Introduction
The Cuatro Ciénegas Valley (CCB), located in the Chihuahuan Desert in the state of Coahuila, Mexico, is surrounded by mountain ranges. Geological data suggest that after the fragmentation of Pangaea and the formation of the first seas, the CCB area was in a shallow marine environment, and at the end of the Eocene it was isolated from the rest of the Gulf of Mexico by tectonic plate movements (Moreno-Letelier et al., 2012). The CCB climate has remained stable for millions of years because it is surrounded by mountain ranges (Wilson & Pitts, 2010). It has a complex system of pools, wetlands, springs, and dunes. Its soils are calcareous and contain a large amount of calcium and magnesium, as well as sodium, potassium, sulfates and carbonates (Souza et al., 2006).
The isolation and relative stability of the CCB, together with its extreme conditions of aridity, humidity and salinity, as well as the presence of gypsiferous soils, have probably been the main drivers of the observed speciation and diversification (Moreno-Letelier et al., 2012). The CCB exhibits a high level of diversity and endemism of microbial species with ancient marine ancestry (Souza et al., 2012), as well as an abundant aquatic fauna in its springs (Tobler & Carson, 2010), whose genomes contain unique adaptive elements that allow them to survive in such an extreme environment (Alcaraz et al., 2008). One notable aspect is the stoichiometric imbalance, where extremely low concentrations of phosphorus (157:1) or nitrogen (1.8:1) allow the development of ancestral microbial communities with unique adaptations (Souza et al., 2008).
The growing interest in studying the CCB is due, in part, to the properties of its water and its arid, gypsiferous soils, which have led it to being compared to a crater on Mars (López-Lozano et al., 2012); therefore, the valley has been considered a model for the search for life on the red planet (Souza et al., 2004). In recent decades, numerous bacterial communities have been isolated and identified in the CCB (Escalante et al., 2008), thanks to researchers who see it as an “astrobiological time machine,” ideal for studying the evolution of biological communities on Earth (Moreno-Letelier et al., 2012). The native bacterial community is dominated by the phylum Pseudomonadota (formerly Proteobacteria), followed in abundance by Bacteroidota (formerly Bacteroidetes) and Actinomycetota (formerly Actinobacteria) (Cerritos et al., 2011; Escalante et al., 2008; Souza et al., 2006).
Since most microorganisms present in the CCB have evolved in situ under restricted nutritional conditions, in highly saline media or in the presence of heavy metals, their adaptability mechanisms have been enhanced. Evolutionary adaptations of microorganisms sometimes lead to opportunities for other organisms. Several bacterial species isolated from the CCB have been reported to synthesize secondary metabolites with potential biotechnological applications (Arocha-Garza et al., 2017; Ramos-Aboites et al., 2018) in different economic sectors such as medicine, industry, or agriculture.
Molecular identification techniques have become an indispensable tool in the study and classification of microorganisms. Sequencing of the 16S rDNA gene for bacterial identification is one of the most widely used methods, and can be complemented by biochemical, proteomic, or molecular methods depending on the specificity required for each study (Bou et al., 2011).
Currently, it is possible to direct the search towards microorganisms of interest, since the decrease in sequencing costs opens a window of opportunity for the search and development of natural products from native microbiota, with potential applications in different areas (Katz & Baltz, 2016). Considering the above, this research aimed to investigate the biotechnological potential of bacteria isolated from the CCB, as well as to establish the phylogenetic relationship among them.
Materials and methods
Sampling sites
Three samplings were conducted in five waterbodies (Poza Azul, Poza de la Becerra, Laguna los Güeros, Laguna Churince [LCH] and Poza Hundidos) and in the area known as “gypsum dunes” (Figure 1): 1) winter 2015-2016, 2) spring 2016 and 3) spring 2018. Once collected, the water, soil, and sediment samples were placed in new, sterile Falcon tubes and transported under refrigeration conditions (4-6 °C) to the analytical facility (Molecular Microbiology Laboratory at the Faculty of Chemical Sciences, Universidad Autónoma de Coahuila, Saltillo unit). In 2018, samples were only taken from two sites due to lack of access, and in the case of the Churince hydrological system, it had already disappeared. Data on the collection sites are presented in Table 1.

