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Genes involved in complex adaptive processes tend to have highly conserved upstream regions in mammalian genomes.

BACKGROUND: Recent advances in genome sequencing suggest a remarkable conservation in gene content of mammalian organisms. The similarity in gene repertoire present in different organisms has increased interest in studying regulatory mechanisms of gene expression aimed at elucidating the differences in phenotypes. In particular, a proximal promoter region contains a large number of regulatory elements that control the expression of its downstream gene. Although many studies have focused on identification of these elements, a broader picture on the complexity of transcriptional regulation of different biological processes has not been addressed in mammals. The regulatory complexity may strongly correlate with gene function, as different evolutionary forces must act on the regulatory systems under different biological conditions. We investigate this hypothesis by comparing the conservation of promoters upstream of genes classified in different functional categories. RESULTS: By conducting a rank correlation analysis between functional annotation and upstream sequence alignment scores obtained by human-mouse and human-dog comparison, we found a significantly greater conservation of the upstream sequence of genes involved in development, cell communication, neural functions and signaling processes than those involved in more basic processes shared with unicellular organisms such as metabolism and ribosomal function. This observation persists after controlling for G+C content. Considering conservation as a functional signature, we hypothesize a higher density of cis-regulatory elements upstream of genes participating in complex and adaptive processes. CONCLUSION: We identified a class of functions that are associated with either high or low promoter conservation in mammals. We detected a significant tendency that points to complex and adaptive processes were associated with higher promoter conservation, despite the fact that they have emerged relatively recently during evolution. We described and contrasted several hypotheses that provide a deeper insight into how transcriptional complexity might have been emerged during evolution.

Animals↗

Modeling Lactococcus lactis using a genome-scale flux model.

BACKGROUND: Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA) and minimization of metabolic adjustment (MOMA) were used as modeling frameworks. RESULTS: The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. CONCLUSION: The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

Bacteria, Anaerobic↗

Efficient assembly of de novo human artificial chromosomes from large genomic loci.

BACKGROUND: Human artificial chromosomes (HACs) are potentially useful vectors for gene transfer studies and for functional annotation of the genome because of their suitability for cloning, manipulating and transferring large segments of the genome. However, development of HACs for the transfer of large genomic loci into mammalian cells has been limited by difficulties in manipulating high-molecular weight DNA, as well as by the low overall frequencies of de novo HAC formation. Indeed, to date, only a small number of large (>100 kb) genomic loci have been reported to be successfully packaged into de novo HACs. RESULTS: We have developed novel methodologies to enable efficient assembly of HAC vectors containing any genomic locus of interest. We report here the creation of a novel, bimolecular system based on bacterial artificial chromosomes (BACs) for the construction of HACs incorporating any defined genomic region. We have utilized this vector system to rapidly design, construct and validate multiple de novo HACs containing large (100-200 kb) genomic loci including therapeutically significant genes for human growth hormone (HGH), polycystic kidney disease (PKD1) and beta-globin. We report significant differences in the ability of different genomic loci to support de novo HAC formation, suggesting possible effects of cis-acting genomic elements. Finally, as a proof of principle, we have observed sustained beta-globin gene expression from HACs incorporating the entire 200 kb beta-globin genomic locus for over 90 days in the absence of selection. CONCLUSION: Taken together, these results are significant for the development of HAC vector technology, as they enable high-throughput assembly and functional validation of HACs containing any large genomic locus. We have evaluated the impact of different genomic loci on the frequency of HAC formation and identified segments of genomic DNA that appear to facilitate de novo HAC formation. These genomic loci may be useful for identifying discrete functional elements that may be incorporated into future generations of HAC vectors.

Biotechnology↗

Transcriptome Analysis, Machine Learning, and Experimental Identification of CDK7 Affecting the Progression of Pregnancy-induced Hypertension by Influencing Macrophage Polarization.

