TF Binding Research Articles

Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities

BackgroundGene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the TFA layer, thus missing a key regulatory element.ResultsThis work integrates TFA prediction algorithms with relevance score based network reconstruction algorithms to reconstruct gene regulatory networks with improved accuracy over classic relevance score based algorithms. This method is called Gene expression and Transcription factor activity based Relevance Network (GTRNetwork). Different combinations of TFA prediction algorithms and relevance score functions have been applied to find the most efficient combination. When the integrated GTRNetwork method was applied to E. coli data, the reconstructed genome-wide gene regulatory network predicted 381 new regulatory links. This reconstructed gene regulatory network including the predicted new regulatory links show promising biological significances. Many of the new links are verified by known TF binding site information, and many other links can be verified from the literature and databases such as EcoCyc. The reconstructed gene regulatory network is applied to a recent transcriptome analysis of E. coli during isobutanol stress. In addition to the 16 significantly changed TFAs detected in the original paper, another 7 significantly changed TFAs have been detected by using our reconstructed network.ConclusionsThe GTRNetwork algorithm introduces the hidden layer TFA into classic relevance score-based gene regulatory network reconstruction processes. Integrating the TFA biological information with regulatory network reconstruction algorithms significantly improves both detection of new links and reduces that rate of false positives. The application of GTRNetwork on E. coli gene transcriptome data gives a set of potential regulatory links with promising biological significance for isobutanol stress and other conditions.

Jury remains out on simple models of transcription factor specificity

Jury remains out on simple models of transcription factor specificity

Calling Cards enable multiplexed identification of the genomic targets of DNA-binding proteins

Transcription factors direct gene expression, so there is much interest in mapping their genome-wide binding locations. Current methods do not allow for the multiplexed analysis of TF binding, and this limits their throughput. We describe a novel method for determining the genomic target genes of multiple transcription factors simultaneously. DNA-binding proteins are endowed with the ability to direct transposon insertions into the genome near to where they bind. The transposon becomes a "Calling Card" marking the visit of the DNA-binding protein to that location. A unique sequence "barcode" in the transposon matches it to the DNA-binding protein that directed its insertion. The sequences of the DNA flanking the transposon (which reveal where in the genome the transposon landed) and the barcode within the transposon (which identifies the TF that put it there) are determined by massively parallel DNA sequencing. To demonstrate the method's feasibility, we determined the genomic targets of eight transcription factors in a single experiment. The Calling Card method promises to significantly reduce the cost and labor needed to determine the genomic targets of many transcription factors in different environmental conditions and genetic backgrounds.

Metal retention in human transferrin: Consequences of solvent composition in analytical sample preparation methods

The analysis of metal-binding proteins requires careful sample manipulation to ensure that the metal-protein complex remains in its native state and the metal retention is preserved during sample preparation or analysis. Chemical analysis for the metal content in proteins typically involves some type of liquid chromatography/electrophoresis separation step coupled with an atomic (i.e., inductively coupled plasma-optical emission spectroscopy or -mass spectrometry) or molecular (i.e., electrospray ionization-mass spectrometry) analysis step that requires altered-solvent introduction techniques. UV-VIS absorbance is employed here to monitor the iron content in human holo-transferrin (Tf) under various solvent conditions, changing polarity, pH, ionic strength, and the ionic and hydrophobic environment of the protein. Iron loading percentages (i.e. 100% loading equates to 2 Fe(3+):1 Tf) were quantitatively determined to evaluate the effect of solvent composition on the retention of Fe(3+) in Tf. Maximum retention of Fe(3+) was found in buffered (20 mM Tris) solutions (96 ± 1%). Exposure to organic solvents and deionized H(2)O caused release of ~23-36% of the Fe(3+) from the binding pocket(s) at physiological pH (7.4). Salt concentrations similar to separation conditions used for ion exchange had little to no effect on Fe(3+) retention in holo-Tf. Unsurprisingly, changes in ionic strength caused by additions of guanidine HCl (0-10 M) to holo-Tf resulted in unfolding of the protein and loss of Fe(3+) from Tf; however, denaturing and metal loss was found not to be an instantaneous process for additions of 1-5 M guanidinium to Tf. In contrast, complete denaturing and loss of Fe(3+) was instantaneous with ≥6 M additions of guanidinium, and denaturing and loss of iron from Tf occurred in parallel proportions. Changes to the hydrophobicity of Tf (via addition of 0-14 M urea) had less effect on denaturing and release of Fe(3+) from the Tf binding pocket compared to changes in ionic strength.

