Biomedical subjects

Ting Chen

Publications and source records attributed to Ting Chen.

At least 19 recordsLinked to original sources

PubMed2025

Microbe-induced gene silencing of fungal gene confers efficient resistance against Fusarium graminearum in maize.

UNLABELLED: Small RNAs (sRNAs), the main effectors of RNA interference (or RNA silencing, RNAi), mediate cell-autonomous and non-cell-autonomous gene silencing. The discoveries of trans-kingdom RNAi and interspecies RNAi have accelerated the development of RNAi-based crop protection technologies. Recently, based on interspecies RNAi, a practical technology termed microbe-induced gene silencing (MIGS) without the need of host genetic modification is developed for crop protection against Verticillium dahliae and Fusarium oxysporum in cotton and rice plants. In this study, we utilized MIGS technology to protect maize against Fusarium graminearum, which is responsible for maize stalk rot. An RNAi-engineered Trichoderma harzianum strain, Th-FgPmt2i, was exploited to generate double-stranded RNAs (dsRNAs) to trigger the silencing of the FgPTM2 gene. Our data verify that sRNAs generated from Th-FgPmt2i can silence the FgPMT2 gene via translational inhibition in F. graminearum. We further demonstrated that Th-FgPmt2i has a stronger capacity than does the T. harzianum chassis for protection of maize against F. graminearum. Coupled with our studies on crop protection against V. dahliae and F. oxysporum, our findings reveal that MIGS can be exploited to protect various crops against distinct fungal pathogens and has extensive applicability. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42994-025-00212-9.

Fusarium graminearum↗

PubMed2024

Proteome analysis provides insights into sex differences in Holothuria Scabra.

Sex-determining mechanism is still ambiguous for sea cucumber Holothuria scabra which only manifests gonochorism in gonad. In this study, proteomic analysis was employed to delineate sex-related proteins and genes in gonads of H. scabra, subsequently validated through Quantitative real-time polymerase chain reaction (qRT-PCR). A total of 5,313 proteins were identified via proteome sequencing. Among these, 817 proteins exhibited expression in both the ovary and testis, with 445 proteins displaying up-regulation and 372 proteins showing down-regulation (ovary vs testis). Furthermore, 136 and 69 proteins were identified as ovary-specific and testis-specific Differentially Abundant Proteins (DAPs), respectively. And 9 DAP coding genes which play crucial role in ovary and testis were verified by qRT-PCR. Notably, 24 ovary-bias proteins enriched in ribosome pathway strongly indicated the crucial role of ribosome in ovary. This study serves to furnish novel evidence pertaining to sex differences in H. scabra.

Animals↗

PubMed2007

Absorption and excretion of luteolin and apigenin in rats after oral administration of Chrysanthemum morifolium extract.

Chrysanthemum morifolium extract (CME) has the protective effect on cardiovascular diseases. Luteolin and apigenin are two major bioactive components in vivo when CME is orally administrated to experimental animal. The present paper shows the study of the absorption and excretion of luteolin and apigenin in rats after a single oral dose of CME (200 mg/kg). The levels of luteolin and apigenin in plasma, urine, feces, and bile were measured by HPLC after deconjugation with hydrochloric acid or beta-glucuronidase/sulfatase. The results showed that the plasma concentrations of luteolin and apigenin reached the highest peak level at 1.1 and 3.9 h after dosing, respectively. The area under the concentration-time curves (AUC) for luteolin and apigenin were 23.03 and 237.6 microg h mL-1, respectively. The total recovery of the dose was 37.9% (6.6% in urine; 31.3% in feces) for luteolin and 45.2% (16.6% in urine; 28.6% in feces) for apigenin. The cumulative luteolin and apigenin excreted in the bile was 2.05% and 6.34% of the dose, respectively. All of the results suggest apigenin may be absorbed more efficiently than luteolin in CME in rats, and both luteolin and apigenin have a slow elimination phase, with a quick absorption, so a possible accumulation of the two flavonoids in the body can be hypothesized.

Absorption↗

PubMed2007

Enhanced hydroxylation of imidacloprid by Stenotrophomonas maltophilia upon addition of sucrose.