INTRODUCTION: Pregnancy-induced hypertension (PIH) is a severe pregnancy complication characterized by placental insufficiency, abnormal vascular remodeling, and immune dysregulation, but personalized therapeutic markers remain unclear. This study aimed to identify key genes and explore immune mechanisms in PIH using transcriptome analysis, machine learning, and experimental validation. METHODS: We analyzed the GSE204835 transcriptomic dataset to screen differentially expressed genes (DEGs) and performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA) for functional annotation. Immune infiltration analysis was also performed to examine the immune landscape in PIH. Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key genes, which were validated in a PIH cell model. Flow cytometry and immunofluorescence assays assessed the effect of CDK7 knockdown on macrophage polarization. RESULTS: A total of 1,598 DEGs (1,123 upregulated, 475 downregulated) were identified. Enrichment analyses highlighted associations with embryonic organ development, oxidative phosphorylation, angiogenesis, and oxidative stress. Immune infiltration analysis revealed altered eosinophil and macrophage polarization in PIH. LASSO regression selected 12 key genes, with CDK7 showing the most significant upregulation in the PIH model. CDK7 knockdown promoted macrophage polarization toward the anti-inflammatory M2 phenotype. DISCUSSION: These findings link CDK7 to immune dysregulation in PIH by modulating macrophage polarization, expanding our understanding of PIH's molecular mechanisms. The study's limitations include reliance on public datasets and in vitro models, warranting in vivo validation. CONCLUSION: CDK7 emerges as a potential therapeutic target for PIH, offering new insights into immunoregulatory interventions for this complication.

Female↗

Proteomics of Shewanella oneidensis MR-1 biofilm reveals differentially expressed proteins, including AggA and RibB.

Shewanella oneidensis MR-1 is a Gram-negative, facultative aerobic bacterium, able to respire a variety of electron acceptors. Due to its capability to reduce solid ferric iron, S. oneidensis plays an important role in microbially induced corrosion of metal surfaces. Since this requires cellular adhesion to the metal surface, biofilm growth is an essential feature of this process. The goal of this work was to compare the global protein expression patterns of sessile and planktonic grown S. oneidensis cells by two-dimensional (2-D) gel electrophoresis. Mass spectrometry was used as an identification tool of the differentially expressed proteins. An IPG strip of pH 3-10 as well as pH 4-7 was applied for iso-electrofocusing. Analysis of the 2-D patterns pointed out a total of 59 relevant spots. Among these proteins, we highlight the involvement of a protein annotated as an agglutination protein (AggA). AggA is a TolC-like protein which is presumably part of an ABC transporter. Another differentially expressed protein is RibB, an enzyme of the riboflavin biosynthesis pathway. Riboflavin is the precursor molecule of flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) and may be necessary for the altered respiratory properties of the biofilm cells versus planktonic cells. Some proteins that were identified indicate an anaerobic state of the biofilm. This anaerobic way of living affects the energy gaining pathways of the cell and is reflected by the presence of several proteins, including those of a heme-utilization system.

Bacterial Proteins↗

Comprehensive genome sequence analysis of a breast cancer amplicon.

Gene amplification occurs in most solid tumors and is associated with poor prognosis. Amplification of 20q13.2 is common to several tumor types including breast cancer. The 1 Mb of sequence spanning the 20q13.2 breast cancer amplicon is one of the most exhaustively studied segments of the human genome. These studies have included amplicon mapping by comparative genomic hybridization (CGH), fluorescent in-situ hybridization (FISH), array-CGH, quantitative microsatellite analysis (QUMA), and functional genomic studies. Together these studies revealed a complex amplicon structure suggesting the presence of at least two driver genes in some tumors. One of these, ZNF217, is capable of immortalizing human mammary epithelial cells (HMEC) when overexpressed. In addition, we now report the sequencing of this region in human and mouse, and on quantitative expression studies in tumors. Amplicon localization now is straightforward and the availability of human and mouse genomic sequence facilitates their functional analysis. However, comprehensive annotation of megabase-scale regions requires integration of vast amounts of information. We present a system for integrative analysis and demonstrate its utility on 1.2 Mb of sequence spanning the 20q13.2 breast cancer amplicon and 865 kb of syntenic murine sequence. We integrate tumor genome copy number measurements with exhaustive genome landscape mapping, showing that amplicon boundaries are associated with maxima in repetitive element density and a region of evolutionary instability. This integration of comprehensive sequence annotation, quantitative expression analysis, and tumor amplicon boundaries provide evidence for an additional driver gene prefoldin 4 (PFDN4), coregulated genes, conserved noncoding regions, and associate repetitive elements with regions of genomic instability at this locus.

Animals↗

Gene and protein profiling of the response of MA-10 Leydig tumor cells to human chorionic gonadotropin.

