Showing papers by "Santa Fe Institute published in 2012"

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations

Abstract: It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes--so-called sporadic or simplex families--we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 677 individual exomes from 209 families. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected β-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

Anticipating Critical Transitions

Abstract: Tipping points in complex systems may imply risks of unwanted collapse, but also opportunities for positive change. Our capacity to navigate such risks and opportunities can be boosted by combining emerging insights from two unconnected fields of research. One line of work is revealing fundamental architectural features that may cause ecological networks, financial markets, and other complex systems to have tipping points. Another field of research is uncovering generic empirical indicators of the proximity to such critical thresholds. Although sudden shifts in complex systems will inevitably continue to surprise us, work at the crossroads of these emerging fields offers new approaches for anticipating critical transitions.

The return of the variance: intraspecific variability in community ecology

Abstract: Despite being recognized as a promoter of diversity and a condition for local coexistence decades ago, the importance of intraspecific variance has been neglected over time in community ecology. Recently, there has been a new emphasis on intraspecific variability. Indeed, recent developments in trait-based community ecology have underlined the need to integrate variation at both the intraspecific as well as interspecific level. We introduce new T-statistics ('T' for trait), based on the comparison of intraspecific and interspecific variances of functional traits across organizational levels, to operationally incorporate intraspecific variability into community ecology theory. We show that a focus on the distribution of traits at local and regional scales combined with original analytical tools can provide unique insights into the primary forces structuring communities.

Multiplex targeted sequencing identifies recurrently mutated genes in autism spectrum disorders.

Abstract: Exome sequencing studies of autism spectrum disorders (ASDs) have identified many de novo mutations but few recurrently disrupted genes. We therefore developed a modified molecular inversion probe method enabling ultra-low-cost candidate gene resequencing in very large cohorts. To demonstrate the power of this approach, we captured and sequenced 44 candidate genes in 2446 ASD probands. We discovered 27 de novo events in 16 genes, 59% of which are predicted to truncate proteins or disrupt splicing. We estimate that recurrent disruptive mutations in six genes-CHD8, DYRK1A, GRIN2B, TBR1, PTEN, and TBL1XR1-may contribute to 1% of sporadic ASDs. Our data support associations between specific genes and reciprocal subphenotypes (CHD8-macrocephaly and DYRK1A-microcephaly) and replicate the importance of a β-catenin-chromatin-remodeling network to ASD etiology.

The Diffusion of Microfinance

Abstract: We examine how participation in a microfinance program diffuses through social networks. We collected detailed demographic and social network data in 43 villages in South India before microfinance was introduced in those villages and then tracked eventual participation. We exploit exogenous variation in the importance (in a network sense) of the people who were first informed about the program, "the injection points". Microfinance participation is higher when the injection points have higher eigenvector centrality. We estimate structural models of diffusion that allow us to (i) determine the relative roles of basic information transmission versus other forms of peer influence, and (ii) distinguish information passing by participants and non-participants. We find that participants are significantly more likely to pass information on to friends and acquaintances than informed non-participants, but that information passing by non-participants is still substantial and significant, accounting for roughly a third of informedness and participation. We also find that, conditioned on being informed, an individual's decision is not significantly affected by the participation of her acquaintances.

Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease

Abstract: The human microbiome plays a key role in a wide range of host-related processes and has a profound effect on human health. Comparative analyses of the human microbiome have revealed substantial variation in species and gene composition associated with a variety of disease states but may fall short of providing a comprehensive understanding of the impact of this variation on the community and on the host. Here, we introduce a metagenomic systems biology computational framework, integrating metagenomic data with an in silico systems-level analysis of metabolic networks. Focusing on the gut microbiome, we analyze fecal metagenomic data from 124 unrelated individuals, as well as six monozygotic twin pairs and their mothers, and generate community-level metabolic networks of the microbiome. Placing variations in gene abundance in the context of these networks, we identify both gene-level and network-level topological differences associated with obesity and inflammatory bowel disease (IBD). We show that genes associated with either of these host states tend to be located at the periphery of the metabolic network and are enriched for topologically derived metabolic “inputs.” These findings may indicate that lean and obese microbiomes differ primarily in their interface with the host and in the way they interact with host metabolism. We further demonstrate that obese microbiomes are less modular, a hallmark of adaptation to low-diversity environments. We additionally link these topological variations to community species composition. The system-level approach presented here lays the foundation for a unique framework for studying the human microbiome, its organization, and its impact on human health.

