Biomedical subjects

Yuhai Tu

Publications and source records attributed to Yuhai Tu.

At least 19 recordsLinked to original sources

PubMed2005

An allosteric model for heterogeneous receptor complexes: understanding bacterial chemotaxis responses to multiple stimuli.

The classical Monod-Wyman-Changeux model for homogeneous allosteric protein complex is generalized in this article to model the responses of heterogeneous receptor complexes to multiple types of ligand stimulus. We show that the recent in vivo experimental data of Escherichia coli chemotaxis responses for mutant strains with different expression levels of the chemo-receptors to different types of stimulus [Sourjik, V. & Berg, H. C. (2004) Nature 428, 437-441] all can be explained consistently within this generalized Monod-Wyman-Changeux model. Based on the model and the existing data, responses of all of the strains (studied in this article) to the presence of any combinations of ligand (Ser and MeAsp) concentrations are predicted quantitatively for future experimental verification. Through modeling the in vivo response data, our study reveals important information about the properties of different types of individual receptors, as well as the composition of the cluster. The energetic contribution of the nonligand binding, cytoplasmic parts of the cluster, such as CheA and CheW, is also discussed. The generalized allosteric model provides a consistent framework in understanding signal integration and differentiation in bacterial chemotaxis. It should also be useful for studying the functions of other heterogeneous receptor complexes.

Bacterial Physiological Phenomena↗

PubMed2005

Excitation-contraction coupling gain and cooperativity of the cardiac ryanodine receptor: a modeling approach.

During calcium-induced calcium-release, the ryanodine receptor (RyR) opens and releases large amounts of calcium from the sarcoplasmic reticulum into the cytoplasm of the myocyte. Recent experiments have suggested that cooperativity between the four monomers comprising the RyR plays an important role in the dynamics of the overall receptor. Furthermore, this cooperativity can be affected by the binding of FK506 binding protein, and hence, modulated by adrenergic stimulation through the phosphorylating action of protein kinase A. This has important implications for heart failure, where it has been hypothesized that RyR hyperphosphorylation, resulting in a loss of cooperativity, can lead to a persistent leak and a reduced sarcoplasmic-reticula content. In this study, we construct a theoretical model that examines the cooperativity via the assumption of an allosteric interaction between the four subunits. We find that the level of cooperativity, regulated by the binding of FK506 binding-protein, can have a dramatic effect on the excitation-contraction coupling gain and that this gain exhibits a clear maximum. These findings are compared to currently available data from different species and allows for an evaluation of the aforementioned heart-failure scenario.

Allosteric Site↗

PubMed2005

How white noise generates power-law switching in bacterial flagellar motors.

The clockwise (CW) or counterclockwise (CCW) spinning of a bacterial flagellar motor is controlled by the concentration [Y] of a phosphorylated protein, CheY-P. Representing the stochastic switching behavior of the motor by a dynamical two-state (CW and CCW) model, whose energy levels fluctuate in time (t) as [Y](t) fluctuates, we show that temporal fluctuations in [Y](t) can generate a power-law distribution for the durations of the CCW states, in agreement with recent experiments. Correlations between the duration times of nearby CCW (CW) intervals are predicted by our model, and shown to exist in the experimental data and to affect the power spectrum for motor switching.

Bacterial Proteins↗

PubMed2005

Report: workshop on mediastinal grey zone lymphoma.

There are several indications that classical Hodgkin lymphoma (cHL) and at least a proportion of cases of Primary Mediastinal B cell Lymphoma (PMBL) are derived from B cells at similar stages of differentiation and share common pathogenic mechanisms. The first indication was the existence of mediastinal grey zone lymphomas as identified in the 4th International Symposium on HL, with clinical, histological and immunohistochemical features intermediate between cHL and PMBL. Second, both tumor types resemble a cell that is developmentally situated in-between the germinal center reaction and a plasma cell. Third, cHL and PMBL were found to have similar gene expression profiles, including the lack of immunoglobulin expression and low levels of B cell receptor signalling molecules, and the secretion of molecules like the chemokine TARC and the prominent expression of IL-13 receptors. Fourth, both entities were found to have common genomic aberrancies, notably in 2p15 and 9p24, the sites of the REL oncogene and the tyrosine kinase gene JAK2, respectively. Further comparison of both lymphoma types may provide further insight in the pathogenic mechanisms and allow the design of diagnostic algorithms to sort out the small number of so-called mediastinal grey zone lymphomas, that appear to be intermediate between PMBL and cHL.

B-Lymphocytes↗

PubMed2004

Origin of apparent critical thickness for island formation in heteroepitaxy.

