophs, and they play vital roles in nutrient cycling, carbon and nitrogen fixation, and the breakdown of organic matter (Kersters et al. 2001; Degli Esposti 2018). The genus Janthinobacterium of the family Oxalobacteraceae within the Pseudomonadota, consists of aerobic, motile, rod‐shaped, chemoorganotrophic, and psychrotolerant organisms. The genus currently comprises 26 species, of which 23 have validly published names (Parte et al. 2020; https://lpsn.dsmz.de/). Janthinobacterium species have been isolated and described from various locations, including glacier ice, aquatic habitats (Ambrožič Avguštin et al. 2013; Gong et al. 2017; Lu et al. 2020; Inan et al. 2023; Park et al. 2023; Yang et al. 2026), trout (Jung et al. 2021), diseased mushrooms (Lincoln et al. 1999), soils (Shoemaker et al. 2015; Wu et al. 2017), and sediments (McTaggart et al. 2015), indicating a diverse distribution.

Janthinobacterium spp. are mostly chemoorganotrophic, which suggests that they are actively involved in the degradation of organic matter (Gillis and De Ley 2006). Most of these strains also synthesize violacein and other pigments that have antiparasitic, antimicrobial, and antioxidant properties (Wu et al. 2021). Moreover, they are psychrotolerant organisms and are commonly found in cold environments (Ambrožič Avguštin et al. 2013; Kumar et al. 2018; Rajawat et al. 2019; Yang et al. 2026). Despite their chemoorganotrophic and psychrotolerant nature, they are understudied in Fennoscandian soils, and little is known about their ecological function and diversity. The current study reports on five new Janthinobacterium strains belonging to two new species of the genus that were isolated from Fennoscandian tundra heath and forest soils. Genome‐based functional analysis was done to examine the metabolic potential and ecological functions of these strains. Moreover, to gain insight into the ecological significance of the Fennoscandian strains, a pangenome comparative analysis was performed with other Janthinobacterium strains isolated from different habitats. The study aims to extend the knowledge about the diversity and functional differences of Janthinobacterium strains in subarctic tundra heath and boreal forest soils.

2. Materials and Methods

2.1. Strain Isolation

Janthinobacterium strains were isolated from soil samples obtained from two ecosystem types: Arctic–alpine tundra soils from Mt. Saana, Kilpisjärvi (69°01′ N, 20°50′ E), and forest soil from an oligotrophic lichen‐dominated Scots pine forest located in Kätkäsuvanto (68°08′ N, 23°21′ E) in Finnish Lapland. Sample collection and isolation are described in more detail by Männistö and Häggblom (2006). Strains K2Li3, K2E3, and K2C7 originated from the Scots pine forest. Soil was sampled in September 2001 from fenced enclosures that have prevented reindeer grazing, and the ground vegetation is dominated almost exclusively by a dense mat of Cladonia stellaris lichen (Stark et al. 2010). Strains S3M3 and S3T4 were isolated from tundra soil samples collected in August 2001 from an altitude of 960 m on Mt. Saana, Kilpisjärvi (Männistö and Häggblom 2006). As the aim was to isolate a diverse collection of bacterial strains, several media were used for isolation. Strains K2Li3, K2C7, and S3T4 were isolated on media containing lichenin, cellulose, or starch as carbon sources, respectively, while strains S3M3 and K2E3 were isolated on media containing moss extract or a combination of soil, moss, and lichen extracts, respectively. The media are described in detail in Männistö and Häggblom (2006). After isolation, the strains were maintained on R2A agar (pH 7.0).

2.2. Phenotypic and Fatty Acid Methyl Ester Analysis

The utilization of different carbon sources by the novel Janthinobacterium spp. was tested using Biolog PM1 plates (Biolog Inc., Hayward, CA). After inoculation, the Biolog plates were incubated at 20°C for 7 days, and growth was determined by measuring optical density at 600 nm and by observing the dye color change. The temperature growth profile was determined by growing the isolates on R2A (Dfico) agar plates (pH 6) for 2 weeks at 4°C–34°C. The pH growth profile was determined by growing the isolates in GY (50 gL‐1 glucose, 10 gL‐1 yeast extract) medium broth at a pH range of 4–10 (in 0.5 pH unit increments) in 96‐well plates.

The total fatty acids were extracted and methylated from the bacterial isolates grown on R2A agar plates (pH 6) at 20°C using a previously described method (Männistö and Häggblom 2006). The fatty acid methyl esters were separated by an Agilent 6890 Series Gas Chromatography System equipped with an HP‐5MS column with helium as the carrier gas and analyzed using a 5973 Mass Selective Detector (Santa Clara, CA). Fatty acid methyl esters were identified by their retention times (Equivalent chain length, ECL, values) and mass spectra.

2.3. Genome Sequencing and Assembly Generation

The genomes of the five Janthinobacterium strains from the subarctic soils (K2Li3, S3T4, K2C7, K2E3, and S3M3) were previously sequenced by the US Department of Energy Joint Genome Institute (Genomic Sequencing of Core and Pangenomes of Soil and Plant‐associated Prokaryotes) using an Illumina NovaSeq S4 sequencer, and assembled using SPAdes v3.13.0 assembler, with the draft genomes available in the JGI Genome Portal (Table S1). Strains S3T4 and K2Li3 were resequenced to close the genome assemblies. The DNA from the bacterial isolates was extracted using the DNeasy UltraClean Microbial Kit (Qiagen) following the manufacturer's protocol. The genomic library for strains S3T4 and K2Li3 was prepared using the MinION Rapid Sequencing Kit (SQK‐RAD004) and sequenced on a MinION‐Mk1C with an R9.4 flow cell. The raw pod5 reads generated from the MinION sequencer were basecalled and demultiplexed in high accuracy mode using Dorado basecaller v0.4.3. The genome assembly using MinION reads for strains K2Li3 and S3T4 was constructed using the Trycycler tool v0.5.4 (Wick et al. 2021) by employing Flye v2.9.3 (Kolmogorov et al. 2019), Minipolish v0.1.3 (Wick and Holt 2021), and Raven v1.8.3 (Vaser and Šikić 2021) assemblers at default settings. The assemblies were further polished using Medaka v1.11.1, Polypolish v0.5.0 (Wick and Holt 2022), and POLCA tool v4.1.0 (Zimin and Salzberg 2020) using Illumina short‐read sequences of the isolate genomes available via the JGI Genome Portal (Table S1). The assembly quality was determined by using CheckM v1.2.2 (Parks et al. 2015) and QUAST tools v5.2.0 (Gurevich et al. 2013).

2.4. Genome Analysis

The genome assemblies of the tundra and forest soil Janthinobacterium strains were analyzed using the DRAM v1.5 tool (Shaffer et al. 2020) to gain insight into the metabolic functions carried out by the strains. Further, the secondary metabolites encoded by the strains were predicted using the antiSMASH v7 (Blin et al. 2023), and the polyphenol degradation ability was assessed using the CAMPER tool (McGivern et al. 2024). The nitrogen and sulfur cycling genes in the genome were predicted by the NCycDB (Tu et al. 2019) and SCycDB (Yu et al. 2021) databases, respectively. Further, the additional annotation of the subarctic Janthinobacterium genomes was performed using the Bacterial and Viral Bioinformatics Resource Center (BV‐BRC) online platform (Olson et al. 2023). The carbohydrate degradation potential of the Janthinobacterium strains was evaluated by employing the dbCAN3 server (Zheng et al. 2023).

2.5. Phylogenetic, Phylogenomic, and Pangenome Analysis

The 16S ribosomal RNA (rRNA) gene sequence was extracted from the genome assemblies of the strains using the Barrnap v0.9 tool, aligned with other Janthinobacterium species, and a maximum likelihood phylogenetic tree was constructed using MEGA‐11 (Tamura et al. 2021) with 1000 bootstrap replications. The Phylogenomics tree was prepared using UBCG v3 (Na et al. 2018) and the RAxML tools (Stamatakis 2014). The average nucleotide identity (ANI) values were calculated using the OrthoANI tool (Yoon et al. 2017).

