The Rare Actinobacterium Crossiella sp. Is a Potential Source of New Bioactive Compounds with Activity against Bacteria and Fungi

Citation: Gonzalez-Pimentel, J.L.; Dominguez-Moñino, I.; Jurado, V.; Laiz, L.; Caldeira, A.T.; Saiz-Jimenez, C. The Rare Actinobacterium Crossiella sp. Is a Potential Source of New Bioactive Compounds with Activity against Bacteria and Fungi. Microorganisms 2022,10, 1575. https://doi.org/10.3390/ microorganisms10081575 Academic Editor: Renmao Tian Received: 5 July 2022 Accepted: 3 August 2022 Published: 5 August 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). microorganisms Article The Rare Actinobacterium Crossiella sp. Is a Potential Source of New Bioactive Compounds with Activity against Bacteria and Fungi Jose Luis Gonzalez-Pimentel 1, Irene Dominguez-Moñino 2, Valme Jurado 2, Leonila Laiz 2, Ana Teresa Caldeira 1and Cesareo Saiz-Jimenez 2,* 1Laboratorio Hercules, Universidade de Evora, 7004-516 Evora, Portugal 2Instituto de Recursos Naturales y Agrobiologia, IRNAS-CSIC, 41012 Sevilla, Spain *Correspondence: [email protected] Abstract: Antimicrobial resistance has become a global problem in recent decades. A gradual reduction in drug discoveries has led to the current antimicrobial resistance crisis. Caves and other subsurface environments are underexplored thus far, and they represent indispensable ecological niches that could offer new molecules of interest to medicine and biotechnology. We explored Spanish show caves to test the bioactivity of the bacteria dwelling in the walls and ceilings, as well as airborne bacteria. We reported the isolation of two strains of the genus Crossiella, likely representing a new species, isolated from Altamira Cave, Spain. In vitro and in silico analyses showed the inhibition of pathogenic Gram-positive and Gram-negative bacteria, and fungi, as well as the taxonomical distance of both strains from their closest relative, Crossiella cryophila. The presence of an exclusive combination of gene clusters involved in the synthesis of lanthipeptides, lasso peptides, nonribosomal peptides and polyketides indicates that species of this genus could represent a source of new compounds. Overall, there is promising evidence for antimicrobial discovery in subterranean environments, which increases the possibility of identifying new bioactive molecules. Keywords: Altamira Cave; bioactive compounds; Crossiella; predicted gene clusters; Spanish show caves 1. Introduction Numerous papers have been published on the production of antimicrobial compounds (ACs) by different bacterial groups isolated from soils and aquatic environments. There is a long tradition of using soils for isolating AC-producing bacteria since the first works of Waksman and collaborators [ 1 ]. A decade later, research focused on marine organisms [ 2 ]. At present, a considerable number of ACs were identified from terrestrial and aquatic microorganisms [3–5]. In 2017, the World Health Organization published a list of 12 dangerous bacteria for which new antibiotics were urgently needed [ 6 ]. Of these bacteria, nine were Gramnegative, which indicates the necessity of using antibiotics against this type of bacteria. Tacconelli et al. [ 7 ] reported that in the last two decades, only two new antibiotic classes that are active against Gram-positive bacteria have been approved by the US Food and Drug Administration and European Medicines Agency. However, in the same period, no new antibiotics against Gram-negative bacteria have been approved, and quinolones, discovered in 1962, represented the last drug recognized to be active against Gram-negative bacteria. Therefore, the search of ACs active against Gram-negative bacteria should be enhanced. Based on the needs of the World Health Organization and the critical shortage of new antibiotics in development against multidrug-resistant bacteria, in the last few years, we have observed a growing interest in ACs produced by microorganisms thriving in caves. In fact, a number of papers have been published on the topic [ 8 – 12 ]. A vast majority of Microorganisms 2022,10, 1575. https://doi.org/10.3390/microorganisms10081575 https://www.mdpi.com/journal/microorganisms Microorganisms 2022,10, 1575 2 of 16 these reports were merely descriptive works on the isolation of selected cave strains that were screened for their antimicrobial