Sucrose's ability to promote the hydroxylation of imidacloprid (IMI) by bacterium Stenotrophomonas maltophilia strain CGMCC 1.1788 was examined. Both growing culture and resting cells could transform IMI into 5-hydroxy IMI. Adding 2% sucrose to the growing culture transformation broth and 5% sucrose to the resting cell transformation broth resulted in biotransformation yields, respectively, 2.5 and 9 times greater than without sucrose. In the growing culture transformation, sucrose increased biomass, which led to enhance hydroxylation of IMI. In the resting cell transformation, sucrose was used not as a carbon source but as an energy source for cofactor regeneration for hydroxylation of IMI. The hydroxylation activity of IMI was promoted eightfold by adding reduced nicotinamide adenine dinucleotide (NADH) to the cell-free extract. The hydroxylation of IMI was significantly inhibited by P450 inhibitor piperonyl butoxide. It seems that the hydroxylation of IMI by S. maltophilia CGMCC 1.1788 might proceed through a system by cooperating with P450 enzyme.

Culture Techniques↗

PubMed2007

A precise packing sequence for self-assembled convex structures.

Molecular simulations of the self-assembly of cone-shaped particles with specific, attractive interactions are performed. Upon cooling from random initial conditions, we find that the cones self-assemble into clusters and that clusters comprised of particular numbers of cones (e.g., 4-17, 20, 27, 32, and 42) have a unique and precisely packed structure that is robust over a range of cone angles. These precise clusters form a sequence of structures at specific cluster sizes (a "precise packing sequence") that for small sizes is identical to that observed in evaporation-driven assembly of colloidal spheres. We further show that this sequence is reproduced and extended in simulations of two simple models of spheres self-assembling from random initial conditions subject to convexity constraints, including an initial spherical convexity constraint for moderate- and large-sized clusters. This sequence contains six of the most common virus capsid structures obtained in vivo, including large chiral clusters and a cluster that may correspond to several non-icosahedral, spherical virus capsids obtained in vivo. Our findings suggest that this precise packing sequence results from free energy minimization subject to convexity constraints and is applicable to a broad range of assembly processes.

Capsid↗

PubMed2006

In vitro anti-tumor immune response induced by dendritic cells transfected with hTERT recombinant adenovirus.

Transduction with recombinant, replication-defective adenoviral (Ad) vectors encoding a transgene is an efficient method for gene transfer into human dendritic cells (DC). Several studies have demonstrated that epitopes of the human telomerase reverse transcriptase gene (hTERT) can produce CTLs specific for malignant tumors. In this study, we constructed an hTERT recombinant adenovirus (rAd-hTERT) using DNA recombination. We found that human dendritic cells transduced with rAd-hTERT could effectively induce hTERT-specific cytotoxic T lymphocytes (CTLs) in vitro against various tumor cell lines, which were hTERT-positive and HLA-A2 matched. We also found that these hTERT-specific CTLs could not lyse autologous lymphocytes with low telomerase activity. Further studies revealed that rAd-hTERT transduced DCs could increase secretion of IFN-gamma by effector cells when they were co-cultured with hTERT-positive and HLA-A2 matched tumor cell lines. These data suggest that an hTERT vaccine can induce anti-tumor immunity against various tumor cells expressing hTERT in a HLA-A2-restricted fashion in vitro. The transduction of DCs with rAd-hTERT offers a great opportunity in cancer immunotherapy.

Adenoviridae↗

PubMed2006

Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy.

BACKGROUND: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have been developed for predicting potential effects of amino acid substitutions using sequence, three-dimensional structural, and evolutionary properties of proteins, the applications are limited by the complication of the features and the availability of protein structural information. Another limitation is that the prediction results are hard to be interpreted with physicochemical principles and biological knowledge. RESULTS: To overcome these limitations, we proposed a novel feature set using physicochemical properties of amino acids, evolutionary profiles of proteins, and protein sequence information. We applied the support vector machine and the random forest with the feature set to experimental amino acid substitutions occurring in the E. coli lac repressor and the bacteriophage T4 lysozyme, as well as to annotated amino acid substitutions occurring in a wide range of human proteins. The results showed that the proposed feature set was superior to the existing ones. To explore physicochemical principles behind amino acid substitutions, we designed a simulated annealing bump hunting strategy to automatically extract interpretable rules for amino acid substitutions. We applied the strategy to annotated human amino acid substitutions and successfully extracted several rules which were either consistent with current biological knowledge or providing new insights for the understanding of amino acid substitutions. When applied to unclassified data, these rules could cover a large portion of samples, and most of the covered samples showed good agreement with predictions made by either the support vector machine or the random forest. CONCLUSION: The prediction methods using the proposed feature set can achieve larger AUC (the area under the ROC curve), smaller BER (the balanced error rate), and larger MCC (the Matthews' correlation coefficient) than those using the published feature sets, suggesting that our feature set is superior to the existing ones. The rules extracted by the simulated annealing bump hunting strategy have comparable coverage and accuracy but much better interpretability as those extracted by the patient rule induction method (PRIM), revealing that the strategy is more effective in inducing interpretable rules.