Table 1.
| Sampling site | Coordinates | pH | Temperature (°C) |
|---|---|---|---|
| First sampling (winter 2015-2016) | |||
| Poza Azul | 26.59312, -102.07192 | 7.08 | 32-38 |
| Poza de La Becerra | 26.878447, -102.138208 | 7.36 | 32.6 |
| Laguna Los Güeros | 26.840, -102.134 | 8.23 | 21.8 |
| Laguna Churince | 26.840127, -102.133946 | 7.5 | 26.5 |
| Dunas | 26.8, -102.12 | -- | 24-27 |
| Second sampling (spring 2016) | |||
| Poza Azul | 26.992, -102.122 | 7.08 | 32-38 |
| Poza de La Becerra | 26.878447, -102.138208 | 7.36 | 32.6 |
| Laguna Los Güeros | 26.840, -102.134 | 8.23 | 21.8 |
| Laguna Churince | 26.840127, -102.133946 | 7.5 | 26.5 |
| Dunas | 26.8, -102.12 | -- | 24-27 |
| Third sampling (spring 2018) | |||
| Poza Azul | 26.59312, -102.07192 | 7.2 | 33 |
| Poza Hundidos | 26.8703, -102.0206 | 8.4 | 29.1 |
Inoculation of microbial cultures
Soil, water, and sediment samples were subjected to serial dilutions to obtain isolated colonies, which were reseeded until pure cultures were obtained. The culture media used were SCN-1 and SCN-25 (with a NaCl ratio of 25:1 with respect to SCN-1 medium) (Küster & Williams, 1964), LB Miller broth (Walczak et al., 2012) supplemented with As2O3 at a final concentration of 1 mM and LB Miller supplemented with Na3AsO3 at a final concentration of 1 mM. Incubation was carried out at 30 °C, both in plates and liquid cultures with shaking at 200 rpm, until growth was observed.
Deoxyribonucleic acid (DNA) extraction
Bacterial genomic DNA was purified following the Wizard® kit protocol (Promega, USA). The quality of DNA purification was verified by 1 % agarose gel electrophoresis in 1x TBE buffer. Gels were stained with GelRed™ Nucleic Acid (Biotium, Inc.) for visualization on a transilluminator (UUV-01, Maestrogen, Mexico). The molecular weight marker HyperLadder™ I (Bioline) was used as a reference standard.
16S rDNA gene amplification
The 16S rDNA gene was amplified by polymerase chain reaction (PCR) in a thermal cycler (2720 Thermal Cycler, Applied Biosystems®, USA) using primers 8F (Brosius et al., 1981) and 1495R (Bianciotto et al., 1996) at a final concentration of 0.5 µM, 1 U MyTaq™ DNA polymerase (Bioline, USA), 1x MyTaq™ reaction buffer and 50 µL molecular grade water. Reaction conditions consisted of an initial denaturation cycle at 94 °C for 5 min, 25 amplification cycles at 94 °C for 60 s, 55 °C for 30 s, 72 °C for 90 s, and a final elongation at 72 °C for 10 min.
PCR products (amplicons) were confirmed by 1x agarose gel electrophoresis. For visualization, they were stained with GelRed® (Biotium, Inc.).
Purification of PCR products
Amplicon purification was performed using the E.Z.N.A.® kit (OMEGA Bio-tek, USA), following the manufacturer's instructions. The purified PCR products were visualized on a 1 % agarose gel using the same procedure described above.
Sequence analysis
The 16S rDNA gene amplicon of each bacterium was sequenced by Macrogen, Korea. For sequencing, primers 27F and 1492R (Caporaso et al., 2010) were used at a final concentration of 5 µM. The quality of the obtained sequences was analyzed with the BioEdit Sequence Alignment Editor© program (Hall, 1999). The sequences were curated and compared with sequences reported in the GenBank database (http://www.ncbi.nlm.nih.gov/BLAST/) using the BLAST+ 2.15.0 algorithm for identification. Sixty-five sequences with about 1400 base pairs of the 16S rDNA gene and the quality required for analysis were obtained.
