Saw this story yesterday discussing the use of quantum optics to improve imaging resolution.
@Nathan any thoughts on this?
Improvements in imaging and measurement of cells and their components is always a good thing. This was a + 30% improvement over existing methods so not bad at all. Things like super resolution imaging are also interesting. (Check out Eikon Therapeutics)
Not an expert here (even though actually a lot of this stuff was similar to the stuff I did in graduate school ages ago…) but:
The paper here is using a type of trick in quantum mechanics (“squeezed states” – The Wave Hunters - 04: Squeezed light - YouTube) to get around standard limits in measurement. This kind of squeezed state trick was also used in the LIGO detectors for gravitational waves: Squeezed States Expand Horizons for LIGO and Virgo | Optics & Photonics News
It may be one of the most important things. It gives us dozens of new ways to quantify aging and interventions to aging and makes everything far more understandable to people
Also better predictive analytics of toxicity of interventions before you try them.
Plus in THE NEAR FUTURE there will be new ML techniques to make biologists be able to do ML on the images without knowing ML.
Thus progress will happen just from biologists collecting ALL THE DATA on the intervention and then submitting images to a database that they can do ML on
Yeah, freeze tissue and then allow you to better quantify things that DON’T TAKE AS LONG AS LIFESPAN/LONGEVITY to quantify. look at the papers that relate to optical pooling at the broad (by david feldman). you can measure differences in spatial localization that give mechanistic insight. also CHANGES IN ORGANELLE SHAPE OVER TIME [THIS IS CRUCIAL FOR MEASURING AGING RATE CHANGES] - use cellprofiler or path.ai [or another ML algo on your data]. changes in the rate/noise at which the cell is able to deliver cargo to far reaches of the cell [also affected by aging]
MAKE SURE RESEARCHERS PUBLISH THEIR RAW IMAGES IN ADDITION TO THEIR RESEARCH PAPERS. This is the research that makes you want to REWRITE EVERY PAPER IN AGING and that makes biochem MUCH LESS BORING TO KIDS. this is how you get new kids obsessed with biochem
Also you can then better image changes in lipofuscin accumulation/protein aggregates over time and how INTERVENTION changes them, especially in yeast cells, in which case studies on intervention take shorter amounts of time. Measuring changes in epigenetic aging rate is “interesting” and a breakthrough that shortens the time it takes to measure age-related changes to units far smaller than those of a lifetime [important for accelerating progress], but gives very little mechanistic insight
do you read jennifer lippincot-schwartz?
also i’m sending this thread to matt kaeberlein to reply to. You may have asked one of the MOST important questions ANYONE can ask and demands a good response to inform design of future research experiments.
“will focus on how emerging fluorescent technologies are increasing spatio-temporal resolution dramatically, permitting simultaneous multispectral imaging of multiple cellular components. In addition, results will be discussed from whole cell milling using Focused Ion Beam Electron Microscopy (FIB-SEM), which reconstructs the entire cell volume at 4 voxel resolution. Using these tools, it is now possible to begin constructing an “organelle interactome”, describing the interrelationships of different cellular organelles as they carry out critical functions. The same tools are also revealing new properties of organelles and their trafficking pathways, and how disruptions of their normal functions due to genetic mutations may contribute to important diseases.”
^covers david feldman’s optical pooling paper!
I just noticed that all the links and papers above are far less boring than the standard molecular biology poster you see at a conference
My impression is that most aging labs don’t have access to super resolution microscopy but this is more fixable than they think it is… Imagine if every aging and toxicology paper had this level of detail…
Counter point: no.
Or, more charitably, achieving infinite precision at a single point in time without the 4D dynamical system context/reasoning/measurements won’t move the needle very much. It’s the uncertainty principle for biology and I’d much rather have way lower resolution but through time than the opposite.
And there’s so much low hanging fruit in that regard.
E.g. see all the failures of target driven drug design.
Failures of target-driven drug design have happened before modern techniques were developed but modern techniques may be the thing that uniquely rescues them from failure.