Amino Acid Sequence↗

PubMed2006

Feedback control of MKP-1 expression by p38.

Mitogen-activated protein (MAP) kinases play a critical role in innate immune responses to microbial infection through eliciting the biosynthesis of proinflammatory cytokines. MAP phosphatases (MKP)-1 is an archetypical member of the dual-specificity phosphatase family that deactivates MAP kinases. Induction of MKP-1 has been implicated in attenuating the lipopolysaccharide (LPS) and Peptidoglycan (PGN) responses, but how the expression of the MKP-1 is regulated is still not fully understood. Here, we show that inhibition of p38 MAP kinase by specific inhibitor SB 203580 or RNA interference (RNAi) markedly reduced the expression of MKP-1 in LPS or PGN-treated macrophages, which is correlated with prolonged activation of p38 and JNK. Depletion of MAPKAP kinase 2 (MK2), a downstream substrate of p38, by RNAi also inhibited the expression of MKP-1. The mRNA level of MKP-1 is not affected by inhibition of p38, but the expression of MKP-1 is inhibited by treatment of cycloheximide. Thus, p38 MAPK plays a critical role in mediating expression of MKP-1 at a post-transcriptional level. Furthermore, inhibition of p38 by SB 203580 prevented the expression of MKP-1 in LPS-tolerized macrophages, restored the activation of MAP kinases after LPS restimulation. These results indicate a critical role of p38-MK2-dependent induction of MKP-1 in innate immune responses.

Animals↗

PubMed2006

Enlargement of gold nanoparticles on the surface of a self-assembled monolayer modified electrode: a mode in biosensor design.

Gold nanoparticle (Au-NP) seeds were adsorbed onto the surface of a self-assembled monolayer (SAM)-modified electrode. With the treatment of this modified electrode by Au-NPs growth solution containing different concentrations of H2O2 or cholesterol along with cholesterol oxidase (ChOx), the Au-NP seeds on the electrode surface were enlarged in varying degrees. As a result, the peak currents in corresponding cyclic voltammograms were inversely proportional to the concentration of H2O2 or cholesterol. ChOx was also further modified onto the surface of Au/SAM/Au-NP electrode to prepare Au/SAM/Au-NP/ChOx electrode. Using the enzyme-modified electrode to detect cholesterol, which also utilized the enlargement of the NPs, an extraordinary low detection limit of 5 x 10(-9) M was achieved and two linear dependence ranges of 7.5 x 10(-8)-1 x 10(-6) and 1 x 10(-6)-5 x 10(-5) M were obtained. Consequently, new kinds of H2O2 and cholesterol biosensors could be fabricated.

Biosensing Techniques↗

PubMed2006

An integrative approach for causal gene identification and gene regulatory pathway inference.

MOTIVATION: Gene expression variation can often be linked to certain chromosomal regions and are tightly associated with phenotypic variation such as disease conditions. Inferring the causal genes for the expression variation is of great importance but rather challenging as the linked region generally contains multiple genes. Even when a single candidate gene is proposed, the underlying biological mechanism by which the regulation is enforced remains unknown. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. RESULTS: We propose a new approach which aims at achieving the above objectives by integrating genotype information, gene expression, protein-protein interaction, protein phosphorylation, and transcription factor (TF)-DNA binding information. A network based stochastic algorithm is designed to infer the causal genes and identify the underlying regulatory pathways. We first quantitatively verified our method by a test using data generated by yeast knock-out experiments. Over 40% of inferred causal genes are correct, which is significantly better than 10% by random guess. We then applied our method to a recent genome-wide expression variation study in yeast. We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. New potential gene regulatory pathways are generated and presented as a global network. AVAILABILITY: Source code is available upon request.

Chromosome Mapping↗

PubMed2006

Network motif identification in stochastic networks.

Network motifs have been identified in a wide range of networks across many scientific disciplines and are suggested to be the basic building blocks of most complex networks. Nonetheless, many networks come with intrinsic and/or experimental uncertainties and should be treated as stochastic networks. The building blocks in these networks thus may also have stochastic properties. In this article, we study stochastic network motifs derived from families of mutually similar but not necessarily identical patterns of interconnections. We establish a finite mixture model for stochastic networks and develop an expectation-maximization algorithm for identifying stochastic network motifs. We apply this approach to the transcriptional regulatory networks of Escherichia coli and Saccharomyces cerevisiae, as well as the protein-protein interaction networks of seven species, and identify several stochastic network motifs that are consistent with current biological knowledge.

