Reactome array: forging a link between metabolome and genome

Sunlight Significantly Enhances Soil Denitrification via an Interfacial Biophotoelectrochemical Pathway

Denitrification is an essential step of the nitrogen cycle in soil. However, although sunlight is an important environmental factor for soil, the investigation of the influence of sunlight on soil denitrification is limited to plant photosynthesis-mediated processes. Herein, a new pathway, denoted as a biophotoelectrochemical process, which is induced by the direct photoexcitation of soil, was found to greatly enhance soil denitrification. Using red soil as the research object, the soil with irradiation showed nitrate reduction that was 2.6-4.7 times faster than that without irradiation. The irradiation of soil accelerated the reduction of nitrite and enhanced the conversion of nitrous oxide to nitrogen, indicating that more electron sources were generated. This resulted from the photoinduced generation of ferrous substrates and photoelectrons. The contribution of irradiation to soil denitrification was almost half (45.4%), of which 30.9% was from photoinduced ferrous substrates and 14.5% was from photoelectrons. Moreover, a designed biophotoelectrochemical cell provided solid evidence for direct photoelectron transfer from soil photosensitive substrates to microorganisms. Irradiation promoted the enrichment of Alicyclobacillus, which participates in iron oxidation and electroautotrophy. This finding reveals a role of sunlight in soil denitrification that has been thus seriously overlooked and provides solid evidence for the natural occurrence of photoelectrotrophic effects.

The identification of gene signature and critical pathway associated with childhood-onset type 2 diabetes

In general, type 2 diabetes (T2D) usually occurs in middle-aged and elderly people. However, the incidence of childhood-onset T2D has increased all across the globe. Therefore, it is very important to determine the molecular and genetic mechanisms of childhood-onset T2D. In this study, the dataset GSE9006 was downloaded from the GEO (Gene Expression Omnibus database); it includes 24 healthy children, 43 children with newly diagnosed Type 1 diabetes (T1D), and 12 children with newly diagnosed T2D. These data were used for differentially expressed genes (DGEs) analysis and weighted co-expression network analysis (WGCNA). We identified 192 up-regulated genes and 329 down-regulated genes by performing DEGs analysis. By performing WGGNA, we found that blue module (539 genes) was highly correlated to cyan module (97 genes). Gene ontology (GO) and pathway enrichment analyses were performed to figure out the functions and related pathways of genes, which were identified in the results of DEGs and WGCNA. Genes with conspicuous logFC and in the high correlated modules were input into GeneMANIA, which is a plugin of Cytoscape application. Thus, we constructed the protein-protein interaction (PPI) network (92 nodes and 254 pairs). Eventually, we analyzed the transcription factors and references related to genes with conspicuous logFC or high-degree genes, which were present in both the modules of WGCNA and PPI network. Current research shows that EGR1 and NAMPT can be used as marker genes for childhood-onset T2D. Gestational diabetes and chronic inflammation are risk factors that lead to the development of childhood-onset T2D.

Identification of key genes and pathways associated with obesity in children

The present study aimed to identify potential key genes and pathways in obese children in order to explore possible molecular mechanisms associated with child obesity. The array dataset GSE29718 was downloaded from the Gene Expression Omnibus database. Subcutaneous adipose tissue samples derived from 7 obese children and 8 lean children were selected for the analysis. Differentially expressed genes (DEGs) in samples from obese children compared with those from lean children were analyzed by the limma package. Gene ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes and Reactome pathway enrichment analyses for up and downregulated genes were performed. A protein-protein interaction (PPI) network was constructed with Cytoscape software and important genes associated with obesity were determined using IRegulon. A total of 199 DEGs (79 up and 120 downregulated genes) were identified in the samples of obese children compared with those from lean children. The PPI network was established with 103 nodes and 147 protein pairs. Matrix metalloproteinase 9 (MMP9) and acetyl-CoA carboxylase β (ACACB) were identified as hub genes in the PPI network and may therefore be marker genes for child obesity. In addition, upregulated DEGs were enriched in Reactome pathways associated with the immune system. Besides, MMP9 was upregulated in immune system processes as a GO term in the category Biological Processes. The results of the present study indicated that MMP9, ACACB and immune system pathways may have a significant role in child obesity.

