Amphibian skin-associated Pigmentiphaga: Genome sequence and occurrence across geography and hosts
Authors:
Molly C. Bletz aff001; Boyke Bunk aff003; Cathrin Spröer aff003; Peter Biwer aff004; Silke Reiter aff005; Falitiana C. E. Rabemananjara aff006; Stefan Schulz aff004; Jörg Overmann aff003; Miguel Vences aff002
Authors place of work:
Department of Biology, University of Massachusetts Boston, Boston, MA, United States of America
aff001; Zoological Institute, Technische Universitt Braunschweig, Braunschweig, Germany
aff002; DSMZ, German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany
aff003; Institute of Organic Chemistry, Technische Universität Braunschweig, Braunschweig, Germany
aff004; Institute for Insect Biotechnology, Justus Liebig University Giessen, Giessen, Germany
aff005; Department of Zoology and Animal Biodiversity, University of Antananarivo, Antananarivo, Madagascar
aff006; Microbiology Institute, Technische Universität Braunschweig, Braunschweig, Germany
aff007
Published in the journal:
PLoS ONE 14(10)
Category:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223747
Summary
The bacterial communities colonizing amphibian skin have been intensively studied due to their interactions with pathogenic chytrid fungi that are causing drastic amphibian population declines. Bacteria of the family Alcaligenaceae, and more specifically of the genus Pigmentiphaga, have been found to be associated specifically to arboreal frogs. Here we analyze their occurrence in a previously assembled global skin microbiome dataset from 205 amphibian species. Pigmentiphaga made up about 5% of the total number of reads in this global dataset. They were mostly found in unrelated arboreal frogs from Madagascar (Mantellidae and Hyperoliidae), but also occurred at low abundances on Neotropical frogs. Based on their 16S sequences, most of the sequences belong to a clade within Pigmentiphaga not assignable to any type strains of the five described species of the genus. One isolate from Madagascar clustered with Pigmentiphaga aceris (>99% sequence similarity on 16S rRNA gene level). Here, we report the full genome sequence of this bacterium which, based on 16S sequences of >97% similarity, has previously been found on human skin, floral nectar, tree sap, stream sediment and soil. Its genome consists of a single circular chromosome with 6,165,255 bp, 5,300 predicted coding sequences, 57 tRNA genes, and three rRNA operons. In comparison with other known Pigmentiphaga genomes it encodes a higher number of genes associated with environmental information processing and cellular processes. Furthermore, it has a biosynthetic gene cluster for a nonribosomal peptide syntethase, and bacteriocin biosynthetic genes can be found, but clusters for β-lactones present in other comparative Pigmentiphaga genomes are lacking.
Keywords:
Comparative genomics – Sequence analysis – Sequence alignment – Phylogenetic analysis – Amphibians – Amphibian genomics – Microbiome – Multiple alignment calculation
Introduction
The cutaneous microbiome of amphibians has become a well-studied system, triggered by the rise of the pathogenic fungi, Batrachochytrium dendrobatidis (Bd) and B. salamandrivorans (Bsal). These fungi colonize the amphibian skin and are causing drastic population declines and extinctions in this class of animals [1,2]. The bacterial communities associated to amphibians interact with these fungi and some of these bacteria have the potential to inhibit the growth of Bd and Bsal, thus providing protection to their hosts [3].
Recent research based on next-generation amplicon sequencing of the 16S rRNA gene show that bacterial communities on the skin of amphibians are predominantly composed of common bacteria recruited from environmental reservoirs [4], and their dominant members can be readily cultured [5]. Unsurprisingly these communities are strongly controlled by environmental factors, e.g., bioclimate [6] and microhabitat [7–9]. However, clear differences have also been found between co-occurring hosts [7,10,11], suggesting that the skin mucosal differences among amphibian species act as filters determining which bacterial species are recruited into the community.
Considering the strong environmental influences on the amphibian cutaneous microbiome, it is of particular interest to analyze in more depth those bacteria that regularly colonize this habitat but are restricted to certain host taxa or host ecomorphs. An in-depth understanding of the genomic background, variation, phylogenetic relationships, and distribution of these bacteria may offer clues to understand which traits predispose them to successfully colonize this particular habitat.
This study was triggered by the observation that operational taxonomic units (OTUs) of the family Alcaligenaceae were strongly associated to arboreal ecomorphs in a study on Madagascan amphibians [12], and were also found to be a common member of the cutaneous microbiome of several Central American tree frogs, such as Agalychnis callidryas [13,14]. The family was represented by a pure culture isolate identified as Pigmentiphaga by 16S sequences in our bacterial culture collection from Madagascar frog skin [15], and also the sequences of Alcaligenaceae OTUs identified by amplicon sequences from Madagascar frogs.
