Senescent cells stop producing nucleotides: new research
sciencedaily.com
sciencedaily.com
It's fun to speculate but to prove your case and make a real dent in human health problems is a lot harder than coming in late and saying "But wait, why don't you just..."
I heartily recommend going back to the great textbooks of these fields and reading them, rather than trying to understand things by dropping into the state of the art research (which is usually wrong, and hard to understand in detail).
Some books I recommend: The Biology of Cancer (Weinberg). After you read this book you'll have a better understanding of why doctors and scientists cringe when people say "cure cancer".
Molecular Biology the Cell (Alberts, etc). After you read this book you'll have a much better understanding of the full complexity that scientists have to deal with in complex cellular systems.
Molecular Biology of the Gene (watson, etc). Can't say much about this book except that's it's a classic reference.
What makes these three books exception is that they support all their factual claims with direct links to the papers that established the facts. And they provide you with the skills to evaluate modern research. But nothing compares to actually going to grad school and participating in the research- once you see how the grants are made, the experiments are, and the papers are written, you'll understand why trying to understand biology by press release is like trying to understand assembly language by watching a Steve Jobs product announcement.
I would suggest, especially for people interested in a relatively niche field like aging, that a good compromise is to read review articles. You can go to PubMed and filter by review articles to find them.
But I wholeheartedly concur that for non-experts to read primary research articles will cause much more confusion than clarity. And doubly so for press releases on those articles.
Molecular Biology of the Cell ed 6 is from 2014
Molecular Biology fo the Gene is a bit older and I would generally not recommend people read it, but the problem is (IMHO) the alternative, Genetics by Lewin, is genetics-oriented instead of molecular biology, and I find that most CS folks understand MB and find genetics confusing.
Review articles are good, but I still recommend starting with textbooks before moving on to reviews.
If I may ask, what's your background that tells you things like "most CS folks understand MB and find genetics confusing"?
What I've learned over the years is that genetics is a field where people who excel in abstract thinking about blobby, messy, wet objects succeed and understand the paradigms. While CS people find molecular biology, with its concerete focus on molecular entities (agents) interacting is very easy to understand. After many years of trying to understand genetics I finally realized that many of the paradigms in genetics are just useful but wrong models that don't correspond to reality.
I'm very guilty of thinking "don't we have enough approximations to brute force some solutions to problems in some parts of biology yet?" and your comment have helped provide some context that these are _hard_ problems and we are still gathering information to form better models in a lot of cases.
If you dont mind me asking, where so you work? (Happy to take it to a private channel as well if you prefer )
We are agreed on that. I shouldn't have said "out of date", which suggests what is in those books is invalid. What I should have said is "they don't really cover topics that are new or controversial and mostly only cover fundamentals".
In reality as you know each new edition of those books is 95% or more identical to the previous edition.
The only downside to this approach is that if people are interested in a particular topic like cell senescence, it's a bit harsh to say "go read these 5 textbooks that may have 2 pages on the subject before you even start looking into the topic you're interested in". And the Biology of Cancer? I'm published on several cell senescence papers and don't know jack about cancer. I own the book and skimmed it though. I think Hallmarks of Cancer review is a much better introduction than this tome. The other two are good fundamentals books though. For aging I recommend Handbook of the Biology of Aging.
FWIW, I do not know a single PhD student that read those books cover-to-cover. In most of my grad school classes you weren't even required to buy the textbook and they were barely used. Actually in grad school I never bought a single textbook for classes, although I did get some for personal use.
I consider that a feature when entering a new field. Once I have the fundamentals, it's much easier to read a paper and have at least a rough idea if it's a crackpot theory or the real deal. Without the fundamentals? No clue.
It is best to stick to the 3 to 10 range though until you know the ins and outs. Lots of Nature papers look exciting and turn out to be wrong. This is a rough guideline that varies by field.
PLoS One is a journal that publishes anything but has a decent impact factor so it is an exception to this rule. There are a few others but it generally holds true.
It's much better if you read the relevant parts of these books and then ramp up from there with the papers that are actually relevant to your studies/work.
With that being said, the Molecular Biology of the Cell and the Biology of Cancer are also very enjoyable (but challenging) reads just for satisfying your curiousity. But don't expect to finish these within a 3 months.