Gene expression analysis of HUVEC in response to TF-binding

IntroductionTissue factor (TF), the cofactor for factor VII/VIIa (FVII/FVIIa) and initiator of the extrinsic pathway, is transiently expressed on intravascular cells under control of cytokines and growth factors. In addition, endothelial cells express a binding site for external TF. In the present study, we investigated gene expression of endothelial cells derived from human umbilical veins (HUVEC) in response to TF-binding to identify differentially expressed genes. Materials and methodsHUVEC were treated with recombinant relipidated TF (Innovin) versus nontreated cells, as well as TF/FVIIa versus FVIIa alone. TF binding was measured by ELISA. Gene expression profiles were examined using HG-U133 plus 2.0 arrays (Affymetrix). ResultsGene expression analysis of HUVEC showed 148 up-regulated and 29 down-regulated genes 4h after TF binding. Notably, the genes, which were significantly up- and down-regulated, either by TF alone or by the complex of TF/FVIIa, exhibited a complete overlap, indicating that activation of endothelial cells after binding of external added TF does not depend on FVIIa as has been demonstrated for TF-expressing cells. TF-mediated regulation of gene expression of several genes, involved in regulation of apoptosis, cell adhesion, cell motility, and angiogenesis, was confirmed by qPCR. Furthermore, in case of SELE, TGFB2, TNFAIP3, TNFSF4, TNFSF18, TAGLN, CXCL1, PCF11 antibodies directed to TF clearly inhibited TF-mediated regulation of gene expression. ConclusionsThe results demonstrate that interaction of TF with HUVEC via a binding site, independent from FVIIa, may result in regulation of a variety of genes involved in arteriosclerosis, cancer, and cardiovascular diseases.

Comparison of Overt and Cryptic Labile Plasma Iron In Thalassemia Patients In Israel and Gaza-Palestine