The pangenome analysis of the subarctic isolates was performed by comparing them with other publicly available Janthinobacterium strains (complete or contig‐level) from different environments using the anvi'o v8 tool (Eren et al. 2021), following a previous method (Delmont and Eren 2018). A contig database of all the strains was constructed and annotated with COGs, KEGG, tRNA‐scan, and single‐copy core gene (SCG)‐taxonomy databases. The pangenome was calculated by employing NCBI‐BLAST and Markov Cluster algorithm (Van Dongen and Abreu‐Goodger 2012) at an inflation value of 6. Further, the core and unique genes in the strains were evaluated using the anvi‐compute‐functional‐enrichment‐in‐pan command.

3. Results and Discussion

3.1. Novel Janthinobacterium Species From Tundra and High‐Latitude Forest Soil

Janthinobacterium strains were isolated from tundra heath and boreal forest soil samples using different carbon substrate combinations (Männistö and Häggblom 2006). Initial analysis of partial 16S rRNA sequences indicated that these were members of the genus Janthinobacterium (Figure S1). The genomes of the subarctic Janthinobacterium strains (K2Li3, S3T4, K2C7, K2E3, and S3M3) were sequenced previously using an Illumina NovaSeq S4 sequencer and assembled using SPAdes v3.13.0 assembler. The Illumina‐based assemblies were not complete (assembly quality and statistics are given in Table S2). Following the phylogenetic analysis, one representative strain from each group (K2Li3 and S3T4) was resequenced using the Oxford Minion, and the complete closed genomes of both strains were assembled (Table S2). The nanopore‐based genome sequences enabled complete circular genome assembly of the Janthinobacterium strains S3T4 and K2Li3, with completeness of 98.73% and 98.45% and contamination of 5.01% and 3.32% at the genus level, respectively.

A phylogenomic tree comparing the subarctic strains with other members of the Janthinobacterium genus is presented in Figure 1. The tree shows the separation of the subarctic strains into two new groups, separate from other described species of the genus Janthinobacterium. Strains K2Li3, K2C7, and K2E3 from forest soil form one cluster, while strains S3T4 and S3M3 from tundra soil form the other. A phylogenomic tree of the subarctic strains and all strains of the Janthinobacterium genus with available genomes is shown in Figure S2. The calculated ANI values between the described Janthinobacterium species and strains K2Li3 and S3T4 were below the threshold value used for species delineation (Figure S3). The combined phylogenomic and ANI analysis clearly indicates that strains K2Li3, K2C7 and K2E3, and S3T4 and S3M3, respectively, represent two novel species of the Janthinobacterium genus. Here we describe two novel species of the genus Janthinobacterium with their respective type strains, for which we propose the names Janthinobacterium silvisoli sp. nov. (strains K2Li3T, K2E7, and K2C7) and Janthinobacterium saanense sp. nov. (strains S3T4T and S3M3).

Figure 1.

Figure 1

Open in a new tab

Maximum likelihood phylogenomics tree of the subarctic isolates and type strains of described Janthinobacterium species. The tree was prepared with the UBCG v3 tool (by taking 92 core genes) employing RAxML with bootstrap values of 1000 replications, shown at the branch point. Values below 50 are not shown. Burkholderia cepacia BC16 was used as an outgroup. The scale bar corresponds to the number of nucleotide substitutions per site.

3.2. Phenotypic Characteristics of Janthinobacterium Isolates

The different carbon sources utilized by the novel Janthinobacterium isolates are listed in Table S3. The strains were able to utilize l‐arabinose, d‐galactose, d‐trehalose, d‐xylose, d‐ribose, d‐fructose, α‐d‐glucose, maltose, sucrose, maltotriose, l‐galactonic, acid‐γ‐lactone, and d‐galacturonic acid. The isolates grew at a pH range of 6–9 and a temperature range of 4°C–35°C. Cellular fatty acid composition analysis after growth on R2A agar at 20°C indicated that C16:0, C17:1 ω10c, C16:1 ω7c, C12:0, and C10:0 3‐OH were the main fatty acids present in the K2Li3 and S3T4 strains, which were also observed in the other described Janthinobacterium species (Table S4).

3.3. Novel Janthinobacterium Strains Are Complex Carbon and Polyphenol Degraders

The novel Janthinobacterium isolates were evaluated for their carbohydrate degradation ability using the dbCAN3 tool. The analysis of the genomes showed that tundra and forest Janthinobacterium species have the potential for degradation of a wide range of complex carbohydrates, such as exopolysaccharides, lignin, peptidoglycan, starch, xylan, cellulose, chitin, chitosan, and pectin (Figure 2A). Subarctic Fennoscandian soils contain a vast pool of organic carbon that is composed of carbohydrates, phenols, carboxylic acids, and peptides (Frossard et al. 2021). Most of this carbon pool originates from plant litter in the form of cellulose, hemicellulose, and pectin (Pushkareva et al. 2020). Previously, the psychrotolerant heterotrophic Janthinobacterium strains isolated from the subarctic sites showed cellulose hydrolytic ability (Männistö and Häggblom 2006). In another study, members of the phylum Pseudomonadota were found active in the degradation of complex carbon, such as cellulose, pectin, chitin, and lignin, in alpine peatland (Yan et al. 2022). The novel Janthinobacterium isolates show the potential for breakdown of these complex carbohydrates, which may account for their distribution in these soils and their role in carbon cycling. Moreover, there was a difference in the abundance/distribution of CAZymes between the Janthinobacterium strains based on their source of isolation, suggesting a link between microbial functional potential and environmental origin. Strains isolated from forest soils exhibited a greater number of pectin‐degrading enzymes compared with those from tundra soils, likely reflecting adaptation to the differing input of organics in these environments. The higher pectinase content in forest‐derived strains is consistent with the greater abundance of pectin‐rich plant material in forest ecosystems, whereas the relatively sparse vegetation in tundra soils may result in lower selective pressure for pectin degradation. These findings suggest that local vegetation and soil composition play an important role in shaping the enzymatic repertoire of soil‐dwelling microorganisms.

Figure 2.

Figure 2

Open in a new tab

Carbohydrate degradation (A) and polyphenol degradation (B) potential of novel Janthinobacterium isolates. The carbohydrate degradation potential of the isolates was determined using the dbCAN3 server, while the polyphenol degradation ability was predicted using the CAMPER tool. The heatmap's gradient values indicate gene copy number.

The subarctic tundra and forest ecosystems are dominated by ericaceous shrubs and other vegetation that are a rich source of phenolic compounds (Eskelinen et al. 2009). The understory vegetation in the coniferous forest site was dominated by the ericaceous shrub Empetrum nigrum and C. stellaris lichen, which produce polyphenol‐rich litter and secondary metabolites (Tybirk et al. 2000; Stark et al. 2007), which may either support or inhibit the soil microbiota. Therefore, Janthinobacterium species were evaluated for polyphenol degradation ability. The analysis shows that the Janthinobacterium strains have the potential for hydrolysis of a variety of polyphenols, such as phenylacetic acid, caffeic acid, ethylbenzene, toluene, naringenin, quercetin, curcumin, catechol, phloroglucinol, and homoprotocatechuic acid (Figure 2B). Earlier studies suggest that the subarctic shrubs Betula nana, E. nigrum, and Salix arctica synthesize phenolic compounds, including catechin, naringenin, quercetin, and catechol (Hansen et al. 2006; Deslippe and Simard 2011; Väisänen et al. 2013; Curtasu and Nørskov 2024). The abundance of polyphenols in the subarctic heath soils likely drives the prevalence of genes encoding polyphenol degradation in Janthinobacterium species. There were differences in the abundance of different polyphenol‐degrading enzymes between the forest and tundra Janthinobacterium strains (Figure 2B). Janthinobacterium strains from forest sites (K2Li3, K2E7, and K2C7) showed higher abundance/distribution of toluene, phloroglucinol, naringenin, catechol, and 4‐methylcatechol‐degrading enzymes. In contrast, the tundra strains (S3T4 and S3M3) showed a higher occurrence of curcumin and pinoresinol‐degrading enzymes. Polyphenols such as catechol and 4‐methylcatechol have been reported in previous studies where they were synthesized and released into soil by native plant communities found in boreal forests (Komenda and Koppmann 2002; Hakola et al. 2017; Purser et al. 2021). The differential abundance of polyphenol‐degrading enzymes among Janthinobacterium strains isolated from forest and tundra environments suggests a strong influence of local environmental conditions and available organic substrates on microbial functional potential. This discrepancy highlights potential unknown metabolic pathways or substrate analogs in subarctic environments and underscores the need for further chemical and ecological characterization of soil organic matter. Overall, these findings suggest that the habitat‐specific chemical landscapes shape the selection of particular strains/species and emphasize the importance of integrating microbial and environmental data in ecosystem studies.

