Next Article in Journal
17-AAG-Induced Activation of the Autophagic Pathway in Leishmania Is Associated with Parasite Death
Next Article in Special Issue
A Systematic Review (1990–2021) of Wild Animals Infected with Zoonotic Leishmania
Previous Article in Journal
Intra-Colonial Viral Infections in Western Honey Bees (Apis Mellifera)
Previous Article in Special Issue
Diverse Genotypes and Species of Cryptosporidium in Wild Rodent Species from the West Coast of the USA and Implications for Raw Produce Safety and Microbial Water Quality
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Metagenomics Analysis Reveals an Extraordinary Inner Bacterial Diversity in Anisakids (Nematoda: Anisakidae) L3 Larvae

1
Museo Nacional de Ciencias Naturales, Dpto Biodiversidad y Biología Evolutiva, CSIC, 28006 Madrid, Spain
2
Centro Nacional de Biotecnología, Departamento de Biotecnología Microbiana, CSIC, 28049 Madrid, Spain
3
Departamento de Protección Vegetal, INIA, 28040 Madrid, Spain
4
Servicio de Immunología, Hospital Universitario La Paz, 28046 Madrid, Spain
5
Instituto de Ciencia y Tecnología de Alimentos y Nutrición, CSIC, 28040 Madrid, Spain
6
Servicio de Microbiología y Unidad de Investigación, Hospital Son Espases, (IdISPa), 07120 Palma de Mallorca, Spain
7
Unidad de Genómica, “Scientific Park of Madrid”, Campus de Cantoblanco, 28049 Madrid, Spain
8
Biotechvana, “Scientific Park”, University of Valencia, 46980 Valencia, Spain
*
Author to whom correspondence should be addressed.
Microorganisms 2021, 9(5), 1088; https://doi.org/10.3390/microorganisms9051088
Submission received: 29 March 2021 / Revised: 5 May 2021 / Accepted: 10 May 2021 / Published: 19 May 2021

Abstract

:
L3 larvae of anisakid nematodes are an important problem for the fisheries industry and pose a potential risk for human health by acting as infectious agents causing allergies and as potential vectors of pathogens and microrganisms. In spite of the close bacteria–nematode relationship very little is known of the anisakids microbiota. Fresh fish could be contaminated by bacteria vectored in the cuticle or in the intestine of anisakids when the L3 larvae migrate through the muscles. As a consequence, the bacterial inoculum will be spread, with potential effects on the quality of the fish, and possible clinical effects cannot be discarded. A total of 2,689,113 16S rRNA gene sequences from a total of 113 L3 individuals obtained from fish captured along the FAO 27 fishing area were studied. Bacteria were taxonomically characterized through 1803 representative operational taxonomic units (OTUs) sequences. Fourteen phyla, 31 classes, 52 orders, 129 families and 187 genera were unambiguously identified. We have found as part of microbiome an average of 123 OTUs per L3 individual. Diversity indices (Shannon and Simpson) indicate an extraordinary diversity of bacteria at an OTU level. There are clusters of anisakids individuals (samples) defined by the associated bacteria which, however, are not significantly related to fish hosts or anisakid taxa. This suggests that association or relationship among bacteria in anisakids, exists without the influence of fishes or nematodes. The lack of relationships with hosts of anisakids taxa has to be expressed by the association among bacterial OTUs or other taxonomical levels which range from OTUs to the phylum level. There are significant biological structural associations of microbiota in anisakid nematodes which manifest in clusters of bacteria ranging from phylum to genus level, which could also be an indicator of fish contamination or the geographic zone of fish capture. Actinobacteria, Aquificae, Firmicutes, and Proteobacteria are the phyla whose abundance value discriminate for defining such structures.

1. Introduction

Nematodes of the family Anisakidae are common parasites of marine mammals, where these nematodes complete their biological cycle reaching the adult stage. With worldwide geographic distribution, the L3 larvae of these nematodes (larvae in the third stage) are an important problem for the fisheries industry [1] due the commercial fishes being very important paratenic hots. The L3 larvae of anisakids pose a risk for human health by acting as agents causing allergies [2,3], as potential vectors of allergens in foods (fish and fish products) [4,5] and pathogenic microoganisms [6]. These nematodes can infect humans an other hosts as fishes and cephalopods which are considered accidental and paratenic host, respectively. After the first clinical case in 1960 associated with the consumption of fresh raw fish infected by Anisakis [7], the incidence of these parasites is today considered an international public health problem. Although the parasite does not develop and complete the biological cycle in the humans [8], the infestation by these nematodes or their excreted-secreted products in fishes may cause severe allergies [4,9] in an ever increasing, more sensitized worldwide population. According to the “Rapid Alert System for Food and Feed of the European Union” A. simplex sensu lato is considered responsible for more than 33% of the biological risk alerts in Europe [10]. The epidemiological studies on the incidence of Anisakiasis (or Anisakiosis) in the Spanish population conclude that it is one of the effects of nematodes with the highest prevalence in Spain with some regional variations ranging from 0.43% to 22% [11]. It is considered a problem associated with Spanish customs and habits given that Spain is one of the main consumer countries of fish and seafood products. The family Anisakidae (Nematoda: Rhabditida: Ascaridomorpha) is represented by at least 24 genera split into three subfamilies: Goeziinae (parasites of Teleostei), Raphidascaridinae (fish parasites in general and occasionally birds) and Anisakinae (parasites of mammals, birds, reptiles and elasmobranch fish). Seven genera of Anisakidae are paratenic or obligatory parasites of marine fishes for human consumption (generally teleostii) [Anisakis, Paranisakis, Contracaecum (Thynascaris), Phocanema (Pseudoterranova), Raphidascaris (Hysterothylacium), Sulcascaris and Terranova] [12]. The best known are Phocanamea (Pseudoterranova), Contracaecum (Thynascaris), Raphidascaris (Hysterothylacium) and Anisakis. Although the real incidence of other species of the genus Anisakis in humans is not known, the species complex Anisakis simplex sensu lato (formed by three species A. simplex sensu stricto, A. pegreffii and A. berlandi [13]) is considered responsible for the majority of parasitosis and allergies by means of the consumption of raw or insufficiently processed or cooked fish in Spain and worldwide [14,15]; the main reason could be due to it being the most frequent species of the family Anisakidae. The infestation of fishes by other Anisakidae is considered restricted to certain geographic areas and associated mainly with cod (infestation by Pseudoterranova decipiens) or herring (Clupea spp.); however, the distribution of anisakid species is universal and having “multi hosts”, with the common knowledge of the presence of L3 larvae of other anisakids in commercial fishes, which are not members of the genus Anisakis.
Nematodes are able to provide valuable information on bacterial virulence mechanisms which are difficult to obtain with traditional animal models [16,17]. In the review of Wekell, et al., [6] at least, 69 pathogenic microorganisms were considered to be mainly propagated through seafood products, suggesting that control of seafood is a relevant aspect in the sanitary alert in the public national health system. When Caenorhabditis elegans have been used as animal model [18] it has been observed that numerous bacteria infect the intestine and cuticular surface, a situation that may ground the hypothesis of dispersing infections among populations in contact with nematodes. It has also been demonstrated that bacteria that may be a risk for human health are also associated to nematodes, including: Aeromonas hydrophila [19], Enterococcus faecalis [20], Escherichia coli [21], Salmonella enterica [22], Serratia marcescens [23], Staphylococcus aureus [24], Streptococcus spp. [25] and Yersinia spp. [26]. Despite this close bacterial–nematode relationship very little is known about the role of nematodes in general in the spread of infectious diseases, a feature particularly relevant in the case of anisakids given the cosmopolitan nature of the family Anisakidae. It is worth mentioning that fresh fish containing anisakids could be contaminated by bacteria vectored in the cuticle or in the intestine of these nematodes when the L3 larvae migrate through the muscles. As a consequence, the bacterial microbiota associated to anisakids will be extended through all fish meat, affecting the shelf life and quality of the product, as well as acting as transmitters of potential pathogens. Indeed, to the known allergenic processes there are other symptomatic effects linked to anisakids intake when raw or poor cooked fish include, diarrheas, vomits, fever and abdominal pain, with all possible combinations [27], all symptoms of bacterial infections.
In this work we have studied the microbiome of Anisakidae based on the examination of fishes parasitized by larval specimens in the same development stage (third stage larvae, L3) captured in waters from the FAO 27 fishing area (a very important commercial area for Europe) in a general survey carried out in the Central Fish Market of Madrid (Mercamadrid).

2. Material and Methods

2.1. Anisakids Collection and Taxonomic Identification

Anisakids were collected during a general survey carried out in Mercamadrid Central Fish Market, related to the incidence of these nematodes in commercial fish species. All specimens studied were captured in the FAO 27 fishing area of distribution. Pools of L3 larvae specimens (12–20) were randomly obtained from each of 113 different individual fishes hosts in which the presence of anisakids were evident in a visual inspection (Additional file 1: Table S1); they were removed from each fish following published procedures [28,29,30]. The 113 larvae pools were rinsed in 0.9% saline solution and placed in an antibiotic-antimicotic solution (80 mg gentamicin sulphate, 0.625 mg amphotericine B, 10,000 IU penicillin G, 10 mg streptomycin sulphate, 4.5 mL of saline Hank´s solution making up to 10 mL of volume with bi-distilled water; Sigma Aldrich, St. Louis, MO, USA). After 40 min in this disinfectant solution the larvae pools were rinsed in bi-distilled water for 1 h. From each of 113 larvae pools (from each fish host), a specimen was isolated and for each of these larvae specimens, the caudal part was used for DNA extraction and polymerase chain reaction (PCR) amplification for species identification; this caudal part and the rest of the body (used for 16S rRNA gene amplification) were separately stored at −80 °C until required. anisakids species identification was performed following the taxonomic criteria of [31,32] by using the ITS1 region of the nuclear ribosomal DNA (rDNA). Briefly, individual anisakids L3 stage juveniles were placed in an Eppendorf tube after previously having a small part of the caudal region removed to allow molecular identification of each individual. DNA was extracted and purified using the Speedtools Tissue DNA Extraction Kit (Biotools) following manufactures instructions. Molecular identification was carried out for each individual using PCR-RFLP. The forward primer A 5′-GTCGAATTCGTAGGTGAACCTGCGGAAGGATCA-3′ and reverse primer B 5′-GCCGGATCCGAATCCTGGTTAGTTTCTTTTCCT -3′ [32] were used in reactions containing, 10 mM Tris-HCl (pH 8.3), 1.5 mM MgCl2, 50 mM KCl, 200 µM each of dATP, dCTP, dGTP and dTTP and 1 unit of DNA polymerase (Biotools B and M labs, S.A. Madrid, Spain). Initial denaturalization was carried out for a period of 2 min at 94 °C followed by 35 cycles of 94 °C for 1 min, 58 °C for 1 min, 72 °C for 1 min followed by a final 7 min extension at 72 °C. Amplified DNA fragments were digested with the restriction enzymes HhaI and HinfI (New England Biolabs, Massachusetts, MA, USA) following the manufacturer’s instructions. Restriction fragments were separated by electrophoresis in aTris- Borate-EDTA (TBE) buffered 2.5% agarose gel, stained with SYBER Safe DNA gel stain and visualized with ultraviolet (UV) illumination.

2.2. 16 S rRNA-rRNA Amplicons, Preparation and Illumina Sequencing

Total DNA of L3 individuals without caudal parts previously used for taxonomic anisakids identification were extracted as above [Speedtools Tissue DNA Extraction Kit (Biotools, B and M labs, S.A. Madrid, Spain)]. Purified DNAs were quantified by Picogreen and 3ng of input DNA were used for specific amplification using the primers.
5’-ACACTGACGACATGGTTCTACACCTACGGGNGGCWGCAG-3’ and
5’-TACGGTAGCAGAGACTTGGTCTGACTACHVGGGTATCTAATCC-3’,
These amplify the V3-V4 region of 16S rRNA gene [33] and include an extension tail that allows further processing. As standard, the first PCR was done for 20 cycles using Q5® Hot Start High-Fidelity DNA Polymerase (New England Biolabs, Massachusetts, MA, USA) in the presence of 100nM primers. Negative non-template controls were included in every round of PCR amplification made to check the possible presence of contaminants at the reagent level, showing in all cases completely negative results. Positive amplifications were assessed by gel electrophoresis and positive samples were used for a second PCR of 15 cycles using Q5® Hot Start High-Fidelity DNA Polymerase (New England Biolabs, Massachusetts, MA, USA) in the presence of 400nM of second-step primers:
5′-AATGATACGGCGACCACCGAGATCTACACTGACGACATGGTTCTACA-3′ and 5′-CAAGCAGAAGACGGCATACGAGAT-[10 nucleotides barcode]-TACGGTAGCAGAGACTTGGTCT-3′) which anneal over the extension of the first primer pair and serve also for sample barcoding, were taken from the Access Array Barcode Library for Illumina Sequencers (Fluidigm). The final amplicons were validated and quantified in a Bioanalyzer (Agilent) so that an equimolecular pool could be prepared. The pool of amplicons was further purified by agarose gel extraction and was titrated after purification and checking by quantitative PCR, using the “Kapa-SYBR FAST qPCR kit forLightCycler480” and a reference standard for quantification. This pool was finally denatured and seeded on an Illumina flow cell at a density of 10pM, where clusters were formed and sequenced using a “MiSeq Reagent Kit v3”, in a 2 × 300 pair-end sequencing run on a MiSeq sequencer (illumina).

2.3. Bioinformatics Analysis and Data Availability

To analyze the structure of the microbiota, the V4 variable region of the microbial 16S rRNA RNA was amplified using the standard Illumina primers (Illumina Inc., San Diego, CA, USA). The resultant libraries were sequenced at the facilities from the “Fundación Parque Científico de Madrid” (FPCM, Campus de Cantoblanco, Spain) using the Illumina platform in a pair-end reads with 280 cycles. Approximately 25 Mb were sequenced from the 113 microbiota with an average of ~250,000 reads for each sampled microbiota (151,171 bp to 412,396 bp) and were analyzed using MOTHUR v.1.35.1 software [34] following the standard procedure (SOP) for Illumina MiSeq sequences (http://www.mothur.org/wiki/MiSeq_SOP, accessed on 16 March 2017) to check the raw data using the FASTQC tool [35]. The sequences were filtered by quality using PRINSEQ-lite v.0.20.4 [36]. To this work, some modifications at the SOP were implemented [37]. Quality control of sequences eliminated low-quality reads (shorter than 200 bp and average quality lower than 25) as described in [38]. The paired-end reads were assembled and sequences were removed if they did not have a length ranging between 280 and 320 base pairs. After assembling, all sequences were trimmed to start and finish at the same coordinates [39]. Unique sequences from all samples were merged and aligned to the SILVA (https://www.arb-silva.de, accessed on 28 January 2017) bacteria reference database [40,41]. Operational taxonomic units (OTUs) were identified and grouped using the software package MOTHUR v.1.31.2 following the recommendations of the standard operating procedure for Illumina MiSeq platform (https://www.mothur.org/wiki/MiSeq_SOP, accessed on 16 March 2017).
According the pipeline followed, paired-end reads were merged and chimeric reads were removed using USEARCH v6.1 [42,43] implemented in MOTHUR. After, resultant sequences were clustered into taxonomic units (OTUs). The resulting sequences that were not classified at least at the kingdom level or identified as Archaea, Eukaryota, chloroplast or mitochondria were removed from the analysis. After, the sequences were classified into groups corresponding to their taxonomy at different levels (kingdom, order, family and genus) and then assigned to OTUs using a phylotype threshold of equal or greater than 97% with further taxonomic classification using the Silva database [44]. After OTU assignation, the data were corrected to fix the misallocated taxa adjusting it to the right level using a custom Perl script. All taxa were counted with respect to their presence in each sample and the taxa with less than 20 sequences counted in all 113 samples were considered less representative and then were culled to avoid misunderstood analysis. Taxa with ≥20 sequences were maintained for further analysis.

2.4. Statistical Analysis

MOTHUR was also used to generate diversity indices (Simpson and Shannon) and rarefaction curves of samples. The Renyi diversity index was used to explore differences in OTU diversity among L3 anisakids individuals. This index provided the profile of four diversity indices (total richness, Shannon–Weiner, Simpson–Yule, and Berger–Parker) according a value (α). The Renyi index has the advantage that allows in a glance to compare independence of samples diversity; that is, when different profiles intercept, their diversity are non-comparable [45]. Calculation of Renyi index was carried out using PAST software [46] (http://folk.uio.no/ohammer/past, accessed on 4 April 2020).
MOTHUR was also used for quantitative analysis by means of correlations (Pearson and Spearman) according to number of sequences in each individual (samples). The programme also provides cluster analysis based on correlations indices in order to detect nematode taxon or host (fish) influence. For detection of bacterial biota structure (clusters or bacterial association), we have used Statistica v.6 programme (STATISTICA data analysis software system, version 6. 2001, www.statsoft.com, accessed on 19 July 2019) [47].
Cluster analysis of samples and factorial analysis, including hierarchical analysis option for classification clusters of variables into de factorial space was performed. Microbiota comparison of clusters was made by the discriminant analysis option after logarithm transformation of abundance [log (x + 1)]. When needed, graphic representation of most significant microbiota was referred to according to those values and clusters of samples. Linkage of clusters of samples with inferred microbiota structure was performed by projection of the active and supplementary variables option through the principal component option into the factor analysis programme; this was used due the facilities for hierarchical analysis of oblique factors which allow the number of clusters in the set of variables to be detected.

