Biomedical subjects

Yu Xia

Publications and source records attributed to Yu Xia.

At least 37 records · Page 2Linked to original sources

PubMed2005

Mutual storage mode ion/ion reactions in a hybrid linear ion trap.

Ion/ion proton transfer reactions involving mutual storage of both ion polarities in a linear ion trap (LIT) that comprises part of a hybrid triple quadrupole/linear ion trap mass spectrometer have been effected. Mutual ion storage in the x- and y-dimensions arises from the normal operation of the oscillating quadrupole field of the quadrupole array, while storage in the z-dimension is enabled by applying unbalanced radio-frequency amplitudes to opposing sets of rods of the array. Efficient trapping (>90%) is achieved for thermalized ions over periods of several seconds. Reactions were demonstrated for multiply charged protein/peptide cations formed by electrospray with anions derived from glow discharge ionization of perfluoro(methyldecalin) (PMD) introduced from the side of the LIT rod array. Doubly and singly charged protein ions are readily formed via ion/ion reactions. The parameters that affect ion/ion reactions are discussed, including the degree of RF unbalance on the LIT rods, vacuum pressure, nature of the buffer gas, reaction time, anion abundance, and the low mass cutoff for ion/ion reaction. The present system has a demonstrated upper mass-to-charge ratio limit of at least 33,000. The system also has high flexibility with respect to defining MS(n) experiments involving both collision-induced dissociation (CID) and ion/ion reactions. Experiments are demonstrated involving beam-type CID in the pressurized collision quadrupole (Q2) followed by ion/ion reactions involving the product ions in the LIT. Ion parking experiments are also demonstrated using the mutual storage ion/ion reaction mode in the LIT, with a parking efficiency over 60%.

Ions↗

PubMed2005

Assessing the limits of genomic data integration for predicting protein networks.

Genomic data integration--the process of statistically combining diverse sources of information from functional genomics experiments to make large-scale predictions--is becoming increasingly prevalent. One might expect that this process should become progressively more powerful with the integration of more evidence. Here, we explore the limits of genomic data integration, assessing the degree to which predictive power increases with the addition of more features. We focus on a predictive context that has been extensively investigated and benchmarked in the past-the prediction of protein-protein interactions in yeast. We start by using a simple Naive Bayes classifier for integrating diverse sources of genomic evidence, ranging from coexpression relationships to similar phylogenetic profiles. We expand the number of features considered for prediction to 16, significantly more than previous studies. Overall, we observe a small, but measurable improvement in prediction performance over previous benchmarks, based on four strong features. This allows us to identify new yeast interactions with high confidence. It also allows us to quantitatively assess the inter-relations amongst different genomic features. It is known that subtle correlations and dependencies between features can confound the strength of interaction predictions. We investigate this issue in detail through calculating mutual information. To our surprise, we find no appreciable statistical dependence between the many possible pairs of features. We further explore feature dependencies by comparing the performance of our simple Naive Bayes classifier with a boosted version of the same classifier, which is fairly resistant to feature dependence. We find that boosting does not improve performance, indicating that, at least for prediction purposes, our genomic features are essentially independent. In summary, by integrating a few (i.e., four) good features, we approach the maximal predictive power of current genomic data integration; moreover, this limitation does not reflect (potentially removable) inter-relationships between the features.

Algorithms↗

PubMed2005

Use of thioredoxin as a reporter to identify a subset of Escherichia coli signal sequences that promote signal recognition particle-dependent translocation.

We have previously reported that the DsbA signal sequence promotes efficient, cotranslational translocation of the cytoplasmic protein thioredoxin-1 via the bacterial signal recognition particle (SRP) pathway. However, two commonly used signal sequences, those of PhoA and MalE, which promote export by a posttranslational mechanism, do not export thioredoxin. We proposed that this difference in efficiency of export was due to the rapid folding of thioredoxin in the cytoplasm; cotranslational export by the DsbA signal sequence avoids the problem of cytoplasmic folding (C. F. Schierle, M. Berkmen, D. Huber, C. Kumamoto, D. Boyd, and J. Beckwith, J. Bacteriol. 185:5706-5713, 2003). Here, we use thioredoxin as a reporter to distinguish SRP-dependent from non-SRP-dependent cleavable signal sequences. We screened signal sequences exhibiting a range of hydrophobicity values based on a method that estimates hydrophobicity. Successive iterations of screening and refining the method defined a threshold hydrophobicity required for SRP recognition. While all of the SRP-dependent signal sequences identified were above this threshold, there were also a few signal sequences above the threshold that did not utilize the SRP pathway. These results suggest that a simple measure of the hydrophobicity of a signal sequence is an important but not a sufficient indicator for SRP recognition. In addition, by fusing a number of both classes of signal sequences to DsbA, we found that DsbA utilizes an SRP-dependent signal sequence to achieve efficient export to the periplasm. Our results suggest that those proteins found to be exported by SRP-dependent signal sequences may require this mode of export because of their tendency to fold rapidly in the cytoplasm.

