Cyanobacteria (Phylum Cyanobacteriota) are Gram-negative bacteria (Bacteria domain) capable of performing oxygenic photosynthesis (Smith et al., 1967) that form a phylogenetically coherent group (Komárek, 2006, Komárek et al., 2014). This group exhibits a great morphological diversity, ranging from unicellular to true-branch heterocytous filament forms (Komárek and Kaštovský, 2003). Additionally, they possess a large genetic, metabolic and physiological variety, allowing these organisms to inhabit a wide range of terrestrial and aquatic environments (Schirrmeister et al., 2013).

The systematics and, consequently, the taxonomy of members of this phylum, have been revised in recent years in order to better understand their evolutionary history (Castenholz, 2001, Fiore, 2007, Genuário et al., 2015, Gugger and Hoffmann, 2004, Hoffmann et al., 2005, Komárek et al., 2014, Vaz et al., 2015). Mainly in the last two decades, the application of molecular techniques, including the complete or partial sequence encoding for the 16S rRNA in phylogenetic studies, has extensively contributed to a better resolution of cyanobacterial systematics (Andreote et al., 2014, Genuário et al., 2017, Genuário et al., 2017, Komárek, 2006, Komárek, 2010, Mai et al., 2018, Obuekwe et al., 2019, Ramos et al., 2018, Silva et al., 2014). Advances in bioinformatics, the development of next-generation sequencing (NGS), and the continuous growth in genome databases, have also highlighted genome-based metadata analysis (Paul et al., 2019). Genomics analysis has thus become a promising methodology, capable of supplying a reproducible and reliable method in order to infer phylogenetic relationships between prokaryotes (Chun et al., 2018). The use of other characteristics, such as ecology, life cycle and ultrastructure, has also been applied to the classification of cyanobacteria, albeit at a lower rate, which has allowed a robust characterization, now known as “Polyphasic Classification” (Hoffmann et al., 2005). Accordingly, in recent years, the use of the polyphasic approach in studies of strains formerly described as Nostoc (Nostoc sensu lato) has indicated a polyphyletic origin of this genus when considering its description based on morphological criteria (Genuário et al., 2017, Hrouzek et al., 2005, Papaefthimiou et al., 2008, Silva et al., 2014). The polyphyletic status of Nostoc led to the revision of the taxonomy and systematics of strains/groups morphologically related to this genus, culminating in the description of many new genera: Mojavia (Řeháková et al., 2007); Desmonostoc (Hrouzek et al., 2013); Halotia (Genuário et al., 2015); Komarekiella (Hentschke et al., 2017); Aliinostoc (Bagchi et al., 2017); Compactonostoc (Cai et al., 2019); Minunostoc (Cai et al., 2019); Desikacharya (Saraf et al., 2019) and Purpurea (Cai et al., 2020), as well as Amazonocrinis, Atlanticothrix and Dendronalium (Alvarenga et al., 2021).

Among these genera, Desmonostoc emerged as one of the most diverse, considering the number of strains assigned to it (Hrouzek et al., 2013, Obuekwe et al., 2019, Pecundo et al., 2021). In addition, phylogenetic analyses based on 16S rRNA sequences retrieved from Desmonostoc strains have indicated that these sequences are grouped into two internal clusters (Hrouzek et al., 2013, Obuekwe et al., 2019). The first one, called D2, harbors the sequence of the type species, D. muscorum, reference strain NIVA-CYA 818 (whose 16S rRNA sequence is available under NCBI code AM711523), while the second one, called D1, aggregates sequences from other Desmonostoc spp. (de Alvarenga et al., 2018, Hrouzek et al., 2013, Kabirnataj et al., 2020, Obuekwe et al., 2019). However, to date, relatively few studies have been carried out aiming to elucidate the phylogenetic and morphological relationships among the strains/species or between members of this genus and closely related genera (de Alvarenga et al., 2018, Cai et al., 2018, Kabirnataj et al., 2020, Maltseva et al., 2022, Miscoe et al., 2016, Obuekwe et al., 2019, Pecundo et al., 2021, Saraf et al., 2018).

Despite this, the use of solely 16S rRNA sequences as markers for molecular phylogeny studies has been discussed (Bolhuis et al., 2010, Esteves-Ferreira et al., 2017, Genuário et al., 2013, Henson et al., 2004, Tamas et al., 2000), since some issues have arisen from lower hierarchical levels of analysis. The use of other molecular markers, such as rpoC1 (Fergusson and Saint, 2000), which encodes for the β-subunit of RNA polymerase, and nifH (Esteves-Ferreira et al., 2017, Genuário et al., 2013, Zehr et al., 1997), which encodes for the enzyme dinitrogenase reductase from the nitrogenase enzymatic complex, has aided in the resolution of some groups or has corroborated infra diversity at generic/specific levels (Genuário et al., 2013, Genuário et al., 2015, Tamas et al., 2000). Ecophysiological characteristics of cyanobacteria can also be used in polyphasic studies (de Alvarenga et al., 2018, Genuário et al., 2017, Genuário et al., 2015, Komárek, 2010), and the use of traits such as the life cycle, can provide a more robust phenotypical and ecological characterization (Hrouzek et al., 2005, Mateo et al., 2011). However, despite the significance of physiological characteristics, relatively few studies have focused on these traits for separating/characterizing groups considering nostocacean strains (de Alvarenga et al., 2018, Genuário et al., 2015).

The application of whole genome sequencing (WGS) and phylogenomics has already been applied to the Phylum Cyanobacteriota, leading to an extensive revision of this group considering orders and families (Strunecký et al., 2022). The WGS can also be used to search for common specific systematic genes, such as nitrogenase encoding genes (nifD, H, K), phycoerythrin (cpeA and cpeB) and gas vesicle (gvpA and gvpC) synthesis genes (Chun et al., 2018, Oren et al., 2022). Unfortunately, despite the increasing accessibility of genomic sequencing techniques and advances in data analysis, the use of WGS is still relatively expensive compared to the sequencing of small target regions. In fact, WGS has not been performed to date on any validly described Desmonostoc species. In addition, to be used for taxonomic purposes, the full-length 16S sequence of proposed type strains should also be determined by the Sanger sequencing method together with NGS (Chun et al., 2018). Nevertheless, the polyphasic approach for taxonomy is still understandable and is used significantly (Strunecký et al., 2022).

To date, no detailed study has been carried out with the aim of characterizing the molecular, physiological, and metabolic diversity of Desmonostoc strains. Thus, in order to elucidate the diversity of Desmonostoc from distinct environments, a set of strains were characterized in this study based on morphologic, molecular, ecological, as well as metabolic and physiological traits. Taken together, the metabolic and physiological data coupled with the morphometric data demonstrated good agreement with their separation based on the phylogeny of 16S rRNA genes. Furthermore, the use of metabolic and physiological traits, despite being an unusual tool for the polyphasic approach and description of novel taxa, was shown to be highly helpful for the proposal of an in-depth discussion of cyanobacterial diversity. Accordingly, these data could also provide insights for discussing the evolution of cyanobacterial genera, as well as identifying more strains for biotechnological application.