Those are the best topics to cover, especially for people starting out and wanting something solid. Anything after that is in flux and will end 90% bogus.
I had this exact experience, when I transitioned from working in big tech to working at a cancer research center. The scales are wildly different. In the time it’s taken me to write this comment, my body has generated nearly a billion new cells at 20GB of data per cell, or about 100 google web indexes worth of data. Very humbling. But also very fun!
From what I hear, this is not too rare. There is a large shortage of good programmers in biotech. Probably because the pay is a lot worse than in the tech industry.
I’d recommend new software engineers go work in tech and save money while the economy is hot, and then transition to bio tech when you are looking for some more challenging work and money isn’t as big a concern.
Reminds me of: "Can a biologist fix a radio?", http://protein.bio.msu.ru/biokhimiya/contents/v69/pdf/bcm_14...
Basically biology feels like a working but horribly written program with secret gotchas everywhere.
I left and went back to coding and mathematics. So easy to make progress. I can pretty much understand the whole system. Everyday I get something real done.
My sense is that this summary of the underlying article is missing something (not uncommon in scientific journalism), or this really isn't all that revolutionary.
I'd love for a better explanation of why this matters, or a better link?
It was probably something Dr. Judith Campesi, a pre eminent senesence scholar, wrote.
Unless you're a water bear your DNA accrues continuous and irreversible damage throughout life. End of the road is either cancer or senesence as an attempt to arrest cancer.
Edit: Can't believe I forgot the third option, cell death.
Here's some info from Dr. Rhonda Patrick and Dr. Judith Campisi when they got together for an interview.
> As our cells accumulate damage, which naturally happens as we age (even as a consequence of energy-generating processes and immune cell activation), there are only so many outcomes that we can expect. The first possibility is that the cells can die. The second is that they can become senescent – where they stop dividing, but stay alive, all-the-while secreting molecules that influence surrounding tissue. Or, the worst of all possible outcomes, the cells can go off the rails and become malignant.
> "Anything that persistent damage to the genome will drive cells into senescence. It makes sense because that puts you at risk for mutations. Mutation puts you at risk for cancer, so the cells want to shut that damaged cell down." - Dr. Judith Campisi
Also, there isn't just one kind of DNA damage or DNA repair. Different kinds of damage have different orders of badness of effects and have different priors of happening by our cellular machinery.
And the primary source/study: http://www.jbc.org/content/early/2019/05/28/jbc.RA118.005806
In fact I wouldn't believe you if you told me that was in fact the case.
What if you dug deeper and found that the steel-lacking factories were the ones which made the worst cars ?
I think that's the default analogy you should be making when you see cells "stopping".
This idea that cells that stop processing, or that undergo apoptosis (cell death) or are incapacitated by free-radical damage / oxidation should be "saved" is probably a mistaken one.
It's probably a much better outcome that they die.
For what it’s worth though, I think there are plenty of examples of car factories closing down because they are unable to secure a supply of raw materials. The machinery and the workers are all still there, but for whatever reason the owner stops sending steel to the plant and it shuts down.
Make of that analogy what you will.
No gas, that's why. How long will it take your cave man brain to figure that out?
The big thing here is that now they know that it is a lack of this particular substance causing the problem. Nobody could have guessed that this was the case. It is part of the debugging process. It provides a path for further discovery. Now they know where to focus their efforts.
does not imply
factory stops => no steel
Seeing that the factory has stopped, you need to determine whether it is because factory is lacking steel; or whether the effects of lack of steel consistent with current outage. This study seems to do this.
Wouldn't inhibiting nucleotide production already be explored well for cancer targets?
Isnt the only new thing here that they profiled and used senescent HMEC cells?
It seems they already had pharmaceutical and genetic means to target the protein already.
The more biology you learn, the cleverer the jokes get:
"""Emboldened by his successes, the next morning the geneticist tied of the hands of an individual dressed in a suit and carrying a briefcase in one hand and a laser pointer in the other (he was a vice president). That evening the geneticist, and Doug (although he would not openly admit it), anxiously awaited to see the effect on the cars. They speculated that the effect might be so great as to prevent the production of the cars entirely. To their surprise, however, that afternoon the cars rolled off the assembly line with no discemible effect.