Pigmentiphaga is a genus of the family Alcaligenaceae, assigned to the order Burkholderiales order within the Betaproteobacteria, and currently containing five species: the type species, P. kullae, plus P. aceris, P. daeguensis, P. litoralis, and P. solis [16–20]. According to these descriptions, the genus contains gram-negative, facultatively anaerobic, motile or nonmotile, catalase- and oxidase-positive, rod-shaped bacteria, found in diverse environments: P. daeguensis from dye wastewater, P. litoralis from tidal sediment, P. soli from soil, P, aceris from tree sap [17–20], and an unidentified species from tree-associated nematodes [21]. Furthermore, Pigmentiphaga have also been isolated from human clinical material [22], and genome sequences are available from these isolates [23]. Pigmentiphaga have been studied in the context of their ability to degrade azo dyes and aniline [16,24], and their role also has been discussed in the context of biphenyl-degradation [25].
Here, we analyze the occurrence of OTUs assigned to Pigmentiphaga on the skin of amphibians across taxa, geography and ecomorphs, assemble the full genome sequence of one Pigmentiphaga isolate obtained from a Madagascan frog, and analyze the phylogenetic relationships and differentiation of this isolate.
Methods
Analysis of amplicon data
To explore the distribution of the focal bacterial groups on amphibian hosts we used a recently published global dataset of amphibian skin microbiomes [6], and extracted all OTUs assigned to the family Alcaligenaceae and genus Pigmentiphaga. This global dataset is a compilation of targeted amplicon sequencing data of the 16S rRNA gene (V4 region) generated on Illumina sequencing platforms. It contains skin microbiome samples from 2,349 post-metamorphic amphibians, comprising 27 amphibian families (205 species) collected from 12 countries (5 continents) [6]. In this study, quality-filtered Illumina reads were classified into sub-operational taxonomic units (sOTUs) using the deblur pipeline [26]. These data were subsequently rarified and taxonomy was assigned using the Ribosomal Database Classifier [27] in QIIME [28] (see [6] for detailed methods). We examined the distribution of the genus Pigmentiphaga across locations (i.e. countries), host species, and host ecomorphological classes. To explore the distribution of the focal bacteria across host phylogeny, a phylogenetic tree of arboreal and scansorial host genera was built using timetree.org [29]. All plots were produced with ggplot2 [30].
Isolate sampling
The bacterium for which we here report the full genome sequence was isolated on 1% tryptone agar from a skin swab of a single individual of the amphibian species, Mantella crocea at Torotorofotsy "Prolemur Camp" near Andasibe, Madagascar (-18.7709 S, 48.43222 E). This individual frog was captured by gloved hands and kept in a sterile Whirl-Pak bag for no longer than 1 hour before sampling. Frog skin microbiota were sampled by first rinsing the skin to remove transient microbes and then swabbing the ventral skin with a sterile rayon tipped swab 10 times. Swabs were stored in Tryptic Soy Yeast Extract media with 20% Glycerol and frozen until processing. The frog was immediately release at the site of capture after sampling.
DNA extraction and complete genome sequencing
DNA was isolated using Qiagen Genomic-tip 100/G (Qiagen, Hilden Germany) according to manufacturer instructions. SMRTbell™ template library was prepared according to the instructions from PacificBiosciences, Menlo Park, CA, USA, following the Procedure & Checklist–Greater Than 10 kb Template Preparation. Briefly, for preparation of 15kb libraries 8μg genomic DNA was sheared using g-tubes™ from Covaris, Woburn, MA, USA according to the instructions of the manufacturer. DNA was end-repaired and ligated overnight to hairpin adapters applying components from the DNA/Polymerase Binding Kit P6 from Pacific Biosciences, Menlo Park, CA, USA. Reactions were carried out according to the manufacturer instructions. BluePippin™ Size-Selection to greater than 4 kb was performed according to the manufacturer's instructions (Sage Science, Beverly, MA, USA). Conditions for annealing of sequencing primers and binding of polymerase to purified SMRTbell™ template were assessed with the Calculator in RS Remote, PacificBiosciences, Menlo Park, CA, USA. 1 SMRT cell was sequenced on the PacBio RSII (PacificBiosciences, Menlo Park, CA, USA) taking one 240-minutes movie. SMRT sequencing revealed a total number of 85,590 reads with a mean read length of 12,138 bp and a N50 value of 16,449 bp. From the same batches of DNA, short insert libraries were created using the Illumina Nextera XT DNA Library Prep Kit (Illumina, San Diego, CA, USA) and sequenced on an Illumina MiSeq (Illumina, San Diego, CA, USA) resulting in 7,916,070 paired-end reads of 2x76 bp.