Blotting, Western↗

PubMed2005

[Expression of P-gp, GST-pi and Topo II alpha in gastric and colorectal cancers and their clinical significance].

OBJECTIVE: To study the expression and clinical significance of P-gp, GST-pi and Topo II alpha in gastric and colorectal cancers. METHODS: The expression of P-gp, GST-pi and Topo II alpha in 83 cases with gastric or colorectal cancer were examined by immunohistochemistry S-P. RESULTS: The positive expression rates of P-gp, GST-pi, Topo II alpha in normal tissue and gastric and colorectal cancers were 69.9%, 65.1%, 50.6% and 83.1%, 85.5%, 45.8%, respectively. The positive rates of P-gp and GST-pi in gastric and colorectal cancer were significantly higher than those in normal gastric and colorectal tissue (P < 0.05). The expression of Topo II alpha in poorly differentiated cancers was significantly higher than that in well-and moderately differentiated cancers. There was no correlation between other items and clinicopathological parameters (P > 0.05). CONCLUSION: P-gp, GST-pi and Topo II alpha play important role in multidrug resistance. Their mechanisms of drug resistance were different. The detection of expression of P-gp, GST-pi and Topo II alpha has an important guiding significance in chemotherapy for gastric and colorectal cancers.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

PubMed2004

Positive ion transmission mode ion/ion reactions in a hybrid linear ion trap.

A triple quadrupole mass spectrometer capable of ion trapping experiments has been adapted for ion/ion reaction studies. The instrument is based on a commercially available linear ion trap (LIT) tandem mass spectrometer (i.e., an MDS SCIEX 2000 Q TRAP) that has been modified by mounting an atmospheric sampling glow discharge ionization (ASGDI) source to the side of the vacuum manifold for production of singly charged anions. The ASGDI source is located line of sight to the side of the third quadrupole of the triple quadrupole assembly (Q3). Anions are focused into the side of the rod array (i.e., anion injection occurs orthogonal to the normal ion flight path). A transmission mode method to perform ion/ion reactions has been developed whereby positive ions are transmitted through the pressurized collision quadrupole (Q2) while anions are stored in Q2. The Q2 LIT is used to trap negative ions whereas the Q3 LIT is used to accumulate positive ions transmitted from Q2. Anions are injected to Q3 and transferred to Q2, where they are stored and collisionally cooled. Multiply charged protein/peptide ions, formed by electrospray, are then mass selected by the first quadrupole assembly (Q1) operated in the rf/dc mode and injected into Q2. The positive ions, including the residual precursor ions and the product ions arising from ion/ion proton-transfer reactions, are accumulated in Q3 until they are analyzed via mass-selective axial ejection for mass analysis. The parameters that affect ion/ion reactions are discussed, including pressure, nature of the gas in Q2, and operation of Q2 as a linear accelerator. Ion/ion reactions in this mode can be readily utilized to separate ions with the same m/z but largely different mass and charge, e.g., +1 bradykinin and +16 myoglobin, in the gas phase.

Animals↗

PubMed2004

Selection and characterization of small random transmembrane proteins that bind and activate the platelet-derived growth factor beta receptor.

Growth factor receptors are typically activated by the binding of soluble ligands to the extracellular domain of the receptor, but certain viral transmembrane proteins can induce growth factor receptor activation by binding to the receptor transmembrane domain. For example, homodimers of the transmembrane 44-amino acid bovine papillomavirus E5 protein bind the transmembrane region of the PDGF beta receptor tyrosine kinase, causing receptor dimerization, phosphorylation, and cell transformation. To determine whether it is possible to select novel biologically active transmembrane proteins that can activate growth factor receptors, we constructed and identified small proteins with random hydrophobic transmembrane domains that can bind and activate the PDGF beta receptor. Remarkably, cell transformation was induced by approximately 10% of the clones in a library in which 15 transmembrane amino acid residues of the E5 protein were replaced with random hydrophobic sequences. The transformation-competent transmembrane proteins formed dimers and stably bound and activated the PDGF beta receptor. Genetic studies demonstrated that the biological activity of the transformation-competent proteins depended on specific interactions with the transmembrane domain of the PDGF beta receptor. A consensus sequence distinct from the wild-type E5 sequence was identified that restored transforming activity to a non-transforming poly-leucine transmembrane sequence, indicating that divergent transmembrane sequence motifs can activate the PDGF beta receptor. Molecular modeling suggested that diverse transforming sequences shared similar protein structure, including the same homodimer interface as the wild-type E5 protein. These experiments have identified novel proteins with transmembrane sequences distinct from the E5 protein that can activate the PDGF beta receptor and transform cells. More generally, this approach may allow the creation and identification of small proteins that modulate the activity of a variety of cellular transmembrane proteins.

Animals↗

PubMed2004

Funnel-like organization in sequence space determines the distributions of protein stability and folding rate preferred by evolution.

To understand the physical and evolutionary determinants of protein folding, we map out the complete organization of thermodynamic and kinetic properties for protein sequences that share the same fold. The exhaustive nature of our study necessitates using simplified models of protein folding. We obtain a stability map and a folding rate map in sequence space. Comparison of the two maps reveals a common organizational principle: optimality decreases more or less uniformly with distance from the optimal sequence in the sequence space. This gives a funnel-shaped optimality surface. Evolutionary dynamics of a sequence population on these two maps reveal how the simple organization of sequence space affects the distributions of stability and folding rate preferred by evolution.

Biological Evolution↗

PubMed2004

Nanoelectrospray ionization of protein mixtures: solution pH and protein pI.

Solutions consisting of single proteins and mixtures of proteins at different pH values have been subjected to both positive ion and negative ion nanoelectrospray ionization to study the influence of solvent pH and protein pI on the ionization responses of proteins. As has been noted previously, it is possible to form protein ions of one polarity despite the fact that the proteins are present as the opposite polarity in solution. However, total response under this condition tends to be at least an order of magnitude less than the condition in which the nanoelectrospray ionization polarity is the same as the net charge of the proteins in solution. Furthermore, maximum signals in positive ion mode were noted when the pH value of the solution was 4-5 units lower than the protein pI. In the negative ion mode, maximum protein anion signals were observed when the pH was roughly 5 units higher than the protein pI. While only small changes in the abundance-weighted average charge were noted as a function of solution conditions, the extent of sodium ion incorporation was seen to depend strongly on the relationship between net protein charge in solution and gas-phase ion polarity. Sodium ion incorporation was minimized under conditions of maximum signal (i.e., low pH positive ion mode and high pH negative ion mode). Sodium ion incorporation was highest when the protein ion polarities in solution and the gas phase were opposite. These observations are consistent with the charged residue model for electrospray ionization and suggest that a degree of selectivity for electrospray ionization applied to protein mixtures can be realized via judicious selection of solution pH and ionization polarity. Furthermore, the relative extent of sodium ion incorporation under a given set of conditions appears to correlate, at least qualitatively, with protein pI.

Animals↗

PubMed2004

Simulating protein evolution in sequence and structure space.

Naturally occurring proteins comprise a special subset of all plausible sequences and structures selected through evolution. Simulating protein evolution with simplified and all-atom models has shed light on the evolutionary dynamics of protein populations, the nature of evolved sequences and structures, and the extent to which today's proteins are shaped by selection pressures on folding, structure and function. Extensive mapping of the native structure, stability and folding rate in sequence space using lattice proteins has revealed organizational principles of the sequence/structure map important for evolutionary dynamics. Evolutionary simulations with lattice proteins have highlighted the importance of fitness landscapes, evolutionary mechanisms, population dynamics and sequence space entropy in shaping the generic properties of proteins. Finally, evolutionary-like simulations with all-atom models, in particular computational protein design, have helped identify the dominant selection pressures on naturally occurring protein sequences and structures.

Algorithms↗

PubMed2004

Computational analysis of membrane proteins: genomic occurrence, structure prediction and helix interactions.

We review recent computational advances in the study of membrane proteins, focusing on those that have at least one transmembrane helix. Transmembrane protein regions are, in many respects, easier to investigate computationally than experimentally, due to the uniformity of their structure and interactions (e.g. consisting predominately of nearly parallel helices packed together) on one hand and presenting the challenges of solubility on the other. We present the progress made on identifying and classifying membrane proteins into families, predicting their structure from amino-acid sequence patterns (using many different methods), and analyzing their interactions and packing The total result of this work allows us for the first time to begin to think about the membrane protein interactome, the set of all interactions between distinct transmembrane helices in the lipid bilayer.

