Sebastian E. Ahnert

Oscillating gene expression determines competence for periodic Arabidopsis root branching.

The Root of the Problem Developmental processes can define repeated patterns of structure, such as somites in vertebrates. In plants, too, repeated structures arise during growth and development. As the above-ground shoot grows, it sends out leaves or branches at intervals guided by hormone signaling. As the below-ground root grows, it too ramifies, sending out lateral roots. Moreno-Risueno et al. (p. 1306; see the Perspective by Traas and Vernoux) explored the expression of genes underlying development of lateral roots and found that oscillations in gene expression guide the specification of lateral roots. Oscillations in gene expression define the positions of periodic lateral roots in a plant model. Plants and animals produce modular developmental units in a periodic fashion. In plants, lateral roots form as repeating units along the root primary axis; however, the developmental mechanism regulating this process is unknown. We found that cyclic expression pulses of a reporter gene mark the position of future lateral roots by establishing prebranch sites and that prebranch site production and root bending are periodic. Microarray and promoter-luciferase studies revealed two sets of genes oscillating in opposite phases at the root tip. Genetic studies show that some oscillating transcriptional regulators are required for periodicity in one or both developmental processes. This molecular mechanism has characteristics that resemble molecular clock–driven activities in animal species.

An Arabidopsis gene regulatory network for secondary cell wall synthesis

The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here we present a protein–DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.

Flavor network and the principles of food pairing

The cultural diversity of culinary practice, as illustrated by the variety of regional cuisines, raises the question of whether there are any general patterns that determine the ingredient combinations used in food today or principles that transcend individual tastes and recipes. We introduce a flavor network that captures the flavor compounds shared by culinary ingredients. Western cuisines show a tendency to use ingredient pairs that share many flavor compounds, supporting the so-called food pairing hypothesis. By contrast, East Asian cuisines tend to avoid compound sharing ingredients. Given the increasing availability of information on food preparation, our data-driven investigation opens new avenues towards a systematic understanding of culinary practice.

The Rich Club of the C. elegans Neuronal Connectome

There is increasing interest in topological analysis of brain networks as complex systems, with researchers often using neuroimaging to represent the large-scale organization of nervous systems without precise cellular resolution. Here we used graph theory to investigate the neuronal connectome of the nematode worm Caenorhabditis elegans, which is defined anatomically at a cellular scale as 2287 synaptic connections between 279 neurons. We identified a small number of highly connected neurons as a rich club (N = 11) interconnected with high efficiency and high connection distance. Rich club neurons comprise almost exclusively the interneurons of the locomotor circuits, with known functional importance for coordinated movement. The rich club neurons are connector hubs, with high betweenness centrality, and many intermodular connections to nodes in different modules. On identifying the shortest topological paths (motifs) between pairs of peripheral neurons, the motifs that are found most frequently traverse the rich club. The rich club neurons are born early in development, before visible movement of the animal and before the main phase of developmental elongation of its body. We conclude that the high wiring cost of the globally integrative rich club of neurons in the C. elegans connectome is justified by the adaptive value of coordinated movement of the animal. The economical trade-off between physical cost and behavioral value of rich club organization in a cellular connectome confirms theoretical expectations and recapitulates comparable results from human neuroimaging on much larger scale networks, suggesting that this may be a general and scale-invariant principle of brain network organization.

A stele-enriched gene regulatory network in the Arabidopsis root.

Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one‐hybrid (Y1H) and two‐hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue‐specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered.

Protein Complexes Are under Evolutionary Selection to Assemble via Ordered Pathways

Summary Is the order in which proteins assemble into complexes important for biological function? Here, we seek to address this by searching for evidence of evolutionary selection for ordered protein complex assembly. First, we experimentally characterize the assembly pathways of several heteromeric complexes and show that they can be simply predicted from their three-dimensional structures. Then, by mapping gene fusion events identified from fully sequenced genomes onto protein complex assembly pathways, we demonstrate evolutionary selection for conservation of assembly order. Furthermore, using structural and high-throughput interaction data, we show that fusion tends to optimize assembly by simplifying protein complex topologies. Finally, we observe protein structural constraints on the gene order of fusion that impact the potential for fusion to affect assembly. Together, these results reveal the intimate relationships among protein assembly, quaternary structure, and evolution and demonstrate on a genome-wide scale the biological importance of ordered assembly pathways.

Principles of assembly reveal a periodic table of protein complexes.