Genome assembly and annotation
Genome assembly was performed applying the RS_HGAP_Assembly.3 protocol included in SMRT Portal version 2.3.0 using default parameters. The assembly revealed a single circular chromosome with a coverage of 133x. The chromosome was circularized, artificial redundancies at the ends of the contigs were removed and adjusted to dnaA as the first gene. Error-correction was performed by a mapping of Illumina short reads onto finished genome using Burrows-Wheeler Alignment bwa 0.6.2 in paired-end (sample) mode using default setting [31] with subsequent variant and consensus calling using VarScan 2.3.6 (Parameters: mpileup2cns—min-coverage 10—min-reads2 6—min-avg-qual 20—min-var-freq 0.8—min-freq-for-hom 0.75—p-value 0.01—strand-filter 1—variants 1—output-vcf 1) [32]. A consensus concordance of QV60 could be reached. Automated genome annotation was carried out using Prokka [33] and NCBI PGAP [34].
Genome comparisons
We used Mauve software [35] to compare gene arrangement of the newly sequenced genome with those of other available Pigmentiphaga genomes. We compared the general gene functional characterization (KEGG functional categories) of the newly sequenced genomes with all other available Pigmentiphaga genomes using BlastKOALA [36]. On average, 50% of genomes’ protein coding sequences were annotated. Identification of natural product gene clusters was performed with the antibiotics and Secondary Metabolite Analysis SHell (antiSMASH version beta5; https://antismash.secondarymetabolites.org) [37] AntiSMASH is an online platform that allows for a genome-wide identification and analysis of secondary metabolite BGCs in bacterial genomes, by integrating and cross-linking with a large number of in silico secondary metabolite analysis tools like CLUSEAN [38], BAGEL2 [39], ClustScan [40], and NORINE [41].
Phylogenetic analysis
We performed BLAST searches against the NCBI database, using the full 16S rRNA gene sequence from the sequenced genome to understand the distribution of this bacterium outside of amphibian hosts. We also used the MOLE-BLAST tool of NCBI to retrieve from GenBank the sequences of bacterial taxa most closely related to the Alcaligenaceae sOTUs in our amplicon data set. MOLE-BLAST is an experimental tool to find closest database neighbors of submitted query sequences, by computing a multiple sequence alignment (MSA) between the query sequences along with their top BLAST database hits.
The obtained sequences, along with sequences of our isolates and amplicon-derived sOTU sequences, were aligned with the MAFFT 7.0 algorithm [42] and phylogenetically analyzed in MEGA v. 7 [43]. We successively filtered the data set to remove highly deviant sequences retrieved from the database (as well as sOTU sequences associated to them), as identified by obvious alignment artefacts and excessively long branches in exploratory phylogenetic trees. The final Maximum Likelihood (ML) tree was computed under the GTR+G model of sequence evolution as determined under the Bayesian Information criterion in MEGA 7.
Volatile compound analysis
A bacterial culture of the target bacterial strain was incubated on 1% tryptone agar for seven days at room temperature. Headspace extracts were obtained using a vacuum pump to draw clean air (purification by active charcoal filter) through a 250 mL glass vessel containing the culture plate. The air was then passed through a thermal desorption tube filled with an absorbent (Tenax TA Tube; GERSTEL, Mülheim an der Ruhr, Germany) for 5 h (three replicates).
Thermal desorption tubes were desorbed using a thermal desorption unit (TDU), cooled injection system (CIS) and a MultiPurposeSampler (MPS) autosampler (GERSTEL, Mülheim an der Ruhr, Germany) connected to an Agilent 7890B gas chromatograph. The gas chromatograph was equipped with a HP-5 MS fused silica capillary column (30 m, 0.25 i. d., 0.25 μm film, Hewlett-Packard, Wilmington, USA) connected to an Agilent 5977A mass-selective detector. Conditions: transfer line 300°C, electron energy 70 eV. Thermal desorption: 30°C, increasing at 60°C/min to 280°C (10 min isothermal). Cooled injection: -150°C, increasing at 12°C/min to 300°C (3 min isothermal). Gas chromatographic method: 50°C (5 min isothermal), increasing at 5°C/min to 320°C, and operated in splitless mode. Helium was used as carrier gas at 1.2 ml/min. GC retention indices (RI) were determined from a homologous series of n-alkanes (C8-C30). Compounds were identified by comparison of mass spectra and retention indices with those of authentic samples.
