A gene regulatory network critical for axillary bud dormancy directly controlled by Arabidopsis BRANCHED1.

The Arabidopsis thaliana transcription factor BRANCHED1 (BRC1) plays a pivotal role in the control of shoot branching as it integrates environmental and endogenous signals that influence axillary bud growth. Despite its remarkable activity as a growth inhibitor, the mechanisms by which BRC1 promotes bud dormancy are largely unknown. We determined the genome-wide BRC1 binding sites in vivo and combined these with transcriptomic data and gene co-expression analyses to identify bona fide BRC1 direct targets. Next, we integrated multi-omics data to infer the BRC1 gene regulatory network (GRN) and used graph theory techniques to find network motifs that control the GRN dynamics. We generated an open online tool to interrogate this network. A group of BRC1 target genes encoding transcription factors (BTFs) orchestrate this intricate transcriptional network enriched in abscisic acid-related components. Promoter::ß-GLUCURONIDASE transgenic lines confirmed that BTFs are expressed in axillary buds. Transient co-expression assays and studies in planta using mutant lines validated the role of BTFs in modulating the GRN and promoting bud dormancy. This knowledge provides access to the developmental mechanisms that regulate shoot branching and helps identify candidate genes to use as tools to adapt plant architecture and crop production to ever-changing environmental conditions.

Turnover in Life-Strategies Recapitulates Marine Microbial Succession Colonizing Model Particles.

Particulate organic matter (POM) in the ocean sustains diverse communities of bacteria that mediate the remineralization of organic complex matter. However, the variability of these particles and of the environmental conditions surrounding them present a challenge to the study of the ecological processes shaping particle-associated communities and their function. In this work, we utilize data from experiments in which coastal water communities are grown on synthetic particles to ask which are the most important ecological drivers of their assembly and associated traits. Combining 16S rRNA amplicon sequencing with shotgun metagenomics, together with an analysis of the full genomes of a subset of isolated strains, we were able to identify two-to-three distinct community classes, corresponding to early vs. late colonizers. We show that these classes are shaped by environmental selection (early colonizers) and facilitation (late colonizers) and find distinctive traits associated with each class. While early colonizers have a larger proportion of genes related to the uptake of nutrients, motility, and environmental sensing with few pathways enriched for metabolism, late colonizers devote a higher proportion of genes for metabolism, comprising a wide array of different pathways including the metabolism of carbohydrates, amino acids, and xenobiotics. Analysis of selected pathways suggests the existence of a trophic-chain topology connecting both classes for nitrogen metabolism, potential exchange of branched chain amino acids for late colonizers, and differences in bacterial doubling times throughout the succession. The interpretation of these traits suggests a distinction between early and late colonizers analogous to other classifications found in the literature, and we discuss connections with the classical distinction between r- and K-strategists.

Relationships between community composition, productivity and invasion resistance in semi-natural bacterial microcosms.

Common garden experiments that inoculate a standardised growth medium with synthetic microbial communities (i.e. constructed from individual isolates or using dilution cultures) suggest that the ability of the community to resist invasions by additional microbial taxa can be predicted by the overall community productivity (broadly defined as cumulative cell density and/or growth rate). However, to the best of our knowledge, no common garden study has yet investigated the relationship between microbial community composition and invasion resistance in microcosms whose compositional differences reflect natural, rather than laboratory-designed, variation. We conducted experimental invasions of two bacterial strains (Pseudomonas fluorescens and Pseudomonas putida) into laboratory microcosms inoculated with 680 different mixtures of bacteria derived from naturally occurring microbial communities collected in the field. Using 16S rRNA gene amplicon sequencing to characterise microcosm starting composition, and high-throughput assays of community phenotypes including productivity and invader survival, we determined that productivity is a key predictor of invasion resistance in natural microbial communities, substantially mediating the effect of composition on invasion resistance. The results suggest that similar general principles govern invasion in artificial and natural communities, and that factors affecting resident community productivity should be a focal point for future microbial invasion experiments.

