Amir Mitchell
@amitchell.bsky.social
Systems biologist trying to disentangle host-drug-microbiome interactions | PI at UMass medical school | hoping to keep the BS to a minimum (not always successful)
https://mitchell-lab.umassmed.edu
https://mitchell-lab.umassmed.edu
Totally agree. Fail early, fail often (and aim high) is something more scientists need to live by.
December 31, 2025 at 2:30 AM
Totally agree. Fail early, fail often (and aim high) is something more scientists need to live by.
Huge credit to @carmenli.bsky.social for her persistence in chasing a moonlight project into its beautiful completion. Credit also goes Ethan Chang, the rotation student contributing to this work 9/9
December 22, 2025 at 3:25 PM
Huge credit to @carmenli.bsky.social for her persistence in chasing a moonlight project into its beautiful completion. Credit also goes Ethan Chang, the rotation student contributing to this work 9/9
Btw, note that “inactivation” can mean more than enzymatic degradation and includes any process that reduces effective drug activity over time (chemical modification, sequestration, etc) 8/9
December 22, 2025 at 3:25 PM
Btw, note that “inactivation” can mean more than enzymatic degradation and includes any process that reduces effective drug activity over time (chemical modification, sequestration, etc) 8/9
We then tested if this assosiation holds through our entire dataset. We used a functional assay for drug inactivation on all drugs and found the association holds up. A long-lag inhibition phenotype is a strong indicator of drug inactivation 7/9
December 22, 2025 at 3:25 PM
We then tested if this assosiation holds through our entire dataset. We used a functional assay for drug inactivation on all drugs and found the association holds up. A long-lag inhibition phenotype is a strong indicator of drug inactivation 7/9
That pushed us to ask whether cellular defenses might impact curve profiles. We cloned different resistance cassettes and measured how they altered the potency-matched growth curves. This strongly hinted that active drug inactivation underlies a long-lag inhibition profile 6/9
December 22, 2025 at 3:25 PM
That pushed us to ask whether cellular defenses might impact curve profiles. We cloned different resistance cassettes and measured how they altered the potency-matched growth curves. This strongly hinted that active drug inactivation underlies a long-lag inhibition profile 6/9
Overlaying the known mechanisms of action over the barycentric landscape ruled out this effect stem exclusively from how drug target bacteria (since drugs with the same mechanism can land in very different regions of the landscape) 5/9
December 22, 2025 at 3:25 PM
Overlaying the known mechanisms of action over the barycentric landscape ruled out this effect stem exclusively from how drug target bacteria (since drugs with the same mechanism can land in very different regions of the landscape) 5/9
Clustering drug by their impact on lag/rate/yield clearly revealed that they vary hugely in how they inhibited growth. In extreme cases, a drug solely affected only a single parameter 4/9
December 22, 2025 at 3:25 PM
Clustering drug by their impact on lag/rate/yield clearly revealed that they vary hugely in how they inhibited growth. In extreme cases, a drug solely affected only a single parameter 4/9
To compare drugs fairly, we didn’t use an arbitrary concentration. Instead, we interpolated each drug to a potency-matched condition (the concentration expected to produce the same overall level of inhibition) 3/9
December 22, 2025 at 3:25 PM
To compare drugs fairly, we didn’t use an arbitrary concentration. Instead, we interpolated each drug to a potency-matched condition (the concentration expected to produce the same overall level of inhibition) 3/9
So we assembled a new carefully curated dataset with growth curves across almost forty drugs, measured across multiple sub-inhibitory concentrations. For each curve, we quantified intuitive its key features: lag, growth rate, and yield 2/9
December 22, 2025 at 3:25 PM
So we assembled a new carefully curated dataset with growth curves across almost forty drugs, measured across multiple sub-inhibitory concentrations. For each curve, we quantified intuitive its key features: lag, growth rate, and yield 2/9
Our recent paper in npj Antimicrobials and Resistance is a great example of scientific serendipity: after staring at thousands of bacterial growth curves over many studies, we started wondering whether the curve shapes themselves carry mechanistic information 1/9 🦠🧪
www.nature.com/articles/s44...
www.nature.com/articles/s44...
