Research
Adapted from Goldford et al. 2018 Science
I use laboratory experiments and theory to understand how microbial communities assemble in a given environment, and why.
For this, I use microbial communities from different environments (including the human gut or soil), and combine two complementary approaches: top-down community assembly to assess what combination of species are selected in a given environment; and bottom-up reconstitution of the dominant species to ask how they interact in duos, trios, and larger groups, in that same environment (Estrela et al. 2022).
Some of the questions I have asked include:
For this, I use microbial communities from different environments (including the human gut or soil), and combine two complementary approaches: top-down community assembly to assess what combination of species are selected in a given environment; and bottom-up reconstitution of the dominant species to ask how they interact in duos, trios, and larger groups, in that same environment (Estrela et al. 2022).
Some of the questions I have asked include:
- Can we predict how different nutrient combinations shape the composition of microbial communities?
- Which features of microbial communities are reproducible and predictable, which are not, and why?
- What explains the taxonomic variability we often see in microbial community assembly?
- How does migration affect community structure and dynamics?
- What role do species interactions play in shaping emergent community properties like function, spatial relationships, and stability?
From Aranda-Diaz et al. 2025 Cell Systems
Assembly of stool‑derived bacterial communities across diverse nutritional environments
Can we predict community composition when a single nutrient is added to a complex medium? By culturing thousands of communities derived from human stool across a range of supplemented single nutrients, we found that composition can be predicted from individual species resource utilization dynamics. Fast-growing species dominate due to an “early-bird” advantage: they first deplete their preferred niche in the complex medium and then rapidly switch to exploit the added nutrient. Slow-growing species persist at low constant abundance through resource partitioning in the complex medium. We also show that when the fastest grower is removed, the next fastest species dominates – demonstrating that early‑bird dynamics strongly govern community structure across diverse nutrient environments (Aranda-Diaz et al 2025).
Can we predict community composition when a single nutrient is added to a complex medium? By culturing thousands of communities derived from human stool across a range of supplemented single nutrients, we found that composition can be predicted from individual species resource utilization dynamics. Fast-growing species dominate due to an “early-bird” advantage: they first deplete their preferred niche in the complex medium and then rapidly switch to exploit the added nutrient. Slow-growing species persist at low constant abundance through resource partitioning in the complex medium. We also show that when the fastest grower is removed, the next fastest species dominates – demonstrating that early‑bird dynamics strongly govern community structure across diverse nutrient environments (Aranda-Diaz et al 2025).
From Estrela et al. 2022 Cell Systems
Convergence and divergence in microbial communities:
predictable metabolic functions, variable species
What makes some features of microbial communities predictable while others remain variable? We explored this by studying how communities assemble in identical glucose-limited environments. Despite differences in microbial species, communities consistently self-organized around key metabolic functions, with the ratio of dominant metabolic groups predicted by a simple resource-partitioning model. This convergence is driven by selection on metabolic traits shared among related species, which can perform equivalent metabolic roles. In contrast, species-level differences arise from multistability in population dynamics. While this multistability can lead to alternative functional states in closed ecosystems, bacterial migration in interconnected metacommunities helps homogenize communities and reduce variability (Estrela et al. 2022).
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Assembly of microbial communities in mixed nutrient environments
Can we predict how nutrients combine to shape the composition of microbial communities? For instance, if we know what communities assemble in environments with nutrient A and nutrient B separately, can we predict the community that will form in an environment with both nutrients (A+B)? By assembling communities in either pairs of nutrients (sugar-sugar, sugar- organic acid, and organic acid- organic acid) or each nutrient alone, we showed that certain nutrient pairs “interact” in a predictable manner at the family-level of taxonomic organization (Estrela et al. 2021). Specifically, sugars dominate over organic acids. To put it simply, communities assembled in a sugar-acid mixture look more like sugar communities than acid communities. More generally, this reveals that not all nutrients are equal when mixed together, and there exist regularities in how they interact when combined to shape the composition of microbial communities. |
Adapted from Estrela et al 2021 eLife
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Adapted from Estrela et al. 2012 (i) and from Estrela & Brown 2013; Estrela et al. 2015 (ii).
Metabolic interactions and consequences for microbial community functional and spatial relationships
How do metabolic interactions between species (cross-feeding, detoxification) shape their emergent functional and spatial relationships? We have shown that a single mechanism of metabolic exchange - food for detoxification of metabolic waste products- can generate a diverse array of ecological relationships, depending on the properties of the metabolic by-products exchanged (Estrela et al. 2012). In addition, using an individual-based model of biofilm growth, we showed that under competitive interactions microbial species tend to segregate while under mutualistic interactions they tend to mix (Estrela & Brown 2013).
I am also interested in applying fundamental principles of microbial interactions to real world problems, especially health and disease. Applying our findings to the challenge of antibiotic resistance, we recently showed that the ecological and spatial relationships between bacterial species impact how communities respond to antibiotics. In particular, we showed that competition between antibiotic-resistant and sensitive bacteria leads to the 'competitive release' of the resistant type whereas mutualism leads to a ‘mutualistic suppression' where both species are harmed by antibiotics. In addition, these effects may be magnified or dampened, respectively, in structured environments because competitors tend to segregate while mutualists tend to mix as they grow (Estrela & Brown 2018).
How do metabolic interactions between species (cross-feeding, detoxification) shape their emergent functional and spatial relationships? We have shown that a single mechanism of metabolic exchange - food for detoxification of metabolic waste products- can generate a diverse array of ecological relationships, depending on the properties of the metabolic by-products exchanged (Estrela et al. 2012). In addition, using an individual-based model of biofilm growth, we showed that under competitive interactions microbial species tend to segregate while under mutualistic interactions they tend to mix (Estrela & Brown 2013).
I am also interested in applying fundamental principles of microbial interactions to real world problems, especially health and disease. Applying our findings to the challenge of antibiotic resistance, we recently showed that the ecological and spatial relationships between bacterial species impact how communities respond to antibiotics. In particular, we showed that competition between antibiotic-resistant and sensitive bacteria leads to the 'competitive release' of the resistant type whereas mutualism leads to a ‘mutualistic suppression' where both species are harmed by antibiotics. In addition, these effects may be magnified or dampened, respectively, in structured environments because competitors tend to segregate while mutualists tend to mix as they grow (Estrela & Brown 2018).
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Evolution of microbial dependencies and host-microbe dependencies
Why and how do some species lose functions that leave them dependent on other species? We showed that whether full autonomy, one-way dependency or mutual dependency arises depends on the interplay between costs, essentiality and privatization level of the function (Estrela et al. 2015). In some cases, such dependencies can be so strong that 'individuals' (or organisms) eventually lose their own 'individuality' and merge together, forming a symbiotic organism. I am interested in why and how this happens. That is, why do different species come together to form a single, fully integrated organism (defined as a major egalitarian transition)? What are the evolutionary paths to symbiotic organismality? We have proposed that classifying host-symbiont associations into two interconnected continuum axes: a symbiont’s dependency for dispersal into new hosts (symbiont mode of transmission) and interdependency for reproduction, growth and survival (dependency for nutrients/services) can help us better understand and predict the evolutionary path to symbiotic organismality (Estrela et al. 2016). |
Adapted from Estrela et al (2015).
Adapted from Estrela et al (2016).
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