3.4. Novel Janthinobacterium Isolates Harbor Stress Response Proteins and Varied Energy‐Generation Strategies

The cold, harsh subarctic ecosystem affects the growth and survival of organisms. Microbes adopt several ways to endure and survive in such conditions. The Janthinobacterium strains in the current study harbor genes for cold, heat, osmotic, and oxidative‐stress responses (Figure 3A). Genes for cold and heat‐shock proteins protect bacterial cells from temperature fluctuations (Zhang and Gross 2021). Moreover, choline uptake, betaine synthesis clusters, and EnvZ and OmpR regulons were observed, which can protect cells from osmotic stress (Sleator and Hill 2002). The potential for biosynthesis of glutathione and other proteins that protect cells from reactive oxygen species was also observed. In addition to stress response proteins, the isolates harbor genes for proteins and enzymes required for DNA damage repair (Figure 3A). The Janthinobacterium isolates possess response proteins that suggest they can survive in the subarctic ecosystem, characterized by nutrient‐limited and cold conditions with periodic temperature fluctuations.

Figure 3.

Figure 3

Open in a new tab

Stress response proteins (A) and energy generation pathways (B) identified in Janthinobacterium strains.

The novel Janthinobacterium isolates appear to adopt several strategies for energy generation in the extreme subarctic habitat. In addition to the central carbon metabolism pathways including glycolysis, TCA cycle, and pentose phosphate pathways, alternative pathways like an anaerobic module of the TCA, Entner–Doudoroff pathway, glycolate, glyoxylate interconversions, gluconeogenesis, and so forth, were present in the genome (Figure 3B). The fermentation routes for energy generation, such as acetoin, butanediol metabolism, lactate, and mixed acid fermentation, were observed in the genomes. The presence of diverse energy‐generating pathways in the genomes suggests that the strains do not depend solely on central carbon metabolism pathways for energy for growth and survival. In a previous study, examining the effect of freeze–thaw cycles on tundra soil bacteria (Männistö et al. 2009) Janthinobacterium/Herbaspirillum spp. were found in high relative abundance in the rRNA‐derived community profiles. These declined in relative abundance during laboratory microcosm incubation and appear to be quite transient. From these data, we concluded that Janthinobacterium spp. represent copiotrophic bacteria with fast turnover of their biomass/ribosomes. Combined, these data further underscore the adaptability and growth strategies of Janthinobacterium species in the subarctic ecosystem.

3.5. Janthinobacterium Isolates Show Potential for Growth in Nitrogen and Sulfur‐Deficient Tundra and Forest Soil

Subarctic soils have low nitrogen content, which limits microbial growth (X. Y. Liu et al. 2018; Stark et al. 2023). Microbes adapt in different ways to nitrogen‐limited conditions, such as increasing inorganic nitrogen uptake and utilization efficiency or using alternative nitrogen sources (Geisseler et al. 2010). Hence, the nitrogen metabolism pathways in the novel Janthinobacterium isolates were explored. The NCyc database analysis showed diverse nitrogen uptake and metabolism mechanisms in the subarctic isolates (Table 1). The strains showed the potential to scavenge nitrogen from organic matter through degradation or from inorganic compounds, such as nitrates. The Janthinobacterium strains harbored genes responsible for organic nitrogen degradation (ansB, asnB, gdh, glnA, glsA, gs_K00265, and gs_K00266), indicating that nitrogen can be assimilated through the breakdown of organic compounds. Moreover, genes for urea metabolism (ureA, ureB, and ureC) were present, releasing nitrogen as ammonia, which can be utilized by microbes. Further, the assimilatory nitrate reduction genes (narB, nasA, and NAD(P)H nitrate reductase) were detected, suggesting inorganic nitrogen utilization by the Janthinobacterium isolates. The denitrification pathways were incomplete, suggesting Janthinobacterium species are not actively involved in releasing nitrogen from the tundra and forest soils. Nitrogen fixation genes were not observed in the strains, suggesting the strains were not involved in nitrogen fixation in the subarctic soils. The analysis suggests that Janthinobacterium isolates can obtain nitrogen from both organic and inorganic sources, supporting their growth in nitrogen‐poor subarctic soils.

Table 1.

Marker genes identified for nitrogen metabolism across subarctic Janthinobacterium strains utilizing the NCyc database.

Strains
Marker genes and functions Janthinobacterium saanense S3T4 J. saanense S3M3 Janthinobacterium silvisoli K2Li3 J. silvisoli K2E3 J. silvisoli K2C7
Organic degradation and synthesis
ansB Glutamin‐(asparagin‐)ase 1 2 2 2 2
asnB Glutamin‐(asparagin‐)ase 2 2 2 2 2
gdh_K00261 Glutamate dehydrogenase (NAD(P)+) 2 2 2 2 2
gdh_K00262 Glutamate dehydrogenase (NADP + ) 1 1 2 2 2
gdh_K15371 Glutamate dehydrogenase 2 2 2 2 2
glnA Glutamine synthetase 7 7 10 10 9
glsA Glutaminase 2 2 2 2 2
gs_K00265 Glutamate synthase (NADPH/NADH) large chain 1 1 1 1 1
gs_K00266 Glutamate synthase (NADPH/NADH) small chain 3 3 3 3 3
nmo Nitronate monooxygenase 6 5 5 4 5
ureA Urease subunit gamma 1 1 1 1 1
ureB Urease subunit beta 1 1 1 1 1
ureC Urease subunit alpha 2 0 2 2 2
Denitrification
napA Periplasmic nitrate reductase NapA 1 1 0 0 0
narJ Nitrate reductase molybdenum cofactor assembly chaperone 2 2 2 1 2
nirB Nitrite reductase (NADH) large subunit 2 2 3 3 3
nirD Nitrite reductase (NADH) small subunit 2 2 2 2 2
nirK Nitrite reductase (NO‐forming) 2 1 1 1 1
nosZ Nitrous‐oxide reductase 0 1 1 1 0
nrfC Protein NrfC 1 1 1 1 1
Assimilatory nitrate reduction
narB Assimilatory nitrate reductase 1 1 1 1 1
nasA Assimilatory nitrate reductase catalytic subunit 2 2 2 2 2
NR Nitrate reductase (NAD(P)H) 3 3 4 4 4
Open in a new tab

Note: The genes for nitrification (amoA, amoB, amoC, hao, nxrA, and nxrB), denitrification (napB, napC, narG, narH, narI, nirS, norB, norC, narZ, narY, narV, and narW), assimilatory nitrate reduction (nasB, nirA, and narC), nitrogen fixation (anfG, nifD, nifH, nifK, and nifW), and anammox (hzo, hzsA, hzsB, hzsC, and hdh) were not found in the strains.

The subarctic tundra and forest soils remain frozen for most of the year, limiting nutrient availability in the soil; therefore, the sulfur assimilation pathways were also explored. The SCyc database analysis suggested diverse pathways for sulfur uptake and usage in Janthinobacterium isolates (Table S5). The genes for the assimilatory sulfate reduction pathway were prominent in the Janthinobacterium isolates, suggesting efficient sulfate utilization for biosynthesis and supporting growth in sulfur‐limited environments. The dissimilatory sulfur reduction and oxidation pathway was incomplete, suggesting that the isolates do not use sulfur for energy generation. The isolates have the potential to utilize inorganic and organic forms of sulfur and have transporters for sulfur acquisition. In summary, the isolates possess a variety of mechanisms for sulfur acquisition, enabling them to thrive in environments where sulfur is limited.

