Biology subjects

Pilosof, S.

Publications and source records attributed to Pilosof, S..

11 recordsLinked to original sources

bioRxiv2025

Structure knows best: predicting ecological interactions across space through pairwise integration of latent network patterns

O_LIEcological communities are complex and exhibit considerable spatial variability, presenting challenges in accurately understanding these systems. A primary obstacle in ecological research is the existence of missing links between species: inevitable unobserved interactions that limit our comprehension of ecological networks and their response to change. While link prediction methods have been developed to address this challenge, most approaches overlook the intrinsic spatial variability of ecological systems. C_LIO_LIWe introduce a flexible, spatially explicit framework based on matrix decomposition that leverages latent structural patterns to predict missing interactions and their strength, without requiring species traits or environmental data. The framework integrates information from paired auxiliary and target networks (locations) using thresholded SVD for link prediction. We applied it to plant-pollinator networks across the Canary Islands, performing pairwise predictions between locations, comparing them to within-location predictions (as a control), and quantifying how spatial variability influences predictive performance. C_LIO_LIPredictions revealed that latent network structure contains substantial predictive information, with F0.5 scores consistently exceeding a random baseline (mean F0.5 = 0.67 {+/-} 0.02 SD), while being less sensitive to interaction strength. The method enabled identifying plausible gaps in the data and producing ecologically coherent predictions. Incorporating information from auxiliary locations enhanced predictive accuracy in certain cases, but success depended on spatial context: predictions were most reliable when derived from nearby, ecologically similar locations, and declined with increasing geographic and ecological distance, consistent with a distance-decay effect. C_LIO_LIWe conclude that the predictability of missing links is spatially variable, reflecting both network and species-level heterogeneity. These patterns provide insights into network structure and the ecological processes shaping it, complementing trait-based approaches. While network structure offers rich predictive information, spatial context is essential for applying it effectively: ignoring spatial variability can obscure ecological signals and inflate predictive error. Our framework is computationally efficient, transferable, and readily applicable to any system with spatial or temporal replication. It can be used for a variety of ecological contexts, including island systems, fragmented landscapes, and environmental gradients, making it a practical and scalable tool for advancing link prediction in ecology. C_LI

ecology↗

bioRxiv2025

The structure of pairwise competition is responsible for sudden regime shifts in a microbe-plasmid model

Plasmids play a crucial role in bacterial communities by facilitating the horizontal transfer of genetic material, particularly genes that confer resistance to different stressor agents. In this work, we introduce a microbe-plasmid model to study the conditions under which a plasmid-carrying bacterial strain can invade its corresponding plasmid-free counterpart, as well as those under which it can be eradicated from the population through potential intervention strategies. We reveal the variety of dynamic regimes of the model depending on the parameter values. In particular, we show that a heterogeneous structure of the competition between the two strains drives the possibility of coexistence of stationary states (i.e. bistability) which creates conditions for sudden regime shifts and hysteresis. We explore the implications of our results for the potential eradication of plasmid-mediated antibiotic resistance.

ecology↗

bioRxiv2025

Metabolite correlation networks reveal complex phenotypes of adaptation-driving mutations

Living organisms are organized into hierarchical levels of increasing complexity. As mutational effects propagate through these levels, multiple phenotypes are produced. However, identifying which phenotypes influence fitness and drive selection remains a key challenge in understanding genotype-phenotype-fitness relationships. Here, we demonstrate that mutation-induced structural changes in metabolite correlation networks--an organizational level with emergent properties shaped by the cumulative effects of multiple biochemical reactions and regulatory mechanisms--constitute complex phenotypes linking mutations to bacterial fitness. We engineered a metabolically suboptimal E. coli strain by replacing the metK gene encoding methionine adenosyltransferase (MAT) with an ortholog from U. urealyticum and subjected it to laboratory evolution. Analysis of correlation networks constructed from 2,118 untargeted metabolites revealed that adaptive mutations enhanced the strains fitness by reducing network density, removing node hubs, and extensively rewiring connectivity. These changes yielded smaller, more cohesive, and better-interconnected network clusters. Moreover, evolution shifted the node representing S-adenosylmethionine (SAM), the product of the MAT-catalyzed reaction, from a peripheral role to a key connector between network clusters with a significantly increased betweenness. None of the accumulated mutations potentially driving this transition directly influenced MAT activity or SAM metabolism, indicating that the shift in SAMs role is an adaptive phenotype emerging from the metabolic systems complexity. Targeted metabolomics of key nodes displaying similar network transitions unveiled additional metabolites involved in SAM-related pathways. We propose the construction and analysis of metabolite correlation networks as an experimental and analytical framework for mapping genotype-phenotype-fitness relationships and exploring the mechanisms of metabolic adaptation.

evolutionary biology↗

bioRxiv2022

Invasive species modulate the structure and stability of a multilayer mutualistic network.