Results and discussion
Representation of Alcaligenaceae in amphibian cutaneous microbiomes
In the global dataset of amplicon sequences from 205 amphibian species [6] Alcaligenaceae sOTUs made up 284,771 out of 5,872,500 total rarified reads in the final data set (4.8%). Alcaligenaceae sOTUs (at a minimum threshold of 5 reads) were found in a total of 119 amphibian species from eight countries, and Pigmentiphaga sOTUs in 95 amphibian species. In a culture database of amphibian skin bacteria [22, Bletz & Woodhams unpublished data] 28 of 5938 isolates were from the Alcaligenaceae, and our isolate was the sole member from the genus Pigmentiphaga. Therefore, apparently, Alcaligenaceae and more specifically Pigmentiphaga appear to be underrepresented in culture databases of amphibian skin microbiota and thus might be less readily culturable than other bacteria from this habitat [5].
The family Alcaligenaceae currently contains 27 genera (UniProt 2019); in the amphibian microbiome data set, 338 out of a total of 124,348 sOTUs were assigned to this family, and of these, 35 to the genus Pigmentiphaga (reads = 266,723). The remaining Alcaligenaceae reads were assigned to the genera Achromobacter (n = 3,355), Alcaligenes (n = 666), Sutterella (n = 20) Oligella (n = 16), Denitrobacter (n = 3), Candidimonas (n = 12) or were left unassigned to a specific genus (n = 13,976).
Confirming previous findings [12–14], in our global skin microbiome dataset [6] Pigmentiphaga was predominantly found on arboreal species as well as scansorial hosts within the amphibian clades Mantellidae (mean: 7.7% + 1.5%SD) and Hyperoliidae (mean: 7.9% + 4.7% SD, which are distributed in Madagascar, and (Hyperoliidae only) in mainland Africa (Fig 1). The genus also appears on amphibians from the genus Pseudacris (Fig 1). Overall, Pigmentiphaga was more common on amphibians from Madagascar; however, this could be associated with extensive sampling of arboreal hosts within this country.
Phylogenetic diversity of Pigmentiphaga in amphibian cutaneous microbiomes
We aligned short amplicon-based consensus sequences of Alcaligenaceae amplicons with the longer 16S sequences of all Madagascan amphibian-derived isolates from a previous work [15] belonging to this family. We then used a series of BLAST and MOLE-BLAST searches, allowing for hits with and without environmental sequences, and restricting searches to type strains or not, to retrieve a representative set of 273 homologous Alcaligenaceae sequences of the 16S rRNA gene for analysis of phylogeny and environmental distribution of our focal bacterial taxa. The exploratory analysis of these sequences along with our Alcaligenaceae sOTU and isolate sequences placed 92 sOTUs, 8 isolates and 82 related sequences retrieved from GenBank in a clade with the Pigmentiphaga type strains. A ML tree calculated on this restricted dataset (Fig 2) reveals a large diversity of Pigmentiphaga, many of which are not assignable to any of the described species. A large number of 61 additional sOTUs from the amphibian skin, as well as one isolate from the skin of a fire salamander (DE946; accession number MH512662) and two from Madagascar frogs (Mada281, Mada1835; accession numbers MF526411, MF523827), are placed in a large subclade of putative Pigmentiphaga sequences that does not contain any type strain sequences. This subclade also contains sOTU7503, the most widespread Alcaligenaceae sOTU in our global amplicon-derived data set (45,697 reads). Various sequences retrieved from GenBank and included in this subclade are named P. daguensis but are unlikely to belong to this species, given that the type strain is placed in another, phylogenetically distant clade. Whether this diverse subclade is to be assigned to Pigmentiphaga definitively, or to another, possibly undescribed genus in the Alcaligenaceae, will require additional study.
Genome characteristics of Pigmentiphaga aceris isolated from amphibian skin
One of our isolates (Mada1488) was placed close to P. aceris and had >99% sequence similarity with the type strain of this species (Table 1). The sequence obtained by direct Sanger sequencing of DNA extracted from this isolate agreed fully with the sequence from both 16S copies found in the assembled genome. One amplicon-derived sOTU also the sequence of this isolate. In our global amphibian data set, 139 of these reads came from the sOTU matching the Mada1488 isolate. This sOTU was found on frogs of the genera Anaxyrus, Boophis, Colostethus, Craugastor, Gephyromantis, Eleutherodactylus, Lithobates, Mantidactylus, Mantella, and Plethodontohyla. Thus, the bacterium represented by our culture (Mada1488) was not very common in our Illumina dataset. As it was the only cultured Pigmentiphaga from amphibian skin assignable to a known species we nevertheless chose this isolate for genome sequencing, to obtain first data of the genomic background of these bacteria.
In culture, this bacterium forms white, glossy colonies with circular form; the elevation is raised and the margins are entire. In a growth inhibition assay (see [15] for methods) the metabolites produced by this bacterium reduced the growth of the amphibian skin pathogen Batrachochytrium dendrobatidis by 60%. BLAST searches in the NCBI nucleotide database revealed that bacterial strains with >97% 16S sequence identity to Mada1488 have been found on human skin, in floral nectar, tree sap, artic stream sediment, and soil (Table 1). The highest identity was found with an uncultured isolate from human skin (99.4% identity), directly followed by the P. aceris type strain (SAP-32) with 99.3% identity.
