Property:Pre-meeting notes
From Complex Time
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H
Caloric restriction (CR) delays aging and the onset of age-related disease in diverse species, including nonhuman primates. Emerging data has focused our studies on links between metabolic status and disease vulnerability; several diseases of aging including diabetes, cancer, and neurodegeneration, have an established metabolic component. Candidate factors involved in longevity regulation are nutrient sensitive and interconnected in terms of signaling pathways and downstream effector actions. Molecular profiling of the transcriptome, proteome, and metabolome identifies CR responsive elements that are highly enriched for metabolic pathways. Here too connectivity among responsive nodes, or mega clusters, is complex. Our recent work shows that small changes in metabolic status precipitate large-scale multi-modal functional changes across diverse cellular processes. We suggest that modest failures in metabolic integrity are amplified by such mechanisms with age to broadly impact homeostasis and adaptation, creating shared vulnerability to diseases and conditions despite differences in their etiology. +
A
Aging in Single-celled Organisms: from Bacteria to the Whole Tree of Life/Toward a Molecular Understanding of Quiescence versus Senescence +
Cellular aging is often used synonymously with cellular senescence, a state of permanent cell-cycle exit associated with DNA damage and cytokine secretion. However, senescence is easily confused with quiescence, in large part due to lack of reliable markers. We have found that the gold-standard senescence marker, senescence-associated beta-galactosidase activity, is unreliable in that it can stain strongly positive in cells that are actively dividing. We have also found that establishing a homogeneous population of senescent cells is quite difficult since many cells continue to cycle and out-proliferate senescent cells, despite the use of standard senescence-inducing treatments. Thus, the senescence field has a chicken/egg problem in that one cannot study senescence if no reliable markers exist to identify senescent cells, and one cannot develop a senescence marker without a truly senescent sample in hand. We are therefore developing a functional readout to identify cells that have not cycled in ''n'' days, where ''n'' is triggered and defined by the researcher and can be several months long. In this way, we can isolate a homogeneous senescent population that can be profiled and compared to quiescent cells to develop better markers for quiescence vs. senescence and to better study cellular aging. +
I
Community ecology is built on the notion of interspecies interactions. The strengths of interactions are almost invariably taken as fixed parameters, which must either be measured or assumed. The few available models that do consider the formation and evolution of interactions, including some built by myself, are based on ad hoc definitions of fitness. In this talk I will present a first-principles approach to how interactions between and within species change. In this picture, the black box of "interspecies interactions" will be replaced with advection, diffusion, dispersal, chemical secretions and domain geometry. I will show that the fundamental laws of fluid dynamics and the physical parameters describing the fluid habitat determine whether species will be driven towards individualism, social cooperation, specialization, or extinction. I will end my talk by proposing ways to tailoring the interaction structure of a microbial community by manipulating flow patterns and domain geometry. +
Irreversible Processes in Ecological Evolution/Natural selection, population cycles, and climate change in forest insects +
Cyclic outbreaks of forest insects devastate forests, leading to widespread defoliation and tree death. Outbreaks would be far worse if not for epidemics of fatal virus diseases, which decimate outbreaking insect populations. The selection pressure imposed by these diseases suggests that natural selection may affect outbreaks, but understanding such effects is impossible with data alone. My lab has therefore used a combination of field experiments and models to test for effects of selection on outbreaks. Our work shows that both heritable host resistance and variation in viral virulence strongly affect outbreaks of the the gypsy moth, Lymantria dispar, an introduced pest of eastern hardwood forests in North America. Over the last few decades, however, an introduced fungal pathogen has competitively displaced the virus. The fungus provides better control, but its survival is much higher when the weather is cool and wet, whereas climate change is likely to cause weather conditions in the range of the gypsy moth to become increasingly hot and dry. By again combining models and data, we have shown that climate change will have a strong negative effect on the gypsy moth fungus, which may lead to the devastation of hardwood forests in North America. A key question is therefore, can the virus make a comeback? Our answers to this question are as yet incomplete, but provide initial chapters in an interesting story about the ecological effects of climate change. +
P
Population and the Environment: Analytical Demography and Applied Population Ethics/Co-evolution of population and environment - environment, food supply & demography +
Due to tight coupling between human population dynamics and their local environments, preindustrial societies—particularly ones on islands--are useful for studying population-environment interaction. In Hawai’i, rapid human population growth and sophisticated social stratification took place before European contact, in the context of sometimes extreme environmental variability. These phenomena define questions, inform the structure of quantitative models, and guide the development of further hypotheses regarding how environment and population interact. I describe how agroecological and environment-dependent demographic models can be developed and integrated to probe the environment-population dynamics of a dryland field system, and to investigate the consequences and possible causes of social complexity. Results suggest that dynamic incorporation of social change could be an important component of studying population-environment interactions. +
C
Ecological communities (more generally, non-linear systems) often showmultiple regimes, which are separated by a sharp and rapid transition. I will discuss the scenario when the driver of the transition is the structure of interactions. Random matrix theory has a powerful set of tools that can be used to unveil the relation between interaction structure and dynamics.