Activation of the steroidogenic machinery by peptide hormones involves a number of steps for transmitting signals from the plasma membrane to mitochondria in a spatially and temporally coordinated manner. Although key proteins mediating the hormonal signal have been identified, recent data suggest that the pathway might involve more complex protein-protein and protein-lipid interactions. Genomic and proteomic methods of analysis, namely the Affymetrix Murine Genome U74A v2 GeneChip and the BD PowerBlot Western Array, were used to identify human chorionic gonadotropin (hCG)-induced changes in mRNA and protein of MA-10 Leydig tumor cells that parallel the increase seen in progesterone synthesis. To analyze the massive amount of data that was generated, a comprehensive protein information matrix summarizing the features of each gene or protein, including its known properties, as well as annotations derived by homology-based functional inference, was developed. Of the genes examined by Affymetrix array, approximately 79 were differentially expressed and of gene products examined by PowerBlot, 9 were differentially expressed (above twofold). Changes in the expression of selected transcripts of interest were confirmed using real-time quantitative polymerase chain reaction and immunoblot analyses. Collectively, these results indicate that hormonal regulation of steroidogenesis is a complex phenomenon, involving proteins that participate in various known and novel pathways, which are implicated in transmitting signals from the plasma membrane to mitochondria and nucleus.

Blotting, Western↗

Large-scale prokaryotic gene prediction and comparison to genome annotation.

MOTIVATION: Prokaryotic genomes are sequenced and annotated at an increasing rate. The methods of annotation vary between sequencing groups. It makes genome comparison difficult and may lead to propagation of errors when questionable assignments are adapted from one genome to another. Genome comparison either on a large or small scale would be facilitated by using a single standard for annotation, which incorporates a transparency of why an open reading frame (ORF) is considered to be a gene. RESULTS: A total of 143 prokaryotic genomes were scored with an updated version of the prokaryotic genefinder EasyGene. Comparison of the GenBank and RefSeq annotations with the EasyGene predictions reveals that in some genomes up to approximately 60% of the genes may have been annotated with a wrong start codon, especially in the GC-rich genomes. The fractional difference between annotated and predicted confirms that too many short genes are annotated in numerous organisms. Furthermore, genes might be missing in the annotation of some of the genomes. We predict 41 of 143 genomes to be over-annotated by >5%, meaning that too many ORFs are annotated as genes. We also predict that 12 of 143 genomes are under-annotated. These results are based on the difference between the number of annotated genes not found by EasyGene and the number of predicted genes that are not annotated in GenBank. We argue that the average performance of our standardized and fully automated method is slightly better than the annotation.

Base Composition↗

Analysis and functional annotation of expressed sequence tags from the fall armyworm Spodoptera frugiperda.

BACKGROUND: Little is known about the genome sequences of lepidopteran insects, although this group of insects has been studied extensively in the fields of endocrinology, development, immunity, and pathogen-host interactions. In addition, cell lines derived from Spodoptera frugiperda and other lepidopteran insects are routinely used for baculovirus foreign gene expression. This study reports the results of an expressed sequence tag (EST) sequencing project in cells from the lepidopteran insect S. frugiperda, the fall armyworm. RESULTS: We have constructed an EST database using two cDNA libraries from the S. frugiperda-derived cell line, SF-21. The database consists of 2,367 ESTs which were assembled into 244 contigs and 951 singlets for a total of 1,195 unique sequences. CONCLUSION: S. frugiperda is an agriculturally important pest insect and genomic information will be instrumental for establishing initial transcriptional profiling and gene function studies, and for obtaining information about genes manipulated during infections by insect pathogens such as baculoviruses.

Animals↗

Comprehensive analyses of prostate gene expression: convergence of expressed sequence tag databases, transcript profiling and proteomics.