Research integrity: the experience of a doubting Thomas

The sensational "reactome array" paper published in Science in 2009 was investigated in Spain by the Ethics Committee of Consejo Superior de Investigaciones Cientificas (CSIC) after Science issued an editorial expression of concern. The paper was retracted in 2010 because of "skepticism" due to "errors" in chemistry. The "errors" were so profound that many readers expressed doubt that they were really errors, but part of an elaborate hoax. I conducted a forensic analysis of mass spectrometry data in the paper's Supporting Online Material (SOM) and was able to prove that thousands of data values were in fact fabricated. The SOM contains signatures of improper extensive spreadsheet manipulations of incorrect atomic and molecular mass values as well as impossibly repetitive deviations of found molecular mass values from their expected values. No evidence of real mass spectrometry data was detected. Both CSIC and Science have been content to retract the paper without acknowledging the fabrications or assigning responsibility for them. Neither CSIC nor Science has expressed interest in having an independent investigation determining how the paper came to be written, reviewed and published. Their weak response to this episode is a daunting signal that there is an impending crisis in research integrity and science journalism.

Dealing with scientific integrity issues: the Spanish experience

Integrity has been an important matter of concern for the scientific community as it affects the basis of its activities. Most countries having a significant scientific activity have dealt with this problem by different means, including drafting specific legal or soft law regulations and the appointment of stable or ad hoc committees that take care of these questions. This has also been the case in Spain. After the period of transition between dictatorship to a democratic regime, and, particularly, after the entrance in the European Union, scientific activity has increased in the country. As it could be expected, problems of misconduct have appeared and different institutions have been dealing with these matters. One of the best examples is that of Consejo Superior de Investigaciones Cientificas (CSIC), the largest institution devoted to scientific research belonging to the Spanish Government. The experience of the CSIC’s Ethics Committee in dealing with conflicts related to scientific practices is discussed here.

The implications of relationships between human diseases and metabolic subpathways

One of the challenging problems in the etiology of diseases is to explore the relationships between initiation and progression of diseases and abnormalities in local regions of metabolic pathways. To gain insight into such relationships, we applied the “k-clique” subpathway identification method to all disease-related gene sets. For each disease, the disease risk regions of metabolic pathways were then identified and considered as subpathways associated with the disease. We finally built a disease-metabolic subpathway network (DMSPN). Through analyses based on network biology, we found that a few subpathways, such as that of cytochrome P450, were highly connected with many diseases, and most belonged to fundamental metabolisms, suggesting that abnormalities of fundamental metabolic processes tend to cause more types of diseases. According to the categories of diseases and subpathways, we tested the clustering phenomenon of diseases and metabolic subpathways in the DMSPN. The results showed that both disease nodes and subpathway nodes displayed slight clustering phenomenon. We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased. Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged. Furthermore, the coexpression levels between disease genes and other types of genes were calculated for each subpathway in the DMSPN. The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.

Core and panmetabolism in Escherichia coli

Escherichia coli exhibits a wide range of lifestyles encompassing commensalism and various pathogenic behaviors which its highly dynamic genome contributes to develop. How environmental and host factors shape the genetic structure of E. coli strains remains, however, largely unknown. Following a previous study of E. coli genomic diversity, we investigated its diversity at the metabolic level by building and analyzing the genome-scale metabolic networks of 29 E. coli strains (8 commensal and 21 pathogenic strains, including 6 Shigella strains). Using a tailor-made reconstruction strategy, we significantly improved the completeness and accuracy of the metabolic networks over default automatic reconstruction processes. Among the 1,545 reactions forming E. coli panmetabolism, 885 reactions were common to all strains. This high proportion of core reactions (57%) was found to be in sharp contrast to the low proportion (13%) of core genes in the E. coli pangenome, suggesting less diversity of metabolic functions compared to that of all gene functions. Core reactions were significantly overrepresented among biosynthetic reactions compared to the more variable degradation processes. Differences between metabolic networks were found to follow E. coli phylogeny rather than pathogenic phenotypes, except for Shigella networks, which were significantly more distant from the others. This suggests that most metabolic changes in non-Shigella strains were not driven by their pathogenic phenotypes. Using a supervised method, we were yet able to identify small sets of reactions related to pathogenicity or commensalism. The quality of our reconstructed networks also makes them reliable bases for building metabolic models.