3.6. Genome Analysis of Janthinobacterium Strains Shows Their Potential for Bioactive Compound Synthesis and Antimicrobial Resistance

Microbes can synthesize secondary bioactive molecules that help them survive and grow in their natural environment (Davies and Ryan 2012). These metabolites can have antimicrobial activity, which inhibits the growth of other microbes, or may have some defense properties (Keswani et al. 2020). The Janthinobacterium isolates were explored for the presence of bioactive secondary metabolites using antiSMASH v7. The results showed that they have gene clusters for the synthesis of metabolites like Linear azole‐containing peptides (LAP), non‐alpha poly‐amino acids like e‐Polylysin (NAPAA), ribosomally synthesized and post‐translationally modified peptides (RiPP), Lanthipeptide‐class‐iv and terpene (Figure 4A). LAPs, NAPAA, and RiPP are a group of peptides with antimicrobial activity (Travin et al. 2019; Ongpipattanakul et al. 2022; Zhu et al. 2023). Most Janthinobacterium species are violet due to the production of violacein, an indole that has antimicrobial and antioxidative activities (Wu et al. 2021). The indole biosynthetic gene cluster was absent in subarctic Janthinobacterium isolates, so their colonies are not violet, but they do harbor gene clusters with potential for the synthesis of other secondary metabolites with potential antimicrobial activity. Gene clusters for the synthesis of antimicrobial compounds in the novel Janthinobacterium isolates suggest a role in their competitiveness with other organisms in the subarctic soils.

Figure 4.

Figure 4

Open in a new tab

Secondary metabolite gene clusters (A) and genes for antibiotic and toxic compound resistance (B) in subarctic tundra and forest Janthinobacterium strains.

Soil is the habitat for a diverse group of microbes that interact and compete for their survival and growth. Many microbes synthesize antimicrobial/antibiotic compounds to resist or inhibit other microbes in their habitat (Spagnolo et al. 2021). A range of antibiotics and resistance traits among Arctic microorganisms have been revealed (McCann et al. 2019; Fang et al. 2024). Therefore, the Janthinobacterium strains were examined for the presence of antimicrobial/antibiotic resistance genes in their genomes. The BV‐BRC annotation of the isolates shows potential resistance of the Janthinobacterium strains to diverse antimicrobial compounds (Figure 4B) that target vital cellular functions, such as cell wall and protein synthesis and transcription. The strains were also predicted to be resistant to antimicrobial/antibiotic compounds, such as fosfomycin, fusidic acid, mupirocin, daptomycin, triclosan, and tetracycline. These antimicrobial resistance traits may contribute to the proliferation and prevalence of the Janthinobacterium strain in subarctic environments.

3.7. Pangenome Comparison of Janthinobacterium Isolates Highlights Both Shared and Unique Genetic Traits

The tundra and forest soil Janthinobacterium strains were compared with other published and public genomes using Anvio. The pangenome analysis of the five subarctic isolates compared with 39 other Janthinobacterium species and strains revealed 27,228 gene clusters with 232,909 genes (Figure 5). There were 701 SCG clusters with 32,169 genes present in all genomes. The unique gene clusters in the Janthinobacterium isolates were explored to determine any differential functions performed by the isolates from subarctic soils. The evaluation of the unique gene clusters based on the COG category shows that they are involved in post‐translational modification, protein turnover, chaperones, energy production and conversion, signal transduction mechanisms, intracellular trafficking, secretion, and vesicular transport (Table 2). The COG functions for the unique gene clusters revealed proteins, such as carbohydrate‐selective porin, which facilitates the transport of carbohydrates across the cell membrane (Wylie and Worobec 1995), as well as thiol‐disulfide isomerase/thioredoxin that help in proper protein folding and maintain intracellular redox homeostasis (Anjou et al. 2024). Thioredoxin also helps in oxidative and nitrosative stress response, signal transduction, and regulating metabolism (Anjou et al. 2024). The unique gene cluster also encodes the cytochrome c biogenesis protein that helps in respiratory electron transport and metabolic pathways (Stevens et al. 2011). The AraC‐containing cupin protein superfamily was observed in the subarctic isolates that function in carbon metabolism and stress responses (Dunwell et al. 2000). Additionally, the unique gene clusters also encode adenylate cyclase that synthesizes cyclic AMP, which further controls cellular activities like carbon source utilization and stress responses (Donovan et al. 2013). The KOfam‐based functional annotation of the unique gene cluster revealed differential functions of the subarctic strains, such as a suppressor for copper‐sensitivity, polyamine oxidase, and high‐affinity Mn2+ porin. Previously, it has been shown that Arctic and subarctic regions have an abundance of copper ions (Skierszkan et al. 2024), and higher metal abundance causes slow litter degradation because of lower microbial growth due to metal toxicity (Sarneel et al. 2020). The presence of copper ion transporters in the novel Janthinobacterium strains would make them resistant to copper toxicity and which further supports their growth in these soils. Additionally, KEGG module‐based annotation of the unique gene clusters shows the presence of ceramide and sphingosine biosynthesis in Janthinobacterium strains. Ceramide and sphingosine have diverse physiological functions in bacteria, like inducing sporulation, bacteriophage protection, and predation (Stankeviciute et al. 2022). In summary, the novel Janthinobacterium isolates have unique gene clusters that may help in stress response, carbohydrate transport and metabolism, predation, as well as energy generation and conservation.

Figure 5.

Figure 5

Open in a new tab

Pangenome analysis of subarctic Janthinobacterium strains alongside other selected members of the genus isolated from various habitats. Comparison of gene clusters between the assembled subarctic soil isolate genomes and known Janthinbacterium spp. Each row designating a Janthinobacterium strain starts with information on the presence of gene clusters (gene clusters are marked by the darker‐colored regions within the row). This is followed by the columns indicating levels of genome total length, completion, singleton gene clusters, and number of gene clusters. The heatmap illustrates the average nucleotide identity (ANI) among the strains.

Table 2.

Unique gene clusters and their functions predicted by COG20 and KEGG modules in the subarctic Janthinobacterium isolates. The gene clusters include functions, such as stress response, carbohydrate transport and metabolism, predation, and energy generation and conservation.

Enrichment score Adjusted q value Accession Gene clusters IDs
COG20 function
Carbohydrate‐selective porin OprB 36.0 0.02 COG3659 GC_00006630, GC_00026065
Thiol‐disulfide isomerase or thioredoxin (TrxA), Cytochrome c biogenesis protein CcdA 36.0 0.02 COG0526!!!COG0785 GC_00006223
AraC‐type DNA‐binding domain and AraC‐containing proteins, Predicted enzyme of the cupin superfamily 25.1 0.27 COG2207!!!COG3450 GC_00007862
Adenylate cyclase, DNA‐binding transcriptional regulator DnrI/AfsR/EmbR 16.3 0.73 COG2114!!!COG3629!!!COG3899!!!COG3903 GC_00009837
COG20 category
Posttranslational modification, protein turnover, chaperones, energy production, and conversion 36.0 0.01 O!!!C!!!O GC_00006223
Signal transduction mechanisms, Transcription 16.3 0.65 T!!!K!!!R!!!R GC_00009837
Signal transduction mechanisms, intracellular trafficking, secretion, vesicular transport, and extracellular structures 10.3 1 T!!!U!!!W GC_00008188
KOfam
Suppressor for copper‐sensitivity B 44.0 0.01 K08344 GC_00006774
Polyamine oxidase [EC:1.5.3.17 1.5.3.‐] 44.0 0.01 K17839 GC_00006657
High‐affinity Mn2+ porin 36.0 0.01 K16080 GC_00006630, GC_00026065
KEGG module
Ceramide biosynthesis, Sphingosine biosynthesis 10.3 1 M00094!!!M00099 GC_00008169
Open in a new tab

The core and shared gene clusters and their functions were also explored among the Janthinobacterium strains. The shared gene functions include central carbon metabolism pathways, such as the TCA cycle, glycolysis, glyoxylate cycle, pentose phosphate pathway, Entner–Doudoroff pathway, and electron transport complexes (Figure S4). The genes for essential and aromatic amino acids biosynthesis, nucleotide biosynthesis, beta‐lactam and multidrug resistance, as well as NAD synthesis, were present in all the genomes. Additionally, the genes to synthesize compounds such as biotin, heme, isoprenoid, cobalamin, molybdenum cofactor, tetrahydrofolate, and ubiquinone were observed in all the Janthinobacterium strains. The necessary genes required for growth and metabolism, like carbon, nucleotide, and amino acid metabolism, coenzyme biosynthesis, were observed in the core genomes of Janthinobacterium strains, specifying their adaptability and abundance in different sites.