Take home messages:
- universality: when many components interact many details do not matter (e.g. the distribution of interaction coefficients) and few global properties of the interactions determine the relevant dynamical properties
- the effect of the structure (whether a given network structure is stabilizing or destabilizing compared to the null/random case) *depends* on the interaction strengths properties +
A
Aging and Adaptation in Infectious Diseases II/Session I: Immune System: Architecture and Dynamics#Universal laws and architectures in complex networked systems with applications to aging and immune systems +
Effective layered architectures such as in brains and organisms seamlessly integrate high level goal and decision making and planning with fast lower level sensing, reflex, and action and facilitate learning, adaptation, augmentation (tools), and teamwork, while maintaining internal homeostasis. This is all despite the severe demands such actions can put on the whole body’s physiology, and despite being implemented in highly energy efficient hardware that has distributed, sparse, quantized, noisy, delayed, and saturating sensing, communications, computing, and actuation. Similar layering extends downward into the cellular level, out into ecological and social systems, and many aspects of this convergent evolution will increasingly dominate our most advanced technologies. Simple demos using audience’s brains can highlight universal laws and architectures and their relevance to tech, bio, neuro, med, and social networks. This suggests conjectures about senescence, and tradeoffs in the evolution of cancer, wound healing, degenerative diseases, auto-immunity, parasitism, and social organization, and potential animal models to explore these tradeoffs.
With this motivation, we’ll sketch progress on a new unified theory of complex networks that integrates communications, control, and computation with applications to cyberphysical systems as well as neuroscience and biology. Though based on completely different constraints arising from different environments, functions, and hardware, such systems face universal tradeoffs (laws) in dimensions such as efficiency, robustness, security, speed, flexibility, and evolvability. And successful systems share remarkable universals in architecture, including layering, localization, and diversity sweet spots, to effectively manage these tradeoffs, as well as universal fragilities, particularly to infectious hijacking.
I have videos of some introductory material and posted it in my public dropbox folder:
https://www.dropbox.com/sh/7bgwzqsl7ycxhie/AABQB9L2J-XmCniwgyO3N83Ba?dl=0
Some new neuro stuff (with videos) is in the subfolder 1.New_CDS141\2.2.UCSDneuro
There are lots of videos and papers on biology and medicine (and lots of tech) in the subfolder 0.Intro2Research.
Given the limited time and that I’m an extreme outlier, I’ll try to post videos (need to organize them) of some additional background material on aging, cancer, immune systems, wound healing, microbiome, etc that give some background on our approach to these topics.