3. Results

The 113 larva L3 individuals used for this study were taken from ten different fish species (Additional file 1: Table S1): Micromesistius poutassou (9), Merluccius merluccius (76), Conger conger (2), Gadus morhua (2), Lepidorhombus boscii (9), Lophius budegassa (5), Lophius piscatorius (5), Phycis blennoides (2), Scomber scombrum (1), Thunnus thynnus (2). The anisakids taxa resulted as: Pseudoterranova sp. (5), Anisakis simplex (100), A. pegreffii (7) and hybrid haplotypes from A. simplex and A. pegreffii (1). The asymmetric representation of these variables in the survey avoid the use of standard parametric statistic. However, the use of a multifactorial approach made it possible to detect the importance of each of the variables related to microbiota, even if they are spurious.
A total of 2,689,113 sequences were generated (average of 23797 sequences per analyzed sample) at the different taxonomical level (phyla, class, order, family, and genus) of associated microbiota based on the 16S rRNA gene sequences for OTUs (Supplementary Materials Table S2). The bacterial lineages which have been detected based on 16S rRNA gene sequencing follow a conservative taxonomy. Fourteen phyla have been taxonomically characterized through 1803 different sequences quoted to OTUs of which, 105 are “unclassified” (5.82% of the whole sequences). In total, 14 phyla, 31 classes and 52 orders were unambiguously identified (Table 1) except four orders from the phylum Cyanobacteria (from classes MLE1-12, Subsection IV and Subsection III in addition to other unclassified classes). Table 2, Table 3 and Table 4 shows the systematics of orders, families (129) and genera (187) (only unambiguous genera are considered; 6 with very scarce representation and 13 unclassified genera were excluded). For most of the Cyanobacteria it was not possible to classify them at phylum level. Proteobacteria (Table 2) is represented by 92 genera (40% are members of the Class Alphaproteobacteria), Firmicutes (75 genera, from which 68% are members from the order Clostridales) and Actinobacteria (Table 3) (46 genera, from which 74% are from the order Actinomycetales) are the most diverse phyla detected in this study. The genera of these three phyla represent 81% of the total associated genera of anisakids. Taking this into account, the class Alphabacteria represented by 7 orders and 55 genera should be the most important from Proteobacteria; Rhizobiales (20 genera), Rhodospirales (14 genera) and Sphingomonadales (at least 9 genera) are the most important orders from Proteobacteria. Class Clostridia would be the most important from Firmicutes, especially the order Clostridiales (51 genera) and class Actinobacteria represented by order Actynomycetales (34 genera) from the phylum Actinobacteria. The phyla Acidobacteria, Aquificae, Clamydiae, Deinococcus-Thermus, Fusobacteria, Planctomycetes, Synergetes and Verrcomicrobia have a low genera’s diversity in anisakids (Table 4).
The presence (frequency) and abundance of phyla and orders in the individuals of anisakids (samples) is summarized in Table 1: Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, Proteobacteria and Cyanobacteria are present in all anisakids specimens. Other important presence is for Acidobacteria (present in 76% of samples), Chloroflexi (74.33%), Planctomycetes (63.72%) and Deinococcus-Thermus (61.94%). There is a minor presence of Verrucomicrobia (23.9%), Chlamydiae (15.93%), Synergistetes (10.62%) and Aquificae (2.65%). The most abundant phyla into the anisakids are Proteobacteria (with an average of 9291 bacteria per L3 larvae), Firmicutes (average 5659) and Actinobacteria (average 2838). Fusobacteria (average 755), Bacteroidetes (average 705) and Cyanobacteria (average 297) could be considered of medium abundance in the L3 larvae compared with the rest of the phyla which range from 9 to 76 bacteria per L3 larva: Aquificae (average 76), Synergistetes (average 73), Chloroflexi (average 66), Acidobacteria (average 59), Planctomycetes (average 35), Deinococcus-Thermus (23), Verrucomicrobia (average 17) and Chlamydiae (average 9).
Orders with higher presence (frequency) range from 75% to 100% considering the total individuals (samples). These are: Acidobacteriales, Actinomycetales, Bacteroidales, Flavobacteriales, Sphingobacteriales, Deinoccocales, Bacillales Lactobacillales, Clostridiales, Fusobacteriales, Caulobacterales, Rhizobiales, Rhodobacterales, Rhodospirillales Sphingomonadales, Burkholderiales, Neisseriales, Campylobacteriales Enterobacteriales, Pasteurellales, Pseudomonadales and Vibrionales. Orders present in the samples (anisakids individuals) with a frequency between 40% to 75% are: Acidimicrobiales, Bifidobacteriales, Coriobacteriales, Erysipelothrichales, Planctomycetales, Aeromonadales, Alteromonadales and Xanthomonadales. Orders with a frequency between 10% to 40% are: Rubrobacterales, Chlamydiales, Anaerolineales, Chloroflexales, Bdellovibrionales, Myxococcales, Cardiobacteriales and Oceanospirillales, Finally, orders with a frequency below 10% in the total of samples are: Aquificales, Caldilineales, Thermales, Mycoplasmatales, Thermoanaerobacteriales, Phycisphaerales, Parvularculales, Rickettsiales, Desulfobacterales, Desulfovibrionales, Desulfuromonadales and Cardiobacteriales. The most abundant orders (number of bacteria per L3 larva) are clearly differentiated from the rest: Actinomycetales (2625), Clostridiales (4450), Rhizobiales (2472) and Sphingomonadales (2692). There are other group of orders whose abundance into the anisakids individuals range between 300 to 800 bacteria per juvenile L3 such as: Lactobacillales, Fusobacteriales, Caulobacterales and Pseudomonadales. The rest of the orders have an average abundance under 300 bacteria per L3 larva.

3.1. Microbial Richness and Diversity of Samples (Anisakids Individuals)

In order to avoid redundancy, the statistical analysis was applied to phylum, order, family and genus levels where taxonomy was well established.
The rarefaction curves per each sample indicate that most of the OTUs in the “sampled community” have not been observed because new OTUs would be found with additional sampling. According to our data, the “asymptotic stage” would be reached in 80% if we would have taken 2500 samples (Figure 1a) (values in Supplementary materials Table S3). In the present study, based only in 113 samples (L3 individuals), we found an average of 123 OTUs per L3 individual (minimum 20 OTUs, maximum 281 OTUs). All of this indicates the extraordinary diversity of bacteria associated to anisakids nematodes and also that this study can be considered representative of that diversity. The diversity ordering by mean of Renyi´s index family curves (Figure 1b) shows independent differences in OTUs diversity comparing all anisakids individuals demonstrating than diversity among them are non-comparable (most of the diversity profiles intersect among them). The use of Shannon and Simpson diversity indices scatter graphically the samples (Supplementary materials Figure S1a,b) indicating again an extraordinary diversity of bacteria at OTUs level. These values range from 0.3 to 4.7 for the Shannon and from 2 to 45 for the Simpson diversity indexes (the inverse option better represents diversity). Both indices clearly detected clusters of samples which are not significantly related with fish hosts or anisakid taxa at the phyla or order levels. This implies that any relationship would exist at a genus or family level without the influence of fish species. The lack of relationships of the microbiome composition with hosts of anisakids taxa has to be expressed by the association among bacterial OTUs or other taxonomical levels which are ranging from OTUs to phylum level.

3.2. Quantitative Analysis (Correlation) Does Not Support Inference of Microbiota Structure

Little correlation was obtained at the OTUs level considering the total number of samples if Pearson or Spearman correlation indices are used (Additional file 3: Figure S2a,b). The average number of sequences per phylum, anisakids and fish hosts are calculated for the most frequent bacteria phyla according to the frequency and are represented in Supplementary materials Figure S3a–c, Table S4. At a bacterial phyla level, Pearson correlation index express better than Spearman some quantitative relationship among anisakids and fish hosts (Supplementary materials Figure S4a,b). Hosts (fish and Anisakids) seems to have some influence in the abundance of each phyla within the microbiome according to the Pearson index. Using this analysis, we found two positive correlations among A. simplex, A. pegreffii, their hybrids and Pseudoterranova sp. when their hosts are SS (Scomber scombrum), MM (Merluccius merluccius), TT (Thunnus thynnus), LoB (Lophius budegassa), GM (Gadus morhua), MP (Micromesistius poutassou) and CC (Conger conger) and another positive correlation between A. simplex and A. pegreffii when the hosts are LP (Lophius piscatorius), MP (Micromesistius poutassou), PB (Phycis blennoides) and LeB (Lepidorhombus boscii). This (the Pearson correlation) could be considered the unique quantitative relationships among bacterial phyla, anisakids and fishes. No other taxonomical level of bacteria below phylum showed any significance. Supplementary materials Table S5 shows the abundance values of the most representatives orders according to anisakids and hosts, while their frequency profiles are represented in Supplementary materials Figure S5a–c. Order composition and their relationships according to anisakids species and fish hosts does not support also the influence of hosts in the microbiota relationships (Supplementary materials Figure S6a,b) above order level, but little further information could be obtained according the data reflect the lower taxonomical level, as is the family and genus level. For this reason we think than an analysis of the microbiome structure, in other words the bacterial clusters that are associated across the different samples, would clarify the factors, which lead the associated microbiome structure to anisakids nematodes.

3.3. Microbiota Structure Associated to Anisakids

Discriminant cluster analysis (Figure 2a–c) of samples based in microbiome composition reflects almost an identical structure of samples through phylum and order levels (Figure 2a,b). At a class level the cluster distribution of the samples is identical to phylum (data at class level not shown); both are practically the same as at order level. The only difference of cluster based in order level with that based on phylum level is that some samples formerly present in a group (G2 or G3) in a phylum cluster are “moving” to other group in order cluster (sample 115 from G2 to G1 and samples 86A, 102A and 105PS from G3 to G1). At the family and genus level, it is almost identical (data at family level is not shown), however the structure of the cluster at family and genus levels (Figure 2c) is very different to the former clusters phylum to order (Figure 2a,b).
Groups of samples are statistically compared by means of discriminant analysis reflecting the differences among them and determining which variables (bacteria) are the most important included in the analysis (Table 5). Actinobacteria (total average = 2,838,283), Aquificae (2,017,699), Firmicutes (total average = 5,659,035) and Proteobacteria (total average = 9,291,938) are the phyla whose abundance determines the sample groups in the clusters. Aquificae, exclusively represented by the genus Hydrogenobacter (total average = 20,176), is absent in G1, with very scarce representation in G3. The statistical values are very significant and also the percentage of classification for each group of samples; total percent of correct classification is 96.46% (Table 5a). When orders are included (Table 5b) the statistical significance as well as the percent of correct classification is also very high (97.34%). Actinobacteria is exclusively represented by the order Actinomicetales (34 genera, including some unclassified), Firmicutes is represented by the orders Bacillales (5 genera including some unclassified) and Clostridiales (51 genera including some unclassified) and Proteobacteria is represented by the orders Campylobacterales (3 genera: Arcobacter, Campylobacter and Sulfurospirillum), Caulobacterales (4 genera: Caulobacter, Brevundimonas, Phenylobacterium and Asticcacaulis). Table 5b also includes the orders Anaerolineales (one unclassified genus) and Caldilineales (genus Caldilinea) from the phylum Cloroflexi and the order Bacteroidales (6 genera) from phylum Bacteroidetes which did not reach the established level of significance (p < 0.05) in Table 5a. At the family and genus levels (Figure 2c) the clusters of samples maintain three different groups (G1, G2 and G3). But the new G1 is mainly formed with samples which were formerly at Order level from G1, five samples of G2 (97, 101s, 101p, 107, 109, 151) and one sample from from G3 (98). The discriminant analysis was not applied at this level due the number of “empty cells” in the data matrix.
Factor analysis allows us to define the number of clusters of bacteria in addition to their association (microbiota association) in spite of the fact that the percentage of representation is low when the number of variables is high as is the case at the genus level. This method combines the bacteria (active variables) explaining the total variability of the factorial space, with the bacteria which explain the variability into each cluster. At the phylum level (Figure 3) the percentage of explanation for the first three factors is 46.62% of the total. The correlations of variables clusters with what are the primary and secondary factors are very high indicating the existence of at least three clusters of phyla: cluster 1(Cyanobacteria and Proteobacteria), cluster 2 (Bacteriodetes, Aquificae, Firmicutes, Fusobacteria and Synergistetes) and Cluster 3 (Verrucomicrobia, Planctomicetes, Chlofoflexi, Deinococcus-Thermus; Acidobacteria, Actinobacteria, Chlamidiae;). The association defined by cluster 1 (Cyanobacteria, Proteobacteria) should be more specific of samples from group 1 (G1); the association defined by cluster 2 (Bacteriodetes, Aquificae, Firmicutes, Fusobacteria and Synergetes) is more related to samples from group 2 (G2) while the other association from cluster 3 is mainly related to Group 1 and 2. Group 3 of samples gather all the associations. The most important phyla to establish the association among them are: Proteobacteria and Cyanobacteria (Cluster 1); Aquificae, Bacterioidetes and Firmicutes (Cluster 2) and Actinobacteria, Chloroflexi, Deinococcus-Thermus and Planctomycetes (Cluster 3).
The total variability at the order level (Figure 4) is explained by 25.75% for the three first factors. One of the reasons could be that it was not possible to classify any order from Cyanobacteria. However, five bacterial clusters can be detected in the hierarchical analysis that involves at least five main factors for ordering the microbiota in the factorial space (36.78% of total explanation). The clustering of associated microbiota detected at phylum level is also detected at order level confirming the relationships. The main influence for conforming the five associated clusters of orders are due to 14 of them: two orders of Bacteroidetes (Flavobacteriales and Bacteroidales), one of Firmicutes (Clostridiales), the only order of Aquificae (Aquificales, due to its central position in the factorial space), one of Planctomycetes (Planctomycetales), six of Proteobacteria (Chromatiales, Neisseriales, Parvularculales, Pasteurellales, Sphingomonadales, Rhodobacterales), one of Actinobacteria (Bifidobacteriales), one of Verrucomicribia (Opitutales) and one of Chloroflexi (Chloroflexales). Regarding the clusters of orders (Figure 4), they can be related with groups of samples (Figure 2b): cluster 1 is mainly associated to samples in group 1, cluster 2 is mainly associated to samples in group 2, clusters 3 and 4 could be associated to any group of samples, and cluster 5 is mainly related to samples of group 3.
Factor analysis and its hierarchical analysis also identified three clusters of bacterial association when it is applied to the genus level (Figure 5). In spite the large number of variables (187 genera), the clusters are quite well defined with very high correlations (values ranging from 0.88 to 0.948) among clusters and variables. Comparison with Figure 2c, Cluster 1 is clearly associated to samples in group 2, cluster 2 with samples of group 1 and 3 and cluster 3 with samples of group 1. In Table 2, Table 3 and Table 4 the genera which conform the three clusters are highlighted by three colors (black, green and red) and those which are of highest influence in the factorial space are marked with an asterisk.

3.4. Genus-Level Associations (Clusters Description): The Ultimate Test Is the Significant Structure which Represents the Microbiota Association at Genus Level