4. Conclusions

Climate change‐driven alteration in the vegetation structure and nutrient dynamics is affecting the quality and quantity of soil organic matter in tundra and boreal forest soil, leading to subsequent impacts on the diversity and abundance of microbial communities, carbon cycling processes, and the availability of nutrients. This study describes two new species of Janthinobacterium from subarctic tundra heath and boreal forest soils. The genome‐based functional analysis of these new species suggests that they play a role in degrading complex carbon and polyphenols. Additionally, the presence of stress response proteins in the genome indicates their potential for adaptation to the cold and harsh subarctic climate. The tundra heath and boreal forest soils are nitrogen‐limited, and to survive in these conditions, the Janthinobacterium strains show the potential to assimilate nitrogen from both organic and inorganic sources. These strains also show potential for resistance mechanisms to a variety of antibiotics and other toxic compounds present in the soil or released by other organisms. Furthermore, they harbor secondary metabolite gene clusters with potential antimicrobial activity, which may enhance their survival in these habitats. The comparative genome analysis indicated that they have unique gene clusters for stress responses, carbohydrate transport and metabolism, and energy generation and conservation. The genome‐based analysis of the Janthinobacterium species elucidated their potential roles in carbon degradation and the release of stored carbon from subarctic tundra and forest soils.

4.1. Description of J. saanense sp. nov

J. saanense (sa.a.nen'se. N.L. neut. adj. saanense pertaining to Mount Saana, Finland, from where the species was isolated).

Cells are Gram‐negative, nonmotile, aerobic rods. Colonies are white when grown on R2A agar. Growth occurs at 4°C–35°C and pH 6–9. The major cellular fatty acids are C16:0, C17:1 ω10c, C16:1 ω7c, C12:0, and C10:0 3‐OH. The DNA G + C content determined from the genome sequence of the type strain is 60.2%. The type strain is S3T4T (= DSMZ 120996 = HAMBI 3823) isolated from tundra soil on Mount Saana, Kilpisjärvi, Finland (69°01′ N, 20°50′ E). NCBI accession numbers for the 16S rRNA gene sequence of the type strain are PX226026, and the IMG Project ID for the genome assembly is Gp0453383.

4.2. Description of J. silvisoli sp. nov

J. silvisoli (sil.vi.so'li. L. fem. n. silva, forest; L. neut. n. solum, soil; N.L. gen. neut. n. silvisoli, of forest soil).

Cells are Gram‐negative, nonmotile, aerobic rods. Colonies are white when grown on R2A agar. Growth occurs at 4°C–35°C and pH 6–9. The major cellular fatty acids are C16:0, C17:1 ω10c, C16:1 ω7c, C12:0, and C10:0 3‐OH. The DNA G + C content determined from the genome sequence of the type strain is 59.72%. The type strain is K2Li3T (= DSMZ 121001 = HAMBI 3838) isolated from soil from an oligotrophic lichen‐dominated Scots pine forest located in Kätkäsuvanto (68°08′ N, 23°21′ E) in Finnish Lapland. NCBI accession numbers for the 16S rRNA gene sequence of the type strain PX226025 and the IMG Project ID for the genome assembly are Gp0453385.

Author Contributions

Anil Kumar: conceptualization, methodology, investigation, formal analysis, data curation, visualization, writing – review and editing. Minna Männistö: conceptualization, methodology, investigation, review and editing, project administration, resources. Lee J. Kerkhof: investigation, supervision, review and editing, resources. Max M. Häggblom: conceptualization, review and editing, supervision, project administration, resources.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

None declared.

Supporting information

Kumar et al_Janthinobacterium_Supplementary Data.

MBO3-15-e70239-s001.pdf (1.3MB, pdf)

Acknowledgments

We thank Kristina Chew, Serena Connolly, and Aharon Oren for assistance and suggestions with nomenclature. We thank Marika Pätsi and Sirkka Aakkonen for their help in cultivating the strains. This study was funded in part by the US National Science Foundation (Award Number 2129351) to M.M.H. and L.J.K., the Research Council of Finland (Decision Numbers 130507 and 310776) to M.K.M., and the USDA‐NIFA Hatch Accession Number 7004814 to M.M.H. Illumina sequencing of the Janthinobacterium strains was done through the Community Science Program (CSP) of the US Department of Energy Joint Genomes Institute (Genomic Sequencing of Core and Pangenomes of Soil and Plant‐associated Prokaryotes; PI William B. Whitman).

Data Availability Statement

Type strains are deposited in the German Collection of Microorganisms and Cell Cultures (DSMZ) and the University of Helsinki HAMBI Culture Collection. IMG Taxon IDs and NCBI accession numbers for the newly assembled Janthinobacterium genomes are J. silvisoli K2Li3, 2849242232, GCA_014200695.1 (Project ID Gp0453385); J. silvisoli K2C7, 2849236846, GCA_014200685.1; J. silvisoli K2E3, 2849247614, GCA_014200725.1; J. saanense S3T4, 2849231242, GCA_014200675.1 (Project ID Gp0453383); and J. saanense S3M3, 284922563 GCA_014200645.15. Accession numbers for 16S rRNA genes are J. silvisoli K2Li3, PX226025; J. silvisoli K2C7, NZ_JACHCJ010000019; J. silvisoli K2E3, NZ_JACHCL010000016; J. saanense S3T4, PX226026; and J. saanense S3M3, NZ_JACHCH010000008.