Economic Incentives and Social Preferences: Substitutes or Complements?

Abstract: Explicit economic incentives designed to increase contributions to public goods and to promote other pro-social behavior sometimes are counterproductive or less effective than would be predicted among entirely self-interested individuals. This may occur when incentives adversely affect individuals’ altruism, ethical norms, intrinsic motives to serve the public, and other social preferences. The opposite also occurs—crowding in —though it appears less commonly . In the fifty experiments that we survey, these effects are common, so that incentives and social preferences may be either substitutes (crowding out) or complements (crowding in). We provide evidence for four mechanisms that may account for these incentive effects on preferences: namely that incentives may (i) provide information about the person who implemented the incentive, (ii) frame the decision situation so as to suggest appropriate behavior, (iii) compromise a control averse individual’s sense of autonomy, and (iv) affect the process by which people learn new preferences. An implication is that the evaluation of public policy must be restricted to allocations that are supportable as Nash equilibria when account is taken of these crowding effects. We show that well designed fines, subsidies, and the like minimize crowding out and may even do the opposite, making incentives and social preferences complements rather than substitutes. ( JEL D02, D03, D04, D83, E61, H41, Z13)

Food webs: reconciling the structure and function of biodiversity

Abstract: The global biodiversity crisis concerns not only unprecedented loss of species within communities, but also related consequences for ecosystem function. Community ecology focuses on patterns of species richness and community composition, whereas ecosystem ecology focuses on fluxes of energy and materials. Food webs provide a quantitative framework to combine these approaches and unify the study of biodiversity and ecosystem function. We summarise the progression of food-web ecology and the challenges in using the food-web approach. We identify five areas of research where these advances can continue, and be applied to global challenges. Finally, we describe what data are needed in the next generation of food-web studies to reconcile the structure and function of biodiversity.

Architectural design influences the diversity and structure of the built environment microbiome

Abstract: Buildings are complex ecosystems that house trillions of microorganisms interacting with each other, with humans and with their environment. Understanding the ecological and evolutionary processes that determine the diversity and composition of the built environment microbiome—the community of microorganisms that live indoors—is important for understanding the relationship between building design, biodiversity and human health. In this study, we used high-throughput sequencing of the bacterial 16S rRNA gene to quantify relationships between building attributes and airborne bacterial communities at a health-care facility. We quantified airborne bacterial community structure and environmental conditions in patient rooms exposed to mechanical or window ventilation and in outdoor air. The phylogenetic diversity of airborne bacterial communities was lower indoors than outdoors, and mechanically ventilated rooms contained less diverse microbial communities than did window-ventilated rooms. Bacterial communities in indoor environments contained many taxa that are absent or rare outdoors, including taxa closely related to potential human pathogens. Building attributes, specifically the source of ventilation air, airflow rates, relative humidity and temperature, were correlated with the diversity and composition of indoor bacterial communities. The relative abundance of bacteria closely related to human pathogens was higher indoors than outdoors, and higher in rooms with lower airflow rates and lower relative humidity. The observed relationship between building design and airborne bacterial diversity suggests that we can manage indoor environments, altering through building design and operation the community of microbial species that potentially colonize the human microbiome during our time indoors.

Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

Abstract: The abundance of different SSU rRNA ("16S") gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly - from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.

Committed carbon emissions, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia

Abstract: Industrial agricultural plantations are a rapidly increasing yet largely unmeasured source of tropical land cover change. Here, we evaluate impacts of oil palm plantation development on land cover, carbon flux, and agrarian community lands in West Kalimantan, Indonesian Borneo. With a spatially explicit land change/carbon bookkeeping model, parameterized using high-resolution satellite time series and informed by socioeconomic surveys, we assess previous and project future plantation expansion under five scenarios. Although fire was the primary proximate cause of 1989–2008 deforestation (93%) and net carbon emissions (69%), by 2007–2008, oil palm directly caused 27% of total and 40% of peatland deforestation. Plantation land sources exhibited distinctive temporal dynamics, comprising 81% forests on mineral soils (1994–2001), shifting to 69% peatlands (2008–2011). Plantation leases reveal vast development potential. In 2008, leases spanned ∼65% of the region, including 62% on peatlands and 59% of community-managed lands, yet <10% of lease area was planted. Projecting business as usual (BAU), by 2020 ∼40% of regional and 35% of community lands are cleared for oil palm, generating 26% of net carbon emissions. Intact forest cover declines to 4%, and the proportion of emissions sourced from peatlands increases 38%. Prohibiting intact and logged forest and peatland conversion to oil palm reduces emissions only 4% below BAU, because of continued uncontrolled fire. Protecting logged forests achieves greater carbon emissions reductions (21%) than protecting intact forests alone (9%) and is critical for mitigating carbon emissions. Extensive allocated leases constrain land management options, requiring trade-offs among oil palm production, carbon emissions mitigation, and maintaining community landholdings.