Cluster 1 merges independently 28 genera which are thermophiles or mesophiles, anaerobes (facultative or strict). This cluster is mainly related with the set of samples from G2 (Figure 2c). In this cluster is located Wolbachia, genus of Rickettsiales, which is an endosymbiont of arthropods and nematodes. It is estimated to infect more than 65% of insect species and considered an extensive symbiont in Nematoda [48]. At least 60.71% of the cluster members are considered typical periodontal and oral bacteria of mammals (some of them include species causing gingival or dental disease in humans) such as: Campylobacter, Capnocytophaga, Eubacterium, Fusobacterium, Porphyromonas, Prevotella, Tannerella [49]; Selenomonas, Leptotrichia and Peptococcus [50,51]; Bulleida [52]; Mogibacterium [53]; Catonella, Johnsonella and Dialister [54]; Filifactor [55] and Parvimonas [56,57]. Species of genus Carnobacterium are not known to be pathogenic in humans; C. divergens and C. maltaromaticum may cause disease in fish [58]. Succinivibrio is an obligate anaerobe which was firstly considered inhabitants of the rumen of cattle and sheep [59]. The rest of the bacteria are considered part of the Human gastrointestinal microbiome: Olsonella [60], Slackia [61], Collinsella [62] and Peptococcus [63]. From what can be considered to be members of a generalistic human microbiome, we found: Anaerococcus [64] and other opportunistic human pathogens causing nosocomial infections such as Finegoldia [65], Peptoniphilus [66] and Dolosigranulum with only one known species, D. pigrum [67].
Cluster 2, associated to samples which have defined the Figure 2c, is characterized by 158 genera (unclassified genera has not been included in factorial analysis). Except three genera (Wolbachia, Campylobacter and Succinivibrio) all the recorded genera from phylum Proteobacteria are represented in this Cluster by: classes Alphaproteobacteria (37 genera), Betaproteobacteria (4), Epsiloproteobacteria (2), Deltaproteobacteria (6) and Gammaproteobacteria (10).
Alphabacteria are represented by 7 orders: Rhizobiales (13 genera) some of which are endosymbionts of animals [68] such as Devosia [69], endosymbionts of plants such as Bradyrhizobium, Bosea and Mesorhizobium [70], but most of the Rhizobiales which have been found in this study are common components of soil and water microbiota: Hyphomicrobium used in the denitrification of sewage [71], Methylobacterium [72], Angulomicrobium, Pedomicrobium [73], Rhodobium [74], Chelatococcus [75], Parvibaculum [76], Nordella [77] and Ochrobactrum (also isolated from the intestinal tract in human) has been associated to nosocomial infections in immunocompromised patients by Holmes et al. [78] and Kern et al. [79].
In this cluster 2 there are the four genera of the order Caulobacterales (Asticcacaulis, Brevundimonas, Phenylobacterium and Caulobacter) usually described as freshwater bacteria [80]. The order Parvularculales is represented by the marine genus Parvularcula [81]. Order Rhodobacterales is represented by water eutrophic bacteria Paracoccus and Roseobacter sensu lato clade, with important functions in the marine biogeochemical cycle (25% of coastal marine bacteria are members of the Roseobacter clade [82]). All the genera found in this study from the order Rhodospirillales are members of Cluster 2. They are typical bacteria of aquatic and soil environment-producing acetic acid (Gluconobacter, Roseomonas, Acetobacter, Acidocella, Acidiphilium) or what are considered purple non sulfur bacteria (Skermanella, Azospirillum, Caenispirillum, Magnetospirillum and Defluviicoccus [83]). Although they are considered mainly as environmental bacteria (air, soil and water), some of these species such as Roseomonas are isolated frequently from wounds, abscesses and the genitourinary tract [84]. The Order Rickettsiales is represented by the genus Rickettsia, which is a symbiont of Eukaryota and can induce disease in humans [85]. Sphingomonadales (Sphingomonas, Novosphingobium, Sphingobium, Sphingopyxis and Erythrobacter) are common aerobic bacteria isolated from a wide range of environments, including temperate and polar soils, marine sediments and plant surfaces and tissues [86].
Genera of the class Betaproteobacteria are Janthinobacterium, Alcaligenes, Ralstonia and Neisseria. Some species have clinical importance for humans [such as Neisseria [87], can be agents of nosocomial and opportunistic infections (Alcaligenes [88]), plant pathogens (Ralstonia [89]) or have antifungal properties able to control Batrachochytrium dendrobatidis when the bacteria is a symbiont of amphibians (i.e., Janthinobacterium [90]).
Arcobacter and Sulfurospirillum are the genera of class Epsiloproteobacteria which are in this cluster; Arcobacter comprises some species which can be human and animal pathogens widely distributed in many environment including marine ones [91] while Sulfurospirillum is found in contaminated sediments, wastewater plants, marine environments or on biocathodes [92]. Class Deltaproteobacteria is represented by the following orders and genera: Bdellovibrionales (Peridibacter and Bdellovibrio), Desulfobacterales (Desulfobulbus), Desulfuromonadales (Geobacter) and Myxococcales (Halianqium). All of these genera are quite uniform from an ecological and physiological point of view (sulfur-reducing bacteria). These genera are very common in anaerobic aquatic and marine sediments [93].
Finally, class Gammaproteobacteria (excluding the unclassified genera) is represented by orders Aeromonadales (Aeromonas), Alteromonadales (Shemanella, Psychromonas), Enterobaceriales (Enteric Bacteria cluster), Oceanospirillales (Marinomonas), Pseudomonadalles (Pseudomonas, Psychrobacter, Acinetobacter), Vibrionales (Photobacterium) and Xanthomonadales (Nevskia). Aeromonas is an ubiquitous genus present in continental and marine water, in which most of their species have been associated with human diseases (as opportunistic in immunocompromised patients, gastroenteritis and infected injuries); it is also considered a pathogen in fishes, amphibians and reptiles [94]. Shewanella and Psychromonas are marine genera from cold waters [95,96]. Bacteria from “Enteric_Bacteria_cluster” [97] (order Enterobacteriales) includes medically important genera and species which are part of human and animal microbiota. Its distribution is widespread along any environment. Marinomonas is a marine bacteria [98] with important ecological implication. Order Pseudomonadales is represented by three genera (Psychrobacter, Acinetobacter and Pseudomonas). Psychrobacter is recorded frequently in marine environments [99] but also in terrestrials and some species have been isolated from foods [100]. Acinetobacter is a typical bacteria from soils [101]. Pseudomonas is a well-known genus with at least eight different phylogenetic groups of species [102]; its distribution is ubiquitous and present in all type of ecological niches from terrestrial to marine. Some species are pathogens of animals and plants. Pseudomonas and Acinetobacter are considered pathogens for immunocompromised patients [103]. Vibrionales (Photobacterium) and Xantomonadales (Nevskia) are present in this cluster. Most of the species of Photobacterium are symbionts of marine organisms [104] and it is demonstrated that also some of them are pathogens of fishes [105]. Nevskia is an aquatic bacteria living at the air–water interface (the epineuston) forming hydrophobic surface films [106] and constitutes a clade of sister species into Xantomonadales [107].
The phylum Actinobacteria is represented in this cluster 2 by two Classes and 33 genera (unclassified genera are not included): Rubrobacteria [order Rubrobacterales (1 genus)], Actinobacteria [orders Actinomycetales (29) and Bifidobacteriales (2)] and Coriobacteria [order Coriobacteriales (1)]. Rubrobacterales is represented by the extremophilic genus Rubrobacter considered to be radiotolerant [108]. From Coriobacteriales we have recorded the genus Atopobium [109] a common member of human pathogenic biota [110,111]. The Order Actinomycetales has a complex taxonomy; they can be found mostly in soil and organic matter and also in animals. In addition, they constitute symbiotic nitrogen-fixing associations with more than 200 species of plants; they can serve as biocontrol agents, or be plant pathogens. Genera of this order are also component of the human urogenital tract or the oral digestive system. They also have wide medicinal (antibiotic production; i.e., Streptomyces spp.) and botanical applications [112]. In cluster 2 is represented by the 29 genera recorded in Table 3. It can be considered as the most important genera: Brachybacterium which has been isolated from sea water [113]; Dietzia considered as opportunistic human pathogen [114]; Rothia which causes a wide range of serious infections, especially in immunocompromised hosts [115]; Mycobacterium, a genus free-living in soil and water widely distributed but the major habitat for some species is the diseased tissue of warm-blooded hosts (M. tuberculosis and M. leprae are the most known pathogens of this genus for humans) [116]; some species of Nocardia cause disease in immunocompromised patients [117].
The phylum Bacteroidetes is represented in cluster 2 by orders Flavobacteriales (Flavobacterium, Cloacibacterium, Chryseobacterium, Polaribacter, Wautersiella, Amoebinatus) and Sphingobacteriales (Pedobacter, Sphingobacterium, Hymenobacter, Dyadobacter, Chitinophaga). Flavobacteriales have been isolated in many environments, including soil, marine water, plants, and animal gut. They play an important role in in aquatic and terrestrial environments, accounting for more than 20% of microbial communities. Some flavobacterial species (Flavobacterium spp.) are also responsible for severe fish disease [118,119]. Sphingobacteriales are all considered as “environmental” bacteria with a wide ecological niche, from water to soil [120]. The phylum Cloroflexi is represented by the orders Caldilineales (Caldilinea) and Cloroflexales (Roseiflexus). Both genera are filamentous thermophilic and found in hot springs [121,122]. All members of phylum Cloroflexi are considered to be the origin of photosynthesis [123].
The phylum Firmicutes is represented by the classes Bacilli (14 genera), and Clostridia (22 genera). The genera of Bacilli are members of two orders [orders Bacillales (Listeria, Ammoniphillus, Kurthia, Staphylococcus and Laceyella) and Lactobacillales (Desemzia, Alloiococcus, Streptococcus, Lactococcus, Leuconostoc, Weissella, Lactobacillus, Flacklamia, Aerococcus)]. From Bacillales Listeria, Kurthia and Ammoniphillus can be found in soil, but the former also is found in vegetables and animals where it can be considered a pathogen [124,125,126]. Eleven species of Staphylococcus can be isolated from humans as commensals, some of them pathogenic in persons debilitated by chronic illness, traumatic injury, burns or immunosuppression [127]; Laceyella is considered to be an environment thermophilic bacteria [128]. From Lactobacillales, Desemzia is a lactic acid bacteria (as the rest of the order) common in fish gut considered to be sometimes abundant in the intestine, notably in freshwater fish [129]; Alloiococcus has only one known species with implications as a secondary pathogen in human otitis [130]. The rest of Lactobacillales of this cluster 2 are ubiquitous bacteria, usually found in decomposing plants, milk products and foods in fermentation (including fish) contributing to the healthy microbiota of animals and humans [131].
The genera of Clostridia is represented by two orders [Thermoanaerobacterales (Caldicellulosiruptor and Thermoanaerobacter) and Clostridiales (Helcococcus, Eubacterium, Sedimentibacter, Shuttleworthia, Oribacterium, Moryella, Butyrivibrio-Pseudobutyrivibrio, Fastidiosipila, Ethanoligenens, Acetivibrio, Sporacetigenium, Desulfosporosinus, Veillonella, Mitsuokella Megamonas, Clostridium, Caloramator, Acetobacterium)]. Both species of Thermoanaerobacterales are thermophilic and anaerobic showing adaptation to survive in elevated temperatures (up to 80–90 °C) without oxygen [132]. Regarding Clostridiales, all genera are strict anaerobic bacteria; the ability to form spores makes them highly stable in the environment being natural soil inhabitants as saprophytic bacteria [133]. However, genera of this order have also common presence as members of gut microbiota with clinical and health functions [134].
The rest of the genera from this cluster 2, are members of the phyla Acidobacteria (Chloroacidobacterium, Acidobacterium, Edaphobacter, Koribacter and Solibacter), Aquificae (Hydrogenobacter), Deinococcus-Thermus (Truepera and Deinococcus), Fusobacteria (Psychrilyobacter and Sneathia), Planctomycetes (Singulisphaera, Planctomyces, CL500-3 and Phycisphaera) and Synergistetes (Jonquetella). The genera of Acidobacteria are considered soil inhabitants with a ubiquitous distribution along many ecosystems [135,136]. Aquificae (Hydrogenobacter) encompass a set of bacteria able to live in harsh environments (these bacteria have been found in springs, pools, and oceans) [137,138]. Truepera and Deinococcus from the phylum Deinococcus-Thermus are considered as typical extremophiles bacteria [139,140,141]. From Fusobacteria, Psychrilyobacter was isolated from marine sediment from the Atlantic Ocean [142] and Sneathia appears to be a significant, emerging opportunistic pathogen that may play a significant role in urogenital track for humans (male and female); as a common component of the vaginal microbiota that can affect vaginal and reproductive health [143]. Planctomycetes (Singulisphaera, Planctomyces, CL500-3 and Phycisphaera) are aquatic bacteria (brackish water mass, fresh water and marine) [144,145] but also present in wastewater and terrestrial soils [146]. Genus Jonquetella is considered to be a bacterium of anaerobic environments including soil, oil wells, and wastewater treatment plants and animal gastrointestinal tracts; as other members of Synergistetes they are also associated to human pathology such as cysts, abscesses, and periodontal diseases [147].
Cluster 3, associated with samples from G1 (Figure 2c), is formed by 22 genera from phyla Proteobacteria (Labrys and Cardiobacterium), Deinococcus-Thermus (Meiothermus), Verrucomicrobia (Opitutus), Actinobacteria (Micrococcus, Arthrobacter, Alloscardovia, Adlercreutzia and Eggerthella), Bacteroidetes (Bacteroides, Parabacteroides and Odoribacter) and Firmicutes (Solobacterium, Roseburia, Coprococcus, Blautia, Dorea, Lachnospira, Faecalibacterium, Subdoligranulum, Ruminococcus and Oscillibacter). This cluster groups bacteria mesophiles as aerobic or anaerobic. The genus Labrys (mesophile, 30 °C) contains soil-inhabiting bacteria species (Rhizobiales) including aerobes or facultative anaerobes bacteria [148]. Cardiobacterium is a part of normal human microbiome (especially oropharyngeal zone) (aerobes and enriched CO2 atmosphere) [149]. Meiothermus (thermophilic, 35–68 °C) aerobic and facultative anaerobes genus [150]. Opitutus behaves as an obligate anaerobe in an oxygen-tolerance test growing at temperatures of 10 to 37 °C [151]. The genus Micrococcus (strict aerobe), includes species that are generally mesophile but some may be also cryophiles; although this genus have been isolated from human skin and animals, it is considered to be a normal environmental inhabitant, especially in water, dust, and soil [152]. Arthrobacter is a strict aerobe genus, usually found in soil. Although Alloscardovia, Adlercreutzia and Eggerthella have been isolated from human and animal digestive tracts [61,153,154], could potentially be present in soil and water as the other Actinobacteria. Alloscardovia, shows high aerotolerance while some species of Adlercreutzia and Eggerthella are anaerobic. As Bacteriodites (order Bacteroidiales) Bacteroides, Parabacteroides and Odoribacter are widely distributed in the environment, including sea, soil, water and digestive tract of humans and animals [155]; they are anaerobic genera. Firmicutes of this cluster are represented by orders Erysipelotrycales by means of Solobacterium (anaerobe, family Erysipelotrichaceae) considered to be a common member of the microbiome of human salivary glands [156] and two families of the order Clostridiales (Lachnospiraceae and Ruminococcaceae). In general bacteria of the family Lachnospiraceae are considered to be very abundant in rumens [157] and the human gut microbiota [158]: Roseburia (anaerobe) is associated to the digestive tract (cecum) of mammals [159,160]; Coprococcus, anaerobic, is part of the human faecal microbiota [161]; Blautia from humans, cattle and chickens [162], Dorea isolated in human faeces [163] and Lachnospira found in the rumen of bovine animals [164] and intestine of others such as pigs [165]. Regarding Ruminococcaceae, all members of this family are obligate anaerobes and mesophiles [166]. Faecalibacterium prausnitzii the unique species of the genus is very abundant in the human gut microbiota [167]. Members of Ruminococcus and Subdoligranulum are also found in the human gut and or faeces [168,169] while the genus Oscillibacter, first isolated from the clam Corbicula japonica [170], has been also recorded in the rumen of cattle [171].

4. Discussion

In this study, we report the first detailed composition of the bacterial diversity associated to anisakid nematodes based on the analysis of bacterial rRNA sequences belonging to the microbiome of anisakids present in paratenic hosts from a large geographical area (FAO 27). The association of microbial organisms with metazoa is now recognized to be inter-dependent, and has been a new frontier in zoology [172]. This association has been denominated metaorganism first and holobiont afterwards [173] and has been considered as a “unit of natural selection” [174]. Following these assumptions, [175] the first systematic analysis of the native microbiome of Caenorhabditis elegans, which is mainly characterized by Proteobacteria including the genera Ochrobactrum, Pseudomonas, Stenotrophomonas and Sphingomonas was performed. In that study the native microbiome of wild type naturate C. elegans strains in comparison with the congeneric species C. briggsae and C. remanei was described. However, it is necessary to assume than while any microbiome can present some biological associations with the host, these are not necessarily symbionts. Therefore, the bacterial communities in nematodes can be composed by associated and symbiotic bacteria.
Our results are obtained after an individualized canonical disinfection of the external cuticle of all Anisakids individuals which were used for the experiment. Consequently, the metagenomics analysis reports the symbionts and associated microbial communities. Because the individuals were in the L3 stage, many of the bacterial communities need to be related to the bacteria which are present in the fish host since the time it was parasitized by the anisakid larvae and the time the fish reached the market. This is sufficient time to obtain a realistic panorama about the microbiota composition of anisakids nematodes in the FAO 27 fishing area. Also, it is worth considering the ability of Proteobacteria to colonize the nematode gut in accordance with experiments carried out by [175]; the plant and fungal endosymbiont bacteria family Burkholderiaceae (represented in our study by genus Ralstonia) has been also demonstrated as a symbiont in the plant parasitic nematode Xiphinema americanum [176]. This would confer possible beneficial fitness, increasing the resistance of nematodes against bacterial pathogens [177] and even antifungal activity as is known from [178]. Mutualism among bacteria and nematodes are well known [179]. Recently Oncholaimus dyvae (sp. nov.) was described in the Lucky Strike vent field on the Mid-Atlantic Ridge [180,181] which was previously considered to harbor bacterial symbionts typical of hydrothermal vent fauna, such as sulfur-oxidizing bacteria related to classes Epsilonproteobacteria and Gammaproteobacteria which are frequently found in our study.
No reports are available regarding the microbiota associated to anisakids on such a large geographic area as FAO 27. Despite the scarce number of samples (111) and the asymmetric representation in the survey of anisakids and fish taxa (not equally represented), the diversity present in the total studied populations is rather high; however it only represents part of the possible diversity according the rarefaction curves of the samples (Figure 1a). Logically it is impossible to discover all the OTUs or species of microbial communities, but the observed bacterial OTUs are compared among them by direct comparison of different samples sizes. Rarefaction (Figure 1a), as a significant general method of significant value [182], suggests than the characterization of most of the diversity would reach between 5000 and 10,000 anisakids individuals where each individual can considered as a “microbial population” [183] although our results are statistically representative. Microbiome composition is not substantially affected by the studied fish hosts and their diversity, and in general is non-comparable according to Renyi´s index (Figure 1b). Proteobacteria, Firmicutes and Actinobacteria are the most diverse compared with the other eleven phyla detected in this study. All of this indicates an extraordinary bacterial diversity associated with these nematodes. Neither evenness (Shannon index) nor dominance (inverse of Simpson´s index) [184] show any fish host trend at OTU-level analysis (Additional file 2: Figure S1a,b) but clusters of samples (individuals) are detected, indicating bacterial associations over OTU level and independent of fishes’ influence. This fact, added to the high level of diversity values suggests a “functional redundancy” in the sense of [185] (within an ecosystem, different species contribute in equivalent ways to an equal function) as detected in gut microbiota when carnivores and herbivores are compared [186] providing support for detecting the microbiome structure, and grounding the hypothesis that bacterial communities associated to anisakids are developed independently of what could be a priori considered the major influence variable such as fish host (or even anisakids taxa).
Within the metazoans, the nematodes occupy third place in number of species, after arthropods and mollusks. However, the abundance of their populations is greater that of any other multicellular organism. They are extraordinarily versatile (parasites of marine and terrestrial animals, plants, and human beings), and of great trophic diversity occupying all the niches in all ecosystems on the planet. Therefore, they are a very diverse group from taxonomic, ecological, and geographical points of view [187,188,189]. The bacterivory is a common and unspecific phenomenon in many species of nematodes. Bacterivores are members of at least seven of the 16orders of Nematoda from marine and terrestrial habits (Rhabditida, Chromodorida, Plectida, Monhysterida, Desmoscolecida, Araeolaimida and Enoplida) [190]. Also specific and mutualistic cases include Steinernema carposae and Xenorhabdus nematophila [191] or symbionts as is the case for Wolbachia and filarial nematodes [48]. Finally, pathogenic bacteria have been demonstrated as an evolutionary force for nematodes [16,179].
The water temperature where samples were taken for this study ranges from −2 °C to +18 °C, and therefore cryophiles are represented in the bacterial communities (typically: Aeromonas, Alcaligenes, Alteromonas, Bacillus, Clostridium, Flavobacterium, Lactobacillus, Leuconostoc, Listeria, Pseudomonas, Serratia, Bacillus, Micrococcus, Lactobacillius and Corynebacterium) [192,193]. Regarding fish hosts, except for the internal organs and the muscles, the scales, the skin, the gills and the digestive tract, harbor a high numbers of bacteria [194] which is increased by the intestinal emissions of fish during fishery manipulation [193] and by L3 anisakids larvae which contaminate the fish muscle by means of post migration after death of fish hosts [195,196].
Many of the bacteria genera we have found in this study encompass non-typical marine bacterial that might cause infections in humans through contaminated fish products due to handling during the processing and distribution chains before reaching consumers. According to some authors [197,198] human pathogen bacteria in the marine environment have been demonstrated to be vectored by fish and 69 human pathogenic microorganisms are considered to be the main source of contamination in sea food products [6]. However the real incidence of bacteria related to seafood illnesses might be dependent on gastronomic tradition (high incidence in countries where there is a high consumption of seafood [199]).
Our results suggest a geographical or ecological influence of bacterial communities association in addition to fish contamination after the capture and during the fish processing manipulations until its arrival to the consumer. At least in this study the fish paratenic host seems a secondary variable as determinant of bacterial community.
Methodologically, in addition to the classical cluster analysis, the factorial approach allows significant clusters to be defined in spite of the percentage of representation (related to the number of variables) being low. This implies, but does not explain, a general variability in the whole set of OTUs, genera etc.; that is, there is detected variability in each cluster but that variability is due to a not considered or studied variable. The number of bacterial genera found in this study is at least 187 (excluding spurious and unclassified OTUs at a genus level). The structure of bacterial communities associated with the samples was substantially maintained and clusters’ similarities were generally the same along the taxonomic scale from phyla to families. Statistically it was not possible to test this at the genus level owing to gaps in the samples which corrupt the statistics (due the unclassified OTUs). It seems that bacterial OTUs are a mixture of environmental and fish intestinal microbiota. Firmicutes, Actinobacteria, Bacterioidetes and Proteobacteria were the core of the seafood bacterial community in what is an important study [200]. Comparing our results with those of these authors, we have obtained the same phyla plus Acidobacteria (3%) as the core of associated bacteria to anisakids, but with different representations, that is: in our case Bacteriodites has a scarce representation (5%) while previous authors recorded 40%; Proteobacteria (70% vs. 50%); Actinobacteria (15% vs. 4.5%) Firmicutes (40% vs. 5%). Interestingly Chaillou et al [200] considered than 83% of the associated microbiota in sea food is from water, sediment and soil origin.
Following that, we think that regarding our study, in most of the cases the associations within groups of bacteria could be linked to the ecological or geographical niches in which the fishes were captured or dependent on the time since capture and fishing manipulation.

