Skip to main content
NCBI home page
Elsevier Sponsored Documents logoLink to Elsevier Sponsored Documents
. 2021 Aug 30;541:736772. doi: 10.1016/j.aquaculture.2021.736772

Genome erosion and evidence for an intracellular niche – exploring the biology of mycoplasmas in Atlantic salmon

B Cheaib a,b,⁎, P Yang c, R Kazlauskaite a, E Lindsay a, C Heys a, T Dwyer a, M De Noa a, Patrick Schaal a, W Sloan b, UZ Ijaz b, MS Llewellyn a
PMCID: PMC8192413  PMID: 34471330

Abstract

Mycoplasmas are the smallest autonomously self-replicating life form on the planet. Members of this bacterial genus are known to parasitise a wide array of metazoans including vertebrates. Whilst much research has been significant targeted at parasitic mammalian mycoplasmas, very little is known about their role in other vertebrates. In the current study, we aim to explore the biology of mycoplasmas in Atlantic Salmon, a species of major significance for aquaculture, including cellular niche, genome size structure and gene content. Using fluorescent in-situ hybridisation (FISH), mycoplasmas were targeted in epithelial tissues across the digestive tract (stomach, pyloric caecum and midgut) from different development stages (eggs, parr, subadult) of farmed Atlantic salmon (Salmo salar), and we present evidence for an intracellular niche for some of the microbes visualised. Via shotgun metagenomic sequencing, a nearly complete, albeit small, genome (~0.57 MB) as assembled from a farmed Atlantic salmon subadult. Phylogenetic analysis of the recovered genome revealed taxonomic proximity to other salmon derived mycoplasmas, as well as to the human pathogen Mycoplasma penetrans (~1.36 Mb). We annotated coding sequences and identified riboflavin pathway encoding genes and sugar transporters, the former potentially consistent with micronutrient provisioning in salmonid development. Our study provides insights into mucosal adherence, the cellular niche and gene catalog of Mycoplasma in the gut ecosystem of the Atlantic salmon, suggesting a high dependency of this minimalist bacterium on its host. Further study is required to explore and functional role of Mycoplasma in the nutrition and development of its salmonid host.

Highlights

  • •

    Mycoplasmas colonize the epithelial niche of the Atlantic salmon GI tract through its different development stages.

  • •

    A nearly complete, albeit small, genome (~0.57 MB) assembled from Atlantic salmon subadult suggests genome reduction.

  • •

    The lack of mobile genes and virulence factors in the mycoplasma genome could support a non-pathogenic lifestyle.

  • •

    Mycoplasma’s genome content suggests role for host nutrient provisioning relevance to aquaculture.

  • •

    Shotgun metagenomics, phylogenetics, and fluorescence in situ hybridization are relevant methods in aquaculture research.

1. Introduction

Mycoplasmas are a diverse group of bacteria known to parasitise a wide array of metazoans, plants, invertebrates and vertebrates, including fisheries (Razin, 1992). Mycoplasma had been isolated from multiple fish species, (Carp: Cyprinus carpio; Tench Tinca tinca; Trout: Salmo trutta; Eel: Anguilla anguilla; Sheat fish: Silurus glanis; Mosaic threadfin: Trichogaster leeri; cichlid:Tropheus sp.; Plaice: Pleuronectes platessa; Salmon: Salmo salar; goldfish: Carassius aurarus; Brook lamprey: Lampetra planeri) by the early 1980s (Kirchhoff and Rosengarten, 1984). More recently, several studies have identified Mycoplasma from marine teleosts using culture-free approaches. Mudsucker (Gillichthys mirabilis) and pinfish (Lagodon rhomboids), for example, have been identified as having gut microbiomes rich in Mycoplasma (Egerton et al., 2018). However, salmonids in particular are frequently reported to be colonised by Mycoplasma (Holben et al., 2002; Llewellyn et al., 2016). This is especially true in Atlantic salmon (Salmo salar), both in wild and in farmed settings (Holben et al., 2002; Zarkasi et al., 2016). In some cases, Mycoplasma phylotypes can comprise >70% of the total microbial reads recovered from salmon intestines (Heys et al., 2020; Llewellyn et al., 2016). The distribution and biological role of Mycoplasma in the intestines of salmonids are far from clear and require further exploration. Nonetheless, demographic modelling of microbial communities suggests colonisation of salmonid guts by these microorganisms as non-neutral, i.e. the rate at which these bacteria colonise the gut indicates a significant degree of specific adaptation to the host environment (Cheaib et al., 2020; Heys et al., 2020). Interestingly, Mycoplasma sp. are also prevalent in different extraintestinal organs (gills, liver, spleen, kidney, reproductive organs, serous membrane from the peritoneum and the swim bladder) of different fish species (EI-Jakee Ei-Jakee, 2020; Sellyei et al., 2021). Even after 40 years form their discovery, the role of Mycoplasma sp. in fisheries and aquaculture production is not clear. In particular, questions around Mycoplasma pathogenicity remains unresolved.

Mycoplasmas, as well as related taxa included in the class Mollicutes (Spiroplasmas, Ureaplasma and Acholeplasmas), are recognized as the smallest and simplest free-living and self-replicating forms of life (Bové, 1993; Trachtenberg, 2005). Mycoplasmas lack a peptidoglycan cell wall and are bounded by a simple cell membrane (Miyata and Ogaki, 2006). In addition to being physically small, mycoplasmas have the smallest genomes of any free-living organism (Razin et al., 1998). Mycoplasma genitalium, in particular, has a genome size of 580 kilobases comprising of only 482 protein-coding genes(Citti and Blanchard, 2013), whilst Mycoplasma mycoides, typically has 473 protein-coding genes, of which 149 still have no known function (Citti and Blanchard, 2013).

The simplicity of mycoplasmas, their small genome sizes, as well as their close association with metazoan hosts has led them to be considered as a target species to explore theories around genome erosion or reductive evolution (Fadiel et al., 2007; Rocha and Blanchard, 2002). Dependence on host organisms can theoretically lead to mutual interdependence of metabolic processes. This results in its relaxed selection among the pool of bacterial genomes, with the main process being the accumulation of loss-of-function mutations in coding genes, and the eventual loss of genetic material from the bacterial genome (Boscaro et al., 2017). Genetic drift can also play a significant role as host-associated microbes have relatively fewer opportunities to exchange genetic material with the wider microbial community (Moran, 1996). Isolation from microbial congeners and host dependence may be further enhanced in mycoplasmas that exploit an intracellular niche, which several species have been shown to do within the literature (Razin et al., 1998; Yavlovich et al., 2004). Mycoplasmas, likely owing to their dependence on their hosts, have fastidious requirements for in vitro culture. Culture-free approaches for microbial identification, especially, with the advent of DNA sequencing approaches, have markedly increased in recent years to identify new Mycoplasma strains (Aceves et al., 2018; Costello et al., 2013; Martin et al., 2013).

In the current study, we aimed to explore the characteristics of Mycoplasma in salmonids, including a potentially intracellular niche, taxonomic affiliations, genome structure and gene content. We also examined genetic features and metabolic functions that reveal the role of reductive evolution in shaping its genome. Finally, we discuss what role Mycoplasma may have in impacting host fitness, especially in the context of aquaculture, by reviewing genomic features it possesses that are consistent with parasitic or symbiotic lifestyles.

2. Materials and methods

2.1. Sample collection

Farmed Atlantic salmon (Salmo salar) subadults (individuals from 3 to 5 kg) fed on a commercial diet were sampled from 3 marine cages at an aquaculture facility at Corran Ferry, near Fort William, Scotland, in Autumn 2017 in collaborations with MOWI Ltd. Salmo salar freshwater parr (30-50 g) and ova were sampled at the Institute of Biodiversity, Animal Health and Comparative Medicine aquarium facility, University of Glasgow. The fishes were euthanized by blunt cranial trauma under a Schedule 1 procedure and gut compartments (stomach, pyloric caecum, and midgut) samples were dissected under aseptic conditions before being fixed in formalin for subsequent microscopy, or flash frozen in liquid nitrogen prior to DNA analysis.