properties by a spot-on lawn antimicrobial assay, and clearly more research on the nature of ACs is needed. Gohain et al. [ 13 ] published a list of actinobacterial species producing more than 60 different ACs, and Zada et al. [ 14 ] reported a list of 20 ACs produced by cave bacteria, from which 12 were excreted by species of Streptomyces, six by species of Paenibacillus and one each by Bacillus licheniformis and Nonomuraea specus. This result indicates the importance of Actinobacteria and Firmicutes as AC producers. The subsurface is a relatively less studied environment, and the exploration of caves as a source of ACs is relatively recent. More than 20 years ago, Groth et al. [ 15 ] reported that caves seemed to be a promising niche for finding actinomycetes producing novel ACs. This assumption was confirmed a few years later with the discovery of cervimycins, a polyketide glycoside complex produced by Streptomyces tendae, isolated from Grotta dei Cervi in Italy [16,17]. In general, most caves are unexplored or rarely visited by humans from which novel or rare taxa can be isolated [3]. This also extends to widely visited show caves [15,18]. As a country, Spain is rich in caves. Some cavities have a long tradition as show caves and attract a high number of visitors. In Andalusia, South Spain, 114 karstic caves and chasms were reported, and visits to caves represent a valuable economic factor for less favored areas. Cave tourism started as early as the first quarter of the 19th century in Ardales Cave [ 18 ]. Altamira Cave, the most famous Spanish cave, was discovered in 1868 and contains rock art attributed to the Upper Paleolithic Age. Early excavations at the beginning of the 20th century in Altamira, as well as further consolidation works due to the collapse of rock blocks from the ceiling, the installation of artificial lighting and massive numbers of visitors, altered the pristine ecosystem and biodeteriorated the paintings. In fact, up to 175,000 visitors were registered in 1973. As a result, the cave had to be closed in 1977, reopened in 1982 and closed again in 2002 due to the contamination of the Polychrome Hall and its paintings by phototrophic microorganisms (cyanobacteria and algae) [19]. Altamira and other Spanish caves were revealed as interesting niches for isolating and describing novel bacterial and fungal species [ 20 – 27 ]. These understudied microorganisms offer a wealth of potential for the discovery of new ACs. Microorganisms employ a variety of strategies to compete successfully against neighbors sharing their niche. The production of ACs, as secondary metabolites, is a common strategy in oligotrophic niches. The secondary metabolites are produced by biosynthetic gene clusters (BGCs). The major classes of ACs are the Non-Ribosomal Peptides (NRP) and Polyketides (PKS), which are synthesized by large multi-enzyme complexes of NRP synthetases (NRPS) and PKS synthases (PKSs). These two classes of BGCs encompass most known antibiotics and antifungals [28,29]. A way to counteract the lack of studies on novel ACs is to characterize the bacterial genome through gene prediction and functional annotations. This permits focusing on bacteria with gene clusters of interest. Here, we report data in favor of caves as environments of increasing interest in the search for bacterial ACs. 2. Materials and Methods 2.1. Sampling, Isolation, and Identification of Bacteria The samples of speleothems, microbial mats, biofilms and sediments were taken from different cave walls and ceilings from 1996 till 2020 (Figure 1). The description of the caves (geology, environmental parameters, geomicrobiology, etc.) are reported elsewhere [15,30–33] . These caves share unique environmental conditions (low and constant temperature, high relative humidity, input of organic carbon by dripping waters and visitors, etc.) which favor the development of complex microbial communities [ 15 , 19 , 30 , 31 ]. Microorganisms 2022,10, 1575 3 of 16 Microorganisms 2022, 10, x FOR PEER REVIEW 3 of 16 2. Materials and Methods 2.1. Sampling, Isolation, and Identification of Bacteria The samples of speleothems, microbial mats, biofilms and sediments were taken from different cave walls and ceilings from 1996 till 2020 (Figure 1). The description of the caves (geology, environmental parameters, geomicrobiology, etc.) are