1. Why different animals live for different lengths of time 🐁🧫🦇

The lecture starts by comparing lifespans of different organisms: yeast, C. elegans, mice, insects (e.g. ants, bees), bats, mini-pigs, etc. The point is not precise numbers, but to illustrate the huge variation in lifespan even among similarly sized animals.

Key ideas:

• Short-lived models (yeast, C. elegans, flies):
  • Lifespan in days to weeks.
  • Very attractive for studying aging because you can observe full life cycles and genetic effects quickly.
  • Practical for a master’s project: you can actually finish an aging experiment within your thesis timespan.
• Longer-lived mammals (mice, mini-pigs, bats, etc.):
  • Mice live ~2–3 years, mini-pigs around 10–15 years; bats can reach several decades.
  • Similar body size does not guarantee similar lifespan (e.g. bat vs mouse).
  • Indicates that aging rate is biologically regulated, not simply a function of body size or metabolic rate.
• Queens vs workers (e.g. in social insects):
  • Queens can live ~30 years while workers with the same genome live ~months to a year.
  • This shows that lifespan can be dramatically modulated by environment and signaling (e.g. hormones, insulin-like signaling), not just by DNA sequence.

Conclusion: Lifespan is highly plastic, and that’s exactly why model organisms are powerful: we can map which genes and pathways shift lifespan so dramatically.

2. Choosing the right model organism: it depends on the question 🧪

A recurring theme:

“The best model depends on what you’re trying to study.”

Examples:

• Heart disease:
  • C. elegans has no heart and no circulatory system.
  • So C. elegans is a poor model for questions that need a heart (e.g. cardiac physiology, heart failure).
  • Mice, pigs, etc. are much better for that.
• Genetics of aging, stress resistance, protein aggregation:
  • C. elegans is excellent:
    • Short lifespan (≈3 weeks).
    • Huge genetic toolbox (mutants, RNAi, CRISPR, transgenics).
    • Large numbers and low cost.
    • Fewer ethical concerns than mammals.
• Ethical and practical considerations:
  • High-throughput screening in monkeys would be ethically unacceptable and financially impossible.
  • Worms and flies allow large-scale screens for genes or drugs that influence lifespan or health.

So model choice is not “what’s closest to humans?” but “what system is good enough to answer this specific mechanistic question?”

3. Aging vs lifespan: survival curves and the NDD-4 mutant 📉

In practice, when people say they “study aging in C. elegans,” they mostly measure lifespan and treat it as a proxy for aging.

Survival curves

• Start with a population (e.g. 100 worms).
• Every day, score how many are alive vs dead.
• Plot:
  • x-axis: age (days).
  • y-axis: fraction of animals alive.
• A right-shifted curve = longer lifespan.
• A left-shifted curve = shorter lifespan.

Example from the lecture:

• Wild type (black circles) vs a mutant called NDD-4 (triangles).
• At the time when all wild types are dead, ~80% of NDD-4 mutants are still alive.
• This indicates a strong lifespan-extension phenotype, suggesting that NDD-4 is involved in pathways that regulate aging.

So “aging” in this context is operationalized as “how long does the population survive” plus some functional metrics (see healthspan below).

4. Age-related phenotypes in C. elegans that mirror humans 🧓🐛

Old worms are clearly distinguishable from young ones, just like old vs young humans.

Major age-related changes:

1. Reduced movement and muscle loss (sarcopenia)
   • Worms move less and less with age.
   • Linked to loss of muscle mass and structural damage in muscle cells.
   • Parallels human sarcopenia in the elderly.
2. Nervous system decline
   • Neuronal function and connectivity deteriorate.
   • Sensory perception and behavior become impaired.
3. Loss of proteostasis
   • Misfolded proteins accumulate.
   • Aggregates form and cause cellular stress.
   • Very similar to what happens in:
     • Alzheimer’s disease,
     • Parkinson’s disease,
     • Huntington’s disease, etc.
4. Lipofuscin accumulation
   • “Age pigment” from oxidized lipids and proteins (lipofuscin).
   • Autofluorescent material that accumulates in long-lived cells; a marker of oxidative damage.
5. Memory loss
   • Worms also lose the ability to form/retain certain simple memories with age.
   • This makes them a useful system for studying age-related cognitive decline at a basic level.