AbstractAbstract 5166 Background.Systemic iron overload (SIO) is characterized by persistently high levels of plasma iron that often surpass transferrin's (Tf) binding capacity and generate chemical forms identified as non-Tf bound iron (NTBI). These forms have been perceived as: a. clinically important indicators of SIO per se and of impending organ damage, because cells chronically exposed to iron overloaded plasma attain iron levels and ensuing ROS formation that override their antioxidant capacities and b. as pharmacological targets for chelation and thereby of prevention of tissue iron overload. However, NTBI determination in the clinical setting has been confounded by the chemical heterogeneity of iron forms found in fluids like plasma/sera of SIO patients, the presence of residual amounts of undefined chelates or chelators and the need to dislodge NTBI from native ligands with agents that facilitate its detection.We have assayed the overt forms of NTBI that represent the native pool of labile (= redox-active, chelatable and membrane permeant) iron in plasma/serum. We defined it as ‘labile plasma iron’ or LPI and analyzed it by the Aferrix FeROS™ test (1) and used it to asses chelation regimens in their ability to maintain patients' plasma at relatively low (basal) LPI levels (<0.4 μ M, ref. 2). Detection of NTBI forms with both low redox activity and poor chelator accessibility (defined as cryptic LPI) can also be done with the FeROS™ test by supplementing samples with an agent (nitrilotriacetate= NTA < 0.5 mM) that in plasma “extracts” iron from native NTBI. Thus whereas LPI measures overtly labile NTBI in native plasma (i.e. LPI), LPIplus detects both overt + cryptic forms, as in classical NTBI assays that involve either mobilization + filtration (3) or in the DCI (directly chelatable iron) assay that measures deferrioxamine chelatable NTBI (4). Aim.To compare SIO parameters in polytransfused thalassemia major patients, chelated and non-chelated, as revealed by measurements of overt and cryptic LPI. Methods.The studies involved: 1. The Hadassah Medical Center (HMC) in Jerusalem, where 15–20 (randomly selected, age 14–35) patients were under regular transfusion/chelation treatment and 2. The European Medical Center in Gaza (EMC), where regularly transfused patients (age 10–22) were only sporadically chelated. NTBI assays were performed on sera prepared from blood, (where applicable taken after >10 hrs drug washout, as described for LPI (1,2) and DCI (4); for LPIplus, the LPI test was conducted in the presence of 0.5 mM NTA. Results.As shown previously (2,4), LPI was detected only in patients with >70% Tf-saturation.In HMC, the mean LPI of n=18 patients rose from 0.51±0.41 μ M to 1.00 ±0.46 μ M in the presence of NTA, matching the DCI level of 0.91±0.7 μ M. The LPI rise was detected in 12/15 (= 80%) of samples with LPI>0.4 μ M (≂p 66% of the entire cohort). Thus, despite chelation, a substantial number of patients had relatively low but significant levels of both overt and cryptic NTBI. Among the 3 patients with no significant LPI or DCI (0.2-0.4 μ M), 2/3 became LPI positive (0.6-0.8 μ M) when tested with NTA.Unexpectedly, in EMC-Gaza, among 20 transfused unchelated patients with serum ferritins > 5000 ng/ml and Tf saturation >100%, 8/20 of them (≂p 40%) had undetectable levels of overt LPI but substantial cryptic NTBI. In the remaining 12/20, the mean overt LPI of 0.69±0.65 μ M rose significantly (p<0.01) to 2.05 ±1.56 μ M when the cryptic component (NTA-extractable) was added. Discussion.Overt and cryptic NTBI components were detected by two modalities of the LPI assay in both regularly chelated and unchelated thalassemia patients, although to different extents and proportions. Compared to chelated patients, those unchelated had significantly higher mean values of both overt and cryptic NTBI components, despite the higher proportion of patients with only cryptic NTBI. On an individual basis, the persistent appearance of either/both LPI component(s) of NTBI could provide a measure of SIO and/or the success of individual chelation regimens. However, remaining to be established is the pathophysiological role of each component of NTBI to SIO, disease progression and treatment success. Supported by ISF and the Canadian Friends of HUJI.1. Esposito et al. Blood 102:2670-7 (2003); 2. Zanninelli et al. Br. J. Hematol. 147: 744–51(2009); 3. Hider R. Eur J Clin Invest 32:S50–4 (2002); 4. Pootrakul et al. Blood 104: 1504–10 (2004). Disclosures:Cabantchik:Aferrix Ltd: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Transferrin Receptor 1: A Ferritin Receptor as Well?

Transferrin Receptor 1: A Ferritin Receptor as Well?

Prediction of Polycomb target genes in mouse embryonic stem cells

Polycomb group (PcG) proteins are important epigenetic regulators, yet the underlying targeting mechanism in mammals is still poorly understood. We have developed a computational approach to predict genome-wide PcG target genes in mouse embryonic stem cells. We use TF binding and motif information as predictors and apply the Bayesian Additive Regression Trees (BART) model for classification. Our model has good prediction accuracy. The performance can be mainly explained by five TF features (Zf5, Tcfcp2l1, Ctcf, E2f1, Myc). Our analysis of H3K27me3 and gene expression data suggests that genomic sequence is highly correlated with the overall PcG target plasticity. We have also compared the PcG target sequence signatures between mouse and Drosophila and found that they are strikingly different. Our predictions may be useful for de novo search for Polycomb response elements (PRE) in mammals.