Computational Biology↗

PubMed2004

Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs.

Proteins function mainly through interactions, especially with DNA and other proteins. While some large-scale interaction networks are now available for a number of model organisms, their experimental generation remains difficult. Consequently, interolog mapping--the transfer of interaction annotation from one organism to another using comparative genomics--is of significant value. Here we quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins. Using interaction information from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Helicobacter pylori, we find that protein-protein interactions can be transferred when a pair of proteins has a joint sequence identity >80% or a joint E-value <10(-70). (These "joint" quantities are the geometric means of the identities or E-values for the two pairs of interacting proteins.) We generalize our interolog analysis to protein-DNA binding, finding such interactions are conserved at specific thresholds between 30% and 60% sequence identity depending on the protein family. Furthermore, we introduce the concept of a "regulog"--a conserved regulatory relationship between proteins across different species. We map interologs and regulogs from yeast to a number of genomes with limited experimental annotation (e.g., Arabidopsis thaliana) and make these available through an online database at http://interolog.gersteinlab.org. Specifically, we are able to transfer approximately 90,000 potential protein-protein interactions to the worm. We test a number of these in two-hybrid experiments and are able to verify 45 overlaps, which we show to be statistically significant.

Amino Acid Sequence↗

PubMed2004

Analyzing cellular biochemistry in terms of molecular networks.

One way to understand cells and circumscribe the function of proteins is through molecular networks. These networks take a variety of forms including webs of protein-protein interactions, regulatory circuits linking transcription factors and targets, and complex pathways of metabolic reactions. We first survey experimental techniques for mapping networks (e.g., the yeast two-hybrid screens). We then turn our attention to computational approaches for predicting networks from individual protein features, such as correlating gene expression levels or analyzing sequence coevolution. All the experimental techniques and individual predictions suffer from noise and systematic biases. These problems can be overcome to some degree through statistical integration of different experimental datasets and predictive features (e.g., within a Bayesian formalism). Next, we discuss approaches for characterizing the topology of networks, such as finding hubs and analyzing subnetworks in terms of common motifs. Finally, we close with perspectives on how network analysis represents a preliminary step toward a systems approach for modeling cells.

Biochemical Phenomena↗

PubMed2004

[Muscle-sparing thoracotomy in chest surgery].

OBJECTIVE: To review the clinical experience of muscle-sparing thoracotomy in intrathoracic surgery. METHODS: Thoracotomy was performed in 386 patients from 1998 to 2002, during the procedure lateral-transverse incision, free dissection of muscular flap and entering to the thoracic cavity through certain intercostal space were applied. Two sets of rib retractors were used to ensure the excellent field exposure. RESULTS: Intrathoracic surgery was carried out by this method with the advantage of excellent surgical field exposure, less pain and relative quick recovery. CONCLUSION: Muscle-sparing thoracotomy has the merits of less injury and the same good exposure as routine thoracotomy and it can be carried out in majority of chest surgery.

Adolescent↗

PubMed2003

Mutation analysis of 20 SARS virus genome sequences: evidence for negative selection in replicase ORF1b and spike gene.

AIM: Recently, more SARS-CoV virus genome sequences are released to the GenBank database. The aim of this study is to reveal the evolution forces of SARS-CoV virus by analyzing the nucleotide mutations in these sequences. METHODS: We obtained 20 SARS-CoV virus genome sequences from NCBI database, and calculated the ratio of non-synonymous nucleotide substitution per non-synonymous site (Ka) and synonymous nucleotide substitution per synonymous site (Ks) for SARS-CoV virus genes. RESULTS: The Ka/Ks ratios for replicase polyprotein ORF1a, ORF1b, and spike protein gene are 1.09 (P=0.6501), 0.38 (P=0.0074), 0.65 (P=0.0685) respectively. CONCLUSION: SARS-CoV virus replicase polyprotein ORF1b is undergoing negative selection; negative selection force is also probably operating on spike protein gene. These results provide basis for future developing a new drug and vaccine against SARS.

Base Sequence↗

PubMed2002

Function of the lectin domain of Mac-1/complement receptor type 3 (CD11b/CD18) in regulating neutrophil adhesion.

