I believe one of the site members is an expert in Cyanobacteria hence the question.

I'm looking for a comprehensive 'phylogenetic tree' of the phylum Cyanobacteria and want to identify all the terrestrial members/groups. For example, Nodosilinea is one of the terrestrial members.

Part of my rationale for the question is that the Orders can be polyphyletic. From an outsider's point of view this is a difficult taxonomic group to understand.


Chroococcales Chroococcidiopsidales Gloeobacterales Nostocales Oscillatoriales Pleurocapsales Spirulinales Synechococcales Incertae sedis

Background Cyanobacteria is a massive phylum and important to both terrestrial and aquatic habitats, but what I need to understand is how terrestrial members are distributed across the tree. The reason they are interesting (both aquatic and terrestrial) is that they are efficient at removing CO2 from the atmosphere. Reducing a carbon footprint is an area of growing commercial interest.

  • $\begingroup$ this is Benjy. I am a grad student at University of Nevada, Las Vegas. I am interested in terrestrial cyanobacteria too. I have read all the papers that you have mentioned such as Chen et al., 2021 and Strunecky et al., 2023. I would like to ask if you have an account of Google Scholar or Twitter. I am also working in a paper related to terrestrial cyanobacteria and bioinformatics and I'd like to read your future paper. Best, Benjy $\endgroup$ Feb 17 at 0:07
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    $\begingroup$ Yes however, I work in industry - a Big Five Tech is the key client (climate health) - and my company (not the client) protects its IP by non-disclosure. @Laura does publish in this area however. I rarely lift my anonymity, except that I that live in Mexico and I'm an active Academic Editor. $\endgroup$
    – M__
    Feb 17 at 17:24

1 Answer 1


Ah! Finally, a question I can answer.

There has been some pretty good work about this recently. In particular, I would reccomend this paper by Chen et al. , which groups cyanobacteria into terrestrial / freshwater / marine and...well, the title says the rest. Some are edge cases by necessity (e.g. some coastal biofilm-forming cyanobacteria may be more similar to terrestrial ones than to many marine ones) but that's just nature.

Chen, MY., Teng, WK., Zhao, L. et al. Comparative genomics reveals insights into cyanobacterial evolution and habitat adaptation. ISME J 15, 211–227 (2021). https://doi.org/10.1038/s41396-020-00775-z (https://rdcu.be/dmJpm)

I regularly use this in my work, mainly because they have their trees posted on iTOL (in the 'Data availability' section) and this makes it really easy to search for specific strains.

Which brings us the the main problem. Right now there are about three main ways of separating the cyanobacterial phylum into orders. There is the NCBI database classification (largely based on 16S rRNA), like for example the Chen et al. paper uses. This may sometimes appear polyphyletic when overimposed on a genome tree. Then there is the GTDB classification (https://gtdb.ecogenomic.org/), which is based on genomes. This can be seen in Alcorta et al. 2020 (Alcorta J, Alarcón-Schumacher T, Salgado O and Díez B (2020) Taxonomic Novelty and Distinctive Genomic Features of Hot Spring Cyanobacteria. Front. Genet. 11:568223. doi: 10.3389/fgene.2020.568223) - on average, the tree shape is similar to the one in Chen et al., but the orders make more sense. The GTDB classification is good phylogenetically, and well-integrated with the database (for example, you can just get the list of all genomes/metagenomes available for an order). But because it's not focused on the taxonomy (the naming of things), the actual names may not always fit with the Bacterial/Botanical Code. One research group has been kind enough to go through the absolute mess that is cyanobacteria taxonomy, and now this paper exists.

Strunecký, O., Ivanova, A. P., & Mareš, J. (2023). An updated classification of cyanobacterial orders and families based on phylogenomic and polyphasic analysis. Journal of Phycology, 59(1), 12-51. (https://onlinelibrary.wiley.com/share/A5UXIHBUCIH9JRTIWFSE?target=10.1111/jpy.13304)

As far as I've seen, their orders more or less match with GTDB, just under different names (except for GTDB Cyanobacteriales with is split into more orders in this paper). They also have a much larger 16S rrNA phylogeny constrained by the genome one.

Hower, that solves only part of the problem. Because at the smaller scale (genus, species), you still have strains labeled by their morphologies, and culture collections are (for understandable reasons) hesitant to change their naming system. For particularly visually non-descript groups like 'Synechococcus' or 'Leptolyngbya', there is a good chance that a particular strain could be nearly anywhere in the phylogenetic tree. I would always get a 16S rRNA (if not already avaiable), BLAST it, and then check where related strains appear in a genome tree.

Edit: I have also heard of Cydrasil (https://www.cydrasil.org/), an online tool which can place a 16S rrNA sequence within the context of the cyanobacterial tree, but I haven't tested it yet.

Hope that helps!

  • $\begingroup$ A HUGE thanks. It's really helpful. It will take me a while to read through all this, but I can now have some expertise in cyanobacteria (or at least half competent). I work in industry BTW (carbon neutral status for blue-chip clients) ... the analytics (and findings) are very advanced ... but my company will not publish (no comment) ... My thinking is that cyanobacteria are huge players in the carbon cycle, but you'll know much more than I. $\endgroup$
    – M__
    Sep 22, 2023 at 13:59
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    $\begingroup$ @M__ Hello. Sorry to necro your question, just wanted to ask you something. My work for the last few years is finally getting close to a publishable format, and I just wanted to ask whether you would agree to being acknowledged in my next paper. You've been answering my questions on Bioinformatics.SE for, well, years, and as someone who got into bioinformatics more deeply than my immediate group could help with, that was very valuable to me. I am very grateful, and would be glad to express that. $\endgroup$
    – Laura
    Jan 29 at 9:41
  • $\begingroup$ Hi @Laura, thats cool and appreciated, thanks. $\endgroup$
    – M__
    Jan 29 at 13:09

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