2.2. Fluorescence in-situ hybridisation (FISH)

Previous work has established the dominance of Mycoplasma in marine Salmo salar GI (gastrointestinal tract) (Heys et al., 2020). To explore their physical distribution in different gut compartments and life cycle stages, FISH was undertaken on stomach, pyloric caecum and hind gut from marine farmed adults (three individuals, MOWI, Scotland) and juvenile parr reared in aquaria at the University of Glasgow (three individuals). Samples were fixed in a freshly made sterile-filtered solution of 4% paraformaldehyde in PBS (pH 7.4) for 16–24 h and maintained at room temperature for 16–48 h. Fixed samples were then washed with sterile-filtered PBS (pH 7.4) three times before being stored in 70% ethanol. Samples were then gradually dehydrated in a series of ethanol-xylene-paraffin treatment steps (Copper et al., 2018). Before sectioning, samples were embedded in paraffin and stored at 4 °C. At least four 3–4 μm sections were taken from each embedded tissue block, rehydrated in sterile ddH20, and mounted on slides for pepsin treatment and straining. Pepsin treatment was undertaken in a 0.05% pepsin solution and 0.01 M HCL. Samples were DAPI stained to target cell nuclei of host cells, and FISH probes were hybridized at 55 °C to the 16S rDNA small subunit of bacterial cells. Multiple FISH probes labelled with Cy3 and Cy5 dyes were deployed to distinguish Mycoplasma strains from other microbes present in samples (Table 1). To improve the visualization of non-mycoplasma bacteria, multiple probes were deployed using the same dye. A Mycoplasma probe (Myc1–1) (Table 1) probe was designed based on Illumina amplicon sequences based upon the most abundant operational taxonomic (OTU) sequence identified in Adult Salmon that we identified in previous work (Heys et al., 2020). To establish respective specificity of probes, positive controls of for both universal probes (E. coli) and Mycoplasma probes (Mycoplasma muris) were used. Attempts culture Mycoplasma from salmon were not successful. All samples were visualised at 20-30× magnification on a DeltaVision-Core microscope (Applied Precision, GE), equipped with a CoolSNAP HQ camera (Photometrics) and operated with SoftWoRx software (Applied Precision, GE).

Table 1.

Fish probes and sequences deployed in this study.

Probes Target group Sequence (5′-3′) Reference
Myc1–1 Mycoplasma GCGGTAATACATAGGTYGCAAGCG This study
Gam-1 Gammaproteobacteria GCCTTCCCACATCGTTT Manz et al., 1992
FIR-1 Firmicutes GGAAGATTCCCTACTGCTG Hallberg et al., 2006
EUB338 All bacteria GCTGCCTCCCGTAGGAGT Amann et al., 1990
EUB338 II Planctomycetes GCAGCCACCCGTAGGTGT Daims et al., 1999
EUB338 III Verrucomicrobia GCTGCCACCCGTAGGTGT
Non EUB338 None CGACGGAGGGCATCCTCA Wallner et al., 1993
Open in a new tab

This table resumes the probes used for targeting general and specific bacterial groups including the Mycoplasmas and control negative.

2.3. DNA extraction, library annotation and sequencing

DNA was extracted from a section of pyloric caecum derived from a single individual on which FISH analyses had identified the presence of Mycoplasma organisms, based on their labelling with a targeted 16S probe. The sample homogenised via bead beating and DNA extracted using a Qiagen DNAeasy Stool Kit. A sequencing library for Illumina Next-Seq WGS (whole genome shotgun) was prepared using a sonication protocol and a TruSeq library protocol and adaptors. Sequencing was undertaken at the University of Glasgow Polyomics facility.

2.4. Data preprocessing, assembly, binning and annotations

The short paired-end NextSeq Illumina reads (2 × 63 million reads) were preprocessed for quality filtering using sickle V1.2 (https://github.com/najoshi/sickle). Decontamination of good quality reads was performed by mapping reads against the Salmo salar genome (available at NCBI sequence archive with the accession number GCF_000233375.1) using Deconseq V 0.4.3 (Schmieder and Edwards, 2011) based on BWA mapper V 0.5.9 (Li, 2013). The decontaminated paired-end reads (~18 millions of bacterial reads) were assembled using the Megahit V1.1 software (Li et al., 2015). The assembled contigs (~93,400) were processed for binning using MetaBAT V2.12.1 (Kang et al., 2015). Quality assessment for completeness and contamination of sequence was performed using CheckM V1.0.18 software (Parks et al., 2015). Annotation of gene content was performed using the pipeline ATLAS-metagenome (Kieser, 2019), which involves the prediction of open reading frames (ORFs) using Prodigal (Hyatt et al., 2010). Translated gene products were clustered using LinClust (Steinegger and Söding, 2018) to generate non-redundant gene and protein catalogues, which were mapped to the eggNOG catalog (Huerta-Cepas et al., 2019) using DIAMOND (Buchfink et al., 2015).

2.5. Phylogenetic analyses

Two approaches were undertaken to construct phylogenetic trees: a) MLST-based (Multi Locus Sequence Typing); and b) 16S gene markers (recovered from the genome) of the mycoplasma MAG (metagenome-assembled genome) from this study as well as what is previously available in the literature. Using CheckM software, the MLST-based strategy focused on a concatenation of 21 conserved housekeeping genes annotated in the mycoplasma MAG supplemented with the orthologues available for all the Mycoplasma genera, to date. The MLST-based dataset included 55 orthologues of protein sequences of concatenated 21 conserved markers. The 16S rDNA sequence dataset included: one sequence of 16S rDNA gene annotated from the mycoplasma MAG; five Operational Taxonomic Units (OTUs) sequences of mycoplasmas characterised form the same farmed salmon system (Heys et al., 2020); 101 and 17 sequences of 16S rDNA from the Mycoplasma sp. and Sprioplasma sp. genomes respectively from IMG database; and 11 sequences, from environmental studies, detected in marine species including shrimp, fish and isopods. DNA and protein sequences were aligned using MAFFT version 6.24 (Katoh and Standley, 2013). Phylogenetic inference was performed using PhyML version 3.0 (Guindon and Gascuel, 2003) and MrBayes V.3.2.6 (Huelsenbeck and Ronquist, 2001). The evolutionary model was chosen using MODELTEST(Posada and Crandall, 1998), and parameters were iteratively estimated in PhyML using the GTR + I + G model for the nucleotide sequence of 16 s trees and the LG + I + G model for amino-acid sequences of concatenated markers trees (Le and Gascuel, 2008). Bootstrap values were calculated using 100 replicates (Felsenstein, 1985). With MrBayes, posterior probability values were calculated using an average standard deviation of partition frequencies <0.01 as a convergence diagnostic (Ronquist et al., 2012). MrBayes runs consisted of eight simultaneous Markov chains, each with 1,000,000 generations, a subsampling frequency of 1000, and a burn-in fraction of 0.15. Trees were then visualised and adapted for presentation in FigTree version1.4.3 as a graphical viewer of phylogenetic trees (http://tree.bio.ed.ac.uk).

2.6. Metabolic pathways comparison and genome reduction analysis

All Pfam V.32 (comprehensive and accurate collection of protein domains and families) annotations were predicted with Prodigal and analysed in terms of function categories and metabolic content (focusing on Enzyme EC numbers). The 570 genes identified were associated with 746 Pfam functions. The Pfam functions led to the recovery of Gene Ontology (GO) terms and were then mapped to the KEGG database. Simultaneously, the alternate approach involving the MetaCyc database was employed to elucidate metabolic pathways from all domains of life (Caspi et al., 2018). The EC numbers of the coding sequence regions in Mycoplasma penetrans were extracted from the KEGG database and were then compared with those annotated within the mycoplasma MAG from Salmo salar in this study. The mapping of metabolic pathways from both genomes was visualised using the iPath (Yamada et al., 2011). From the IMG genomic database, all available metadata on sequenced mycoplasma strains were then collected and compared to the mycoplasma MAG for the genome size, GC content, gene content and their preference (e.g. intracellular, free-living etc). Annotations for the mycoplasma MAG were submitted to CG view (Grant and Stothard, 2008) for radial visualization of its genomic. Using a core gene approach, the 570 predicted genes were compared at the DNA and protein sequence levels against all the available genes of Mycoplasma penetrans using BLAST+ V 2.8.1 (Altschul et al., 1990). The best hits for each query were represented in a radial plot using Circoletto software version V.069–9 (Darzentas, 2010). Complimentary annotations were performed using RAST software which, consisted of subsystem classification of microbial functions available in the curated database, i.e. SEED subsystems (Overbeek et al., 2014).

3. Results

3.1. Fluorescence in situ hybridization (FISH) of mycoplasmas in the farmed salmon

The set of probes used in FISH for the identification of bacterial populations is summarized in Table 1. The Mycoplasma probe Myc1–1 showed specific hybridization, and its specificity was evaluated against in pure culture Escherichia coli and Mycoplasma muris (Supplementary Fig. S1). The probe gives a positive signal solely with cultured Mycoplasma muris. We made multiple attempts in both solid and liquid culture mycoplasmas from the salmon intestines, but without success. FISH visualization in salmon ova demonstrated a low abundance of bacteria and no signal of Mycoplasma sp. (Fig. 1A; Supplementary Fig. S2.1). In Salmo salar freshwater parr, Mycoplasma sp. aggregates were observed on the stomach lining of all samples (Fig. 1B; Supplementary Fig. S2.2), as well as on the muscular mucosae, and epithelium of the pyloric caecum (Fig. 1C; Supplementary Fig. S2.3). In the midgut of salmon parr (distal to the pyloric caecum) the aggregation of Mycoplasma sp. in the epithelium cells was also identified (Supplementary Fig. S2.4). In the stomach (Fig. 1D; Supplementary Fig. S2.5) and pyloric caecum (Fig. 1E–F; Supplementary Fig. S2.6) of adult salmon, Mycoplasma sp. signals were clustered in small aggregates in the lumen around the nuclei of epithelial cells. Fig. 1 indicates this intracellular clustering most clearly. In the midgut of adult salmon, Mycoplasma sp. showed lower abundance and the signals of Mycoplasma sp. showed aggregations near epithelium cell nuclei (Supplementary Fig. S2.7). More comprehensive, 16S -amplicon-seq based surveys of Mycoplsama abundances in farmed sub adults from the same site can be found in Heys et al., 2020.