reported elsewhere [15,30–33]. These caves share unique environmental conditions (low and constant temperature, high relative humidity, input of organic carbon by dripping waters and visitors, etc.) which favor the development of complex microbial communities [15,19,30,31]. The samples were placed in sterile tubes and kept at 5 °C until arrival at the laboratory. Subsequently, they were immediately processed by suspension in saline solution and inoculation in different culture media to isolate both chemolithotrophic and heterotrophic bacteria, as reported by Groth et al. [15,16] and Jurado et al. [20–23]. The cultures were incubated at 28 °C for several weeks to allow the growth of slow-growing strains. Figure 1. Caves sampled in Spain in search of antimicrobial compounds (ACs). Seven caves from four Spanish regions were studied. The number of strains tested by region was represented in blue. Circles represent the tested bacteria (external circles) and AC-producing bacteria (internal circles). The air samples from the caves were collected using a high volume Surface Air System sampler (Duo SAS, model Super 360, International pBI, Milan, Italy). The samples were taken in duplicate, and the volume of filtered air was set at 100 L [32]. The culture medium was trypticase-soy-agar (TSA), and the plates were incubated at 28 °C. Morphologically different colonies were isolated in the TSA culture medium. Bacterial identification was carried out by sequencing the 16S ribosomal RNA (rRNA) gene [33]. The identification of phylogenetically related taxa was determined by the global alignment algorithm, using the EzBioCloud database [34]. The number of strains tested from each cave and the activity against pathogenic bacteria are shown in Figures S1 and S2 (Supplementary Materials). Figure 1. Caves sampled in Spain in search of antimicrobial compounds (ACs). Seven caves from four Spanish regions were studied. The number of strains tested by region was represented in blue. Circles represent the tested bacteria (external circles) and AC-producing bacteria (internal circles). The samples were placed in sterile tubes and kept at 5 ◦ C until arrival at the laboratory. Subsequently, they were immediately processed by suspension in saline solution and inoculation in different culture media to isolate both chemolithotrophic and heterotrophic bacteria, as reported by Groth et al. [ 15 , 16 ] and Jurado et al. [ 20 – 23 ]. The cultures were incubated at 28 ◦C for several weeks to allow the growth of slow-growing strains. The air samples from the caves were collected using a high volume Surface Air System sampler (Duo SAS, model Super 360, International pBI, Milan, Italy). The samples were taken in duplicate, and the volume of filtered air was set at 100 L [ 32 ]. The culture medium was trypticase-soy-agar (TSA), and the plates were incubated at 28 ◦ C. Morphologically different colonies were isolated in the TSA culture medium. Bacterial identification was carried out by sequencing the 16S ribosomal RNA (rRNA) gene [ 33 ]. The identification of phylogenetically related taxa was determined by the global alignment algorithm, using the EzBioCloud database [ 34 ]. The number of strains tested from each cave and the activity against pathogenic bacteria are shown in Figures S1 and S2 (Supplementary Materials). 2.2. Bacterial and Fungal Inhibition Assays Of all the bacteria isolated, two strains of Crossiella (Cross-1 and Cross-2) were selected for further analysis. The strains were cultured in flasks with 150 mL of nutrient broth with 2% of glycerol (v/v) at 30 ◦ C and 180 rpm. The implementation of glycerol as the carbon source promotes the synthesis of the antibiotics in actinomycetes [ 35 , 36 ]. After incubation, the cultures were filtered through a 0.22 µ m pore size nucleopore polycarbonate filter and the filtrates were tested for antibacterial activity. The pathogenic bacteria used in this test were Bacillus cereus CECT 148, Staphylococcus aureus CECT 4630, Escherichia coli DSM 105182, Pseudomonas aeruginosa CECT 110 and Acinetobacter baumannii DSM 30007. In addition, an environmental bacterium, Arthrobacter sp., was added to the test, due to Microorganisms 2022,10, 1575 4 of 16 its low antimicrobial resistance. The pathogenic bacterial suspensions were prepared in 0.9% (w/v) sterile saline solution and adjusted to 0.5 