Taxogenomic and Comparative Genomic Analysis of the Genus Saccharomonospora Focused on the Identification of Biosynthetic Clusters PKS and NRPS

fmicb-12-603791 March 7, 2021 Time: 16:50 # 1 ORIGINAL RESEARCH published: 11 March 2021 doi: 10.3389/fmicb.2021.603791 Edited by: Jesse G. Dillon, California State University, Long Beach, United States Reviewed by: David Edward Whitworth, Aberystwyth University, United Kingdom Lorena Carro, Newcastle University, United Kingdom Hilal Ay, Ondokuz Mayıs University, Turkey *Correspondence: Antonio Ventosa [email protected] †These authors have contributed equally to this work Specialty section: This article was submitted to Extreme Microbiology, a section of the journal Frontiers in Microbiology Received: 07 September 2020 Accepted: 17 February 2021 Published: 11 March 2021 Citation: Ramírez-Durán N, de la Haba RR, Vera-Gargallo B, Sánchez-Porro C, Alonso-Carmona S, Sandoval-Trujillo H and Ventosa A (2021) Taxogenomic and Comparative Genomic Analysis of the Genus Saccharomonospora Focused on the Identification of Biosynthetic Clusters PKS and NRPS. Front. Microbiol. 12:603791. doi: 10.3389/fmicb.2021.603791 Taxogenomic and Comparative Genomic Analysis of the Genus Saccharomonospora Focused on the Identification of Biosynthetic Clusters PKS and NRPS Ninfa Ramírez-Durán1,2†, Rafael R. de la Haba2†, Blanca Vera-Gargallo2, Cristina Sánchez-Porro2, Scarlett Alonso-Carmona1, Horacio Sandoval-Trujillo3and Antonio Ventosa2* 1Faculty of Medicine, Autonomous University of the State of Mexico, Toluca, Mexico, 2Department of Microbiology and Parasitology, Faculty of Pharmacy, University of Sevilla, Seville, Spain, 3Department of Biological Systems, Metropolitan Autonomous University-Xochimilco, Mexico City, Mexico Actinobacteria are prokaryotes with a large biotechnological interest due to their ability to produce secondary metabolites, produced by two main biosynthetic gene clusters (BGCs): polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS). Most studies on bioactive products have been carried out on actinobacteria isolated from soil, freshwater or marine habitats, while very few have been focused on halophilic actinobacteria isolated from extreme environments. In this study we have carried out a comparative genomic analysis of the actinobacterial genus Saccharomonospora, which includes species isolated from soils, lake sediments, marine or hypersaline habitats. A total of 19 genome sequences of members of Saccharomonospora were retrieved and analyzed. We compared the 16S rRNA gene-based phylogeny of this genus with evolutionary relationships inferred using a phylogenomic approach obtaining almost identical topologies between both strategies. This method allowed us to unequivocally assign strains into species and to identify some taxonomic relationships that need to be revised. Our study supports a recent speciation event occurring between Saccharomonospora halophila and Saccharomonospora iraqiensis. Concerning the identification of BGCs, a total of 18 different types of BGCs were detected in the analyzed genomes of Saccharomonospora, including PKS, NRPS and hybrid clusters which might be able to synthetize 40 different putative products. In comparison to other genera of the Actinobacteria, members of the genus Saccharomonospora showed a high degree of novelty and diversity of BGCs. Keywords: actinobacteria, Saccharomonospora, biosynthetic gene clusters, secondary metabolites, polyketide synthase, non-ribosomal peptide synthetase, comparative genomic analysis, taxophylogenomic analysis Frontiers in Microbiology | www.frontiersin.org 1March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 2 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora INTRODUCTION Actinobacteria are a diverse group of clinical, industrial and ecologically important bacteria known for their capacity to cause diseases as well as their potential to produce secondary metabolites widely used in a variety of fields, such as medicine, pharmacy, industrial microbiology and biotechnology, among others (Bérdy, 2012;Doroghazi and Metcalf, 2013). Synthesis of bacterial secondary metabolites might have been originated due to necessary adaptations to diverse environments with the objective to help the producer microorganism to compete for survival resources (Doroghazi and Metcalf, 