5. Conclusions

There are significant biological structural associations of microbiota in anisakid nematodes which can only be explained or determined by geographic and human influence. This is manifested in clusters and association of bacteria ranging from plylum to genus level which could be also an indicator of degree of fish contamination or from the geographic zone of fishing. Actinobacteria (Actinomycetales), Aquificae (Aquificales), Firmicutes (Bacillales and Clostridiales), Proteobacteria (Campylobacterales and Caulobacterales) are the phyla whose value of abundance enable us to define such a structure.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/microorganisms9051088/s1, All data generated or analyzed during this study are included in this article and its Additional information files. The 16S rRNA gene sequences have been deposited at GenBank under the accession numbers file SUB8561078: MW335712-MW336932; Table S1. Samples used in the survey (project: Anavas 16S); Table S2. The different taxonomical level (phyla, class, order, family, genus) of associated microbiota to anisakids based in the 16S rRNA sequences for OTUs; Figure S1. Analysis of biota diversity in anisakids; Table S3. Rarefaction values per OTUs used for obtaining the Figure 1; Figure S2. Quantitative analysis: correlations between samples based and bacterial OTUs composition; Figure S3. Distribution of most representative microbiota phyla according anisakids and Fish; Figure S4. Pearson and Sperman Correlation based on the bacteria phylum composition of the four anisakids variant; Figure S5. Distribution of most representative microbiota orders according anisakids and Fish; Figure S6. Pearson and Sperman correlation based on the order composition of the anisakid variants and fishes; Table S4. Average number of sequences per anisakids and fish hosts calculated for the most frequent bacteria phyla; Table S5. Average number of sequences per anisakids and fish hosts calculated for the most frequent bacteria order.

Author Contributions

A.N., J.L.M., S.C.A., L.R., M.G.-M. and M.C., conceived and designed the study. A.N. and J.L.M. coordinated the study. S.C.A., I.S.-A., N.C.-S., L.R., R.R., M.R.G., Y.J.-R., M.C. and M.G.-M. performed the biological and taxonomic experiments. S.C.A., L.R., N.C.-S., M.R.G., I.S.-A. and R.R., performed the 16S rRNA gene experiments. F.L., C.L., S.C.A., Y.J.-R., R.R. and A.N. performed the bioinformatics analyses. A.N., F.L., S.C.A., C.L., L.Z., A.O., J.L.M., analyzed and interpreted the data. A.N. and J.L.M. wrote the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by funds of the Laboratory of Nematology from the Museo Nacional de Ciencias Naturales (from CSIC) and partially by Spanish National project AGL2015-68248-C2-1-R.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Gene sequences have been deposited at GenBank under the accession numbers file SUB8561078: MW335712-MW336932.

