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
Funding agencies should impose application funnels that maintain ~25% success rates (very low rates, with the same pool of money, are only seemingly kind to the applicants and are detrimental to collective productivity)
April 17, 2026 at 12:21 AM
Funding agencies should impose application funnels that maintain ~25% success rates (very low rates, with the same pool of money, are only seemingly kind to the applicants and are detrimental to collective productivity)
IMO, the real cost of low success rates is not the time wasted on reviews but the time researchers collectively waste developing grant proposals that will not be funded. 1/2
April 17, 2026 at 12:21 AM
IMO, the real cost of low success rates is not the time wasted on reviews but the time researchers collectively waste developing grant proposals that will not be funded. 1/2
It's an important piece (provocative, yes, even triggering). It surfaces one the biggest challenges research universities will soon face. The current incentive model in (US) academia awards progress more than anything which only compounds the problem
March 17, 2026 at 2:46 PM
It's an important piece (provocative, yes, even triggering). It surfaces one the biggest challenges research universities will soon face. The current incentive model in (US) academia awards progress more than anything which only compounds the problem
Absolutely, what can be more fitting 😉
March 13, 2026 at 9:17 PM
Absolutely, what can be more fitting 😉
I tip my hat at the authors putting in all the efforts for these follow-up experiments
February 10, 2026 at 5:44 PM
I tip my hat at the authors putting in all the efforts for these follow-up experiments
Just concluded a 2-week coding spree with a student using VS+codex. The x5-10 gain in productivity blew my mind 🤯. BUT, I'm also sure that for inexperienced coders AI-coding makes garbage-in-gargbe-out pitfall inescapable.
January 31, 2026 at 8:21 PM
Just concluded a 2-week coding spree with a student using VS+codex. The x5-10 gain in productivity blew my mind 🤯. BUT, I'm also sure that for inexperienced coders AI-coding makes garbage-in-gargbe-out pitfall inescapable.
Beautiful “full arc” story on abx response with impressive level of mechanistic detail (could be a class example for undergrad microbiology lesson)
January 19, 2026 at 1:22 PM
Beautiful “full arc” story on abx response with impressive level of mechanistic detail (could be a class example for undergrad microbiology lesson)
Congrats on publishing this beautiful work! I'm still mind-blown that: (1) there's a 7th RND pump in E. coli and (2) that its somewhat unclear what it actually pumps out IRL
January 16, 2026 at 6:30 PM
Congrats on publishing this beautiful work! I'm still mind-blown that: (1) there's a 7th RND pump in E. coli and (2) that its somewhat unclear what it actually pumps out IRL
It's a beautiful approach! But it's very disappointing that there is actually NO phenotypic characterization of the rearranged strains in the manuscript ... hoping it's an evolving manuscript that they'll keep updating
January 16, 2026 at 6:28 PM
It's a beautiful approach! But it's very disappointing that there is actually NO phenotypic characterization of the rearranged strains in the manuscript ... hoping it's an evolving manuscript that they'll keep updating
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