Characterization of the Interaction between Diferric Transferrin and Transferrin Receptor 2 by Functional Assays and Atomic Force Microscopy

Transferrin receptor 2 (TfR2), a homologue of the classical transferrin receptor 1 (TfR1), is found in two isoforms, α and β. Like TfR1, TfR2α is a type II membrane protein, but the β form lacks transmembrane portions and therefore is likely to be an intracellular protein. To investigate the functional properties of TfR2α, we expressed the protein with FLAG tagging in transferrin-receptor-deficient Chinese hamster ovary cells. The association constant for the binding of diferric transferrin (Tf) to TfR2α is 5.6×106 M−1, which is about 50 times lower than that for the binding of Tf to TfR1, with correspondingly reduced rates of iron uptake. Evidence for Tf internalization and recycling via TfR2α without degradation, as in the TfR1 pathway, was also found. The interaction of TfR2α with Tf was further investigated using atomic force microscopy, a powerful tool used for investigating the interaction between a ligand and its receptor at the single-molecule level on the living cell surface. Dynamic force microscopy reveals a difference in the interactions of Tf with TfR2α and TfR1, with Tf–TfR1 unbinding characterized by two energy barriers, while only one is present for Tf–TfR2. We speculate that this difference may reflect Tf binding to TfR2α by a single lobe, whereas two lobes of Tf participate in binding to TfR1. The difference in the binding properties of Tf to TfR1 and TfR2α may help account for the different physiological roles of the two receptors.

Correlated changes between regulatory cis elements and condition-specific expression in paralogous gene families

Gene duplication is integral to evolution, providing novel opportunities for organisms to diversify in function. One fundamental pathway of functional diversification among initially redundant gene copies, or paralogs, is via alterations in their expression patterns. Although the mechanisms underlying expression divergence are not completely understood, transcription factor binding sites and nucleosome occupancy are known to play a significant role in the process. Previous attempts to detect genomic variations mediating expression divergence in orthologs have had limited success for two primary reasons. First, it is inherently challenging to compare expressions among orthologs due to variable trans-acting effects and second, previous studies have quantified expression divergence in terms of an overall similarity of expression profiles across multiple samples, thereby obscuring condition-specific expression changes. Moreover, the inherently inter-correlated expressions among homologs present statistical challenges, not adequately addressed in many previous studies. Using rigorous statistical tests, here we characterize the relationship between cis element divergence and condition-specific expression divergence among paralogous genes in Saccharomyces cerevisiae. In particular, among all combinations of gene family and TFs analyzed, we found a significant correlation between TF binding and the condition-specific expression patterns in over 20% of the cases. In addition, incorporating nucleosome occupancy reveals several additional correlations. For instance, our results suggest that GAL4 binding plays a major role in the expression divergence of the genes in the sugar transporter family. Our work presents a novel means of investigating the cis regulatory changes potentially mediating expression divergence in paralogous gene families under specific conditions.

The Complex Spatio-Temporal Regulation of the Drosophila Myoblast Attractant Gene duf/kirre

A key early player in the regulation of myoblast fusion is the gene dumbfounded (duf, also known as kirre). Duf must be expressed, and function, in founder cells (FCs). A fixed number of FCs are chosen from a pool of equivalent myoblasts and serve to attract fusion-competent myoblasts (FCMs) to fuse with them to form a multinucleate muscle-fibre. The spatial and temporal regulation of duf expression and function are important and play a deciding role in choice of fibre number, location and perhaps size. We have used a combination of bioinformatics and functional enhancer deletion approaches to understand the regulation of duf. By transgenic enhancer-reporter deletion analysis of the duf regulatory region, we found that several distinct enhancer modules regulate duf expression in specific muscle founders of the embryo and the adult. In addition to existing bioinformatics tools, we used a new program for analysis of regulatory sequence, PhyloGibbs-MP, whose development was largely motivated by the requirements of this work. The results complement our deletion analysis by identifying transcription factors whose predicted binding regions match with our deletion constructs. Experimental evidence for the relevance of some of these TF binding sites comes from available ChIP-on-chip from the literature, and from our analysis of localization of myogenic transcription factors with duf enhancer reporter gene expression. Our results demonstrate the complex regulation in each founder cell of a gene that is expressed in all founder cells. They provide evidence for transcriptional control—both activation and repression—as an important player in the regulation of myoblast fusion. The set of enhancer constructs generated will be valuable in identifying novel trans-acting factor-binding sites and chromatin regulation during myoblast fusion in Drosophila. Our results and the bioinformatics tools developed provide a basis for the study of the transcriptional regulation of other complex genes.