McFarland units using a densitometer DEN-1B (BioSan SIA, Riga, Latvia). An inhibitory assay was carried out in duplicate in a SPECTROstar Nano microplate device (BMG Labtech, Ortenberg, Germany). The microplates were subjected to orbital shaking at 500 rpm, at 30 ◦ C for 24 h and recorded every 30 min. The fungal growth inhibition assay was carried out on a solid culture of NA-Glycerol, a methodology similar to that used by Kerr [ 37 ]. The biomass of the strains Cross-1 and Cross-2 were spread over agar in a zigzag pattern and incubated at 30 ◦ C for 24 h before inoculation of the fungal species. Once the fungi were inoculated, the plates were incubated at 25 ◦ C for 28 days. The fungal species used in this trial were previously isolated from caves and include Aspergillus versicolor, Penicillium chrysogenum, Cladosporium cladosporioides, Fusarium solani and Ochroconis lascauxensis, some of them entomopathogens and others opportunistic pathogens [38,39]. 2.3. Genomic Analysis The DNA extracted for the whole genome shotgun was sequenced by Macrogen Inc. (Seoul, Korea) for both of the Illumina short-reads 150 PE, using a NovaSeq 6000 sequencer (Illumina, San Diego, CA, USA) and TruSeq DNA PCR-free for the library construction. De novo assembly was performed with SPAdes [ 40 ], using the raw reads. A pairwise genome comparison was carried out using the JSpeciesWS web tool [ 41 ]. Tetra correlation search (TCS) was deployed to look for the closest genomes, which were engaged along with both of the strains, Cross-1 and Cross-2, to calculate the Average Nucleotide Identity with BLAST (ANIb) and MUMmer (ANIm) algorithms. A phylogenomic approach was carried out through the alignment of 71 concatenated genes provided by the anvi’o platform [ 42 ]. A phylogenetic tree was reconstructed using the best substitution model predicted by MEGA XI [ 43 ]. The evolutionary history was deduced using the maximum-likelihood method and the general time-reversible model with discrete gamma distribution and invariant sites [ 44 ]. The nodes of the phylogenetic tree were well-supported with bootstrap values greater than 70. The functional characterization of the genes was obtained using Prokka version 1.14.6 [ 45 ] and antiSMASH 6.0 with strict mode and all of the extra features for the automated genome mining of secondary metabolism [ 46 ]. According to antiSMASH, the homology between sequences was fixed with a BLAST e-value below 1 × 10 −5 , with a 30% minimal sequence identity and a coverage above 25% of the sequence. The biosynthetic core genes from predicted gene clusters with antiSMASH were annotated with the UniProt database, using BLAST. The GenBank/EMBL/DDBJ accession numbers 16S rRNA gene sequences of the strains Cross-1 and Cross-2 were ON669108 and ON669109, respectively. The sequencing data generated in this study were deposited in the National Center for Biotechnology Information (NCBI), under the BioProject ID number PRJNA769239. The whole-genome shotgun project was deposited at DDBJ/ENA/GenBank under the accession numbers JALMDJ000000000 and JALMDK000000000, for the Crossiella sp. strains Cross-1 and Cross-2, respectively. 3. Results and Discussion 3.1. Caves as a Promising Source of Antimicrobial Compounds (ACs) We sampled karstic caves in the Iberian Peninsula as well as volcanic caves in the Canary Islands (Figure 1). The samples obtained from the rock surfaces and macroscopic biofilms colonizing the walls were inoculated on Petri plates with different culture media. In addition, the bacteria were collected from the air with a high-volume sampler [ 47 ]. These samplings composed a collection of more than one thousand bacteria to be tested. We used several hundreds of isolates from different caves (Figure 1) to test for the production of ACs in a recent screen carried out as part of a European project aiming to prospect subsurface environments for bioactive compounds with potential for use in Microorganisms 2022,10, 1575 5 of 16 medicine, agriculture and environment. The high number of AC-producing bacteria was noticeable, from not only the Altamira and Tito Bustillo caves, but also the volcanic caves located in the Canary Islands (Table 1). Other screened marine and terrestrial caves showed <1 to 7% AC-producing strains. It is worth noting that the bacteria collected from biofilms and/or rock surfaces