Periodic Reporting for period 4 - NoisyAgeing (Beyond genotype to phenotype: how ancestor lifestyle impacts on lifespan variation in descendants)
Période du rapport: 2019-12-01 au 2021-06-30
The dramatic increase in the global population’s age is good news. However, society must prevent the financial burden and personal suffering of unhealthy ageing. But how can we study a complex problem such as ageing?
Using simple model organisms -such as the nematode C.elegans- has proven to be a good strategy because many genes that influence ageing are shared with humans.
The discovery that genes control longevity has been quite significant however, thousands of genes participate in this complex process and the environment can probably explain the high degree of discordance in lifespan among identical twins.
Based on these unresolved issues, the two main goals of this project were to understand the non-genetic and environmental influences on lifespan and stress related phenotypes using C. elegans as a model organism.
and to develop in silico predictive tools to simply the complexity.
With regards to the first objective of this project, if one is to study the environmental and stochastic influences on ageing, then a key question is how do we sense and respond to changes in the environment.
Endotherms -such as mammals and birds- can control body temperature by using a skin-brain thermostat system. By contrast, ectotherms -such as reptiles, fish, and invertebrates-
cannot control their own body temperature. This is problematic for cell membranes, consisting primarily of fats, extremely sensitive to temperature.
This raises the question: How do cell membranes adapt to temperature change? Work in bacteria, and subsequently in multicellular animals, show that they use a strategy -named homeoviscous adaptation- which w
under warm temperatures helps to compact the lipid bilayer by using specific fats/lipids. Multicellularity, however, poses additional challenges because membrane lipids are only produced and kept in specialized fat storage tissues.
The question then is: how do distant tissues get the desired lipids to remodel their membranes?
We took advantage of many genetic tools available in C.elegans to discover that neurons co-opted an ancient heat sensing system to record ambient temperature.
When exposed to heat stress, cells activate Heat Shock factor 1 (HSF-1), which rapidly induces the expression of heat shock proteins involved in chaperoning and refolding heat-damaged proteins.
We find that HSF-1 works in neurons to coordinate a complex neuro-hormonal response to stimulates the gut to produce fats that are better suited for warm temperatures
This sophisticated response allows worms to survive and live longer under warm conditions.
We also developed technologies to accurately follow the variability in the expression of stress proteins in worms,
and future work will further elaborate in the causes and consequences of this variability for the survival of worms.
With regard to the second objective of this project, there are two main conceptual and technical challenges that apply to the study of ageing in model organisms. First: even for short-lived animals such as worms, experiments are costly in terms of time.
Second, ageing is a highly complex process with thousands of genes involved and to improve understanding,
we need to study the overall organisation of the system.
We therefore developed two in silico models to improve computational predictions of both metabolic fluxes and gene regulatory interactions.
Metabolism can be defined as the chemical reactions in the cells that change food into energy. The passage of metabolites through a chain of enzymatic reactions is called metabolic flux.
Long-lived animals are thought to use less energy at rest, but how metabolic fluxes change with age and how they operate in long lived animals is not fully understood.
Our lab advanced computational methods to improve the study of metabolism as a system by improving annotation and methods to quantify fluxes using genome wide metabolic modelling.
Gene regulatory interactions can be defined as a collection of molecular regulators that interact with each other to determine the expression of genes that regulate the function of the cell.
To simplify a complex problem, we computed the largest network of gene regulatory interactions that characterise a long-lived Notch receptor mutant in worms and used network analysis to discover that the flow of information resembles an hourglass structure (see diagram 2).
We then performed in silico and genetic screens to demonstrate that the genes that have the largest influence in the lifespan of worms are all concentrated at the core of the network. This strategy allowed us to discover 50 new ageing genes, 86% of them with human orthologues.
We have established a framework with predictive power that can accelerate gene discovery in the question of ageing in C. elegans and potentially in humans.
Using simple model organisms -such as the nematode C.elegans- has proven to be a good strategy because many genes that influence ageing are shared with humans.
