Rowan Green
@rowancallumg.bsky.social
560 followers 1.1K following 36 posts
Postdoc studying viral evolution with @asherleeks.bsky.social | previously @mermanchester.bsky.social | mutagenesis | bacteria | viruses | big R nerd 🧬🦠💻 🏳️‍⚧️ He/Him
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rowancallumg.bsky.social
Across domains of life 2017: doi.org/cb9s
Potential mechanism 2024: doi.org/m8zt

As discussed in the 2024 paper, ecological relevance likely depends on the amount of through-flow in the environment. Less flow = more opportunity for collective detoxification of the environment
Spontaneous mutation rate is a plastic trait associated with population density across domains of life
Author summary Spontaneous mutations fuel evolution, but the rate at which they occur can vary for a particular organism depending on its environment—a phenomenon known as mutation-rate plasticity. Fo...
doi.org
Reposted by Rowan Green
zaminiqbal.bsky.social
Great thread! All good, but this does grab the attention:
"our findings with ΔnudJ suggest future anti-evolution drug strategies could suppress spontaneous resistance evolution not only through minimizing resistance mutations but also by specifically limiting access to the fittest mutations."
rowancallumg.bsky.social
Finally, a shoutout to the blueycolors colour scheme for making all of my ggplots far more fun! 🟦 🟧 13/13
rowancallumg.bsky.social
Deleting the nudJ gene not only makes rifampicin resistance less likely by reducing the mutation rate but also reduces the chance of a resistant mutant rising to fixation as ΔnudJ favours lower fitness mutations: synergystic effects of mutation rates and spectra impeding resistance evolution 12/13
rowancallumg.bsky.social
Resistance mutations accessed by ΔnudJ (blue) were significantly less fit than those accessed by the wildtype (orange) & both strains accessed mutants less fit than one would expect by chance (black: all mutations occurring at =rates): spontaneous mutation is not optimised for future fitness. 11/13
Distribution of fitness effects showing mean fitness to be lowest in nudJ knockout followed by the wt followed by the null expectation of all mutations as equal rates
rowancallumg.bsky.social
Rather than looking at a genome-wide scale we took rifampicin resistance mutants observed in each genetic background and measured their fitness in a common genetic background. This choice to consider fitness at a single locus is reflective of resistance evolution to many antibiotics. 10/13
rowancallumg.bsky.social
Now for the cool evolution part: work from @deepaagashe.bsky.social and others has shown that shifts in the mutational spectrum can lead to genome wide changes in the fitness effects of accessed mutations. Was our ΔnudJ strain accessing mutations with different fitness effects to the wildtype? 9/13
rowancallumg.bsky.social
A mutation rates is made up from the rates of many different types of mutations (the mutational spectrum). We find that ΔnudJ has a significantly altered mutational spectrum to the wildtype, e.g. in the wt 22% of mutations are A>G, in ΔnudJ this is 9%. This is reversed by IS1 mutation in waaZ. 8/13
Proportion of rifR mutations accounted for by each SNP type (+small indels) showing nudJ knockout to have less A>G and more A>C mutations, proportionally, than the wt
rowancallumg.bsky.social
The antimutator ΔnudJ not only reduces mutation rates but also decreases the responsiveness of mutation rates to population density (usually mutation rates are elevated at low population densities in batch culture). Both of these traits are reverted by our strains carrying secondary mutations. 7/13
Scatter plot of mutation rate as a function of pop density showing nudJ knockout to have lower mutation rate and less variation by density while wt and nudJ + secondary mutation strains have high mutations rates significantly negatively correlated with pop density.
rowancallumg.bsky.social
I then focussed in on ΔnudJ, finding surprisingly that the mutation rate had reverted to the of the wildtype! We found that independent mutations in 2 of our stocks were responsible for this phenotype reversion, with initially frustrating inconsistencies resulting in new genetic understanding. 6/13
rowancallumg.bsky.social
Disruption of nucleotide metabolism gene mutT increases mutation rates however, its sibling genes in the nudix hydrolase family had not been characterised. A massive survey by coauthor Huw Richards found that 4 knockouts from this family result in significant mutation rate decreases (nudBFJ&H) 5/13
Mutation rates of nudix knockouts, mutT is the only mutator (mut rate > wt) and nudHJFB are antimutators (mut rate < wt)
rowancallumg.bsky.social
Mutator strains in which disruption of a single gene (usually DNA replication and repair enzymes) increases mutation rates are very common in laboratory and clinical E coli populations. BUT gene disruptions that reduce mutation rates (antimutator strains) are far less frequently observed (4/13)
rowancallumg.bsky.social
The antibiotic killed cells could stretch from Manchester to Paris and back to the UK while the total cell count would reach from my PhD lab in Manchester @mermanchester.bsky.social to my postdoc lab in Vancouver @zoology.ubc.ca ‪‬ 4.7 times. ‬(3/13)
rowancallumg.bsky.social
This team effort involved 4 PhD students, 1 undergrad, 1 masters student, 6 groups leaders, 7 years of (on-and-off) research, >8.5x10^11 E. coli cells killed with antibiotics and >3.5x10^13 E. coli cells grown in total. (2/13)
Reposted by Rowan Green
taylorlabgroup.bsky.social
🦠 New paper led by James Horton (feat. J Cherry & @gretelwaugh.bsky.social) reveals GnT DNA motif can boost T→A mutation rates up to 1000×, & how tweaking nearby bases can fine-tune its potency.
General across bacteria + potential in synbio.
📄 academic.oup.com/mbe/advance-ar…
🔗 James’s thread ⬇️
https://academic.oup.com/mbe/advance-ar…
Reposted by Rowan Green
stepadenisov.bsky.social
Aerobic bacteria show higher A>G (and lower G>A) mutation rate than anaerobes. First results in bioinformatic project to estimate mutation spectra across bacterial tree under my supervision. Qs and ideas are wellcome. #SMBE2025
Reposted by Rowan Green
brunoluviano.bsky.social
Same genome, different shape, different outcome.

SOS-independent phenotypic differences shape survival in E. coli.

Very happy to share our preprint!
penamiller.bsky.social
New preprint led by @brunoluviano.bsky.social & Fernando Santos.

We show that filamentation enhances bacterial survival under toxic stress — not as collateral damage, but as a regulated morphological response.

TL;DR: Filamentation isn’t a symptom, it’s a strategy!
www.biorxiv.org/content/10.1...
rowancallumg.bsky.social
Empty desk in Manchester ready for new adventures in microbial evolution elsewhere 🤯🦠 I can't express how much I will miss everyone in @mermanchester.bsky.social (leaving was made a little sweeter by my first ever 'best talk' prize at #northernBUG / #YUEG at @huddersfielduni.bsky.social last week)
rowancallumg.bsky.social
Thank you so much to my examiners for a great discussion. And to my supervisors and lab mates for making the past 4 years such a positive and formative experience! @mermanchester.bsky.social is the place to be ❤️ (also thank you to e coli for mutating every day, all of your mutations are appreciated)
mermanchester.bsky.social
🎉 Congratulations to Dr Rowan Green, who defended his PhD today! @rowancallumg.bsky.social
rowancallumg.bsky.social
Excited to speak at #PGG58 / #PopGroup58 about mutation rates, mutation spectra, antibiotic resistance and (if I talk fast enough) how the environment affects these.
Tuesday in LT3 right after lunch. 🦠🧬
Come for the mutations, stay for the Bluey colour schemed ggplots. 📊🟦🟧