M. Madan Babu

The genome of the social amoeba Dictyostelium discoideum

The social amoebae are exceptional in their ability to alternate between unicellular and multicellular forms. Here we describe the genome of the best-studied member of this group, Dictyostelium discoideum. The gene-dense chromosomes of this organism encode approximately 12,500 predicted proteins, a high proportion of which have long, repetitive amino acid tracts. There are many genes for polyketide synthases and ABC transporters, suggesting an extensive secondary metabolism for producing and exporting small molecules. The genome is rich in complex repeats, one class of which is clustered and may serve as centromeres. Partial copies of the extrachromosomal ribosomal DNA (rDNA) element are found at the ends of each chromosome, suggesting a novel telomere structure and the use of a common mechanism to maintain both the rDNA and chromosomal termini. A proteome-based phylogeny shows that the amoebozoa diverged from the animal–fungal lineage after the plant–animal split, but Dictyostelium seems to have retained more of the diversity of the ancestral genome than have plants, animals or fungi.

Genomic analysis of regulatory network dynamics reveals large topological changes

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here—particularly the large-scale topological changes and hub transience—will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Molecular signatures of G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) are physiologically important membrane proteins that sense signalling molecules such as hormones and neurotransmitters, and are the targets of several prescribed drugs. Recent exciting developments are providing unprecedented insights into the structure and function of several medically important GPCRs. Here, through a systematic analysis of high-resolution GPCR structures, we uncover a conserved network of non-covalent contacts that defines the GPCR fold. Furthermore, our comparative analysis reveals characteristic features of ligand binding and conformational changes during receptor activation. A holistic understanding that integrates molecular and systems biology of GPCRs holds promise for new therapeutics and personalized medicine.

Classification of Intrinsically Disordered Regions and Proteins.

1.1. Uncharacterized Protein Segments Are a Source of Functional Novelty Over the past decade, we have observed a massive increase in the amount of information describing protein sequences from a variety of organisms.1,2 While this may reflect the diversity in sequence space, and possibly also in function space,3 a large proportion of the sequences lacks any useful function annotation.4,5 Often these sequences are annotated as putative or hypothetical proteins, and for the majority their functions still remain unknown.6,7 Suggestions about potential protein function, primarily molecular function, often come from computational analysis of their sequences. For instance, homology detection allows for the transfer of information from well-characterized protein segments to those with similar sequences that lack annotation of molecular function.8−10 Other aspects of function, such as the biological processes proteins participate in, may come from genetic- and disease-association studies, expression and interaction network data, and comparative genomics approaches that investigate genomic context.11−17 Characterization of unannotated and uncharacterized protein segments is expected to lead to the discovery of novel functions as well as provide important insights into existing biological processes. In addition, it is likely to shed new light on molecular mechanisms of diseases that are not yet fully understood. Thus, uncharacterized protein segments are likely to be a large source of functional novelty relevant for discovering new biology.

Gene regulatory network growth by duplication

We are beginning to elucidate transcriptional regulatory networks on a large scale and to understand some of the structural principles of these networks, but the evolutionary mechanisms that form these networks are still mostly unknown. Here we investigate the role of gene duplication in network evolution. Gene duplication is the driving force for creating new genes in genomes: at least 50% of prokaryotic genes and over 90% of eukaryotic genes are products of gene duplication. The transcriptional interactions in regulatory networks consist of multiple components, and duplication processes that generate new interactions would need to be more complex. We define possible duplication scenarios and show that they formed the regulatory networks of the prokaryote Escherichia coli and the eukaryote Saccharomyces cerevisiae. Gene duplication has had a key role in network evolution: more than one-third of known regulatory interactions were inherited from the ancestral transcription factor or target gene after duplication, and roughly one-half of the interactions were gained during divergence after duplication. In addition, we conclude that evolution has been incremental, rather than making entire regulatory circuits or motifs by duplication with inheritance of interactions.