showed higher bioactivity than those isolated from the air, which rarely reached 10% AC-producing strains. These data suggest an interest in exploring northern Spain and volcanic caves in search of ACs. Table 1. Cave bacteria producing antimicrobial compounds (AC) against pathogenic bacteria. Source Tested Strains AC Strains % Altamira Cave (rock) 289 77 26.6 Tito Bustillo Cave (rock) 181 42 23.2 Ardales Cave (air) 89 9 10.1 Maravillas Grotta (air) 200 14 7.0 Tesoro Cave (air) 89 4 4.5 Tesoro Cave (rock) 8 2 25.0 La Palma Island lava tubes (rock) 160 30 23.8 Viento Cave (Tenerife Island) (rock) 31 7 22.8 Total 1047 178 17.0 Total (rocks) 669 151 22.6 Total (air) 378 27 7.1 One factor that seems to be associated with the bioactivity of the isolated bacteria should be highlighted. The characteristics of the samples from which the bacteria were originally isolated determined their capacity to develop a dynamic secondary metabolism, as was the case for the bacteria isolated from the rock surfaces compared to the airborne bacteria, independent of the number of tested bacteria (Figure S1, Supplementary Materials ). Although most of the bioactive bacteria were mainly grouped into the phyla Actinobacteria, Firmicutes and Proteobacteria, the strains isolated from rock surfaces and air had different abilities to inhibit the growth of pathogens, suggesting that the biosynthesis of antimicrobials is a fundamental mechanism for cave wall colonization, along with other mechanisms of adaptation to those extreme environments. 3.2. The Case of Altamira Cave A few authors hypothesized that cave oligotrophy enhanced the competition among the bacteria, as well as the synthesis of the ACs that inhibit the growth of other microorganisms [ 13 , 48 ]. This may not be the case in Altamira Cave. The cave, in addition to the massive numbers of visitors and the input of organic carbon from those visitors over 150 years, was also contaminated with drip waters containing dissolved organic matter from cattle dung from livestock just above the cave. Cuezva et al. [ 19 ] reported that although the cattle activities were discontinued in 1998, organic matter and humus from manure produced over decades entered the cave in the drip waters and sustained microorganisms. The most intriguing finding was the absence of fungi on the walls and sediments in the highly anthropized Altamira Cave, as determined by the failure to amplify fungal DNA from the wall samples [ 49 ], despite the high concentration of fungal spores measured in the air, which amounted up to 390 CFU/m 3 in the Polychrome Hall [ 50 ]. This lack of fungal colonization was attributed to the Actinobacteria thriving on the walls, such as Actinomadura, Amycolatopsis, Nocardia, Micromonospora, Rhodococcus and Streptomyces [ 15 , 31 ], that produced ACs with antifungal properties. Most of these bacteria were isolated from white colonies distributed all around the cave (Figure S3, Supplementary Materials). Bérdy [ 51 ] listed the number of species of Actinobacteria producing ACs, which amounted to more than 11,100 and were mainly represented by Actinomadura (345), Amycolatopsis (120), Nocardia (357), Micromonospora (740), Rhodococcus (13) and Streptomyces Microorganisms 2022,10, 1575 6 of 16 (~8000). Most of these genera were observed in Altamira Cave, as well as other species of the genera Bacillus, Myxococcus, Pseudomonas and Stenotrophomonas, that produce ACs with antifungal properties [ 15 , 31 ]. Therefore, the absence of fungi on the Altamira Cave walls was not surprising, and the conclusion was that the original cave microbiome protected the walls from secondary colonizations. 3.3. Isolation of Crossiella Strains The microbiological studies carried out between 1996 and 2012 in Altamira Cave yielded a wide collection of bacteria that were preserved in a lab collection and kept at −80 ◦C in a freezer [ 15 , 31 , 50 ]. The survey and screening of this collection yielded an abundance of Streptomyces (S. lunaelactis, S. avidinii, S. xanthophaeus, S. xanthochromogenes, S. nojiriensis, etc.) which predominates over other Actinobacteria genera (Allokutzneria, Micromonospora, Knoellia, Rhodococcus, Crossiella, Kocuria, Kribbella, Nocardiopsis, Microbacterium, etc.). Of all of the isolated bacteria, a total of 12 strains identified as Crossiella sp., with two different morphologies, stand out (Figure S4, Supplementary Materials). These strains, that inhibit the growth of pathogens, were isolated exclusively from the walls of Altamira Cave and were selected for further studies. 