A lectin function within CD11b mediates both cytotoxic priming of Mac-1/complement receptor type 3 (CR3) by beta-glucan and the formation of transmembrane signaling complexes with GPI-anchored glycoproteins such as CD16b (FcgammaRIIIb). A requirement for GPI-anchored urokinase plasminogen activator receptor (uPAR; CD87) in neutrophil adhesion and diapedesis has been demonstrated with uPAR-knockout mice. In this study, neutrophil activation conditions generating high-affinity (H-AFN) or low-affinity (L-AFN) beta(2) integrin adhesion were explored. A role for the Mac-1/CR3 lectin domain and uPAR in mediating H-AFN or L-AFN adhesion was suggested by the inhibition of Mac-1/CR3-dependent adhesion to ICAM-1 or fibrinogen by beta-glucan or anti-uPAR. The formation of uPAR complexes with Mac-1/CR3 activated for L-AFN adhesion was demonstrated by fluorescence resonance energy transfer. Conversely, Jurkat cell LFA-1 H-AFN-adhesion to ICAM-1 was not associated with uPAR/LFA-1 complexes, any requirement for GPI-anchored glycoproteins, or inhibition by beta-glucan. A single CD11b lectin site for beta-glucan and uPAR was suggested because the binding of either beta-glucan or uPAR to Mac-1/CR3 selectively masked two CD11b epitopes adjacent to the transmembrane domain. Moreover, treatment with phosphatidylinositol-specific phospholipase C that removed GPI-anchored proteins increased CD11b-specific binding of (125)I-labeled beta-glucan by 3-fold and this was reversed with soluble recombinant uPAR. Conversely, neutrophil activation for generation of Mac-1/CR3/uPAR complexes inhibited CD11b-dependent binding of (125)I-labeled beta-glucan by 75%. These data indicate that the same lectin domain within CD11b regulates both the cytotoxic and adhesion functions of Mac-1/CR3.

Animals↗

PubMed2002

Roles of mutation and recombination in the evolution of protein thermodynamics.

We present a comprehensive study of the evolutionary origin of the thermodynamic behavior of proteins. With the use of a simplified model, we exhaustively enumerate the space of all sequences and the space of all structures, simulate the evolutionary relationship between sequences and structures, and characterize the steady-state sequence distribution for all structures in terms of several thermodynamic variables. We assess the effects of two major forces of evolution: mutation and recombination. Three simplifications are made. First, a two-dimensional lattice model is used to represent protein sequences and structures. Second, proteins undergo neutral evolution so that the fitness landscape has a flat allowed region inside of which all sequences are equally fit. Third, we ignore otherwise important factors such as finite population size and evolutionary time. Two scenarios emerge from our study. The first occurs when evolution is dominated by mutation events. Even though the prototype sequence that is most mutationally robust is preferred by evolution, the preference is not strong enough to offset the huge size of sequence space. Most native sequences are located near the boundary of the fitness region and are marginally compatible with the native structure. The second scenario occurs when evolution is dominated by recombination events. Now evolutionary preference for prototype sequence is strong enough to overcome the size of sequence space so that most native sequences are located near the center of sequence-structure compatibility. We conclude that the relative frequency of mutation and recombination events is a major determinant of how optimal protein sequences are for their structures.

Evolution, Molecular↗

PubMed2002

Mutant DNA-binding domain of HSF4 is associated with autosomal dominant lamellar and Marner cataract.

Congenital cataracts cause 10-30% of all blindness in children, with one-third of cases estimated to have a genetic cause. Lamellar cataract is the most common type of infantile cataract. We carried out whole-genome linkage analysis of Chinese individuals with lamellar cataract, and found that the disorder is associated with inheritance of a 5.11-cM locus on chromosome 16. This locus coincides with one previously described for Marner cataract. We screened individuals of three Chinese families for mutations in HSF4 (a gene at this locus that encodes heat-shock transcription factor 4) and discovered that in each family, a distinct missense mutation, predicted to affect the DNA-binding domain of the protein, segregates with the disorder. We also discovered an association between a missense mutation and Marner cataract in an extensive Danish family. We suggest that HSF4 is critical to lens development.

Amino Acid Sequence↗

PubMed2002

A draft sequence of the rice genome (Oryza sativa L. ssp. japonica).

The genome of the japonica subspecies of rice, an important cereal and model monocot, was sequenced and assembled by whole-genome shotgun sequencing. The assembled sequence covers 93% of the 420-megabase genome. Gene predictions on the assembled sequence suggest that the genome contains 32,000 to 50,000 genes. Homologs of 98% of the known maize, wheat, and barley proteins are found in rice. Synteny and gene homology between rice and the other cereal genomes are extensive, whereas synteny with Arabidopsis is limited. Assignment of candidate rice orthologs to Arabidopsis genes is possible in many cases. The rice genome sequence provides a foundation for the improvement of cereals, our most important crops.

Arabidopsis↗