A systems biology approach to the identification and analysis of transcriptional regulatory networks in osteocytes

BackgroundThe osteocyte is a type of cell that appears to be one of the key endocrine regulators of bone metabolism and a key responder to initiate bone formation and remodeling. Identifying the regulatory networks in osteocytes may lead to new therapies for osteoporosis and loss of bone.ResultsUsing microarray, we identified 269 genes over-expressed in osteocyte, many of which have known functions in bone and muscle differentiation and contractility. We determined the evolutionarily conserved and enriched TF binding sites in the 5 kb promoter regions of these genes. Using this data, a transcriptional regulatory network was constructed and subsequently partitioned to identify cis-regulatory modules.ConclusionOur results show that many osteocyte-specific genes, including two well-known osteocyte markers DMP1 and Sost, have highly conserved clustering of muscle-related cis-regulatory modules, thus supporting the concept that a muscle-related gene network is important in osteocyte biology and may play a role in contractility and dynamic movements of the osteocyte.

Insights into the Bacterial Transferrin Receptor: The Structure of Transferrin-Binding Protein B from Actinobacillus pleuropneumoniae

Pathogenic bacteria from the Neisseriaceae and Pasteurellacea families acquire iron directly from the host iron-binding glycoprotein, transferrin (Tf), in a process mediated by surface receptor proteins that directly bind host Tf, extract the iron, and transport it across the outer membrane. The bacterial Tf receptor is comprised of a surface exposed lipoprotein, Tf-binding protein B (TbpB), and an integral outer-membrane protein, Tf-binding protein A (TbpA), both of which are essential for survival in the host. In this study, we report the 1.98 A resolution structure of TbpB from the porcine pathogen Actinobacillus pleuropneumoniae, providing insights into the mechanism of Tf binding and the role of TbpB. A model for the complex of TbpB bound to Tf is proposed. Mutation of a single surface-exposed Phe residue on TbpB within the predicted interface completely abolishes binding to Tf, suggesting that the TbpB N lobe comprises the sole high-affinity binding region for Tf.

Characterization of porcine factor VII, X and comparison with human factor VII, X

Objective Factor VII (FVII) and factor X (FX) are two predominant molecules of coagulation cascade. Whether porcine FVII and FX could efficiently work in human circulation is important for successful pig to human liver transplantation. We compared the genetic characterizations and coagulation activities of porcine and human FVII and FX to shed insight into the further investigation of potential inter-species molecular incompatibility between porcine FVII, FX and human derived procoagulants and anticoagulants in xenotransplantation. Methods Multiple rounds of PCR were used to screen the positive clones from a porcine liver tissue cDNA library. 5′ RACE and 3′ RACE were conducted to get the full-length cDNA. The three-dimensional structure of protein was modeled by Swiss-Model program. Prothrombin Time (PT) of porcine and human plasma was determined by coagulation autoanalyzer. Activities of porcine FVII and FX were detected by adding the porcine plasma into FVII or FX-deficient human plasma. Results We cloned the full-length cDNA of porcine FVII and FX, which contained 1416 bp and 1856 bp, coding 445 and 479 amino acids, respectively. Porcine FVII and FX shared 74.08% and 73.1% amino acid identities with human FVII and FX. Sequence alignments showed that porcine FVII might have additional γ-carboxyglutamic acid in Gla domain, and one important variation of Lys62-Glu in light chain. No significant difference was observed in TF binding region of heavy chain, while 4 variations were identified in the important functional residues responsible for proteolysis activity, as Gln217-Glu, Thr151-Lys, Glu154-Val and Gln40-Leu. However, no apparent change was displayed in the 3-D model of the heavy chain of porcine FVII. When porcine FX was analyzed, great variations have been found at active peptide (Ser143 to Arg194) with only 11.6% identity. Some important variations at γ-carboxyglutamic acids and Ca 2+ binding sites were identified, while high conservations were discovered at other functional sites. Comparisons on 3-D protein models demonstrated that the protein backbones of porcine and human FX were highly conserved, and little difference was shown at the molecular surface of anticoagulant binding sites S2 and S3. PT detection of porcine and human plasma showed similar results, while coagulation activities of porcine FVII and FX were remarkably higher than that of human. Conclusion Porcine FVII and FX showed relatively high homology with human FVII and FX in nucleotide, amino acid sequences and three-dimensional structure. However, the different affinities to important macromolecules caused by genetic differences might contribute to the molecular incompatibilities in liver xenotransplantation.

