Alberto Pascual-García

The architecture of mutualistic networks minimizes competition and increases biodiversity

The main theories of biodiversity either neglect species interactions or assume that species interact randomly with each other. However, recent empirical work has revealed that ecological networks are highly structured, and the lack of a theory that takes into account the structure of interactions precludes further assessment of the implications of such network patterns for biodiversity. Here we use a combination of analytical and empirical approaches to quantify the influence of network architecture on the number of coexisting species. As a case study we consider mutualistic networks between plants and their animal pollinators or seed dispersers. These networks have been found to be highly nested, with the more specialist species interacting only with proper subsets of the species that interact with the more generalist. We show that nestedness reduces effective interspecific competition and enhances the number of coexisting species. Furthermore, we show that a nested network will naturally emerge if new species are more likely to enter the community where they have minimal competitive load. Nested networks seem to occur in many biological and social contexts, suggesting that our results are relevant in a wide range of fields.

Microbial Succession in the Gut: Directional Trends of Taxonomic and Functional Change in a Birth Cohort of Spanish Infants

In spite of its major impact on life-long health, the process of microbial succession in the gut of infants remains poorly understood. Here, we analyze the patterns of taxonomic and functional change in the gut microbiota during the first year of life for a birth cohort of 13 infants. We detect that individual instances of gut colonization vary in the temporal dynamics of microbiota richness, diversity, and composition at both functional and taxonomic levels. Nevertheless, trends discernible in a majority of infants indicate that gut colonization occurs in two distinct phases of succession, separated by the introduction of solid foods to the diet. This change in resource availability causes a sharp decrease in the taxonomic richness of the microbiota due to the loss of rare taxa (p = 2.06e-9), although the number of core genera shared by all infants increases substantially. Moreover, although the gut microbial succession is not strictly deterministic, we detect an overarching directionality of change through time towards the taxonomic and functional composition of the maternal microbiota. Succession is however not complete by the one year mark, as significant differences remain between one-year-olds and their mothers in terms of taxonomic (p = 0.009) and functional (p = 0.004) microbiota composition, and in taxonomic richness (p = 2.76e-37) and diversity (p = 0.016). Our results also indicate that the taxonomic composition of the microbiota shapes its functional capacities. Therefore, the observed inter-individual variability in taxonomic composition during succession is not fully compensated by functional equivalence among bacterial genera and may have important physiological consequences. Finally, network analyses suggest that positive interactions among core genera during community assembly contribute to ensure their permanence within the gut, and highlight an expansion of complexity in the interactions network as the core of taxa shared by all infants grows following the introduction of solid foods.

Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php

Quantifying the evolutionary divergence of protein structures: The role of function change and function conservation

The molecular clock hypothesis, stating that protein sequences diverge in evolution by accumulating amino acid substitutions at an almost constant rate, played a major role in the development of molecular evolution and boosted quantitative theories of evolutionary change. These studies were extended to protein structures by the seminal paper by Chothia and Lesk, which established the approximate proportionality between structure and sequence divergence. Here we analyse how function influences the relationship between sequence and structure divergence, studying four large superfamilies of evolutionarily related proteins: globins, aldolases, P‐loop and NADP‐binding. We introduce the contact divergence, which is more consistent with sequence divergence than previously used structure divergence measures. Our main findings are: (1) Small structure and sequence divergences are proportional, consistent with the molecular clock. Approximate validity of the clock is also supported by the analysis of the clustering coefficient of structure similarity networks. (2) Functional constraints strongly limit the structure divergence of proteins performing the same function and may allow to identify incomplete or wrong functional annotations. (3) The rate of structure versus sequence divergence is larger for proteins performing different functions than for proteins performing the same function. We conjecture that this acceleration is due to positive selection for new functions. Accelerations in structure divergence are also suggested by the analysis of the clustering coefficient. (4) For low sequence identity, structural diversity explodes. We conjecture that this explosion is related to functional diversification. (5) Large indels are almost always associated with function changes. Proteins 2010.

Bacteria dialog with Santa Rosalia: Are aggregations of cosmopolitan bacteria mainly explained by habitat filtering or by ecological interactions?