2013). Genes involved in secondary metabolite production are commonly grouped within the genome and are usually known as biosynthetic gene clusters (BGCs) (Osbourn, 2010). Actinobacteria represent one of the most important sources for discovering new biologically active metabolites (Kamjam et al., 2017;Matsumoto and Takahashi, 2017) due to the presence of two main biosynthetic clusters, polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS), involved in the synthesis of bioactive molecules through multifunctional pathways (Fischbach and Walsh, 2006). Biosynthetic gene clusters for secondary metabolites have been studied in actinobacteria isolated from different environments, such as soil (Sharma et al., 2016;Wang et al., 2018), caves (Gosse et al., 2019), freshwater (Zothanpuia et al., 2018), marine (Zhang et al., 2019; Ishaque et al., 2020) and as endophytes from plants (Passari et al., 2016, 2017). Halophilic actinobacteria from extreme ecosystems have also been reported, but only biosynthetic gene clusters from Actinopolyspora erythraea YIM 90600Thave been located and identified so far (Chen et al., 2014;Corral et al., 2020). Although a large number of secondary metabolites has been discovered, new bioactive products are still required to cover the current needs of clinical, veterinary and agricultural areas, given the frequent development of microbial resistance of pathogens (Rangseekaew and Pathom-aree, 2019), the appearance of novel diseases, the existence of naturally resistant bacteria and the toxicity of several compounds used in agriculture and cattle industry (Fischbach and Walsh, 2009). The rapid advance of complete genome sequencing and comparative genomic techniques have made it possible to apply bioinformatic tools, such as genomic mining, to carry out a comparative analysis of genomes available in public databases (Challis, 2008). This approach allows one, on the one hand, to comprehend the evolutionary relationships among microbial species and, on the other hand, to identify clusters of genes involved in biosynthetic pathways of relevant biomolecules with potential use for disease treatments. The actinobacterial genus Saccharomonospora, belonging to the family Pseudonocardiaceae, was proposed in 1971 (Nonomura and Ohara, 1971) and currently comprises 14 validly published species names (Nonomura and Ohara, 1971;Challis, 2008;Syed et al., 2008;Fischbach and Walsh, 2009;Veyisoglu et al., 2013;Chen et al., 2014;Passari et al., 2016, 2017;Tseng et al., 2018;Zothanpuia et al., 2018;Rangseekaew and Pathomaree, 2019;Zhang et al., 2019;Corral et al., 2020;Ishaque et al., 2020). The species name “Saccharomonospora internatus” has been effectively but not validly published (Greiner-Mai et al., 1987) and has been recently reclassified as an additional strain of the species Saccharomonospora viridis (Nouioui et al., 2018). Finally, the species initially described as Saccharomonospora paurometabolica (Li et al., 2003) was proved to be a subspecies of Saccharomonospora iraqiensis (Nouioui et al., 2018). Members of this genus have been isolated from diverse environments, such as soil, lake sediments, marsh soil, peat, manure, compost, and overheated fodder, with some of them being classified as halophilic microorganisms (Kim, 2015). In this study we have carried out phylogenomic and comparative genomic analyses of the genus Saccharomonospora aimed at reviewing the current taxonomy of this genus and locating and identifying PKS and NRPS biosynthetic clusters present in the genomes with potential for future development of novel active biomolecules. MATERIALS AND METHODS Genome Sequence Retrieval All genome sequences affiliated to members of the genus Saccharomonospora and publicly available at the National Center for Biotechnology Information (NCBI) and at the Joint Genome Institute (JGI) databases as of May 31st, 2019 were retrieved. A total of 19 complete or draft genomes were recovered, including type and other reference strains (Table 1). Genome sequences for the type strains of the species S. colocasiae,S. oceani, and S. xiaoerkulensis were not included in the analyses due to the absence of data in public databases. Prediction of Open Reading Frames and genome annotation, including protein-coding genes as well as other functional genome units such as structural RNAs, tRNAs, was