3.4. In Vitro Analyses for Inhibition of Pathogenic Microorganisms In vitro analyses were carried out with the two Crossiella strains to identify the distinctive features related to the inhibition of pathogenic bacteria and fungi. Both of the strains were able to inhibit the pathogens Bacillus cereus, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa and Acinetobacter baumannii, as well as the fungi Aspergillus versicolor, Penicillium chrysogenum, Cladosporium cladosporioides, Fusarium solani and Ochroconis lascauxensis, isolated from the caves [ 38 , 39 , 52 ]. To evaluate the ability of the Crossiella strains to inhibit pathogenic bacteria, an assay was performed using the filtrate with seven days of incubation. In this case, both of the strains completely inhibited the growth of the pathogens, whereas a bacteriostatic effect was observed when the filtrate was diluted to half with the culture medium (Figure 2). The growth inhibition in fungi was absolutely effective for all of the strains tested, except for Fusarium solani, for which the inhibition was minimal with respect to the rest of the fungal strains (Figure 3). There are only two described species within the genus Crossiella,C. equi and C. cryophila. The first one was originally isolated from equine placentas [ 53 ], and it was associated with infectious diseases and disorders in horses [ 54 ], but no bioactive compound has been described thus far. Crossiella cryophila, originally described and validly published by Labeda and Lechevalier [ 55 ], within the genus Saccharothrix, was accommodated to the new genus Crossiella as the type species of this group [ 56 ]. Crossiella cryophila synthesizes dopsisamine, a broad spectrum antibiotic [ 57 ]. However, this antimicrobial compound does not affect Serratia or Pseudomonas. 3.5. In Silico Analyses for the Identification of Biosynthetic Gene Clusters 3.5.1. Phylogenomics In silico analyses were performed to find the similarities and dissimilarities with the closest relatives of Crossiella. The assembly of the raw data from the sequenced genomic DNA resulted in 10,680,392 bp and 10,681,678 bp genomes and 45 and 43 contigs, for Cross-1 and Cross-2, respectively. Both of the genomes presented the same GC content of 70.4%. The phylogenetic tree showed that the closest relative was C. cryophila, forming, along with C. equi, a separated branch from the species belonging to the family Pseudonocardiaceae (Figure 4). A pairwise genome comparison, using the Jspecies web tool, showed values for ANIb and ANIm above 99.99%, indicating that these two strains belong to the same species of bacterium. However, values below 95% were found for the closest relatives, C. cryophila and C. equi, and suggested that the studied strains could represent a new species within the genus Crossiella. Microorganisms 2022,10, 1575 7 of 16 Microorganisms 2022, 10, x FOR PEER REVIEW 7 of 16 dopsisamine, a broad spectrum antibiotic [57]. However, this antimicrobial compound does not affect Serratia or Pseudomonas. Figure 2. Microplate growth inhibition assay of bacterial pathogens. Pathogen inhibition tests using the filtrate of both Crossiella strains (A); diluted Cross-1 mixture (50% filtrate + 50% culture medium) (B); diluted Cross-2 mixture (50% filtrate + 50% culture medium) (C). Charts represent the growth curve of pathogens after 24 h of incubation at 30 °C (B. cereus, S. aureus, E. coli, P. aeruginosa, A. baumannii and Arthrobacter sp.) and pathogen inhibition when filtrates from Crossiella strains were used (Cross—B. cereus; Cross—S. aureus; Cross—E. coli; Cross—P. aeruginosa; Cross—A. baumannii; Cross—Arthrobacter sp.). Figure 2. Microplate growth inhibition assay of bacterial pathogens. Pathogen inhibition tests using the filtrate of both Crossiella strains ( A ); diluted Cross-1 mixture (50% filtrate + 50% culture medium) ( B ); diluted Cross-2 mixture (50% filtrate + 50% culture medium) ( C ). Charts represent the growth curve of pathogens after 24 h of incubation at 30 ◦ C (B. cereus, S. aureus, E. coli, P. aeruginosa, A. baumannii and Arthrobacter sp.) and pathogen inhibition when filtrates from Crossiella