Conclusion: Many cellular and physiological hallmarks of human aging are recapitulated in worms, just compressed into ~3 weeks instead of decades.

5. Mechanisms known to influence lifespan 🧬🥗⚡

A large number of conserved mechanisms affect lifespan across species, including C. elegans.

5.1 Dietary restriction (DR)

• Reducing calorie intake (≈30%) without causing malnutrition:
  • Robustly increases lifespan in many species (yeast, worms, flies, rodents, probably also humans).
  • Hard to implement in humans long term because of compliance issues.
• DR is linked to nutrient-sensing pathways like TOR and insulin/IGF signaling, and to autophagy.

5.2 TOR signaling and autophagy

• TOR (Target of Rapamycin): nutrient and growth factor sensor.
• When nutrients are scarce:
  • TOR is downregulated → autophagy is activated.
• Autophagy = cellular self-eating:
  • Damaged proteins and organelles are degraded and recycled.
  • Essential for cellular quality control.
• Lifespan extension by DR or TOR inhibition usually requires functional autophagy:
  • Blocking autophagy prevents lifespan extension in many models.
  • Longer-lived animals generally show better recycling and cleanup capacity.

5.3 Mitochondrial function and bioenergetics

• Mitochondria provide ATP and also generate reactive oxygen species (ROS).
• Both too little and too much mitochondrial activity can be harmful.
• Subtle changes in mitochondrial function can modulate lifespan, often via stress signaling pathways.

5.4 Proteostasis and stress resistance

• Proteostasis: maintaining correctly folded and functional proteins.
• Long-lived mutants:
  • Typically handle misfolded proteins better.
  • Induce chaperones and stress response pathways more efficiently.
  • Show increased resistance to:
    • Heat shock,
    • Oxidative stress,
    • Other environmental stresses.
• Almost all known long-lived mutants are also more stress resistant; there is only one reported exception, which the lecturer suggests might be an error.

All these mechanisms converge: longer life usually correlates with better stress handling, better damage repair, and better metabolic regulation.

6. Hallmarks of aging and C. elegans 📚

The field has summarized aging biology into a set of “hallmarks of aging”, originally 9 and later expanded. To qualify as a hallmark, a process must:

1. Change with age.
2. Modulating it (up or down) must affect lifespan.

Key hallmarks mentioned:

• Genomic instability
• Telomere attrition (shortening of telomeres)
• Epigenetic alterations
• Loss of proteostasis
• Disabled macroautophagy
• Deregulated nutrient sensing
• Mitochondrial dysfunction
• Cellular senescence
• Stem cell exhaustion
• Altered intercellular communication
• Chronic inflammation
• Dysbiosis (imbalanced gut microbiota)

In C. elegans:

• Most of these processes are found as well.
• Exception: classical telomere dynamics are somewhat different/less relevant in C. elegans compared to humans.
• This overlap supports the idea that insights from worms are relevant to human aging, not just idiosyncratic features of a weird little worm.

7. Insulin/IGF signaling and aging: DAF-2 → PI3K → DAF-16 🧬🧠

One of the best-characterized longevity pathways is insulin/IGF signaling (IIS).

7.1 The pathway in C. elegans

Simplified IIS cascade:

• DAF-2: insulin/IGF receptor homolog (like the insulin/IGF-1 receptor in mammals).
• AGE-1 / PI3K (H1 in the transcript): phosphoinositide 3-kinase downstream of DAF-2.
• Downstream kinases (e.g. AKT-like kinases) phosphorylate DAF-16.
• DAF-16: FOXO transcription factor.

Key relationships:

• When IIS is high:
  • DAF-16 is phosphorylated and retained in the cytoplasm.
  • Longevity genes under DAF-16 control are suppressed.
• When IIS is reduced (e.g. DAF-2 mutants, PI3K mutants, DR-like states, certain stresses):
  • DAF-16 moves into the nucleus.
  • DAF-16 activates a gene expression program that:
    • Enhances stress resistance,
    • Improves proteostasis,
    • Modulates metabolism,
    • Ultimately increases lifespan.

