The transition of cetaceans (whales, dolphins, and porpoises) from terrestrial to aquatic lifestyles is a striking example of natural selection driving major phenotypic changes (Figure 1). For instance, cetaceans have evolved the ability to withstand high pressure and to store oxygen for long periods, among other adaptations (Das et al. 2023). Many phenotypic changes, such as shifts in organ structure, have been well-characterized through fossils (Thewissen et al. 2009). Although such phenotypic transitions are now well understood, we have only a partial understanding of the underlying genetic mechanisms. Scanning for signatures of adaptation in genes related to phenotypes of interest is one approach to better understand these mechanisms. This was the focus of Uribe and colleagues’ (2024) work, who tested for such signatures across cetacean protein-coding genes.

Figure 1: The skeletons of Ambulocetus (an early whale; top) and Pakicetus (the earliest known cetacean, which lived about 50 million years ago; bottom). Copyright: J. G. M. Thewissen. Displayed here with permission from the copyright holder.

The authors were specifically interested in investigating the evolution of ion channels, as these proteins play fundamental roles in physiological processes. An important aspect of their work was to develop a bioinformatic pipeline to identify orthologous ion channel genes across a set of genomes. After applying their bioinformatic workflow to 18 mammalian species (including nine cetaceans), they conducted tests to find out whether these genes showed signatures of positive selection in the cetacean lineage. For many ion channel genes, elevated ratios of non-synonymous to synonymous substitution rates were detected (for at least a subset of sites, and not necessarily the entire coding region of the genes). The genes concerned were enriched for several functions, including heart and nervous system-related phenotypes.

One top gene hit among the putatively selected genes was SCN5A, which encodes a sodium channel expressed in the heart. Interestingly, the authors noted a specific amino acid replacement, which is associated with sensitivity to the toxin tetrodotoxin in other lineages. This substitution appears to have occurred in the common ancestor of toothed whales, and then was reversed in the ancestor of bottlenose dolphins. The authors describe known bottlenose dolphin interactions with toxin-producing pufferfish that could result in high tetrodotoxin exposure, and thus perhaps higher selection for tetrodotoxin resistance. Although this observation is intriguing, the authors emphasize it requires experimental confirmation.

The authors also recapitulated the previously described observation (Yim et al. 2014; Huelsmann et al. 2019) that cetaceans have fewer protein-coding genes compared to terrestrial mammals, on average. This signal has previously been hypothesized to partially reflect adaptive gene loss. For example, specific gene loss events likely decreased the risk of developing blood clots while diving (Huelsmann et al. 2019). Uribe and colleagues also considered overall gene turnover rate, which encompasses gene copy number variation across lineages, and found the cetacean gene turnover rate to be three times higher than that of terrestrial mammals. Finally, they found that cetaceans have a higher proportion of ion channel genes (relative to all protein-coding genes in a genome) compared to terrestrial mammals. 

Similar investigations of the relative non-synonymous to synonymous substitution rates across cetacean and terrestrial mammal orthologs have been conducted previously, but these have primarily focused on dolphins as the sole cetacean representative (McGowen et al. 2012; Nery et al. 2013; Sun et al. 2013). These projects have also been conducted across a large proportion of orthologous genes, rather than a subset with a particular function. Performing proteome-wide investigations can be valuable in that they summarize the genome-wide signal, but can suffer from a high multiple testing burden. More generally, investigating a more targeted question, such as the extent of positive selection acting on ion channels in this case, or on genes potentially linked to cetaceans’ increased brain sizes (McGowen et al. 2011) or hypoxia tolerance (Tian et al. 2016), can be easier to interpret, as opposed to summarizing broader signals. However, these smaller-scale studies can also experience a high multiple testing burden, especially as similar tests are conducted across numerous studies, which often is not accounted for (Ioannidis 2005). In addition, integrating signals across the entire genome will ultimately be needed given that many genetic changes undoubtedly underlie cetaceans’ phenotypic diversification. As highlighted by the fact that past genome-wide analyses have produced some differing biological interpretations (McGowen et al. 2012; Nery et al. 2013; Sun et al. 2013), this is not a trivial undertaking. 

Nonetheless, the work performed in this preprint, and in related research, is valuable for (at least) three reasons. First, although it is a challenging task, a better understanding of the genetic basis of cetacean phenotypes could have benefits for many aspects of cetacean biology, including conservation efforts. In addition, the remarkable phenotypic shifts in cetaceans make the question of what genetic mechanisms underlie these changes intrinsically interesting to a wide audience. Last, since the cetacean fossil record is especially well-documented (Thewissen et al. 2009), cetaceans represent an appealing system to validate and further develop statistical methods for inferring adaptation from genetic data. Uribe and colleagues’ (2024) analyses provide useful insights relevant to each of these points, and have generated intriguing hypotheses for further investigation.