The complete genome of Pigmentiphaga aceris (Mada1488) consists of a single circular chromosome with 6,165,255 bp and a GC content of 62.1%. Prokka predicted 5,300 coding sequences, 57 tRNA genes, and three rRNA operons (Fig 3). A multiple genome alignment suggests that the new genome shows only limited similarities to the five congeneric genomes available (S1 Fig); however, the five available genomes all belong to closely related strains (all >98% 16S similarity to the type strains of P. kullae and P. daeguensis, which themselves show 99.6% similarity, questioning the distinctness of these two taxa at the species level).
The newly sequenced genome of P. aceris (Mada1488) differs in its gene functions compared to other known Pigmentiphaga genomes; more specifically, genes associated with environmental information processing and cellular processes were more abundant in Mada1488 (S2 Fig). Natural product biosynthetic gene clusters (BGCs) are moderately represented in the newly sequenced genome, and the cluster content differs from that in the other available Pigmentiphaga genomes (S1 Table). Amongst others, P. aceris (Mada1488) contains a nonribosomal peptide syntethase (NRPS) cluster most likely involved in the production of a peptide siderophore similar to enterobactin [45], and a BGC coding for bacteriocin biosynthetic genes, both missing in the other Pigmentiphaga. Bacteriocines are widely occurring, ribosomally produced antimicrobial peptides, presumably with an anti-competitor function [46] and an often narrow activity range against Gram-positive as well as Gram-negative bacteria [47,48]. The most noticeable feature in the comparative Pigmentiphaga genomes but absent in P. aceris (Mada1488) are clusters for β-lactones, a class of protein-inhibiting natural products with a wide range of activities [49]. Furthermore, P. aceris (Mada1488) lacks genes involved in ectoin biosynthesis. Because ectoins are usually produced to protect the bacteria from environmental extremes like hyperosmotic conditions [50], the lack of ectoins might support this strain being adapted to rather stable environmental conditions.
Volatile compounds produced by Pigmentiphaga aceris
The ability to produce volatile organic compounds (VOCs) is widespread among bacteria [51] and our data demonstrate this ability also in Pigmentiphaga aceris (Mada1488). GC/MS analysis of headspace extracts from this bacterium revealed the release of 21 compounds (S1 Table), among them sulfur-containing volatiles such as methanethiole, dimethyl disulfide (1), dimethyl trisulfide (2), S-methyl ethanethioate (3), S-methyl propanethioate (4), S-methyl 2-methylpropanethioate (5), S-methyl 3-methylbutanethioate (6) and S-methyl phenylethanethioate (7), as well as γ-decalactone (8) (S3 Fig). Some these compounds, for example, dimethyl trisulfide and S-methyl 3-methylbutanethioate, have been associated with inhibition of a variety of plant pathogens [52,53], suggesting they may play a role in suppression of amphibian fungal pathogens, such as Bd and Bsal.
Conclusions
To our knowledge, Pigmentiphaga aceris (Mada1488) is the first amphibian skin-derived bacterial isolate with a full genome sequenced. Overall, the genome does not present any outstanding characteristics, in line with the hypothesis that the amphibian cutaneous microbiome mainly consists of generalist species recruited from environmental reservoirs. It is remarkable that bacterial strains most similar to Mada1488 have multiple times been found in plant-associated microbiomes (tree sap, nectar, phyllosphere). The finding of a Pigmentiphaga similar to the strain described herein on human skin may be explained by a bias of information in genetic databases towards human-derived microbes, but also confirms that these bacteria are not strictly associated to plants only. Yet, it is tempting to relate the apparent common occurrence of Pigmentiphaga on plants to its high abundance in treefrogs which may have acquired it from plant-associated reservoirs. To test this hypothesis, in-depth analysis of additional bacteria differentially abundant on arboreal vs. terrestrial amphibians may be rewarding. A wider sampling of genomes represented in amphibian cutaneous microbiomes will be a crucial step to better understand functional properties of these bacterial communities and their potential role in defense against pathogens.
Data availability
The complete genome sequence of Pigmentiphaga aceris Mada1488 has been deposited at NCBI GenBank under the accession no. CP043046. The version described in this paper is the first version. (BioProject no. PRJNA561098). The 16S sequence of this isolate is archived under accession no. MF525803.1. Accession numbers of sequences used in the phylogenetic analysis are given in the respective tree. Accession numbers for the raw data of amplicon analyses are summarized in a previous study [6].