The principles of protein assembly A knowledge of protein structure greatly enhances our understanding of protein function. In many cases, function depends on oligomerization. Ahnert et al. used mass spectrometry data together with a large-scale analysis of structures of protein complexes to examine the fundamental steps of protein assembly. Systematically combining assembly steps revealed a large set of quaternary topologies that were organized into a periodic table. Based on this table, the authors accurately predicted the expected frequencies of quaternary structure topologies. Science, this issue p. 10.1126/science.aaa2245 Understanding the organizing principles allows exhaustive enumeration of possible protein quaternary structure topologies. INTRODUCTION The assembly of proteins into complexes is crucial for most biological processes. The three-dimensional structures of many thousands of homomeric and heteromeric protein complexes have now been determined, and this has had a broad impact on our understanding of biological function and evolution. Despite this, the organizing principles that underlie the great diversity of protein quaternary structures observed in nature remain poorly understood, particularly in comparison with protein folds, which have been extensively classified in terms of their architecture and evolutionary relationships. RATIONALE In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization. Our approach was to consider protein complexes in terms of their assembly. Many protein complexes assemble spontaneously via ordered pathways in vitro, and these pathways have a strong tendency to be evolutionarily conserved. Furthermore, there are strong similarities between protein complex assembly and evolutionary pathways, with assembly pathways often being reflective of evolutionary histories, and vice versa. This suggests that it may be useful to consider the types of protein complexes that have evolved from the perspective of what assembly pathways are possible. RESULTS We first examined the fundamental steps by which protein complexes can assemble, using electrospray mass spectrometry experiments, literature-curated assembly data, and a large-scale analysis of protein complex structures. We found that most assembly steps can be classified into three basic types: dimerization, cyclization, and heteromeric subunit addition. By systematically combining different assembly steps in different ways, we were able to enumerate a large set of possible quaternary structure topologies, or patterns of key interfaces between the proteins within a complex. The vast majority of real protein complex structures lie within these topologies. This enables a natural organization of protein complexes into a “periodic table,” because each heteromer can be related to a simpler symmetric homomer topology. Exceptions are mostly the result of quaternary structure assignment errors, or cases where sequence-identical subunits can have different interactions and thus introduce asymmetry. Many of these asymmetric complexes fit the paradigm of a periodic table when their assembly role is considered. Finally, we implemented a model based on the periodic table, which predicts the expected frequencies of each quaternary structure topology, including those not yet observed. Our model correctly predicts quaternary structure topologies of recent crystal and electron microscopy structures that are not included in our original data set. CONCLUSION This work explains much of the observed distribution of known protein complexes in quaternary structure space and provides a framework for understanding their evolution. In addition, it can contribute considerably to the prediction and modeling of quaternary structures by specifying which topologies are most likely to be adopted by a complex with a given stoichiometry, potentially providing constraints for multi-subunit docking and hybrid methods. Lastly, it could help in the bioengineering of protein complexes by identifying which topologies are most likely to be stable, and thus which types of essential interfaces need to be engineered. Protein assembly steps lead to a periodic table of protein complexes and can predict likely quaternary structure topologies. Three main assembly steps are possible: cyclization, dimerization, and subunit addition. By combining these in different ways, a large set of possible quaternary structure topologies can be generated. These can be arranged on a periodic table that describes most known complexes and that can predict previously unobserved topologies. Structural insights into protein complexes have had a broad impact on our understanding of biological function and evolution. In this work, we sought a comprehensive understanding of the general principles underlying quaternary structure organization in protein complexes. We first examined the fundamental steps by which protein complexes can assemble, using experimental and structure-based characterization of assembly pathways. Most assembly transitions can be classified into three basic types, which can then be used to exhaustively enumerate a large set of possible quaternary structure topologies. These topologies, which include the vast majority of observed protein complex structures, enable a natural organization of protein complexes into a periodic table. On the basis of this table, we can accurately predict the expected frequencies of quaternary structure topologies, including those not yet observed. These results have important implications for quaternary structure prediction, modeling, and engineering.

The emergence of protein complexes: quaternary structure, dynamics and allostery

All proteins require physical interactions with other proteins in order to perform their functions. Most of them oligomerize into homomers, and a vast majority of these homomers interact with other proteins, at least part of the time, forming transient or obligate heteromers. In the present paper, we review the structural, biophysical and evolutionary aspects of these protein interactions. We discuss how protein function and stability benefit from oligomerization, as well as evolutionary pathways by which oligomers emerge, mostly from the perspective of homomers. Finally, we emphasize the specificities of heteromeric complexes and their structure and evolution. We also discuss two analytical approaches increasingly being used to study protein structures as well as their interactions. First, we review the use of the biological networks and graph theory for analysis of protein interactions and structure. Secondly, we discuss recent advances in techniques for detecting correlated mutations, with the emphasis on their role in identifying pathways of allosteric communication.

Comparison of pattern detection methods in microarray time series of the segmentation clock.

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

How much non-coding DNA do eukaryotes require?

Despite tremendous advances in the field of genomics, the amount and function of the large non-coding part of the genome in higher organisms remains poorly understood. Here we report an observation, made for 37 fully sequenced eukaryotic genomes, which indicates that eukaryotes require a certain minimum amount of non-coding DNA (ncDNA). This minimum increases quadratically with the amount of DNA located in exons. Based on a simple model of the growth of regulatory networks, we derive a theoretical prediction of the required quantity of ncDNA and find it to be in excellent agreement with the data. The amount of additional ncDNA (in basepairs) which eukaryotes require obeys N(DEF)=1/2 (N(C)/N(P)) (N(C)-N(P)), where N(C) is the amount of exonic DNA, and N(P) is a constant of about 10 Mb. This value N(DEF) corresponds to a few percent of the genome in Homo sapiens and other mammals, and up to half the genome in simpler eukaryotes. Thus, our findings confirm that eukaryotic life depends on a substantial fraction of ncDNA and also make a prediction of the size of this fraction, which matches the data closely.