The two scientists conversed late into the evening about the implications of this result. The geneticist, always having had a dislike for men in suits, concluded that the vice president sat around drinking coffee all day (much like geneticists) and had no role in the production of the automobiles. Doug, however, held the view that there was more than one vice president so that if one was unable to perform, others could take over his duties."""
(in biology, many processes have redundant components)
http://www.jbc.org/content/294/27/10564
It's also faster and easier. It's faster because it's shorter (2k vs 5k). It's easier because 'abstract format' is a tigher constraint than 'popular science story format'. (Much as Wikipedia entries are often easier than random web pages because they're constrained to a standard format.)
That article was like saying that geriatric people are observed to never go clubbing, and if you prevent young people from clubbing they mope around the house all day, so maybe if we get people to go clubbing every day they'll never grow old.
The abstract is a lot more reasonable and sensible, and concludes that (lack of) nucleotide synthesis does seem to play an important role in senescence. They were able to kick things back into action with telomerase. Enforced clubbing resources bed sores. No word yet on how many additional injuries it might trigger from ill-advised breakdancing.
"Scott Fraser and his lab worked with the research team to develop 3D imagery of the results. The images unexpectedly revealed that senescent cells often have two nuclei, and that they do not synthesize DNA."
Huh, the interesting part to me was that the senescent cells have two nuclei. Muscle cells fuse during development and have multiple nuclei, and they can't divide anymore either. I wonder if senescence happens due to mitosis being stopped short by some mechanism, and whether the multiple nuclei are a symptom or one mechanism by which cells enter senescence.
The development lifecycle also ends once a cell has differentiated into its ultimate tissue type. You don't want everything to be forever pluripotent.
Proliferation and pluripotency are classic markers for cancer.
According to Wikipedia, it looks like G-phase is part of interphase. During interphase, the cell isn't actually in the process of dividing, right? Wouldn't it be more likely that a senescent cell would have two nuclei if there was an error during telophase, right before cytokinesis?
Am I the only one wondering if this person is confusing cause and effect?
No you are not. I work in this field and confusions of cause and effect are a daily occurrence. It is as dumfoundedd said, the reality is that aging is a complex causal network. I think everyone knows that but can't resist the temptation to pretend like the one edge they are working on in the network is the end-all.
It can get very ridiculous. At this year's aging meeting someone was actually proposing DNN predictions of age based on people's faces as a gold standard for biomarkers of aging. That is, they were suggesting people's faces were a better indicator of their internal biological state of aging than both their actual age and any internal biological marker.
Metagenomics is another one, although more debatable. I personally find it much more plausible that changes in the aging gut cause changes in the microbiome than the reverse (in general).
Horvath's epigenetic clock is another one, he presented a elastic net model that could predict age based on DNA methylation using a few hundred loci. For several years and even now, way too many investigators thought those loci were actually causal in aging because they don't understand how statistics work.
It annoys me. I have long considered writing a review to remind people what causality means. It is far too common for people to observe correlations and just straight to predicting causality without any additional evidence besides the correlation.
The interesting finding of this paper is that inhibition of nucleotide synthesis can induce senescence. But the (simplistic) definition of senescence is inability to replicate. You can't replicate without nucleotides, but this doesn't at all mean that the ordinary cause of senescence is lack of nucleotides. The common understanding is that it is G1 or G2 arrest due to DNA damage of one sort or another. Furthermore, the observation that senescent cells don't produce many nucleotides is kind of a duh. It is useful and important that they quantified it, but still it is hardly surprising.
But there is still hope. I just saw my chair in the hall, told him about this paper, and asked his opinion of the idea that "fixing nucleotide synthesis may help reduce cell senescence or help cells age more slowly". His response was to laugh, pat me on the shoulder, and walk away, if that says anything.
Once the squirrel starts to stink, bury it.
It may be true that slowing down loss of nucleotide synthesis, while not fixing the root cause, may still slow down the aging process. Just like giving Parkinson's patients L-DOPA doesn't resolve the root cause of the disease; it's treating the effect and not the cause. But there isn't really anything better out there (AFAIK), and it slows down the brain degeneration process by replenishing one of the important things that gets destroyed in the degeneration, just as fixing nucleotide production may slow down cell degeneration. It's a very imperfect solution, but it still provides some relief for many people. We've got to work with what we've got.
Probably the first result would be cancer.