Crowd disasters as systemic failures: analysis of the Love Parade disaster

Abstract: Each year, crowd disasters happen in different areas of the world. How and why do such disasters happen? Are the fatalities caused by relentless behavior of people or a psychological state of panic that makes the crowd ‘go mad’? Or are they a tragic consequence of a breakdown of coordination? These and other questions are addressed, based on a qualitative analysis of publicly available videos and materials, which document the planning and organization of the Love Parade in Duisburg, Germany, and the crowd disaster on July 24, 2010. Our analysis reveals a number of misunderstandings that have widely spread. We also provide a new perspective on concepts such as ‘intentional pushing’, ‘mass panic’, ‘stampede’, and ‘crowd crushes’. The focus of our analysis is on the contributing causal factors and their mutual interdependencies, not on legal issues or the judgment of personal or institutional responsibilities. Video recordings show that people stumbled and piled up due to a ‘domino effect’, resulting from a phenomenon called ‘crowd turbulence’ or ‘crowd quake’. Crowd quakes are a typical reason for crowd disasters, to be distinguished from crowd disasters resulting from ‘mass panic’ or ‘crowd crushes’. In Duisburg, crowd turbulence was the consequence of amplifying feedback and cascading effects, which are typical for systemic instabilities. Accordingly, things can go terribly wrong in spite of no bad intentions from anyone. Comparing the incident in Duisburg with others, we give recommendations to help prevent future crowd disasters. In particular, we introduce a new scale to assess the criticality of conditions in the crowd. This may allow preventative measures to be taken earlier on. Furthermore, we discuss the merits and limitations of citizen science for public investigation, considering that today, almost every event is recorded and reflected in the World Wide Web.

Nodal dynamics, not degree distributions, determine the structural controllability of complex networks.

Abstract: Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167–173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set, is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.

Social capital and social quilts : network patterns of favor exchange

Abstract: We examine the informal exchange of favors in societies such that any two individuals interact too infrequently to sustain exchange, but such that the social pressure of the possible loss of multiple relationships can sustain exchange. Patterns of exchange that are locally enforceable and renegotiation-proof necessitate that all links are “supported”: any two individuals exchanging favors have a common friend. In symmetric settings, such robust networks are “social quilts”: tree-like unions of completely connected subnetworks. Examining favor exchange networks in 75 villages in rural India, we find high levels of support and identify characteristics that correlate with support.

Dimensionality of consumer search space drives trophic interaction strengths

Abstract: Interactions between the feeding habits of different organisms in a food chain or web trophic interactions can take place in two or three dimensions, and many communities show a mix of the two. By relating search rate and consumption rate to body mass, the authors show that the relationship between trophic-interaction strength and body size scales sublinearly in two-dimensional interactions but superlinearly in three-dimensional ones. They develop a model to show how this explains differences between, for example, aquatic and terrestrial ecosystems because the extra dimension provides an additional niche or opportunity in which to find resources. As an example, the model predicts that a foraging Galpagos sea lion could enjoy a consumption rate up to 30 times higher in a pelagic zone near the surface of the ocean (in three dimensions) than deep-down in a benthic zone (in two dimensions).

Phenological tracking enables positive species responses to climate change

Abstract: Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically “track” climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlier-active competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced thei...