performed following the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) (Haft et al., 2018). Phylogenetic and Phylogenomic Analyses Phylogenetic trees based on the 16S rRNA gene sequences extracted from the annotated genomes or retrieved from GenBank/EMBL/DDBJ databases were constructed using the neighbor-joining (Saitou and Nei, 1987), maximum-parsimony (Fitch, 1971) and maximum-likelihood (Felsenstein, 1981) algorithms in MEGA X software (Kumar et al., 2018). The distance matrix was corrected using the Jukes-Cantor model of DNA evolution (Jukes and Cantor, 1969). Branch support was assessed by 1,000 bootstrap pseudo-replicates (Felsenstein, 1985). For phylogenomic tree construction only amino acidic sequences of single-copy core genes shared by all the analyzed genomes were used, as described elsewhere (de la Haba et al., 2019). Selection of those common orthologous genes (OGs) was done by finding the reciprocal best matches between pairs of genome sequences after an all-versus-all Blast search as implemented in the Enveomics collection toolbox (Rodriguez- R and Konstantinidis, 2016). Subsequently, selected OGs were aligned by using Muscle (Edgar, 2004), concatenated and employed for approximately maximum-likelihood phylogenomic tree reconstruction with FastTreeMP v.2.1.8 (Price et al., 2010) Frontiers in Microbiology | www.frontiersin.org 2March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 3 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora TABLE 1 | Main features of genome sequences of strains of the genus Saccharomonospora used in this study. Strain Accession No. Assembly Level Size (Mb) GC% Scaffolds Contigs CDS N50 L50 Group Saccharomonospora amisosensis DSM 45685T PRJNA546941 1GCF_011761185.1 Scaffold 5.53 68.6 3 3 5,395 4,804,314 1 Marine/Lake Saccharomonospora azurea NA-128T CM001466.1 GCF_000231055.3 Chromosome 4.76 70.0 1 96 4,406 4,763,852 1 Terrestrial Saccharomonospora azurea SZMC 14600 AHBX00000000.1 GCF_000236985.1 Contig 4.97 70.3 216 218 4,624 55,033 29 Terrestrial Saccharomonospora cyanea NA-134T CM001440.1 GCF_000244975.1 Chromosome 5.41 69.7 1 5 5,086 5,408,301 1 Terrestrial Saccharomonospora glauca K62T CM001484.1 (chromosome), CM001485.1 (plasmid) GCF_000243395.3 Chromosome 4.56 69.1 2 11 4,269 4,538,746 1 Terrestrial Saccharomonospora halophila 8T AICX00000000.1 GCF_000383775.1 Scaffold 3.69 70.4 116 644 3,656 69,647 16 Moderately halophilic terrestrial Saccharomonospora iraqiensis subsp. iraqiensis IQ-H1T AICW00000000.1 GCF_000430445.1 Scaffold 3.90 71.0 139 732 4,014 87,719 16 Moderately halophilic terrestrial Saccharomonospora iraqiensis subsp. paurometabolica YIM 90007T AGIT00000000.2 GCF_000231035.3 Scaffold 4.67 71.3 82 1,031 4,537 171,692 9 Moderately halophilic terrestrial Saccharomonospora marina XMU15T CM001439.1 GCF_000244955.1 Chromosome 5.97 68.9 1 8 5,664 5,965,593 1 Marine/Lake Saccharomonospora piscinae KCTC 19743T VCEK00000000.1 GCF_005862235.1 Scaffold 4.90 71.0 11 21 4,508 1,086,926 3 Marine/Lake Saccharomonospora saliphila YIM 90502T AICY00000000.1 GCF_000383795.1 Scaffold 4.03 70.6 145 679 3,916 96,274 11 Moderately halophilic terrestrial Saccharomonospora viridis DSM 43017T CP001683.1 GCF_000023865.1 Complete 4.31 67.3 1 1 3,870 4,308,349 1 Clinical Saccharomonospora viridis JCM 3315 JRZE00000000.1 GCF_000787535.1 Contig 4.30 67.4 13 13 3,876 1,283,650 2 Clinical Saccharomonospora viridis ATCC 33517 FOWS00000000.1 GCF_900115515.1 Scaffold 4.31 67.4 12 17 3,879 1,283,650 2 Clinical Saccharomonospora xinjiangensis XJ-54T AICV00000000.1 GCF_000258175.1 Scaffold 4.78 68.9 2 16 4,366 4,773,543 1 Terrestrial Saccharomonospora sp. 31sw CP038101.1 GCF_004519465.1 Complete 4.71 69.1 1 1 4,350 4,713,652 1 Terrestrial Saccharomonospora sp. LRS4.154 MWIH00000000.1 GCF_002077655.1 Scaffold 4.86 71.0 13 17 4,568 731,563 3 Marine/Lake Saccharomonospora sp. CNQ-490 AZUM00000000.1 GCF_000527075.1 Contig 4.94 71.1 25 25 4,518 613,253 3 Marine/Lake Saccharomonospora sp. CUA-673 MKKE00000000.1 GCF_001942305.1 Contig 5.42 70.0 85 85 5,219 122,768 14 Marine/Lake 1NCBI BioProject ID. Frontiers in Microbiology | www.frontiersin.org 3March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 4 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora TABLE 2 | Grouping of Saccharomonospora strains under study according to their isolation