Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

miRNApath: A database of miRNAs, target genes and metabolic pathways

MicroRNAs (miRNAs) are small non-coding RNAs that regulate target gene expression and hence play important roles in metabolic pathways. Recent studies have evidenced the interrelation of miRNAs with cell proliferation, differentiation, development, and diseases. Since they are involved in gene regulation, they are intrinsically related to metabolic pathways. This leads to questions that are particularly interesting for investigating medical and laboratorial applications. We developed an miRNApath online database that uses miRNA target genes to link miRNAs to metabolic pathways. Currently, databases about miRNA target genes (DIANA miRGen), genomic maps (miRNAMap) and sequences (miRBase) do not provide such correlations. Additionally, miRNApath offers five search services and a download area. For each search, there is a specific type of input, which can be a list of target genes, miRNAs, or metabolic pathways, which results in different views, depending upon the input data, concerning relationships between the target genes, miRNAs and metabolic pathways. There are also internal links that lead to a deeper analysis and cross-links to other databases with more detailed information. miRNApath is being continually updated and is available at http://lgmb.fmrp.usp.br/mirnapath. ©FUNPEC-RP.

Whole Genome Analysis of Gene Expression Reveals Coordinated Activation of Signaling and Metabolic Pathways during Pollen-Pistil Interactions in Arabidopsis

Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

O-GlcNAc transferase integrates metabolic pathways to regulate the stability of c-MYC in human prostate cancer cells

Metabolic disruptions that occur widely in cancers offer an attractive focus for generalized treatment strategies. The hexosamine biosynthetic pathway (HBP) senses metabolic status and produces an essential substrate for O-linked β-N-acetylglucosamine transferase (OGT), which glycosylates and thereby modulates the function of its target proteins. Here, we report that the HBP is activated in prostate cancer cells and that OGT is a central regulator of c-Myc stability in this setting. HBP genes were overexpressed in human prostate cancers and androgen regulated in cultured human cancer cell lines. Immunohistochemical analysis of human specimens (n = 1987) established that OGT is upregulated at the protein level and that its expression correlates with high Gleason score, pT and pN stages, and biochemical recurrence. RNA interference-mediated siliencing or pharmacologic inhibition of OGT was sufficient to decrease prostate cancer cell growth. Microarray profiling showed that the principal effects of OGT inhibition in prostate cancer cells were related to cell-cycle progression and DNA replication. In particular, c-MYC was identified as a candidate upstream regulator of OGT target genes and OGT inhibition elicited a dose-dependent decrease in the levels of c-MYC protein but not c-MYC mRNA in cell lines. Supporting this relationship, expression of c-MYC and OGT was tightly correlated in human prostate cancer samples (n = 1306). Our findings identify HBP as a modulator of prostate cancer growth and c-MYC as a key target of OGT function in prostate cancer cells.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.

Relative contributions of lipooligosaccharide inner and outer core modifications to nontypeable Haemophilus influenzae pathogenesis

Nontypeable Haemophilus influenzae (NTHi) is a frequent commensal of the human nasopharynx that causes opportunistic infection in immunocompromised individuals. Existing evidence associates lipooligosaccharide (LOS) with disease, but the specific and relative contributions of NTHi LOS modifications to virulence properties of the bacterium have not been comprehensively addressed. Using NTHi strain 375, an isolate for which the detailed LOS structure has been determined, we compared systematically a set of isogenic mutant strains expressing sequentially truncated LOS. The relative contributions of 2-keto-3-deoxyoctulosonic acid, the triheptose inner core, oligosaccharide extensions on heptoses I and III, phosphorylcholine, digalactose, and sialic acid to NTHi resistance to antimicrobial peptides (AMP), self-aggregation, biofilm formation, cultured human respiratory epithelial infection, and murine pulmonary infection were assessed. We show that opsX, lgtF, lpsA, lic1, and lic2A contribute to bacterial resistance to AMP; lic1 is related to NTHi self-aggregation; lgtF, lic1, and siaB are involved in biofilm growth; opsX and lgtF participate in epithelial infection; and opsX, lgtF, and lpsA contribute to lung infection. Depending on the phenotype, the involvement of these LOS modifications occurs at different extents, independently or having an additive effect in combination. We discuss the relative contribution of LOS epitopes to NTHi virulence and frame a range of pathogenic traits in the context of infection.

Nuclear ARRB1 induces pseudohypoxia and cellular metabolism reprogramming in prostate cancer

Tumour cells sustain their high proliferation rate through metabolic reprogramming, whereby cellular metabolism shifts from oxidative phosphorylation to aerobic glycolysis, even under normal oxygen levels. Hypoxia-inducible factor 1A (HIF1A) is a major regulator of this process, but its activation under normoxic conditions, termed pseudohypoxia, is not well documented. Here, using an integrative approach combining the first genome-wide mapping of chromatin binding for an endocytic adaptor, ARRB1, both in vitro and in vivo with gene expression profiling, we demonstrate that nuclear ARRB1 contributes to this metabolic shift in prostate cancer cells via regulation of HIF1A transcriptional activity under normoxic conditions through regulation of succinate dehydrogenase A (SDHA) and fumarate hydratase (FH) expression. ARRB1-induced pseudohypoxia may facilitate adaptation of cancer cells to growth in the harsh conditions that are frequently encountered within solid tumours. Our study is the first example of an endocytic adaptor protein regulating metabolic pathways. It implicates ARRB1 as a potential tumour promoter in prostate cancer and highlights the importance of metabolic alterations in prostate cancer.

Peroxisomal beta-oxidation--a metabolic pathway with multiple functions.