Species interactions are the backbone of the structure and dynamics of communities. The extensive research into the link between structure and stability has been primarily theoretical and focused on monotrophic networks. Therefore, how the disruption of multitrophic interactions alters communities response to perturbations in nature remains an open question. Here, we explored how non-native ungulates affect pollination-seed dispersal multilayer networks in Patagonia, Argentina. Ungulates disrupt a hummingbird-mistletoe-marsupial keystone interaction, which alters community composition. We calculated interlayer connectivity, modularity, and species roles in connecting modules for intact vs. invaded networks. To link structural changes to stability, we quantified network tolerance to a single random species removal (disturbance propagation) and sequential species removal (robustness) using a stochastic coextinction model. Non-native ungulates reduced the connectivity between pollination and seed dispersal and produced fewer modules with a skewed size distribution. Moreover, species shifted their structural role, primarily from connectors to peripherals, thereby fragmenting the network by reducing the "bridges" among modules. These structural changes altered the dynamics of cascading effects in the community, increasing disturbance propagation and reducing network robustness. Our results highlight the importance of understanding the mechanisms that alter the structure and subsequent stability of multitrophic communities in nature.

ecology↗

bioRxiv2022

Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness in the mitochondria

Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where multiple chaperons service hundreds of clients, forming complex chaperone-client interaction networks (CCINs). Studying (i) how network structure varies across cancer types and (ii) the influence of structure on networks robustness to chaperon targeting is key to developing cancer-specific drug therapy. We investigate these yet unaddressed questions using theory and methodology from network ecology. We show that CCINs are non-randomly structured across cancer types. Moreover, we identify groups of chaperones that interact with similar clients, providing specialization on clients but also redundancy in the case of chaperone removal on the other. Simulations of network robustness show that this modular structure strongly affects cancer-specific response to chaperon removal. Our results open the door for new hypotheses regarding the ecology and evolution of CCINs and can inform caner-specific drug development strategies.

ecology↗

bioRxiv2022

Multilayer Networks of Plasmid Genetic Similarity Reveal Potential Pathways of Gene Transmission

Antimicrobial resistance (AMR) is a major threat to public health. Plasmids are principal vectors of antimicrobial resistance genes, greatly contributing to their spread and mobility across hosts. Nevertheless little is known about the dynamics of plasmid genetic exchange across animal hosts. The cow rumen ecosystem is an excellent model system because it hosts diverse plasmid communities which interact and exchange genes. Here, we use theory and methodology from network and disease ecology to investigate the potential of gene transmission between plasmids using a data-set of 21 plasmidomes from a single dairy cow population. We constructed a multilayer network based on pairwise genetic similarity between plasmids serving as a signature for past genetic exchange to identify potential routes and mechanisms of gene transmission within and between cows. The transmission network was dominated by links between cows. Modularity analysis unraveled a major cross-cow transmission pathway with additional small pathways. Plasmid functions influenced network structure: plasmids containing mobility genes were more connected; those with the same AMR genes formed their own modules. We find signatures of gene superspreading in which a few plasmids and cows are responsible for most gene exchange. An agent-based transmission model showed that a new gene invading the cow population is likely to reach all cows. Finally, we showed that link weights contain a non-random signature for the mechanisms of gene transmission allowing us to differentiate between dispersal and genetic exchange. These results provide insights into the mechanisms by which genes, including those providing AMR, spread across animal hosts.

ecology↗

bioRxiv2020

Frequency-dependent competition between strains imparts resilience to perturbations in a model of Plasmodium falciparum malaria transmission.

In high-transmission endemic regions, local populations of Plasmodium falciparum exhibit vast diversity of the var genes encoding its major surface antigen, with each parasite comprising multiple copies from this diverse gene pool. This strategy to evade the immune system through large combinatorial antigenic diversity is common to other hyperdiverse pathogens. It underlies a series of fundamental epidemiological characteristics, including large reservoirs of transmission from high prevalence of asymptomatics and long-lasting infections. Previous theory has shown that negative frequency-dependent selection (NFDS) mediated by the acquisition of specific immunity by hosts structures the diversity of var gene repertoires (strains), in a pattern of limiting similarity that is both non-random and non-neutral. A combination of stochastic agent-based models and network analyses has enabled the development and testing of theory in these complex adaptive systems, where assembly of local parasite diversity occurs under frequency-dependent selection and large pools of variation. We show here the application of these approaches to theory comparing the resilience of the malaria transmission system to intervention when strain diversity is assembled under (competition-based) selection vs. a form of neutrality, where immunity depends only on the number but not the genetic identity of previous infections. The transmission system is considerably more resilient under NFDS, exhibiting a lower extinction probability despite comparable prevalence during intervention. We explain this pattern on the basis of the structure of strain diversity, in particular the more pronounced fraction of highly dissimilar parasites. For simulations that survive intervention, prevalence under specific immunity is lower than under neutrality, because the recovery of diversity is considerably slower than that of prevalence and decreased var gene diversity reduces parasite transmission. A Principal Component Analysis of network features describing parasite similarity reveals that despite lower overall diversity, NFDS is quickly restored after intervention constraining strain structure and maintaining patterns of limiting similarity important to parasite persistence. Given the resulting resilience to perturbations, intervention efforts will likely require longer times than the usual practice to eliminate P. falciparum populations. We discuss implications of our findings and potential analogies for ecological communities with non-neutral assembly processes involving frequency-dependence.