Phylogenetic tree construction
A phylogenetic tree was constructed to determine the distance between bacterial isolates using the MEGA-X program (Kumar et al., 2018). The 16S rDNA gene sequences were aligned using the MUSCLE tool (Edgar, 2004). After alignment and trimming, the optimal evolutionary model was calculated using the MEGA-X program and jModelTest. The phylogenetic tree was generated with the Maximum-likelihood (ML) GTR I+ G method using the MEGA-X program with 1,000 replicates.
Results and discussion
Molecular identification
A total of 65 results were obtained, of which five strains were identified at family level, 37 at genus level and 23 at species level, with 99 to 100 % identity. According to the NCBI database, most of the identified strains were found to belong to the genus Bacillus (39.92 %) (Figure 2).

Of the bacteria identified, 39 belong to the phylum Bacillota (formerly Firmicutes), a group widely distributed in the valley (Cerritos et al., 2011; Moreno-Letelier et al., 2012). The genus Bacillus includes bacteria that have adaptive advantages, such as endospore formation, adaptation to sudden temperature changes, motility, halotolerance, and peptide synthesis, among others (Avalos-Zavaleta et al., 2018).
Phylogeny
Of the 39 strains belonging to the phylum Bacillota, 34 are from the family Bacillaceae: 24 from the genus Bacillus, two from the genus Lysinibacillus, two from the genus Exiguobacterium, one from the genus Priestia, one Peribacillus, one Rossellomorea, and one from the genus Cytobacillus. Some bacteria of the last four genera had been identified as Bacillus; however, recent studies have reclassified them. Two strains belonging to the family Planococcaceae and three from the family Paenibacillaceae were also identified.
From the phylum Actinomycetota, 12 strains were identified: one from the genus Nocardioides, one from the genus Gordonia, and 10 from the family Micrococcaceae (five belong to the genus Micrococcus, three to the genus Kocuria, one to the genus Citricoccus, and one strain could not be identified to the genus level).
Fourteen strains were identified from the phylum Pseudomonadota, four of which belong to the α-Proteobacteria class, in particular to the genera Peteryoungia, Pseudochrobactrum, Pannonibacter, and Sphingopyxis. The remaining 10 strains are part of the γ-Proteobacteria class: five belong to the genus Pseudomonas, two to the genus Stutzerimonas, one to the genus Billgrantia, and one to the genus Stenotrophomonas. Some of these genera were also recently reclassified.
The diversity of CCB bacterial species is a product of very ancient lineages that became isolated and continued to evolve (Arocha-Garza et al., 2017; Moreno-Letelier et al., 2012; Souza et al., 2006). Through their genome, it is possible to identify how and when the basin became isolated, the stability of environmental conditions over time, and how species have adapted to survive extreme conditions.
Biotechnological potential
The applications of microbiota are very diverse, and the bacteria identified in this study have potential biotechnological uses in agricultural, industrial and health sectors (Table 2). The studies found correspond to strains isolated in various parts of the world, some under salinity or temperature conditions similar to those reported in the present work. It is worth mentioning that different strains of the same species can present different activities, which has an impact on their possible applications.
Table 2.
| Isolates | Identification | Background | References |
|---|---|---|---|
| UADEC2CC107 | Siderophore production and auxin synthesis. Potential in phytoremediation. Improves heavy metal accumulation. |
Navarro-Torre et al. (2021) | |
| UADEC32 | Absorption or removal of Hg II, As III, As V and Cd pollutants in soil. Production of alkaline proteases. |
Abu-Dieyeh et al.
(2019), Hare & Chowdhary (2019), Saggu & Mishra (2017), Yakoubi et al. (2018) |
|
| UADEC2CC3 | N fixation and P solubilization. Sulfate and sulfonate assimilation and transport. Synthesis of siderophores, IAA, VOCs. Activity against phytopathogens, nematicidal activity against |
El-Komy (2005),
López-Bucio et al. (2007), Nascimiento et al. (2020), Ortíz-Castro et al. (2008), Vary et al. (2007), Velineni & Brahmaprakash (2011), Wang et al. (2020) |
|
| UADEC5 | Production of cellulase and xylanase enzymes. IAA production, phosphate solubilization. Nematicidal activity against |
Ali et al. (2015), Boucherba et al. (2017), Indira & Jayabalan, (2020), Liu et al. (2020) |
|
| UADEC1CC17 | Production of enzymes, xylanase, chitinase. Antifungal activity against |
Freitas-Silva et al.