References

Das, K., Sköld, H., Lorenz, A., Parmentier, E. 2023. Who are the marine mammals? In: “Marine Mammals: A Deep Dive into the World of Science”. Brennecke, D., Knickmeier, K., Pawliczka, I., Siebert, U., Wahlberg, M (editors). Springer, Cham. p. 1–14. https://doi.org/10.1007/978-3-031-06836-2_1

Huelsmann, M., Hecker, N., Springer, M., S., Gatesy, J., Sharma, V., Hiller, M. 2019. Genes lost during the transition from land to water in cetaceans highlight genomic changes associated with aquatic adaptations. Science Advances. 5(9):eaaw6671. https://doi.org/10.1126/sciadv.aaw6671

Ioannidis, J., P., A. 2005. Why most published research findings are false. PLOS Medicine. 2(8):e124. https://doi.org/10.1371/journal.pmed.0020124

McGowen MR, Montgomery SH, Clark C, Gatesy J. 2011. Phylogeny and adaptive evolution of the brain-development gene microcephalin (MCPH1) in cetaceans. BMC Evolutionary Biology. 11(1):98. https://doi.org/10.1186/1471-2148-11-98

McGowen MR, Grossman LI, Wildman DE. 2012. Dolphin genome provides evidence for adaptive evolution of nervous system genes and a molecular rate slowdown. Proceedings of the Royal Society B: Biological Sciences. 279(1743):3643–3651. https://doi.org/10.1098/rspb.2012.0869

Nery, M., F., González, D., J., Opazo, J., C. 2013. How to make a dolphin: molecular signature of positive selection in cetacean genome. PLOS ONE. 8(6):e65491. https://doi.org/10.1371/journal.pone.0065491

Sun, Y.-B., Zhou, W.-P., Liu, H.-Q., Irwin, D., M., Shen, Y.-Y., Zhang, Y.-P. 2013. Genome-wide scans for candidate genes involved in the aquatic adaptation of dolphins. Genome Biology and Evolution. 5(1):130–139. https://doi.org/10.1093/gbe/evs123

Tian, R., Wang, Z., Niu, X., Zhou, K., Xu, S., Yang, G. 2016. Evolutionary genetics of hypoxia tolerance in cetaceans during diving. Genome Biology and Evolution. 8(3):827–839. https://doi.org/10.1093/gbe/evw037

Thewissen, J., G., M., Cooper, L., N., George, J., C., Bajpai, S. 2009. From land to water: the origin of whales, dolphins, and porpoises. Evolution: Education and Outreach. 2(2):272–288. https://doi.org/10.1007/s12052-009-0135-2

Uribe, C., Nery, M., Zavala, K., Mardones, G., Riadi, G., Opazo, J. 2024. Evolution of ion channels in cetaceans: A natural experiment in the tree of life. bioRxiv, ver. 8 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2023.06.15.545160

Yim, H.-S., Cho, Y., S., Guang, X., Kang, S., G., Jeong, J.-Y., Cha, S.-S., Oh, H.-M., Lee, J.-H., Yang, E., C., Kwon, K., K., et al. 2014. Minke whale genome and aquatic adaptation in cetaceans. Nature Genetics. 46(1):88–92. https://doi.org/10.1038/ng.2835

Bacteria and phages have coexisted and coevolved for a long time. Phages are bacteria-infecting viruses, with a symbiotic status sensu lato, meaning they can be pathogenic, commensal or mutualistic. Thus, the association between bacteria phages has probably played a key role in the high adaptability of bacteria to most - if not all – of Earth’s ecosystems, including other living organisms (such as eukaryotes), and also regulate bacterial community size (for instance during bacterial blooms). 

As genetic entities, phages are submitted to mutations and natural selection, which changes their DNA sequence. Therefore, comparative genomic analyses of contemporary phages can be useful to understand their evolutionary dynamics. International initiatives such as SEA-PHAGES have started to tackle the issue of history of phage-bacteria interactions and to describe the dynamics of the co-evolution between bacterial hosts and their associated viruses. Indeed, the understanding of this cross-talk has many potential implications in terms of health and agriculture, among others.

The work of Koert et al. (2021) deals with one of the largest groups of bacteria (Actinobacteria), which are Gram-positive bacteria mainly found in soil and water. Some soil-born Actinobacteria develop filamentous structures reminiscent of the mycelium of eukaryotic fungi. In this study, the authors focused on the Streptomyces clade, a large genus of Actinobacteria colonized by phages known for their high level of genetic diversity.

The authors tested the hypothesis that large exchanges of genetic material occurred between Streptomyces and diverse phages associated with bacterial hosts. Using public datasets, their comparative phylogenomic analyses identified a new cluster among Actinobacteria–infecting phages closely related to phages of Firmicutes. Moreover, the GC content and codon-usage biases of this group of phages of Actinobacteria are similar to those of Firmicutes. 