Predicting drug inactivation by changes in bacterial growth dynamics - npj Antimicrobials and Resistance
npj Antimicrobials and Resistance - Predicting drug inactivation by changes in bacterial growth dynamics
www.nature.com
December 22, 2025 at 3:25 PM
Our recent paper in npj Antimicrobials and Resistance is a great example of scientific serendipity: after staring at thousands of bacterial growth curves over many studies, we started wondering whether the curve shapes themselves carry mechanistic information 1/9 🦠🧪
www.nature.com/articles/s44...
www.nature.com/articles/s44...
This was a true collaboration between physicists (Andrew Mugler and @motasemelgamel.bsky.social), an immunologist (Michael Brehm from @umasschan.bsky.social ), and systems biologists (with @serkansayin.bsky.social and Brittany Rosener from my lab also at @umasschan.bsky.social ) (7/7)
December 17, 2025 at 6:52 PM
This was a true collaboration between physicists (Andrew Mugler and @motasemelgamel.bsky.social), an immunologist (Michael Brehm from @umasschan.bsky.social ), and systems biologists (with @serkansayin.bsky.social and Brittany Rosener from my lab also at @umasschan.bsky.social ) (7/7)
Beyond providing (to our knowledge) the first dynamical model for tumor colonization, our study matters given the fierce debate on the tumor microbiome. These statistical “fingerprints” may help distinguish genuine colonizers from technical artifacts/contamination (possibly even by microscopy) (6/7)
December 17, 2025 at 6:52 PM
Beyond providing (to our knowledge) the first dynamical model for tumor colonization, our study matters given the fierce debate on the tumor microbiome. These statistical “fingerprints” may help distinguish genuine colonizers from technical artifacts/contamination (possibly even by microscopy) (6/7)
The surprise: lineage sizes formed a scale-free power law that matches Zipf’s law (rank–frequency slope ~−1). This signature was robust across dozens of tumors and multiple collection days post bacteria intratumor injection (5/7)
December 17, 2025 at 6:52 PM
The surprise: lineage sizes formed a scale-free power law that matches Zipf’s law (rank–frequency slope ~−1). This signature was robust across dozens of tumors and multiple collection days post bacteria intratumor injection (5/7)
When we injected bacteria directly into the tumor (circumventing the bottleneck), we detected thousands of colonizing lineages, yet their sizes were still highly uneven (ruling out early tumor arrivers dominate) (4/7)
December 17, 2025 at 6:52 PM
When we injected bacteria directly into the tumor (circumventing the bottleneck), we detected thousands of colonizing lineages, yet their sizes were still highly uneven (ruling out early tumor arrivers dominate) (4/7)
Since we used genetically barcoded bacteria, we could also monitor growth of individual colonizers. We found that growth was extremely uneven with a handful of lineages becoming dominant (“winner-takes-most”) (3/7)
December 17, 2025 at 6:52 PM
Since we used genetically barcoded bacteria, we could also monitor growth of individual colonizers. We found that growth was extremely uneven with a handful of lineages becoming dominant (“winner-takes-most”) (3/7)
Main takeaways: Post systemic infection, there's a tight colonization bottleneck (per-cell colonization probability ~0.005%). Yet, once colonization happens, growth is remarkably fast (~50 min generation time) and bacterial load in tumors approaches saturation within a day (2/7)
December 17, 2025 at 6:52 PM
Main takeaways: Post systemic infection, there's a tight colonization bottleneck (per-cell colonization probability ~0.005%). Yet, once colonization happens, growth is remarkably fast (~50 min generation time) and bacterial load in tumors approaches saturation within a day (2/7)
We just published in @molsystbiol.org with the Mugler lab (UPitt) on bacterial population dynamics during tumor colonization (mouse model). Our study was guided by a Luria–Delbrück-style idea: infer mechanism from statistics (1/7) 🧪🦠
doi.org/10.1038/s443...
doi.org/10.1038/s443...
December 17, 2025 at 6:52 PM
We just published in @molsystbiol.org with the Mugler lab (UPitt) on bacterial population dynamics during tumor colonization (mouse model). Our study was guided by a Luria–Delbrück-style idea: infer mechanism from statistics (1/7) 🧪🦠
doi.org/10.1038/s443...
doi.org/10.1038/s443...