(2021), Huang et al. (2012), Nagar et al. (2010), Reiss et al. (2011), Rishad et al. (2017) |
|
| UADEC27 | Bioremediation of agricultural soils polluted with chlorsulfuron, trifluralin, heavy metals and hydrocarbons. Wastewater treatment. Produces siderophores, solubilizes phosphates, secretes IAA and VOCs and is a biocontrol agent. Antagonistic activity against |
Al-Sman et al. (2019),
Erguven et al. (2016), Erturk et al. (2012), Hassen et al. (2010), Mani et al. (2016), Miao et al. (2018), Ortakaya et al. (2017), Schwartz et al. (2013) |
|
| UADEC38 | Production of gibberellin, auxin, expansin and cytokinin. Increased Fe solubilization. Production of lipopeptides and β1,3-glucanase. Activity against sp., sp. and keratinase. Bioremediation of soils polluted with pesticides, heavy metals and hydrocarbons. |
Anjum et al. (2019),
de Andrade et al. (2019), Lin et al. (2016), Milijašević-Marčić et al. (2017), Rahimi et al. (2018), Reddy et al. (2017), Regmi et al. (2017), Sajitha et al. (2018), Suryawanshi et al. (2018), Tahir et al. (2017), Tumpa et al. (2017), Zhou et al. (2018) |
|
| UADEC28 | Use of hydrocarbons as a carbon source. | Al-Awadhi et al. (2012) | |
| UADEC2CC38 | Decontamination of effluents contaminated with Cr III and Cr VI. Obtaining of antimicrobial extract. |
Mohapatra et al.
(2017), Singh et al. (2019) |
|
| UADEC2CC8 | Antibacterial activity against polluted with petroleum and its byproducts. |
Erofeevskaia et al.
(2016), Shanthakumar et al. (2015) |
|
| UADEC2CC12 | Bioremediation of effluents contaminated with naphthalene. |
Yetti & Thonotowai, (2016) | |
| UADEC1CC14 | Bioremediation by enzymatic action of azoreductase and NADH-DCIP reductase. Production of the exopolysaccharide kocuran with potential in the pharmaceutical industry. Bioremediation and production of biosurfactants. |
Karnwal (2017),
Kumar & Sujitha (2014), Parshetti et al. (2010), Wu et al. (2014) |
|
| UADEC1CC8, UADEC2CC228 | Synthesis of the peptide kocurin with proven antibacterial activity against pathogenic bacteria. Bioremediation of As III, As V, TNT, and accumulation of Cs137 and Co60. Degradation of 2,4,6-trichlorophenol and hydrocarbons. |
Al-Awadhi et al.
(2012), Banerjee et al. (2016), Caliz et al. (2011), Lara-Severino et al. (2016), Martín et al. (2013), Tišáková et al. (2013), Zacaria-Vital et al. (2019) |
|
| UADEC49 | PHB synthesis. Cr VI accumulation and removal. |
Long et al. (2013),
Sharma & Harish, (2015) |
|
| UADEC35 | Bioremediation of wastewater and soils polluted with Cr VI. Ammonium and nitrite removal. Synthesis of siderophores, and IAA. Phosphate solubilization and synthesis of biopolymers. |
Bai et al. (2019),
Chai et al.