Fatty acid degradation in most organisms occurs primarily via the beta-oxidation cycle. In mammals, beta-oxidation occurs in both mitochondria and peroxisomes, whereas plants and most fungi harbor the beta-oxidation cycle only in the peroxisomes. Although several of the enzymes participating in this pathway in both organelles are similar, some distinct physiological roles have been uncovered. Recent advances in the structural elucidation of numerous mammalian and yeast enzymes involved in beta-oxidation have shed light on the basis of the substrate specificity for several of them. Of particular interest is the structural organization and function of the type 1 and 2 multifunctional enzyme (MFE-1 and MFE-2), two enzymes evolutionarily distant yet catalyzing the same overall enzymatic reactions but via opposite stereochemistry. New data on the physiological roles of the various enzymes participating in beta-oxidation have been gathered through the analysis of knockout mutants in plants, yeast and animals, as well as by the use of polyhydroxyalkanoate synthesis from beta-oxidation intermediates as a tool to study carbon flux through the pathway. In plants, both forward and reverse genetics performed on the model plant Arabidopsis thaliana have revealed novel roles for beta-oxidation in the germination process that is independent of the generation of carbohydrates for growth, as well as in embryo and flower development, and the generation of the phytohormone indole-3-acetic acid and the signal molecule jasmonic acid.

Unprecedented loss of ammonia assimilation capability in a urease-encoding bacterial mutualist.

BACKGROUND: Blochmannia are obligately intracellular bacterial mutualists of ants of the tribe Camponotini. Blochmannia perform key nutritional functions for the host, including synthesis of several essential amino acids. We used Illumina technology to sequence the genome of Blochmannia associated with Camponotus vafer. RESULTS: Although Blochmannia vafer retains many nutritional functions, it is missing glutamine synthetase (glnA), a component of the nitrogen recycling pathway encoded by the previously sequenced B. floridanus and B. pennsylvanicus. With the exception of Ureaplasma, B. vafer is the only sequenced bacterium to date that encodes urease but lacks the ability to assimilate ammonia into glutamine or glutamate. Loss of glnA occurred in a deletion hotspot near the putative replication origin. Overall, compared to the likely gene set of their common ancestor, 31 genes are missing or eroded in B. vafer, compared to 28 in B. floridanus and four in B. pennsylvanicus. Three genes (queA, visC and yggS) show convergent loss or erosion, suggesting relaxed selection for their functions. Eight B. vafer genes contain frameshifts in homopolymeric tracts that may be corrected by transcriptional slippage. Two of these encode DNA replication proteins: dnaX, which we infer is also frameshifted in B. floridanus, and dnaG. CONCLUSIONS: Comparing the B. vafer genome with B. pennsylvanicus and B. floridanus refines the core genes shared within the mutualist group, thereby clarifying functions required across ant host species. This third genome also allows us to track gene loss and erosion in a phylogenetic context to more fully understand processes of genome reduction.

Lactic acidosis triggers starvation response with paradoxical induction of TXNIP through MondoA.

Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the "anti-Warburg" metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers.

Oncofetal gene SALL4 in aggressive hepatocellular carcinoma

Hepatocellular carcinoma is the third leading cause of cancer-related deaths worldwide. In the heterogeneous group of hepatocellular carcinomas, those with characteristics of embryonic stem-cell and progenitor-cell gene expression are associated with the worst prognosis. The oncofetal gene SALL4, a marker of a subtype of hepatocellular carcinoma with progenitor-like features, is associated with a poor prognosis and is a potential target for treatment.

Functional taxonomy of bacterial hyperstructures.

The levels of organization that exist in bacteria extend from macromolecules to populations. Evidence that there is also a level of organization intermediate between the macromolecule and the bacterial cell is accumulating. This is the level of hyperstructures. Here, we review a variety of spatially extended structures, complexes, and assemblies that might be termed hyperstructures. These include ribosomal or "nucleolar" hyperstructures; transertion hyperstructures; putative phosphotransferase system and glycolytic hyperstructures; chemosignaling and flagellar hyperstructures; DNA repair hyperstructures; cytoskeletal hyperstructures based on EF-Tu, FtsZ, and MreB; and cell cycle hyperstructures responsible for DNA replication, sequestration of newly replicated origins, segregation, compaction, and division. We propose principles for classifying these hyperstructures and finally illustrate how thinking in terms of hyperstructures may lead to a different vision of the bacterial cell.

Comparative genomics of metabolic networks of free-living and parasitic eukaryotes

Background Obligate endoparasites often lack particular metabolic pathways as compared to free-living organisms. This phenomenon comprises anabolic as well as catabolic reactions. Presumably, the corresponding enzymes were lost in adaptation to parasitism. Here we compare the predicted core metabolic graphs of obligate endoparasites and non-parasites (free living organisms and facultative parasites) in order to analyze how the parasites' metabolic networks shrunk in the course of evolution. Results Core metabolic graphs comprising biochemical reactions present in the presumed ancestor of parasites and non-parasites were reconstructed from the Kyoto Encyclopedia of Genes and Genomes. While the parasites' networks had fewer nodes (metabolites) and edges (reactions), other parameters such as average connectivity, network diameter and number of isolated edges were similar in parasites and non-parasites. The parasites' networks contained a higher percentage of ATP-consuming reactions and a lower percentage of NAD-requiring reactions. Control networks, shrunk to the size of the parasites' by random deletion of edges, were scale-free but exhibited smaller diameters and more isolated edges. Conclusions The parasites' networks were smaller than those of the non-parasites regarding number of nodes or edges, but not regarding network diameters. Network integrity but not scale-freeness has acted as a selective principle during the evolutionary reduction of parasite metabolism. ATP-requiring reactions in particular have been retained in the parasites' core metabolism while NADH- or NADPH-requiring reactions were lost preferentially.