BackgroundSince the landmark Santa Rosalia paper by Hutchinson, niche theory addresses the determinants of biodiversity in terms of both environmental and biological aspects. Disentangling the role of habitat filtering and interactions with other species is critical for understanding microbial ecology. Macroscopic biogeography explores hypothetical ecological interactions through the analysis of species associations. These methods have started to be incorporated into microbial ecology relatively recently, due to the inherent experimental difficulties and the coarse grained nature of the data.ResultsHere we investigate the influence of environmental preferences and ecological interactions in the tendency of bacterial taxa to either aggregate or segregate, using a comprehensive dataset of bacterial taxa observed in a wide variety of environments. We assess significance of taxa associations through a null model that takes into account habitat preferences and the global distribution of taxa across samples. The analysis of these associations reveals a surprisingly large number of significant aggregations between taxa, with a marked community structure and a strong propensity to aggregate for cosmopolitan taxa. Due to the coarse grained nature of our data we cannot conclusively reject the hypothesis that many of these aggregations are due to environmental preferences that the null model fails to reproduce. Nevertheless, some observations are better explained by ecological interactions than by habitat filtering. In particular, most pairs of aggregating taxa co-occur in very different environments, which makes it unlikely that these associations are due to habitat preferences, and many are formed by cosmopolitan taxa without well defined habitat preferences. Moreover, known cooperative interactions are retrieved as aggregating pairs of taxa. As observed in similar studies, we also found that phylogenetically related taxa are much more prone to aggregate than to segregate, an observation that may play a role in bacterial speciation.ConclusionsWe hope that these results stimulate experimental verification of the putative cooperative interactions between cosmopolitan bacteria, and we suggest several groups of aggregated cosmopolitan bacteria that are interesting candidates for such an investigation.

Mutualism supports biodiversity when the direct competition is weak

A key question of theoretical ecology is which properties of ecosystems favour their stability and help maintaining biodiversity. This question recently reconsidered mutualistic systems, generating intense controversy about the role of mutualistic interactions and their network architecture. Here we show analytically and verify with simulations that reducing the effective interspecific competition and the propagation of perturbations positively influences structural stability against environmental perturbations, enhancing persistence. Noteworthy, mutualism reduces the effective interspecific competition only when the direct interspecific competition is weaker than a critical value. This critical competition is in almost all cases larger in pollinator networks than in random networks with the same connectance. Highly connected mutualistic networks reduce the propagation of environmental perturbations, a mechanism reminiscent of MacArthur’s proposal that ecosystem complexity enhances stability. Our analytic framework rationalizes previous contradictory results, and it gives valuable insight on the complex relationship between mutualism and biodiversity.

Learning structural bioinformatics and evolution with a snake puzzle

Wepropose here a working unit for teaching basic concepts of structural bioinformatics and evolution through the example of a wooden snake puzzle, strikingly similar to toy models widely used in the literature of protein folding. In our experience, developed at a Master’s course at the Universidad Autónoma deMadrid (Spain), the concreteness of this example helps to overcome difficulties caused by the interdisciplinary nature of this field and its high level of abstraction, in particular for students coming from traditional disciplines. The puzzle will allow us discussing a simple algorithm for finding folded solutions, through which we will introduce the concept of the configuration space and the contact matrix representation. This is a central tool for comparing protein structures, for studying simple models of protein energetics, and even for a qualitative discussion of folding kinetics, through the concept of the Contact Order. It also allows a simple representation ofmisfolded conformations and their free energy. These concepts will motivate evolutionary questions, which we will address by simulating a structurally constrainedmodel of protein evolution, againmodelled on the snake puzzle. In thisway, we can discuss the analogy between evolutionary concepts and statisticalmechanics that facilitates the understanding of both concepts. The proposed examples and literature are accessible, andwe provide supplementarymaterial (see ‘Data Availability’) to reproduce the numerical experiments. We also suggest possible directions to expand the unit. We hope that this work will further stimulate the adoption of games in teaching practice. Subjects Bioinformatics, Computational Biology, Computer Education, Scientific Computing and Simulation

Effective competition determines the global stability of model ecosystems

We investigate the stability of Lotka-Volterra (LV) models constituted by two groups of species such as plants and animals in terms of the intragroup effective competition matrix, which allows separating the equilibrium equations of the two groups. In matrix analysis, the effective competition matrix represents the Schur complement of the species interaction matrix. It has been previously shown that the main eigenvalue of this effective competition matrix strongly influences the structural stability of the model ecosystem. Here, we show that the spectral properties of the effective competition matrix also strongly influence the dynamical stability of the model ecosystem. In particular, a necessary condition for diagonal stability of the full system, which guarantees global stability, is that the effective competition matrix is diagonally stable, which means that intergroup interactions must be weaker than intra-group competition in appropriate units. For mutualistic or competitive interactions, diagonal stability of the effective competition is a sufficient condition for global stability if the inter-group interactions are suitably correlated, in the sense that the biomass that each species provides to (removes from) the other group must be proportional to the biomass that it receives from (is removed by) it. For a non-LV mutualistic system with saturating interactions, we show that the diagonal stability of the corresponding LV system close to the fixed point is a sufficient condition for global stability.