(2019), Liao et al. (2020), Ray et al. (2016), Wang et al. (2013), Xu et al. (2012) |
|
| UADEC2CC7, UADEC2CC17 | Production of nocardamine, an Fe-transporting agent. N fixation, phosphate solubilization. Bioremediation of wastewater and soils polluted with selenite, selenate and Cr VI. Degradation of 2-nitrobrombenzene. |
Pham et al. (2017),
Sathishkumar et al. (2017), Wang et al. (2019), Yan et al. (2008), Zhang et al. (2011) |
|
| UADEC1CC9, UADEC2CC24 | Degradation of organophosphorus insecticides and their derivatives. P solubilization, N fixation and IAA production. |
Dellai et al. (2016),
Mahiudddin et al. (2014), Tang et al. (2018), Verma et al. (2015), Yadav et al. (2018) |
|
| UADEC1CC312 | Production of iturinic lipopeptides.
Production of biosurfactants with potential in bioremediation of hydrocarbon-polluted soils. Production of alkaline protease with application in detergents. |
Dunlap et al. (2019),
Elhamdi et al. (2023), Goma-Tchimbakal et al. (2022) |
It has been suggested that Bacillota and Pseudomonadota tend to exhibit greater production of secondary metabolites due to their genome size (Baltz, 2017). Likewise, it is suggested that places with unusual conditions (such as the CCB) and little explored are an important source of microorganisms capable of synthesizing bioactive molecules of interest (Arocha-Garza et al., 2017).
Phylum Bacillota
In recent studies, bacteria with potential applications in biotechnology have been isolated from the CCB. Zarza et al. (2018) detected the presence of genes related to the antagonism of species with which they cohabit on two Bacillus strains by analyzing its complete genome sequence. Moreover, Freitas-Silva et al. (2021) reported a strain of the species Bacillus pumilus with antibacterial activity, and Verdín-García et al. (2018) described the ability of several bacterial isolates (from the LCH) to degrade hemicellulose.
Phylum Actinomycetota
The phylum Actinomycetota has been widely studied in the CCB, highlighting the cytotoxic and antagonistic effect of several species isolated from the LCH, with potential pharmaceutical applications (Arocha-Garza et al., 2017). In addition, isolates have been identified that present characteristic mechanisms of BPCV, such as phosphate solubilization, nitrogen fixation, siderophore production, and indoleacetic acid (IAA) production, as well as cellulase production, which gives them high biotechnological potential in the industry (Cruz-Morales et al., 2017; Escudero-Agudelo et al., 2023; Ramos-Aboites et al., 2018). The ability of several strains to synthesize or transport siderophores has been reported. These strains were isolated from various iron-deficient CCB sites, and belong to the genera Kocuria, Streptomyces, Nocardia and Lentza (Cruz-Morales et al., 2017; Ramos-Aboites et al., 2018). In another study, 156 Actinomycetota strains with cellulolytic capacity were identified, all isolated from pools in the CCB; among these, 12 showed significantly high hydrolysis values (Escudero-Agudelo et al., 2023).
Phylum Pseudomonadota
In another study, methylotrophic strains of the phylum Pseudomonadota were isolated and identified, the study of which could contribute to our understanding of the carbon cycle in the CCB (Valdivia-Anistro et al., 2022). In addition, several species of the genus Pseudomonas have been isolated, including a strain producing a new biosurfactant and others that synthesize non-ribosomal cyclodipeptides and the antibiotic 2,4-diacetylphloroglucinol, both involved in the competitive mechanisms of growth inhibition of other bacterial communities (Toribio et al., 2011; Martínez-Carranza et al., 2018).
Conclusions
The 16S rDNA gene sequence analysis allowed the identification of 65 strains isolated from the CCB, of which 60 were identified to genus level, and some even to species level, while five strains were only identified to family level. The use of bioinformatics tools was essential for molecular identification and the construction of a phylogenetic tree, which allowed us to know the taxonomic location and the relationship among the different strains identified.
Most of the identified microorganisms belong to the phylum Bacillota (with the genus Bacillus standing out), followed by the phyla Actinomycetota and Pseudomonadota. Among the strains identified, potential biotechnological applications were found in bacteria isolated under conditions similar to those of the CCB, and even in some strains from the same lagoons. These applications include their use as plant growth-promoting bacteria, synthesis of natural products, bioremediation of soils and waters polluted with metals and hydrocarbons, and production of exopolysaccharides, among others. These findings open the door to future studies to evaluate their biotechnological capabilities.