strains were used (Cross—B. cereus; Cross—S. aureus; Cross—E. coli; Cross—P. aeruginosa; Cross—A. baumannii; Cross—Arthrobacter sp.). Microorganisms 2022,10, 1575 8 of 16 Microorganisms 2022, 10, x FOR PEER REVIEW 8 of 16 Figure 3. Fungal inhibition assay after 28 days of incubation. The bioactivity of strains Cross-1 (left column) and Cross-2 (center column) were evaluated in comparison with the normal growth of fungus (right column). Bacteria were cultured 24 h before the inoculation of fungal strains. The fungi were picked with a wood-stick and positioned separately in four external points of the plate and between the traced bacteria. Figure 3. Fungal inhibition assay after 28 days of incubation. The bioactivity of strains Cross-1 ( left column) and Cross-2 ( center column) were evaluated in comparison with the normal growth of fungus ( right column). Bacteria were cultured 24 h before the inoculation of fungal strains. The fungi were picked with a wood-stick and positioned separately in four external points of the plate and between the traced bacteria. Microorganisms 2022,10, 1575 9 of 16 Microorganisms 2022, 10, x FOR PEER REVIEW 9 of 16 3.5. In Silico Analyses for the Identification of Biosynthetic Gene Clusters 3.5.1. Phylogenomics In silico analyses were performed to find the similarities and dissimilarities with the closest relatives of Crossiella. The assembly of the raw data from the sequenced genomic DNA resulted in 10,680,392 bp and 10,681,678 bp genomes and 45 and 43 contigs, for Cross-1 and Cross-2, respectively. Both of the genomes presented the same GC content of 70.4%. The phylogenetic tree showed that the closest relative was C. cryophila, forming, along with C. equi, a separated branch from the species belonging to the family Pseudonocardiaceae (Figure 4). A pairwise genome comparison, using the Jspecies web tool, showed values for ANIb and ANIm above 99.99%, indicating that these two strains belong to the same species of bacterium. However, values below 95% were found for the closest relatives, C. cryophila and C. equi, and suggested that the studied strains could represent a new species within the genus Crossiella. Figure 4. Maximum-likelihood phylogenetic tree based on 71 single-genes sequences showing the relationship of strains Cross-1 and Cross-2 with related species belonging to the family Pseudonocardiaceae. The bootstrap consensus tree inferred from 1000 replicates is taken to represent the evolutionary history of the taxa analyzed. There were a total of 45,445 positions in the final dataset. The genome of Nocardia asteroides ATCC 19247 T was used as outgroup. Bar, 0.05 substitutions per nucleotide position. Figure 4. Maximum-likelihood phylogenetic tree based on 71 single-genes sequences showing the relationship of strains Cross-1 and Cross-2 with related species belonging to the family Pseudonocardiaceae. The bootstrap consensus tree inferred from 1000 replicates is taken to represent the evolutionary history of the taxa analyzed. There were a total of 45,445 positions in the final dataset. The genome of Nocardia asteroides ATCC 19247 T was used as outgroup. Bar, 0.05 substitutions per nucleotide position. 3.5.2. Functional Annotations To characterize the genome through the functional enrichment of the predicted genes, two strategies were carried out to compare the presence/absence of genes in the four bacteria, Cross-1, Cross-2, C. cryophila and C. equi. The prediction and functional annotations of genes were implemented using prokka, and the antiSMASH web tool was used to predict the clusters involved in the secondary metabolism. The gene prediction resulted in a higher number of features in Cross-2, with 9465 genes , in contrast to C. equi, with 8329 genes. A total of 9459 genes were predicted for Cross-1, and 8647 genes were predicted for C. cryophila. Likewise, Cross-2 presented a higher number of gene clusters involved in the production of secondary metabolites, with 50 predicted gene clusters, although eight of them were on the edge or in unfinished regions, due to the fragmented draft genome. Cross-1 presented 49 clusters, seven of which were partially defined. Despite this variation between these two strains, Cross-1 and Cross-2 showed similar types and numbers of features involved in secondary metabolism. 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