References

  1. Ambrožič Avguštin, J. , Žgur Bertok D., Kostanjšek R., and Avguštin G.. 2013. “Isolation and Characterization of a Novel Violacein‐Like Pigment Producing Psychrotrophic Bacterial Species Janthinobacterium svalbardensis sp. nov.” Antonie Van Leeuwenhoek 103: 763–769. [DOI] [PubMed] [Google Scholar]
  2. Anjou, C. , Lotoux A., Morvan C., and Martin‐Verstraete I.. 2024. “From Ubiquity to Specificity: The Diverse Functions of Bacterial Thioredoxin Systems.” Environmental Microbiology 26: e16668. [DOI] [PubMed] [Google Scholar]
  3. Bintanja, R. , and Andry O.. 2017. “Towards a Rain‐Dominated Arctic.” Nature Climate Change 7: 263–267. [Google Scholar]
  4. Bjorkman, A. D. , Myers‐Smith I. H., Elmendorf S. C., et al. 2018. “Plant Functional Trait Change Across a Warming Tundra Biome.” Nature 562: 57–62. [DOI] [PubMed] [Google Scholar]
  5. Blin, K. , Shaw S., Augustijn H. E., et al. 2023. “AntiSMASH 7.0: New and Improved Predictions for Detection, Regulation, Chemical Structures and Visualisation.” Nucleic Acids Research 51: W46–W50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Curtasu, M. V. , and Nørskov N. P.. 2024. “Quantitative Distribution of Flavan‐3‐ols, Procyanidins, Flavonols, Flavanone and Salicylic Acid in Five Varieties of Organic Winter Dormant Salix spp. by LC‐MS/MS.” Heliyon 10: e25129. 10.1016/j.heliyon.2024.e25129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Davies, J. , and Ryan K. S.. 2012. “Introducing the Parvome: Bioactive Compounds in the Microbial World.” ACS Chemical Biology 7: 252–259. [DOI] [PubMed] [Google Scholar]
  8. Degli Esposti, M. 2018. “Proteobacteria: From Anaerobic to Aerobic Organisms.” In Phylogeny and Evolution of Bacteria and Mitochondria, edited by Degli Esposti M., 69–104. CRC Press. [Google Scholar]
  9. Delmont, T. O. , and Eren A. M.. 2018. “Linking Pangenomes and Metagenomes: The Prochlorococcus Metapangenome.” PeerJ 6: e4320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Deslippe, J. R. , and Simard S. W.. 2011. “Below‐Ground Carbon Transfer Among Betula nana May Increase With Warming in Arctic Tundra.” New Phytologist 192: 689–698. [DOI] [PubMed] [Google Scholar]
  11. Donovan, G. T. , Norton J. P., Bower J. M., and Mulvey M. A.. 2013. “Adenylate Cyclase and the Cyclic AMP Receptor Protein Modulate Stress Resistance and Virulence Capacity of Uropathogenic Escherichia coli .” Infection and Immunity 81: 249–258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dunwell, J. M. , Khuri S., and Gane P. J.. 2000. “Microbial Relatives of the Seed Storage Proteins of Higher Plants: Conservation of Structure and Diversification of Function During Evolution of the Cupin Superfamily.” Microbiology and Molecular Biology Reviews 64: 153–179. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Elmendorf, S. C. , Henry G. H. R., Hollister R. D., et al. 2012. “Global Assessment of Experimental Climate Warming on Tundra Vegetation: Heterogeneity Over Space and Time.” Ecology Letters 15: 164–175. [DOI] [PubMed] [Google Scholar]
  14. Eren, A. M. , Kiefl E., Shaiber A., et al. 2021. “Community‐Led, Integrated, Reproducible Multi‐Omics With Anvi'o.” Nature Microbiology 6: 3–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Eskelinen, A. , Stark S., and Männistö M.. 2009. “Links Between Plant Community Composition, Soil Organic Matter Quality and Microbial Communities in Contrasting Tundra Habitats.” Oecologia 161: 113–123. [DOI] [PubMed] [Google Scholar]
  16. Fang, X. M. , Li J., Wang N. F., Zhang T., and Yu L. Y.. 2024. “Metagenomics Uncovers Microbiome and Resistome in Soil and Reindeer Faeces From Ny‐Ålesund (Svalbard, High Arctic).” Environmental Research 262: 119788. [DOI] [PubMed] [Google Scholar]
  17. Frossard, A. , De Maeyer L., Adamczyk M., Svenning M., Verleyen E., and Frey B.. 2021. “Microbial Carbon Use and Associated Changes in Microbial Community Structure in High‐Arctic Tundra Soils Under Elevated Temperature.” Soil Biology and Biochemistry 162: 108419. [Google Scholar]
  18. Geisseler, D. , Horwath W. R., Joergensen R. G., and Ludwig B.. 2010. “Pathways of Nitrogen Utilization by Soil Microorganisms—A Review.” Soil Biology and Biochemistry 42: 2058–2067. [Google Scholar]
  19. Gillis, M. , and De Ley J.. 2006. “The Genera Chromobacterium and Janthinobacterium .” In The Prokaryotes, edited by Dworkin M., Falkow S., Rosenberg E., Schelifer K. H., and Stackebrandt E., 737–746. Springer. [Google Scholar]
  20. Gong, X. , Skrivergaard S., Korsgaard B. S., et al. 2017. “High Quality Draft Genome Sequence of Janthinobacterium psychrotolerans sp. nov., Isolated From a Frozen Freshwater Pond.” Standards in Genomic Sciences 12: 8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Gurevich, A. , Saveliev V., Vyahhi N., and Tesler G.. 2013. “QUAST: Quality Assessment Tool for Genome Assemblies.” Bioinformatics 29: 1072–1075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Hakola, H. , Tarvainen V., Praplan A. P., et al. 2017. “Terpenoid and Carbonyl Emissions From Norway Spruce in Finland During the Growing Season.” Atmospheric Chemistry and Physics 17: 3357–3370. [Google Scholar]
  23. Hansen, A. H. , Jonasson S., Michelsen A., and Julkunen‐Tiitto R.. 2006. “Long‐Term Experimental Warming, Shading and Nutrient Addition Affect the Concentration of Phenolic Compounds in Arctic‐Alpine Deciduous and Evergreen Dwarf Shrubs.” Oecologia 147: 1–11. [DOI] [PubMed] [Google Scholar]
  24. Inan Bektas, K. , Nalcaoglu A., Kati H., et al. 2023. “ Janthinobacterium kumbetense sp. nov., a Violacein‐Producing Bacterium Isolated From Spring Water in Turkey, and Investigation of Antimicrobial Activity of Violacein.” FEMS Microbiology Letters 370: fnac119. [DOI] [PubMed] [Google Scholar]
  25. Jung, W. J. , Kim S. W., Giri S. S., et al. 2021. “ Janthinobacterium tructae sp. nov., Isolated From Kidney of Rainbow Trout (Oncorhynchus mykiss).” Pathogens 10: 229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kersters, K. , Vos P. D., Gillis M., et al. 2001. “Proteobacteria.” Encyclopedia of Life Sciences. 10.1038/NPG.ELS.0000465. [DOI] [Google Scholar]
  27. Keswani, C. , Singh H. B., García‐Estrada C., et al. 2020. “Antimicrobial Secondary Metabolites From Agriculturally Important Bacteria as Next‐Generation Pesticides.” Applied Microbiology and Biotechnology 104: 1013–1034. [DOI] [PubMed] [Google Scholar]
  28. Kolmogorov, M. , Yuan J., Lin Y., and Pevzner P. A.. 2019. “Assembly of Long, Error‐Prone Reads Using Repeat Graphs.” Nature Biotechnology 37: 540–546. [DOI] [PubMed] [Google Scholar]
  29. Komenda, M. , and Koppmann R.. 2002. “Monoterpene Emissions From Scots Pine (Pinus sylvestris): Field Studies of Emission Rate Variabilities.” Journal of Geophysical Research: Atmospheres 107, no. D13: ACH 1‐1–ACH 1‐13. [Google Scholar]
  30. Kumar, R. , Acharya V., Singh D., and Kumar S.. 2018. “Strategies for High‐Altitude Adaptation Revealed From High‐Quality Draft Genome of Non‐Violacein Producing Janthinobacterium lividum ERGS5:01.” Standards in Genomic Sciences 13: 11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Lincoln, S. P. , Fermor T. R., and Tindall B. J.. 1999. “ Janthinobacterium agaricidamnosum sp. nov., a Soft rot Pathogen of Agaricus bisporus .” International Journal of Systematic and Evolutionary Microbiology 49: 1577–1589. [DOI] [PubMed] [Google Scholar]