Crucial experimental observation:

• All mutations that reduce IIS and extend lifespan require DAF-16.
  • If you remove DAF-16 in a long-lived DAF-2 mutant, lifespan goes back to normal.
  • Thus, DAF-16 is epistatic to DAF-2 and other IIS components for lifespan.

7.2 Conservation and human relevance

• The core pathway is conserved from worms to mammals.
• In humans, FOXO variants are enriched in centenarians (people ≥100 years old).
• Strong evidence that IIS/FOXO is a central, conserved regulator of organismal aging.

8. Watching DAF-16 in action: GFP and nuclear translocation 🔬✨

Because DAF-16 is a transcription factor whose location (cytoplasm vs nucleus) changes with signaling, it is a convenient biosensor for IIS activity.

• Researchers create DAF-16::GFP worms:
  • DAF-16 protein is fused to GFP.
• Under normal/high IIS:
  • GFP signal is diffuse in the cytoplasm.
• Under stress or reduced IIS:
  • GFP signal becomes nuclear, visible as bright spots in nuclei.

This gives a simple readout:

• If a mutation or drug pushes DAF-16 into the nucleus, it likely reduces IIS or triggers stress pathways.
• You can test whether a treatment acts via IIS by following DAF-16::GFP localization in live worms.

9. GFP reporters: translational vs transcriptional 🧬💡

The lecture distinguishes two important types of GFP reporters used to analyze gene expression and protein localization.

9.1 Translational reporters

• Construct: promoter – ORF (gene) – GFP.
• Outcome:
  • The actual protein is produced with a GFP tag.
• What you learn:
  • Where the protein itself is localized in the animal (subcellular compartments, tissues).
  • Dynamics of protein localization under different conditions.

9.2 Transcriptional reporters

• Construct: promoter – GFP (no coding region of the original protein).
• Outcome:
  • GFP is expressed whenever the promoter is active.
• What you learn:
  • Where and when the gene is transcriptionally active, but not where the protein ends up.

Both types are essential tools:

• To see if a pathway is activated by an intervention (gene, drug, stress).
• To map developmental expression patterns.
• To link behavior/phenotypes (e.g. defective movement) to underlying tissue defects (e.g. motor neurons vs muscle).

10. Neuronal GFP and motor neurons controlling movement 🧠➡️💪

An example from the lecture: a GFP reporter labeling cholinergic motor neurons.

• The worms’ head contains a dense neural structure called the nerve ring (analogous to a simple “brain”).
• Along the body, motor neurons run in longitudinal cords.
• These motor neurons synapse onto muscle cells and coordinate the S-shaped sinusoidal movement typical of C. elegans.

Using GFP-labeled neuronal strains, researchers can:

• Count neurons, assess their morphology, and check if connections form correctly.
• Correlate abnormal movement with:
  • Defects in motor neurons, or
  • Alternatively, defects in muscles.

This is crucial for separating neurogenic vs myogenic causes of movement disorders in mutants.

11. Visualizing muscle and other tissues: phalloidin and antibodies 🧫

Beyond GFP, other staining methods are used:

11.1 Phalloidin staining of muscle

• Phalloidin binds specifically to F-actin.
• Used to visualize muscle fibers in fixed worms:
  • You see parallel muscle bands along the body wall.
• Excellent for:
  • Assessing muscle structure,
  • Detecting age-related muscle degeneration, fragmentation, or loss of organization.

Limitations:

• Requires fixation and permeabilization → worms must be killed.
• In contrast, GFP-based reporters can be imaged in live worms.

11.2 Antibody staining

• You can use primary antibodies (e.g. generated in a collaborator’s lab) to mark specific antigens.
• Example from the lecture:
  • An antibody stains only a subset of cells in embryos.
  • Those cells later become gut cells.
  • Even if the antigen is unknown, this immediately gives a powerful cell lineage marker.

Often combined with DAPI (DNA stain) to see nuclei and confirm cell counts.

These tools, together with genetics, allow detailed mechanistic dissection of developmental and aging processes.

12. From mutagenesis to RNAi to CRISPR: how technology shapes aging research 🧪🔧

The history of worm aging research nicely illustrates how tools change what questions we can ask.

