2022 Serrapilheira/ICTP-SAIFR Training Program in Quantitative Biology and Ecology

Cooperation is a main driver of biological complexity at all levels. In the viral world, gene sharing among viral genomes, complementation between genomes or interactions within quasispecies are frequently observed. In this contribution, we explore the effects of flexible associations between fully fledged viruses and subviral entities, such as virus satellites, in viral dynamics and, in particular, in stable viral coexistence. We devise a mathematical model to compare different situations of competition between two viruses and to quantify how the association with a satellite qualitatively modifies dynamical equilibria. The relevant parameter is the invasion fitness of each virus or of the virus-satellite tandem, which in the model depends on the transmission rate of viruses and on their effect on host survival. In a virus-virus competition, one of the viruses becomes eventually extinct, recasting the competitive exclusion law of ecology. However, an association with a satellite might change the outcome of the competition in two ways, either to favor the less competitive virus (regardless of whether it is the helper virus or not) or to allow for the stable coexistence of the two viruses and the satellite. The virus-satellite association differs from other mechanisms proposed in ecology to date to enhance species coexistence. We hypothesize that such an association constitutes a parsimonious evolutionary pathway towards more stable cooperative associations, such as bipartite viral forms, a collaborative association unique to viruses.

The sequencing of ancient genomes has provided an unprecedented opportunity to study human evolutionary history over thousands of years, in different regions of the world. Here, I will describe several methods developed in our group to relate genomic data to informative parameters about population expansions, movement and adaptation, while explicitly accounting for both spatial and temporal dimensions. These include a new way to model the spread of ancestry in ancient genomes across a landscape, along with a new simulation framework for easily generating spatial simulations of arbitrary complexity. We have recently applied some of these methods to a new dataset including thousands of ancient human genomes and used them to infer major population movements over the past 13 millennia of Eurasian history.

Mathematical and computational models are powerful tools to investigate patterns and delve into the processes behind them, making sense of the complexity of natural systems, from individuals to communities. In this talk, I will present the two main lines that guide my research: interaction networks and evolutionary models. In the first part, I will discuss how interactions across different levels of organization are shaped in nature and discuss the theoretical processes that may have resulted in observed interaction patterns. In the second part, I will address how genetic structure is important for the evolution of strategies and how the evolutionary process leaves signals in phylogenetic trees. 

Macroecology, as a relatively new field in Ecology, holds distinct methodological characteristics that lead to profound philosophical changes in the nature of evidence to support and build theories and models. One reason for this is the impracticability of controlled or manipulative experimental studies at broad spatial and temporal scales, as well as historical contingencies and the complexity of ecological dynamics at these scales. We follow here a model-based reasoning for building scientific theories and show in particular how computer simulation models, applied to different case studies in diversity gradients, can be successfully used in macroecology as mediating theory and data.  

Diseases are mostly a consequence of an abnormality in multiple genes. Network Medicine investigates how genes interact to each other in complex intracellular and intercellular networks. The talk will show the recent advances on this emerging field of research and its impact on precision medicine and drug repositioning in Chikungunya, Zika, Malaria and Yellow Fever.