Acknowledgments

We thank the members of Computer Department of the Museo Nacional de Ciencias Naturales for their valuable support.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Rohlwing, T.; Palm, H.W.; Rosenthal, H. Parasitation with Pseudoterranova decipiens (Nematoda) influences the survival rate of the European smelt Osmerus eperlanus retained by a screen wall of a nuclear power plant. Dis. Aquat. Organ. 1998, 32, 233–236. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Sakanari, J.A.; McKerrow, J.H. Anisakiasis. Clin. Microbiol. Rev. 1989, 2, 278–284. [Google Scholar] [CrossRef] [PubMed]
  3. Llorens, C.; Arcos, S.C.; Robertson, L.; Ramos, R.; Futami, R.; Soriano, B.; Ciordia, S.; Careche, M.; González-Muñoz, M.; Jiménez-Ruiz, Y.; et al. Functional insights into the infective larval stage of Anisakis simplex s.s., Anisakis pegreffii and their hybrids based on gene expression patterns. BMC Genom. 2018, 19, 592. [Google Scholar] [CrossRef] [Green Version]
  4. Moneo, I.; Caballero, M.L.; Gómez, F.; Ortega, E.; Alonso, M.J. Isolation and characterization of a major allergen from the fish parasite Anisakis simplex. J. Allergy Clin. Immunol. 2000, 106, 177–182. [Google Scholar] [CrossRef]
  5. Baeza, M.L.; Matheu, V.; Rodriguez, A.; De Barrio, M.; Tornero, P.; Rubio, M.; Zubeldia, J.M. Excretory-secretory Anisakis simplex allergens: In vivo and in vitro studies. J. Allergy Clin. Immunol. 2001, 107, S184. [Google Scholar]
  6. Wekell, M.M.; Hungerford, J.M. Microbiological quality of seafoods: Marine toxins. In Seafood: Chemistry, Processing Technology and Quality; Shahidi, F., Botta, J.R., Eds.; Blackie: London, UK, 1994; pp. 220–232. [Google Scholar] [CrossRef]
  7. Van Thiel, P.H.; Kuipers, F.C.; Roskam, R.T. A nematode parasitic to herring causing acute abdominal syndromes in man. Trop. Geogr. Med. 1960, 12, 97–113. [Google Scholar]
  8. Køie, M.; Berland, B.; Burt, M.D.B. Development to third-stage larva occurs in eggs of Anisakis simplex and Pseudoterranova decipiens (Nematoda, Ascaridoidea, Anisakidae). Can. J. Fish Aquat. Sci. 1995, 52, 134–139. [Google Scholar] [CrossRef]
  9. Moneo, I.; Caballero, M.L.; Rodríguez-Pérez, R.; Rodríguez-Mahillo, A.I.; González-Muñoz, M. Sensitization to the fish parasite Anisakis simplex: Clinical and laboratory aspects. Parasitol. Res. 2007, 101, 1051–1055. [Google Scholar] [CrossRef]
  10. Kleter, G.A.; Prandini, A.; Filippi, L.; Marvin, H.J.P. Identification of potentially emerging food safety issues by analysis of reports published by the European Community’s Rapid Alert System for Food and Feed (RASFF) during a four-year period. Food Chem. Toxicol. 2009, 47, 932–950. [Google Scholar] [CrossRef]
  11. Puente, P.; Anadón, A.M.; Rodero, M.; Romaní, F.; Ubeira, F.M.; Cuellar, C. Anisakis simplex: The high prevalence in Madrid (Spain) and its relation with fish consumption. Exp. Parasitol. 2007, 118, 271–274. [Google Scholar] [CrossRef]
  12. Anderson, R.C.; Chabaud, A.G.; Willmott, S. Keys to the Nematodes Parasites of Vertebrates; CABI International: Cambridge, Oxfordshire, UK, 2009; 463p. [Google Scholar]
  13. Mattiucci, S.; Cipriani, P.; Webb, S.C.; Paoletti, M.; Marcer, F.; Bellisario, B.; Gibson, D.I.; Nascetti, G. Genetic and Morphological Approaches Distinguish the Three Sibling Species of the Anisakis simplex Species Complex, with a Species Designation as Anisakis berlandi n. sp. for A. simplex sp. C (Nematoda: Anisakidae). J. Parasitol. 2014, 100, 199–214. [Google Scholar] [CrossRef] [PubMed]
  14. Audicana, M.T.; Ansotegui, I.J.; Fernández de Corres, L.; Kennedy, M.W. Anisakis simplex: Dangerous-dead and alive? Trends Parasitol. 2002, 18, 20–25. [Google Scholar] [CrossRef]
  15. Audicana, M.T.; Kennedy, M.W. Anisakis simplex: From Obscure Infectious Worm to Inducer of Immune Hypersensitivity. Clin. Microbiol. Rev. 2008, 21, 360–379. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Navas, A.; Cobas, G.; Talavera, M.; López, J.A.; Ayala, J.; Martínez, J.L. Experimental validation of Haldane’s hipótesis on the role of infection as an evolutionary force for Metazoans. Proc. Natl. Acad. Sci. USA 2007, 34, 13728–13731. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Cabot, G.; Zamorano, L.; Moyà, B.; Juan, C.; Navas, A.; Blázquez, J.; Oliver, A. Evolution of Pseudomonas aeruginosa antimicrobial resistance and fitness under low and high mutation supply rates. Antimicrob. Agents Chemother. 2016, 60, 1767–1778. [Google Scholar] [CrossRef] [Green Version]
  18. Ruíz Díez, B.; Sánchez, P.; Baquero, F.; Martínez, J.L.; Navas, A. Differential interaction and virulence within the Caenorhabditis elegans-Pseudomonas aeruginosa pathogenesis model. J. Theor. Biol. 2003, 225, 469–476. [Google Scholar] [CrossRef]
  19. Couillaut, C.; Ewbank, J.J. Diverse bacteria pathogens of Caenorhabditis elegans. Infect. Immun. 2002, 70, 4705–4707. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Sifri, C.D.; Mylonakis, E.; Singh, K.V.; Qin, X.; Garsin, D.A.; Murray, B.E.; Ausubel, F.M.; Calderwood, S.B. Virulence effect of Enterococcus faecalis protease genes and the quorum-sensing locus fsr in Caenorhabditis elegans and mice. Infect. Immun. 2002, 70, 56475650. [Google Scholar] [CrossRef] [Green Version]
  21. Garsin, D.A.; Villanueva, J.M.; Begun, J.; Kim, D.H.; Sifri, C.D.; Calderwood, S.B.; Ruvkun, G.; Ausubel, F.M. Long-lived C.elegans daf-2 mutants are resistant to bacterial pathogens. Science 2003, 300, 1921. [Google Scholar] [CrossRef] [Green Version]
  22. Tenor, J.L. Caenorhabdditis elegans based screen identifies Salmonella virulence factors required for conserved host-pathogens interactions. Proc. Natl. Acad. Sci. USA 2004, 96, 2408–2413. [Google Scholar]
  23. Mallo, G.V.; Kurz, C.L.; Couillault, C.; Pujol, N.; Granjeaud, S.; Kohara, Y.; Ewbank, J.J. Inducible antibacterial defense system in C. elegans. Curr. Biol. 2002, 12, 1209–1214. [Google Scholar] [CrossRef] [Green Version]
  24. Bae, T.; Banger, A.K.; Wallace, A.; Glass, E.M.; Aslund, F.; Schneewind, O.; Missiakas, D.M. Staphylococcus aureus virulence genes identified by bursa aurealis mutagenesis and nematode killing. Proc. Natl. Acad. Sci. USA 2004, 101, 12312–12317. [Google Scholar] [CrossRef] [Green Version]
  25. Bolm, M.; Jansen, W.T.M.; Schnabel, R.; Chhatwal, G.S. Hydrogen peroxide-mediated killing of Caenorhabditis elegans: A common feature of different streptoccal species. Infect. Immun. 2004, 72, 1192–1194. [Google Scholar] [CrossRef] [Green Version]
  26. Darby, C.; Hsu, J.W.; Ghori, N.; Falkow, S. Caenorhabditis elegans: Plague bacteria biofilm blocks food intake. Nature 2002, 417, 243–244. [Google Scholar] [CrossRef] [PubMed]
  27. González Quijada, S.; González Escudero, R.; Arias García, L.; Gil Martín, A.R.; Vicente Serrano, J.; Corral Fernández, E. Anisakiasis gastrointestinal manifestations: Description of 42 cases. Rev. Clin. Esp. 2005, 205, 311–315. [Google Scholar] [CrossRef] [PubMed]
  28. Valero, A.; Lopez-Cuello, M.; Benítez, R.; Adroher, F.J. Anisakis spp. in European hake, Merluccius merluccius (L.) from the Atlantic off north-west Africa and the Mediterranean off southern Spain. Acta Parasitol. 2006, 51, 209–212. [Google Scholar] [CrossRef]
  29. Iglesias, L.; Valero, A.; Adroher, F.J. Some factors which influence the in vitro maintenance of Anisakis simplex (Nematoda). Folia Parasitol. 1997, 44, 297–301. [Google Scholar]
  30. Zhu, X.Q.; Podolska, M.; Liu, J.S.; Yu, H.Q.; Chen, H.H.; Lin, Z.X.; Luo, C.B.; Song, H.Q.; Lin, R.Q. Identification of anisakid nematodes with zoonotic potential from Europe and China by single-strand conformation polymorphism analysis of nuclear ribosomal DNA. Parasitol. Res. 2007, 101, 1703–1707. [Google Scholar] [CrossRef] [PubMed]
  31. Abollo, E.; Paggi, L.; Pascual, S.; D’Amelio, S. Occurrence of recombinant genotypes of Anisakis simplex s. s. and Anisakis pegreffii (Nematoda, Anisakidae) in an area of sympatry. Infect. Genet. Evol. 2003, 3, 175–181. [Google Scholar] [CrossRef]
  32. D’Amelio, S.; Mathiopoulos, K.D.; Santos, C.P.; Pugachev, O.N.; Webb, S.C.; Picanco, M.; Paggi, L. Genetic markers in ribosomal DNA for the identification of members of the genus Anisakis (Nematoda: Ascaridoidea) defined by polymerase-chain-reaction-based restriction fragment length polymorphism. Int. J. Parasitol. 2000, 30, 223–226. [Google Scholar] [CrossRef]
  33. Caporaso, J.G.; Lauber, C.L.; Walters, W.A.; Berg-Lyons, D.; Lozupone, C.A.; Turnbaugh, P.J.; Fierer, N.; Knight, R. Global patterns of 16S rRNA rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108, 4516–4522. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Schloss, P.D.; Westcott, S.L.; Ryabin, T.; Hall, J.R.; Hartmann, M.; Hollister, E.B.; Lesniewski, R.A.; Oakley, B.B.; Parks, D.H.; Robinson, C.J.; et al. Introducing Mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. App. Environ. Microbiol. 2009, 75, 7537–7541. [Google Scholar] [CrossRef] [Green Version]
  35. Andrews, S. FastQC a Quality Control Tool for High Throughput Sequence Data [Online]. 2010. Available online: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (accessed on 8 January 2017).
  36. Schmieder, R.; Edwards, R. Quality control and preprocessing of metagenomic datasets. Bioinformatics 2011, 27, 863–864. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Kozich, J.J.; Westcott, S.L.; Baxter, N.T.; Highlander, S.K.; Schlossa, P.D. Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform. App. Environ. Microbiol. 2013, 79, 5112–5120. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Narciso-da-Rocha, C.; Rocha, J.; Vaz-Moreira, I.; Lira, F.; Tamames, J.; Henriques, I.; Martinez, J.L.; Manaia, C.M. Bacterial lineages putatively associated with the dissemination of antibiotic resistance genes in a full-scale urban wastewater treatment plant. Environ. Int. 2018, 118, 179–188. [Google Scholar] [CrossRef]
  39. Schloss, P.D. Secondary structure improves OTU assignments of 16S rRNA rRNA gene sequences. ISME J. 2013, 7, 457–460. [Google Scholar] [CrossRef]
  40. Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B.M.; Ludwig, W.G.; Peplies, J.; Glöckner, F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucl. Acids Res. 2007, 35, 7188–7196. [Google Scholar] [CrossRef] [Green Version]
  41. Pruesse, E.; Joerg, P.; Gloeckner, F.O. SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 2012, 28, 1823–1829. [Google Scholar] [CrossRef]
  42. Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, 2460–2461. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Edgar, R.C.; Haas, B.J.; Clemente, J.C.; Quince, C.; Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011, 27, 2194–2200. [Google Scholar] [CrossRef] [Green Version]
  44. Quast, C.; Pruesse, E.; Yilmaz, P.; Gerken, J.; Schweer, T.; Yarza, P.; Peplies, J.; Glöckner, F.O. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013, 41, D590–D596. [Google Scholar] [CrossRef] [PubMed]
  45. Henderson, P.A. Practical Methods in Ecology; Blackwell Publishing Company: Oxford, UK, 2006. [Google Scholar]
  46. Hammer, Ø.; Harper, D.A.T.; Ryan, P.D. PAlaeontological STatistics, ver.1.9 Users Manual. 2009. Available online: http://folk.uio.no/ohammer/past/past.pdf (accessed on 4 April 2020).
  47. StatSoft, Inc. STATISTICA (Data Analysis Software System), Version 6. 2001. Available online: https://www.statsoft.com (accessed on 19 July 2019).
  48. Werren, J.H.; Baldo, L.; Clark, M.E. Wolbachia: Master manipulators of invertebrate biology. Nat. Rev. Microbiol. 2008, 6, 741–751. [Google Scholar] [CrossRef] [PubMed]
  49. Picolos, D.K.; Lerche-Sehm, J.; Abron, A.; Fine James, B.; Papapanou, P.N. Infection patterns in chronic and aggressive periodontitis. J. Clin. Periodontol. 2005, 32, 1055–1061. [Google Scholar] [CrossRef]
  50. Goodson, J.M.; Groppo, D.; Halem, S.; Carpino, E. Is Obesity an Oral Bacterial Disease? J. Dent. Res. 2009, 88, 519–523. [Google Scholar] [CrossRef] [PubMed]
  51. Thompson, J.; Pikis, A. Metabolism of sugars by genetically diverse species of oral Leptotrichia. Mol. Oral Microbiol. 2012, 27, 34–44. [Google Scholar] [CrossRef]
  52. Downes, J.; Olsvik, B.; Hiom, S.J.; Spratt, D.A.; Cheeseman, S.L.; Olsen, I.; Weightman, A.J.; Wade, W.G. Bulleidia extructa gen. nov., sp. nov., isolated from the oral cavity. Int. J. Syst. Evol. Microbiol. 2000, 50, 979–983. [Google Scholar] [CrossRef] [Green Version]
  53. Nakazawa, F.; Sato, M.; Poco, S.E.; Hashimura, T.; Ikeda, T.; Kalfas, S.; Sundqvist, G.; Hoshino, E. Description of Mogibacterium pumilum gen. nov., sp. nov. and Mogibacterium vescum gen. nov., sp. nov., and reclassification of Eubacterium timidum (Holdeman et al., 1980) as Mogibacterium timidum gen. nov., comb. nov. Int. J. Syst. Evol. Microbiol. 2000, 50, 679–688. [Google Scholar] [CrossRef] [Green Version]
  54. Moore, L.V.; Moore, W.E.C. Oribaculum catoniae gen. nov., sp. nov.; Catonella morbi gen. nov., sp. nov.; Hallella seregens gen. nov., sp. nov.; Johnsonella ignava gen. nov., sp. nov.; and Dialister pneumosintes gen. nov., comb. nov., nom. rev., Anaerobic Gram-Negative Bacilli from the Human Gingival Crevice. Int. J. Syst. Bacteriol. 1994, 44, 187–192. [Google Scholar] [CrossRef] [Green Version]
  55. Collins, M.D.; Lawson, P.A.; Willems, A.; Cordoba, J. J.; Fernandez-Garayzabal, J.; Garcia, P.; Cai, J.; Hippe, H.; Farrow, J.A.E. The Phylogeny of the Genus Clostridium: Proposal of Five New Genera and Eleven New Species Combinations. Int. J. Syst. Bacteriol. 1994, 44, 812–826. [Google Scholar] [CrossRef] [Green Version]
  56. Tindall, B.J.; Euzéby, J.P. Proposal of Parvimonas gen. nov. and Quatrionicoccus gen. nov. as replacements for the illegitimate, prokaryotic, generic names Micromonas Murdoch and Shah 2000 and Quadricoccus Maszenan et al., 2002, respectively. Int. J. Syst. Evol. Microbiol. 2006, 56, 2711–2713. [Google Scholar] [CrossRef] [Green Version]
  57. Kumar, P.S. Smoking and the subgingival ecosystem: A pathogen-enriched community. Future Microbiol. 2012, 7, 917–919. [Google Scholar] [CrossRef]
  58. Leisner, J.J.; Laursen, B.G.; Prévost, H.; Drider, D.; Dalgaard, P. Carnobacterium: Positive and negative effects in the environment and in foods. FEMS Microbiol. Rev. 2007, 31, 592–613. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Hespell, R.B. The Genera Succinivibrio and Succinimonas. In The Prokaryotes; Balows, A., Trüper, H.G., Dworkin, M., Harder, W., Schleifer, K.H., Eds.; Springer: New York, NY, USA, 1992. [Google Scholar]
  60. Ricaboni, D.; Mailhe, M.; Vitton, V.; Bittar, F.; Raoult, D.; Fournier, P.E. Olsenella provencensis sp. nov., Olsenella phocaeensis sp. nov., and Olsenella mediterranea sp. nov. isolated from the human colon. Hum. Microbiome J. 2017, 4, 22–23. [Google Scholar] [CrossRef]
  61. Wade, W.G.; Downes, J.; Dymock, D.; Hiom, S.J.; Weightman, A.J.; Dewhirst, F.E.; Paster, B.J.; Tzellas, N.; Coleman, B. The family Coriobacteriaceae: Reclassification of Eubacterium exiguum (Poco et al., 1996) and Peptostreptococcus heliotrinreducens (Lanigan 1976) as Slackia exigua gen. nov., comb. nov. and Slackia heliotrinireducens gen. nov., comb. nov., and Eubacterium lentum (Prevot 1938) as Eggerthella lenta gen. nov., comb. nov. Int. J. Syst. Bacteriol. 1999, 49, 595–600. [Google Scholar] [CrossRef] [PubMed]
  62. Kageyama, A.; Benno, Y.; Nakase, T. Phylogenetic and phenotypic evidence for the transfer of Eubacterium aerofaciens to the genus Collinsella as Collinsella aerofaciens gen. nov., comb. nov. Int. J. Syst. Bacteriol. 1999, 49, 557–565. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Shkoporov, A.N.; Efimov, B.A.; Kondova, I.; Ouwerling, B.; Chaplin, A.V.; Shcherbakova, V.A.; Langermans, J.A.M. Peptococcus simiae sp. nov., isolated from Rhesus macaque faeces and emended description of the genus Peptococcus. Int. J. Syst. Evol. Microbiol. 2016, 66, 5187–5191. [Google Scholar] [CrossRef] [PubMed]
  64. Ezaki, T.; Kawamura, Y.; Li, N.; Li, Z.Y.; Zhao, L.; Shu, S. Proposal of the genera Anaerococcus gen. nov., Peptoniphilus gen. nov. and Gallicola gen. nov. for members of the genus Peptostreptococcus. Int. J. Syst. Evol. Microbiol. 2001, 51, 1521–1528. [Google Scholar] [CrossRef] [Green Version]
  65. De Moreuil, C.; Héry-Arnaud, G.; David, C.H.; Provost, B.; Mondine, P.; Alavi, Z.; de Saint Martin, L.; Bezon, E.; Berre, R.L. Finegoldia magna, not a well-known infectious agent of bacteriemic post-sternotomy mediastinitis. Anaerobe 2015, 32, 32–33. [Google Scholar] [CrossRef]
  66. Brown, K.; Church, D.; Lynch, T.; Gregson, D. Bloodstream infections due to Peptoniphilus spp.: Report of 15 cases. Clin. Microbiol. Infec. 2014, 20, O857–O860. [Google Scholar] [CrossRef] [Green Version]
  67. Lecuyer, H.; Audibert, J.; Bobigny, A.; Eckert, C.; Janniere-Nartey, C.; Buu-Hoi, A.; Mainardi, J.L.; Podglajen, I. Dolosigranulum pigrum Causing Nosocomial Pneumonia and Septicemia. J. Clin. Microbiol. 2007, 45, 3474–3475. [Google Scholar] [CrossRef] [Green Version]
  68. Neuvonen, M.M.; Tamarit, D.; Näslund, K.; Liebig, J.; Feldhaar, H.; Moran, N.A.; Guy, L.; Andersson, S.G.E. The genome of Rhizobiales bacteria in predatory ants reveals urease gene functions but no genes for nitrogen fixation. Sci. Rep. 2016, 6, 39197. [Google Scholar] [CrossRef]
  69. Vannini, C.; Rosati, G.; Verni, F.; Petroni, G. Identification of the bacterial endosymbiontsof the marine ciliate Euplotes magnicirratus (Ciliophora, Hypotrichia) and proposal of Candidatus Devosia euplotis. Int. J. Syst. Evol. Microbiol. 2004, 54, 1151–1156. [Google Scholar] [CrossRef] [Green Version]
  70. Erlacher, A.; Cernava, T.; Cardinale, M.; Soh, J.; Sensen, C.W.; Grube, M.; Berg, G. Rhizobiales as functional and endosymbiontic members in the lichen symbiosis of Lobaria pulmonaria L. Front. Microbiol. 2015, 6, 53. [Google Scholar] [CrossRef]
  71. Rainey, F.A.; Ward-Rainey, N.; Gliesche, C.G.; Stackebrandtl, E. Phylogenetic analysis and intrageneric structure of the genus Hyphornicrobium and the related genus Filornicrobium. Int. J. Syst. Bacteriol. 1998, 48, 635–639. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Gallego, V.; Garcia, M.T.; Ventosa, A. Methylobacterium adhaesivum sp. nov., a methylotrophic bacterium isolated from drinking water. Int. J. Syst. Evol. Microbiol. 2006, 56, 339–342. [Google Scholar] [CrossRef] [PubMed]
  73. Garrity, G.M.; Winters, M.; Searles, D.B. Taxonomic Outline of the Procaryotic Genera Bergey’s Manual of Systematic Bacteriology, 2nd ed.; Release 1.0; Springer: New York, NY, USA, 2001; pp. 1–39. [Google Scholar]
  74. Hiraishi, A.; Urata, K.; Satoh, T. A new genus of marine budding phototrophic bacteria, Rhodobium gen. nov., which includes Rhodobium orientis sp. nov. and Rhodobium marinum comb. nov. Int. J. Syst. Evol. Microbiol. 1995, 45, 226–234. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Yoon, J.H.; Kang, S.J.; Im, W.T.; Lee, S.T.; Oh, T.K. Chelatococcus daeguensis sp. nov., isolated from wastewater of a textile dye works, and emended description of the genus Chelatococcus. Int. J. Syst. Evol. Microbiol. 2008, 58, 2224–2228. [Google Scholar] [CrossRef] [Green Version]
  76. Schleheck, D.; Tindall, B.J.; Rosselló-Mora, R.; Cook, A.M. Parvibaculum lavamentivorans gen. nov., sp. nov., a novel heterotroph that initiates catabolism of linear alkylbenzenesulfonate. Int. J. Syst. Evol. Microbiol. 2004, 54, 1489–1497. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. La Scola, B.; Barrassi, L.; Raoult, D. A novel alpha-Proteobacterium, Nordella oligomobilis gen. nov., sp. nov., isolated by using amoebal co-cultures. Res. Microbiol. 2004, 155, 47–51. [Google Scholar] [CrossRef]
  78. Holmes, B.; Popoff, M.; Kiredjian, M.; Kersters, K. Ochrobactrum anthropi gen. nov., sp. nov. from human clinical specimens and previously known as Group Vd. Int. J. Syst. Bacteriol. 1988, 38, 408. [Google Scholar] [CrossRef]
