Georg Casari

Proteome survey reveals modularity of the yeast cell machinery

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

A physical and functional map of the human TNF-α/NF-κB signal transduction pathway

Signal transduction pathways are modular composites of functionally interdependent sets of proteins that act in a coordinated fashion to transform environmental information into a phenotypic response. The pro-inflammatory cytokine tumour necrosis factor (TNF)-α triggers a signalling cascade, converging on the activation of the transcription factor NF-κB, which forms the basis for numerous physiological and pathological processes. Here we report the mapping of a protein interaction network around 32 known and candidate TNF-α/NF-κB pathway components by using an integrated approach comprising tandem affinity purification, liquid-chromatography tandem mass spectrometry, network analysis and directed functional perturbation studies using RNA interference. We identified 221 molecular associations and 80 previously unknown interactors, including 10 new functional modulators of the pathway. This systems approach provides significant insight into the logic of the TNF-α/NF-κB pathway and is generally applicable to other pathways relevant to human disease.

CONSERVED CLUSTERS OF FUNCTIONALLY RELATED GENES IN TWO BACTERIAL GENOMES

Abstract. An approach for genome comparison, combining function classification of gene products and sequence comparison, is presented. The genomes of Haemophilus influenzae and Escherichia coli are analyzed, and all genes are classified into nine major functional classes, corresponding to important cellular processes. To study gene order relationships and genome organization in the two bacteria, we performed statistics on neighboring pairs of genes. To estimate the significance of the observations, a statistical model based on binomial distributions has been developed. Significant patterns of gene order are observed within, as well as between, the two bacterial genomes: Functionally related genes tend to be neighbors more often than do unrelated genes. Some of these groups represent well-known operons, but additional gene clusters are identified. These clusters correspond to genomic elements that have been conserved during bacterial evolution. In addition to nearest-neighbor relationships, the method is also useful to study the relative direction of transcription in genomes, which is also highly conserved between homologous gene pairs. This new approach combines the high-level description of molecular function with pair statistics that express genome organization. It is expected to complement traditional methods of sequence analysis in the study of genomic structure, function, and evolution.

Identification of farnesoid X receptor beta as a novel mammalian nuclear receptor sensing lanosterol

ABSTRACT Nuclear receptors are ligand-modulated transcription factors. On the basis of the completed human genome sequence, this family was thought to contain 48 functional members. However, by mining human and mouse genomic sequences, we identified FXRβ as a novel family member. It is a functional receptor in mice, rats, rabbits, and dogs but constitutes a pseudogene in humans and primates. Murine FXRβ is widely coexpressed with FXR in embryonic and adult tissues. It heterodimerizes with RXRα and stimulates transcription through specific DNA response elements upon addition of 9-cis-retinoic acid. Finally, we identified lanosterol as a candidate endogenous ligand that induces coactivator recruitment and transcriptional activation by mFXRβ. Lanosterol is an intermediate of cholesterol biosynthesis, which suggests a direct role in the control of cholesterol biosynthesis in nonprimates. The identification of FXRβ as a novel functional receptor in nonprimate animals sheds new light on the species differences in cholesterol metabolism and has strong implications for the interpretation of genetic and pharmacological studies of FXR-directed physiologies and drug discovery programs.

Modular decomposition of protein-protein interaction networks

We introduce an algorithmic method, termed modular decomposition, that defines the organization of protein-interaction networks as a hierarchy of nested modules. Modular decomposition derives the logical rules of how to combine proteins into the actual functional complexes by identifying groups of proteins acting as a single unit (sub-complexes) and those that can be alternatively exchanged in a set of similar complexes. The method is applied to experimental data on the pro-inflammatory tumor necrosis factor-α (TNF-α)/NFκB transcription factor pathway.

EXPLORING THE MYCOPLASMA-CAPRICOLUM GENOME - A MINIMAL CELL REVEALS ITS PHYSIOLOGY

We report on the analysis of 214 kb of the parasitic eubacterium Mycoplasma capricolum sequenced by genomic walking techniques. The 287 putative proteins detected to date represent about half of the estimated total number of 500 predicted for this organism. A large fraction of these (75%) can be assigned a likely function as a result of similarity searches. Several important features of the functional organization of this small genome are already apparent. Among these are (i) the expected relatively large number of enzymes involved in metabolic transport and activation, for efficient use of host cell nutrients; (ii) the presence of anabolic enzymes; (iii) the unexpected diversity of enzymes involved in DNA replication and repair: and (iv) a sizeable number of orthologues (82 so far) in Escherichia coli. This survey is beginning to provide a detailed view of how M. capricolum manages to maintain essential cellular processes with a genome much smaller than that of its bacterial relatives.

Classification of protein families and detection of the determinant residues with an improved self-organizing map

Abstract. Using a SOM (self-organizing map) we can classify sequences within a protein family into subgroups that generally correspond to biological subcategories. These maps tend to show sequence similarity as proximity in the map. Combining maps generated at different levels of resolution, the structure of relations in protein families can be captured that could not otherwise be represented in a single map. The underlying representation of maps enables us to retrieve characteristic sequence patterns for individual subgroups of sequences. Such patterns tend to correspond to functionally important regions. We present a modified SOM algorithm that includes a convergence test that dynamically controls the learning parameters to adapt them to the learning set instead of being fixed and externally optimized by trial and error. Given the variability of protein family size and distribution, the addition of this feature is necessary. The method is successfully tested with a number of families. The rab family of small GTPases is used to illustrate the performance of the method.

From molecular networks to qualitative cell behavior.

Adaptation and behavior are characteristics of life which are fundamentally dynamic. If we want to model the living cell we have to describe it as a dynamic system. Typical dynamic models are based on quantitative differential equations requiring very detailed kinetic knowledge. Alternative modeling techniques for less fine‐grained information are better suited to available functional genomics data. As such, constraint‐based techniques and qualitative modeling have proven themselves to be valid approaches in cell biology. These approaches offer formal support to check the consistency of molecular networks against phenotypic observations in the light of dynamic systems.

Computational comparisons of model genomes

Complete genomes from model organisms provide new challenges for computational molecular biology. Novel questions emerge from the genome data obtained from the functional prediction of thousands of gene products. In this review, we present some approaches to the computational comparison of genomes, based on sequence and text analysis, and comparisons of genome composition and gene order.

Characterization of new proteins found by analysis of short open reading frames from the full yeast genome.

We have analysed short open reading frames (between 150 and 300 base pairs long) of the yeast genome (Saccharomyces cerevisiae) with a two‐step strategy. The first step selects a candidate set of open reading frames from the DNA sequence based on statistical evaluation of DNA and protein sequence properties. The second step filters the candidate set by selecting open reading frames with high similarity to other known sequences (from any organism). As a result, we report ten new predicted proteins not present in the current sequence databases. These include a new alcohol dehydrogenase, a protein probably related to the cell cycle, as well as a homolog of the prokaryotic ribosomal protein L36 likely to be a mitochondrial ribosomal protein coded in the nuclear genome. We conclude that the analysis of short open reading frames leads to biologically interesting discoveries, even though the quantitative yield of new proteins is relatively low.