Animals↗

PubMed2006

An integrated approach to the prediction of domain-domain interactions.

BACKGROUND: The development of high-throughput technologies has produced several large scale protein interaction data sets for multiple species, and significant efforts have been made to analyze the data sets in order to understand protein activities. Considering that the basic units of protein interactions are domain interactions, it is crucial to understand protein interactions at the level of the domains. The availability of many diverse biological data sets provides an opportunity to discover the underlying domain interactions within protein interactions through an integration of these biological data sets. RESULTS: We combine protein interaction data sets from multiple species, molecular sequences, and gene ontology to construct a set of high-confidence domain-domain interactions. First, we propose a new measure, the expected number of interactions for each pair of domains, to score domain interactions based on protein interaction data in one species and show that it has similar performance as the E-value defined by Riley et al. Our new measure is applied to the protein interaction data sets from yeast, worm, fruitfly and humans. Second, information on pairs of domains that coexist in known proteins and on pairs of domains with the same gene ontology function annotations are incorporated to construct a high-confidence set of domain-domain interactions using a Bayesian approach. Finally, we evaluate the set of domain-domain interactions by comparing predicted domain interactions with those defined in iPfam database that were derived based on protein structures. The accuracy of predicted domain interactions are also confirmed by comparing with experimentally obtained domain interactions from H. pylori. As a result, a total of 2,391 high-confidence domain interactions are obtained and these domain interactions are used to unravel detailed protein and domain interactions in several protein complexes. CONCLUSION: Our study shows that integration of multiple biological data sets based on the Bayesian approach provides a reliable framework to predict domain interactions. By integrating multiple data sources, the coverage and accuracy of predicted domain interactions can be significantly increased.

Algorithms↗

PubMed2006

Placenta-derived soluble MHC class I chain-related molecules down-regulate NKG2D receptor on peripheral blood mononuclear cells during human pregnancy: a possible novel immune escape mechanism for fetal survival.

Mammalian pregnancy is an intriguing immunological phenomenon where the semiallogeneic fetus is not rejected. Tolerance toward the fetus involves a number of mechanisms associated with modifications of the immune status of the mother. In this study, we strongly suggest a novel mechanism for fetal evasion of maternal immune attack, based on the engagement and down-regulation of the activating NK cell receptor NKG2D on PBMC by soluble MHC class I chain-related proteins A and B (collectively termed MIC). A similar immune escape pathway was previously described in tumors. We found that MIC mRNA was constitutively expressed by human placenta and could be up-regulated upon heat shock treatment. Our immunomorphologic studies showed that the MIC expression in placenta was restricted to the syncytiotrophoblast. Immunoelectron microscopy revealed a dual MIC expression in the syncytiotrophoblast: on the apical and basal cell membrane and in cytoplasmic vacuoles as MIC-loaded microvesicles/exosomes. Soluble MIC molecules were present at elevated levels in maternal blood throughout normal pregnancy and were released by placental explants in vitro. Simultaneously, the cell surface NKG2D expression on maternal PBMC was down-regulated compared with nonpregnant controls. The soluble MIC molecules in pregnancy serum were able to interact with NKG2D and down-regulate the receptor on PBMC from healthy donors, with the consequent inhibition of the NKG2D-dependent cytotoxic response. These findings suggest a new physiological mechanism of silencing the maternal immune system that promotes fetal allograft immune escape and supports the view of the placenta as an immunoregulatory organ.

Down-Regulation↗

PubMed2006

Further understanding human disease genes by comparing with housekeeping genes and other genes.

BACKGROUND: Several studies have compared various features of heritable disease genes with other so called non-disease genes, but they have yielded some conflicting results. A potential problem in those studies is that the non-disease genes contained a large number of essential genes--genes which are indispensable for humans to survive and reproduce. Since a functional disruption of an essential gene has fatal consequences, it's more reasonable to regard essential genes as extremely severe "disease" genes. Here we perform a comparative study on the features of human essential, disease, and other genes. RESULTS: In the absence of a set of well defined human essential genes, we consider a set of 1,789 ubiquitously expressed human genes (UEHGs), also known as housekeeping genes, as an approximation. We demonstrate that UEHGs are very likely to contain a large proportion of essential genes. We show that the UEHGs, disease genes and other genes are different in their evolutionary conservation rates, DNA coding lengths, gene functions, etc. Our findings systematically confirm that disease genes have an intermediate essentiality which is less than housekeeping genes but greater than other human genes. CONCLUSION: The human genome may contain thousands of essential genes having features which differ significantly from disease and other genes. We propose to classify them as a unique group for comparisons of disease genes with non-disease genes. This new way of classification and comparison enables us to have a clearer understanding of disease genes.