This work demonstrates for the first time the transfer of a bacteriophage lineage from one bacterial phylum to another one. The results presented here suggest that the age of the described transfer is probably recent since several genomic characteristics of the phage are not fully adapted to their new hosts. However, the frequency of such transfer events remains an open question. If frequent, such exchanges would mean that pools of bacteriophages are regularly fueled by genetic material coming from external sources, which would have important implications for the co-evolutionary dynamics of phages and bacteria.

References

Koert, M., López-Pérez, J., Courtney Mattson, C., Caruso, S. and Erill, I. (2021) Evidence for shared ancestry between Actinobacteria and Firmicutes bacteriophages. bioRxiv, 842583, version 5 peer-reviewed and recommended by Peer community in Genomics. doi: https://doi.org/10.1101/842583 

Biological systems depend on finely tuned interactions of their components. Thus, regulating these components is critical for the system's functionality. In prokaryotic cells, riboswitches are regulatory elements controlling transcription or translation. Riboswitches are RNA molecules that are usually located in the 5′-untranslated region of protein-coding genes. They generate secondary structures leading to the regulation of the expression of the downstream protein-coding gene (Kavita and Breaker, 2022). Riboswitches are very versatile and can bind a wide range of small molecules; in many cases, these are metabolic byproducts from the gene’s enzymatic or signaling pathway. Their versatility and abundance in many species make them attractive for synthetic biological circuits. One class that has been drawing the attention of synthetic biologists is toehold switches (Ekdahl et al., 2022; Green et al., 2014). These are single-stranded RNA molecules harboring the necessary elements for translation initiation of the downstream gene: a ribosome-binding site and a start codon. Conformation change of toehold switches is triggered by an RNA molecule, which enables translation.

To exploit the most out of toehold switches, automation of their design would be highly advantageous. Cisneros and colleagues (Cisneros et al., 2022) developed a tool, “Toeholder”, that automates the design of toehold switches and performs in silico tests to select switch candidates for a target gene. Toeholder is an open-source tool that provides a comprehensive and automated workflow for the design of toehold switches. While web tools have been developed for designing toehold switches (To et al., 2018), Toeholder represents an intriguing approach to engineering biological systems by coupling synthetic biology with computational biology. Using molecular dynamics simulations, it identified the positions in the toehold switch where hydrogen bonds fluctuate the most. Identifying these regions holds great potential for modifications when refining the design of the riboswitches. To be effective, toehold switches should provide a strong ON signal and a weak OFF signal in the presence or the absence of a target, respectively. Toeholder nicely ranks the candidate toehold switches based on experimental evidence that correlates with toehold performance (based on good ON/OFF ratios).

Riboswitches are highly appealing for a broad range of applications, including pharmaceutical and medical purposes (Blount and Breaker, 2006; Giarimoglou et al., 2022; Tickner and Farzan, 2021), thanks to their adaptability and inexpensiveness. The Toeholder tool developed by Cisneros and colleagues is expected to promote the implementation of toehold switches into these various applications.

References

Blount KF, Breaker RR (2006) Riboswitches as antibacterial drug targets. Nature Biotechnology, 24, 1558–1564. https://doi.org/10.1038/nbt1268

Cisneros AF, Rouleau FD, Bautista C, Lemieux P, Dumont-Leblond N, ULaval 2019 T iGEM (2022) Toeholder: a Software for Automated Design and In Silico Validation of Toehold Riboswitches. bioRxiv, 2021.11.09.467922, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.11.09.467922

Ekdahl AM, Rojano-Nisimura AM, Contreras LM (2022) Engineering Toehold-Mediated Switches for Native RNA Detection and Regulation in Bacteria. Journal of Molecular Biology, 434, 167689. https://doi.org/10.1016/j.jmb.2022.167689

Giarimoglou N, Kouvela A, Maniatis A, Papakyriakou A, Zhang J, Stamatopoulou V, Stathopoulos C (2022) A Riboswitch-Driven Era of New Antibacterials. Antibiotics, 11, 1243. https://doi.org/10.3390/antibiotics11091243

Green AA, Silver PA, Collins JJ, Yin P (2014) Toehold Switches: De-Novo-Designed Regulators of Gene Expression. Cell, 159, 925–939. https://doi.org/10.1016/j.cell.2014.10.002

Kavita K, Breaker RR (2022) Discovering riboswitches: the past and the future. Trends in Biochemical Sciences. https://doi.org/10.1016/j.tibs.2022.08.009

Tickner ZJ, Farzan M (2021) Riboswitches for Controlled Expression of Therapeutic Transgenes Delivered by Adeno-Associated Viral Vectors. Pharmaceuticals, 14, 554. https://doi.org/10.3390/ph14060554

To AC-Y, Chu DH-T, Wang AR, Li FC-Y, Chiu AW-O, Gao DY, Choi CHJ, Kong S-K, Chan T-F, Chan K-M, Yip KY (2018) A comprehensive web tool for toehold switch design. Bioinformatics, 34, 2862–2864. https://doi.org/10.1093/bioinformatics/bty216