Characterization of the Interaction Between Diferric Transferrin and Transferrin Receptor 2 by Functional Assays and Atomic Force Microscopy (AFM).

[Introduction and aim] Transferrin receptor 2 (TfR2) is a homologue of the classical transferrin receptor 1 (TfR1), and TfR2 has two isoforms, α and β. Like TfR1, TfR2α is a type II membrane protein expressing mainly in the hepatocytes on their cell surface, but the β form lacks intracellular and transmembrane portions and therefore is likely to be an intracellular protein. Although the main physiological functions of these two isoforms are still not fully understood, TfR2α binds diferric transferrin (Tf), and is therefore thought likely to be involved in cellular iron metabolism. In fact, mutations of TfR2 cause hemochromatosis, implying that the function of TfR2 might be a regulation of iron metabolism. The aim of the present study was to investigate the interaction of TfR2α with Tf by functional assays and atomic force microscopy (AFM), which would be a powerful tool for investigation of the interaction between ligand and receptor on living cell surface.[Methods] To investigate the functional properties of TfR2α, we established the stable clone that expresses TfR2α protein with FLAG-tagging from transferrin receptor-deficient Chinese hamster ovary (CHO) cells (TRVb). That clone was applied for the 125I –labeled Tf (125I –Tf) binding study at 4 oC. The cells were applied for Tf and iron uptake study using 125I –Tf and 59Fe –loaded Tf at 37 oC. AFM is the method that can investigate the unbinding force between receptor and ligand at single molecule level when their binding is physically detached, and we applied this method for determine the interaction between Tf and TfR2α using the transiently transfected human hepatome-derived HLF cells with TfR2α-expression vector.[Results] The association constant for binding of 125I-Tf to TfR2α was calculated to be 5.6 x 106 M−1 from non-linear least squares curve fitting to a saturable binding isotherm, which is much lower than that of TfR1. Although CHO cells showed a receptor-independent non-specific association with Tf at 37 oC, we observed cell-associated Tf persisting after acid-washing in TfR2α overexpressing cells, We also confirmied the existence of internalized Tf into cells via TfR2α. Overexpressed TfR2α protein was also shown to mediate iron uptake although its rate of iron donation is slower than TfR1. The interaction between Tf and TfR2α was also confirmed by AFM, but the unbinding force was different from that between Tf and TfR1. This report might be the first that showed the binding and unbinding properties between Tf and TfR2α by AFM.[Discussion and conclusions] TfR2α binds to Tf although its affinity for Tf is low, and TfR2α possesses iron donating ability to the cells when TfR2α is over-expressed in our functional assays. AFM study also showed the binding between Tf and TfR2α on cell surface, but the properties of unbinding between them were different from those between Tf and TfR1. In conclusion, TfRα binds to Tf at cell surface and functions as iron donator to the cells like TfR1, but there should be the difference in the properties of binding with Tf between TfR1 and TfR2α, implying that the difference makes them having different physiological role in living organisms.