Supporting information
S2 Fig [pdf]
Comparative summary of gene function across the newly sequenced (red box) and other available genomes from this genus.
S1 Table [docx]
Natural product biosynthetic gene clusters (BGCs) in available genomes as predicted by AntiSMASH.
S2 Table [docx]
Volatile compounds released by (Mada1488).
Zdroje
1. Fisher MC, Garner TW, Walker SF. Global emergence of Batrachochytrium dendrobatidis and amphibian chytridiomycosis in space, time, and host. Annu Rev Microbiol. 2009;63: 291–310. doi: 10.1146/annurev.micro.091208.073435 19575560
2. Stegen G, Pasmans F, Schmidt BR, Rouffaer LO, Van Praet S, Schaub M, et al. Drivers of salamander extirpation mediated by Batrachochytrium salamandrivorans. Nature. Nature Publishing Group; 2017;544: 353–356. doi: 10.1038/nature22059 28425998
3. Bletz MC, Loudon AH, Becker MH, Bell SC, Woodhams DC, Minbiole KPC, et al. Mitigating amphibian chytridiomycosis with bioaugmentation: Characteristics of effective probiotics and strategies for their selection and use. Ecol Lett. 2013;16. doi: 10.1111/ele.12099 23452227
4. Loudon AH, Woodhams DC, Parfrey LW, Archer HM, Knight R, McKenzie V, et al. Microbial community dynamics and effect of environmental microbial reservoirs on red-backed salamanders (Plethodon cinereus). ISME J. Nature Publishing Group; 2014;8: 830–40. doi: 10.1038/ismej.2013.200 24335825
5. Walke JB, Becker MH, Hughey MC, Swartwout M, Jensen R V, Belden LK. Most of the dominant members of amphibian skin bacterial communities can be readily cultured. Appl Environ Microbiol. 2015; doi: 10.1128/AEM.01486-15 26162880
6. Kueneman JG, Bletz MC, Becker CG, Woodhams DC, Vences M. Community richness of amphibian skin bacteria correlates with bioclimate at the global scale. Nat Ecol Evol. 2019;
7. Kueneman JG, Parfrey LW, Woodhams DC, Archer HM, Knight R, McKenzie VJ. The amphibian skin-associated microbiome across species, space and life history stages. Mol Ecol. 2014;23: 1238–1250. doi: 10.1111/mec.12510 24171949
8. Bletz MC, Perl RGB, Vences M. Skin microbiota differs drastically between co-occurring frogs and newts. Open Sci. 2017;4: 170107.
9. Jani AJ, Briggs CJ. Host and aquatic environment shape the amphibian skin microbiome but effects on downstream resistance to the pathogen Batrachochytrium dendrobatidis are variable. Front Microbiol. 2018;9: 1–17. doi: 10.3389/fmicb.2018.00001
10. Sabino-Pinto J, Bletz MC, Islam MM, Shimizu N, Bhuju S, Geffers R, et al. Composition of the cutaneous bacterial community in Japanese amphibians: effects of captivity, host species, and body region. Microb Ecol. Microbial Ecology; 2016; 460–469. doi: 10.1007/s00248-016-0797-6 27278778
11. Bletz MC, Bina Perl RG, Vences M. Skin microbiota differs drastically between co-occurring frogs and newts. R Soc Open Sci. 2017;4. doi: 10.1098/rsos.170107 28484639
12. Bletz MC, Archer H, Harris RN, McKenzie VJ, Rabemananjara FCE, Rakotoarison A, et al. Host ecology rather than host phylogeny drives amphibian skin microbial community structure in the biodiversity hotspot of Madagascar. Front Microbiol. 2017;8: Article 1530. doi: 10.3389/fmicb.2017.01530 28861051
13. Belden LK, Hughey MC, Rebollar EA, Umile TP, Loftus SC, Burzynski EA, et al. Panamanian frog species host unique skin bacterial communities. Front Microbiol. 2015;6: 1171. doi: 10.3389/fmicb.2015.01171 26579083
14. Abarca JG, Vargas G, Zuniga I, Whitfield SM, Woodhams DC, Kerby J, et al. Assessment of bacterial communities associated with the skin of costa rican amphibians at la selva biological station. Front Microbiol. 2018;9: 1–12. doi: 10.3389/fmicb.2018.00001
15. Bletz MCMC, Myers J, Woodhams DCDC, Rabemananjara FCEFCE, Rakotonirina A, Weldon C, et al. Estimating herd immunity to amphibian chytridiomycosis in Madagascar based on the defensive function of amphibian skin bacteria. Front Microbiol. 2017;8. doi: 10.3389/fmicb.2017.01751 28959244
16. Blümel S, Mark B, Busse H-J, Kämpfer P, Stolz A. Pigmentiphaga kullae gen. nov., sp. nov., a novel member of the family Alcaligenaceae with the ability to decolorize azo dyes aerobically. Int J Syst Evol Microbiol. Microbiology Society; 2001;51: 1867–1871. doi: 10.1099/00207713-51-5-1867 11594620
17. Yoon J-H, Kang S-J, Kim W, Oh T-K. Pigmentiphaga daeguensis sp. nov., isolated from wastewater of a dye works, and emended description of the genus Pigmentiphaga. Int J Syst Evol Microbiol. Microbiology Society; 2007;57: 1188–1191. doi: 10.1099/ijs.0.64901-0 17551027
18. Lee J-J, Srinivasan S, Kim MK. Pigmentiphaga soli sp. nov., a bacterium isolated from soil. J Microbiol. Springer; 2011;49: 857–861. doi: 10.1007/s12275-011-1375-8 22068507
19. Lee SD. Pigmentiphaga aceris sp. nov., isolated from tree sap. Int J Syst Evol Microbiol. Microbiology Society; 2017;67: 3198–3202. doi: 10.1099/ijsem.0.002073 28840799
20. Chen Y-G, Zhang Y-Q, Huang K, Tang S-K, Cao Y, Shi J-X, et al. Pigmentiphaga litoralis sp. nov., a facultatively anaerobic bacterium isolated from a tidal flat sediment. Int J Syst Evol Microbiol. Microbiology Society; 2009;59: 521–525. doi: 10.1099/ijs.0.002949-0 19244433
21. Proença DN, Grass G, Morais P V. Understanding pine wilt disease: roles of the pine endophytic bacteria and of the bacteria carried by the disease‐causing pinewood nematode. Microbiologyopen. Wiley Online Library; 2017;6: e00415.
22. Bridger N, Drews S, Burdz T, Wiebe D, Pacheco AL, Ng B, et al. Isolation and characterization of Pigmentiphaga-like isolates from human clinical material. J Med Microbiol. Microbiology Society; 2013;62: 708–711. doi: 10.1099/jmm.0.051615-0
23. Bernier A-M, Bernard K. Draft Whole-Genome Sequences for Two Pigmentiphaga Isolates Recovered from Human Clinical Materials. Genome Announc. Am Soc Microbiol; 2017;5: e00726–17. doi: 10.1128/genomeA.00726-17 28774981
24. Huang J, Ling J, Kuang C, Chen J, Xu Y, Li Y. Microbial biodegradation of aniline at low concentrations by Pigmentiphaga daeguensis isolated from textile dyeing sludge. Int Biodeterior Biodegradation. Elsevier; 2018;129: 117–122.
25. Garrido-Sanz D, Manzano J, Martín M, Redondo-Nieto M, Rivilla R. Metagenomic analysis of a biphenyl-degrading soil bacterial consortium reveals the metabolic roles of specific populations. Front Microbiol. Frontiers; 2018;9: 232.
26. Amir A, McDonald D, Navas-Molina JA, Kopylova E, Morton JT, Zech Xu Z, et al. Deblur rapidly resolves single-nucleotide community sequence patterns. Gilbert JA, editor. mSystems. 2017;2.
27. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73: 5261–5267. doi: 10.1128/AEM.00062-07 17586664
28. Caporaso JG, Lauber CL, Walters WA, Berg-lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci. 2011;108: 4516–4522. doi: 10.1073/pnas.1000080107 www.pnas.org/cgi/doi/10.1073/pnas.1000080107 20534432
29. Hedges SB, Dudley J, Kumar S. TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics. 2006;22: 2971–2972. Available: https://doi.org/10.1093/bioinformatics/btl505 17021158