Fig. 1.

Fig. 1

Open in a new tab

FISH visualization of Mycoplasma in salmon parr and adults. The images were an overlay of DAPI signals (blue), hybridization signals of Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes (Cy5, red) and Mycoplasma sp. Specific Myc1–1 probe (Cy3, orange). Scale bars are shown in the bottom left corner of each image (A) Mycoplasma sp. are absent from salmon ova, and bacteria scarce. (Scale 10um). (B) Distribution of Mycoplasma sp. in the stomach of salmon parr, scaled at 10 μm. Orange signals indicate mycoplasmas were clustered in small groups. (C) Distribution of Mycoplasma sp. in the epithelium of pyloric caecum of salmon parr (Scale 10um). (D) Distribution of Mycoplasma sp. in the stomach of adult salmon (Scaled 50 μm). (E, F) Distribution of Mycoplasma sp. in the pyloric caecum of adult salmon scaled at 10 μm (E) and 5 μm (F) respectively. Mycoplasmas signals were aggregated on the muscularis mucosae, lamina propria (E) and clustered in high abundance around epithelial cell nuclei (white arrows, F). These experiments were performed using at least three technical replicates of each life stage and digestive tract compartment. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.2. Mycoplasma MAG (metagenome-assembled genome) features and orthologs

Using a total of 63,180,207 reads, and after decontamination, 93,397 contigs were assembled using megahit software (see Materials and methods). The assembled contigs were binned, annotated, and assessed for completeness (see materials and methods). The best quality assembled bins corresponded to a nearly complete genome assigned to a Mycoplasma sp. (see the genome sequence in Supplementary File 2). The completeness of this metagenome-assembled genome (MAG) was estimated at 92.18% with 0.38% of contamination (Table 2). The metagenome and MAGE were deposited into the NCBI database under the Bio project accession number PRJNA714611.

Table 2.

Summary of Mycoplasma metagenome assembled genome (MAG).

Genome Mycoplasma assembled genome
Completeness 92.18
Contamination 0.38
Unique markers (of 43) 39
Multi-copy 0
Taxonomy (contained) Genus: Mycoplasma
Taxonomy of sister lineage Mycoplasma penetrans
GC content 24.98
Genome size (mbp) 0.57
Gene count 570
Coding density 0.93
Length 577,903
N50 14,796
Genome completeness 92.18%
Open in a new tab

The shotgun metagenomics data (63 million reads) were trimmed after a quality control assessment, then assembled using Megahit, binned using Metabat and checked for binning quality using CheckM software. The metagenome was sequenced from the pyloric caecum of one individual subadult farmed Atlantic salmon (Salmo salar).

The average size of the assembled genome was estimated to be 0.57 Mb and comprised a set of 570 predicted genes accounting for a total of 694 CDS regions found on the 5′3’ and 3′5’ ORFs. The GC percentage was estimated to be 24.98% (Table 2). Circular representation of the genomic structure of the mycoplasma MAG highlights CDS annotations on the negative (Fig. S3-a) and positive (Fig. S3-b) strands, respectively. To further resolve CDS annotations, a supplementary annotation framework was applied using the curated SEED database and the RAST server (Glass et al., 2010). The number of curated annotations was reduced to 600 CDS across the negative (275 CDS) and positive strands (325 CDS). Among these CDS regions, 390 had functional annotations, and within these, three annotated CDS regions (> 85% of similarity threshold against SEED) were identified as riboflavin kinase (EC 2.7.1.26/EC 2.7.1.26;1278 bp) along with two Riboflavin/purine transporters of length 1383 bp and 1608 bp, respectively. Other functions required for host-microbiota symbioses, such as ribonucleotide reductase, were annotated with SEED and are reported (Supplementary Table 1).

3.3. Phylogenetic proximity to Mycoplasma penetrans

Robust phylogenetic trees were recovered based on 16S rDNA and MLST data. The 16S rDNA tree includes four OTUs of Mycoplasma detected in the digestive tract of farmed salmon previously (Jin et al., 2019), as well as all OTUs recovered from our recent work on the same farm system (Heys et al., 2020). All Mycoplasma OTUs, including the MAG we sequenced lie in a clade alongside M. muris and M. penetrans. (Fig. 2). No evidence of an ecological association between mycoplasmas from similar ecotopes (e.g. marine, freshwater, terrestrial) was noted.

Fig. 2.

Fig. 2

Open in a new tab

Phylogenetic tree based on 16S rRNA gene sequences of mycoplasmas. Sequence name abbreviation of tree tips labels and clade A (including Spiroplasmas) are reported in Supp. File (sheet 2). The tree as consrtucted using MrBayes software , the nodes labels represent the calculated posterior probability values (see Materials and methods).

To further ascertain the above clustering of 16S rDNA sequences of Mycoplasma, and the phylogenetic relatedness, a second analysis based on MLST approach using 21 concatenated housekeeping genes (see PFAM IDs of markers and their functions in Supplementary File 1) increased our confidence in M. penetrans being close to the recovered mycoplasma MAG (Fig. 3). These 21 markers are detected in single copies and are conserved in the bacteria and the mycoplasmas lineage. The MLST tree shows high posterior probabilities in support of this topology (post prob. >0.9). Tip labels of the selected Mycoplasma sp. were further annotated with the information of genome size in Mbp. It should be noted that the genome sizes did not appear to correlate with the phylogenetic distribution of Mycoplasma sp. in the tree. The genome size of M. penetrans (1.36 Mb) is approximately double to that of the mycoplasma MAG and, is the highest among the Mycoplasma sp. genomes.

Fig. 3.

Fig. 3

Open in a new tab

Phylogenetic tree of mycoplasmas based on 21 MLST markers with the details given in the supplementary data. Sequence name abbreviation of tree tips labels is explained in Supp. File 1 (sheet 3). The tree as consrtucted using MrBayes software , the nodes labels represent the calculated posterior probability values (see Materials and methods).

3.4. Orthology, metabolic pathways and genome reduction analyses

A core genome analysis including the amino acid sequences of predicted CDS and all the available CDS from the closely related M. penetrans, available on NCBI repository, were blasted against the COG database. Circular track of the genome including the orthology clearly showed the difference in genome size between the mycoplasma MAG and M. penetrans. We observed heterogeneity across in terms of GC content and GC skew (Fig. 4). An orthology analysis based on SEED annotations indicated 14 functions (oxidative stress, periplasmic stress, protein biosynthesis, detoxification, ribonuclease H, cation transporters, ABC transporters) specific to the mycoplasma MAG, 144 functions specific to M. penetrans, and 156 functions that are common to mycoplasma MAG and M. penetrans. The shared functions between these two genomes belong to nine different general subsystems including those related to commensalism such as riboflavin metabolism; intracellular resistance; and resistance to antibiotics and toxic compounds (RATC) (Supplementary Table 2). We only found two similarity hits associated with RATC. Complimentary analysis pointed out a bifunctional riboflavin kinase/FMN FMN adenylyltransferase among the best reciprocal similarity's hits between the mycoplasma MAG in this study and Mycoplasma penetrans (Fig. S5; Supplementary Table 3).

Fig. 4.

Fig. 4

Open in a new tab

Circular track of the core genes. This figure highlights the orthologs genes shared between the mycoplasma MAG from this study and related Mycoplasma penetrans species.

To understand genome reduction in the mycoplasmas lineage, the genome size and genes count were compared across 247 strains (Fig. 5A; Supplementary Table 4) of the mycoplasmas available in the integrated microbial database (IMG). These strains include a wide variety of human and animal sources and comprising both parasitic and commensal. Given the collected data (Supplementary Table 4), also, this study mycoplasma MAG, gene content and genome size are strongly correlated. The average genome size of the 247 available mycoplasmas was 0.87 Mbp ± 0.15, and the average genes count was 790 ± 157 genes; however, this was not the case with all considered genomes. For instance, 8 genomes are lower than 0.8 Mb, accumulating somewhere between 829 and 1036 genes. Further analysis revealed that pseudogenes count had no relationship with genome size whilst both the transmembrane proteins and GC content were correlated with Mycoplasma sp. genome sizes (Fig. 5B). Furthermore, the average count of pseudogenes was significantly higher in free-living than within intracellular mycoplasmas (Supplementary Fig. S4), although available databases contain incomplete information with regards to mycoplasmas lifestyles. Finally, enzyme content was analysed in terms of metabolic pathways by comparing the annotated EC numbers of the mycoplasma MAG and M. penetrans. Common pathways of both genomes are highlighted in red lines (Fig. 6) including the riboflavin biosynthesis pathway.