  79. Kern, W.V.; Oethinger, M.; Kaufhold, A.; Rozdizinski, E.; Marre, R. Ochobactrum anthropi bacteremia: Report of four cases and short review. Infection 1993, 21, 306–310. [Google Scholar] [CrossRef]
  80. Abraham, W.R.; Macedo, A.J.; Lünsdorf, H.; Fischer, R.; Pawelczyk, S.; Smith, J.; Vancanneyt, M. Phylogeny by a polyphasic approach of the order Caulobacterales, proposal of Caulobacter mirabilis sp. nov., Phenylobacterium haematophilum sp. nov. and Phenylobacterium conjunctum sp. nov., and emendation of the genus Phenylobacterium. Int. J. Syst. Evol. Microbiol. 2008, 58, 1939–1949. [Google Scholar] [CrossRef] [PubMed]
  81. Cho, J.C.; Giovannoni, S.J. Parvularcula bermudensis gen. nov., sp. nov., a marine bacterium that forms a deep branch in the α-Proteobacteria. Int. J. Syst. Evol. Bacteriol. 2003, 53, 1031–1036. [Google Scholar] [CrossRef] [PubMed]
  82. Buchan, A.; González, J.M.; Moran, M.A. Overview of the marine roseobacter lineage. Appl. Environ. Microb. 2005, 71, 5665–5677. [Google Scholar] [CrossRef] [Green Version]
  83. Bryant, D.A.; Frigaard, N.U. Prokaryotic photosynthesis and phototrophy illuminated. Trends Microbiol. 2006, 14, 488–496. [Google Scholar] [CrossRef]
  84. Dé, I.; Rolston, K.V.; Han, X.Y. Clinical significance of Roseomonas species isolated from catheter and blood samples: Analysis of 36 cases in patients with cancer. Clin. Infect. Dis. 2004, 38, 1579–1584. [Google Scholar] [CrossRef] [PubMed]
  85. Walker, D.H. Rickettsiae. In Barron’s Medical Microbiology, 4th ed.; Barron, S., Ed.; University of Texas Medical Branch: Galveston, TX, USA, 1996. [Google Scholar]
  86. Kertesz, M.A.; Kawasaki, A.; Stolz, A. Aerobic Hydrocarbon-Degrading Alphaproteobacteria: Sphingomonadales. In Taxonomy, Genomics and Ecophysiology of Hydrocarbon-Degrading Microbes. Handbook of Hydrocarbon and Lipid Microbiology; McGenity, T., Ed.; Springer: Cham, Switzerland, 2019. [Google Scholar] [CrossRef]
  87. Knapp, J.S. Historical perspectives and identification of Neisseria and related species. Clin. Microbiol. Rev. 1988, 1, 415–431. [Google Scholar] [CrossRef]
  88. Kavuncuoglu, F.; Unal, A.; Oguzhan, N.; Tokgoz, B.; Oymak, O.; Utas, C. First Reported Case of Alcaligenes faecalis Peritonitis. J. Int. Soc. Periton. Dial. 2010, 30, 118–119. [Google Scholar] [CrossRef]
  89. Saddler, G.S. Management of bacterial wilt disease. In Bacterial wilt Disease and the Ralstonia Solanacearum Species Complex; Allen, C., Prior, P., Hayward, A.C., Paul, M.N., Eds.; APS Press: St Paul, MN, USA, 2005; pp. 121–132. [Google Scholar]
  90. Brucker, R.M.; Harris, R.N.; Schwantes, C.R.; Gallaher, T.N.; Flaherty, D.C.; Lam, B.A.; Minbiole, K.P.C. Amphibian chemical defense: Antifungal metabolites of the microsymbiont Janthinobacterium lividum on the salamander Plethodon cinereus. J. Chem. Ecol. 2008, 34, 1422–1429. [Google Scholar] [CrossRef]
  91. Fera, M.T.; Maugeri, T.L.; Gugliandolo, C.; Beninati, C.; Giannone, M.; La Camera, E.; Carbone, M. Detection of Arcobacter spp. in the Coastal Environment of the Mediterranean Sea. App. Environ. Microbiol. 2004, 70, 1271–1276. [Google Scholar] [CrossRef] [Green Version]
  92. Kruse, S.; Goris, T.; Westermann, M.; Adrian, L.; Dieker, G. Hydrogen production by Sulfurospirillum species enables syntrophic interactions of Epsilonproteobacteria. Nat. Commun. 2018, 9, 4872. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Dworkin, M. (Editor-in-Chief); The Prokaryotes. A Handbook on the Biology of Bacteria Third EditionVolume 7: Proteobacteria: Delta and Epsilon Subclasses. Deeply Rooting Bacteria; Falkow, S., Rosenberg, E., Schleifer, K.H., Stackebrandt, E., Eds.; Springer: New York, NY, USA, 2006; pp. 5–191. [Google Scholar]
  94. Tena, D.; González-Praetorius, A.; Gimeno, C.; Pérez-Pomata, M.T.; Bisquer, J. Infección extraintestinal por Aeromonas spp.: Revisión de 38 casos. Enferm. Infecc. Microbiol. Clin. 2007, 25, 235–241. [Google Scholar] [CrossRef]
  95. Ivanova, E.P.; Flavier, S.; Christen, R. Phylogenetic relationships among marine Alteromonas-like proteobacteria: Emended description of the family Alteromonadaceae and proposal of Pseudoalteromonadaceae fam. nov., Colwelliaceae fam. nov., Shewanellaceae fam. nov., Moritellaceae fam. nov., Ferrimonadaceae fam. nov., Idiomarinaceae fam. nov. and Psychromonadaceae fam. nov. Int. J. Syst. Evol. Microbiol. 2004, 54, 1773–1788. [Google Scholar] [PubMed] [Green Version]
  96. Mountfort, D.O.; Rainey, F.A.; Burghardt, J.; Kaspar, H.F.; Stackebrandt, E. Psychromonas antarctica gen. nov., sp. nov., a new aerotolerant anaerobic, halophilic psychrophile isolated from pond sediment of the McMurdo Ice Shelf, Antarctica. Arch. Microbiol. 1998, 169, 231–238. [Google Scholar] [CrossRef] [PubMed]
  97. Wertz, J.E.; Goldstone, C.; Gordon, D.M.; Riley, M.A. A molecular phylogeny of enteric bacteria and implications for a bacterial species concept. J. Evol. Biol. 2003, 16, 1236–1248. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Espinosa, E.; Marco-Noales, E.; Gómez, D.; Lucas-Elío, P.; Ordax, M.; Garcias-Bonet, N.; Duarte, C.M.; Sanchez-Amat, A. Taxonomic study of Marinomonas strains isolated from the seagrass Posidonia oceanica, with descriptions of Marinomonas balearica sp. nov. and Marinomonas pollencensis sp. nov. Int. J. Syst. Evol. Microbiol. 2010, 60, 93–98. [Google Scholar] [CrossRef] [PubMed]
  99. Romanenko, L.A. Psychrobacter submarinus sp. nov. and Psychrobacter marincola sp. nov., psychrophilic halophiles from marine environments. Int. J. Syst. Evol. Microbiol. 2002, 52, 1291–1297. [Google Scholar] [PubMed] [Green Version]
  100. Páèová, Z.; Urbanová, E.; Durnová, E. Psychrobacter immobilis isolated from foods: Characteristics and identification. Vet. Med. 2001, 46, 95–100. [Google Scholar] [CrossRef] [Green Version]
  101. Dijkshoorn, L. The Diversity of the Genus Acinetobacter. In Acinetobacter Molecular Biology; Gerischer, U., Ed.; Caister Academic Press: Poole, UK, 2008. [Google Scholar]
  102. Anzai, Y.; Kim, H.; Park, J.Y.; Wakabayashi, H. Phylogenetic affiliation of the pseudomonads based on 16S rRNA rRNA sequence. Int. J. Syst. Evol. Microbiol. 2000, 50, 1563–1589. [Google Scholar] [CrossRef] [Green Version]
  103. Rahal, J. Novel antibiotic combinations against infections with almost completely resistant Pseudomonas aeruginosa and Acinetobacter species. Clin. Infect. Dis. 2006, 43 (Suppl. 2), S95–S99. [Google Scholar] [CrossRef] [Green Version]
  104. Madigan, M.; Martinko, J.; Brock, T.; Dunlap, P.C. Brock Biology of Microorganisms, 12nd ed.; Benjamin Cummings: San Francisco, CA, USA, 2009. [Google Scholar]
  105. Austin, B.; Austin, D. A. Bacterial Fish Pathogens: Disease of Farmed and Wild Fish, 6th ed.; eBook; Springer: Berlin/Heidelberg, Germany, 2016; 732p. [Google Scholar]
  106. Stürmeyer, H.; Overmann, J.; Babenzien, H.D.; Cypionka, H. Ecophysiological and Phylogenetic Studies of Nevskia ramosa in Pure Culture. Appl. Environ. Microbiol. 1998, 64, 1890–1894. [Google Scholar] [CrossRef] [Green Version]
  107. Naushad, S.; Adeolu, M.; Wong, S.; Sohail, M.; Schellhorn, H.E.; Gupta, R.S. A phylogenomic and molecular marker based taxonomic framework for the order Xanthomonadales: Proposal to transfer the families Algiphilaceae and Solimonadaceae to the order Nevskiales ord. nov. and to create a new family within the order Xanthomonadales, the family Rhodanobacteraceae fam. nov., containing the genus Rhodanobacter and its closest relatives. Antonie Leeuwenhoek 2015, 107, 467–485. [Google Scholar] [PubMed]
  108. Suzuki, K.; Collins, M.D.; Iijima, E.; Komagata, K. Chemotaxonomic characterization of a radiotolerant bacterium Arthrobacter radiotolerans: Description of Rubrobacter radiotolerans gen. nov., comb. nov. FEMS Microbiol. Lett. 1988, 52, 33–40. [Google Scholar] [CrossRef] [Green Version]
  109. Collins, M.D.; Wallbanks, S. Comparative sequence analyses of the 16S rRNA rRNA genes of Lactobacillus minutus, Lactobacillus rimae and Streptococcus parvulus: Proposal for the creation of a new genus Atopobium. FEMS Microbiol. Lett. 1992, 95, 235–240. [Google Scholar] [CrossRef]
  110. Rodriguez Jovita, M.; Collins, M.D.; Sjödén, B.; Falsen, E. Characterization of a novel Atopobium isolate from the human vagina: Description of Atopobium vaginae sp. nov. Int. J. Syst. Bacteriol. 1999, 49, 1573–1576. [Google Scholar] [CrossRef] [Green Version]
  111. Cools, P.; Oyaert, M.; Vaneechoutte, M.; De Laere, E.; Vervaeke, S. Atopobium deltae sp. nov., isolated from the blood of a patient with Fournier’s gangrene. Int. J. Syst. Evol. Microbiol. 2014, 64, 3140–3145. [Google Scholar] [CrossRef]
  112. Waksman, S.A.; Schatz, A.; Reynolds, D.M. Production of antibiotic substances by Actinomycetes. Ann. N. Y. Acad. Sci. 2010, 1213, 112–124. [Google Scholar] [CrossRef]
  113. Kaur, G.; Kumar, N.; Mual, P.; Kumar, A.; Kumar, R.M.; Mayilraj, S. Brachybacterium aquaticum sp. nov., a novel actinobacterium isolated from seawater. Int. J. Syst. Evol. Microbiol. 2016, 66, 4705–4710. [Google Scholar] [CrossRef]
  114. Koerner, R.J.; Goodfellow, M.; Jones, A.L. The genus Dietzia: A new home for some known and emerging opportunist pathogens. FEMS Immunol. Med. Microbiol. 2009, 55, 296–305. [Google Scholar] [CrossRef] [Green Version]
  115. Ramanan, P.; Barreto, J.N.; Osmon, D.R.; Tosh, P.K. Rothia Bacteremia: A 10-Year Experience at Mayo Clinic, Rochester, Minnesota. J. Clin. Microbiol. 2014, 52, 3184–3189. [Google Scholar] [CrossRef] [Green Version]
  116. Murray, P.R.; Rosenthal, K.S.; Pfaller, M.A. Capítulo 28: Mycobacterium. In Microbiología Médica, 6th ed.; Murray, P.R., Ed.; Elsevier-Mosby: Madrid, España, 2009; pp. 277–290. [Google Scholar]
  117. Ryan, K.J.; Ray, C.G. (Eds.) Sherris Medical Microbiology, 4th ed.; McGraw Hill: Madrid, Spain, 2004; Volume xiii, 979p. [Google Scholar]
  118. Yang, J.A.; Kwon, K.K.; Oh, H.M. Complete Genome Sequence of Flavobacteriales Bacterium Strain UJ101 Isolated from a Xanthid Crab. Genome Announc. 2017, 5, e01551-16. [Google Scholar] [CrossRef] [Green Version]
  119. Noga, E.J. Fish Disease: Diagnosis and Treatment, 2nd ed.; Wiley-Blackwell: Ames, IA, USA, 2010; pp. 13–48. [Google Scholar]
  120. Krieg, N.R.; Staley, J.T.; Brown, D.R.; Hedlund, B.P.; Paster, B.J.; Ward, N.L.; Brown, D.; Parte, A. (Eds.) Bergey’s Manual of Systematic Bacteriology, 2nd ed.; The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes; Springer: New York, NY, USA, 2010. [Google Scholar]
  121. Grégoire, P.; Bohli, M.; Cayol, J.L.; Joseph, M.; Guasco, S.; Dubourg, K.; Cambar, J.; Michotey, V.; Bonin, P.; Fardeau, M.L.; et al. Caldilinea tarbellica sp. nov., a filamentous, thermophilic, anaerobic bacterium isolated from a deep hot aquifer in the Aquitaine Basin. Int. J. Syst. Evol. Microbiol. 2011, 61, 1436–1441. [Google Scholar] [CrossRef]
  122. Hanada, S.; Takaichi, S.; Matsuura, K.; Nakamura, K. Roseiflexus castenholzii gen. nov., sp. nov., a thermophilic, filamentous, photosynthetic bacterium that lacks chlorosomes. Int. J. Syst. Evol. Microbiol. 2002, 52, 187–193. [Google Scholar] [CrossRef] [PubMed]
  123. Cavalier-Smith, T. Rooting the tree of life by transition analyses. Biol. Direct. 2006, 1, 19. [Google Scholar] [CrossRef] [Green Version]
  124. Edelson, B.T.; Unanue, E.R. Immunity to Listeria infection. Curr. Opin. Imunol. 2000, 12, 425–431. [Google Scholar] [CrossRef]
  125. Zaitsev, G.M.; Tsitko, I.V.; Rainey, F.A.; Trotsenko, Y.A.; Uotila, J.S.; Stackebrandt, E.; Salkinoja-Salonen, M.S. New aerobic ammonium-dependent obligately oxalotrophic bacteria: Description of Ammoniphilus oxalaticus gen. nov., sp. nov. and Ammoniphilus oxalivorans gen. nov., sp. nov. Int. J. Syst. Bacteriol. 1998, 48, 151–163. [Google Scholar] [CrossRef] [PubMed]
  126. Mei, Y. Screening and distributing features of bacteria with hydantoinase and carbamoylase. Microbiol. Res. 2009, 3, 322–329. [Google Scholar] [CrossRef]
  127. Foster, T. Staphylococcus. In Medical Microbiology, 4th ed.; Baron, S., Ed.; University of Texas Medical Branch at Galveston: Galveston, TX, USA, 1996; Chapter 12. Available online: https://www.ncbi.nlm.nih.gov/books/NBK8448 (accessed on 24 September 2019).
  128. Yoon, J.H.; Kim, I.G.; Shin, Y.K.; Park, Y.H. Proposal of the genus Thermoactinomyces sensu stricto and three new genera, Laceyella, Thermoflavimicrobium and Seinonella, on the basis of phenotypic, phylogenetic and chemotaxonomic analyses. Int. J. Syst. Evol. Microbiol. 2005, 55, 395–400. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  129. Gatesoupe, F.J. Updating the importance of lactic acid bacteria in fish farming: Natural occurrence and probiotic treatments. J. Mol. Microb. Biotech. 2008, 14, 107–114. [Google Scholar] [CrossRef] [Green Version]
  130. Harimaya, A.; Takada, R.; Hendolin, P.H.; Fujii, N.; Ylikoski, J.; Himi, T. High Incidence of Alloiococcus otitidis in Children with Otitis Media, Despite Treatment with Antibiotics. J. Clin. Microbiol. 2006, 44, 946–949. [Google Scholar] [CrossRef] [Green Version]
  131. Lorenzo, J.M.; Munekata, P.E.; Dominguez, R.; Pateiro, M.; Saraiva, J.A.; Franco, D. Main Groups of Microorganisms of Relevance for Food Safety and Stability: General Aspects and Overall Description. In Innovative Technologies for Food Preservation. Inactivation of Spoilage and Pathogenic Microorganisms; Barba, F.J., Sant’Ana, A.S., Orlien, V., Koubaa, M., Eds.; Academic Press: Cambridge, MA, USA, 2018; pp. 53–107. [Google Scholar]
  132. Hogan, C.M. Extremophile. In Encyclopedia of Earth; Monosson, E., Cleveland, C., Eds.; National Council for Science and the Environment: Washington, DC, USA, 2010. [Google Scholar]
  133. Boutard, M.; Cerisy, T.; Nogue, P.Y. Functional diversity of carbohydrate-active enzymes enabling a bacterium to ferment plant biomass. PLoS Genet. 2014, 10, e1004773. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  134. Labus, J.S.; Hsiao, E.; Tap, J.; Derrien, M.; Gupta, A.; Le Nevé, B.; Brazeilles, R.; Grinsvall, C.; Ohman, L.; Törnblom, H.; et al. Clostridia from the Gut Microbiome are Associated with Brain Functional Connectivity and Evoked Symptoms in IBS. Gastroenterology 2017, 152, S40. [Google Scholar] [CrossRef]
  135. Kuske, C.R.; Barns, S.M.; Busch, J.D. Diverse uncultivated bacterial groups from soils of the arid southwestern United States that are present in many geographic regions. Appl. Environ. Microbiol. 1997, 63, 3614–3621. [Google Scholar] [CrossRef] [Green Version]
  136. Quaiser, A.; Ochsenreiter, T.; Lanz, C.; Schuster, S.C.; Treusch, A.H.; Eck, J.; Schleper, C. Acidobacteria form a coherent but highly diverse group within the bacterial domain: Evidence from environmental genomics». Mol. Microbiol. 2003, 50, 563–575. [Google Scholar] [CrossRef]
  137. Kawasumi, T.; Igarashi, Y.; Kodama, T.; Minoda, Y. Hydrogenobacter thermophilus gen. nov., sp. nov., an extremely thermophilic, aerobic, hydrogen-oxidizing bacterium. Int. J. Syst. Bacteriol. 1984, 34, 5–10. [Google Scholar] [CrossRef] [Green Version]
  138. Huber, R.; Wilharm, T.; Huber, D.; Trincone, A.; Burggaf, S.; Konig, H.; Reinhard, R.; Rockinger, I.; Fricke, H.; Stetter, K.O. Aquifex pyrophilus gen. nov. sp. nov., represents a novel group of marine hyperthermophilic hydrogen-oxidizing bacteria. Syst. Appl. Microbiol. 1992, 15, 340–351. [Google Scholar] [CrossRef]
  139. Griffiths, E.; Gupta, R.S. Identification of signature proteins that are distinctive of the Deinococcus–Thermus phylum. Int. Microbiol. 2007, 10, 201–208. [Google Scholar] [PubMed]
  140. Albuquerque, L.; Simões, C.; Nobre, M.F.; Pino, N.M.; Battista, J.; Silva, M.T.; Rainey, F.A.; da Costa, M.S. Truepera radiovictrix gen. nov., sp. nov., a new radiation resistant species and the proposal of Trueperaceae fam. nov. FEMS Microbiol. Lett. 2005, 247, 161–169. [Google Scholar] [CrossRef] [Green Version]
  141. Yang, Y.; Itoh, T.; Yokobori, S.; Itahashi, S.; Shimada, H.; Satoh, K.; Ohba, H.; Narumi, I.; Yamagishi, A. Deinococcus aerius sp. nov., isolated from the high atmosphere. Int. J. Syst. Evol. Microbiol. 2009, 59, 1862–1866. [Google Scholar] [CrossRef]
  142. Zhao, J.S.; Manno, D.; Hawari, J. Psychrilyobacter atlanticus gen. nov., sp. nov., a marine member of the phylum Fusobacteriathatproduces H2and degrades nitramine explosivesunder low temperature condition. Int. J. Syst. Evol. Microbiol. 2009, 59, 491–497. [Google Scholar] [CrossRef]
  143. Harwich, M.D.; Serrano, M.G.; Fettweis, J.M.; Alves, J.M.P.; Reimers, M.A.; Vaginal Microbiome Consortium (additional members); Buck, G.A.; Jefferson, K.K. Genomic sequence analysis and characterization of Sneathia amnii sp. nov. BMC Genom. 2012, 13, S4. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  144. Glöckner, F.O.; Kube, M.; Bauer, M.; Teeling, H.; Lombardot, T.; Ludwig, W.; Gade, D.; Beck, A.; Borzym, K.; Heitman, K.; et al. Complete genome sequence of the marine planctomycete Pirellula sp. strain 1. Proc. Natl. Acad. Sci. USA 2003, 100, 8298–8303. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  145. Kulichevskaya, I.S.; Ivanova, A.O.; Baulina, O.I.; Bodelier, P.L.; Damsté, J.S.; Dedysh, S.N. Singulisphaera acidiphila gen. nov., sp. nov., a non-filamentous, Isosphaera-like planctomycete from acidic northern wetlands. Int. J. Syst. Evol. Microbiol. 2008, 58, 1186–1193. [Google Scholar] [CrossRef] [PubMed]
  146. Fuerst, J.; Sagulenko, E. Beyond the bacterium: Planctomycetes challenge our concepts of microbial structure and function. Nat. Rev. Microbiol. 2011, 9, 403–413. [Google Scholar] [CrossRef] [PubMed]
  147. Jumas-Bilak, E.; Carlier, J.P.; Jean-Pierre, H.; Citron, D.; Bernard, K.; Damay, A.; Gay, B.; Teyssier, C.; Campos, J.; Marchandin, H. Jonquetella anthropi gen. nov., sp. nov., the first member of the candidate phylum ‘Synergistetes’ isolated from man. Int. J. Syst. Bacteriol. 2007, 57, 2743–2748. [Google Scholar] [CrossRef]
  148. Albert, R.A.; Waas, N.E.; Langer, S.; Pavlons, S.C.; Feldner, J.L.; Rosselló-Mora, R.; Busse, H.J. Labrys wisconsinensis sp. nov., a budding bacterium isolated from Lake Michigan water, and emended description of the genus Labrys. Int. J. Syst. Evol. Microbiol. 2010, 60, 1570–1576. [Google Scholar] [CrossRef]
  149. Han, X.Y.; Falsen, E. Characterization of oral strains of Cardiobacterium valvarum and emended description of the organism. J. Clin. Microbiol. 2005, 43, 2370–2374. [Google Scholar] [CrossRef] [Green Version]
  150. Albuquerque, L.; Ferreira, C.; Tomaz, D.; Tiago, T.; Veríssimo, A.; da Costa, M.S.; Nobre, M.F. Meiothermus rufus sp. nov., a new slightly thermophilic red-pigmentedspecies and emended description of the genus Meiothermus. Syst. App. Microbiol. 2009, 32, 306–313. [Google Scholar] [CrossRef] [PubMed]
  151. Chin, K.J.; Liesack, W.; Janssen, P.H. Opitutus terrae gen. nov., sp. nov., to accommodate novel strains of the division Verrucomicrobia isolated from rice paddy soil. Int. J. Syst. Evol. Microbiol. 2001, 51, 1965–1968. [Google Scholar] [CrossRef] [Green Version]
  152. Kocur, M.; Kloos, W.E.; Schleifer, K.H. The Genus Micrococcus. In The Prokaryotes; Dworkin, M., Falkow, S., Rosenberg, E., Schleifer, K.H., Stackebrandt, E., Eds.; Springer: New York, NY, USA, 2006; pp. 961–971. [Google Scholar] [CrossRef]
  153. Mattarelli, P.; Brandi, G.; Calabrese, C.; Fornari, F.; Prati, G.M.; Biavati, B.; Sgorbati, B. Occurrence of Bifidobacteriaceae in human hypochlorhydria stomach. Microb. Ecol. Health Dis. 2014, 25. [Google Scholar] [CrossRef]
  154. Maruo, T.; Sakamoto, M.; Ito, C.; Toda, T.; Benno, Y. Adlercreutzia equolifaciens gen. Nov., sp. Nov., an equol-producing bacterium isolated from human faeces, and emended description of the genus Eggerthella. Int. J. Syst. Evol. Microbiol. 2008, 58, 1221–1227. [Google Scholar] [CrossRef]