source and NaCl requirements for growing. Strain Isolation source NaCl range (optimum),% (w/v) Group Saccharomonospora amisosensis DSM 45685TDeep marine sediment in Black Sea (Turkey) 0–10 Marine/Lake Saccharomonospora marina XMU15TOcean sediment of the East China Sea 0–5 (0–3) Saccharomonospora piscinae KCTC 19743TFishpond sediment in Taiwan 0–8 (5) Saccharomonospora sp. LRS4.154 Laguna del Rosario in Oaxaca (Mexico) 0–8 (5) Saccharomonospora sp. CNQ-490 Marine sediment in San Diego (United States) ∼2.5 Saccharomonospora sp. CUA-673 Marine sponge in San Diego (United States) ∼2.5 Saccharomonospora halophila 8TMarsh soil in Kuwait 10–30 (10) Moderately halophilic terrestrial Saccharomonospora iraqiensis subsp. iraqiensis IQ-H1TExtremely saline soil in Iraq 5–20 (10–15) Saccharomonospora iraqiensis subsp. paurometabolica YIM 90007T Soil sample from the Xinjiang Province (China) 5–20 (10) Saccharomonospora saliphila YIM 90502TMuddy soil Karnataka Province (India) 0–20 (10) Saccharomonospora azurea NA-128TSoil sample from Sichuan (China) ≤7 Terrestrial Saccharomonospora azurea SZMC 14600 Soil from China ≤7 Saccharomonospora cyanea NA-134TSoil samples from Sichuan (China) ≤10 Saccharomonospora glauca K62TMoldy hay, soil, compost, and manure from Germany ≤7 Saccharomonospora xinjiangensis XJ-54TSoil in Xinjiang (China) 0 Saccharomonospora sp. 31sw Soil from Iran 3 Saccharomonospora viridis DSM 43017TManure, compost, overheated fodder, soil, lake sediments, peat ≤3 Clinical Saccharomonospora viridis JCM 3315 Saccharomonospora viridis ATCC 33517 where branch confidence was evaluated using the Shimodaira- Hasegawa test (Shimodaira and Hasegawa, 1999). Comparative Genomic Analyses Measures of similarity between genome sequences were achieved by using different algorithms to calculate Overall Genome Relatedness Indexes (OGRI) values, i.e., Orthologous Average Nucleotide Identity (OrthoANI), estimated using the OrthoANI- usearch Tool (Yoon et al., 2017), digital DNA-DNA hybridization (dDDH), determined using the Genome-to-Genome Distance Calculator (GGDC) (formula 2) (Meier-Kolthoff et al., 2013), and Average Amino-acid Identity (AAI), calculated using AAI calculator (Rodriguez-R and Konstantinidis, 2016). Pan-genome analysis was carried out using the Enveomics tool (Rodriguez-R and Konstantinidis, 2016) to cluster CDSs in orthologous and singleton gene clusters, as indicated in section “Phylogenetic and Phylogenomic Analyses.” Pan-genome visualization was performed using Anvi’o (Eren et al., 2015). Flower plot displaying the core, accessory, and strain-specific genes was drawn in R using the ‘plotrix’ package. The characteristic curves showing the pan-genome and the coregenome evolution at the genus level were depicted using the Pan-Genome Profile Analyze Tool (PanGP) (Zhao et al., 2014) with distance guide (DG) sampling algorithm. Synteny among the genomes of strains of the genus Saccharomonospora was studied after rearranging the draft genome scaffolds to a related reference genome using the Mauve Contig Mover functionality (Rissman et al., 2009). Pairwise comparison between ordered genomes was achieved by Blastn search (e-value ≤10−3) and synteny plots were displayed using Easyfig v.2.2.3 (Sullivan et al., 2011). Pan- and core-genome calculations were performed with the Enveomics package (Rodriguez-R and Konstantinidis, 2016). Biosynthetic Gene Cluster (BGC) Analysis Location and identification of BGCs within genomes of Saccharomonospora was accomplished with the help of antiSMASH 5.0 web server (Blin et al., 2019), which uses Hidden Markov Models and rules based-detection to identify a broad array of BGCs, including those encoding PKS and NRPS. AntiSMASH detection strictness level was set to “relaxed.” In order to detect if the identified BGCs were enriched in the core- or accessory-genomes, we performed a nucleotide Blast search of the reverse translated protein pertaining to the core- and dispensable-genomes, respectively, against the BGCs from each of the analyzed genomes, and the corresponding Blast alignment length was used to calculate the fraction of BGCs spanned by core and accessory genes, respectively. Since large BGCs (such as PKS, NRPS and hybrid clusters) may be split across several scaffolds/contigs when analyzing incomplete genomes leading to miscalculation of the predicted