Fig. 5.

Fig. 5

Open in a new tab

Genomic features of Mycoplasmas. (A) The plot of genome size and genes count in the Myoplsamas lineage. (B) The plot of functions and GC contents against genome size in the Mycoplasmas lineage.

Fig. 6.

Fig. 6

Open in a new tab

Pairwise Metabolic pathways comparison of mycoplasma MAG from this study and Mycoplasma penetrans. Red colour represents shared and conserved pathways between the two genomes, whereas blue colour represents the metabolic pathways of the mycoplasma MAG from this study and the green colour represent the metabolic pathways of Mycoplasma penetrans. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

4. Discussion

Mycoplasmas are hyper-abundant commensals of salmonid guts. Our study suggests, based on FISH data, that in Salmo salar, these organisms grow intracellularly in the epithelial and possibly muscular lining of the fish's GI tract, both in freshwater and during marine lifecycle stages. Mycoplasmas were not visualised on salmon ova, but we cannot rule out vertical transmission between individuals. The Mycoplasma sp. sequences recovered from Salmo salar, including the mycoplasma MAG reported here, had a strong phylogenetic similarity to M. penetrans. Comparative analysis of genome size and content across Mycoplasma sp. strains suggest that the genome we recovered in this study is, to the best of our knowledge, among the smallest ever observed. Comparative genomics analyses between the mycoplasma MAG and M. penetrans were undertaken and provide insight into the potential host-microbe interaction. Several features of the Mycoplasma's genome organisation and content suggest a strong level of dependence on the salmon host, as well as a potential role for nutrient provisioning relevant to aquaculture.

Mycoplasmas have been widely reported within Salmo salar (Holben et al., 2002), and other teleosts (Cheaib et al., 2021; Ei-Jakee, 2020; Sellyei et al., 2021). It is not uncommon to find that communities of gut microorganisms are dominated by mycoplasmas (Dehler et al., 2017). The modelling approaches comparing environmental and intestinal frequency distributions of these organisms undertaken in this study have previously suggested that salmon mycoplasmas are well adapted to the colonisation of their hosts (Heys et al., 2020). Culture-based approaches have had been less successful in isolating these organisms (Llewellyn et al., 2014) and despite numerous attempts, we failed to obtain pure cultures of Mycoplasma sp. from the adult salmon used in this study (data not shown). This may be attributed to a potential source of bias arising from cell wall deficiency (Razin, 1995) in mycoplasmas which decreases their growth in presence of inhibitors such as nucleoside and nucleobase as demonstrated in Mycoplasma pneumoniae (Sun and Wang, 2013) and others mycoplasmas (Wehelie et al., 2004). FISH data from the current study, however, indicate that many mycoplasmas could be sequestered within the basal the epithelial cells, suggesting potential unknown parameters in symbiosis with Salmo salar which were missed from the culture media trials and reduce their cultivability. Although only a qualitative assessment is possible by employing FISH, consistent with recent 16S amplicon-seq data from the same farm site (Heys et al., 2020), our data suggest that Mycoplasma comprised the majority of the resident microbes (Fig. 2).

A high level of adaptation to, and dependence on the host organism, is a key feature of many Mycoplasma species (Faucher et al., 2019). The exploitation of an intracellular niche, dependence on the host, and relative isolation from the other microorganisms and mobile genetic elements are thought to have contributed to genome decay in mycoplasmas (Sirand-Pugnet et al., 2007). One result of this decay is a reduction in genome size and the number of genes, and the mycoplasma MAG in this study appears to have been potentially affected by such processes in comparison to the other mycoplasmas (Fig. S5). According to the phylogenetic tree, we did not observe any specific relationship between the tree topology and the genome sizes of mycoplasmas (Fig. 2). Indeed, the closely related M. penetrans was over three times larger than the size of the mycoplasma MAG in this study. Despite sharing a recent ancestor with the human pathogen M. penetrans, a long and close evolutionary association of this Mycoplasma and salmonids is possible given the similarity of another mycoplasma MAG sourced from the Norwegian sea salmon and identified to M. penetrans (Jin et al., 2019). We were also able to identify Mycoplasma sp. in freshwater parr via the FISH method in this study. One potential route for vertical transmission of the Mycoplasma sp. among salmon could be observed during oviposition. We were not able to identify microbes colonising eggs in this study, although our sample size was limited. Further development on specific Mycoplasma sp. strain markers could potentially reveal their abundance as well as their epidemiology, and potential routes of intergenerational transmission.

Some insight for the potential role of these mycoplasma on salmon health in an aquaculture setting may be possible. Many well-characterised mycoplasmas are pathogens (Meseguer et al., 2003; Rosengarten et al., 2000; Sasaki et al., 2002), with several Mycoplasma sp. being responsible for human, animal and plant diseases; however, some species are considered to be commensal organisms (Razin et al., 1998; Siqueira et al., 2013). The role of Mycoplasma in the context of Salmo salar is not well established. Koch's postulates were not applied in this study (Falkow, 2004). Given the challenges encountered in culturing these microorganisms, it seems quite likely that they may never be applied. Furthermore, the apparent abundance of Mycoplasma in the healthy salmonids (Heys et al., 2020; Holben et al., 2002; Llewellyn et al., 2016), and lack of any clear associated pathology in gut tissues, implies that there is not a significant impact on the host health or fitness. Commensal exploitation of the host intracellular niche is potentially the most parsimonious description of the host-microbe interaction in this case. The ultimate metabolic adaptation to an intracellular lifestyle (i.e Buchnera, Wigglesworthia and Blochmannia) appears to be solely regulated by the metabolic activity of the host cells to which the bacteria may actively contribute to, by delivering essential metabolites that are limited in their habitats and are not produced by the hosts (Fuchs et al., 2012). In this context, the presence of genes encoding riboflavin pathway could potentially indicate benefit from the salmon host perspective of Mycoplasma sp. colonisation. Riboflavin, known as the precursor for the cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide, is an essential metabolite in organisms (Fuchs et al., 2012; Gutiérrez-Preciado et al., 2015), although vertebrates cannot synthesize it on their own (Vitreschak et al., 2002). The Mycoplasma may play a role in riboflavin supplementation in salmon, as has been suggested in several deep-sea snailfish (Lian et al., 2020), although it must be noted that riboflavin biosynthetic pathways also occur in pathogenic mycoplasmas (Gutiérrez-Preciado et al., 2015). Riboflavin supplementation is not limited to the mycoplasmas; in the bedbug Cimex lectularius, the gram-negative Wolbachia can synthesize biotin and riboflavin which, are crucial for the host growth and reproduction (Kubiak et al., 2018; Moriyama et al., 2015). Riboflavin biosynthesis is common for symbiotic associations and therefore occurs even in small and optimized genomes size like Wolbachia (~ 1.48 Mb) and mycoplasmas (0.51–1,38 Mb).

Also, it is reported that many Mycoplasma species can modify their surface antigenic molecules with high frequency (Horino et al., 2003; Rosengarten et al., 2000) which may likely play a key role in outmanoeuvring the host immune system. This ability may generate phenotypic heterogeneity in colonising Mycoplasma populations and provide fitness benefits such as evasion of host immune responses and to the adaptation to the environmental changes (Halbedel et al., 2007; Horino et al., 2003). The majority of the variable surface antigenic molecules of mycoplasmas are lipoproteins (Chambaud et al., 1999; Halbedel et al., 2007; Wise, 1993), which, depending on the species, are encoded by single or multiple genes (Rosengarten et al., 2000; Rosengarten and Wise, 1990). The expression of these lipoproteins, due to extensive antigenic variation, is thought to be a major factor for immune evasion, for example, the P35 lipoprotein and its paralogs, which are distributed across the surface of M. penetrans cells, are immunodominant (Distelhorst et al., 2017; Neyrolles et al., 1999; Wang et al., 1992). Two lipoprotein encoding genes were found only in Mycoplasma penetrans but not in the mycoplasma MAG of this study, and the lack of such virulence factors or mobile genes could again support a non-pathogenic lifestyle (Supplementary Table 2).

Our work demonstrates a potentially important ecological and functional association between Mycoplasma sp. and Salmo salar that merits further investigation in the context of aquaculture disease and, potentially, nutrition. Targeted meta-transcriptomics and strain-specific screening for this organism could improve our understanding of its biology, function, and its role in the host homeostasis. Furthermore, targeted studies involving genome reduction and their association with the host dynamics are also necessary to fully understand the evolution of Mycoplasma sp. symbiosis in Salmo salar. Furthermore, bespoke infections experiments, informed by the findings of this study, may lead to the development of practices that can improve the aquaculture industry, especially in the context of the probiotic potential of mycoplasmas in salmonids.