Some videos/slides relevant to this meeting are in the subfolder: 1.New_CDS141\4.2.AgingSFI
I
Irreversible Processes in Ecological Evolution/Emergent structure and dynamics in stochastic, open, competitive communities +
Here I describe recent theoretical work by my lab looking at the emergent patterning in models where niche differentiation acts in concert with drift and immigration, as well as empirical work looking for that patterning. The results of our study of “stochastic niche communities” provides further generalization of the recent theoretical developments suggesting that niche differentiation may actually lead to clusters of species similar in traits, in contrast with traditional expectations of even spacing or overdispersion. These traditional expectations are derived from models ignoring stochasticity and immigration as well as other factors. I will review both classical and more recent theoretical developments along the way. We also find niche differentiation plays a more complex role in species persistence in stochastic niche communities than classically expected, enhancing persistence of a select few species, and lessening the persistence of others. We have also demonstrated the occurrence of this pattern of clusters across an array of niche mechanisms, and groundtruthed metrics for its detection in field data. Finally, we have applied our metrics to trait and abundance data for tree species in the 50 ha plot on Barro Colorado Island, and find significant clusters in four traits linked to niche axes. I will discuss all of these developments and also highlight connections to the question of irreversibility in the ecological and evolutionary dynamics of competing species. +
A
Aging in Single-celled Organisms: from Bacteria to the Whole Tree of Life/Stochasticity, immortality, and mortality in E. coli +
Here we show that the bacterium Escherichia coli exhibits both lineage mortality and immortality. The outcome depends on a whether a balance is achieved between damage accumulation and the asymmetric allocation of damage from mother to daughters. At low damage rates, both old and new daughters, which are allocated respectively more and less damage, generated immortal lineages that achieved stable growth rate equilibria. At high rates, mortality ensued because while the new daughter lineage persisted, the old daughter lineage stopped dividing. The stoppage was found to result from an increase in the stochasticity of cell growth. +
P
Population and the Environment: Analytical Demography and Applied Population Ethics/Foundation of population ethics - population axiology & moral theory +
How should we compare states of affairs that differ in not only the identities and qualities of life of those who comprise them, but also in their populations? This is the central challenge for moral philosophers working on population and future generations. I introduce the key ideas and arguments. I focus on the ‘repugnant conclusion’: the view that large populations of people with relatively low qualities of life may be better than small populations with relatively higher quality of life. I explore some of the arguments for and against this view and sketch the range of positions that those who wish to avoid it have adopted. +
Population and the Environment: Analytical Demography and Applied Population Ethics/Co-evolution of population and environment - anthropogenic change & biodiversity +
Human activities are often seen as detrimental to biodiversity. We will explore the science and sociology behind this narrative. We will both delve into the math behind extrapolations of species diversity and loss, and illuminate the shortcomings of the false dichotomy between humans and nature. Predicting biodiversity loss in ecology and conservation biology has historically been viewed through the lens of direct population destruction, habitat loss, and climate change. Habitat area has plays a key role in biodiversity theories as area mediates population size and is affected by all forms of habitat destruction including climate change. Thus we will focus heavily on theories of how biodiversity responds to changes in area. Predictions of biodiversity loss have failed to consider biases scientists bring to such predictions. We will therefore explore how presumptions about species interactions and human-nature relationships, largely dating to the Victorian era, have limited insight into biodiversity dynamics and conservation. +
D
Humans are “complex biological systems consisting of multiple levels of non-linearly interacting elements”. Our bodies have astonishing powers of self-repair, and in the absence of catastrophic stress or genetic defects, can maintain homeostasis for a long time. Humans are one of the most long-lived species on the planet. However, there seems to be a “natural limit” of human life span that has not changed substantially despite the advances of medicine. Self-repair and recovery from stresses “naturally” diminish with age. Eventually, tipping points push the system into increasingly less resilient states. Are there any purely conceptual models that can describe human aging, resilience and frailty, especially the slow-down of recovery and the emergence of tipping points? This talk will provide a high-level overview of some potentially useful models and how they relate to each other – focusing on models of entropic/informational breakdown and stochastic stress response. However, while such models can capture aspects of the problem, challenges remain to connect these mathematical models to the complex, multi-hierarchical, multi-timescale, feedback-controlled system of a human body. +
H
I discuss approaches to two problems on very different timescales. For a single lifetime, transitions between states of health (disability) can be viewed as stochastic movement out of a potential with two minima. Aging can mean changes in the amplitude of noise, depth of potential, or width of potential. Such dynamics are conceptually similar to the disability transition in current medical understanding. What are the math features? Can we make this into a statistical model? On evolutionary timescales, post-reproductive life can evolve according to varipus arguments that are all examples of “borrowed fitness.” I explain what this means and mainly ask what questions we should be asking. +
C
I gave a basic review of percolation theory on lattices and outlined the behavior of physical observables, such as the correlation length, the mean cluster size, and the percolation probability on the bond occupation probability. I then discussed the analogous percolation transition on complex networks, where the degree distribution can be broad. The basic new feature of complex networks is that they are relatively robust to random removal of nodes or links and quite vulnerable to the removal of the highest-degree nodes.
Finally, I presented two examples of network breakdown phenomena: the electrical failure of electrical networks of fuse elements and the external voltage is increased, and the clogging of fluid networks during the process of filtration. +
H
Hallmarks of Biological Failure/Explain this! - Evolutionary approaches to unanswered questions in cancer biology +
I plan to throw out some observations (e.g. age-dependent cancer incidence for different organs and different species), and how these are currently enigmatic. I’ll discuss possible explanations, but also highlight were explanations are currently lacking. +
A
Aging and Adaptation in Infectious Diseases II/Session II: Immune System: Aging and Heterogeneity#The arrow of time as seen through the immune system and the physiological internalization of time +
I will be summarizing, and thematically integrating, two areas of research presented at the first SFI working group meeting. First, I will discuss the arrow of time, from birth to death, as seen through the lens of the immune system: from the development of the infant immune system through immunosenescence and the end of life. Second, I will review the internalization of time via two mechanisms: biological clocks and the "jamming" of immunological memory. Lastly, I will propose a conceptual framework for integrating these themes as spiral trajectories of endogenous immunity and vulnerability. +
I
I will discuss several examples from population genetics and adaptive dynamics where the probability for a transition between “equilibrium” states is very low. These situations can occur when stochastic environmental conditions create scenarios with alternate stable states that can only be invaded by mutations of large effect, for instance in scenarios with overlapping generations and lottery competition. In a similar vein, when mutations of small effect cause intermediate phenotypes with low fitness, transitions can be rare. Another type of transition involves feedback between the environment and the distribution of population phenotypes, for example in terms of the evolution of mating preferences in combination with the evolution of ecological specialization. Yet another scenario occurs when multiple independent mutations are required to cross an “adaptive valley”. This has parallels in ecological theory, for example with the invasion of novel habitats (e.g. zoonotic diseases). I will encourage discussion of how these different concepts and modes of analysis may be extended to situations with eco-evo feedbacks. +
H
Hallmarks of Biological Failure/Complexity, Breaking Bad Tradeoffs, and the Evolution of Biological Failure +
I will discuss two points. First, how are genomic and organismal complexity related to slow, and fast, failure? Do biological systems fail more under conditions of high
complexity and tight coupling, as posited for inanimate systems? Do increases in genomic and organismal complexity result in short-term benefits, but more longer-term evolutionary vulnerabilities? Second, how do tradeoffs mediate failure? Most tradeoffs are 'bad' in that system-wide organismal lifetime optimization is not achieved, even if they are relatively 'good' for propagating genes. Can such bad tradeoffs be broken, artificially, by humans?
I think so, in some cases. I discuss examples, from mental disorders, life histories, and senescence. +
A
Aging and Adaptation in Infectious Diseases II/Session II: Immune System: Aging and Heterogeneity#Influenza viruses encountered in childhood leave a lifelong imprint +
Immune imprinting to the influenza viruses encountered in childhood strongly shapes lifelong risk. These findings raise questions about the expansion of antibody repertoires over time. Does the first influenza exposure, or the first few, have the greatest influence on lifelong immunological trajectories? Why have older cohorts evidently failed to develop strong memory against strains that emerged later in in their lifetimes? What are the costs and benefits of childhood imprinting for effective protection later in adulthood? +
I
In a seminal paper in 1972, Robert May studied complex ecosystems using Random Matrix Theory. Nearly fifty years later, the rise of quantitative microbial ecology makes it possible to test and refine this approach. Random matrix models successfully capture a wide range of large-scale patterns observed in real microbial communities, including functional and family-level reproducibility, compositional clustering by environment, enterotypes, dissimilarity-overlap correlations, decreased diversity in harsh environments, compositional nestedness, succession dynamics and modularity. After describing the computational model we have developed to reproduce all these patterns, I will present a set of analytic results that explain why this works in the real world. Adding even a small amount of noise to a sufficiently diverse community induces a phase transition to a “typical” phase, where community-level properties such as diversity and rank-abundance curves are indistinguishable from those of a completely random ecosystem. I will explain how the properties of this phase are governed by “susceptibilities” describing the linear response of the ecosystem to small changes in population sizes or resource concentrations. These susceptibilities can be obtained from Random Matrix Theory, in the spirit of May’s paper, and can also be measured by subjecting a community to controlled perturbations. +