1. Classical mutagenesis (early era)
   • Random mutagenesis, then screen for interesting phenotypes (e.g. dauer formation, altered development).
   • Some mutants later were found to live longer.
   • Tom Johnson proposed intentionally looking for long-lived mutants; many initially thought this was naive because aging was seen as too complex.
   • He eventually identified age-1, which turned out to be a PI3 kinase (part of IIS).
2. RNA interference (RNAi) revolution (~20 years ago)
   • Systematic gene knockdown became possible.
   • Allowed genome-wide RNAi screens for genes that extend lifespan.
   • This greatly expanded the set of candidate longevity genes (hundreds of genes, many in related pathways).
3. Small-molecule / compound screens
   • Companies and labs began screening for drugs that increase lifespan or healthspan, often in worms first.
   • Attracted huge interest (e.g. tech billionaires funding anti-aging therapeutics).
4. CRISPR/Cas9 (recent era)
   • Precise genome editing became straightforward in worms.
   • Instead of random mutations, researchers can:
     • Edit specific genes,
     • Model human disease variants,
     • Tag endogenous proteins with GFP, etc.

Overall: As tools improved, the field moved from “find whatever random mutant lives long” to precise testing of hypotheses and pathways.

13. Epistasis analysis in IIS: positioning NDD-4 in the pathway 🔗

The lecture revisits epistasis using the NDD-4 mutant and IIS components.

Key logic:

• If a mutant (e.g. NDD-4) extends lifespan, we want to know:
  • Does it act within the IIS/DAF-16 pathway?
  • Or does it act independently of IIS?

13.1 Using DAF-16 loss-of-function

• DAF-16 is required for IIS-mediated lifespan extension.
• Experiment:
  1. Start with long-lived NDD-4 mutant.
  2. Introduce a DAF-16 loss-of-function mutation.
  3. Measure lifespan of the double mutant.
• Interpretation:
  • If lifespan goes back to wild-type → NDD-4 acts through DAF-16/IIS.
  • If lifespan remains long → NDD-4 acts independently of DAF-16.
  • In reality, they got an intermediate result:
    • Part of the lifespan benefit disappears, but not all.
    • Conclusion: NDD-4 has both DAF-16–dependent and DAF-16–independent effects.

13.2 Combining NDD-4 with DAF-2 mutants

• DAF-2 mutants are strongly long-lived.
• Experiment:
  • Knock down DAF-2 and also mutate NDD-4.
  • Ask whether lifespan is longer than in DAF-2 alone.
• Result:
  • The double combination produces a synergistic lifespan extension, approaching ~100 days or more (in other studies, up to ~250 days vs ~21 days in wild type).
• Interpretation:
  • NDD-4 acts partly in parallel to IIS.
  • When both pathways are perturbed, the combined effect on lifespan is dramatically enhanced.

Epistasis here is used not only to place genes in a linear pathway but also to reveal parallel, interacting longevity pathways.

14. From lifespan to healthspan: not just living longer, but living better 💚

The field has shifted from focusing only on lifespan to also considering healthspan: how long an organism remains healthy and functional.

Key question:

Is it useful to live to 120 if the last 30 years are spent frail and bedridden?

In worms, healthspan can be assessed by:

• Stress resistance:
  • Survival under heat shock, oxidative stress, etc.
• Immune and pathogen resistance:
  • Ability to resist bacterial infections.
• Neuronal health:
  • Retention of normal behavior and sensory responses.
• Muscle function:
  • Ability to move normally as they age.
• Intestinal barrier integrity:
  • Whether the gut barrier still prevents bacteria from spreading throughout the body.
• Reproductive health:
  • Whether worms can reproduce later in life and how well.

Some long-lived mutants are frail (barely moving, sickly), while others retain youthful function. Healthspan metrics distinguish between these cases.

15. Quantifying healthspan with movement tracking 📹📊

A concrete example of healthspan measurement is movement/activity tracking.

• Put worms in liquid.
• Record their movement on video.
• Use a worm tracker software to automatically count:
  • Body bends (thrashes) per unit time.

Observations:

• In wild-type worms:
  • Activity declines with age; they thrash less and less.
• In some long-lived mutants:
  • Movement remains high at advanced age → good healthspan.
• In others:
  • Lifespan is extended, but movement is minimal → poor healthspan.

Thus, movement quantification is a simple high-throughput readout of healthspan, complementing lifespan data.