Author statement

Details of each author with their contribution in this paper:

Name of the author and e-mail ID Types of contribution
Bachar Cheaib
bachar.cheaib@glasgow.ac.uk 		Data analysis, Bioinformatics, Writing- Original draft
Pei Yang
pei-yang@outlook.com 		Methodology and Reviewing
Raminta Kazlauskaite:
r.kazlauskaite.1@research.gla.ac.uk 		Methodology and Reviewing
Elle Lindsay:
e.lindsay.1@research.gla.ac.uk 		Sampling and Reviewing
Chloe Heys
Chloe.Heys@glasgow.ac.uk 		Sampling and Editing
Toni Dwyer
Toni.Dwyer@glasgow.ac.uk 		Sampling and Reviewing
Michele De Noa
Michele.DeNoia@glasgow.ac.uk 		Methodology and Reviewing
Patrick Schaal
Patrick_Schaal@gmx.de 		Sampling and Reviewing
William Sloan
William.Sloan@glasgow.ac.uk 		Funding acquisition and Editing
Umer Ijaz
Umer.Ijaz@glasgow.ac.uk 		Funding acquisition and Editing
Martin Llewellyn
Martin.Llewellyn@glasgow.ac.uk 		Funding acquisition, Supervision, and Editing
Open in a new tab

Author contributions

ML and BC conceived and designed the study. PY, RK, MDN, TD, CH, PS, and EL collected the samples, performed FISH experiments, and analysed image data. BC performed the bioinformatics and interpreted the results. BC and ML wrote the original draft of the manuscript. All authors contributed to revisions of the manuscript.

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgements

This research was supported in part by a research grant from Biotechnology and Biological Sciences Research Council (BBSRC) grant number BB/P001203/1, Science Foundation Ireland, the Marine Institute and the Dept. for the Economy, N. Ireland, under the Investigators Programme Grant No. SFI/15/IA/3028, and the Scottish Aquaculture Innovation Centre. The authors gratefully acknowledge the Glasgow Imaging and PolyOmics Facility for their support & assistance in this work’. Umer Zeeshan Ijaz is supported by NERC Independent Research Fellowship NERC NE/L011956/1 as well as Lord Kelvin Adam Smith Leadership Fellowship (Glasgow).

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.aquaculture.2021.736772.

Appendix A. Supplementary data

Supplementary Fig. S1. Evaluation of the specificity of Mycoplasma probe against pure culture Escherichia coli (A) and Mycoplasma muris (B). Mycoplasma probe Myc1–1 showed specific hybridization, giving a positive signal solely with Mycoplasma muris. EUB338 I-II probes with Cy5 (red) and Mycoplasma specific probe (MYC) with Cy-3 (orange). DAPI A – E. coli, all probes overlaid (no Cy-3 fluorescence detected); B Mycoplasma – probes shown separately. Mycoplasma in size (0.1 um) is below the resolution of light microscopy, as such it is not possible to visualise individual cells.

mmc1.pdf (90.7KB, pdf)

Supplementary Fig. S2.1. The distribution of bacteria in the farmed salmon eggs. A very low abundance of bacteria was observed. Sections of egg samples were hybridized with Myc1–1 probe (Cy3, orange), Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes (Cy5, red) and stained with DAPI (blue). No signal of Mycoplasma was detected in egg samples, scaled at 50 μm.

Supplementary Fig. S2.2. Distribution of Mycoplasma in the stomach of salmon parr. (A) Image of DAPI signals (blue), (B) Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes with Cy5 (red), (C) Image of Mycoplasma Specific probe Cy-3(orange), (D) Overlay image of all channels, (E) Mycoplasma signals were clustered in small groups. These are scaled at 100 μm for (A, B, C, D,) and 20 μm for (E).

Supplementary Fig. S2.3. Distribution of Mycoplasma in the pyloric caecum of salmon parr. The images were an overlay of DAPI signals (blue), hybridization signals of Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes (Cy5, red) and Mycoplasma specific Myc1–1 probe (Cy3, orange). Signals of Mycoplasma aggregates on the muscularis mucosae are scaled at 10 μm.

Supplementary Fig. S2.4. Distribution of Mycoplasma in the midgut of salmon parr. Overlay of all channels. (A), Mycoplasma showed low abundance with a small number of bacteria detected in midgut sections. (B), Signals of Mycoplasma aggregated near epithelium cell nuclei. These are scaled at 20 μm for (A) and 10 μm for (B).

Supplementary Fig. S2.5. Distribution of Mycoplasma in the stomach of adult salmon. (A), DAPI, (B), MycI probe, and (C) all other bacteria probes. More signals were observed using universal probes in b than c using Mycoplasma specific probe. These are scaled at 50 μm.

Supplementary Fig. S2.6. Distribution of Mycoplasma in the pyloric caecum of adult salmon. Signals of bacterial aggregates on the muscularis mucosae, lamina propria (A) and epithelium (B) of the pyloric caecum. (C) Overlay of all channels and differential interference contrast (DIC) image showed Mycoplasma signals were clustered in high abundance around epithelium cell nuclei. These images are scaled at 50 μm for (A), 20 μm for (B), and 5 μm for (C).

Supplementary Fig. S2.7. Distribution of Mycoplasma in the midgut of adult salmon. Overlay of all channels scaled at 20 μm. (A), Mycoplasma was distributed closely to epithelium cells. (B), Overlay of all channels and DIC image confirmed Mycoplasma were in epithelium cells.

mmc2.pdf (1MB, pdf)

Supplementary Fig. S3. Circular track highlighting the functional annotations of the mycoplasma MAG from this study. The functions were predicted on (A) the negative strand 3′-5′ and (B) the positive strand 5′-3′.

mmc3.pdf (508.7KB, pdf)
mmc4.pdf (666.5KB, pdf)

Supplementary Fig. S4. Relationships of lifestyle and genome reduction. These include (A) plot of genes count and genome size, the (B) plot of genes count and pseudogenes, and (C) the proportion of non-coding DNA across lifestyle.

mmc5.pdf (148.7KB, pdf)

Supplementary Fig. S5. Circular track of best BLAST similarities. This figure highlights orthologous CDS regions between the mycoplasma MAG from this study and Mycoplasma penetrans. The orthologous CDS (WP.011077747.1) labelled in red encodes for bifunctional riboflavin kinase/FMN adenylyltransferase in Mycoplasma penetrans. See abbreviations of orthologs from this figure in Supplementary Table 3.

mmc6.pdf (151.1KB, pdf)

Supplementary Table 1. Summary of SEED subsystems annotations of the mycoplasma MAG from the pyloric caecum of Atlantic salmon (Salmo salar).

mmc7.xlsx (56.6KB, xlsx)

Supplementary Table 2. Summary of shared and unique SEED subsystems after pairwise genomic comparison of the mycoplasma MAG from this study and Mycoplasma penetrans.

mmc8.xlsx (29.2KB, xlsx)

Supplementary Table 3. Summary of best CDS orthologs based on best reciprocal BLAST hits between the mycoplasma MAG in this study and Mycoplasma penetrans.

mmc9.xlsx (11.1KB, xlsx)

Supplementary Table 4. Summary of genomic features from 247 strains of mycoplasmas. These data were collected from the IMG database.

mmc10.xlsx (250.7KB, xlsx)

Supplementary File 1. This file contains in sheet 1 the accession numbers and functions of the 21 markers concatenated in the MLST-based tree. Sheet 2 contains the sequence name abbreviation of tips labels within the 16 s gene tree and the sequence names of clade A. The sheet 3 includes the sequence name abbreviations of tips labels within the concatenated markers MLST-based tree.

mmc11.xlsx (27.8KB, xlsx)

Supplementary File 2

mmc12.zip (153.2KB, zip)