number of BGCs by antiSMASH, we used the NaPDoS (Natural Product Domain Seeker) tool (Ziemert et al., 2012) to connect PKS, NRPS or hybrid clusters divided into several scaffolds/contigs. BGC domains harbor the genetic signature of their historical relative and thus scaffolds/contigs containing Frontiers in Microbiology | www.frontiersin.org 4March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 5 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora FIGURE 1 | Neighbor-joining phylogenetic tree based on the 16S rRNA gene sequence comparison of members of the genus Saccharomonospora and the most closely related genus Prauserella. Bootstrap values ≥70% (based on 1,000 pseudo-replicates) are shown above the branches. Strains of Saccharomonospora were colored according to the group they belong to (blue for marine/lake, orange for moderately halophilic terrestrial, green for terrestrial and purple for clinical). Filled circles indicate clusters that were also recovered using maximum-parsimony and maximum-likelihood algorithms. Nocardia brasiliensis DSM 43758Twas used as an outgroup. Bar, 0.01 changes per nucleotide position. pieces of one gene cluster are likely to phylogenetically clade together. Therefore, detection of PKS-derived ketosynthase domains (KS) and NRPS-derived condensation domains (C) with NaPDoS software, followed by alignment of the identified domain sequences with Muscle (Edgar, 2004) and phylogenetic reconstruction with Mega X software (Kumar et al., 2018) allow us to narrow down a more accurate number of PKS/NRPS/hybrid clusters present in fragmented next-generation sequencing assemblies. If a BGC was in the middle of a scaffold/contig (i.e., has sequence before and after the region antiSMASH identified), Frontiers in Microbiology | www.frontiersin.org 5March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 6 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora FIGURE 2 | Approximately maximum-likelihood phylogenomic tree based on the concatenation of the translated sequence of the 876 single-copy genes shared by the members of the genera Saccharomonospora and Prauserella under study. Bootstrap values ≥70% (based on Shimodaira-Hasegawa-like local support) are shown above the branches. Strains of Saccharomonospora were colored according to the group they belong to (blue for marine/lake, orange for moderately halophilic terrestrial, green for terrestrial and purple for clinical). Bar, 0.05 changes per nucleotide position. it is considered complete; otherwise it was marked as a partial cluster. If KS or C domains on different scaffolds/contigs were sister taxa in the domain-based trees (Supplementary Figure 1), the BGCs on the two or more scaffolds/contigs were considered part of one cluster and the corresponding scaffolds/contigs were joined together. The total length of the prospective BGC was also taken into consideration to determine the most probably number of PKS and NRPS clusters. For each genome, the sum of the lengths of all clusters (partial and complete) within a category (PKS or NRPS) was divided by the average length of all the complete clusters into this category. The resulting measure is the expected number of PKS or NRPS clusters based on an average length specific to each genome (Supplementary Table 1). These estimates support the joining of clusters using NaPDoS and domain-based phylogenetic trees (Supplementary Figure 1). Circular display of the corrected antiSMASH results was carried out using Circos Table Viewer v.0.63-9 visualization software (Krzywinski et al., 2009). In order to predict the association of the detected BGCs with the production of known or novel bioactive compounds, the PKS, NRPS and hybrid clusters matches localized with antiSMASH were further screened with Blast search within the MIBiG database (Kautsar et al., 2020). Phenotypic Characterization Comparative phenotypic features of strains S. piscinae KCTC 19743Tand Saccharomonospora sp. LRS4.154 were determined as described elsewhere (Tseng et al., 2018). RESULTS Saccharomonospora Strain Grouping A total of 19 genome sequences affiliated to members of the genus Saccharomonospora were retrieved from NCBI GenBank (18 genomes) and from JGI (1 genome) databases, 12 of which belong to type strains of species or subspecies within this genus, and the Frontiers in Microbiology | www.frontiersin.org 6March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 7 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora remaining seven were not affiliated to any particular species or subspecies (Table 1). The draft genome of Saccharomonospora iraqiensis subsp. iraqiensis IQ-H1Twas named as Actinopolyspora iraqinesis IQ-H1Tin GenBank database but it was also included in this study since both names are homotypic synonyms. Genome assembly varied between contig, scaffold, chromosome and complete genome level, with six out of the genomes assembled as a single scaffold or contig (Table 1). Saccharomonospora genomes have a size ranging from 3.69 Mb to 5.97 Mb, with a DNA G +C content of 67.3–71.3 mol% and contain between 3,656 and 5,664 protein-coding genes (Table 1). The recovered genomes were grouped into four different sets according to their isolation source and to their NaCl requirements for growing (Table 2): •Marine/lake: strains isolated from marine environments or lakes and with optimal growth at or lower than 5% (w/v) NaCl. •Moderately halophilic terrestrial: strains recovered from terrestrial hypersaline habitats and with optimal growth around 10% (w/v) NaCl. •Terrestrial: strains from soil samples and manure growing between 0 and 10% (w/v) NaCl. •Clinical: strains of the species S. viridis, the sole taxon in the genus associated to diseases. Taxophylogenomic Assessment The 16S rRNA gene sequence analysis was employed to infer the evolutionary relationships among the members of the currently described species of the genus Saccharomonospora, as well as other Saccharomonospora strains unassigned to any of the existing species (Figure 1). The closest related genus Prauserella was also included as a reference. The two genera were clearly separated according to this 16S rRNA gene-based phylogeny. All the unassigned Saccharomonospora strains were grouped into one of the described species of Saccharamonospora, with the exception of the strain Saccharomonospora sp. CUA-673, which clustered with the type strain of Prauserella rugosa and, therefore, seems to be misnamed. Sequence similarities for reference nontype or unnamed strains of Saccharomonospora with respect to the most closely related type strain were always above 99.5%, that is, beyond the threshold value for circumscribing prokaryotic species (98.65%) (Kim et al., 2014). Again, the only exception was Saccharomonospora sp. CUA-673, which shared less than 96.0% 16S rRNA gene sequence similarity with respect to the Saccharomonospora type strains but showed 98.7% sequence similarity to the type strain of Prauserella rugosa, indicating that it is closely related to that species. Therefore, no putative novel species of Saccharomonospora might be proposed after 16S rRNA gene sequence phylogenetic analysis. On the other hand, some type strains that clustered together based on 16S rRNA gene phylogeny showed a sequence similarity above the mentioned threshold value, particularly, S. amisosensis vs S. marina and the group constituted by S. iraqiensis subsp. iraqiensis,S. iraqiensis subsp. paurometabolica and S. halophila. So, according to the 16S rRNA gene sequence results, the species within each of FIGURE 3 | Heatmap of genome relatedness among members of the genus Saccharomonospora estimated by means of OrthoANI (A) and dDDH (B) values. those clusters might be merged into a single taxon, but a more confident evolutionary study is required to confirm the 16S rRNA gene-based hypothesis. Phylogenomic trees that more reliably infer the evolutionary relationships among taxa can be obtained using the genome sequence information. In this particular case, we employed 876 concatenated amino acid sequences of the orthologous single-copy genes present in all the genomes under study (Figure 2). Although the clusters obtained in both trees Frontiers in Microbiology | www.frontiersin.org 7March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 8 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora FIGURE 4 | Synteny plot among highly conserved (A) and partially conserved (B) genomes of Saccharomonospora. Only matches with ≥500 bp alignment length and ≥90% identity are shown. were mostly in agreement, the phylogenomic tree showed a branch support of 100% in all bifurcations. This tree also points to a clear separation