The discovery that genes control longevity has been quite significant however, thousands of genes participate in this complex process and the environment can probably explain the high degree of discordance in lifespan among identical twins.
Based on these unresolved issues, the two main goals of this project were to understand the non-genetic and environmental influences on lifespan and stress related phenotypes using C. elegans as a model organism.
and to develop in silico predictive tools to simply the complexity.
With regards to the first objective of this project, if one is to study the environmental and stochastic influences on ageing, then a key question is how do we sense and respond to changes in the environment.
Endotherms -such as mammals and birds- can control body temperature by using a skin-brain thermostat system. By contrast, ectotherms -such as reptiles, fish, and invertebrates-
cannot control their own body temperature. This is problematic for cell membranes, consisting primarily of fats, extremely sensitive to temperature.
This raises the question: How do cell membranes adapt to temperature change? Work in bacteria, and subsequently in multicellular animals, show that they use a strategy -named homeoviscous adaptation- which w
under warm temperatures helps to compact the lipid bilayer by using specific fats/lipids. Multicellularity, however, poses additional challenges because membrane lipids are only produced and kept in specialized fat storage tissues.
The question then is: how do distant tissues get the desired lipids to remodel their membranes?
We took advantage of many genetic tools available in C.elegans to discover that neurons co-opted an ancient heat sensing system to record ambient temperature.
When exposed to heat stress, cells activate Heat Shock factor 1 (HSF-1), which rapidly induces the expression of heat shock proteins involved in chaperoning and refolding heat-damaged proteins.
We find that HSF-1 works in neurons to coordinate a complex neuro-hormonal response to stimulates the gut to produce fats that are better suited for warm temperatures
This sophisticated response allows worms to survive and live longer under warm conditions.
We also developed technologies to accurately follow the variability in the expression of stress proteins in worms,
and future work will further elaborate in the causes and consequences of this variability for the survival of worms.
With regard to the second objective of this project, there are two main conceptual and technical challenges that apply to the study of ageing in model organisms. First: even for short-lived animals such as worms, experiments are costly in terms of time.
Second, ageing is a highly complex process with thousands of genes involved and to improve understanding,
we need to study the overall organisation of the system.
We therefore developed two in silico models to improve computational predictions of both metabolic fluxes and gene regulatory interactions.
Metabolism can be defined as the chemical reactions in the cells that change food into energy. The passage of metabolites through a chain of enzymatic reactions is called metabolic flux.
Long-lived animals are thought to use less energy at rest, but how metabolic fluxes change with age and how they operate in long lived animals is not fully understood.
Our lab advanced computational methods to improve the study of metabolism as a system by improving annotation and methods to quantify fluxes using genome wide metabolic modelling.
Gene regulatory interactions can be defined as a collection of molecular regulators that interact with each other to determine the expression of genes that regulate the function of the cell.
To simplify a complex problem, we computed the largest network of gene regulatory interactions that characterise a long-lived Notch receptor mutant in worms and used network analysis to discover that the flow of information resembles an hourglass structure (see diagram 2).
We then performed in silico and genetic screens to demonstrate that the genes that have the largest influence in the lifespan of worms are all concentrated at the core of the network. This strategy allowed us to discover 50 new ageing genes, 86% of them with human orthologues.
We have established a framework with predictive power that can accelerate gene discovery in the question of ageing in C. elegans and potentially in humans.
Dissemination in the form of open-access Publications:
1. Novel methods for high throughput detection of inter-individual variability in C. elegans gene expression.
• doi:10.1371/journal.pgen.1008638
• doi:10.3791/ 61132
• doi: 10.3791/61136
• DOI: 10.1042/EBC20160025
2. We have discovered that neuronal stress influences neuro-hormonal responses that influence fat metabolism:
• https://doi.org/10.1371/journal.pbio.3001431(s’ouvre dans une nouvelle fenêtre)
• doi: 10.1016/j.cub.2019.06.031.