  155. Ormerod, K.L.; Wood, D.L.A.; Lachner, N.; Gellatly, S.L.; Daly, J.N.; Parsons, J.D.; Dal’Molin, C.G.O.; Palfreyman, R.W.; Nielsen, L.K.; Cooper, M.A.; et al. Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. Microbiome 2016, 4, 36. [Google Scholar] [CrossRef] [Green Version]
  156. Wang, K.; Lu, W.; Tu, Q.; Ge, Y.; He, J.; Zhou, Y.; Gou, Y.; Van Nostrand, J.D.; Qin, Y.; Li, J.; et al. Preliminary analysis of salivary microbiome and their potential roles in oral lichen planus. Sci. Rep. 2016, 6, 22943. [Google Scholar] [CrossRef] [PubMed]
  157. Seshadri, R.; Leahy, S.C.; Attwood, G.T.; Teh, K.H.; Lambie, S.C.; Cookson, A.L.; Eloe-Fadrosh, E.A.; Pavlopoulos, G.A.; Hadjithomas, M.; Varghese, N.J.; et al. Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection. Nat. Biotechnol. 2018, 36, 359–367. [Google Scholar] [CrossRef] [PubMed]
  158. Kanki, P.; Grimes, D.J. (Eds.) Infectious Diseases Selected Entries from the Encyclopedia of Sustainability Science and Technology; Springer: New York, NY, USA, 2013. [Google Scholar]
  159. Stanton, T.B.; Savage, D.C. Roseburia cecicola gen. nov., sp. nov., a motile, obligately anaerobic bacterium from a mouse cecum. Int. J. Syst. Bacteriol. 1983, 33, 618–627. [Google Scholar] [CrossRef] [Green Version]
  160. Duncan, S.H.; Aminov, R.I.; Scott, K.P.; Louis, P.; Stanton, T.B.; Flint, H.J. Proposal of Roseburia faecis sp. nov., Roseburia hominis sp. nov. and Roseburia inulinivorans sp. nov., based on isolates from human faeces. Int. J. Syst. Evol. Microbiol. 2006, 56, 2437–2441. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  161. Holdeman, L.V.; Moore, W.E.C. New genus, Coprococcus, twelve new species, and emended descriptions of four previously described species of bacteria from human feces. Int. J. Syst. Bacteriol. 1974, 24, 260–277. [Google Scholar] [CrossRef] [Green Version]
  162. McLellan, S.L.; Newton, R.J.; Vandewalle, J.L.; Shanks, O.C.; Huse, S.M.; Eren, A.M.; Sogin, M.L. Sewage reflects the distribution of human faecal Lachnospiraceae. Environ. Microbiol. 2013, 15, 2213–2222. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Taras, D.; Simmering, R.; Collins, M.D.; Lawson, P.A.; Blaut, M. Reclassification of Eubacterium formicigenerans Holdeman and Moore 1974 as Dorea formicigenerans gen. nov., comb. nov., and description of Dorea longicatena sp. nov., isolated from human faeces. Int. J. Syst. Evol. Microbiol. 2002, 52, 423–428. [Google Scholar] [CrossRef] [Green Version]
  164. Bryant, M.P.; Small, N. Characteristics of two new genera of anaerobic curved rods isolated from the rumen of cattle. J. Bacteriol. 1956, 72, 22–26. [Google Scholar] [CrossRef] [Green Version]
  165. Cornick, N.A.; Jensen, N.S.; Stahl, D.A.; Hartman, P.A.; Allison, M.J. Lachnospira pectinoschiza sp. nov., an anaerobic pectinophile from the pig intestine. Int. J. Syst. Bacteriol. 1994, 44, 87–93. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  166. Rainey, F.A. Ruminococcaceae fam. nov. In Bergey’s Manual of Systematics of Archaea and Bacteria; Whitman, W.B., Ed.; in association with Bergey’s Manual Trust; Wiley and Sons, Inc.: Hoboken, NJ, USA, 2015; Volume 2. [Google Scholar] [CrossRef]
  167. Khan, M.T.; Duncan, S.H.; Stams, A.J.; van Dijl, J.M.; Flint, H.J.; Harmsen, H.J. The gut anaerobe Faecalibacterium prausnitzii uses an extracellular electron shuttle to grow at oxic-anoxic interphases. ISME J. 2012, 6, 1578–1585. [Google Scholar] [CrossRef]
  168. Rajilić-Stojanović, M.; de Vos, W.M. The first 1000 cultured species of the human gastrointestinal microbiota. FEMS Microbiol. Rev. 2014, 38, 996–1047. [Google Scholar] [CrossRef] [PubMed]
  169. Holmstrøm, K.; Collins, M.D.; Møller, T.; Falsen, E.; Lawson, P.A. Subdoligranulum variabile gen. nov., sp. nov. from human feces. Anaerobe 2004, 10, 197–203. [Google Scholar] [CrossRef] [PubMed]
  170. Iino, T.; Mori, K.; Tanaka, K.; Suzuki, K.I.; Harayama, S. Oscillibacter valericigenes gen. nov., sp. nov., a valerate-producing anaerobic bacterium isolated from the alimentary canal of a Japanese corbicula clam. Int. J. Syst. Evol. Microbiol. 2007, 57, 1840–1845. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  171. Lee, G.H.; Rhee, M.S.; Chang, D.H.; Lee, J.; Kim, S.; Yoon, M.H.; Kim, B.C. Oscillibacter ruminantium sp. nov., isolated from the rumen of Korean native cattle. Int. J. Syst. Evol. Microbiol. 2013, 63, 1942–1946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  172. Bosch, T.C.G.; McFall-Ngai, M.J. Metaorganisms as the new frontier. Zoology 2011, 114, 185–190. [Google Scholar] [CrossRef] [Green Version]
  173. Bordenstein, S.R.; Theis, K.R. Host biology in light of the microbiome: Ten principles of holobionts and hologenomes. PLoS Biol. 2015, 13, e1002226. [Google Scholar] [CrossRef] [Green Version]
  174. Zilber-Rosenberg, I.; Rosenberg, E. Role of microorganisms in the evolution of animals and plants: The hologenome theory of evolution. FEMS Microbiol. Rev. 2008, 32, 723–735. [Google Scholar] [CrossRef]
  175. Dirksen, P.; Arnaud Marsh, S.; Braker, I.; Heitland, N.; Wagner, S.; Nakad, R.; Mader, S.; Petersen, C.; Kowallik, V.; Rosenstiel, P.; et al. The native microbiome of the nematode Caenorhabditis elegans: Gateway to a new host-microbiome model. BMC Biol. 2016, 14, 38. [Google Scholar] [CrossRef] [Green Version]
  176. Palomares-Rius, J.E.; Archidona-Yuste, A.; Cantalapiedra-Navarrete, C.; Prieto, P.; Castillo, P. Molecular diversity of bacterial endosymbionts associated with dagger nematodes of the genus Xiphinema (Nematoda: Longidoridae) reveals a high degree of phylogenetic congruence with their host. Mol. Ecol. 2016, 25, 6225–6247. [Google Scholar] [CrossRef] [PubMed]
  177. Kim, Y.; Mylonakis, E. Caenorhabditis elegans immune conditioning with the probiotic bacterium Lactobacillus acidophilus strain NCFM enhances grampositive immune responses. Infect. Immun. 2012, 80, 2500–2508. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  178. Danna, P.L.; Urban, C.; Rahal, J.J.; Bellin, E. Role of Candida in pathogenesis of antibiotic-associated diarrhoea in elderly inpatients. Lancet 1991, 337, 511–514. [Google Scholar] [CrossRef]
  179. Morran, L.T.; Penley, M.J.; Byrd, V.S.; Meyer, A.J.; O’Sullivan, T.S.; Bashey, F.; Goodrich-Blair, H.; Lively, C.M. Nematode-Bacteria Mutualism: Selection Within the Mutualism Supersedes Selection Outside of the Mutualism. Evolution 2016, 70, 687–695. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  180. Zeppilli, D.; Bellec, L.; Cambon-Bonavita, M.A.; Decraemer, W.; Fontaneto, D.; Fuchs, S.; Gayet, N.; Mandon, P.; Michel, L.N.; Portail, M.; et al. Ecology and trophic role of Oncholaimus dyvae sp. nov. (Nematoda: Oncholaimidae) from the lucky strike hydrothermal vent field (Mid-Atlantic Ridge). BMC Zool. 2019, 4, 6. [Google Scholar] [CrossRef]
  181. Bellec, L.; Cambon-Bonavita, M.A.; Cueff-Gauchard, V.; Durand, L.; Gayet, N.; Zeppilli, D.A. Nematode of the Mid-Atlantic Ridge Hydrothermal Vents Harbors a Possible Symbiotic Relationship. Front. Microbiol. 2018, 9, 2246. [Google Scholar] [CrossRef]
  182. Sanders, H.L. Benthic marine diversity and the stability-time hypothesis. Brookhaven Symp. Biol. 1969, 22, 71–81. [Google Scholar]
  183. Hughes, J.B.; Bohannan, B.J.M. Application of ecological diversity statistics in microbial ecology. Mol. Microb. Ecol. Manual 2004, 1321–1344. [Google Scholar] [CrossRef]
  184. Kim, B.R.; Shin, J.; Guevarra, R.B.; Lee, J.H.; Wan Kim, D.; Seol, K.H.; Lee, J.H.; Kim, H.B.; Isaacson, R. Deciphering Diversity Indices for a Better Understanding of MicrobialCommunitie. J. Microbiol. Biotechnol. 2017, 27, 2089–2093. [Google Scholar] [CrossRef] [Green Version]
  185. Rosenfeld, J.S. Functional redundancy in Ecology and Conservation. OIKOS 2002, 98, 156–162. [Google Scholar] [CrossRef] [Green Version]
  186. Xue, Z.; Zhang, W.; Wang, L.; Hou, R.; Zhang, M.; Fei, L.; Zhang, X.; Huang, H.; Bridgewater, L.C.; Jiang, Y.; et al. The Bamboo-Eating Giant Panda Harbors a Carnivore-Like Gut Microbiota, with Excessive Seasonal Variations. mBio 2015, 6, e00022-15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  187. Ettema, C.H. Soil nematode diversity: Species coexistence and ecosystem function. J. Nematol. 1998, 30, 159–169. [Google Scholar]
  188. De Ley, P. A quick tour of nematode diversity and the backbone of nematode phylogeny. WormBook 2006, 1–8. [Google Scholar] [CrossRef] [PubMed]
  189. Borgonie, G.; Garcia-Moyano, A.; Litthauer, D.; Bert, W.; Bester, A.; van Heerden, E.; Moller, C.; Erasmus, M.; Onstott, T.C. Nematoda from the terrestrial deep subsurface of South Africa. Nature 2011, 474, 79–82. [Google Scholar] [CrossRef] [Green Version]
  190. Poinar, G.O., Jr.; Hansen, E.L. Associations between nematodes and bacteria. Helminthol. Abst. B 1986, 55, 61–79. [Google Scholar]
  191. Goodrich-Blair, H. They’ve got a ticket to ride: Xenorhabdus nematophila-Steinernema carpocapsae symbiosis. Curr. Opin. Microbiol. 2007, 10, 225–230. [Google Scholar] [CrossRef]
  192. Gram, L.; Huss, H.H. Microbiological spoilage of fish and fish products. In. J. Food Microbiol. 1996, 33, 121–137. [Google Scholar] [CrossRef]
  193. Svanevik, C.S.; Lunestad, B.T. Characterisation of the microbiota of Atlantic mackerel (Scomber scombrus). Int. J. Food Microbiol. 2011, 151, 164–170. [Google Scholar] [CrossRef]
  194. Huss, H. Quality and quality changes in fresh fish. In FAO Fisheries; Technical Paper No. 348; FAO: Rome, Italy, 1995. [Google Scholar]
  195. Svanevik, C.S.; Levsen, A.; Lunestad, B.T. The role of muscle-invading anisakid larvae on bacterial contamination of the flesh of post-harvest blue whiting (Micromesistius poutassou). Food Control 2013, 30, 526–530. [Google Scholar] [CrossRef]
  196. Svanevik, C.S.; Lunestad, B.T.; Levsen, A. Effect of Anisakis simplex (sl) larvae on the spoilage rate and shelf-life of fish mince prod ucts under laboratory conditions. Food Control 2014, 46, 121–126. [Google Scholar] [CrossRef] [Green Version]
  197. Novotny, L.; Dvorska, L.; Lorencova, A.; Beran, V.; Pavlik, I. Fish: A potential source of bacterial pathogens for human beings. Vet. Med. 2004, 49, 343–358. [Google Scholar] [CrossRef]
  198. Svanevik, C.S.; Roiha, I.S.; Levsen, A.; Lunestad, B.T. Microbiological assessment along the fish production chain of the Norwegian pelagic fisheries sector results from a spot sampling programme. Food Microbiol. 2015, 51, 144–153. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  199. Butt, A.A.; Aldridge, K.E.; Sanders, C.V. Infections related to the ingestion of seafood Part I: Viral and bacterial infections. Lancet Infec. Dis. 2004, 4, 201–212. [Google Scholar] [CrossRef]
  200. Chaillou, S.; Chaulot-Talmon, A.; Caekebeke, H.; Cardinal, M.; Christieans, S.; Denis, C.; Desmonts, M.H.; Dousset, X.; Feurer, C.; Hamon, E.; et al. Origin and ecological selection of core and food-specific bacterial communities associated with meat and seafood spoilage. ISME J. 2015, 9, 1105–1118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Diversity profiles. (a) Rarefaction curves of operational taxonomic units (OTUs) which are clustered at 97% sequence identity across the 113 samples of anisakids. All samples are represented. None fish host or anisakids species seems to be related with the bacterial OTUs diversity structure. (b) Diversity ordering by mean of Renyi´s index family curves showing differences in OTUs diversity among each anisakid individuals. The Renyi index estimates total richness for a = 0, Shannon-Weiner index for α = 1, the inverse Simpson-Yule index for α = 2 and 1/Berger-Parker index for α = Infinite. Most of the anisakids individuals are non-comparable because their diversity profiles are intersecting.
Figure 1. Diversity profiles. (a) Rarefaction curves of operational taxonomic units (OTUs) which are clustered at 97% sequence identity across the 113 samples of anisakids. All samples are represented. None fish host or anisakids species seems to be related with the bacterial OTUs diversity structure. (b) Diversity ordering by mean of Renyi´s index family curves showing differences in OTUs diversity among each anisakid individuals. The Renyi index estimates total richness for a = 0, Shannon-Weiner index for α = 1, the inverse Simpson-Yule index for α = 2 and 1/Berger-Parker index for α = Infinite. Most of the anisakids individuals are non-comparable because their diversity profiles are intersecting.
Microorganisms 09 01088 g001aMicroorganisms 09 01088 g001b
Figure 2. Cluster analysis of anisakids samples L3 considering three different taxonomic levels of bacteria; phyla (a), order (b) and genus (c). Substantially the same structure is maintained from phyla to order level. At genus level a new significant cluster (green) is formed joining samples from red and green clusters from higher taxonomic levels, while the extended black cluster from phyla and order levels is split in two (black and red). This structure is manifested by ordination methods through correspondence and detected by the factorial analysis (Figure 3, Figure 4 and Figure 5).
Figure 2. Cluster analysis of anisakids samples L3 considering three different taxonomic levels of bacteria; phyla (a), order (b) and genus (c). Substantially the same structure is maintained from phyla to order level. At genus level a new significant cluster (green) is formed joining samples from red and green clusters from higher taxonomic levels, while the extended black cluster from phyla and order levels is split in two (black and red). This structure is manifested by ordination methods through correspondence and detected by the factorial analysis (Figure 3, Figure 4 and Figure 5).
Microorganisms 09 01088 g002aMicroorganisms 09 01088 g002b
Figure 3. Factorial Analysis considering the anisakids samples and bacteria at phyla level. In the factorial space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) can be seen the correspondence with the classified clusters of Figure 2a.
Figure 3. Factorial Analysis considering the anisakids samples and bacteria at phyla level. In the factorial space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) can be seen the correspondence with the classified clusters of Figure 2a.
Microorganisms 09 01088 g003aMicroorganisms 09 01088 g003b
Figure 4. Factorial analysis considering the anisakids samples and bacteria at order levels. In the In the Factorial Space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) is disposed the correspondence with the classified clusters of Figure 2b.
Figure 4. Factorial analysis considering the anisakids samples and bacteria at order levels. In the In the Factorial Space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) is disposed the correspondence with the classified clusters of Figure 2b.
Microorganisms 09 01088 g004
Figure 5. Factorial analysis considering the anisakids samples and bacteria at genus level. In the Factorial Space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) is disposed the correspondence with the classified clusters of Figure 2c.
Figure 5. Factorial analysis considering the anisakids samples and bacteria at genus level. In the Factorial Space defined by Factor 1 vs. Factor 2 (a) and Factor 1 vs. Factor 3 (b) is disposed the correspondence with the classified clusters of Figure 2c.
Microorganisms 09 01088 g005aMicroorganisms 09 01088 g005b
Table 1. Order of bacteria distributed to classes and phyla, which have been recorder in 113 L3 individuals of anisakids. Colors are in accordance to the association they forms in Figure 3 and Figure 4. Asterisks denote the importance the taxa have in factorial analysis. Also is reported the frequency and the average mean of phyla and orders in 113 L3 individuals of anisakids.
Table 1. Order of bacteria distributed to classes and phyla, which have been recorder in 113 L3 individuals of anisakids. Colors are in accordance to the association they forms in Figure 3 and Figure 4. Asterisks denote the importance the taxa have in factorial analysis. Also is reported the frequency and the average mean of phyla and orders in 113 L3 individuals of anisakids.
AcidobacteriaActinobacteria*Aquificae*Bacteroidetes*ChlamydiaeChloroflexi*Deinococcus-Thermus*Firmicutes*Fusobacteria*Planctomycetes*Proteobacteria*Synergistetes*VerrucomicrobiaCyanobacteria*Unclassified
(105 seqs)
AcidobacteriaAcidobacteriales (75.2%), 59.80
Rubrobacteria Rubrobacterales (13.3%), 8.93
Actinobacteria Acidimicrobiales
Actinomycetales Bifidobacteriales *
(54%), 75.79
(100%), 2625.95
(57.52%), 79.78
Coriobacteriia Coriobacteriales (65.48%), 76.01
Aquificae Aquificales* (2.65%), 76.00
Bacteroidia Bacteroidales* (97.34%), 211.62
Flavobacteria Flavobacteriales* (99.11%), 254.03
Sphingobacteria Sphingobacteriales (91.15%), 129.55
Chlamydiae Chlamydiales (15.93%), 9.55
Anaerolineae Anaerolineales (13.27%), 21.13
Caldilineae Caldilineales (7.08%), 23.87
Chloroflexia Chloroflexales* (10.62%), 5.41
Deinococci Thermales
Deinoccocales
(6.19%), 30.14
(59.30%), 21.50
Bacilli Bacillales
Lactobacillales
(99.11%), 112,41
(99.11%), 323.06
Mollicutes Mycoplasmatales (8.10%), 16.78
Erysipelotrichia Erysipelothrichales (52.21%), 22.76
Clostridia Clostridiales* Thermoanaerobacteriales (100%), 4450.98
(8.85%), 21.90
Fusobacteria Fusobacteriales (100%), 755.18
Planctomycetya Planctomycetales* (45.13%), 16.43
Phycisphaerae Phycisphaerales (5.31%), 32.00
Alphaproteobacteria Caulobacterales
Parvularculales*
Rhizobiales
Rhodobacterales*
Rhodospirillales
Rickettsiales
Sphingomonadales*
(94.70%), 667.46
(0.89%), 31.00
(100%), 2472.23
(91,15%), 192.87
(96,46%), 197.50
(7,68%), 15.11
(100%), 2692.78
Betaproteobacteria Burkholderiales
Neisseriales*
(100%), 189.26(83,18%), 28.25
Epsiloproteobacteria Campylobacteriales (95.60%), 540.42
Deltaproteobacteria Bdellovibrionales
Desulfobacterales
Desulfovibrionales
Desulfuromonadales
Myxococcales
(14.16%), 25.31
(1.76%), 15,50
(6.2%), 6.28
(7.96%), 7.22
(25.66%), 10.93
Gammaproteobacteria Aeromonadales
Alteromonadales
Cardiobacteriales
Chromatiales*
Enterobacteriales
Oceanospirillales
Pasteurellales*
Pseudomonadales
Vibrionales
Xanthomonadales
(44.24%), 77.56
(53,09%), 22.10
(19,46%), 11.77
(8.85%), 7.30
(87.61%), 35,56
(30.97%), 7.65(80.53%), 37,61
(100%), 301.72
(82,30%), 199.86
(57,52%), 10.41
Synergistia Synergistales
Opitutae Opitutales
unclassified unclassified
MLE1-12 unclassified
Subsection IV unclassified
Subsection III unclassified
(Phyla % in total samples)
Mean of sequences
(76%)
59.60
(100%)
2838.28
(2.65%)
76.00
(100%)
705.41
(15.93%)
9.55
(74.33%)
66.13
(61.94%)
23.87
(100%)
5659.03
(100%)
755.18
(63.72%)
35.56
(100%)
9291.94
(10.62%)
73.75
(23.9%)
17.59
(100%)
297.74
Table 2. Genera of Proteobacteria members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
Table 2. Genera of Proteobacteria members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
Alphaproteobacteria BetaproteobacteriaEpsiloproteobacteria Deltaproteobacteria Gammaproteobacteria
CaulobacteralesParvularculalesRhizobialesRhodobacteralesRhodospirillalesRickettsialesSphingomonadalesBurkholderialesNeisserialesCampylobacteralesBdellovibrionalesDesulfobacteralesDesulfovibrionalesDesulfuromonadalesMyxococcalesAeromonadalesAlteromonadalesCardiobacterialesChromatialesEnterobacterialesOceanospirillalesPasteurellalesPseudomonadalesVibrionalesXanthomonadales
CaulobacteraceaeCaulobacter
Brevundimonas
Phenylobacterium
Asticcacaulis
Parvularculaceae Parvularcula
Bradyrhizobiaceae Bradyrhizobium
unclassified
Bosea
Methylobacteriaceae Methylobacterium*
unclassified unclassified
Hyphomicrobiaceae Devosia*
unclassified
Hyphomicrobium
Angulomicrobium
Pedomicrobium
Rhodobiaceae RhodobiuM*
Phyllobacteriaceae Mesorhizobium
unclassified
Xanthobacteraceae Labrys
Beijerinckiaceae Chelatococcus
Methylocystaceae unclassified
Rhodobiaceae Parvibaculum
Brucellaceae Ochrobactrum
Nordella cluster Nordella
Rhizobiaceae unclassified