We find that a continuum model of heteroepitaxy exhibits a sharp crossover with increasing coverage, from planar growth to island formation. The "critical thickness" at which this Stranski-Krastanov transition occurs depends sensitively on misfit strain, with a dependence strikingly similar to that seen experimentally. The initial planar growth occurs because of intermixing of deposited material with the substrate. While the transition is strictly kinetic in nature, it depends only weakly on growth rate. The role of surface segregation is also discussed.

Journal Article↗

PubMed2004

Reconstructing biological networks using conditional correlation analysis.

MOTIVATION: One of the present challenges in biological research is the organization of the data originating from high-throughput technologies. One way in which this information can be organized is in the form of networks of influences, physical or statistical, between cellular components. We propose an experimental method for probing biological networks, analyzing the resulting data and reconstructing the network architecture. METHODS: We use networks of known topology consisting of nodes (genes), directed edges (gene-gene interactions) and a dynamics for the genes' mRNA concentrations in terms of the gene-gene interactions. We proposed a network reconstruction algorithm based on the conditional correlation of the mRNA equilibrium concentration between two genes given that one of them was knocked down. Using simulated gene expression data on networks of known connectivity, we investigated how the reconstruction error is affected by noise, network topology, size, sparseness and dynamic parameters. RESULTS: Errors arise from correlation between nodes connected through intermediate nodes (false positives) and when the correlation between two directly connected nodes is obscured by noise, non-linearity or multiple inputs to the target node (false negatives). Two critical components of the method are as follows: (1) the choice of an optimal correlation threshold for predicting connections and (2) the reduction of errors arising from indirect connections (for which a novel algorithm is proposed). With these improvements, we can reconstruct networks with the topology of the transcriptional regulatory network in Escherichia coli with a reasonably low error rate.

Algorithms↗

PubMed2004

Tracking CD40 signaling during germinal center development.

Substantial evidence indicates that signaling through the CD40 receptor (CD40) is required for germinal center (GC) and memory B-cell formation. However, it is not fully understood at which stages of B-cell development the CD40 pathway is activated in vivo. To address this question, we induced CD40 signaling in human transformed GC B cells in vitro and identified a CD40 gene expression signature by DNA microarray analysis. This signature was then investigated in the gene expression profiles of normal B cells and found in pre- and post-GC B cells (naive and memory) but, surprisingly, not in GC B cells. This finding was validated in lymphoid tissues by showing that the nuclear factor-kappaB (NF-kappaB) transcription factors, which translocate to the nucleus upon CD40 stimulation, are retained in the cytoplasm in most GC B cells, indicating the absence of CD40 signaling. Nevertheless, a subset of centrocytes and B cells in the subepithelium showed nuclear staining of multiple NF-kappaB subunits, suggesting that a fraction of naive and memory B cells may be subject to CD40 signaling or to other signals that activate NF-kappaB. Together, these results show that GC expansion occurs in the absence of CD40 signaling, which may act only in the initial and final stages of the GC reaction.

B-Lymphocytes↗

PubMed2004

Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

MOTIVATION: Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. RESULTS: We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. AVAILABILITY: Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

Algorithms↗

PubMed2004

Effects of receptor interaction in bacterial chemotaxis.

Signaling in bacterial chemotaxis is mediated by several types of transmembrane chemoreceptors. The chemoreceptors form tight polar clusters whose functions are of great biological interest. Here, we study the general properties of a chemotaxis model that includes interaction between neighboring chemoreceptors within a receptor cluster and the appropriate receptor methylation and demethylation dynamics to maintain (near) perfect adaptation. We find that, depending on the receptor coupling strength, there are two steady-state phases in the model: a stationary phase and an oscillatory phase. The mechanism for the existence of the two phases is understood analytically. Two important phenomena in transient response, the overshoot in response to a pulse stimulus and the high gain in response to sustained changes in external ligand concentrations, can be explained in our model, and the mechanisms for these two seemingly different phenomena are found to be closely related. The model also naturally accounts for several key in vitro response experiments and the recent in vivo fluorescence resonance energy transfer experiments for various mutant strains. Quantitatively, our study reveals possible choices of parameters for fitting the existing experiments and suggests future experiments to test the model predictions.

Bacterial Physiological Phenomena↗

PubMed2003

Quantitative modeling of sensitivity in bacterial chemotaxis: the role of coupling among different chemoreceptor species.

We propose a general theoretical framework for modeling receptor sensitivity in bacterial chemotaxis, taking into account receptor interactions, including those among different receptor species. We show that our model can quantitatively explain the recent in vivo measurements of receptor sensitivity at different ligand concentrations for both mutant and wild-type strains. For mutant strains, our model can fit the experimental data exactly. For the wild-type cell, our model is capable of achieving high gain while having modest values of Hill coefficient for the response curves. Furthermore, the high sensitivity of the wild-type cell in our model is maintained for a wide range of ambient ligand concentrations, facilitated by near-perfect adaptation and dependence of ligand binding on receptor activity. Our study reveals the importance of coupling among different chemoreceptor species, in particular strong interactions between the aspartate (Tar) and serine (Tsr) receptors, which is crucial in explaining both the mutant and wild-type data. Predictions for the sensitivity of other mutant strains and possible improvements of our model for the wild-type cell are also discussed.