References

  1. Aceves A.K., Johnson P., Bullard S.A., Lafrentz S., Arias C.R. Description and characterization of the digestive gland microbiome in the freshwater mussel Villosa nebulosa (Bivalvia: Unionidae) J. Molluscan Stud. 2018;84:240–246. doi: 10.1093/mollus/eyy014. [DOI] [Google Scholar]
  2. Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. J. Mol. Biol. 1990;215:403–410. doi: 10.1016/S0022-2836(05)80360-2. [DOI] [PubMed] [Google Scholar]
  3. Amann R.I., Binder B.J., Olson R.J., Chisholm S.W., Devereux R., Stahl D.A. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 1990 Jun;56(6):1919–1925. doi: 10.1128/AEM.56.6. PMID: 2200342; PMCID: PMC184531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Boscaro V., Kolisko M., Felletti M., Vannini C., Lynn D.H., Keeling P.J. Parallel genome reduction in symbionts descended from closely related free-living bacteria. Nat. Ecol. Evol. 2017;1:1160–1167. doi: 10.1038/s41559-017-0237-0. [DOI] [PubMed] [Google Scholar]
  5. Bové J.M. Molecular features of Mollicutes. Clin. Infect. Dis. 1993;17:S10–S31. doi: 10.1093/clinids/17.Supplement_1.S10. [DOI] [PubMed] [Google Scholar]
  6. Buchfink B., Xie C., Huson D.H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods. 2015;12:59–60. doi: 10.1038/nmeth.3176. [DOI] [PubMed] [Google Scholar]
  7. Caspi R., Billington R., Fulcher C.A., Keseler I.M., Kothari A., Krummenacker M., Latendresse M., Midford P.E., Ong Q., Ong W.K., Paley S., Subhraveti P., Karp P.D. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 2018;46:D633–D639. doi: 10.1093/nar/gkx935. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chambaud I., Wróblewski H., Blanchard A. Interactions between mycoplasma lipoproteins and the host immune system. Trends Microbiol. 1999;7:493–499. doi: 10.1016/S0966-842X(99)01641-8. [DOI] [PubMed] [Google Scholar]
  9. Cheaib B., Seghouani H., Ijaz U.Z., Derome N. Community recovery dynamics in yellow perch microbiome after gradual and constant metallic perturbations. Microbiome. 2020;8:14. doi: 10.1186/s40168-020-0789-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cheaib B., Seghouani H., Llewellyn M., Vandal-Lenghan K., Mercier P.-L., Derome N. The yellow perch (Perca flavescens) microbiome revealed resistance to colonisation mostly associated with neutralism driven by rare taxa under cadmium disturbance. Anim. Microbiome. 2021;3:3. doi: 10.1186/s42523-020-00063-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Citti C., Blanchard A. Mycoplasmas and their host: emerging and re-emerging minimal pathogens. Trends Microbiol. 2013;21:196–203. doi: 10.1016/j.tim.2013.01.003. [DOI] [PubMed] [Google Scholar]
  12. Copper J.E., Budgeon L.R., Foutz C.A., van Rossum D.B., Vanselow D.J., Hubley M.J., Clark D.P., Mandrell D.T., Cheng K.C. Comparative analysis of fixation and embedding techniques for optimized histological preparation of zebrafish. Comp. Biochem. Physiol. Toxicol. Pharmacol. CBP. 2018;208:38–46. doi: 10.1016/j.cbpc.2017.11.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Costello E.K., Carlisle E.M., Bik E.M., Morowitz M.J., Relman D.A. Microbiome assembly across multiple body sites in low-birthweight infants. mBio. 2013:4. doi: 10.1128/mBio.00782-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Daims H., Brühl A., Amann R., Schleifer K.H., Wagner M. The domain-specific probe EUB338 is insufficient for the detection of all Bacteria: development and evaluation of a more comprehensive probe set. Syst. Appl. Microbiol. 1999 Sep;22(3):434–444. doi: 10.1016/S0723-2020(99)80053-8. PMID: 10553296. [DOI] [PubMed] [Google Scholar]
  15. Darzentas N. Circoletto: visualizing sequence similarity with Circos. Bioinformatics. 2010;26:2620–2621. doi: 10.1093/bioinformatics/btq484. [DOI] [PubMed] [Google Scholar]
  16. Dehler C.E., Secombes C.J., Martin S.A.M. Seawater transfer alters the intestinal microbiota profiles of Atlantic salmon (Salmo salar L.) Sci. Rep. 2017;7:13877. doi: 10.1038/s41598-017-13249-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Distelhorst S.L., Jurkovic D.A., Shi J., Jensen G.J., Balish M.F. The variable internal structure of the mycoplasma penetrans attachment organelle revealed by biochemical and microscopic analyses: implications for attachment organelle mechanism and evolution. J. Bacteriol. 2017;199 doi: 10.1128/JB.00069-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Egerton S., Culloty S., Whooley J., Stanton C., Ross R.P. The gut microbiota of marine fish. Front. Microbiol. 2018;9 doi: 10.3389/fmicb.2018.00873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Ei-Jakee J. Isolation and characterization of mycoplasmas from some moribund Egyptian fishes. Aquac. Int. 2020;12 [Google Scholar]
  20. Fadiel A., Eichenbaum K.D., El Semary N., Epperson B. Mycoplasma genomics: tailoring the genome for minimal life requirements through reductive evolution. Front. Biosci. J. Virtual Libr. 2007;12:2020–2028. doi: 10.2741/2207. [DOI] [PubMed] [Google Scholar]
  21. Falkow S. Molecular Koch’s postulates applied to bacterial pathogenicity — a personal recollection 15 years later. Nat. Rev. Microbiol. 2004;2:67–72. doi: 10.1038/nrmicro799. [DOI] [PubMed] [Google Scholar]
  22. Faucher M., Nouvel L.-X., Dordet-Frisoni E., Sagné E., Baranowski E., Hygonenq M.-C., Marenda M.-S., Tardy F., Citti C. Mycoplasmas under experimental antimicrobial selection: the unpredicted contribution of horizontal chromosomal transfer. PLoS Genet. 2019;15 doi: 10.1371/journal.pgen.1007910. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evol. Int. J. Org. Evol. 1985;39:783–791. doi: 10.1111/j.1558-5646.1985.tb00420.x. [DOI] [PubMed] [Google Scholar]
  24. Fuchs T.M., Eisenreich W., Heesemann J., Goebel W. Metabolic adaptation of human pathogenic and related nonpathogenic bacteria to extra- and intracellular habitats. FEMS Microbiol. Rev. 2012;36:435–462. doi: 10.1111/j.1574-6976.2011.00301.x. [DOI] [PubMed] [Google Scholar]
  25. Glass E.M., Wilkening J., Wilke A., Antonopoulos D., Meyer F. Using the metagenomics RAST server (MG-RAST) for analyzing shotgun metagenomes. Cold Spring Harb Protoc. 2010;2010 doi: 10.1101/pdb.prot5368. pdb.prot5368. [DOI] [PubMed] [Google Scholar]
  26. Grant J.R., Stothard P. The CGView server: a comparative genomics tool for circular genomes. Nucleic Acids Res. 2008;36:W181–W184. doi: 10.1093/nar/gkn179. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Guindon S., Gascuel O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 2003;52:696–704. doi: 10.1080/10635150390235520. [DOI] [PubMed] [Google Scholar]
  28. Gutiérrez-Preciado A., Torres A.G., Merino E., Bonomi H.R., Goldbaum F.A., García-Angulo V.A. Extensive identification of bacterial riboflavin transporters and their distribution across bacterial species. PLoS One. 2015;10 doi: 10.1371/journal.pone.0126124. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hallberg K.B., Coupland K., Kimura S., Johnson D.B. Macroscopic streamer growths in acidic, metal-rich mine waters in north Wales consist of novel and remarkably simple bacterial communities. Appl. Environ. Microbiol. 2006;72:2022–2030. doi: 10.1128/AEM.72.3.2022-2030.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Halbedel S., Hames C., Stülke J. Regulation of carbon metabolism in the Mollicutes and its relation to virulence. J. Mol. Microbiol. Biotechnol. 2007;12:147–154. doi: 10.1159/000096470. [DOI] [PubMed] [Google Scholar]
  31. Heys C., Cheaib B., Busetti A., Kazlauskaite R., Maier L., Sloan W.T., Ijaz U.Z., Kaufmann J., McGinnity P., Llewellyn M.S. Neutral processes dominate microbial community assembly in Atlantic Salmon, Salmo salar. Appl. Environ. Microbiol. 2020;86 doi: 10.1128/AEM.02283-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Holben W.E., Williams P., Saarinen M., Särkilahti L.K., Apajalahti J.H.A. Phylogenetic analysis of intestinal microflora indicates a novel mycoplasma Phylotype in farmed and wild Salmon. Microb. Ecol. 2002;44:175–185. doi: 10.1007/s00248-002-1011-6. [DOI] [PubMed] [Google Scholar]
  33. Horino A., Sasaki Y., Sasaki T., Kenri T. Multiple promoter inversions generate surface antigenic variation in mycoplasma penetrans. J. Bacteriol. 2003;185:231–242. doi: 10.1128/JB.185.1.231-242.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Huelsenbeck J.P., Ronquist F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics. 2001;17:754–755. doi: 10.1093/bioinformatics/17.8.754. [DOI] [PubMed] [Google Scholar]
  35. Huerta-Cepas J., Szklarczyk D., Heller D., Hernández-Plaza A., Forslund S.K., Cook H., Mende D.R., Letunic I., Rattei T., Jensen L.J., von Mering C., Bork P. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 2019;47:D309–D314. doi: 10.1093/nar/gky1085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Hyatt D., Chen G.-L., LoCascio P.F., Land M.L., Larimer F.W., Hauser L.J. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. doi: 10.1186/1471-2105-11-119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Jin Y., Angell I.L., Sandve S.R., Snipen L.G., Olsen Y., Rudi K. Atlantic salmon raised with diets low in long-chain polyunsaturated n-3 fatty acids in freshwater have a mycoplasma-dominated gut microbiota at sea. Aquac. Environ. Interact. 2019;11:31–39. doi: 10.3354/aei00297. [DOI] [Google Scholar]
  38. Kang D.D., Froula J., Egan R., Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3 doi: 10.7717/peerj.1165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Katoh K., Standley D.M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 2013;30:772–780. doi: 10.1093/molbev/mst010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Kieser S. Academic; 2019. ATLAS: A Snakemake Workflow for Assembly, Annotation, and Genomic Binning of Metagenome Sequence Data [WWW Document]https://silask.github.io/publication/atlas/ URL. (accessed 6.22.20) [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Kirchhoff H., Rosengarten R. Isolation of a motile mycoplasma from fish. Microbiology. 1984;130:2439–2445. doi: 10.1099/00221287-130-9-2439. [DOI] [PubMed] [Google Scholar]
  42. Kubiak K., Sielawa H., Chen W., Dzika E. Endosymbiosis and its significance in dermatology. J. Eur. Acad. Dermatol. Venereol. 2018;32:347–354. doi: 10.1111/jdv.14721. [DOI] [PubMed] [Google Scholar]