The (very real) cost of changing your research field. Absolutely true! But the freedom to pivot is one of the greatest things in this profession.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
The pivot penalty in research - Nature
An analysis of millions of scientific papers and patents reveals a ‘pivot penalty’ when researchers shift direction, with the impact of studies decreasing rapidly the further they move from their prev...
www.nature.com
May 31, 2025 at 1:37 PM
The (very real) cost of changing your research field. Absolutely true! But the freedom to pivot is one of the greatest things in this profession.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Great opportunity to participate in scientific outreach!
Starting to write to folks to consider appear on my #MattersMicrobial podcast. Would love an astrobiologist! Looking for other cool and #OMG #WTM microbial enthusiasts to appear. Happy to hear suggestions. I need to fill July and August.
May 22, 2025 at 6:05 PM
Great opportunity to participate in scientific outreach!
Had a fantastic time with @markowenmartin.bsky.social’s on his #MattersMicrobial podcast (@microbetv.bsky.social). We discussed how to uncover the killing mechanisms of hundreds of antibacterials simultaneously and how #AI can transform the search for new antibiotics 🧪🦠💊
youtu.be/Wa0zd-TRCO8?...
youtu.be/Wa0zd-TRCO8?...
Matters Microbial #89: Can AI Point Us to New Antibiotics
YouTube video by MicrobeTV
youtu.be
May 5, 2025 at 4:47 PM
Had a fantastic time with @markowenmartin.bsky.social’s on his #MattersMicrobial podcast (@microbetv.bsky.social). We discussed how to uncover the killing mechanisms of hundreds of antibacterials simultaneously and how #AI can transform the search for new antibiotics 🧪🦠💊
youtu.be/Wa0zd-TRCO8?...
youtu.be/Wa0zd-TRCO8?...
Reposted by Amir Mitchell
Yo, micro/evo/qbio/physics of living systems/astrobiology/renegade cell bio folks- if you are interested in starting a feed, reply/repost this. Let's get the crew back together!
Would anyone be interested in starting a microbial evolution feed on here? EvoSky is rather organismal, which is great, but would love to see experimental evo folks' feeds too. Thoughts?
January 29, 2025 at 11:40 PM
Yo, micro/evo/qbio/physics of living systems/astrobiology/renegade cell bio folks- if you are interested in starting a feed, reply/repost this. Let's get the crew back together!
Fascinating shift in the geography of drug development (excellent writing too!)
If you haven't read this article yet, you should! Link here: atelfo.github.io/2024/12/20/...
I think Alex should write more because he's really, really great at it.
I think Alex should write more because he's really, really great at it.
Will all our drugs come from China?
Personal site for posts about my interests: the biotech industry, medicine, molecular biology, neuroscience, biorisk, science, consciousness, AI, innovation, decision making, philosophy, games, sci-fi, probability, and forecasting (among other things). I write to learn, mostly about biotech.
atelfo.github.io
January 26, 2025 at 3:29 AM
Fascinating shift in the geography of drug development (excellent writing too!)
The inherent stochasticity of biological systems 😉
January 18, 2025 at 7:46 PM
The inherent stochasticity of biological systems 😉
Interested in Antimicrobial Resistance & Quantitative Bio? Join a 3-day meeting+workshop with some of my favorite #AMR #QBio scientists this April (University of Exeter, UK). Register here: tinyurl.com/QAMR2025reg 🧪🦠
January 17, 2025 at 3:16 PM
Interested in Antimicrobial Resistance & Quantitative Bio? Join a 3-day meeting+workshop with some of my favorite #AMR #QBio scientists this April (University of Exeter, UK). Register here: tinyurl.com/QAMR2025reg 🧪🦠
Amazing book, shaped my worldview on Science. Kuhn’s genius was also in claiming that “paradigm shifts” are not purely logical, but are tainted by social & psychological factors. He claimed that established scientists are often conservatives resisting such shifts.
December 28, 2024 at 3:02 AM
Amazing book, shaped my worldview on Science. Kuhn’s genius was also in claiming that “paradigm shifts” are not purely logical, but are tainted by social & psychological factors. He claimed that established scientists are often conservatives resisting such shifts.