Several methods have been developed for the comprehensive analysis of gene expression in complex biological systems. Generally these procedures assess either a portion of the cellular transcriptome or a portion of the cellular proteome. Each approach has distinct conceptual and methodological advantages and disadvantages. We have investigated the application of both methods to characterize the gene expression pathway mediated by androgens and the androgen receptor in prostate cancer cells. This pathway is of critical importance for the development and progression of prostate cancer. Of clinical importance, modulation of androgens remains the mainstay of treatment for patients with advanced disease. To facilitate global gene expression studies we have first sought to define the prostate transcriptome by assembling and annotating prostate-derived expressed sequence tags (ESTs). A total of 55000 prostate ESTs were assembled into a set of 15953 clusters putatively representing 15953 distinct transcripts. These clusters were used to construct cDNA microarrays suitable for examining the androgen-response pathway at the level of transcription. The expression of 20 genes was found to be induced by androgens. This cohort included known androgen-regulated genes such as prostate-specific antigen (PSA) and several novel complementary DNAs (cDNAs). Protein expression profiles of androgen-stimulated prostate cancer cells were generated by two-dimensional electrophoresis (2-DE). Mass spectrometric analysis of androgen-regulated proteins in these cells identified the metastasis-suppressor gene NDKA/nm23, a finding that may explain a marked reduction in metastatic potential when these cells express a functional androgen receptor pathway.

DNA, Complementary↗

Iron-related transcriptomic variations in CaCo-2 cells, an in vitro model of intestinal absorptive cells.

Regulation of iron absorption by duodenal enterocytes is essential for the maintenance of homeostasis by preventing iron deficiency or overload. Despite the identification of a number of genes implicated in iron absorption and its regulation, it is likely that further factors remain to be identified. For that purpose, we used a global transcriptomic approach, using the CaCo-2 cell line as an in vitro model of intestinal absorptive cells. Pangenomic screening for variations in gene expression correlating with intracellular iron content allowed us to identify 171 genes. One hundred nine of these genes are clustered into five types of expression profile. This is the first time that most of these genes have been associated with iron metabolism. Functional annotation of these five clusters indicates potential links between the immune response, proteolysis processes, and iron depletion. In contrast, iron overload is associated with cellular metabolism, especially that of lipids and glutathione involving redox function and electron transfer.

Caco-2 Cells↗

Methods for the functional genomic analysis of ubiquitin ligases.

Ubiquitin ligases (E3s) are critical components of the ubiquitin-proteasome system as they are the major determinants of specificity in ubiquitin conjugation. The number of predicted E3s in the mammalian genome is exceeding 400 and is represented by two major subfamilies: HECT domain-containing E3s and RING finger-type E3s. Given the size of this protein family and lack of knowledge on the functions of most of these 400 proteins, their functional annotation should benefit from modern genomic tools. This article presents a methodology consisting of the use of a cDNA expression library to identify suppressors of polyglutamine (polyQ)-mediated protein aggregate formation in cells, as an example of a genomic approach to assign functions to E3s. In this screen, we identified novel RING finger-type E3s exhibiting suppressor activity among >50% of all the potential E3s in the mouse and human genomes. This method could be adapted easily to identify E3s that function in other processes and signaling pathways.

Algorithms↗

Tailored gene array databases: applications in mechanistic toxicology.

MOTIVATION: The development of an annotated global database suitable for a wide range of investigations is a challenging and labor-intensive task. Thus, the development of databases tailored for specific applications remains necessary. For example, in the field of toxicology, no annotated gene array databases are now available that may assist in the correlation of changes in gene activity to cellular functions and processes associated with the toxic response. RESULTS: As an example of a tailored annotated database, an attempt was made to systematize available biological information on genes present on the Affymetrix Rat Toxicology U34 GeneChip, with a focus on how the gene products relate to liver cells and their response to chemical toxins. The information collected was imbedded in a local relational database to analyze data obtained in toxicological gene array experiments with hydrazine-exposed hepatocytes. The advantages and benefits of the tailored database in the biological interpretation of the results are demonstrated.

Abstracting and Indexing↗

Investigating metabolite essentiality through genome-scale analysis of Escherichia coli production capabilities.

MOTIVATION: A phenotype mechanism is classically derived through the study of a set of mutants and comparison of their biochemical capabilities. One method of comparing mutant capabilities is to characterize producible and knocked out metabolites. However such an effect is difficult to manually assess, especially for a large biochemical network and a complex media. Current algorithmic approaches towards analyzing metabolic networks either do not address this specific property or are computationally infeasible on the genome-scale. RESULTS: We have developed a novel genome-scale computational approach that identifies the full set of biochemical species that are knocked out from the metabolome following a gene deletion. Results from this approach are combined with data from in vivo mutant screens to examine the essentiality of metabolite production for a phenotype. This approach can also be a useful tool for metabolic network annotation validation and refinement in newly sequenced organisms. Combining an in silico genome-scale model of Escherichia coli metabolism with in vivo survival data, we uncover possible essential roles for several cell membranes, cell walls, and quinone species. We also identify specific biomass components whose production appears to be non-essential for survival, contrary to the assumptions of previous models. AVAILABILITY: Programs are available upon request from the authors in the form of Matlab script files. SUPPLEMENTARY INFORMATION: http://www.cis.upenn.edu/biocomp/manuscripts/bioinformatics_bti245/supp-info.html.