Cannibalizes any under-performing cells.
Disclaimer: I am not a scientist and nobody should self experiment. I simply reached a dead end with doctors and won't accept "nothing can be done" as a valid answer.
^ From the article. Yet, when I check the linked journal entry:
> Inhibition of nucleotide synthesis promotes replicative senescence of human mammary epithelial cells
^ journal article title, which seems somewhat the reverse of the article claim.
> To test whether cellular immortalization would reverse these observations, we expressed telomerase in HMECs. In addition to preventing senescence, telomerase expression maintained metabolic flux from glucose into nucleotide synthesis pathways. Finally, we investigated whether inhibition of nucleotide synthesis in proliferating HMECs is sufficient to induce senescence.
^ From the journal article abstract. This states NONE of the "took young cells and..." claims from the article, but rather the opposite.
> Taken together, our results suggest that nucleotide synthesis inhibition plays a causative role in the establishment of replicative senescence in HMECs.
Umm...unless I'm missing something, this is literally taking correlation and determining causation.
TL;DR: This looks like an exploratory data point in the "how does the telomere clock actually cause senescence in a cell". While this COULD lead to some "new" treatment, vast issues remain, including both "is this the sole cause", "is this actually relevant", and "if this is the Big Cause, what could we do about it anyway?"
Yes. But when you're in a machine as complex as a cell and trying to figure out how to stop some process, if you can find a correlation, it's at least worth a try to treat that as causation. It's much better than picking a random answer.
Where we go wrong is when the game of telephone gets played and the correlation gets locked in as the official causation answer. But technically, "I see a correlation between A and B, therefore I hypothesize that the cause of the correlation is that A causes B" is at least a good first hypothesis. (The moreso when "B causes A" is not plausible for some reason.)
I don't think the study was a bad thing at all (from my limited understanding), but the article was...a poor representation of it.
Paul Graham's essay "The Submarine" is quite instructive here.
No, it isn't. Or if it is, it's barely better, not much better. See my lengthier reply above.
The reason why this is false is because in biology, there is an enormous correlation structure in which, to a good approximation, everything is correlated with everything. If you take a random gene, its expression will be significantly correlated or anticorrelated with well over half of all other genes. Probably over 80% if I remember correctly. Depends on the number of samples, if you get into 10K+ samples it approaches 100%.
In an area like aging, skin wrinkling is correlated with sarcopenia is correlated with atherosclerosis is correlated with number of senescent cells is correlated with all kinds of gene and metabolite expression levels etc ... you get the idea.
In genetics a SNP will be correlated with hundreds of thousands of other SNPs.
I guess you can go so far as to say correlations can generate hypotheses. People certainly do this all the time. But "a correlation is tentative evidence of direct causation" is just wrong. Technically it is evidence, it's just that in my experience in biology it is such weak evidence as to be useless without other evidence.
Yes, but not all at the same ratios; it is not the case that literally everything is correlated to everything else to 99.9%. When people say "everything is correlated with everything" they mean that 60%s and 70% and 80%s show up in a large number of places, it does not literally mean that for every two possible processes the correlation is 99.9%. It's not practical to set up a large correlation net with that strong a correlation everywhere unless it really is all the same thing. (It might be mathematically possible, but it's not something you're going to encounter naturally.)
You're still better off choosing something that is very strongly correlated, because you have still shaved off huge swathes of the possibility space to start with which is much less likely to be directly involved. Yes, you still have a decent chance of being wrong, but you also have to remember that in the process of being wrong, you will gather more data. (Well... assuming that you actually listen to the data and don't hide behind some scientific dogma, but that's another discussion.) You're better off choosing something and probing than sitting there, agog at the net of correlations, and being paralyzed by the possibilities. Get in there and start shaving them off, and start with your best guesses, even if they're only your best guesses by a little bit.
This is the part where they took young cells and stopped them from producing nucleotides, and it's also what's described in the paper title.
"This is your research on P-hacking."
"Just say no to P-hacking!"
Once you are aware of the problem, you have three choices that I could see: (1) roll the dice and legitimately win the lottery of objective truth discovery, (2) consciously be evil in order to feed your family, or (3) escape and go find another flawed system to feed yourself.
So I chose (3) and went to med school.
Acquaintance of mine runs this thing, and is very passionate on the topic.