  43. Le S.Q., Gascuel O. An improved general amino acid replacement matrix. Mol. Biol. Evol. 2008;25:1307–1320. doi: 10.1093/molbev/msn067. [DOI] [PubMed] [Google Scholar]
  44. Li D., Liu C.-M., Luo R., Sadakane K., Lam T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674–1676. doi: 10.1093/bioinformatics/btv033. [DOI] [PubMed] [Google Scholar]
  45. Li H. 2013. Aligning Sequence Reads, Clone Sequences and Assembly Contigs with BWA-MEM. ArXiv13033997 Q-Bio. [Google Scholar]
  46. Lian C.-A., Yan G.-Y., Huang J.-M., Danchin A., Wang Y., He L.-S. Genomic characterization of a novel gut Symbiont from the Hadal Snailfish. Front. Microbiol. 2020;10 doi: 10.3389/fmicb.2019.02978. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Llewellyn M.S., Boutin S., Hoseinifar S.H., Derome N. Teleost microbiomes: the state of the art in their characterization, manipulation and importance in aquaculture and fisheries. Front. Microbiol. 2014;5 doi: 10.3389/fmicb.2014.00207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Llewellyn M.S., McGinnity P., Dionne M., Letourneau J., Thonier F., Carvalho G.R., Creer S., Derome N. The biogeography of the Atlantic salmon (Salmo salar) gut microbiome. ISME J. 2016;10:1280–1284. doi: 10.1038/ismej.2015.189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Manz W., Amann R., Ludwig W., Wagner M., Schleifer K.H. Phylogenetic oligonucleotide probes for the major subclasses of proteobacteria: problems and solutions. Syst. Appl. Microbiol. 1992;15:593–600. [Google Scholar]
  50. Martin D.H., Zozaya M., Lillis R.A., Myers L., Nsuami M.J., Ferris M.J. Unique vaginal microbiota that includes an unknown mycoplasma-like organism is associated with Trichomonas vaginalis infection. J. Infect. Dis. 2013;207:1922–1931. doi: 10.1093/infdis/jit100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Meseguer M.A., Álvarez A., Rejas M.T., Sánchez C., Pérez-Díaz J.C., Baquero F. Mycoplasma pneumoniae: a reduced-genome intracellular bacterial pathogen. Infect. Genet. Evol. 2003;3:47–55. doi: 10.1016/S1567-1348(02)00151-X. [DOI] [PubMed] [Google Scholar]
  52. Miyata M., Ogaki H. Cytoskeleton of Mollicutes. J. Mol. Microbiol. Biotechnol. 2006;11:256–264. doi: 10.1159/000094059. [DOI] [PubMed] [Google Scholar]
  53. Moran N.A. Accelerated evolution and Muller’s rachet in endosymbiotic bacteria. Proc. Natl. Acad. Sci. 1996;93:2873–2878. doi: 10.1073/pnas.93.7.2873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Moriyama M., Nikoh N., Hosokawa T., Fukatsu T. Riboflavin provisioning underlies Wolbachia’s fitness contribution to its insect host. mBio. 2015:6. doi: 10.1128/mBio.01732-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Neyrolles O., Eliane J.-P., Ferris S., Ayr Florio da Cunha R., Prevost M.-C., Bahraoui E., Blanchard A. Antigenic characterization and cytolocalization of P35, the major mycoplasma penetrans antigen. Microbiol. Read. Engl. 1999;145(Pt 2):343–355. doi: 10.1099/13500872-145-2-343. [DOI] [PubMed] [Google Scholar]
  56. Overbeek R., Olson R., Pusch G.D., Olsen G.J., Davis J.J., Disz T., Edwards R.A., Gerdes S., Parrello B., Shukla M., Vonstein V., Wattam A.R., Xia F., Stevens R. The SEED and the rapid annotation of microbial genomes using subsystems technology (RAST) Nucleic Acids Res. 2014;42:D206–D214. doi: 10.1093/nar/gkt1226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Parks D.H., Imelfort M., Skennerton C.T., Hugenholtz P., Tyson G.W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–1055. doi: 10.1101/gr.186072.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Posada D., Crandall K.A. Modeltest: testing the model of DNA substitution. Bioinforma. Oxf. Engl. 1998;14:817–818. doi: 10.1093/bioinformatics/14.9.817. [DOI] [PubMed] [Google Scholar]
  59. Razin S. Peculiar properties of mycoplasmas: the smallest self-replicating prokaryotes. FEMS Microbiol. Lett. 1992;100:423–431. doi: 10.1111/j.1574-6968.1992.tb14072.x. [DOI] [PubMed] [Google Scholar]
  60. Razin S., Yogev D., Naot Y. Molecular biology and pathogenicity of mycoplasmas. Microbiol. Mol. Biol. Rev. 1998;62:1094–1156. doi: 10.1128/mmbr.62.4.1094-1156.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Razin Shmuel. Molecular properties of mollicutes: a synopsis. In: Razin Shmuel, Tully J.G., editors. Molecular and Diagnostic Procedures in Mycoplasmology. Academic Press; San Diego: 1995. pp. 1–25. [DOI] [Google Scholar]
  62. Rocha E.P.C., Blanchard A. Genomic repeats, genome plasticity and the dynamics of mycoplasma evolution. Nucleic Acids Res. 2002;30:2031–2042. doi: 10.1093/nar/30.9.2031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Ronquist F., Teslenko M., van der Mark P., Ayres D.L., Darling A., Höhna S., Larget B., Liu L., Suchard M.A., Huelsenbeck J.P. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 2012;61:539–542. doi: 10.1093/sysbio/sys029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Rosengarten R., Wise K.S. Phenotypic switching in mycoplasmas: phase variation of diverse surface lipoproteins. Science. 1990;247:315–318. doi: 10.1126/science.1688663. [DOI] [PubMed] [Google Scholar]
  65. Rosengarten R., Citti C., Glew M., Lischewski A., Droeße M., Much P., Winner F., Brank M., Spergser J. Host-pathogen interactions in mycoplasma pathogenesis: virulence and survival strategies of minimalist prokaryotes. Int. J. Med. Microbiol. 2000;290:15–25. doi: 10.1016/S1438-4221(00)80099-5. [DOI] [PubMed] [Google Scholar]
  66. Sasaki Y., Ishikawa J., Yamashita A., Oshima K., Kenri T., Furuya K., Yoshino C., Horino A., Shiba T., Sasaki T., Hattori M. The complete genomic sequence of mycoplasma penetrans, an intracellular bacterial pathogen in humans. Nucleic Acids Res. 2002;30:5293–5300. doi: 10.1093/nar/gkf667. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Schmieder R., Edwards R. Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS One. 2011;6 doi: 10.1371/journal.pone.0017288. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Sellyei B., Varga Z., Cech G., Varga Á., Székely C. Mycoplasma infections in freshwater carnivorous fishes in Hungary. J. Fish Dis. 2021;44:297–304. doi: 10.1111/jfd.13283. [DOI] [PubMed] [Google Scholar]
  69. Siqueira F.M., Thompson C.E., Virginio V.G., Gonchoroski T., Reolon L., Almeida L.G., da Fonsêca M.M., de Souza R., Prosdocimi F., Schrank I.S., Ferreira H.B., de Vasconcelos A.T.R., Zaha A. New insights on the biology of swine respiratory tract mycoplasmas from a comparative genome analysis. BMC Genomics. 2013;14:175. doi: 10.1186/1471-2164-14-175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Sirand-Pugnet P., Lartigue C., Marenda M., Jacob D., Barré A., Barbe V., Schenowitz C., Mangenot S., Couloux A., Segurens B., de Daruvar A., Blanchard A., Citti C. Being pathogenic, plastic, and sexual while living with a nearly minimal bacterial genome. PLoS Genet. 2007;3 doi: 10.1371/journal.pgen.0030075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Steinegger M., Söding J. Clustering huge protein sequence sets in linear time. Nat. Commun. 2018;9:2542. doi: 10.1038/s41467-018-04964-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Sun R., Wang L. Inhibition of mycoplasma pneumoniae growth by FDA-approved anticancer and antiviral nucleoside and nucleobase analogs. BMC Microbiol. 2013;13:184. doi: 10.1186/1471-2180-13-184. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Trachtenberg S. Mollicutes. Curr. Biol. 2005;15:R483–R484. doi: 10.1016/j.cub.2005.06.049. [DOI] [PubMed] [Google Scholar]
  74. Vitreschak A.G., Rodionov D.A., Mironov A.A., Gelfand M.S. Regulation of riboflavin biosynthesis and transport genes in bacteria by transcriptional and translational attenuation. Nucleic Acids Res. 2002;30:3141–3151. doi: 10.1093/nar/gkf433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Wallner G., Amann R., Beisker W. Optimizing fluorescent in situ hybridization with rRNA-targeted oligonucleotide probes for flow cytometric identification of microorganisms. Syst. Appl. Microbiol. 1993;14(2):136–143. doi: 10.1002/cyto.990140205. PMID: 7679962. [DOI] [PubMed] [Google Scholar]
  76. Wang R.Y.-H., Hayes M.M., Wear D.J., Lo S.C., Shih J.W.-K., Alter H.J., Grandinetti T., Pierce P.F. High frequency of antibodies to Mycoplasma penetrans in HIV-infected patients. Lancet. 1992;340:1312–1316. doi: 10.1016/0140-6736(92)92493-Y. Originally published as Volume 2, Issue 8831. [DOI] [PubMed] [Google Scholar]
  77. Wehelie R., Eriksson S., Wang L. Effect of fluoropyrimidines on the growth of Ureaplasma urealyticum. Nucleosides Nucleotides Nucleic Acids. 2004;23:1499–1502. doi: 10.1081/NCN-200027714. [DOI] [PubMed] [Google Scholar]
  78. Wise K.S. Adaptive surface variation in mycoplasmas. Trends Microbiol. 1993;1:59–63. doi: 10.1016/0966-842x(93)90034-o. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Yamada T., Letunic I., Okuda S., Kanehisa M., Bork P. iPath2.0: interactive pathway explorer. Nucleic Acids Res. 2011;39:W412–W415. doi: 10.1093/nar/gkr313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Yavlovich A., Tarshis M., Rottem S. Internalization and intracellular survival of Mycoplasma pneumoniae by non-phagocytic cells. FEMS Microbiol. Lett. 2004;233:241–246. doi: 10.1111/j.1574-6968.2004.tb09488.x. [DOI] [PubMed] [Google Scholar]
  81. Zarkasi K.Z., Taylor R.S., Abell G.C.J., Tamplin M.L., Glencross B.D., Bowman J.P. Atlantic Salmon (Salmo salar L.) gastrointestinal microbial community dynamics in relation to Digesta properties and diet. Microb. Ecol. 2016;71:589–603. doi: 10.1007/s00248-015-0728-y. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Supplementary Fig. S1. Evaluation of the specificity of Mycoplasma probe against pure culture Escherichia coli (A) and Mycoplasma muris (B). Mycoplasma probe Myc1–1 showed specific hybridization, giving a positive signal solely with Mycoplasma muris. EUB338 I-II probes with Cy5 (red) and Mycoplasma specific probe (MYC) with Cy-3 (orange). DAPI A – E. coli, all probes overlaid (no Cy-3 fluorescence detected); B Mycoplasma – probes shown separately. Mycoplasma in size (0.1 um) is below the resolution of light microscopy, as such it is not possible to visualise individual cells.