  32. Liu, X. Y. , Koba K., Koyama L. A., et al. 2018. “Nitrate Is an Important Nitrogen Source for Arctic Tundra Plants.” Proceedings of the National Academy of Sciences 115: 3398–3403. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Liu, L. , Xie R., Ma D., Fu L., and Wu X.. 2023. “Effects of Snow Removal on Seasonal Dynamics of Soil Bacterial Community and Enzyme Activity.” European Journal of Soil Biology 119: 103564. [Google Scholar]
  34. Lu, H. , Deng T., Cai Z., et al. 2020. “ Janthinobacterium violaceinigrum sp. nov., Janthinobacterium aquaticum sp. nov. and Janthinobacterium rivuli sp. nov., Isolated From a Subtropical Stream in China.” International Journal of Systematic and Evolutionary Microbiology 70: 2719–2725. [DOI] [PubMed] [Google Scholar]
  35. Malard, L. A. , Anwar M. Z., Jacobsen C. S., and Pearce D. A.. 2019. “Biogeographical Patterns in Soil Bacterial Communities Across the Arctic Region.” FEMS Microbiology Ecology 95: fiz128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Maliniemi, T. , Lohi J., Alahuhta J., et al. 2025. “Dwarf Shrub Expansion and Loss of Lichens Distinctly Dominate Multi‐Decadal Changes in Northern Boreal Understory Plant Communities.” Nordia Geographical Publications 54: 9–19. [Google Scholar]
  37. Männistö, M. K. , Ahonen S. H. K., Ganzert L., Tiirola M., Stark S., and Häggblom M. M.. 2024. “Bacterial and Fungal Communities in Sub‐Arctic Tundra Heaths Are Shaped by Contrasting Snow Accumulation and Nutrient Availability.” FEMS Microbiology Ecology 100: fiae036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Männistö, M. K. , and Häggblom M. M.. 2006. “Characterization of Psychrotolerant Heterotrophic Bacteria From Finnish Lapland.” Systematic and Applied Microbiology 29: 229–243. [DOI] [PubMed] [Google Scholar]
  39. Männistö, M. K. , Tiirola M., and Häggblom M. M.. 2009. “Effect of Freeze–Thaw Cycles on Bacterial Communities of Arctic Tundra Soil.” Microbial Ecology 58: 621–631. 10.1007/s00248-009-9516-x. [DOI] [PubMed] [Google Scholar]
  40. McCann, C. M. , Christgen B., Roberts J. A., et al. 2019. “Understanding Drivers of Antibiotic Resistance Genes in High Arctic Soil Ecosystems.” Environment International 125: 497–504. [DOI] [PubMed] [Google Scholar]
  41. McGivern, B. B. , Cronin D. R., Ellenbogen J. B., et al. 2024. “Microbial Polyphenol Metabolism Is Part of the Thawing Permafrost Carbon Cycle.” Nature Microbiology 9: 1454–1466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. McTaggart, T. L. , Shapiro N., Woyke T., and Chistoserdova L.. 2015. “Draft Genome of Janthinobacterium sp. RA13 Isolated From Lake Washington Sediment.” Genome Announcements 3: 1588–1602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Mikkonen, S. , Laine M., Mäkelä H. M., et al. 2015. “Trends in the Average Temperature in Finland, 1847–2013.” Stochastic Environmental Research and Risk Assessment 29: 1521–1529. [Google Scholar]
  44. Na, S. I. , Kim Y. O., Yoon S. H., Ha S., Baek I., and Chun J.. 2018. “UBCG: Up‐to‐Date Bacterial Core Gene Set and Pipeline for Phylogenomic Tree Reconstruction.” Journal of Microbiology 56: 280–285. [DOI] [PubMed] [Google Scholar]
  45. Olson, R. D. , Assaf R., Brettin T., et al. 2023. “Introducing the Bacterial and Viral Bioinformatics Resource Center (BV‐BRC): A Resource Combining PATRIC, IRD and ViPR.” Nucleic Acids Research 51: D678–D689. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Ongpipattanakul, C. , Desormeaux E. K., Dicaprio A., van der Donk W. A., Mitchell D. A., and Nair S. K.. 2022. “Mechanism of Action of Ribosomally Synthesized and Post‐Translationally Modified Peptides.” Chemical Reviews 122: 14722–14814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Park, S. , Kim I., Chhetri G., et al. 2023. “ Roseateles albus sp. nov., Roseateles koreensis sp. nov. and Janthinobacterium fluminis sp. nov., isolated From Freshwater at Jucheon River, and Emended Description of Roseateles aquaticus comb. nov.” International Journal of Systematic and Evolutionary Microbiology 73: 006043. [DOI] [PubMed] [Google Scholar]
  48. Parks, D. H. , Imelfort M., Skennerton C. T., Hugenholtz P., and Tyson G. W.. 2015. “CheckM: Assessing the Quality of Microbial Genomes Recovered From Isolates, Single Cells, and Metagenomes.” Genome Research 25: 1043–1055. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Parte, A. C. , Sardà Carbasse J., Meier‐Kolthoff J. P., Reimer L. C., and Göker M.. 2020. “List of Prokaryotic Names With Standing in Nomenclature (LPSN) Moves to the DSMZ.” International Journal of Systematic and Evolutionary Microbiology 70: 5607–5612. Accessed September 22, 2025. 10.1099/ijsem.0.004332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Purser, G. , Drewer J., Heal M. R., Sircus R. A. S., Dunn L. K., and Morison J. I. L.. 2021. “Isoprene and Monoterpene Emissions From Alder, Aspen and Spruce Short‐Rotation Forest Plantations in the United Kingdom.” Biogeosciences 18: 2487–2510. [Google Scholar]
  51. Pushkareva, E. , Eckhardt K. U., Hotter V., et al. 2020. “Chemical Composition of Soil Organic Matter and Potential Enzyme Activity in the Topsoil Along a Moisture Gradient in the High Arctic (Svalbard).” Geoderma 368: 114304. [Google Scholar]
  52. Rajawat, M. V. S. , Singh R., Singh D., and Saxena A. K.. 2019. “Psychrotrophs of the Genus Janthinobacterium With Potential to Weather Potassium Aluminosilicate Mineral.” 3 Biotech 9: 142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sarneel, J. M. , Sundqvist M. K., Molau U., Björkman M. P., and Alatalo J. M.. 2020. “Decomposition Rate and Stabilization Across Six Tundra Vegetation Types Exposed to ≫20 Years of Warming.” Science of the Total Environment 724: 138304. [DOI] [PubMed] [Google Scholar]
  54. Shaffer, M. , Borton M. A., McGivern B. B., et al. 2020. “DRAM for Distilling Microbial Metabolism to Automate the Curation of Microbiome Function.” Nucleic Acids Research 48: 8883–8900. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Shoemaker, W. R. , Muscarella M. E., and Lennon J. T.. 2015. “Genome Sequence of the Soil Bacterium Janthinobacterium sp. KBS0711.” Genome Announcements 3: 689–704. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Skierszkan, E. K. , Carey S. K., Jackson S. I., Fellwock M., Fraser C., and Lindsay M. B. J.. 2024. “Seasonal Controls on Stream Metal(Loid) Signatures in Mountainous Discontinuous Permafrost.” Science of the Total Environment 908: 167999. [DOI] [PubMed] [Google Scholar]
  57. Sleator, R. D. , and Hill C.. 2002. “Bacterial Osmoadaptation: The Role of Osmolytes in Bacterial Stress and Virulence.” FEMS Microbiology Reviews 26: 49–71. [DOI] [PubMed] [Google Scholar]
  58. Sorensen, P. O. , Finzi A. C., Giasson M. A., Reinmann A. B., Sanders‐DeMott R., and Templer P. H.. 2018. “Winter Soil Freeze–Thaw Cycles Lead to Reductions in Soil Microbial Biomass and Activity Not Compensated for by Soil Warming.” Soil Biology and Biochemistry 116: 39–47. [Google Scholar]
  59. Spagnolo, F. , Trujillo M., and Dennehy J. J.. 2021. “Why Do Antibiotics Exist?” mBio 12: e01966‐21. 10.1128/mBio.01966-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Stamatakis, A. 2014. “RAxML Version 8: A Tool for Phylogenetic Analysis and Post‐Analysis of Large Phylogenies.” Bioinformatics 30: 1312–1313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Stankeviciute, G. , Tang P., Ashley B., et al. 2022. “Convergent Evolution of Bacterial Ceramide Synthesis.” Nature Chemical Biology 18: 305–312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Stark, S. , Kumar M., Myrsky E., et al. 2023. “Decreased Soil Microbial Nitrogen Under Vegetation ‘Shrubification’ in the Subarctic Forest–Tundra Ecotone: The Potential Role of Increasing Nutrient Competition Between Plants and Soil Microorganisms.” Ecosystems 26: 1504–1523. [Google Scholar]