Algorithms↗

Phospho3D: a database of three-dimensional structures of protein phosphorylation sites.

Phosphorylation is the most common protein post-translational modification. Phosphorylated residues (serine, threonine and tyrosine) play critical roles in the regulation of many cellular processes. Since the amount of data produced by screening assays is growing continuously, the development of computational tools for collecting and analysing experimental data has become a pivotal task for unravelling the complex network of interactions regulating eukaryotic cell life. Here we present Phospho3D, http://cbm.bio.uniroma2.it/phospho3d, a database of 3D structures of phosphorylation sites, which stores information retrieved from the phospho.ELM database and is enriched with structural information and annotations at the residue level. The database also collects the results of a large-scale structural comparison procedure providing clues for the identification of new putative phosphorylation sites.

Databases, Protein↗

Functional genomic analysis of C. elegans molting.

Although the molting cycle is a hallmark of insects and nematodes, neither the endocrine control of molting via size, stage, and nutritional inputs nor the enzymatic mechanism for synthesis and release of the exoskeleton is well understood. Here, we identify endocrine and enzymatic regulators of molting in C. elegans through a genome-wide RNA-interference screen. Products of the 159 genes discovered include annotated transcription factors, secreted peptides, transmembrane proteins, and extracellular matrix enzymes essential for molting. Fusions between several genes and green fluorescent protein show a pulse of expression before each molt in epithelial cells that synthesize the exoskeleton, indicating that the corresponding proteins are made in the correct time and place to regulate molting. We show further that inactivation of particular genes abrogates expression of the green fluorescent protein reporter genes, revealing regulatory networks that might couple the expression of genes essential for molting to endocrine cues. Many molting genes are conserved in parasitic nematodes responsible for human disease, and thus represent attractive targets for pesticide and pharmaceutical development.

Animals↗

Network pharmacology approach to unveiling the mechanism of berberine in the amelioration of morphine tolerance.

OBJECTIVE: To investigate the mechanism underlying the effect of the Huanglian decoction (, HLD) on morphine tolerance (MT), using network pharmacology, and to verify these mechanisms in vitro and in vivo. METHODS: Available biological data on each drug in the HLD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The target proteins of MT were retrieved from the GeneCards, PharmGkb, Therapeutic Target Database, DrugBank, and Online Mendelian Inheritance in Man databases. Information regarding MT and the drug targets was compared to obtain overlapping elements. This information was imported into the Search Tool for the Retrieval of Interacting Genes/Proteins platform to obtain a protein-protein interaction network diagram. Then, a "component-target" network diagram was constructed using screened drug components and target information, viaCytoscape (Institute for Systems Biology, Seattle, WA, USA). The database for annotation, visualization, and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses. Pathway information predicted by network pharmacology was verified using animal studies and cell experiments. RESULTS: Network pharmacology analysis identified 22 active compounds of HLD and revealed that HLD partially ameliorated MT by modulating inflammatory, apoptosis, and nuclear factor kappa B (NF-κB) signaling pathways. Berberine (BBR), one of the main components of HLD, inhibited the development of MT in mice. BBR reduced cell viability while increasing B-cell lymphoma 2 (Bcl-2) protein expression and decreasing CD86, NF-κB, Bax, and Caspase-3 protein expression in brain vascular 2 (BV2) mcroglia cells treated with morphine. Additionally, BBR contributed to a reduction in pro-inflammatory cytokine release and apoptotic cell number. CONCLUSIONS: BBR, a key component of HLD, effectively suppressed microglial activation and neuro-inflammation by regulating the NF-κB and apoptosis signaling pathways, thereby delaying MT. This study offers a novel approach to enhance the clinical analgesic efficacy of morphine.

Berberine↗