High-throughput chromatin information enables accurate tissue-specific prediction of transcription factor binding sites

In silico prediction of transcription factor binding sites (TFBSs) is central to the task of gene regulatory network elucidation. Genomic DNA sequence information provides a basis for these predictions, due to the sequence specificity of TF-binding events. However, DNA sequence alone is an impoverished source of information for the task of TFBS prediction in eukaryotes, as additional factors, such as chromatin structure regulate binding events. We show that incorporating high-throughput chromatin modification estimates can greatly improve the accuracy of in silico prediction of in vivo binding for a wide range of TFs in human and mouse. This improvement is superior to the improvement gained by equivalent use of either transcription start site proximity or phylogenetic conservation information. Importantly, predictions made with the use of chromatin structure information are tissue specific. This result supports the biological hypothesis that chromatin modulates TF binding to produce tissue-specific binding profiles in higher eukaryotes, and suggests that the use of chromatin modification information can lead to accurate tissue-specific transcriptional regulatory network elucidation.

HPLC−ICPMS and Stable Isotope-Labeled Approaches To Assess Quantitatively Ti(IV) Uptake by Transferrin in Human Blood Serum

Little is known about the effects of titanium found in patients wearing prostheses or about the biochemical pathways of this metal when used as an anticancer drug (e.g., titanocene dichloride). In this work, transferrin has been confirmed as the only carrier protein binding Ti in human blood serum samples by making use of different HPLC protein separations followed by element-specific Ti detection by ICPMS. Besides, isotope dilution analysis has been applied to the quantitative speciation of Ti-Tf in standards and human blood serum samples. Species-unspecific and species-specific isotope dilution modes have been explored. In the first case, very low Ti-Tf results were obtained even using two different chromatographic mechanisms, anion exchange (20-24%) and size exclusion (33-36%). Surprisingly, no major Ti species except Ti-Tf were observed in the chromatograms, suggesting that Ti(IV) hydrolysis and precipitation as inactive titanium oxide species could take place inside the chromatographic columns. These results demonstrate that chemical degradation of metalloproteins during analytical separations could ruin the sought speciation quantitative results. The isotope dilution species-specific mode, much more accurate in such cases, has been instrumental in demonstrating the possibility of gross errors in final metalloprotein quantification. For this purpose, an isotopically enriched standard of (49)Ti-Tf was synthesized and applied to the quantitative speciation of Ti-Tf again. Using this species-specific spike, Ti-Tf dissociation inside the chromatographic columns used could be corrected, and thus, quantitative Ti-Tf binding in serum (92-102%) was observed. In other words, the usefulness and potential of a species-specific isotope dilution analysis approach to investigate quantitatively metal-protein associations, which can be dissociated at certain experimental conditions, is demonstrated here for the first time.

Probabilistic inference of transcription factor binding from multiple data sources.

An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for easy and systematic integration of our binding predictions into other probabilistic modeling methods, such as expression-based gene network inference. The method answers the question of whether the whole analyzed promoter has a binding site, but can also be extended to estimate the binding probability at each nucleotide position. Further, we introduce an extension to model combinatorial regulation by several TFs. Most importantly, the proposed methods can make principled probabilistic inference from multiple evidence sources, such as, multiple statistical models (motifs) of the TFs, evolutionary conservation, regulatory potential, CpG islands, nucleosome positioning, DNase hypersensitive sites, ChIP-chip binding segments and other (prior) sequence-based biological knowledge. We developed both a likelihood and a Bayesian method, where the latter is implemented with a Markov chain Monte Carlo algorithm. Results on a carefully constructed test set from the mouse genome demonstrate that principled data fusion can significantly improve the performance of TF binding prediction methods. We also applied the probabilistic modeling framework to all promoters in the mouse genome and the results indicate a sparse connectivity between transcriptional regulators and their target promoters. To facilitate analysis of other sequences and additional data, we have developed an on-line web tool, ProbTF, which implements our probabilistic TF binding prediction method using multiple data sources. Test data set, a web tool, source codes and supplementary data are available at: http://www.probtf.org.