between Saccharomonospora and Prauserella genera, with probably no cryptic species of Saccharomonospora and with the need of transfer the strain Saccharomonospora sp. CUA-673 to the genus Prauserella (most likely as a new species given the long branch between this strain and the type strain of Prauserella rugosa). Similar to the 16S rRNA gene tree, the phylogenomic tree shows evidence for merging the species S. amisosensis –S. marina, on the one hand, and the species S. iraqiensis subsp. iraqiensis – S. iraqiensis subsp. paurometabolica –S. halophila on the other hand. Finally, according to the phylogenomic study, the species Prauserella coralliicola and Prauserella endophytica clustered very closely and most probably they constitute a single species, but this proposal is beyond the scope of the present manuscript. We further analyzed the congruence between the clustering of Saccharomonospora strains in the phylogenetic/phylogenomic trees and the groups previously established based on the strain isolation source and NaCl requirements. Only clinical and moderately halophilic terrestrial isolates formed independent groups in the inferred phylogenies (Figures 1,2). In the case of the clinical strains clustering was expected since the three clinical strains belonged to the same species and, in fact, two of them, namely S. viridis ATCC 33517 and S. viridis JCM 3315, are equivalent strains with different culture collection number. More interesting seems the grouping of moderately halophilic strains under the same clade, which suggests an environmentdriven evolution of those strains to thrive in such extreme conditions. Although terrestrial strains were not clustered as a monophyletic branch according to the 16S rRNA gene phylogeny, they formed a monophyletic group in the phylogenomic tree (excepting the genome sequence of S. colocasiae), hinting at a common origin of those strains from soils, contaminants, and manure sources. Re-evaluation of the Species of Saccharomonospora Using Genome Sequence Distances Similarity among genome sequences can be estimated by means of OGRI (Chun and Rainey, 2014). Although there are many algorithms to calculate OGRI values, the two most widely used for taxonomic purposes at species level are OrthoANI (Lee et al., 2016) and dDDH (Meier-Kolthoff et al., 2013). Gold standard for prokaryotic species delineation is still the wet-lab DNA-DNA hybridization (DDH), a widely considered tedious, laborious and error-prone method (Rosselló-Mora, 2006). A DDH cutoff value to unequivocally discriminate if two microbial genomes should be considered as the same or different species has been established at 70% (Wayne et al., 1987;Stackebrandt and Goebel, 1994). Nevertheless, OrthoANI and dDDH have been proposed as surrogates for DDH (Meier-Kolthoff et al., 2013; Lee et al., 2016), with well accepted threshold values for species delineation of approximately 95% (Konstantinidis and Tiedje, 2005a;Goris et al., 2007;Richter and Rossello-Mora, 2009;Chun and Rainey, 2014) and 70% (Auch et al., 2010), respectively. With regard to genus delineation, the most used OGRI value is AAI (Konstantinidis and Tiedje, 2005b), with a cutoff value about 65% (Konstantinidis et al., 2017). OrthoANI and dDDH values were calculated for all pairs of Saccharomonospora genomes (Figure 3) and for the pair Saccharomonospora sp. CUA- 673 vs. Prauserella rugosa DSM 43194T(OrthoANI 84.2%, dDDH 27.8%). Additionally, AAI values between members of Saccharomonospora and Prauserella were calculated. As supported by phylogenetic/phylogenomic trees, AAI values indicated a good delineation of the genera Saccharomonospora Frontiers in Microbiology | www.frontiersin.org 8March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 9 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora FIGURE 5 | Comparative pangenome display of the 19 Saccharomonospora strains analyzed in this study. The inner layers represent individual genomes organized regarding their isolation source and their NaCl requirements for growing. In the layers, dark colors indicate the presence of a gene cluster and light color its absence. The core- (978 genes) and the accessory- (11,297 genes) genomes are indicated in purple and read, respectively, in the outmost layer. and Prauserella with only a small overlap. AAI values within the Saccharomonospora