MECHANISM AND PHYSICAL INSIGHT IS CRITICALLY IMPORTANT.
Also, I’ve spoken to aging researchers on this - many don’t know how to use these latest technologies. You need the proper experimental design to use with spatial transcriptomics and i suspect it will come from outside perspectives (not many people can read or summarize all the papers I linked above - if I had money I would try to get a research assistant to summarize them and outline how to create an experiment with modern imaging techniques to make longevity research more insight-driven and less black-box, but I don’t know how many people can be trained to do this yet)
research - Kaganovich Lab might find it most useful
See? Michigan State Scientists Use AIMS Awards to Parse Autophagy
protein degradation IS one of the most important things controlling rate of aging, so understanding what enhances it/reduces it helps us modulate rate of aging
https://timrpeterson.wustl.edu/manuscript/2018/12/05/Omniphenotype.html
Measuring state transitions in single cells
So if the paths are pretty similar across ages, are the rates different? How can we even measure state transition rates in single cells? In previous work with Wallace Marshall, I developed a tool to infer cell states from cell behavior captured by timelapse microscopy. We found we could measure state transitions during early myogenic activation in that first paper. Measuring cell state transitions rates in aged vs. young cells was an obvious next step.
Eikon co-founders Eric Betzig, Robert Tjian, Xavier Darzacq, and Luke Lavis looked at this disconnect between life and biology and asked: What if we could add an extra dimension of capturing those images live, not as static snapshots, but as continuous live events, in order to better understand biological processes? Things like protein binding and resonance time, distances traveled and cellular location of molecules. And what if we process this all at high throughput and in a highly-automated way?
I think that you made a very important point Alex, that many researchers may not even have access to advanced imaging technology but it seems that it would be so useful to revisit and observe what effect specific therapies have at a cellular level.
Also, it looks like you referenced quite a few people who are doing research this way. I think it will be important to have people who can summarize the current research and draw conclusions because I think often times researchers may become hyperfocused or biased to their own specific niche.
Another question that I have been considering a lot lately is how presbyopia and cataracts form. These are age-related eye conditions which happen to everyone eventually. Traditionally it is taught that the lens in the eye grows like an onion and the cells in the middle are old, the lens then gets bigger, less flexible and cloudy. I don’t think this is the whole story because cataract progression is highly variable in the population and apparently at least somewhat modifiable by many substances. So long story short, I came across this paper and it describes the discrepancies between different measurement techniques and also between in vitro and in vivo findings.
(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871961/#__ffn_sectitle).
Also to the point about re-visiting the research, this paper is 10 years old and I couldn’t find anything recent with a better answer.
I think this is an important question because if the lens does indeed keep growing through life, like an onion, then it is going to be more difficult restore the youthful phenotype, but if it somehow maintains itself until damage accumulates then there is a potential to activate repair pathways. Also I think if the lens keeps growing, then treatment that is directed specifically to the lens will be needed, meaning that any single systemic therapy will be unlikely to fully restore the entire organism. Advances in vivo imaging could help find the answer to this important question.
https://www.bioimagingguide.org/02_Sample_acquisition/Resources.html
Really though, image the shapes of organelles in response to intervention (or as one paper wrote, C ELEGANS MOVEMENT COMPLEXITY CAN DECREASE WELL BEFORE MORBIDITY/DEATH => MAKING IT POSSIBLE TO MEASURE DIFFERENCES IN AGING RATE [IN RESPONSE TO INTERVENTION] IN A WIDE VARIETY OF ORGANISMS THAT HAVE LONGER-THAN-MOUSE-LIFESPANS)
Microscopy of mitochondrial cristae structures as a way to measue decreases in function (see gladyshev latest paper)
phenotype screening (this applies for all levels of microscopy )
- Cell age is a tricky phenotype to quantify — there isn’t a singular molecular marker we can rely on to predict all of the functional consequences of aging that we’re interested in. Rather than searching for a single molecular biomarker, NewLimit is building machine learning models that allow us to infer cell age from cell profiles (previously discussed in our February 2023 Progress Update).