Bacterial Proteins↗

PubMed2003

Transcriptional analysis of the B cell germinal center reaction.

The germinal center (GC) reaction is crucial for T cell-dependent immune responses and is targeted by B cell lymphomagenesis. Here we analyzed the transcriptional changes that occur in B cells during GC transit (naive B cells --> centroblasts --> centrocytes --> memory B cells) by gene expression profiling. Naive B cells, characterized by the expression of cell cycle-inhibitory and antiapoptotic genes, become centroblasts by inducing an atypical proliferation program lacking c-Myc expression, switching to a proapoptotic program, and down-regulating cytokine, chemokine, and adhesion receptors. The transition from GC to memory cells is characterized by a return to a phenotype similar to that of naive cells except for an apoptotic program primed for both death and survival and for changes in the expression of cell surface receptors including IL-2 receptor beta. These results provide insights into the dynamics of the GC reaction and represent the basis for the analysis of B cell malignancies.

Apoptosis↗

PubMed2003

Perfect and near-perfect adaptation in a model of bacterial chemotaxis.

The signaling apparatus mediating bacterial chemotaxis can adapt to a wide range of persistent external stimuli. In many cases, the bacterial activity returns to its prestimulus level exactly, and this perfect adaptability is robust against variations in various chemotaxis protein concentrations. We model the bacterial chemotaxis signaling pathway, from ligand binding to CheY phosphorylation. By solving the steady-state equations of the model analytically, we derive a full set of conditions for the system to achieve perfect adaptation. The conditions related to the phosphorylation part of the pathway are discovered for the first time, while other conditions are generalizations of the ones found in previous works. Sensitivity of the perfect adaptation is evaluated by perturbing these conditions. We find that, even in the absence of some of the perfect adaptation conditions, adaptation can be achieved with near-perfect precision as a result of the separation of scales in both chemotaxis protein concentrations and reaction rates, or specific properties of the receptor distribution in different methylation states. Since near-perfect adaptation can be found in much larger regions of the parameter space than that defined by the perfect adaptation conditions, their existence is essential to understand robustness in bacterial chemotaxis.

Adaptation, Physiological↗

PubMed2003

Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions.

We have developed a model of cardiac thin filament activation using an Ising model approach from equilibrium statistical physics. This model explicitly represents nearest-neighbor interactions between 26 troponin/tropomyosin units along a one-dimensional array that represents the cardiac thin filament. With transition rates chosen to match experimental data, the results show that the resulting force-pCa (F-pCa) relations are similar to Hill functions with asymmetries, as seen in experimental data. Specifically, Hill plots showing (log(F/(1-F)) vs. log [Ca]) reveal a steeper slope below the half activation point (Ca(50)) compared with above. Parameter variation studies show interplay of parameters that affect the apparent cooperativity and asymmetry in the F-pCa relations. The model also predicts that Ca binding is uncooperative for low [Ca], becomes steeper near Ca(50), and becomes uncooperative again at higher [Ca]. The steepness near Ca(50) mirrors the steep F-pCa as a result of thermodynamic considerations. The model also predicts that the correlation between troponin/tropomyosin units along the one-dimensional array quickly decays at high and low [Ca], but near Ca(50), high correlation occurs across the whole array. This work provides a simple model that can account for the steepness and shape of F-pCa relations that other models fail to reproduce.

Actin Cytoskeleton↗

PubMed2003

Gene expression dynamics during germinal center transit in B cells.

The germinal center (GC) reaction in T cell dependent antibody responses is crucial for the generation of B cell memory and plays a critical role in B cell lymphomagenesis. To gain insight into the physiology of this reaction, we identified the transcriptional changes that occur in B cells during the GC-transit (naïve B cells --> CD77(+) centroblasts (CBs) --> CD77(-) centrocytes (CCs) --> memory B cells) by DNA microarray experiments and the subsequent data analysis employing unsupervised and supervised hierarchical clustering. The naïve B cell is characterized by a nonproliferative, anti-apoptotic phenotype and the expression of various chemokine and cytokine receptors. The transition from naïve B cells to CBs is associated with (1) the up-regulation of genes associated with cellular proliferation, DNA-repair, and chromatin remodeling; (2) the acquisition of a pro-apoptotic phenotype; (3) the down-regulation of cytokine, chemokine, and adhesion receptors expressed in the naïve cells; and (4) the expression of a distinct adhesion repertoire. The CB and the CC revealed surprisingly few gene expression differences, suggesting that the CC is heterogeneous in its cellular composition. The CB/CC to memory B cell transition shows a general reversion to the profile characteristic for the naïve B cells, with the exception of the up-regulation of several surface receptors, including CD27, CD80, and IL-2Rbeta, and the simultaneous expression of both anti- and pro-apoptotic genes. These gene expression profiles of the normal B cell subpopulations are being used to identify the signals occurring during GC development, the cellular derivation of various types of B cell malignancies, and the genes deregulated in GC-derived tumors.