• DOI:https://doi.org/10.1016/j.devcel.2020.10.024
3. Our unpublished work refers to statistical methods methods to quantify the variability of neuronal stress and the consequences for survival:
• "Inter-individual variability in neuronal stress responses drives phenotypic heterogeneity in isogenic worms". Chauve L, Vallejo C, Murdoch S, Todtenhaupt P, Biggins L, Marioni J, Casanueva, O. Manuscript in preparation.
4. Development of in silico methods to study complexity in ageing worms
To study of Complex Metabolic Fluxes:
• DOI=10.3389/fmolb.2018.00096
• DOI=10.3389/fmolb.2019.00002
• https://doi.org/10.1016/j.coisb.2018.11.005(s’ouvre dans une nouvelle fenêtre)
To study of Gene regulatory networks in a longevity model:
• "Gene Regulatory Network inference in long-lived C. elegans reveals modular properties that are predictive of novel ageing genes" (2021) Suriyalaksh M, Raimondi C, Mains, Segonds-Pichon A, Mukhtar S, Murdoch S, Aldunate R, Krueger F, Guimerà R, Andrews S, Sales-Pardo M*
Casanueva O* (2021) iScience in press (* shared first and last authors)
Dissemination in other forms
15 Academic presentations 6 events related to the organisation of Workshops and Conferences, 14 Public engagement events
1. Novel methods for high throughput detection of inter-individual variability in C. elegans gene expression.
• doi:10.1371/journal.pgen.1008638
• doi:10.3791/ 61132
• doi: 10.3791/61136
• DOI: 10.1042/EBC20160025
2. We have discovered that neuronal stress influences neuro-hormonal responses that influence fat metabolism:
• https://doi.org/10.1371/journal.pbio.3001431(s’ouvre dans une nouvelle fenêtre)
• doi: 10.1016/j.cub.2019.06.031.
• DOI:https://doi.org/10.1016/j.devcel.2020.10.024
3. Our unpublished work refers to statistical methods methods to quantify the variability of neuronal stress and the consequences for survival:
• "Inter-individual variability in neuronal stress responses drives phenotypic heterogeneity in isogenic worms". Chauve L, Vallejo C, Murdoch S, Todtenhaupt P, Biggins L, Marioni J, Casanueva, O. Manuscript in preparation.
4. Development of in silico methods to study complexity in ageing worms
To study of Complex Metabolic Fluxes:
• DOI=10.3389/fmolb.2018.00096
• DOI=10.3389/fmolb.2019.00002
• https://doi.org/10.1016/j.coisb.2018.11.005(s’ouvre dans une nouvelle fenêtre)
To study of Gene regulatory networks in a longevity model:
• "Gene Regulatory Network inference in long-lived C. elegans reveals modular properties that are predictive of novel ageing genes" (2021) Suriyalaksh M, Raimondi C, Mains, Segonds-Pichon A, Mukhtar S, Murdoch S, Aldunate R, Krueger F, Guimerà R, Andrews S, Sales-Pardo M*
Casanueva O* (2021) iScience in press (* shared first and last authors)
Dissemination in other forms
15 Academic presentations 6 events related to the organisation of Workshops and Conferences, 14 Public engagement events
This project successfully pushed the boundaries of the state of the art in the field in several ways.
First, by developing methodologies including new ways to measure and quantify
inter-individual variability in gene expression and to measure and new in silicon methods to study metabolic fluxes in ageing metazoans.
In addition, we discovered a novel mechanism that helps ectotherms sense and transmit information regarding environmental heat
and computed the largest gene regulatory network of a longevity pathway with high predictive power for gene discovery.
First, by developing methodologies including new ways to measure and quantify
inter-individual variability in gene expression and to measure and new in silicon methods to study metabolic fluxes in ageing metazoans.
In addition, we discovered a novel mechanism that helps ectotherms sense and transmit information regarding environmental heat
and computed the largest gene regulatory network of a longevity pathway with high predictive power for gene discovery.