Much like animals and plants, microorganisms such as bacteria and fungi naturally live in communities, where different species exist together and share the same resources. These communities can be quite stable over time and resist the invasion of new species ­ for example, by collectively and rapidly consuming all the available resources before invaders arrive. The gut microbiome is one example of such a microbial community, but there are many others. There have been many studies of how artificial microbial communities created in the lab resist invasion, but it remains unclear how naturally-occurring microbial communities do so, because they are harder to study in the lab. A leading theory is that certain combinations of microbes (i.e. communities) grow and consume resources faster than other combinations ­ this is known as achieving high productivity. Jones et al. conducted invasion experiments across hundreds of naturally-occurring microbial communities collected from woodland puddles that form in the exposed roots of beech trees. Each community contained different combinations of bacteria, but they all largely survived by breaking down leaf litter, so Jones et al. created a tea from beech leaves in which to grow these natural communities in the lab. The relationships between community composition, productivity and invasion resistance were then assessed using a combination of DNA sequencing, measurements of community growth and measurements of invader survival. Jones et al. found that natural combinations of bacteria that grew well together drove invasion resistance in these communities, mirroring results seen in much more artificial communities grown in the lab. These results suggest that productivity is a key factor underpinning invasion resistance in naturally-occurring microbial communities. This is a useful insight that could shape thinking about how the long-term stability of beneficial microbial communities ­ such as healthy gut microbiomes ­ might be improved, and how harmful communities ­ such as dental plaques ­ could be destabilised. The next step will be to conduct similar experiments in other natural microbe communities to see how generally applicable these results are.

Empowering the crowd: feasible strategies for epidemic management in high-density informal settlements. The case of COVID-19 in Northwest Syria.

More than 1 billion people live in informal settlements worldwide, where precarious living conditions pose unique challenges to managing a COVID-19 outbreak. Taking Northwest Syria as a case study, we simulated an outbreak in high-density informal Internally Displaced Persons (IDP) camps using a stochastic Susceptible-Exposed-Infectious-Recovered model. Expanding on previous studies, taking social conditions and population health/structure into account, we modelled several interventions feasible in these settings: moderate self-distancing, self-isolation of symptomatic cases and protection of the most vulnerable in 'safety zones'. We considered complementary measures to these interventions that can be implemented autonomously by these communities, such as buffer zones, health checks and carers for isolated individuals, quantifying their impact on the micro-dynamics of disease transmission. All interventions significantly reduce outbreak probability and some of them reduce mortality when an outbreak does occur. Self-distancing reduces mortality by up to 35% if contacts are reduced by 50%. A reduction in mortality by up to 18% can be achieved by providing one self-isolation tent per eight people. Protecting the most vulnerable in a safety zone reduces the outbreak probability in the vulnerable population and has synergistic effects with the other interventions. Our model predicts that a combination of all simulated interventions may reduce mortality by more than 90% and delay an outbreak's peak by almost 2 months. Our results highlight the potential for non-medical interventions to mitigate the effects of the pandemic. Similar measures may be applicable to controlling COVID-19 in other informal settlements, particularly IDP camps in conflict regions, around the world.

Phylogenetic Core Groups: a promising concept in search of a consistent methodological framework : Comment to ``A conceptual framework for the phylogenetically-constrained assembly of microbial communities''.

In this comment, we analyse the conceptual framework proposed by Aguirre de Cárcer (Microbiome 7:142, 2019), introducing the novel concept of Phylogenetic Core Groups (PCGs). This notion aims to complement the traditional classification in operational taxonomic units (OTUs), widely used in microbial ecology, to provide a more intrinsic taxonomical classification which avoids the use of pre-determined thresholds. However, to introduce this concept, the author frames his proposal in a wider theoretical framework based on a conceptualization of selection that we argue is a tautology. This blurs the subsequent formulation of an assembly principle for microbial communities, favouring that some contradictory examples introduced to support the framework appear aligned in their conclusions. And more importantly, under this framework and its derived methodology, it is not possible to infer PCGs from data in a consistent way. We reanalyse the proposal to identify its logical and methodological flaws and, through the analysis of synthetic scenarios, we propose a number of methodological refinements to contribute towards the determination of PCGs in a consistent way. We hope our analysis will promote the exploration of PCGs as a potentially valuable tool, helping to bridge the gap between environmental conditions and community composition in microbial ecology. Video Abstract.

Importance of environmental factors over habitat connectivity in shaping bacterial communities in microbial mats and bacterioplankton in an Antarctic freshwater system.