Extensive in vivo metabolite-protein interactions revealed by large-scale systematic analyses

Natural small compounds comprise most cellular molecules and bind proteins as substrates, products, cofactors, and ligands. However, a large-scale investigation of in vivo protein-small metabolite interactions has not been performed. We developed a mass spectrometry assay for the large-scale identification of in vivo protein-hydrophobic small metabolite interactions in yeast and analyzed compounds that bind ergosterol biosynthetic proteins and protein kinases. Many of these proteins bind small metabolites; a few interactions were previously known, but the vast majority are new. Importantly, many key regulatory proteins such as protein kinases bind metabolites. Ergosterol was found to bind many proteins and may function as a general regulator. It is required for the activity of Ypk1, a mammalian AKT/SGK kinase homolog. Our study defines potential key regulatory steps in lipid biosynthetic pathways and suggests that small metabolites may play a more general role as regulators of protein activity and function than previously appreciated.

Systems approaches to microbial communities and their functioning

Recent advances in molecular microbial ecology and systems biology enhance insight into microbial community structure and functioning. They provide conceptual and technical bases for the translation of species-data and community-data into a model framework accounting for the functioning of and interactions between metabolic networks of species in multispecies environments. Function-directed and single cell-directed approaches supplement and improve metagenomics-derived community information. The topology of the metabolic network, reconstructed from a species' genome sequence, provides insight into its metabolic environments and interactions with other microorganisms. Progress in the theoretical and experimental analysis of flux through metabolic networks paves the way for their application at the community level, contributing to understanding of material flows between and within species and their resilience toward perturbations.

Exploring research frontiers in microbiology: the challenge of metagenomics in soil microbiology

Soil is one of the most complex and challenging environments for microbiologists. In fact, although it contains the largest microbial diversity on the planet, the majority of these microbes are still uncharacterized and represent an enormous unexplored reservoir of genetic and metabolic diversity. Metagenomics, the study of the entire genome of soil biota, currently represents a powerful tool for assessing the diversity of complex microbial communities, providing access to a number of new species, genes or novel molecules that are relevant for biotechnology and agricultural applications. In this paper, the onset of new high-throughput metagenomic approaches and new perspectives in soil microbial ecology and data handling are discussed.

Quantitative global studies of reactomes and metabolomes using a vectorial representation of reactions and chemical compounds

Background

Global studies of the protein repertories of organisms are providing important information on the characteristics of the protein space. Many of these studies entail classification of the protein repertory on the basis of structure and/or sequence similarities. The situation is different for metabolism. Because there is no good way of measuring similarities between chemical reactions, there is a barrier to the development of global classifications of "metabolic space" and subsequent studies comparable to those done for protein sequences and structures.

Results

In this work, we propose a vectorial representation of chemical reactions, which allows them to be compared and classified. In this representation, chemical compounds, reactions and pathways may be represented in the same vectorial space. We show that the representation of chemical compounds reflects their physicochemical properties and can be used for predictive purposes. We use the vectorial representations of reactions to perform a global classification of the reactome of the model organism E. coli.

Conclusions

We show that this unsupervised clustering results in groups of enzymes more coherent in biological terms than equivalent groupings obtained from the EC hierarchy. This hierarchical clustering produces an optimal set of 21 groups which we analyzed for their biological meaning.

Marine metagenomics: new tools for the study and exploitation of marine microbial metabolism

The marine environment is extremely diverse, with huge variations in pressure and temperature. Nevertheless, life, especially microbial life, thrives throughout the marine biosphere and microbes have adapted to all the divergent environments present. Large scale DNA sequence based approaches have recently been used to investigate the marine environment and these studies have revealed that the oceans harbor unprecedented microbial diversity. Novel gene families with representatives only within such metagenomic datasets represent a large proportion of the ocean metagenome. The presence of so many new gene families from these uncultured and highly diverse microbial populations represents a challenge for the understanding of and exploitation of the biology and biochemistry of the ocean environment. The application of new metagenomic and single cell genomics tools offers new ways to explore the complete metabolic diversity of the marine biome.