ecology↗

bioRxiv2020

A dynamical perspective to community detection in ecological networks

O_LIAnalysing how species interact in modules is a fundamental problem in network ecology. Theory shows that a modular network structure can reveal underlying dynamic ecological and evolutionary processes, influence dynamics that operate on the network and affect the stability of the ecological system. C_LIO_LIAlthough many ecological networks describe flows, such as biomass flows in food webs or disease trans-mission, most modularity analyses have ignored network flows, which can hinder our understanding of the interplay between structure and dynamics. C_LIO_LIHere we present Infomap, an established method based on network flows to the field of ecological networks. Infomap is a flexible tool that can identify modules in virtually any type of ecological network and is particularly useful for directed, weighted and multilayer networks. We illustrate how Infomap works on all these network types. We also provide a fully documented repository with additional ecological examples. Finally, to help researchers analyse their networks with Infomap, we introduce the open source R package infomapecology. C_LIO_LIAnalysing flow-based modularity is useful across ecology and transcends to other biological and non-biological disciplines. A dynamic approach for detecting modular structure has strong potential to provide new insights into the organisation of ecological networks. C_LI

ecology↗

bioRxiv2019

The network structure and eco-evolutionary dynamics of CRISPR-induced immune diversification

As a heritable sequence-specific adaptive immune system, CRISPR-Cas is a powerful force shaping strain diversity in host-virus systems. While the diversity of CRISPR alleles has been explored, the associated structure and dynamics of host-virus interactions have not. We explore the role of CRISPR in mediating the interplay between host-virus interaction structure and eco-evolutionary dynamics in a computational model and compare results with three empirical datasets from natural systems. We show that the structure of the networks describing who infects whom and the degree to which strains are immune, are respectively modular (containing groups of hosts and viruses that interact strongly) and weighted-nested (specialist hosts are more susceptible to subsets of viruses that in turn also infect the more generalist hosts with many spacers matching many viruses). The dynamic interplay between these networks influences transitions between dynamical regimes of virus diversification and host control. The three empirical systems exhibit weighted-nested protection networks, a pattern our theory shows is indicative of hosts able to suppress virus diversification. Previously missing from studies of microbial host-pathogen systems, the protection network plays a key role in the coevolutionary dynamics.

evolutionary biology↗

bioRxiv2018

Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum

In their competition for hosts, parasites with antigens that are novel to host immunity will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For Plasmodium falciparum-the causative agent of malaria-in endemic regions, the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering; this undermines the definition of strains as specific, temporally-persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within, than between, the modules, and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is in turn associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.\n\nSignificanceMany pathogens, including the causative agent of malaria Plasmodium falciparum, use antigenic variation, obtained via recombination, as a strategy to evade the human immune system. The vast diversity and multiplicity of genes encoding antigenic variation in high transmission regions challenge the notion of the existence of distinct strains: temporally-persistent and specific combinations of genes relevant to epidemiology. We examine the role of human immune selection in generating such genetic population structure in the major blood-stage antigen of Plasmodium falciparum. We show, using simulated and empirical data, that immune selection generates and maintains modules of genomes with higher genetic similarity within, than between, these groups. Selection further promotes the persistence of these modules for much longer times than those of their constituent genomes. Simulations show that the temporal modular structure reduces the speed at which hosts acquire immunity to the parasite. We argue that in P. falciparum modules can be viewed as dynamic strains occupying different niches in human immune space; they are thus relevant to formulating transmission models that encompass the antigenic diversity of the parasite. Our analyses may prove useful to understand the interplay between temporal genetic structure and epidemiology in other pathogens of human and wildlife importance.

ecology↗

bioRxiv2017

Networks of genetic similarity reveal non-neutral processes shape strain structure in Plasmodium falciparum

Pathogens compete for hosts through patterns of cross-protection conferred by immune responses to antigens. In Plasmodium falciparum malaria, the var multigene family encoding for the major blood-stage antigen PfEMP1 has evolved enormous genetic diversity through ectopic recombination and mutation. With 50-60 var genes per genome, it is unclear whether immune selection can act as a dominant force in structuring var repertoires of local populations. The combinatorial complexity of the var system remains beyond the reach of existing strain theory, and previous evidence for non-random structure cannot demonstrate immune selection without comparison to neutral models. We develop two neutral models that encompass malaria epidemiology but exclude competitive interactions between parasites. These models, combined with networks of genetic similarity, reveal non-neutral strain structure in both simulated systems and an extensively sampled population in Ghana. The unique population structure we identify underlies the large transmission reservoir characteristic of highly endemic regions in Africa.

ecology↗