mmc1.pdf (90.7KB, pdf)

Supplementary Fig. S2.1. The distribution of bacteria in the farmed salmon eggs. A very low abundance of bacteria was observed. Sections of egg samples were hybridized with Myc1–1 probe (Cy3, orange), Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes (Cy5, red) and stained with DAPI (blue). No signal of Mycoplasma was detected in egg samples, scaled at 50 μm.

Supplementary Fig. S2.2. Distribution of Mycoplasma in the stomach of salmon parr. (A) Image of DAPI signals (blue), (B) Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes with Cy5 (red), (C) Image of Mycoplasma Specific probe Cy-3(orange), (D) Overlay image of all channels, (E) Mycoplasma signals were clustered in small groups. These are scaled at 100 μm for (A, B, C, D,) and 20 μm for (E).

Supplementary Fig. S2.3. Distribution of Mycoplasma in the pyloric caecum of salmon parr. The images were an overlay of DAPI signals (blue), hybridization signals of Gam-1, FIR-1, EUB338, EUB338 II, EUB338 III probes (Cy5, red) and Mycoplasma specific Myc1–1 probe (Cy3, orange). Signals of Mycoplasma aggregates on the muscularis mucosae are scaled at 10 μm.

Supplementary Fig. S2.4. Distribution of Mycoplasma in the midgut of salmon parr. Overlay of all channels. (A), Mycoplasma showed low abundance with a small number of bacteria detected in midgut sections. (B), Signals of Mycoplasma aggregated near epithelium cell nuclei. These are scaled at 20 μm for (A) and 10 μm for (B).

Supplementary Fig. S2.5. Distribution of Mycoplasma in the stomach of adult salmon. (A), DAPI, (B), MycI probe, and (C) all other bacteria probes. More signals were observed using universal probes in b than c using Mycoplasma specific probe. These are scaled at 50 μm.

Supplementary Fig. S2.6. Distribution of Mycoplasma in the pyloric caecum of adult salmon. Signals of bacterial aggregates on the muscularis mucosae, lamina propria (A) and epithelium (B) of the pyloric caecum. (C) Overlay of all channels and differential interference contrast (DIC) image showed Mycoplasma signals were clustered in high abundance around epithelium cell nuclei. These images are scaled at 50 μm for (A), 20 μm for (B), and 5 μm for (C).

Supplementary Fig. S2.7. Distribution of Mycoplasma in the midgut of adult salmon. Overlay of all channels scaled at 20 μm. (A), Mycoplasma was distributed closely to epithelium cells. (B), Overlay of all channels and DIC image confirmed Mycoplasma were in epithelium cells.

mmc2.pdf (1MB, pdf)

Supplementary Fig. S3. Circular track highlighting the functional annotations of the mycoplasma MAG from this study. The functions were predicted on (A) the negative strand 3′-5′ and (B) the positive strand 5′-3′.

mmc3.pdf (508.7KB, pdf)
mmc4.pdf (666.5KB, pdf)

Supplementary Fig. S4. Relationships of lifestyle and genome reduction. These include (A) plot of genes count and genome size, the (B) plot of genes count and pseudogenes, and (C) the proportion of non-coding DNA across lifestyle.

mmc5.pdf (148.7KB, pdf)

Supplementary Fig. S5. Circular track of best BLAST similarities. This figure highlights orthologous CDS regions between the mycoplasma MAG from this study and Mycoplasma penetrans. The orthologous CDS (WP.011077747.1) labelled in red encodes for bifunctional riboflavin kinase/FMN adenylyltransferase in Mycoplasma penetrans. See abbreviations of orthologs from this figure in Supplementary Table 3.

mmc6.pdf (151.1KB, pdf)

Supplementary Table 1. Summary of SEED subsystems annotations of the mycoplasma MAG from the pyloric caecum of Atlantic salmon (Salmo salar).

mmc7.xlsx (56.6KB, xlsx)

Supplementary Table 2. Summary of shared and unique SEED subsystems after pairwise genomic comparison of the mycoplasma MAG from this study and Mycoplasma penetrans.

mmc8.xlsx (29.2KB, xlsx)

Supplementary Table 3. Summary of best CDS orthologs based on best reciprocal BLAST hits between the mycoplasma MAG in this study and Mycoplasma penetrans.

mmc9.xlsx (11.1KB, xlsx)

Supplementary Table 4. Summary of genomic features from 247 strains of mycoplasmas. These data were collected from the IMG database.

mmc10.xlsx (250.7KB, xlsx)

Supplementary File 1. This file contains in sheet 1 the accession numbers and functions of the 21 markers concatenated in the MLST-based tree. Sheet 2 contains the sequence name abbreviation of tips labels within the 16 s gene tree and the sequence names of clade A. The sheet 3 includes the sequence name abbreviations of tips labels within the concatenated markers MLST-based tree.

mmc11.xlsx (27.8KB, xlsx)

Supplementary File 2

mmc12.zip (153.2KB, zip)

RESOURCES