Adolescent↗

PubMed2006

Identification of human liver mitochondrial aldehyde dehydrogenase as a potential target for microcystin-LR.

Microcystins (MCs) are hepatotoxins produced by a variety of freshwater cyanobacteria. The toxicity of these hepatotoxins is a severe health issue for both humans and livestock; MCs have been implicated in the development of liver cancer, necrosis, and even deadly intrahepatic bleeding. Microcystin-LR (MC-LR) is the MC variant most commonly encountered in a contaminated aquatic system. Thus far, MC-LR has only been shown to target the serine/threonine protein phosphatases 1 and 2A (PP1 and PP2A) and it is still unknown whether MC-LR can bind and inhibit any other protein targets inside the cell. To find potential MC-LR targets, we screened a phage display library for peptide ligands that specifically recognize MC-LR. Using these peptide sequences as guides, we performed a series of bioinformatics analyses revealing that MC-LR binds human liver aldehyde dehydrogenase 2 (ALDH2) at residues 447-451. We confirmed MC-LR binding of ALDH2 via automated docking computation, which yielded results matching our experimental and bioinformatics analyses. ALDH2 dysfunction may lead to aldehyde-induced reactive oxygen species (ROS) generation and, in turn, apoptosis. Therefore, ALDH2 could potentially be a target of MC-LR associated with the process of ROS-induced apoptosis. Our current study presents a new approach to the study of interactions of biological molecules by combining phage display technology with computational methods.

Aldehyde Dehydrogenase↗

PubMed2006

PepHMM: a hidden Markov model based scoring function for mass spectrometry database search.

An accurate scoring function for database search is crucial for peptide identification using tandem mass spectrometry. Although many mathematical models have been proposed to score peptides against tandem mass spectra, our method (called PepHMM, http://msms.cmb.usc.edu) is unique in that it combines information on machine accuracy, mass peak intensity, and correlation among ions into a hidden Markov model (HMM). In addition, we develop a method to calculate statistical significance of the HMM scores. We implement the method and test them on two sets of experimental data generated by two different types of mass spectrometers and compare the results with MASCOT and SEQUEST under the same condition. One experimental results show that PepHMM has a much higher accuracy (with 6.5% error rate) than MASCOT (with 17.4% error rate), and the other experimental results show that PepHMM identifies 43 and 31% more correct spectra than SEQUEST and MASCOT, respectively.

Algorithms↗

PubMed2006

Diffusion kernel-based logistic regression models for protein function prediction.

Assigning functions to unknown proteins is one of the most important problems in proteomics. Several approaches have used protein-protein interaction data to predict protein functions. We previously developed a Markov random field (MRF) based method to infer a protein's functions using protein-protein interaction data and the functional annotations of its protein interaction partners. In the original model, only direct interactions were considered and each function was considered separately. In this study, we develop a new model which extends direct interactions to all neighboring proteins, and one function to multiple functions. The goal is to understand a protein's function based on information on all the neighboring proteins in the interaction network. We first developed a novel kernel logistic regression (KLR) method based on diffusion kernels for protein interaction networks. The diffusion kernels provide means to incorporate all neighbors of proteins in the network. Second, we identified a set of functions that are highly correlated with the function of interest, referred to as the correlated functions, using the chi-square test. Third, the correlated functions were incorporated into our new KLR model. Fourth, we extended our model by incorporating multiple biological data sources such as protein domains, protein complexes, and gene expressions by converting them into networks. We showed that the KLR approach of incorporating all protein neighbors significantly improved the accuracy of protein function predictions over the MRF model. The incorporation of multiple data sets also improved prediction accuracy. The prediction accuracy is comparable to another protein function classifier based on the support vector machine (SVM), using a diffusion kernel. The advantages of the KLR model include its simplicity as well as its ability to explore the contribution of neighbors to the functions of proteins of interest.

Databases, Protein↗

PubMed2006

Src tyrosine kinase as a chemotherapeutic target: is there a clinical case?

Src tyrosine kinase was the first protooncogene described. It has been found to be overexpressed and activated in a large number of different cancers. Cellular Src has been shown to activate a number of different effectors that are involved in different aspects of cancer biology such as metastasis, cell cycle regulation and cell survival. Despite this, Src inhibitors have not entered the regular arsenal of chemotherapeutics. This article reviews some of the biology, rationale, in vitro and in vivo preclinical evidence, and some very early clinical trials demonstrating efficacy of Src inhibitors.

Animals↗