  63. Stark, S. , Kytöviita M. M., and Neumann A. B.. 2007. “The Phenolic Compounds in Cladonia Lichens Are Not Antimicrobial in Soils.” Oecologia 152: 299–306. [DOI] [PubMed] [Google Scholar]
  64. Stark, S. , Männistö M. K., and Smolander A.. 2010. “Multiple Effects of Reindeer Grazing on the Soil Processes in Nutrient‐Poor Northern Boreal Forests.” Soil Biology and Biochemistry 42: 2068–2077. [Google Scholar]
  65. Stevens, J. M. , Mavridou D. A. I., Hamer R., Kritsiligkou P., Goddard A. D., and Ferguson S. J.. 2011. “Cytochrome c Biogenesis System I.” FEBS Journal 278: 4170–4178. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Stroeve, J. C. , Notz D., Dawson J., Schuur E. A. G., Dahl‐Jensen D., and Giesse C.. 2025. “Disappearing Landscapes: The Arctic at +2.7°C Global Warming.” Science 387: 616–621. [DOI] [PubMed] [Google Scholar]
  67. Tamura, K. , Stecher G., and Kumar S.. 2021. “MEGA11: Molecular Evolutionary Genetics Analysis Version 11.” Molecular Biology and Evolution 38, no. 7: 3022–3027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Travin, D. Y. , Watson Z. L., Metelev M., et al. 2019. “Structure of Ribosome‐Bound Azole‐Modified Peptide Phazolicin Rationalizes Its Species‐Specific Mode of Bacterial Translation Inhibition.” Nature Communications 10, no. 1: 1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Tu, Q. , Lin L., Cheng L., Deng Y., and He Z.. 2019. “NCycDB: A Curated Integrative Database for Fast and Accurate Metagenomic Profiling of Nitrogen Cycling Genes.” Bioinformatics 35: 1040–1048. [DOI] [PubMed] [Google Scholar]
  70. Tybirk, K. , Nilsson M. C., Michelsen A., et al. 2000. “Nordic Empetrum Dominated Ecosystems: Function and Susceptibility to Environmental Changes.” AMBIO: A Journal of the Human Environment 29: 90–97. [Google Scholar]
  71. Väisänen, M. , Martz F., Kaarlejärvi E., Julkunen‐Tiitto R., and Stark S.. 2013. “Phenolic Responses of Mountain Crowberry (Empetrum nigrum ssp. hermaphroditum) to Global Climate Change Are Compound Specific and Depend on Grazing by Reindeer (Rangifer tarandus).” Journal of Chemical Ecology 39: 1390–1399. [DOI] [PubMed] [Google Scholar]
  72. Van Dongen, S. , and Abreu‐Goodger C.. 2012. “Using MCL to Extract Clusters From Networks.” Methods in Molecular Biology 804: 281–295. [DOI] [PubMed] [Google Scholar]
  73. Vaser, R. , and Šikić M.. 2021. “Time‐ and Memory‐Efficient Genome Assembly With Raven.” Nature Computational Science 1: 332–336. [DOI] [PubMed] [Google Scholar]
  74. Vozzo, J. T. , Chen W., and Fraterrigo J. M.. 2025. “Arctic Shrub Expansion Generates Regional Variation in Litter Decomposition by Altering Litter Quality and the Decomposition Environment.” Functional Ecology 39: 1567–1578. [Google Scholar]
  75. Wick, R. R. , and Holt K. E.. 2021. “Benchmarking of Long‐Read Assemblers for Prokaryote Whole Genome Sequencing.” F1000Research 8: 2138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Wick, R. R. , and Holt K. E.. 2022. “Polypolish: Short‐Read Polishing of Long‐Read Bacterial Genome Assemblies.” PLoS Computational Biology 18: e1009802. 10.1371/journal.pcbi.1009802. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Wick, R. R. , Judd L. M., Cerdeira L. T., et al. 2021. “Trycycler: Consensus Long‐Read Assemblies for Bacterial Genomes.” Genome Biology 22: 266. 10.1186/s13059-021-02483-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Wong, S. K. , Cui Y., Chun S. J., et al. 2023. “Vegetation as a Key Driver of the Distribution of Microbial Generalists That in Turn Shapes the Overall Microbial Community Structure in the Low Arctic Tundra.” Environmental Microbiome 18: 41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Wu, X. , Deutschbauer A. M., Kazakov A. E., et al. 2017. “Draft Genome Sequences of Two Janthinobacterium lividum Strains, Isolated From Pristine Groundwater Collected From the Oak Ridge Field Research Center.” Genome Announcements 5: 10–1128. 10.1128/GENOMEA.00582-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Wu, X. , Kazakov A. E., Gushgari‐Doyle S., et al. 2021. “Comparative Genomics Reveals Insights Into Induction of Violacein Biosynthesis and Adaptive Evolution in Janthinobacterium .” Microbiology Spectrum 9: e01414‐21. 10.1128/SPECTRUM.01414-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Wylie, J. L. , and Worobec E. A.. 1995. “The OprB Porin Plays a Central Role in Carbohydrate Uptake in Pseudomonas aeruginosa .” Journal of Bacteriology 177: 3021–3026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Yan, Z. , Kang E., Zhang K., et al. 2022. “Asynchronous Responses of Microbial CAZymes Genes and the Net CO2 Exchange in Alpine Peatland Following 5 Years of Continuous Extreme Drought Events.” ISME Communications 2: 115. 10.1038/s43705-022-00200-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Yang, L. L. , Xin Y. H., and Liu Q.. 2026. “Description of 15 Novel Species Within Genus Janthinobacterium Isolated From Glaciers.” International Journal of Systematic and Evolutionary Microbiology 76: 7020. 10.1099/ijsem.0.007020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Yoon, S. H. , Ha S., Lim J., Kwon S., and Chun J.. 2017. “A Large‐Scale Evaluation of Algorithms to Calculate Average Nucleotide Identity.” Antonie Van Leeuwenhoek 110: 1281–1286. [DOI] [PubMed] [Google Scholar]
  85. Yu, X. , Zhou J., Song W., et al. 2021. “SCycDB: A Curated Functional Gene Database for Metagenomic Profiling of Sulphur Cycling Pathways.” Molecular Ecology Resources 21: 924–940. [Google Scholar]
  86. Zhang, Y. , and Gross C. A.. 2021. “Cold Shock Response in Bacteria.” Annual Review of Genetics 55: 377–400. [DOI] [PubMed] [Google Scholar]
  87. Zheng, J. , Ge Q., Yan Y., Zhang X., Huang L., and Yin Y.. 2023. “dbCAN3: Automated Carbohydrate‐Active Enzyme and Substrate Annotation.” Nucleic Acids Research 51: W115–W121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Zhu, H. , Liu R., Shang Y., and Sun L.. 2023. “Polylysine Complexes and Their Biomedical Applications.” Engineered Regeneration 4: 20–27. [Google Scholar]
  89. Zimin, A. V. , and Salzberg S. L.. 2020. “The Genome Polishing Tool POLCA Makes Fast and Accurate Corrections in Genome Assemblies.” PLoS Computational Biology 16: e1007981. 10.1371/journal.pcbi.1007981. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Kumar et al_Janthinobacterium_Supplementary Data.

MBO3-15-e70239-s001.pdf (1.3MB, pdf)

Data Availability Statement

Type strains are deposited in the German Collection of Microorganisms and Cell Cultures (DSMZ) and the University of Helsinki HAMBI Culture Collection. IMG Taxon IDs and NCBI accession numbers for the newly assembled Janthinobacterium genomes are J. silvisoli K2Li3, 2849242232, GCA_014200695.1 (Project ID Gp0453385); J. silvisoli K2C7, 2849236846, GCA_014200685.1; J. silvisoli K2E3, 2849247614, GCA_014200725.1; J. saanense S3T4, 2849231242, GCA_014200675.1 (Project ID Gp0453383); and J. saanense S3M3, 284922563 GCA_014200645.15. Accession numbers for 16S rRNA genes are J. silvisoli K2Li3, PX226025; J. silvisoli K2C7, NZ_JACHCJ010000019; J. silvisoli K2E3, NZ_JACHCL010000016; J. saanense S3T4, PX226026; and J. saanense S3M3, NZ_JACHCH010000008.

Articles from MicrobiologyOpen are provided here courtesy of Wiley

RESOURCES