The biogeography and filtering of woody plant functional diversity in North and South America

Abstract: Aim In recent years evidence has accumulated that plant species are differentially sorted from regional assemblages into local assemblages along local-scale environmental gradients on the basis of their function and abiotic filtering. The favourability hypothesis in biogeography proposes that in climatically difficult regions abiotic filtering should produce a regional assemblage that is less functionally diverse than that expected given the species richness and the global pool of traits. Thus it seems likely that differential filtering of plant traits along local-scale gradients may scale up to explain the distribution, diversity and filtering of plant traits in regional-scale assemblages across continents. The present work aims to address this prediction.

Classic Period collapse of the Central Maya Lowlands: Insights about human–environment relationships for sustainability

Abstract: The ninth century collapse and abandonment of the Central Maya Lowlands in the Yucatan peninsular region were the result of complex human–environment interactions. Large-scale Maya landscape alterations and demands placed on resources and ecosystem services generated high-stress environmental conditions that were amplified by increasing climatic aridity. Coincident with this stress, the flow of commerce shifted from land transit across the peninsula to sea-borne transit around it. These changing socioeconomic and environmental conditions generated increasing societal conflicts, diminished control by the Maya elite, and led to decisions to move elsewhere in the peninsular region rather than incur the high costs of maintaining the human–environment systems in place. After abandonment, the environment of the Central Maya Lowlands largely recovered, although altered from its state before Maya occupation; the population never recovered. This history and the spatial and temporal variability in the pattern of collapse and abandonment throughout the Maya lowlands support the case for different conditions, opportunities, and constraints in the prevailing human–environment systems and the decisions to confront them. The Maya case lends insights for the use of paleo- and historical analogs to inform contemporary global environmental change and sustainability.

The scaling of human interactions with city size

Abstract: The size of cities is known to play a fundamental role in social and economic life. Yet, its relation to the structure of the underlying network of human interactions has not been investigated empirically in detail. In this paper, we map society-wide communication networks to the urban areas of two European countries. We show that both the total number of contacts and the total communication activity grow superlinearly with city population size, according to well-defined scaling relations and resulting from a multiplicative increase that affects most citizens. Perhaps surprisingly, however, the probability that an individual's contacts are also connected with each other remains largely unaffected. These empirical results predict a systematic and scale-invariant acceleration of interaction-based spreading phenomena as cities get bigger, which is numerically confirmed by applying epidemiological models to the studied networks. Our findings should provide a microscopic basis towards understanding the superlinear increase of different socioeconomic quantities with city size, that applies to almost all urban systems and includes, for instance, the creation of new inventions or the prevalence of certain contagious diseases.

Vertical T cell immunodominance and epitope entropy determine HIV-1 escape

Abstract: HIV-1 accumulates mutations in and around reactive epitopes to escape recognition and killing by CD8+ T cells. Measurements of HIV-1 time to escape should therefore provide information on which parameters are most important for T cell–mediated in vivo control of HIV-1. Primary HIV-1–specific T cell responses were fully mapped in 17 individuals, and the time to virus escape, which ranged from days to years, was measured for each epitope. While higher magnitude of an individual T cell response was associated with more rapid escape, the most significant T cell measure was its relative immunodominance measured in acute infection. This identified subject-level or “vertical” immunodominance as the primary determinant of in vivo CD8+ T cell pressure in HIV-1 infection. Conversely, escape was slowed significantly by lower population variability, or entropy, of the epitope targeted. Immunodominance and epitope entropy combined to explain half of all the variability in time to escape. These data explain how CD8+ T cells can exert significant and sustained HIV-1 pressure even when escape is very slow and that within an individual, the impacts of other T cell factors on HIV-1 escape should be considered in the context of immunodominance.

A general model for effects of temperature on ectotherm ontogenetic growth and development

Abstract: The temperature size rule (TSR) is the tendency for ectotherms to develop faster but mature at smaller body sizes at higher temperatures. It can be explained by a simple model in which the rate of growth or biomass accumulation and the rate of development have different temperature dependence. The model accounts for both TSR and the less frequently observed reverse-TSR, predicts the fraction of energy allocated to maintenance and synthesis over the course of development, and also predicts that less total energy is expended when developing at warmer temperatures for TSR and vice versa for reverse-TSR. It has important implications for effects of climate change on ectothermic animals.