Rhodobacteraceae
Paracoccus*
unclassified
Roseobacter_clade
Acetobacteraceae Gluconobacter
unclassified
Roseomonas*
Acetobacter
Acidocella
Acidiphilium
Rhodospirillaceae Skermanella
Azospirillum
Caenispirillum
Magnetospirillum
unclassified
Defluviicoccus
unclassified unclassified
wr0007 unclassified
Candidatus_Alysiosphaera cluster unclassified
Anaplasmataceae Wolbachia
Rickettsiaceae Rickettsia*
Candidatus_Odyssella cluster unclassified
SM2D12 unclassified
Sphingomonadaceae Sphingomonas*
Novosphingobium* unclassified Sphingobium Sphingopyxis*
unclassified unclassified
Erythrobacteraceae unclassified
Erythrobacter
GOBB3-C201 unclassified
Oxalobacteraceae Janthinobacterium*
Alcaligenaceae Alcaligenes
Comamonadaceae unclassified
Burkholderiaceae Ralstonia
Neisseriaceae Neisseria*
unclassified

Campylobacteraceae
Arcobacter
Campylobacter*
Sulfurospirillum
Bacteriovoraceae Peredibacter
Bdellovibrionacea Bdellovibrio
Desulfobulbaceae Desulfobulbus
Desulfovibrionaceae unclassified
Geobacteraceae Geobacter
Polyangiaceae unclassified
Haliangiaceae Haliangium
Unclassified unclassified
Aeromonadaceae Aeromonas
Succinivibrionaceae Succinivibrio
Shewanellaceae Shewanella*
Psychromonadaceae Psychromonas
Cardiobacteriaceae unclassified
Cardiobacterium
Chromatiaceae Unclassified
Enterobacteriaceae unclassified
Enteric_Bacteria_cluster
Oceanospirillaceae Marinomonas
Pasteurellaceae unclassified
Pseudomonadaceae Pseudomonas*
unclassified

Moraxellaceae
Psychrobacter
Acinetobacter
unclassified
Vibrionaceae unclassified
Photobacterium
Sinobacteraceae Nevskia
Xanthomonadaceae unclassified
Table 3. Genera of Actinobacteria, Bacterioidetes Cloroflexi and Firmicutes members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
Table 3. Genera of Actinobacteria, Bacterioidetes Cloroflexi and Firmicutes members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
Actinobacteria Bacteroidetes Chloroflexi Firmicutes
Rubrobacteria Actinobacteria CoriobacteriaBacteroidiaFlavobacteriaSphingobacteriaAnaerolineaeCaldilineaeChloroflexiaBacilli MollicutesErysipelotrichiaClostridia
RubrobacteralesAcidimicrobialesActinomycetalesBifidobacterialesCoriobacterialesBacteroidalesFlavobacterialesSphingobacterialesAnaerolinealesCaldilinealesChloroflexalesBacillalesLactobacillalesMycoplasmatalesErysipelotrichalesClostridialesThermoanaerobacterales
RubrobacteriaceaeRubrobacter
Acidimicrobiaceae (5)unclassified
Actinomycetaceae (2) Actinomyces*
Mobiluncus
Brevibacteriaceae (2) Brevibacterium*
Cellulomonadaceae unclassified
Corynebacteriaceae Corynebacterium*
Dermabacteraceae Brachybacterium*
Dermatophilaceae unclassified
Dietziaceae Dietzia
Geodermatophilaceae Blastococcus
Geodermatophilus
Glycomycetaceae Glycomyces
Intrasporangiaceae Ornithinicoccus
Kineosporiaceae Kineococcus
Microbacteriaceae unclassified
Micrococcaceae Micrococcus*
Rothia *
Kocuria
Arthrobacter
Micromonosporaceae Actinoplanes
Mycobacteriaceae Mycobacterium*

Nocardiaceae
Rhodococcus Gordonia
Nocardia

Nocardioidaceae
Nocardioides* Aeromicrobium
Kribbella
Propionibacteriaceae Propionibacterium*
Friedmanniella

Pseudonocardiaceae
Pseudonocardia
Amycolatopsis
Sporichthyaceae hgcI_clade
Streptomycetaceae Streptomyces
Streptosporangiaceae Nonomuraea
Thermomonosporaceae Actinomadura
Bifidobacteriaceae Alloscardovia
Bifidobacterium
Gardnerella
Coriobacteriaceae Atopobium*
Olsenella*
Slackia
Unclassified
Collinsella
Adlercreutzia
Eggerthella
Prevotellaceae Prevotella*
Bacteroidaceae Bacteroides*

Porphyromonadaceae
Porphyromonas*
Parabacteroides
Tannerella*
Odoribacter
Flavobacteriaceae Flavobacterium*
unclassified
Cloacibacterium
Capnocytophaga*
Chryseobacterium
Polaribacter
Wautersiella
Amoebinatus

Sphingobacteriaceae
Pedobacter
unclassified
Sphingobacterium

Cytophagaceae
Hymenobacter*
Dyadobacter
unclassified unclassified

Chitinophagaceae
unclassified
Chitinophaga
Anaerolineaceae Unclassified
Caldilineaceae Caldilinea
Chloroflexaceae Roseiflexus
Listeriaceae Listeria
Paenibacillaceae Ammoniphilus
Planococcaceae Kurthia
Staphylococcaceae Staphylococcus*
Thermoactinomycetaceae Laceyella
unclassified unclassified
Carnobacteriaceae unclassified
Desemzia
Dolosigranulum
Alloiococcus
Carnobacterium

Streptococcaceae
Streptococcus*
Lactococcus*

Leuconostocaceae
Leuconostoc
Weissella*

Lactobacillaceae
unclassified
Lactobacillus

Aerococcaceae
Flacklamia
Aerococcus
Mycoplasmataceae unclassified

Erysipelotrichaceae
Bulleidia*
Solobacterium
unclassified
Family_XI_Incertae_Sedis Anaerococcus*
Finegoldia *
Peptoniphilus
Parvimonas*
Mogibacterium*
Helcococcus
unclassified
Eubacterium
Sedimentibacter
Lachnospiraceae Roseburia*
Johnsonella*
Catonella*
unclassified
Incertae_Sedis
Coprococcus*
Shuttleworthia
Blautia*
Oribacterium*
Moryella*
Butyrivibrio-Pseudobutyrivibrio
Dorea
Lachnospira
Ruminococcaceae Faecalibacterium*
Subdoligranulum
unclassified
Fastidiosipila*
Incertae_Sedis
Ruminococcus
Ethanoligenens
Acetivibrio
Oscillibacter
Peptostreptococc
aceae
Incertae_Sedis
Peptostreptococcus*
Filifactor*
Peptococcus*
Sporacetigenium*
Desulfosporosinus
Veillonellaceae Veillonella*
Selenomonas*
unclassified
Mitsuokella
Megamonas
Dialister*

Clostridiaceae
unclassified
Clostridium*
Caloramator
unclassified unclassified
Eubacteriaceae Eubacterium*
Acetobacterium

Family_III_Incertae_Sedis
Caldicellulosiruptor
Thermoanaerobacter
Table 4. Genera of Acidobacteria, Aquificae Clamydiae, Deinococcus-Thermus, Fusobacteria, Planctomycetes, Synergetes and Verrcomicrobia members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
Table 4. Genera of Acidobacteria, Aquificae Clamydiae, Deinococcus-Thermus, Fusobacteria, Planctomycetes, Synergetes and Verrcomicrobia members of anisakids microbiota. Colors represent the clusters in which they are in Figure 5. Asterisks denote the most contributive in the ordination of Factorial Space.
AcidobacteriaAquificaeChamydiaeDeinococcus-ThermusFusobacteriaPlanctomycetesSynergistetesVerrucomicrobia
AcidobacteriaAquificaeChlamydiaeDeinococciFusobacteriaPlanctomycetaPhycisphaeraeSynergistiaOpitutae
AcidobacterialesAquificalesChlamydialesThermalesDeinococcalesFusobacterialesPlanctomycetalesPhycisphaeralesSynergistalesOpitutales
AcidobacteriaceaeChloroacidobacterium
Acidobacterium
Edaphobacter*
Koribacter Solibacter
Aquificaceae Hydrogenobacter
Unclassified unclassified
Thermaceae Meiothermus
Trueperaceae Truepera*
Deinococcaceae Deinococcus*
Fusobacteriaceae Fusobacterium*
unclassified
Psychrilyobacter
Leptotrichiaceae Leptotrichia*
Sneathia
unclassified
Planctomycetaceae Singulisphaera*
Planctomyces*
Unclassified
Phycisphaeraceae CL500-3
Phycisphaera
Synergistaceae unclassified
Jonquetella
Opitutaceae Opitutus*
Table 5. Discriminant analysis values for significant bacteria at phylum (a) and order (b) level and according group of sample classification (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
Table 5. Discriminant analysis values for significant bacteria at phylum (a) and order (b) level and according group of sample classification (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
F (28.194) = 20.998 p < 0.0000F-Remove
(2.97)
p-LevelSample Group 1Sample Group 2Sample Group 3All Groups
Actinobacteria6.0925 **0.0032185324.2082505.1672115.3642838.283
Aquificae4.4817 **0.0137520.00018.0000.15584422.017699
Firmicutes126.8766 ***0.0000005412.58324247.082839.0135659.035
Proteobacteria76.6841 ***0.00000023561.55097.1675498.0139291.938
Percent correct classification 87.5091.66100.0096.46
(a)
F (104.118) = 5.7435 p < 0.0000F-Remove
(2.59)
p-LevelSample Group 1Sample Group 2Sample Group 3All Groups
Actinomycetales6.736752 ***0.0024675007.20821311960.872625.947
Anaerolineales3.30950 *0.0434278.8333330.000001.3636362.80531
Bacillales3.98242 *0.02385991.08334158.8333110.3636111.4159
Bacteroidales6.13735 **0.003789177.4167858.75113.1948206.0089
Caldilineales3.22566 *0.0468327.750.083333340.051948051.690266
Campylobacterales9.84095 ***0.0002051903.16795.58334149.9091516.5132
Caulobacterales8.75310 ***0.0004691726.917109.6667372.1688632.0266
Clostridiales6.00333 *0.0042354161.16720972.331966.5584450.982
Sphingomonadales13.72837 ***0.00001360.54167184.8333125.6234118.0885
Percent correct classification 91.6691.6610097.34
(b)
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Arcos, S.C.; Lira, F.; Robertson, L.; González, M.R.; Carballeda-Sangiao, N.; Sánchez-Alonso, I.; Zamorano, L.; Careche, M.; Jiménez-Ruíz, Y.; Ramos, R.; et al. Metagenomics Analysis Reveals an Extraordinary Inner Bacterial Diversity in Anisakids (Nematoda: Anisakidae) L3 Larvae. Microorganisms 2021, 9, 1088. https://doi.org/10.3390/microorganisms9051088

AMA Style

Arcos SC, Lira F, Robertson L, González MR, Carballeda-Sangiao N, Sánchez-Alonso I, Zamorano L, Careche M, Jiménez-Ruíz Y, Ramos R, et al. Metagenomics Analysis Reveals an Extraordinary Inner Bacterial Diversity in Anisakids (Nematoda: Anisakidae) L3 Larvae. Microorganisms. 2021; 9(5):1088. https://doi.org/10.3390/microorganisms9051088

Chicago/Turabian Style

Arcos, Susana C., Felipe Lira, Lee Robertson, María Rosa González, Noelia Carballeda-Sangiao, Isabel Sánchez-Alonso, Laura Zamorano, Mercedes Careche, Yolanda Jiménez-Ruíz, Ricardo Ramos, and et al. 2021. "Metagenomics Analysis Reveals an Extraordinary Inner Bacterial Diversity in Anisakids (Nematoda: Anisakidae) L3 Larvae" Microorganisms 9, no. 5: 1088. https://doi.org/10.3390/microorganisms9051088

APA Style

Arcos, S. C., Lira, F., Robertson, L., González, M. R., Carballeda-Sangiao, N., Sánchez-Alonso, I., Zamorano, L., Careche, M., Jiménez-Ruíz, Y., Ramos, R., Llorens, C., González-Muñoz, M., Oliver, A., Martínez, J. L., & Navas, A. (2021). Metagenomics Analysis Reveals an Extraordinary Inner Bacterial Diversity in Anisakids (Nematoda: Anisakidae) L3 Larvae. Microorganisms, 9(5), 1088. https://doi.org/10.3390/microorganisms9051088

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop