RBFOX1 regulates both splicing and transcriptional networks in human neuronal development.

RNA splicing plays a critical role in the programming of neuronal differentiation and, consequently, normal human neurodevelopment, and its disruption may underlie neurodevelopmental and neuropsychiatric disorders. The RNA-binding protein, fox-1 homolog (RBFOX1; also termed A2BP1 or FOX1), is a neuron-specific splicing factor predicted to regulate neuronal splicing networks clinically implicated in neurodevelopmental disease, including autism spectrum disorder (ASD), but only a few targets have been experimentally identified. We used RNA sequencing to identify the RBFOX1 splicing network at a genome-wide level in primary human neural stem cells during differentiation. We observe that RBFOX1 regulates a wide range of alternative splicing events implicated in neuronal development and maturation, including transcription factors, other splicing factors and synaptic proteins. Downstream alterations in gene expression define an additional transcriptional network regulated by RBFOX1 involved in neurodevelopmental pathways remarkably parallel to those affected by splicing. Several of these differentially expressed genes are further implicated in ASD and related neurodevelopmental diseases. Weighted gene co-expression network analysis demonstrates a high degree of connectivity among these disease-related genes, highlighting RBFOX1 as a key factor coordinating the regulation of both neurodevelopmentally important alternative splicing events and clinically relevant neuronal transcriptional programs in the development of human neurons.

Impact of profiling technologies in the understanding of recombinant protein production.

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Perceiving molecular evolution processes in Escherichia coli by comprehensive metabolite and gene expression profiling.

BACKGROUND: Evolutionary changes that are due to different environmental conditions can be examined based on the various molecular aspects that constitute a cell, namely transcript, protein, or metabolite abundance. We analyzed changes in transcript and metabolite abundance in evolved and ancestor strains in three different evolutionary conditions - excess nutrient adaptation, prolonged stationary phase adaptation, and adaptation because of environmental shift - in two different strains of bacterium Escherichia coli K-12 (MG1655 and DH10B). RESULTS: Metabolite profiling of 84 identified metabolites revealed that most of the metabolites involved in the tricarboxylic acid cycle and nucleotide metabolism were altered in both of the excess nutrient evolved lines. Gene expression profiling using whole genome microarray with 4,288 open reading frames revealed over-representation of the transport functional category in all evolved lines. Excess nutrient adapted lines were found to exhibit greater degrees of positive correlation, indicating parallelism between ancestor and evolved lines, when compared with prolonged stationary phase adapted lines. Gene-metabolite correlation network analysis revealed over-representation of membrane-associated functional categories. Proteome analysis revealed the major role played by outer membrane proteins in adaptive evolution. GltB, LamB and YaeT proteins in excess nutrient lines, and FepA, CirA, OmpC and OmpA in prolonged stationary phase lines were found to be differentially over-expressed. CONCLUSION: In summary, we report the vital involvement of energy metabolism and membrane-associated functional categories in all of the evolutionary conditions examined in this study within the context of transcript, outer membrane protein, and metabolite levels. These initial data obtained may help to enhance our understanding of the evolutionary process from a systems biology perspective.

2DBase: 2D-PAGE database of Escherichia coli.

We present a web-based integrated proteome database, termed 2DBase of Escherichia coli which was designed to store, compare, analyse, and retrieve various information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry. The main objectives of this database are (1) to provide the features for query and data-mining applications to access the stored proteomics data (2) to efficiently compare the specific protein spots present in the comparable proteome maps and (3) to analyse the data with the integrated classification for cellular functions of gene products of E. coli. This database currently contains 12 gels consisting of 1185 protein spots information in which 723 proteins were identified and annotated. Individual protein spots in the existing gels can be displayed, queried, analyzed, and compared in a tabular format based on various functional categories enabling quick and subsequent analyses. Our database satisfies the requirement to be a federated 2-DE database by accomplishing various tasks through a web interface providing access to a relational database system. The 2DBase of E. coli database can be accessed at http://2dbase.techfak.uni-bielefeld.de/.

The plasticity of global proteome and genome expression analyzed in closely related W3110 and MG1655 strains of a well-studied model organism, Escherichia coli-K12.

The use of Escherichia coli as a model organism has provided a great deal of basic information in biomolecular sciences. Examining trait differences among closely related strains of the same species addresses a fundamental biological question: how much diversity is there at the single species level? The main aim of our research was to identify significant differences in the activities of groups of genes between two laboratory strains of an organism closely related in genome structure. We demonstrate that despite strict and controlled growth conditions, there is high plasticity in the global proteome and genome expression in two closely related E. coli K12 sub-strains (W3110 and MG1655), which differ insignificantly in genome structure. The growth patterns of these two sub-strains were very similar in a well-equipped bioreactor, and their genome structures were shown to be almost identical by DNA microarray. However, detailed profiling of protein and gene expression by 2-dimensional gel electrophoresis and microarray analysis showed many differentially expressed genes and proteins, combinations of which were highly correlated. The differentially regulated genes and proteins belonged to the following functional categories: genes regulated by sigma subunit of RNA polymerase (RpoS), enterobactin-related genes, and genes involved in central metabolism. Genes involved in central cell metabolism - the glycolysis pathway, the tricarboxylic acid cycle and the glyoxylate bypass - were differentially regulated at both the mRNA and proteome levels. The strains differ significantly in central metabolism and thus in the generation of precursor metabolites and energy. This high plasticity probably represents a universal feature of metabolic activities in closely related species, and has the potential to reveal differences in regulatory networks. We suggest that unless care is taken in the choice of strains for any validating experiment, the results might be misleading.