Continuum percolation thresholds in two dimensions

Abstract: A wide variety of methods have been used to compute percolation thresholds. In lattice percolation, the most powerful of these methods consists of microcanonical simulations using the union-find algorithm to efficiently determine the connected clusters, and (in two dimensions) using exact values from conformal field theory for the probability, at the phase transition, that various kinds of wrapping clusters exist on the torus. We apply this approach to percolation in continuum models, finding overlaps between objects with real-valued positions and orientations. In particular, we find precise values of the percolation transition for disks, squares, rotated squares, and rotated sticks in two dimensions and confirm that these transitions behave as conformal field theory predicts. The running time and memory use of our algorithm are essentially linear as a function of the number of objects at criticality.

Testing the metabolic theory of ecology

Abstract: The metabolic theory of ecology (MTE) predicts the effects of body size and temperature on metabolism through considerations of vascular distribution networks and biochemical kinetics. MTE has also been extended to characterise processes from cellular to global levels. MTE has generated both enthusiasm and controversy across a broad range of research areas. However, most efforts that claim to validate or invalidate MTE have focused on testing predictions. We argue that critical evaluation of MTE also requires strong tests of both its theoretical foundations and simplifying assumptions. To this end, we synthesise available information and find that MTE's original derivations require additional assumptions to obtain the full scope of attendant predictions. Moreover, although some of MTE's simplifying assumptions are well supported by data, others are inconsistent with empirical tests and even more remain untested. Further, although many predictions are empirically supported on average, work remains to explain the often large variability in data. We suggest that greater effort be focused on evaluating MTE's underlying theory and simplifying assumptions to help delineate the scope of MTE, generate new theory and shed light on fundamental aspects of biological form and function.

Persistence and periodicity in a dynamic proximity network.

Abstract: The topology of social networks can be understood as being inherently dynamic, with edges having a distinct position in time. Most characterizations of dynamic networks discretize time by converting temporal information into a sequence of network "snapshots" for further analysis. Here we study a highly resolved data set of a dynamic proximity network of 66 individuals. We show that the topology of this network evolves over a very broad distribution of time scales, that its behavior is characterized by strong periodicities driven by external calendar cycles, and that the conversion of inherently continuous-time data into a sequence of snapshots can produce highly biased estimates of network structure. We suggest that dynamic social networks exhibit a natural time scale \Delta_{nat}, and that the best conversion of such dynamic data to a discrete sequence of networks is done at this natural rate.

Physiological regulatory networks: ecological roles and evolutionary constraints

Abstract: Ecological and evolutionary physiology has traditionally focused on one aspect of physiology at a time. Here, we discuss the implications of considering physiological regulatory networks (PRNs) as integrated wholes, a perspective that reveals novel roles for physiology in organismal ecology and evolution. For example, evolutionary response to changes in resource abundance might be constrained by the role of dietary micronutrients in immune response regulation, given a particular pathogen environment. Because many physiological components impact more than one process, organismal homeostasis is maintained, individual fitness is determined and evolutionary change is constrained (or facilitated) by interactions within PRNs. We discuss how PRN structure and its system-level properties could determine both individual performance and patterns of physiological evolution.

Climate change in size-structured ecosystems.

Abstract: One important aspect of climate change is the increase in average temperature, which will not only have direct physiological effects on all species but also indirectly modifies abundances, interaction strengths, food-web topologies, community stability and functioning. In this theme issue, we highlight a novel pathway through which warming indirectly affects ecological communities: by changing their size structure (i.e. the body-size distributions). Warming can shift these distributions towards dominance of small- over large-bodied species. The conceptual, theoretical and empirical research described in this issue, in sum, suggests that effects of temperature may be dominated by changes in size structure, with relatively weak direct effects. For example, temperature effects via size structure have implications for top-down and bottom-up control in ecosystems and may ultimately yield novel communities. Moreover, scaling up effects of temperature and body size from physiology to the levels of populations, communities and ecosystems may provide a crucially important mechanistic approach for forecasting future consequences of global warming.

A complex systems approach to constructing better models for managing financial markets and the economy

Abstract: We outline a vision for an ambitious program to understand the economy and financial markets as a complex evolving system of coupled networks of interacting agents. This is a completely different vision from that currently used in most economic models. This view implies new challenges and opportunities for policy and managing economic crises. The dynamics of such models inherently involve sudden and sometimes dramatic changes of state. Further, the tools and approaches we use emphasize the analysis of crises rather than of calm periods. In this they respond directly to the calls of Governors Bernanke and Trichet for new approaches to macroeconomic modelling.