Freshwater ecosystems are considered hotspots of biodiversity in Antarctic polar deserts. Anticipated warming is expected to change the hydrology of these systems due to increased meltwater and reduction of ice cover, with implications for environmental conditions and physical connectivity between habitats. Using 16S rRNA gene sequencing, we evaluated microbial mat and planktonic communities within a connected freshwater system in the McMurdo Wright Valley, Antarctica, to determine the roles of connectivity and habitat conditions in controlling microbial assemblage composition. We examined communities from glacial Lake Brownworth, the perennially ice-covered Lake Vanda and the Onyx River, which connects the two. In Lake Vanda, we found distinct microbial assemblages occupying sub-habitats at different lake depths, while the communities from Lake Brownworth and Onyx River were structurally similar. Despite the higher physical connectivity and dispersal opportunities between bacterial communities in the shallow parts of the system, environmental abiotic conditions dominated over dispersal in driving community structure. Functional metabolic pathway predictions suggested differences in the functional gene potential between the microbial mat communities located in shallower and deeper water depths. The findings suggest that increasing temperatures and meltwater due to future climate change will affect bacterial diversity and functioning in Antarctic freshwater ecosystems.

Impact of manipulation of glycerol/diol dehydratase activity on intestinal microbiota ecology and metabolism.

Glycerol/diol dehydratases (GDH) are enzymes that catalyse the production of propionate from 1,2-propanediol, and acrolein from glycerol. Acrolein reacts with dietary carcinogenic heterocyclic amines (HCA), reducing HCA mutagenicity, but is itself also an antimicrobial agent and toxicant. Gut microbial GDH activity has been suggested as an endogenous acrolein source; however, there is limited information on the potential of the intestinal microbiota to have GDH activity, and what impact it can have on the intestinal ecosystem and host health. We hypothesized that GDH activity of gut microbiota is determined by the abundance and distribution of GDH-active taxa and can be enhanced by supplementation of the GDH active Anaerobutyricum hallii, and tested this hypothesis combining quantitative profiling of gdh, model batch fermentations, microbiota manipulation, and kinetic modelling of acrolein formation. Our results suggest that GDH activity is a common trait of intestinal microbiota shared by a few taxa, which was dependent on overall gdh abundance. Anaerobutyricum hallii was identified as a key taxon in GDH metabolism, and its supplementation increased the rate of GDH activity and acrolein release, which enhanced the transformation of HCA and reduced fermentation activity. The findings of this first systematic study on acrolein release by intestinal microbiota indicate that dietary and microbial modulation might impact GDH activity, which may influence host health.

Community-level signatures of ecological succession in natural bacterial communities.

A central goal in microbial ecology is to simplify the extraordinary biodiversity that inhabits natural environments into ecologically coherent units. We profiled (16S rRNA sequencing)  > 700 semi-aquatic bacterial communities while measuring their functional capacity when grown in laboratory conditions. This approach allowed us to investigate the relationship between composition and function excluding confounding environmental factors. Simulated data allowed us to reject the hypothesis that stochastic processes were responsible for community assembly, suggesting that niche effects prevailed. Consistent with this idea we identified six distinct community classes that contained samples collected from distant locations. Structural equation models showed there was a functional signature associated with each community class. We obtained a more mechanistic understanding of the classes using metagenomic predictions (PiCRUST). This approach allowed us to show that the classes contained distinct genetic repertoires reflecting community-level ecological strategies. The ecological strategies resemble the classical distinction between r- and K-strategists, suggesting that bacterial community assembly may be explained by simple ecological mechanisms.

Metabolically cohesive microbial consortia and ecosystem functioning.

Recent theory and experiments have reported a reproducible tendency for the coexistence of microbial species under controlled environmental conditions. This observation has been explained in the context of competition for resources and metabolic complementarity given that, in microbial communities (MCs), many excreted by-products of metabolism may also be resources. MCs therefore play a key role in promoting their own stability and in shaping the niches of the constituent taxa. We suggest that an intermediate level of organization between the species and the community level may be pervasive, where tightly knit metabolic interactions create discrete consortia that are stably maintained. We call these units Metabolically Cohesive Consortia (MeCoCos) and we discuss the environmental context in which we expect their formation, and the ecological and evolutionary consequences of their existence. We argue that the ability to identify MeCoCos would open new avenues to link the species-, community- and ecosystem-level properties, with consequences for our understanding of microbial ecology and evolution, and an improved ability to predict ecosystem functioning in the wild. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

The Molecular Clock in the Evolution of Protein Structures.