Tight Regulation of Unstructured Proteins: From Transcript Synthesis to Protein Degradation

Altered abundance of several intrinsically unstructured proteins (IUPs) has been associated with perturbed cellular signaling that may lead to pathological conditions such as cancer. Therefore, it is important to understand how cells precisely regulate the availability of IUPs. We observed that regulation of transcript clearance, proteolytic degradation, and translational rate contribute to controlling the abundance of IUPs, some of which are present in low amounts and for short periods of time. Abundant phosphorylation and low stochasticity in transcription and translation indicate that the availability of IUPs can be finely tuned. Fidelity in signaling may require that most IUPs be available in appropriate amounts and not present longer than needed.

Intrinsically disordered proteins: regulation and disease

Intrinsically disordered proteins (IDPs) are enriched in signaling and regulatory functions because disordered segments permit interaction with several proteins and hence the re-use of the same protein in multiple pathways. Understanding IDP regulation is important because altered expression of IDPs is associated with many diseases. Recent studies show that IDPs are tightly regulated and that dosage-sensitive genes encode proteins with disordered segments. The tight regulation of IDPs may contribute to signaling fidelity by ensuring that IDPs are available in appropriate amounts and not present longer than needed. The altered availability of IDPs may result in sequestration of proteins through non-functional interactions involving disordered segments (i.e., molecular titration), thereby causing an imbalance in signaling pathways. We discuss the regulation of IDPs, address implications for signaling, disease and drug development, and outline directions for future research.

An expanded Oct4 interaction network: implications for stem cell biology, development, and disease.

Summary The transcription factor Oct4 is key in embryonic stem cell identity and reprogramming. Insight into its partners should illuminate how the pluripotent state is established and regulated. Here, we identify a considerably expanded set of Oct4-binding proteins in mouse embryonic stem cells. We find that Oct4 associates with a varied set of proteins including regulators of gene expression and modulators of Oct4 function. Half of its partners are transcriptionally regulated by Oct4 itself or other stem cell transcription factors, whereas one-third display a significant change in expression upon cell differentiation. The majority of Oct4-associated proteins studied to date show an early lethal phenotype when mutated. A fraction of the human orthologs is associated with inherited developmental disorders or causative of cancer. The Oct4 interactome provides a resource for dissecting mechanisms of Oct4 function, enlightening the basis of pluripotency and development, and identifying potential additional reprogramming factors.

Tissue-specific splicing of disordered segments that embed binding motifs rewires protein interaction networks.

Summary Alternative inclusion of exons increases the functional diversity of proteins. Among alternatively spliced exons, tissue-specific exons play a critical role in maintaining tissue identity. This raises the question of how tissue-specific protein-coding exons influence protein function. Here we investigate the structural, functional, interaction, and evolutionary properties of constitutive, tissue-specific, and other alternative exons in human. We find that tissue-specific protein segments often contain disordered regions, are enriched in posttranslational modification sites, and frequently embed conserved binding motifs. Furthermore, genes containing tissue-specific exons tend to occupy central positions in interaction networks and display distinct interaction partners in the respective tissues, and are enriched in signaling, development, and disease genes. Based on these findings, we propose that tissue-specific inclusion of disordered segments that contain binding motifs rewires interaction networks and signaling pathways. In this way, tissue-specific splicing may contribute to functional versatility of proteins and increases the diversity of interaction networks across tissues.

A Database of Bacterial Lipoproteins (DOLOP) with Functional Assignments to Predicted Lipoproteins

Lipid modification of the N-terminal Cys residue (N-acyl-S-diacylglyceryl-Cys) has been found to be an essential, ubiquitous, and unique bacterial posttranslational modification. Such a modification allows anchoring of even highly hydrophilic proteins to the membrane which carry out a variety of functions important for bacteria, including pathogenesis. Hence, being able to identify such proteins is of great value. To this end, we have created a comprehensive database of bacterial lipoproteins, called DOLOP, which contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. The website also features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include the following: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins. The website, along with additional information on the biosynthetic pathway, statistics on predicted lipoproteins, and related figures, is available at http://www.mrc-lmb.cam.ac.uk/genomes/dolop/.