Characteristic differences between the promoters of intron-containing and intronless ribosomal protein genes in yeast

BackgroundMore than two thirds of the highly expressed ribosomal protein (RP) genes in Saccharomyces cerevisiae contain introns, which is in sharp contrast to the genome-wide five percent intron-containing genes. It is well established that introns carry regulatory sequences and that the transcription of RP genes is extensively and coordinately regulated. Here we test the hypotheses that introns are innately associated with heavily transcribed genes and that introns of RP genes contribute regulatory TF binding sequences. Moreover, we investigate whether promoter features are significantly different between intron-containing and intronless RP genes.ResultsWe find that directly measured transcription rates tend to be lower for intron-containing compared to intronless RP genes. We do not observe any specifically enriched sequence motifs in the introns of RP genes other than those of the branch point and the two splice sites. Comparing the promoters of intron-containing and intronless RP genes, we detect differences in number and position of Rap1-binding and IFHL motifs. Moreover, the analysis of the length distribution and the folding free energies suggest that, at least in a sub-population of RP genes, the 5' untranslated sequences are optimized for regulatory function.ConclusionOur results argue against the direct involvement of introns in the regulation of transcription of highly expressed genes. Moreover, systematic differences in motif distributions suggest that RP transcription factors may act differently on intron-containing and intronless gene promoters. Thus, our findings contribute to the decoding of the RP promoter architecture and may fuel the discussion on the evolution of introns.

Intracellular Recycling and Iron Donating Ability of Transferrin Receptor 2α Protein Expressed in Transferrin Receptor-Deficient Chinese Hamster Ovary Cells.

[Introduction] Transferrin receptor 2 (TfR2), a homologue of the transferrin receptor 1 (TfR1), is found in two isoforms, α and β. Like the classical TfR1, TfR2α is a type II membrane protein expressing mainly in the hepatocytes as homodimer on their cell surface, but the β form lacks intracellular and transmembrane portions and therefore is likely to be an intracellular protein. Although the main physiological functions of these two isoforms are still not fully understood, TfR2α binds transferrin (Tf), and is therefore thought likely to be involved in cellular iron metabolism. Disruption of TfR2 leads to hemochromatosis, implying that the function of TfR2 might be a regulation of iron metabolism. However, TfR1 have remarkably high binding affinity to diferric Tf and only little expression on the cell surface of hepatocytes so that TfR1 must be fully saturated under physiological conditions. Besides, TfR2 is upregulated in some conditions in that iron accumulation was observed, for instance in the liver of the patients of hepatitis C, indicating that TfR2 might also function as the iron donator for the hepatocytes. The aim of the present study was to investigate the interactions of TfR2α with Tf, and to elucidate whether TfR2α have the ability of iron donation to the cells.[Methods] To investigate the functional properties of TfR2α, we expressed TfR2α protein with FLAG-tagging in transferrin receptor-deficient Chinese hamster ovary (CHO) cells (TRVb). The stably transfected cells expressing TfR2α-FLAG were applied for the 125I -labeled Tf (125I -Tf) binding study at 4 °C. The cells were applied for Tf and iron uptake study using 125I -Tf and 59Fe -loaded at 37 °C. To determine the fate of Tf internalized into the cells, the release of internalized Tf were then investigated. Degradation of released Tf was also investigated by precipitation using trichloroacetic acid/phosphotungustic acid.[Results] The association constant for binding of 125I-Tf to TfR2α was calculated to be 5.6 × 106 M−1 from non-linear least squares curve fitting to a saturable binding isotherm, which is about 50 times lower than that of TfR1. Although CHO cells showed a receptor-independent non-specific association with Tf at 37 °C, we observed cell-associated Tf persisting after acid-washing in TfR2α overexpressing cells, confirming that the existence of Tf internalization via TfR2α. After internalization, efflux of Tf, without substantial degradation, is also confirmed. Thus, Tf internalized by TfR2α, and presumably recycles, like TfR1 pathway. Overexpressed TfR2α protein was also shown to mediate iron uptake although its rate of iron donation is slower than TfR1.[Discussion and Conclusions] TfR2α binds to Tf although its affinity for Tf is low, and TfR2α possesses iron donating ability to the cells when TfR2α is over-expressed in our study. Although TfR2α has been reported to be involved in iron sensing and regulation of hepcidin expression, the involvement of the Tf binding and iron donating properties of TfR2α should be considered when the pathophysiology of iron metabolism is investigated, especially in the conditions that TfR2α is upregulated, for instance in hepatitis C.