The molecular clock hypothesis, which states that substitutions accumulate in protein sequences at a constant rate, plays a fundamental role in molecular evolution but it is violated when selective or mutational processes vary with time. Such violations of the molecular clock have been widely investigated for protein sequences, but not yet for protein structures. Here, we introduce a novel statistical test (Significant Clock Violations) and perform a large scale assessment of the molecular clock in the evolution of both protein sequences and structures in three large superfamilies. After validating our method with computer simulations, we find that clock violations are generally consistent in sequence and structure evolution, but they tend to be larger and more significant in structure evolution. Moreover, changes of function assessed through Gene Ontology and InterPro terms are associated with large and significant clock violations in structure evolution. We found that almost one third of significant clock violations are significant in structure evolution but not in sequence evolution, highlighting the advantage to use structure information for assessing accelerated evolution and gathering hints of positive selection. Clock violations between closely related pairs are frequently significant in sequence evolution, consistent with the observed time dependence of the substitution rate attributed to segregation of neutral and slightly deleterious polymorphisms, but not in structure evolution, suggesting that these substitutions do not affect protein structure although they may affect stability. These results are consistent with the view that natural selection, both negative and positive, constrains more strongly protein structures than protein sequences. Our code for computing clock violations is freely available at https://github.com/ugobas/Molecular_clock.

Modular Assembly of Polysaccharide-Degrading Marine Microbial Communities.

Understanding the principles that govern the assembly of microbial communities across earth's biomes is a major challenge in modern microbial ecology. This pursuit is complicated by the difficulties of mapping functional roles and interactions onto communities with immense taxonomic diversity and of identifying the scale at which microbes interact [1]. To address this challenge, here, we focused on the bacterial communities that colonize and degrade particulate organic matter in the ocean [2-4]. We show that the assembly of these communities can be simplified as a linear combination of functional modules. Using synthetic polysaccharide particles immersed in natural bacterioplankton assemblages [1, 5], we showed that successional particle colonization dynamics are driven by the interaction of two types of modules: a first type made of narrowly specialized primary degraders, whose dynamics are controlled by particle polysaccharide composition, and a second type containing substrate-independent taxa whose dynamics are controlled by interspecific interactions-in particular, cross-feeding via organic acids, amino acids, and other metabolic byproducts. We show that, as a consequence of this trophic structure, communities can assemble modularly-i.e., by a simple sum of substrate-specific primary degrader modules, one for each complex polysaccharide in the particle, connected to a single broad-niche range consumer module. Consistent with this model, a linear combination of the communities on single-polysaccharide particles accurately predicts community composition on mixed-polysaccharide particles. Our results suggest that the assembly of heterotrophic communities that degrade complex organic materials follows simple design principles that could be exploited to engineer heterotrophic microbiomes.

A constructive approach to the epistemological problem of emergence in complex systems.

Emergent patterns in complex systems are related with many intriguing phenomena in modern science. One question that has sparked vigorous debates is if difficulties in the modelization of emergent behaviours are a consequence of ontological or epistemological limitations. To elucidate this question, we propose a novel approximation through constructive logic. Under this framework, experimental measurements will be considered conceptual building blocks from which we aim to achieve a description of the microstates ensemble mapping the macroscopic emergent observation. This procedure allow us to have full control of any information loss, thus making the analysis of different systems fairly comparable. In particular, we aim to look for compact descriptions of the constraints underlying a dynamical system, as a necessary a priori step to develop explanatory (mechanistic) models. We apply our proposal to a synthetic system to show that the number and scope of the system's constraints hinder our ability to build compact descriptions, being those systems under global constraints a limiting case in which such a description is unreachable. This result clearly links the epistemological limits of the framework selected with an ontological feature of the system, leading us to propose a definition of emergence strength which we make compatible with the scientific method through the active intervention of the observer on the system, following the spirit of Granger causality. We think that our approximation clarifies previous discrepancies found in the literature, reconciles distinct attempts to classify emergent processes, and paves the way to understand other challenging concepts such as downward causation.

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.

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

BACKGROUND: Since 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. RESULTS: Here 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. CONCLUSIONS: We 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.

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.

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.

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.

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.