B-Lymphocytes↗

PubMed2003

Identification of Hodgkin and Reed-Sternberg cell-specific genes by gene expression profiling.

Hodgkin lymphoma (HL) is a malignancy of unknown pathogenesis. The malignant Hodgkin and Reed/Sternberg (HRS) cells derive from germinal center B cells (or rarely, T cells) but have a heterogeneous and largely uncharacterized phenotype. Using microarrays, we compared the gene expression profile of four HL cell lines with profiles of the main B cell subsets and B cell non-HLs to find out whether HRS cells, despite their described heterogeneity, show a distinct gene expression, to study their relationship to other normal and malignant B cells, and to identify genes aberrantly or overexpressed by HRS cells. The HL lines indeed clustered as a distinct entity, irrespective of their B or T cell derivation, and their gene expression was most similar to that of EBV-transformed B cells and cell lines derived from diffuse large cell lymphomas showing features of in vitro-activated B cells. Twenty-seven genes, most of which were previously unknown to be expressed by HRS cells, showed aberrant expression specifically in these cells, e.g., the transcription factors GATA-3, ABF1, EAR3, and Nrf3. For five genes, expression in primary HRS cells was confirmed. The newly identified HL-specific genes may play important roles in the pathogenesis of HL, potentially represent novel diagnostic markers, and can be considered for therapeutic targeting.

B-Lymphocytes↗

PubMed2003

Identification of a global gene expression signature of B-chronic lymphocytic leukemia.

B-chronic lymphocytic leukemia (B-CLL) is an adult-onset leukemia characterized by significant accumulation of apoptosis-resistant monoclonal B lymphocytes. In this study, we performed gene expression profiling on B cells obtained from 10 healthy age-matched individuals and CLL B cells from 38 B-CLL patients to identify key genetic differences between CLL and normal B cells. In addition, we leveraged recent independent studies to assess the reproducibility of our molecular B-CLL signature. We used a novel combination of several methods of data analysis including our own software and identified 70 previously unreported genes that differentiate leukemic cells from normal B cells, as well as confirmed recently reported B-CLL specific expression levels of an additional 10 genes. Importantly, many of these genes have previously been linked with other cancers, thus lending further support to their importance as candidate genes leading to B-CLL pathogenesis. We have also validated a subset of these genes using independent methodologies. Moreover, we show that our genes can be used to create a diagnostics signature that performs with perfect sensitivity and specificity in an independent cohort of 21 B-CLL and 20 normal subjects, thus strongly validating the informative nature of our set of genes. Finally, we identified a group of 31 genes that distinguish between low (Rai stage 0) and high (Rai stage 4) risk patients, suggesting that there may also be a gene expression signature that associates with disease progression.

ATP-Binding Cassette Transporters↗

PubMed2003

Can we identify cellular pathways implicated in cancer using gene expression data?

The cancer state of a cell is characterized by alterations of important cellular processes such as cell proliferation, apoptosis, DNA-damage repair, etc. The expression of genes associated with cancer related pathways, therefore, may exhibit differences between the normal and the cancerous states. We explore various means to find these differences. We analyze 6 different pathways (p53, Ras, Brca, DNA damage repair, NFkappab and beta-catenin) and 4 different types of cancer: colon, pancreas, prostate and kidney. Our results are found to be mostly consistent with existing knowledge of the involvement of these pathways in different cancers. Our analysis constitutes proof of principle that it may be possible to predict the involvement of a particular pathway in cancer or other diseases by using gene expression data. Such method would be particularly useful for the types of diseases where biology is poorly understood.

Biomarkers, Tumor↗

PubMed2002

Microscopic dynamics of silicon oxidation.

We study the silicon oxidation process and the dynamic structure of the SiO2-Si (001) interface using a grand canonical Monte Carlo approach. We find that Si-O-Si bridge bonds are the main building blocks of the advancing interface, and we identify a kinetic pathway that continually creates new bridge bonds. Oxidation proceeds by local events, with little evidence of "step flow" in the simulation. Yet the interface remains remarkably smooth and abrupt as it advances.

Journal Article↗