30. Wickham H. ggplot2: Elegant graphics for data analysis. New York: Springer; 2009.
31. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics. Oxford University Press; 2010;26: 589–595. doi: 10.1093/bioinformatics/btp698 20080505
32. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. Cold Spring Harbor Lab; 2012;22: 568–576. doi: 10.1101/gr.129684.111 22300766
33. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. Oxford University Press; 2014;30: 2068–2069. doi: 10.1093/bioinformatics/btu153 24642063
34. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. Oxford University Press; 2016;44: 6614–6624. doi: 10.1093/nar/gkw569 27342282
35. Darling ACE, Mau B, Blattner FR, Perna NT. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. Cold Spring Harbor Lab; 2004;14: 1394–1403. doi: 10.1101/gr.2289704 15231754
36. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. Elsevier; 2016;428: 726–731. doi: 10.1016/j.jmb.2015.11.006 26585406
37. Blin K, Wolf T, Chevrette MG, Lu X, Schwalen CJ, Kautsar SA, et al. antiSMASH 4.0—improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Res. Oxford University Press; 2017;45: W36–W41. doi: 10.1093/nar/gkx319 28460038
38. Weber T, Rausch C, Lopez P, Hoof I, Gaykova V, Huson DH, et al. CLUSEAN: a computer-based framework for the automated analysis of bacterial secondary metabolite biosynthetic gene clusters. J Biotechnol. Elsevier; 2009;140: 13–17. doi: 10.1016/j.jbiotec.2009.01.007 19297688
39. de Jong A, van Heel AJ, Kok J, Kuipers OP. BAGEL2: mining for bacteriocins in genomic data. Nucleic Acids Res. Oxford University Press; 2010;38: W647–W651. doi: 10.1093/nar/gkq365 20462861
40. Starcevic A, Zucko J, Simunkovic J, Long PF, Cullum J, Hranueli D. ClustScan: an integrated program package for the semi-automatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures. Nucleic Acids Res. Oxford University Press; 2008;36: 6882–6892. doi: 10.1093/nar/gkn685 18978015
41. Caboche S, Pupin M, Leclère V, Fontaine A, Jacques P, Kucherov G. NORINE: a database of nonribosomal peptides. Nucleic Acids Res. Oxford University Press; 2007;36: D326–D331. doi: 10.1093/nar/gkm792 17913739
42. Katoh K, Rozewicki J, Yamada KD. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinform. 2017;
43. Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33: msw054. doi: 10.1093/molbev/msw054 27004904
44. Carver T, Thomson N, Bleasby A, Berriman M, Parkhill J. DNAPlotter: circular and linear interactive genome visualization. Bioinformatics. Oxford University Press; 2008;25: 119–120. doi: 10.1093/bioinformatics/btn578 18990721
45. Crosa JH, Walsh CT. Genetics and assembly line enzymology of siderophore biosynthesis in bacteria. Microbiol Mol Biol Rev. Am Soc Microbiol; 2002;66: 223–249. doi: 10.1128/MMBR.66.2.223-249.2002 12040125
46. Riley MA, Wertz JE. Bacteriocins: evolution, ecology, and application. Annu Rev Microbiol. Annual Reviews 4139 El Camino Way, PO Box 10139, Palo Alto, CA 94303–0139, USA; 2002;56: 117–137. doi: 10.1146/annurev.micro.56.012302.161024 12142491
47. Kumariya R, Garsa AK, Rajput YS, Sood SK, Akhtar N, Patel S. Bacteriocins: Classification, synthesis, mechanism of action and resistance development in food spoilage causing bacteria. Microb Pathog. Elsevier; 2019;
48. Cotter PD, Ross RP, Hill C. Bacteriocins—a viable alternative to antibiotics? Nat Rev Microbiol. Nature Publishing Group; 2013;11: 95. doi: 10.1038/nrmicro2937 23268227
49. Robinson SL, Christenson JK, Wackett LP. Biosynthesis and chemical diversity of β-lactone natural products. Nat Prod Rep. Royal Society of Chemistry; 2019;
50. Czech L, Höppner A, Kobus S, Seubert A, Riclea R, Dickschat JS, et al. Illuminating the catalytic core of ectoine synthase through structural and biochemical analysis. Sci Rep. Nature Publishing Group; 2019;9: 364. doi: 10.1038/s41598-018-36247-w 30674920
51. Schulz S, Dickschat JS. Bacterial volatiles: the smell of small organisms. Nat Prod Rep. Royal Society of Chemistry; 2007;24: 814–842. doi: 10.1039/b507392h 17653361
52. Zhang L, Khabbaz SE, Wang A, Li H, Abbasi PA. Detection and characterization of broad-spectrum antipathogen activity of novel rhizobacterial isolates and suppression of Fusarium crown and root rot disease of tomato. J Appl Microbiol. 2015;118: 685–703. doi: 10.1111/jam.12728 25512025
53. Ossowicki A, Jafra S, Garbeva P. The antimicrobial volatile power of the rhizospheric isolate Pseudomonas donghuensis P482. PLoS One. 2017;12: 1–13. doi: 10.1371/journal.pone.0174362 28358818
Článok vyšiel v časopise
PLOS One
2019 Číslo 10
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Correction: Low dose naltrexone: Effects on medication in rheumatoid and seropositive arthritis. A nationwide register-based controlled quasi-experimental before-after study
- Combining CDK4/6 inhibitors ribociclib and palbociclib with cytotoxic agents does not enhance cytotoxicity
- Experimentally validated simulation of coronary stents considering different dogboning ratios and asymmetric stent positioning
- Risk factors associated with IgA vasculitis with nephritis (Henoch–Schönlein purpura nephritis) progressing to unfavorable outcomes: A meta-analysis