Comparative genomic analysis and genome sequence of Halomonas salifodinae strain A2, isolated from the Zapotitlán Salinas Valley Puebla, México

doi:10.21203/rs.3.rs-4596214/v1

Download PDF

Research Article

Comparative genomic analysis and genome sequence of Halomonas salifodinae strain A2, isolated from the Zapotitlán Salinas Valley Puebla, México

https://doi.org/10.21203/rs.3.rs-4596214/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Here, we report the genome sequence of strain A2. The genome size was 3,855,926 bp, the GC content was 67.4%, and it contains 3509 genes, 62 tRNA, eight rRNA, and four snRNA. Phylogenetic analysis of the 16 S rRNA gene in the RDP, NCBI, and TYGS databases indicates that strain A2 belongs to Halomonas salifodinae. Also, MLSA analysis confirms that A2 is closely related to H. salifodinae. Phylogenomic and comparative genomic analysis using the ANIs and dDDH indicators classify H. salifodinae A2 and Bisbaumannia pacifica NBRC 102220 in a separate phylogenetic group of the genus Halomonas. The phylogenomic and pangenome analysis support the above, placing H. salifodinae A2 in a separate group with B. pacifica NBRC 102220. The pangenomic analysis shows 136,122 genes that comprise the pangenome with 317 core genes, 3457 shell genes, 132,332 accessory genome, and 691 unique genes. We found 29 genes for secretion systems in the genome analysis, 23 for Na + and K + ion transport, 6 BGC groups, a total of 12 genomic islands, an 8.2Kb gene prophage region, 15 regions associated with CRISPR and one CAS-TypeIF cas gene cluster region, 12 genes of biotechnological importance, 38 unique genes essential for adaptability and biotechnological relevance, as well as, 35 genes for the synthesis of compatible solutes. Furthermore, we propose the reclassification of the species within the genus Bisbaumannia.

Biotechnology

Bisbaumannia

Compatible solutes

Halomonas

Osmoadaptation

Halotolerant or halophilic microorganisms, capable of living in saline environments, offer many potential applications in various fields (Margesin and Schinner 2001). Water bodies with concentrated salt solutions, such as saline lakes, coastal lagoons, and artificial salt mines, are extreme environments inhabited by only a few life forms but generally maintain dense microbial populations comprising species from all three domains of life (Oren et al. 2008). Moderately halophilic bacteria are extremophile microorganisms that grow optimally in media containing 3–15% NaCl (Kushner et al. 1988), although most can grow in an extensive range of salinities (Ventosa et al. 1998).

To withstand these conditions, bacteria accumulate organic compounds called compatible solutes highly soluble in water to maintain an osmotic balance with the surrounding medium (Brown 1976; Litzner et al. 2006; Roberts 2005). The predominant compatible solutes in halophilic bacteria are derivatives of amino acids such as ectoine (Oren et al. 2008; Roberts 2005). Compatible solutes benefit bacterial cells as osmoregulatory solutes and as protein protectants by mitigating the detrimental effects of freezing, desiccation, and high temperatures (Borges et al. 2002; Clegg et al. 1982).

It has been proposed that compatible solutes can counteract osmotic inhibition by increasing the overall water content and, consequently, the cytoplasmic volume of cells. (Clegg et al. 1982; Galinski et al. 1997; Kolp et al. 2006). The structure-forming and breakage properties of compatible solutes indirectly influence the hydration “shells” and, therefore, the activities of the proteins involved (Arakawa and Timasheff 1985; Bolen et al. 2001; Di Gioacchino et al. 2019; Kurz 2008; Liu and Bolen 1995; Timasheff 2002). The predominant compatible solutes in halophilic bacteria are derivatives of amino acids such as ectoine (Oren et al. 2008; Roberts 2005). Many bacteria synthesise the aspartate derivative ectoine (1,4,5,6, tetra-2-methyl-4-pyrimidonecarboxylic acid) as one of their primary compatible solutes (Roberts 2005). Ectoine is synthesised from aspartate-semialdehyde and comprises three enzymatic steps; the genes involved in ectoine synthesis are located continuously in the ectABC operon (Ono et al. 1999).

The Halomonas genus includes Gram-negative bacilli that can be motile or non-motile, catalase-positive, and aerobic. However, some strains can grow anaerobically in the presence of nitrate and require media to be supplemented with concentrations of 3–15% NaCl for optimal growth. It is one of the most representative groups of bacteria within moderate halophilic organisms; it is included in the phylum Proteobacteria, class Gamma-Proteobacteria, order Oceanospirillales, family Halomonadaceae (de la Haba et al. 2023; Dobson and Franzmann 1996; Vreeland and Martin 1980).

Complete or partial genome sequencing benefits functional studies of compatible solutes such as ectoine (Imhoff et al. 2020; Zhang et al. 2022). The biological information these sequences provide offers new resources, such as unique genes and their functions, the presence and absence of specific genes, and many other characteristics hidden within the genomes (Gao et al. 2015).

There is a wide range of technological and industrial applications for ectoine and other compatible solutes, starting with cosmetics such as sunscreens and anti-ageing products (Bujak et al. 2020; Heinrich et al. 2007; Ma et al. 2022). Treatments of inflammatory skin conditions such as topical dermatitis, dry eye, dry nose, and rhinosinusitis have been developed and successfully tested in clinical trials (Eichel et al. 2013; Dao et al. 2019). Also, protecting DNA against ionising radiation during radiotherapies and chemotherapies in cancer patients (Dao et al. 2018; Refaat et al. 2018; Rieckmann et al. 2019; Schröter et al. 2017). As a protein stabiliser in experimental therapies against neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Huntington’s (Arora and Park 2004; Ashraf et al. 2014; Bazazzadegan et al. 2017; Furusho and Shoi 2005; Kanapathipillai et al. 2008; Yang et al. 1999). In addition, a new application for producing ectoine using biogas promotes a green and circular economy (Cantera et al. 2020; Pérez et al. 2022).

In this study, the genome of a moderately halophilic bacteria, strain A2, isolated from the Zapotitlán Salinas Valley Puebla, México, was sequenced and analysed. Phylogenetic analysis indicates that strain A2 belongs to the species Halomonas salifodinae. Several genes related to adaptation to saline environments and regions of interest were located within the genome, such as secretory proteins, ion transport, secondary metabolites, genomic islands, CRISPR-Cas regions, prophage sequence regions, genes of biotechnological importance, and biosynthetic genes for compatible solutes. In addition, pangenome analysis and detection of unique genes were performed.

Bacterial strain and culture.

Strain A2 was isolated from the “Las Chiquitas” salt mine (18°20’49.0 “N − 97°26’59.0” W) in the Zapotitlán Salinas Valley Puebla, Mexico. The strain A2 was isolated by taking 1 ml of the 1:10 sample dilution for inoculation. The culture medium was BD Bioxon® nutritive medium (Becton Dickinson, USA) containing 5.0 g pancreatic digest of gelatine, 3.0 g beef extract, 15.0 g agar, and we added 10% NaCl (1.7mol/l). The pH of the medium was 7.8. To determine the optimal growth of the strain, cultures were carried out at different salinity concentrations (0–20% NaCl, 0-3.5 mol/l) at 35°C.

Observation of bacterial morphology

Strain A2 was cultured in a nutrient medium with 1.7 mol/l NaCl at 35° C for 36 h. Cell morphology was determined by Gram staining using optical microscopy at x400 and x1000 magnification. Cells were prepared for transmission electron microscopy (TEM) by performing conventional fixation with glutaraldehyde and aqueous osmium tetroxide and dehydrating the sample with ethanol. Electron micrographs were prepared using a JEOL® TEM model JEM-1010 with an acceleration voltage of 80 kV.

DNA extraction and genome sequencing.

The strain was grown in a nutrient medium in 1.7 mol/l NaCl at 35° C for 36 h. It was collected during the logarithmic growth phase in 2 ml tubes stored at -70°C and then sent on dry ice for processing. The genome was sequenced by Novogene Co. America (CA, USA) on the Illumina Novaseq 6000 platform; the raw data were cleaned until obtaining a Clean Data Q20(%) 97.31 and Q30(%) 92.6. Genome assembly was performed using SOAPdenovo software version 2.0 (Luo et al. 2012), SPAdes version 3.15.1 (Prjibelski et al. 2020), and Abyss software version 2.0. (Jackman et al. 2017). The assembly results from the three software were integrated with the CISA software (Lin and Liao 2013), and the resulting assembly with the least number of scaffolds was selected.

Gene prediction and annotation

The prediction of genome components included coding genes, repetitive sequences, non-coding RNA, genomic islands, prophages regions, clustered regularly interspaced short palindromic repeat sequences (CRISPR), and secondary metabolism genes, was performed as follows: GeneMarkS program server version 4.28 (Besemer et al. 2001) was employed to retrieve related coding genes, interspersed repetitive sequences were predicted using RepeatMasker server version 4.1.3 (Saha et al. 2008), tandem repeats were analysed by the server tandem repeat finder (TRF) (Benson 1999), tRNA genes were predicted by tRNAscan-SE version 2.0 (Chan and Lowe 2019; Lowe and Chan 2016), rRNA were analysed by rRNAmmer-1.2 (Lagesen et al. 2007), BLAST predicted small nuclear RNAs (snRNAs) against the Rfam database (Gardner et al. 2009), the Islandviewer 4 (Hsiao et al. 2003) was used to predict Genomic Islands and PHASTER (Arndt et al. 2016) was used for prophage prediction. CRISPRFinder (Grissa et al. 2007) was used for CRISPR identification, and we analysed secondary metabolism gene clusters using antiSMASH 7.0 (Blin et al. 2023).

We used six databases to predict gene functions, Diamond version 0.8.35 (Buchfink et al. 2021), hmmer3 version 3.3.2 (Eddy 2011) and Blast2go (version 2.5) were applied to annotate genes in Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), Nonredundant Protein Database (NR), Protein Family Database (Pfam) and Swiss-Prot. A whole-genome blast search (E value less than 1e-5, per cent minimum alignment length greater than 40%) was performed on the above six databases. Genes involved in survival in saline environments, biosynthesis of compatible solutes, and other genes of biotechnological importance were searched and detected manually using the annotation provided by the KEGG and NR databases and confirmed by local alignments with the BLAST® tool in the National Center for Biotechnology Information (NCBI).

Phylogenetic analysis

For phylogenetic analysis, the sequence of the 16S rRNA gene of A2 was compared in the GeneBank databases of the NCBI, Ribosome Data Project (RDP) (Cole et al. 2014), EzBioCloud, and Type Strain Genome Server (TYGS) (Meier-Kolthoff et al. 2022). The sequences with high similarities were obtained from the GeneBank and RDP databases, and Pseudomonas aeruginosa strain DSM 50071 (NR_026078.1) was used as the outgroup. The MEGA11 software (Tamura et al. 2021) was used to align, compare, and construct the phylogenetic tree using the Neighbour Joining (NJ) method with Bootstrap of 1000. To corroborate the taxonomic classification of A2, another phylogenetic tree using Multilocus Sequence Analysis (MLSA) genes rpoD, gyrB, secA, atpA, and 23S rRNA (de la Haba et al. 2012) was constructed, concatenated, and trimmed to similar lengths from the closely related species; Pseudomonas aeruginosa strain DSM 50071 (NR_026078. 1) was selected as outgroup. The phylogenetic tree of the MSLA genes was constructed in the MEGA11 software using the NJ method with Bootstrap of 1000. The taxonomic analysis of the complete A2 genome was performed on the TYGS server (Meier-Kolthoff et al. 2022). The Average Nucleotide Identity (ANI) values were calculated using the EzBioCloud ANIs calculator server (Yoon et al. 2017). The digital DNA-DNA Hybridization (dDDH) values were calculated in the Genome-to-Genome distance calculator (GGDC) server 3.0 (Meier-Kolthoff et al. 2022). Pangenome construction was performed using rapid large-scale prokaryote pangenome analysis in Roary software version 3.11.2 (Page et al. 2015) using the GFF3 files provided by the Prokka software (Seemann 2014). We used IQTREE server version 2.3.4 (Trifinopoulos et al. 2016) to construct the Maximum Likelihood phylogenetic tree using the GTR model with an Ultrafast Bootstrap of 1000. Based on de la Haba et al. 2023, we used a PH27A strain of Terasakiispira papahanaumokuakeensis as outgroup. A comparison of the proteomes of A2 and nine of the closest species was performed using the Proteome Comparison Tool on the BV-BRC server (Olson et al. 2023).

Strain A2 growth conditions

Strain A2 was grown in the nutrient medium at different concentrations of NaCl (0–20%, 0-3.5 mol/l) at 35°C, showing optimal growth at 1.7mol/l NaCl concentration. The strain showed observable growth after 36 hours in a concentration range of 0.5–2.6 mol/l (3–15%) NaCl. In the 0-0.5 mol/l concentration and beyond 2.6 mol/l concentration, the growth was not detectable in the same time range.

Cellular and colonial morphology

The colonies of strain A2 had an indefinite morphology, with an irregular light brown growth pattern and a slightly viscous consistency that expanded in all directions. For the cellular morphology of A2, we observed small cells around 1µm in length (Fig. 1) and a coccobacillus morphology that reacted negatively to Gram staining.

Genome Overview

The genome sequence of A2 was 3,855,926 bp in 33 scaffolds with an N50 Length of 336,455 bp and an N90 Length 84,770 with a Max Length scaffold of 483,539 bp, a Min Length scaffold of 648 bp with a GC content of 67.4% (Table 1). The genome contains 3,509 genes, with a percentage of coding genes of 87.86%. In the genome of A2, there are a total of 74 RNAs, of which 62 are tRNA genes, eight are rRNA genes, including one 16S rRNA, one 23S rRNA, and six for 5S rRNA; the remaining four correspond to snRNA (Table S1). Furthermore, about 303 tandem repeat sequences were found, as well as 211 mini- and five microsatellites (Table S2). Six databases were used to annotate the functions of the CDSs. The total number of genes annotated by each GO, KEGG, COG, NR, Pfam, and Swiss-Prot database were 2557, 3380, 2967, 3405, 2557, and 1848 respectively (Table 1).

Table 1

Project information and genome statistics
Attributes	Value
Sequencing platform	Illumina
Genome size (bp)	3,855,926
GC content %	67.4
Scaffold Max Lenght (bp)	483,539
Scaffold Min Length (bp)	648
N50 Length(bp)	336,455
N90 Length (bp)	84,770
Scaffolds	33
Number of coding genes	3509
RNA genes	74
tRNA	62
rRNA genes	8
5 S rRNA	6
16 S rRNA	1
23 S rRNA	1
sRNA	4
GO annotation	2557
KEGG annotation	3380
COG annotation	2967
NR annotation	3405
Pfam anotattion	2557
Swiss-Prot annotation	1848

Genome annotation

For A2, the GO annotations (Fig. 2a) are in three main categories: molecular function (3167), cellular component (2303), and biological process (5552). In the molecular function category, the five subcategories with the most annotations were catalytic activity (1380) and binding (1173). Cell part and cell were the subcategories that presented the most annotations, with 949 each in the cellular component category. In the biological process category were the metabolic process (1467), cellular process (1401), localisation (569), and establishment of localisation (552).

Based on sequence homologies, a total of 3344 were mapped to 24 categories in COG (Fig. 2b). Regarding the above, amino acid transport and metabolism (E), general functions prediction (R), energy production and conversion (C), translation, ribosomal structure, and biogenesis (J), transcription (K) and inorganic ion transport metabolism (P) were the most abundant categories in COG with 9.9%, 8.9%, 7.0%, 6.9%, 6.9%, and 6.0% respectively. These functions are essential for halophilic bacteria survival in hypersaline environments (Zhang et al. 2022).

The KEGG annotations (Fig. 2c) have six categories with many annotated genes. For the metabolism category, we have amino acid and carbohydrate metabolism, which have the highest proportion of annotated genes, with 250 and 191, respectively. Regarding the annotation of amino acid metabolism, we can mention metabolic routes such as alanine, aspartate, and glutamate metabolism (ko00250), arginine and proline metabolism (ko00330), lysine biosynthesis (ko00300) and cysteine and methionine metabolism (ko00270), all of them closely related to the metabolic pathway of degradation and biosynthesis of ectoine and other compatible solutes, which is immersed in the glycine, serine and threonine metabolism pathway (ko00260). Pyruvate metabolism (ko00620) has the highest amount of carbohydrate metabolism annotations, glyoxylate and dicarboxylate metabolism (ko00630) have a second place and are followed by propanoate metabolism (ko00640) and butanoate metabolism (ko00650) respectively.

Phylogenetic and phylogenomic analysis

The results for the phylogenetic analysis of the 16S rRNA gene (1528 bp) showed that A2 belongs to the genus Halomonas with 99.9% homology in the NCBI database with Halomonas sp. strain K-15-10-3 (OP077305.1) 16S rRNA gene, partial sequence (1507 bp), 99.2% with Halomonas salifodinae strain BC7 (EF527873.1) 16S rRNA gene (1428 bp) partial sequence and 99.1% with Halomonas pacifica strain NBRC 102220 16S rRNA gene (1463 bp) partial sequence, however, in the new classification by de la Haba et al. (2023), H. pacifica becomes Bisbaumannia pacifica NBRC 102220 ( NR_114047.1). For type species in the EzBiocloud database, there is 99.3% homology with H. salifodinae BC7, 98.9% with B. pacifica NBRC 102220, and 97.6% with Halomonas sediminicola CPS11 (NR_152067.1). The phylogenetic tree (Fig. 3) constructed with the results from the NCBI and RDP database shows the close relationship of A2 with H. salifodinae strain BC7 and B. pacifica strain NBRC 102220 forming a branch apart from the other species. The phylogenetic tree constructed with the MLSA genes (Fig. 4) also results in a high homology between A2 and H. salifodinae JCM14803 (GCA_039522585.1), and both show a close relationship with B. pacifica DSM 4742. In the phylogenetic analysis of the 16S rRNA gene sequences (Fig. 5) and the genome-to-genome comparison (Fig. 6) that was carried out in TYGS, the results are similar and corroborate the phylogenetic closeness of A2 with H. salifodinae JCM14803 and B. pacifica NBRC 102220 that found in the same branch. The proteome of A2 shows considerably higher homology to the proteome of H. salifodinae IM328, followed by that of B. pacifica NBRC 102220, compared to the proteomes of closely related Halomonas species (Fig. 7). Based on the above data the genome of A2 was compared with genomes of closely related species using ANI and dDDH analysis (Table 2, S3, S4). The ANI and dDDH values between A2 and H. salifodinae IM328 (GCA_036871055.1) were 95.95% and 85.6%, respectively. At the same time, B. pacifica NBRC 102220 were 89.9% and 69.7%, respectively; the ANI and dDDH values for the other related species did not exceed 81% and 30.6%, respectively. According to species delimitation, cut-off values of 95% for ANI and 70% for dDDH and showing ≥ 98.7 % 16S similarity (Chun et al. 2018; Meier-Kolthof et al. 2022) and supported by the previous information, Halomonas sp. A2 is designated as Halomonas salifodinae strain A2. Furthermore, it is proposed that Halomonas salifodinae belongs to the genus Bisbaumannia because it shows more significant similarity than the genus Halomonas.

Table 2

The ANI and dDDH analysis between A2 and its closely related species
Hit taxon	ANI (%)	dDDH (%)
Halomonas salifodinae IM328	95.9	85.6
Bisbaumannia pacifica NBRC 102220	89.9	69.7
Halomonas alkalicola strain CICC 11012s	81.1	29.6
Billgrantia campisalis strain A4	80.9	28.4
Halomonas shengliensis CGMCC 1.6444	80.6	28.5
Halomonas campaniensis 5AG	80.6	30.6
Halomonas ventosae CECT 5797	80.1	28.6

Secretory system analysis

The general secretion (Sec) and twin-arginine translocation (Tat) pathways are the most used bacterial secretion systems to transport proteins across the cytoplasmic membrane (Natale et al. 2008). Most proteins transported by the Sec and Tat pathways remain inside the cell, either in the periplasm or the inner membrane. The Sec system can also transport proteins that must stay in the inner membrane through the signal recognition particle (SRP) pathway (Green and Mecsas 2016). The Sec pathway transfers the protein to the periplasmic space before it is folded, and the Tat pathway transfers the folded protein to the periplasm. In contrast, the SRP pathway allows the protein to be folded and transferred simultaneously (Valent et al. 1998). Secretion System Type I is dedicated to transporting digestive enzymes, such as proteases and lipases, as well as adhesins and heme-binding proteins (Green and Mecsas, 2016). Meanwhile, the Secretion System Type VI translocates proteins to various recipient cells, including eukaryotic cell targets and, more commonly, other bacteria (Russell et al. 2014). A total of 28 genes related to the bacterial secretion system were found in the genome of H. salifodinae A2 (Table S5). We have 11 Sec-SRP genes, three from Tat, one from the Type I secretion system, and 13 from Type VI.

Ion transport proteins analysis

In many halophilic microorganisms, potassium absorption and the synthesis of compatible organic solutes control osmotic regulation in conditions of high salinity; K + limitation inhibits growth and adaptation to the saline environment, especially at high salinities, and causes a decrease in intracellular compatible organic solutes (Kraegeloh and Kunte 2002). The Tkr and Pha1 systems regulate K + transport and entry into the cell. The Trk system acts as a transmembrane transport protein, is ATP-dependent, and promotes K + uptake through an electrochemical gradient. (Kraegeloh et al. 2005). The Pha1 system functions as a K+/H + antiporter with optimal pH involved in potassium transport under slightly alkaline conditions; the Pha1 system can also transport Na+ (Yamaguchi et al. 2009). In A2, two genes, trkA and trkH, belonging to the Trk system, and five Pha1 system genes involved with K + transport were identified (Table S6). Surviving in environments with high salinity is complex; not only does the absorption of K + help keep the osmotic pressure under control, but the expulsion of Na + is essential to maintaining balance. Therefore, precise metabolic systems must be available for the transport of Na+. For A2, we found that there are six genes of the Nqr system that encode subunits of NADH: ubiquinone reductase (Na+-transporting) and seven genes of the multisubunit sodium/proton antiporter Mrp system (Table S6).

Secondary metabolites analysis

The antiSMASH 7.0 biosynthetic gene cluster prediction tool was used to detect biosynthetic gene clusters (BGCs) in the genome sequence of H. salifodinae A2 (Table S7). The results demonstrate the presence of biosynthetic gene clusters for different types of metabolites mentioned below. Ranthipeptide, an emerging class of natural products belonging to the ribosomally synthesised and posttranslationally modified peptide (RiPP) superfamily, analysis shows that these two ranthipeptides participate in quorum sensing and the control of cellular metabolism (Chen et al. 2020). Resorcinol for the catabolic metabolism of the aromatic compound resorcinol (Yang et al. 2022). Betalactone represents a poorly explored group of secondary metabolites with pharmaceutical potential, many of them with potent bioactivity against bacteria, fungi, or human cancer cell lines. (Džunková et al. 2023; Robinson et al. 2019). Siderophores are synthesised and secreted by many bacteria, yeasts, fungi, and plants for Fe (III) chelation under low iron conditions (Timofeeva et al. 2022).

Genomic islands analysis

Horizontal gene transfer is an important mechanism for microbial genome evolution, allowing rapid adaptation and survival in specific niches. Genomic islands, commonly defined as groups of bacterial or archaeal genes of probable horizontal origin, are of medical, environmental, or industrial interest (Bertelli et al. 2019). Using Islandviewer 4 software, groups of genes associated with genomic islands in the genome of A2 were detected by the IslandPath-DIMOB and SIGI-HMM prediction methods (Fig. 8). The results of the analysis revealed that A2 has 12 genomic islands with a total of 168 kbp, of which the three largest have a size of 34 kbp, 27 kbp and 19 kbp. Among other groups of genes present (Table S8) in the genomic islands are six genes that encode proteins directly related to Fe metabolism, TonB-dependent receptor, siderophore-iron reductase FhuF, AraC family transcriptional regulator, ferrioxamine B receptor, iron complex transport system ATP-binding protein and Fe3+-hydroxamate ABC transporter permease FhuB, all related to different Halomonas species, these genes have great importance in response to alkaline stress (Zhai et al. 2021). Two ISAs1 family transposases from Halomonas halodenitrificans, four TypeI-F CRISPR-associated, two associated with proteins, and two associated with helicase and endonuclease from Halotalea alkalilenta. In addition to three genes associated with the fimbrial adhesin protein and pilus assembly protein from Alcanivorax sp. PN-3.

Prophage regions analysis

Prophages, due to their ability to share genes, play a key role in bacterial adaptation to compete with other bacteria and adjust metabolism depending on the environmental conditions in which they are found to survive and grow (Bondy-Denomy and Davidson 2014). Typically, the prolonged presence of a prophage within a bacteria sometimes leads to the degradation of genetic sequences of the prophage genome, a phenomenon called “phage domestication” (Touchon et al. 2014). Newly integrated phages appear to be inactivated by the host and then eliminate unhelpful genes through point mutations and deletions in genetic regions that are not under selection. Through this process, it can be justified that most prophage sequences found within bacterial genomes are incomplete and do not contain essential genes for interaction with the bacteria (Bobay et al. 2014). An 8.2Kb extended incomplete prophage region containing ten ORFs was found at position 31514–39718 within the A2 genome using the PHASTER server (Table S9). The prophage region was classified as incomplete (< 70 score). This region was confirmed to match the sequences of PHAGE_Entero_mEp460_NC_019716. Enterobacteriaceae phage mep460 is a species of dsDNA virus from the class Caudoviricetes, bacterial and archaeal viruses with head-tail morphology.

CRISPR sequence analysis

CRISPR elements are essential for bacterial genomes, providing acquired immunity against viruses and plasmids (Horvath and Barrangou 2010). Several CRISPRs with a unique or different repeat sequence can be found in each strain, but only one of each type is associated with the cas genes because the spacers in the CRISPRs are different. The unique sequences or spacers correspond mostly to foreign DNA fragments, i.e. viruses, plasmids, or mobile genetic elements. Several genes called cas are associated with CRISPR and are found near them. They perform three different functions of the immune system: adaptation, crRNA maturation, and interference, and their number varies from one type to another. Phylogenetic studies on the CAS protein suggest that CRISPRs are acquired through horizontal transfer. CRISPR loci are transcribed into a pre-crRNA from the leader that acts as a promoter, and then this precursor matures into a small crRNA that plays a role in the selection and destruction of homologous foreign sequences (Couvin et al. 2018; Grissa et al. 2007). In A2, 15 CRISPR regions of 100 to 130 nucleotides in length were located with evidence level one and a CAS-TypeIF cas gene cluster region with a level of evidence 4 (Table S10, S11).

Biotechnological importance genes

Many microorganisms produce natural polyesters such as polyhydroxyalkanoates (PHA) as energy and carbon reserve materials under stressful growth conditions. They can subsequently be degraded by intracellular depolymerases and metabolised as an alternative carbon and energy source (Philip et al. 2007). PHAs have properties like those of conventional petroleum-based plastics, so in addition to their biocompatibility, they are considered materials with high biotechnological potential in industrial applications (Keshavarz and Roy 2010). In A2, the genes phbB acetoacetyl-CoA reductase, phbC polyhydroxyalkanoate synthase, and phaR polyhydroxyalkanoate synthesis repressor PhaR were detected, which participate in the biosynthesis of intracellular PHA.

Alpha-amylase is an enzyme of biotechnological interest because it is used for its antibiofilm properties to control microorganisms. Bacterial biofilms are a significant threat to industries, the environment, and the healthcare sector (Goel et al. 2022). The amyA gene encoding alpha-amylase was detected among the unique genes for A2.

Strain A2 also carries multiple genes directly involved in arsenic resistance; these genes have been reported in some species of the Halomonacea family (Diken et al. 2015; Lin et al. 2012; Wu et al. 2018). The ars system of arsenic detoxification is the most studied; Its operation begins with the uptake of arsenate by the phosphate transporters of the pstABCS complex (Lin et al. 2012) and the uptake of arsenite by aquaglyceroporins, which transform As (V) into As (III) by arsenate reductases, and the efflux of As (III) by arsenite efflux permeases (Wu et al. 2018). The presence of the genes arsA arsenite/tail-anchored protein-transporting ATPase, arsB arsenite transporter, arsC arsenate reductase, and arsH arsenical resistance protein ArsH suggest that A2 is an arsenite-specific efflux and arsenic-reducing prokaryote. These arsenic resistance genes, in addition to previous studies performed in other species, validate the genomic potential of A2 as a candidate organism for bioremediation studies (Diken et al. 2015). Genes of biotechnological importance found in A2 can be seen in supplementary Table S12.

Pangenome Analysis

Pangenome analysis was performed using Roary v3.13.0, using GFF3 files generated by Prokka. Consequently, we obtained four different classes of genes belonging to the ‘core’ (95% ≤strains ≤ 100%), ‘softcore’ (90%≤ strains < 95%), ‘shell’ (15%≤ strains < 90%) and ‘cloud’ (0%≤ strains < 15%). Pangenome analysis was performed using the A2 genome and 100 reference genomes of described Halomonas and related species found in the NCBI database. Pangenome analysis using Roary revealed 136,122 genes composing the pangenome of A2 and associated species at the 90% threshold. The number of core genes shared by 95–100% of strains was 317, while the cluster of softcore or near-core accessory genes shared by 90% to < 95% of strains was 16. The accessory set of gene clusters widely distributed in the species that form the shell genes were 3,457 genes shared by between 15% and < 95% of the strains. The accessory set of rare genes in the species that form the gene clouds that occur in 0% to < 15% of the strains showed the most significant number of 132,332 genes, also called unique genes. The large number of genes in the cloud implies significant heterogeneity between species (Carpi et al. 2022). The above agrees with what was reported by de la Haba et al. 2023 where the significant genetic variability within the genus is mentioned, which prevents the formation of a monophyletic group, which is why the taxonomy of the genus was reorganised. The results in the pangenome matrix and phylogenomic trees (Fig. 9, 10) constructed from the alignment of 152 core genes from 40 related species show a close relationship between H. salifodinae A2 and H. salifodinae IM328; both show a greater close with B. pacifica NBRC 102220 forming a branch separate from the Halomonas genus.

Unique genes

In H. salifodinae A2, 691 unique genes were detected, compared with other species, and 431 only compared with H. salifodinae IM328. There are 38 unique genes important for adaptability and biotechnological relevance involved in molybdenum metabolism, tungsten, copper, iron, antimicrobial resistance systems, biofilm formation, acid resistance, and an entire bo₃-type cytochrome oxidase system. Some of these are described below and in the supplementary material Table S13.

The trace elements molybdenum and tungsten are used by virtually all life forms as binding cofactors in many enzymes (Johnson et al. 1996). Bacterial genes for molybdenum- and tungsten-containing enzymes are often differentially regulated depending on the availability of the metal in the environment (Rajeev et al. 2019). Both Mo and W atoms share several similar chemical characteristics; due to this, there are several strategies to differentiate them and avoid incorrect insertion of the metal into the active site of the enzymes. These elements enter the intracellular medium as soluble oxoanions, MoO₄^2- and WO₄^2-, through specific ATP-binding cassette (ABC) transporter systems. Within prokaryotes, these transport systems are divided into three different families: Mod, Wtp, and Tup (Otrelo-Cardoso et al. 2014). The genes tupA Tungstate-binding protein TupA and tupC Tungstate uptake system ATP-binding protein TupC of the TupABC system were detected; these participate in the cellular uptake of tungsten and belong to the ABC type transport systems (ATP Binding Cassette). The TupA component is a periplasmic protein that binds tungstate anions, which are then transported across the membrane by the TupB component using ATP hydrolysis as an energy source (the reaction catalysed by the ModC component). In addition, the genes related to molybdenum metabolism modA Molybdate-binding protein ModA, mobA Molybdenum cofactor guanylyltransferase, mobB Molybdopterin-guanine dinucleotide biosynthesis adapter protein, moeA_1 Molybdopterin molybdenumtransferase were detected in A2.

Bacteria use flagella for mobility in adverse environments and movement to less hostile sites suitable for adaptation and survival. They are usually formed by multiple protein subunits (He et al. 2023). Flagella assembly is highly ordered and governed by a hierarchical mode of regulation that is tightly controlled by at least 17 operons composed of more than 50 genes (Chevance and Hughes, 2008). In A2, nine genes were found to be directly involved in synthesising proteins to structure some of the parts of the flagellum, such as the basal body, axial structure, or flagellar filament. Some of these genes are fliD1 Flagellar hook-associated protein 2, fliF Flagellar M-ring protein, and flgA Flagella basal body P-ring formation protein FlgA.

The genes of the cytochrome bo₃ complex were determined as unique genes in A2. Cytochrome bo₃ is encoded by the cyoABCDE operon (Forte et al. 2019). The three gene products of cyoA, cyoB, and cyoC are related to subunits II, I, and III, respectively, of the eukaryotic and prokaryotic aa₃-type cytochrome c oxidases, and this belongs to the heme-copper oxidase type A-1 superfamily (Sousa et al. 2012). The enzyme generates a proton motive force with high efficiency (H + / e ^- = 2) since it is endowed with proton pumping activity (Puustinen et al. 1991). The cytochrome bo₃ complex predominates in growth conditions where oxygen tension is high (Chepuri et al. 1990). The enzyme consists of four subunits and has three redox cofactors, a low-spin heme b, a high-spin heme o₃, and Cu_B, all located in subunit I. Heme b is the primary electron acceptor of ubiquinol, while heme o₃ and Cu_B form a binuclear active centre where O₂ chemistry occurs (Melin et al. 2018). As previously thought, Cytochrome bo3 contains only one ubiquinol binding site located on subunit I instead of two, known as the high-affinity QH site. (Choi et al. 2017)

The Type I protein secretion system prsE and prsD genes were determined to be unique genes in A2. This system is responsible for the secretion of the EPS-glycanases PlyA and PlyB, two exopolysaccharides (EPS) necessary for biofilm formation (Russo et al. 2006). These enzymes play a crucial role in biofilm formation by cleaving EPS chains and modulating biofilm structure and maturation (Lucke et al. 2020).

A2 would also have the presence of unique genes for a resistance system to acidic environments. The genes adiC Arginine/agmatine antiporter and adiA biodegradative arginine decarboxylase are reported in Escherichia coli as one of three acid resistance systems. The adi gene region is organised into two transcriptional units, adiAY and adiC, which are coordinately regulated but transcribed independently in E. coli. The data also illustrate that the AdiA antiporter system and AdiC decarboxylase are designed to function only at high acidity levels, sufficient to damage the cell (Gong et al. 2003). Furthermore, arginine is more than a common amino acid for protein synthesis; it can also be used as the sole nitrogen source for E. coli and as a carbon source for many other bacteria. It even functions as a substrate for synthesising polyamines essential for the extreme acid resistance of E. coli (Charlier et al. 2019).

Two unique genes, bepE and bepF, which are important in antibiotic resistance and were reported in Brucella suis, were detected in A2. These genes are involved in forming efflux pumps that facilitate the exit of various toxic compounds from the cell. Resistance nodulation-cell division (RND) type efflux pumps are responsible for the multidrug resistance phenotype observed in many clinically relevant species. Furthermore, RND pumps have been implicated in physiological processes, with roles in the virulence mechanisms of several pathogenic bacteria (Martin et al. 2009).

Genes for the biosynthesis of compatible solutes

Ectoine is synthesised from aspartate through a series of enzymatic reactions. First, L-aspartate-phosphate is synthesised by aspartate kinase (LysC) through ATP-dependent phosphorylation of L-aspartate and catalysed by L-aspartate-beta-semialdehyde dehydrogenase (Asd) through an NADPH-dependent reaction to form L-aspartate-semialdehyde (Schwibbert et al. 2011). Aspartate-semialdehyde is transaminated to 2,4-diaminobutyric acid (DABA); this reaction is catalysed by the DABA transaminase (EctB) encoded in the ectB gene. An acetyl group is then transferred to DABA from acetyl-CoA by DABA-N-acetyltransferase (EctA) encoded by the ectA gene, synthesising N-acetyl-1,4-diaminobutyric acid (Ono et al. 1999). Finally, ectoine synthase (EctC), encoded by the ectC gene, catalyses the cyclic condensation of N-acetyl-l-2,4-diaminobutyric acid, leading to the formation of ectoine (Galinski et al. 1997; Ono et al. 1999). Under certain stress conditions, Halomonas elongata and some other halophiles can convert ectoine to 5-hydroxyectoine with ectoine hydroxylase encoded by the ectD gene (Bursy et al. 2007; García-Estepa et al. 2006). All genes for ectoine and hydroxyectoine synthesis were found in A2. The classic configuration of these genes in the Halomonas genus is maintained in A2, with the ectABC genes arranged continuously in a downstream direction. Still, the ectD gene is separated from the other genes in the upstream direction. We compared the gene configurations with different bacterial species (Fig. 11). Furthermore, ectoine can also be used as a carbon source by using the doeABCDX system. The degradation of ectoine begins by hydrolysis of ectoine to N-αacetyl-1-2,4-diaminobutyric acid by DoeA (ectoine hydrolase) followed by deacetylation of N-α-acetyl-1-2,4-diaminobutyric acid to 1–2,4-diaminobutyric acid by DoeB and a transaminase reaction by DoeD to form L-aspartate semialdehyde. Finally, DoeC can oxidise L-aspartate-semialdehyde to aspartate. DoeX is a Lrp/AsnC family transcriptional regulator. The doeABCDX genes are found in the genome of A2, suggesting that it has the putative ability to degrade ectoine.

The betaine synthesis betAB, betI, and betT genes are present in A2. They synthesise betaine from the precursor choline in a two-step process that involves choline dehydrogenase BetB and betaine aldehyde dehydrogenase BetA; these convert choline to betaine aldehyde and betaine aldehyde to betaine, respectively (Cánovas et al. 1996). The betT gene encodes BetT, a high-affinity choline transporter, and betI encodes BetI, a transcriptional repressor of bet genes (Scholz et al. 2016).

Using glutamate and glutamine as compatible solutes is very common in bacteria. The glutamate synthesis pathway depends on glutamate dehydrogenase (Gdh) encoded by gdhA, while glutamine synthesis falls on glutamine synthetase (Gln) encoded by the glnA gene (Kloosterman et al. 2006). In the genome of A2, the genes gdhA and glnA were found to synthesise glutamate and glutamine, respectively.

The proABC genes involved in proline synthesis are found in the genome of A2. The proB gene encodes glutamate 5-kinase, proA encodes glutamate-5-semialdehyde dehydrogenase, and proC encodes pyrroline-5-carboxylate reductase (Goswami et al. 2022). In addition, other genes related to proline metabolism were found, such as proS encoding a proline-tRNA ligase, proV encoding transport system ATP-binding protein, proW encoding a transport system permease protein, and proX encoding transport system substrate-binding protein all related to glycine/betaine-proline transport, putA encodes proline dehydrogenase and putP sodium/proline symporter. The genes for synthesising compatible solutes found in A2 can be seen in supplementary Table S14.

In this study, the sequencing and analysis of the genome of strain A2 was carried out, which was classified as belonging to the species Halomonas salifodinae. The genome has a length of 3,855,926 bp, and the GC content was 67.4%. Genome annotation indicates pathways are directly involved in adaptation to hypersaline environments, such as inorganic ion transport metabolism and amino acid metabolism, in which ectoine synthesis is immersed. The different genes found for secretion systems, ion transport, BGC for secondary metabolites, genomic islands, phage sequences, CRISPR sequences and cas genes, the genes for compatible solutes and biotechnological importance, and the unique genes found in the genome provide extensive information about the genetic profile of the species that can be used in future research. The pangenome and comparative genomics analysis provided conclusive results about the phylogeny of the species Halomonas salifodinae, consistently placing it within a group with Bisbaumannia pacifica, the only representative species of the genus Bisbaumannia belonging to the Halomonacea family. Therefore, Halomonas salifodinae would be reclassified to Bisbaumannia salifodinae following the taxonomic proposal for the genus by de la Haba et al. (2023) with the following taxonomic conclusion:

Description of Bisbaumannia salifodinae comb. nov.

Bisbaumannia salifodinae sa.li.fo.di’nae. L. masc. n. salt (gen. salis), salt; L. fem. n. fodina, mine; N.L. gen. fem. n. salifodinae, of a salt mine

Basonym: Halomonas salifodinae Wang et al. 2008

The description is as given in the original proposal of the basonym (Wang et al. 2008).

At the date of this study, there is no reference genome for the species. However, two genomes are available in the NCBI database, although neither is defined as a reference genome for the species.

JCM 14803 accession number GCA_039522585.1. This genome is 4.3 Mb, and its GC content is 66.5%. Genome Geo loc name: Salt mine in north-western China. Date: Feb 22, 2023

IM328 accession number GCA_036871055.1. This genome is 4 Mb, and its GC content is 67%. Genome Geo loc name: China: A soda-saline lake in Inner Mongolia. Date: Apr 5, 2024

Type strain: BC 7; CGMCC 1.6774; JCM 14803

Type strain 16S rRNA gene sequence accession number: EF527873.1

Acknowledgements:

This work constitutes a requirement and is part of the productivity of studies aimed at obtaining the degree of Doctor en Ciencias Biológicas, for which we thank the Posgrado en Ciencias Biológicas of the Universidad Nacional Autónoma Mexico. The study received funding from the Consejo Nacional de Humanidades Ciencia y Tecnología (CONAHCyT) as a doctoral scholarship.

Conflict of interest

The authors declare that there is no conflict of interest.

Author Contributions

All authors contributed to the study's conception and design. Alberto León Lemus and Martha Martínez García performed material preparation, data collection, and analysis. Luis Alberto León Lemus wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript.

Data Availability

This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accession JBDUMR000000000. The version described in this paper is version JBDUMR010000000. The genome sequence data could be accessed under the accession number (BioProject PRJNA1114308, Biosample SAMN41481530) in the NCBI database (www.ncbi.nlm.nih. gov).

Consent to participate

All co-authors gave their consent to participate in the development of this work.

Consent for publication

All co-authors gave their consent to publish this work.

Arakawa T, Timasheff SN (1985) The stabilization of proteins by osmolytes. Biophys J 47:411–414. http://dx.doi.org/10.1016/s0006-3495(85)83932-1
Arndt D, Grant JR, Marcu A, Sajed T, Pon A, Liang Y, et al. (2016) PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res 44(W1): W16–21. http://dx.doi.org/10.1093/nar/gkw387
Arora A, Ha C, Park CB (2004) Inhibition of insulin amyloid formation by small stress molecules. FEBS Lett 564:121–125. http://dx.doi.org/10.1016/s0014-5793(04)00326-6
Ashraf G, Greig N, Khan T, Hassan I, Tabrez S, Shakil S, et al. (2014) Protein misfolding and aggregation in Alzheimer’s disease and type 2 diabetes mellitus. CNS Neurol Disord Drug Targets 13:1280–1293. http://dx.doi.org/10.2174/1871527313666140917095514
Bazazzadegan N, Dehghan Shasaltaneh M, Saliminejad K, Kamali K, Banan M, Nazari R, et al. (2017) Effects of ectoine on behaviour and candidate genes expression in ICV-STZ rat model of sporadic Alzheimer’s disease. Adv Pharm Bull 7:629–636. http://dx.doi.org/10.15171/apb.2017.075
Benson G. Tandem repeats finder: a program to analyse DNA sequences (1999) Nucleic Acids Res 27:573–580. http://dx.doi.org/10.1093/nar/27.2.573
Bertelli C, Tilley KE, Brinkman FSL (2019) Microbial genomic island discovery, visualization and analysis. Brief Bioinform 20:1685–1698. http://dx.doi.org/10.1093/bib/bby042
Besemer J. (2001) GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res 29:2607–2618. http://dx.doi.org/10.1093/nar/29.12.2607
Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F, Alanjary M, et al. (2023) antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures, and visualisation. Nucleic Acids Res 51:46–50. http://dx.doi.org/10.1093/nar/gkad344
Bobay L-M, Touchon M, Rocha EPC (2014) Pervasive domestication of defective prophages by bacteria. Proc Natl Acad Sci U S A 111:12127–12132. http://dx.doi.org/10.1073/pnas.1405336111
Bolen DW, Baskakov IV (2001) The osmophobic effect: natural selection of a thermodynamic force in protein folding Edited by D. Draper. J Mol Biol 310:955–963. http://dx.doi.org/10.1006/jmbi.2001.4819
Bondy-Denomy J, Davidson AR (2014) When a virus is not a parasite: the beneficial effects of prophages on bacterial fitness. J Microbiol 52:235–242. http://dx.doi.org/10.1007/s12275-014-4083-3
Borges N, Ramos A, Raven N, Sharp R, Santos H (2002) Comparative study of the thermostabilizing properties of mannosylglycerate and other compatible solutes on model enzymes. Extremophiles 6:209–216. http://dx.doi.org/10.1007/s007920100236
Brown AD (1976) Microbial water stress. Bacteriol Rev 40:803–846. http://dx.doi.org/10.1128/br.40.4.803-846.1976
Buchfink B, Reuter K, Drost H-G (2021) Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods 18:366–368. http://dx.doi.org/10.1038/s41592-021-01101-x
Bujak T, Zagórska-Dziok M, Nizioł-Łukaszewska Z (2020) Complexes of ectoine with the anionic surfactants as active ingredients of cleansing cosmetics with reduced irritating potential. Molecules 25:1433. http://dx.doi.org/10.3390/molecules25061433
Bursy J, Pierik AJ, Pica N, Bremer E (2007) Osmotically induced synthesis of the compatible solute hydroxyectoine is mediated by an evolutionarily conserved ectoine hydroxylase. J Biol Chem 282:31147–31155. http://dx.doi.org/10.1074/jbc.m704023200
Cánovas D, Vargas C, Csonka LN, Ventosa A, Nieto JJ (1996) Osmoprotectants in Halomonas elongata: high-affinity betaine transport system and choline-betaine pathway. J Bacteriol 178:7221–7226. http://dx.doi.org/10.1128/jb.178.24.7221-7226.1996
Cantera S, Phandanouvong-Lozano V, Pascual C, García-Encina PA, Lebrero R, Hay A, et al. (2020) A systematic comparison of ectoine production from upgraded biogas using Methylomicrobium alcaliphilum and a mixed haloalkaliphilic consortium. Waste Manag 102:773–781. http://dx.doi.org/10.1016/j.wasman.2019.11.043
Carpi FM, Coman MM, Silvi S, Picciolini M, Verdenelli MC, Napolioni V (2022) Comprehensive pan‐genome analysis of Lactiplantibacillus plantarum complete genomes. J Appl Microbiol 132:592–604. http://dx.doi.org/10.1111/jam.15199
Chan PP, Lowe TM (2019) TRNAscan-SE: Searching for tRNA genes in genomic sequences. In: Methods in Molecular Biology, New York, Springer New York, pp. 1–14. https://doi.org/10.1007/978-1-4939-9173-0_1
Charlier D, Bervoets I (2019) Regulation of arginine biosynthesis, catabolism and transport in Escherichia coli. Amino Acids 51:1103–1127. http://dx.doi.org/10.1007/s00726-019-02757-8
Chen Y, Yang Y, Ji X, Zhao R, Li G, Gu Y, et al. (2020) The SCIFF‐derived ranthipeptides participate in quorum sensing in solventogenic clostridia. Biotechnol J 15. http://dx.doi.org/10.1002/biot.202000136
Chepuri V, Lemieux L, Au DC, Gennis RB (1990) The sequence of the cyo operon indicates substantial structural similarities between the cytochrome o ubiquinol oxidase of Escherichia coli and the aa₃-type family of cytochrome c oxidases. J Biol Chem 265:11185–11192. http://dx.doi.org/10.1016/s0021-9258(19)38574-6
Chevance FFV, Hughes KT (2008) Coordinating assembly of a bacterial macromolecular machine. Nat Rev Microbiol 6:455–465. http://dx.doi.org/10.1038/nrmicro1887
Choi SK, Schurig-Briccio L, Ding Z, Hong S, Sun C, Gennis RB (2017) Location of the substrate binding site of the cytochrome bo₃ ubiquinol oxidase from Escherichia coli. J Am Chem Soc139:8346–8354. http://dx.doi.org/10.1021/jacs.7b03883
Chun J, Oren A, Ventosa A, Christensen H, Arahal DR, da Costa MS, et al. (2018) Proposed minimal standards for the use of genome data for the taxonomy of prokaryotes. Int J Syst Evol Microbiol 68:461–466. http://dx.doi.org/10.1099/ijsem.0.002516
Clegg JS, Seitz P, Seitz W, Hazlewood CF (1982) Cellular responses to extreme water loss: The water-replacement hypothesis. Cryobiology 19:306–316. http://dx.doi.org/10.1016/0011-2240(82)90159-6
Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Sun Y, et al. (2014) Ribosomal Database Project: data and tools for high throughput rRNA analysis. Nucleic Acids Res 42:633–642. http://dx.doi.org/10.1093/nar/gkt1244
Couvin D, Bernheim A, Toffano-Nioche C, Touchon M, Michalik J, Néron B, et al. (2018) CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins. Nucleic Acids Res 46:246–251. http://dx.doi.org/10.1093/nar/gky425
Dao V-A, Bilstein A, Overhagen S, Géczi L, Baráth Z, Mösges R (2018) Effectiveness, tolerability, and safety of ectoine-containing mouthwash versus those of a calcium phosphate mouthwash for the treatment of chemotherapy-induced oral mucositis: A prospective, active-controlled, non-interventional study. Oncology and Therapy, 6:59-72 https://doi.org/10.1007/s40487-018-0060-z
Dao V-A, Overhagen S, Bilstein A, Kolot C, Sonnemann U, Mösges R (2019) Ectoine lozenges in the treatment of acute viral pharyngitis: a prospective, active-controlled clinical study. Eur Arch Otorhinolaryngol 276:775–783. http://dx.doi.org/10.1007/s00405-019-05324-9
de la Haba RR, Arahal DR, Sánchez-Porro C, Chuvochina M, Wittouck S, Hugenholtz P, et al. (2023) A long-awaited taxogenomic investigation of the family Halomonadaceae. Front Microbiol 14. http://dx.doi.org/10.3389/fmicb.2023.1293707
de la Haba RR, Márquez MC, Papke RT, Ventosa A (2012) Multilocus sequence analysis of the family Halomonadaceae. Int J Syst Evol Microbiol 62:520–538. http://dx.doi.org/10.1099/ijs.0.032938-0
Di Gioacchino M, Bruni F, Sodo A, Imberti S, Ricci MA (2019) Ectoine hydration, aggregation and influence on water structure. Mol Phys 117:3311–3319. http://dx.doi.org/10.1080/00268976.2019.1649484
Diken E, Ozer T, Arikan M, Emrence Z, Oner ET, Ustek D, et al. (2015) Genomic analysis reveals the biotechnological and industrial potential of levan producing halophilic extremophile, Halomonas smyrnensis AAD6T. Springerplus 4: 1-11. http://dx.doi.org/10.1186/s40064-015-1184-3
Dobson SJ, Franzmann PD (1996) Unification of the Genera Deleya (Baumann et al. 1983), Halomonas (Vreeland et al. 1980), and Halovibrio (Fendrich 1988) and the Species Paracoccus halodenitrificans (Robinson and Gibbons 1952) into a Single Genus, Halomonas, and Placement of the Genus Zymobacter in the Family Halomonadaceae. Int J Syst Bacteriol. 46:550–558. http://dx.doi.org/10.1099/00207713-46-2-550
Džunková M, La Clair JJ, Tyml T, Doud D, Schulz F, Piquer-Esteban S, et al. (2023) Synthase-selected sorting approach identifies a beta-lactone synthase in a nudibranch symbiotic bacterium. Microbiome 11:130. http://dx.doi.org/10.1186/s40168-023-01560-8
Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol 7:e1002195. http://dx.doi.org/10.1371/journal.pcbi.1002195
Eichel A, Wittig J, Shah-Hosseini K, Mösges R (2013) A prospective, controlled study of SNS01 (ectoine nasal spray) compared to BNO-101 (phytotherapeutic dragées) in patients with acute rhinosinusitis. Curr Med Res Opin 29:739–746. http://dx.doi.org/10.1185/03007995.2013.800474
Forte E, Borisov VB, Siletsky SA, Petrosino M, Giuffrè A (2019) In the respiratory chain of Escherichia coli cytochromes bd-I and bd-II are more sensitive to carbon monoxide inhibition than cytochrome bo₃. Biochim Biophys Acta Bioenerg 1860:148088. http://dx.doi.org/10.1016/j.bbabio.2019.148088
Furusho K, Yoshizawa T, Shoji S (2005) Ectoine alters subcellular localization of inclusions and reduces apoptotic cell death induced by the truncated Machado–Joseph disease gene product with an expanded polyglutamine stretch. Neurobiol Dis 20:170–178. http://dx.doi.org/10.1016/j.nbd.2005.02.011
Galinski EA, Stein M, Amendt B, Kinder M (1997) The kosmotropic (structure-forming) effect of compensatory solutes. Comp Biochem Physiol A Comp Physiol 117:357–365. http://dx.doi.org/10.1016/s0300-9629(96)00275-7
Gao X-Y, Zhi X-Y, Li H-W, Zhou Y, Lapidus A, Han J, et al. (2015) Draft genome sequence of Halomonas lutea strain YIM 91125T (DSM 23508T) isolated from the alkaline Lake Ebinur in Northwest China. Stand Genomic Sci 10:1-9. http://dx.doi.org/10.1186/1944-3277-10-1
García-Estepa R, Argandoña M, Reina-Bueno M, Capote N, Iglesias-Guerra F, Nieto JJ, et al. (2006) The ectD gene, which is involved in the synthesis of the compatible solute hydroxyectoine, is essential for thermoprotection of the halophilic bacterium Chromohalobacter salexigens. J Bacteriol 188:3774–3784. http://dx.doi.org/10.1128/jb.00136-06
Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, et al. (2009) Rfam: updates to the RNA families database. Nucleic Acids Res 37:136–140. http://dx.doi.org/10.1093/nar/gkn766
Goel C, Shakir C, Tesfaye A, Raghavanpillai Sabu K, Idhayadhulla A, Manilal A, et al. (2022) Antibiofilm Potential of Alpha-Amylase from a Marine Bacterium, Pantoea agglomerans. Can J Infect Dis Med Microbiol 2022:1–10. http://dx.doi.org/10.1155/2022/7480382
Gong S, Richard H, Foster JW (2003) YjdE (AdiC) Is the arginine: Agmatine antiporter essential for arginine-dependent acid resistance in Escherichia coli. J Bacteriol 185:4402–4409. http://dx.doi.org/10.1128/jb.185.15.4402-4409.2003
Goswami G, Hazarika DJ, Chowdhury N, Bora SS, Sarmah U, Naorem RS, et al. (2022) Proline confers acid stress tolerance to Bacillus megaterium G18. Sci Rep 12: 8875. http://dx.doi.org/10.1038/s41598-022-12709-0
Green ER, Mecsas J (2016) Bacterial secretion systems: An overview. In: Virulence Mechanisms of Bacterial Pathogens. Washington, DC, USA: ASM Press pp. 213–239. https://doi.org/10.1128/9781555819286.ch8
Grissa I, Vergnaud G, Pourcel C (2007) CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res 35(Web Server):W52–57. http://dx.doi.org/10.1093/nar/gkm360
He L, Zhao L, Li Q, Huang L, Qin Y, Zhuang Z, et al. (2023) Flagellar gene fliP contributes to the virulence of Pseudomonas plecoglossicida by regulating its motility. Aquaculture 576:739874. http://dx.doi.org/10.1016/j.aquaculture.2023.739874
Heinrich U, Garbe B, Tronnier H (2007) In vivo assessment of Ectoin: A randomized, vehicle-controlled clinical trial. Skin Pharmacol Physiol 20:211–218. http://dx.doi.org/10.1159/000103204
Horvath P, Barrangou R (2010) CRISPR/Cas, the immune system of bacteria and Archaea. Science 327:167–170. http://dx.doi.org/10.1126/science.1179555
Hsiao W, Wan I, Jones SJ, Brinkman FSL (2003). IslandPath: aiding detection of genomic islands in prokaryotes. Bioinformatics 19:418–420. http://dx.doi.org/10.1093/bioinformatics/btg004
Imhoff JF, Rahn T, Künzel S, Keller A, Neulinger SC (2020) Osmotic adaptation and compatible solute biosynthesis of phototrophic bacteria as revealed from genome analyses. Microorganisms 9:46. http://dx.doi.org/10.3390/microorganisms9010046
Jackman SD, Vandervalk BP, Mohamadi H, Chu J, Yeo S, Hammond SA, et al. (2017) ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter. Genome Res 27:768–777. http://dx.doi.org/10.1101/gr.214346.116
Johnson MK, Rees DC, Adams MWW (1996) Tungstoenzymes. Chem Rev 96:2817–2840. http://dx.doi.org/10.1021/cr950063d
Kanapathipillai M, Ku SH, Girigoswami K, Park CB (2008) Small stress molecules inhibit aggregation and neurotoxicity of prion peptide 106–126. Biochem Biophys Res Commun 365:808–813. http://dx.doi.org/10.1016/j.bbrc.2007.11.074
Keshavarz T, Roy I (2010) Polyhydroxyalkanoates: bioplastics with a green agenda. Curr Opin Microbiol 13:321–326. http://dx.doi.org/10.1016/j.mib.2010.02.006
Kloosterman TG, Hendriksen WT, Bijlsma JJE, Bootsma HJ, van Hijum SAFT, Kok J, et al. (2006) Regulation of glutamine and glutamate metabolism by GlnR and GlnA in streptococcus pneumoniae. J Biol Chem 281:25097–25109. http://dx.doi.org/10.1074/jbc.m601661200
Kolp S, Pietsch M, Galinski EA, Gütschow M (2006) Compatible solutes as protectants for zymogens against proteolysis. Biochim Biophys Acta Proteins Proteom 1764:1234–1242. http://dx.doi.org/10.1016/j.bbapap.2006.04.015
Kraegeloh A, Amendt B, Kunte HJ (2005) Potassium transport in a halophilic member of the bacteria domain: Identification and characterization of the K + uptake systems TrkH and TrkI from Halomonas elongata DSM 2581 T. J Bacteriol 187:1036–1043. http://dx.doi.org/10.1128/jb.187.3.1036-1043.2005
Kraegeloh A, Kunte H (2002) Novel insights into the role of potassium for osmoregulation in Halomonas elongata. Extremophiles 6:453–462. http://dx.doi.org/10.1007/s00792-002-0277-4
Kurz M (2008) Compatible solute influence on nucleic acids: Many questions but few answers. Saline Systems 4:6. http://dx.doi.org/10.1186/1746-1448-4-6
Kushner DJ (1988) Physiology of halophilic eubacteria. Halophilic bacteria 109–138.
Lagesen K, Hallin P, Rødland EA, Stærfeldt H-H, Rognes T, Ussery DW (2007) RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res 35:3100–3108. http://dx.doi.org/10.1093/nar/gkm160
Lin S-H, Liao Y-C (2013) CISA: Contig integrator for sequence assembly of bacterial genomes. PLoS One 8:e60843. http://dx.doi.org/10.1371/journal.pone.0060843
Lin Y, Fan H, Hao X, Johnstone L, Hu Y, Wei G, et al. (2012) Draft genome sequence of Halomonas sp. strain HAL1, a moderately halophilic arsenite-oxidizing bacterium isolated from Gold-Mine soil. J Bacteriol 194:199–200. http://dx.doi.org/10.1128/jb.06359-11
Litzner BR, Caton TM, Schneegurt MA (2006) Carbon substrate utilization, antibiotic sensitivity, and numerical taxonomy of bacterial isolates from the Great Salt Plains of Oklahoma. Arch Microbiol 185:286–296. http://dx.doi.org/10.1007/s00203-006-0096-6
Liu Y, Bolen DW (1995) The peptide backbone plays a dominant role in protein stabilization by naturally occurring osmolytes. Biochemistry 34:12884–2891. http://dx.doi.org/10.1021/bi00039a051
Lowe TM, Chan PP (2016) tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res 44:W54–W57. http://dx.doi.org/10.1093/nar/gkw413
Lucke M, Correa MG, Levy A (2020) The role of secretion systems, effectors, and secondary metabolites of beneficial rhizobacteria in interactions with plants and microbes. Front Plant Sci 11: 589416. http://dx.doi.org/10.3389/fpls.2020.589416
Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. (2012) SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1: 2047-217X. http://dx.doi.org/10.1186/2047-217x-1-18
Ma Z, Wu C, Zhu L, Chang R, Ma W, Deng Y, et al. (2022) Bioactivity profiling of the extremolyte ectoine as a promising protectant and its heterologous production. 3 Biotech 12:331. http://dx.doi.org/10.1007/s13205-022-03370-5
Margesin R, Schinner F (2001) Potential of halotolerant and halophilic microorganisms for biotechnology. Extremophiles 5:73–83. http://dx.doi.org/10.1007/s007920100184
Martin FA, Posadas DM, Carrica MC, Cravero SL, O’Callaghan D, Zorreguieta A (2009) Interplay between two RND systems mediating antimicrobial resistance in Brucella suis. J Bacteriol 191:2530–2540. http://dx.doi.org/10.1128/jb.01198-08
Meier-Kolthoff JP, Carbasse JS, Peinado-Olarte RL, Göker M (2022) TYGS and LPSN: a database tandem for fast and reliable genome-based classification and nomenclature of prokaryotes. Nucleic Acids Res 50(D1):D801–817. http://dx.doi.org/10.1093/nar/gkab902
Melin F, Sabuncu S, Choi SK, Leprince A, Gennis RB, Hellwig P (2018) Role of the tightly bound quinone for the oxygen reaction of cytochrome bo₃ oxidase from Escherichia coli. FEBS Lett 592:3380–3387. http://dx.doi.org/10.1002/1873-3468.13263
Natale P, Brüser T, Driessen AJM (2008) Sec- and Tat-mediated protein secretion across the bacterial cytoplasmic membrane—Distinct translocases and mechanisms. Biochim Biophys Acta Biomembr 1778:1735–1756. http://dx.doi.org/10.1016/j.bbamem.2007.07.015
Olson RD, Assaf R, Brettin T, Conrad N, Cucinell C, Davis JJ, et al. (2023) Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR. Nucleic Acids Res 51(D1):D678–689. http://dx.doi.org/10.1093/nar/gkac1003
Ono H, Sawada K, Khunajakr N, Tao T, Yamamoto M, Hiramoto M, et al. 1999 Characterization of biosynthetic enzymes for ectoine as a compatible solute in a moderately halophilic Eubacterium, Halomonas elongata. J Bacteriol 181:91–99. http://dx.doi.org/10.1128/jb.181.1.91-99.1999
Oren A (2008) Microbial life at high salt concentrations: phylogenetic and metabolic diversity. Saline Systems 4:1-3. http://dx.doi.org/10.1186/1746-1448-4-2
Otrelo-Cardoso A, Nair R, Correia M, Rivas M, Santos-Silva T (2014) TupA: A tungstate binding protein in the periplasm of Desulfovibrio alaskensis G20. Int J Mol Sci 15(7):11783–11798. http://dx.doi.org/10.3390/ijms150711783
Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MTG, et al. (2015) Roary: rapid large-scale prokaryote pangenome analysis. Bioinformatics 31:3691–3693. http://dx.doi.org/10.1093/bioinformatics/btv421
Pérez V, Moltó JL, Lebrero R, Muñoz R (2022) Ectoine production from biogas: A sensitivity analysis. Effect of local commodity prices, economy of scale, market trends and biotechnological limitations. J Clean Prod 369:133440. http://dx.doi.org/10.1016/j.jclepro.2022.133440
Philip S, Keshavarz T, Roy I (2007) Polyhydroxyalkanoates: biodegradable polymers with a range of applications. J Chem Technol Biotechnol 82:233–247. http://dx.doi.org/10.1002/jctb.1667
Trifinopoulos J, Nguyen LT, von Haeseler A, Minh BQ (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucl. Acids Res. 44:W232-W235. https://doi.org/10.1093/nar/gkw256
Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A (2020) Using SPAdes DE Novo Assembler. Curr Protoc Bioinformatics 70:e102. http://dx.doi.org/10.1002/cpbi.102
Puustinen A, Finel M, Haltia T, Gennis RB, Wikstrom M (1991) Properties of the two terminal oxidases of Escherichia coli. Biochemistry 30:3936–3942. http://dx.doi.org/10.1021/bi00230a019
Rajeev L, Garber ME, Zane GM, Price MN, Dubchak I, Wall JD, et al. (2019) A new family of transcriptional regulators of tungstoenzymes and molybdate/tungstate transport. Environ Microbiol 21:784–799. http://dx.doi.org/10.1111/1462-2920.14500
Refaat R, Sarhan D, Kotb M, El-Abd E, El-Bassiouni E (2018) Post-irradiation protective effects of ectoine on brain and testicles in male mice. Pharmacol Rep 70:304–308. http://dx.doi.org/10.1016/j.pharep.2017.10.002
Rieckmann T, Gatzemeier F, Christiansen S, Rothkamm K, Münscher A (2019) The inflammation-reducing compatible solute ectoine does not impair the cytotoxic effect of ionizing radiation on head and neck cancer cells. Sci Rep 9:6594. http://dx.doi.org/10.1038/s41598-019-43040-w
Roberts MF (2005) Organic compatible solutes of halotolerant and halophilic microorganisms. Saline Systems 1:1-30. http://dx.doi.org/10.1186/1746-1448-1-5
Robinson SL, Christenson JK, Wackett LP (2019) Biosynthesis and chemical diversity of β-lactone natural products. Nat Prod Rep 36:458–475. http://dx.doi.org/10.1039/c8np00052b
Russell AB, Peterson SB, Mougous JD (2014) Type VI secretion system effectors: poisons with a purpose. Nat Rev Microbiol 12:137–148. http://dx.doi.org/10.1038/nrmicro3185
Russo DM, Williams A, Edwards A, Posadas DM, Finnie C, Dankert M, et al. (2006) Proteins exported via the PrsD-PrsE type I secretion system and the acidic exopolysaccharide are involved in biofilm formation by Rhizobium leguminosarum. J Bacteriol 188:4474–4486. http://dx.doi.org/10.1128/jb.00246-06
Saha S, Bridges S, Magbanua ZV, Peterson DG (2008) Empirical comparison of ab initio repeat finding programs. Nucleic Acids Res 36:2284–2294. http://dx.doi.org/10.1093/nar/gkn064
Scholz A, Stahl J, de Berardinis V, Müller V, Averhoff B (2016) Osmotic stress response in Acinetobacter baylyi: identification of a glycine–betaine biosynthesis pathway and regulation of osmoadaptive choline uptake and glycine–betaine synthesis through a choline‐responsive BetI repressor. Environ Microbiol Rep 8:316–322. http://dx.doi.org/10.1111/1758-2229.12382
Schröter M-. A, Meyer S, Hahn MB, Solomun T, Sturm H, Kunte HJ (2017) Ectoine protects DNA from damage by ionizing radiation. Sci Rep 7:15272. http://dx.doi.org/10.1038/s41598-017-15512-4
Schwibbert K, Marin-Sanguino A, Bagyan I, Heidrich G, Lentzen G, Seitz H, et al. (2011) A blueprint of ectoine metabolism from the genome of the industrial producer Halomonas elongata DSM 2581T. Environ Microbiol 13:1973–1994. http://dx.doi.org/10.1111/j.1462-2920.2010.02336.x
Seemann T (2014) Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069. http://dx.doi.org/10.1093/bioinformatics/btu153
Sousa FL, Alves RJ, Ribeiro MA, Pereira-Leal JB, Teixeira M, Pereira MM (2012) The superfamily of heme–copper oxygen reductases: Types and evolutionary considerations. Biochim Biophys Acta Bioenerg 1817:629–637. http://dx.doi.org/10.1016/j.bbabio.2011.09.020
Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular evolutionary genetics analysis version 11. Mol Biol Evol 38:3022–3027. http://dx.doi.org/10.1093/molbev/msab120
Timasheff SN (2002) Protein-solvent preferential interactions, protein hydration, and the modulation of biochemical reactions by solvent components. Proc Natl Acad Sci U S A 99:9721–9726. http://dx.doi.org/10.1073/pnas.122225399
Timofeeva AM, Galyamova MR, Sedykh SE (2022) Bacterial siderophores: Classification, biosynthesis, perspectives of use in agriculture. Plants 11:3065. http://dx.doi.org/10.3390/plants11223065
Touchon M, Bobay L-M, Rocha EPC (2014) The chromosomal accommodation and domestication of mobile genetic elements. Curr Opin Microbiol 22:22–29. http://dx.doi.org/10.1016/j.mib.2014.09.010
Valent QA (1998) The Escherichia coli SRP and SecB targeting pathways converge at the translocon. EMBO J 17:2504–2512. http://dx.doi.org/10.1093/emboj/17.9.2504
Ventosa A, Nieto JJ, Oren A (1998) Biology of moderately halophilic aerobic bacteria. Microbiol Mol Biol Rev 62:504–544. http://dx.doi.org/10.1128/mmbr.62.2.504-544.1998
Vreeland RH, Martin EL (1980) Growth characteristics, effects of temperature, and ion specificity of the halotolerant bacterium Halomonas elongata. Can J Microbiol 26:746–752. http://dx.doi.org/10.1139/m80-130
Wang Y, Wu Y-H, Wang C-S, Xu X-W, Oren A, Zhu X-F, et al. (2008) Halomonas salifodinae sp. nov., a halophilic bacterium isolated from a salt mine in China. Int J Syst Evol Microbiol 58:2855–2858. http://dx.doi.org/10.1099/ijs.0.2008/000729-0
Wu S, Wang L, Gan R, Tong T, Bian H, Li Z, et al. (2018) Signature Arsenic Detoxification Pathways in Halomonas sp. strain GFAJ-1. MBio 9: 10-1128. http://dx.doi.org/10.1128/mbio.00515-18
Yamaguchi T, Tsutsumi F, Putnoky P, Fukuhara M, Nakamura T (2009) pH-dependent regulation of the multi-subunit cation/proton antiporter Pha1 system from Sinorhizobium meliloti. Microbiology 155:2750–2756. http://dx.doi.org/10.1099/mic.0.028563-0
Yang D-S, Yip CM, Huang THJ, Chakrabartty A, Fraser PE (1999) Manipulating the amyloid-β aggregation pathway with chemical chaperones. J Biol Chem 274:32970–32974. http://dx.doi.org/10.1074/jbc.274.46.32970
Yang Y, Hu X, Zhang X, Chen X, Wei X, Chen Z, et al. (2022) Acclimatization of resorcinol results in microbial community dynamics and physicochemical characteristics of aerobic activated sludge. J Clean Prod 364:132467. http://dx.doi.org/10.1016/j.jclepro.2022.132467
Yoon S-H, Ha S-M, Lim J, Kwon S, Chun J (2017) A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110:1281–1286. http://dx.doi.org/10.1007/s10482-017-0844-4
Zhai L, Xie J, Feng H, Sun S, Cheng K, Yao S (2021) Mechanism of TonB-dependent transport system in Halomonas alkalicola CICC 11012s in response to alkaline stress. Extremophiles 25:39–49. http://dx.doi.org/10.1007/s00792-020-01209-6
Zhang T, Cui T, Cao Y, Li Y, Li F, Zhu D, et al. (2022) Whole genome sequencing of the halophilic Halomonas qaidamensis XH36, a novel species strain with high ectoine production. Antonie Van Leeuwenhoek 115:545–559. http://dx.doi.org/10.1007/s10482-022-01709-9

No competing interests reported.

Supplementarymaterial.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Comparative genomic analysis and genome sequence of Halomonas salifodinae strain A2, isolated from the Zapotitlán Salinas Valley Puebla, México

Status:

Version 1

Abstract

Figures

Introduction

Materials and Method

Results and discussion

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1