genomes (excluding that of strain CUA- 673) ranged from 71 to 100%, while values between the two genera varied from 67 to 76%. According to AAI values, strain CUA-673 was clearly a member of Prauserella, showing 66– 82% AAI values with members of this genus in comparison to 65-66% AAI values with member of Saccharomonospora. On the other hand, OrthoANI and dDDH values demonstrated that no putative new species exist among the studied genomes of Saccharomonospora besides the already mentioned strain Saccharomonospora sp. CUA-673, which should be renamed as Praseurella sp. CUA-673 and constitute a novel species within this genus that may be proposed after a detailed taxonomic polyphasic approach (Tindall et al., 2010). The reference non-type strains S. azurea SZMC 14600 and S. viridis ATCC 33517 (= JCM 3315) are properly named, according to the OGRI values obtained with respect to the type strains of the corresponding species. Furthermore, the strains Saccharomonospora sp. LRS4.154 and Saccharomonospora sp. CNQ-490 are clearly additional strains of S. piscinae and should be renamed accordingly. Similarly, Frontiers in Microbiology | www.frontiersin.org 9March 2021 | Volume 12 | Article 603791 fmicb-12-603791 March 7, 2021 Time: 16:50 # 16 Ramírez-Durán et al. Comparative Taxogenomics of the Genus Saccharomonospora CONCLUSION Genome-scale data of Saccharomonospora strains can be used to elucidate evolutionary relationships among microorganisms of this genus and to unequivocally assign strains into species. Based on the results of this manuscript we, hereby, propose the emended description of the species S. piscinae as indicated below. This genus has been revealed as an important source of a wide variety of biosynthetic gene clusters, which may be responsible for the production of novel non-yet-discovered bioactive molecules with potential application to biotechnology and biomedicine. Emended Description of Saccharomonospora piscinae Tseng et al. (2018) The description is as given before (Tseng et al., 2018), with the following amendment. The aerial mycelium is pale green to greenish gray or black. Oval spores have smooth or rugose surface. Olive green soluble pigments may be produced. Halotolerant or moderate halophile. Growth occurs between 0 to 20% (w/v) NaCl and 20 to 55◦C. Gelatin may be liquefied. Menaquinone MK-8(H2) may be present as minor component. DNA G +C content is 70.6–71.0 mol% (genome). Strains LRS4.154 (= CECT 9353 = DSM 105201) and CNQ- 490, isolated from saline soil of Laguna El Rosario, Oaxaca, Mexico, and from a deep-sea sediment sample 2 km west of the Scripps pier, La Jolla, CA, United States, respectively, are additional reference strains of this species. DATA AVAILABILITY STATEMENT The genome sequences analyzed in this study can be found in the GenBank and Joint Genome Institute databases under the accession numbers shown in Table 1. AUTHOR CONTRIBUTIONS NR-D, RH, BV-G, CS-P, HS-T, and AV did the conceptualization. NR-D and RH did the methodology, formal analysis, data curation, writing-original draft preparation, and visualization. BV-G, CS-P, and SA-C did the validation. NR-D, RH, and CS-P did the investigation. NR-D, RH, and AV did the resources. NR-D, RH, BV-G, CS-P, SA-C, HS-T, and AV did the writing – review and editing. HS-T and AV did the supervision. CS-P and AV did the project administration. NR-D, CS-P, and AV did the funding acquisition. All authors have read and agreed to the published version of the manuscript. FUNDING This research was funded by FEDER/Spanish Ministry of Science and Innovation-State Research Agency (project CGL2017-83385-P), the National Council of Science and Technology with a scholarship granted to N. Ramírez-Durán (application 2018-000007-01EXTV-00289) for a sabbatical stay at the University of Sevilla, the Secretary for Research and Advanced Studies of the Autonomous University of the State of Mexico (project 5009/2020CIB), and Junta de Andalucía (grants BIO-213 and US-1263771), Spain, which included FEDER funds. ACKNOWLEDGMENTS We wish to thank the reviewers for their generous and meaningful efforts. SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb. 2021.603791/full#supplementary-material REFERENCES Auch, A. F., von Jan, M., Klenk, H.-P., and Göker, M. (2010). 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