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Yingyao Zhou

Publications and source records attributed to Yingyao Zhou.

At least 19 recordsLinked to original sources

Just-in-time purification: an effective solution for cherry-picking and purifying active compounds from large legacy libraries.

Many companies possess a compound collection consisting of purified compounds and of unpurified products from combinatorial libraries. Using commercial and proprietary compounds as examples, this report provides clear examples of the significant impact purification can have on the activity observed for a compound and highlights the need to retest the purified compounds prior to creating structure-activity relationships. Crude mixtures made with commercial compounds led to an increase in the number of false positives in the SXR-GAL4 assay as compared with their pure and purified counterparts. An examination of proprietary compounds in an HIV assay resulted in the purification of 61 active crude synthetic mixtures. Of these 61 compounds, 32 were 5-fold less active and 2 were 5-fold more active after purification. This report details a semiautomated process developed and implemented for cherry-picking, tracking, and selectively purifying compounds found active in high-throughput screening campaigns.

Chromatography, Liquid↗

A systematic map of genetic variation in Plasmodium falciparum.

Discovering novel genes involved in immune evasion and drug resistance in the human malaria parasite, Plasmodium falciparum, is of critical importance to global health. Such knowledge may assist in the development of new effective vaccines and in the appropriate use of antimalarial drugs. By performing a full-genome scan of allelic variability in 14 field and laboratory strains of P. falciparum, we comprehensively identified approximately 500 genes evolving at higher than neutral rates. The majority of the most variable genes have paralogs within the P. falciparum genome and may be subject to a different evolutionary clock than those without. The group of 211 variable genes without paralogs contains most known immunogens and a few drug targets, consistent with the idea that the human immune system and drug use is driving parasite evolution. We also reveal gene-amplification events including one surrounding pfmdr1, the P. falciparum multidrug-resistance gene, and a previously uncharacterized amplification centered around the P. falciparum GTP cyclohydrolase gene, the first enzyme in the folate biosynthesis pathway. Although GTP cyclohydrolase is not the known target of any current drugs, downstream members of the pathway are targeted by several widely used antimalarials. We speculate that an amplification of the GTP cyclohydrolase enzyme in the folate biosynthesis pathway may increase flux through this pathway and facilitate parasite resistance to antifolate drugs.

ATP-Binding Cassette Transporters↗

Haplotype-based quantitative trait mapping using a clustering algorithm.

BACKGROUND: With the availability of large-scale, high-density single-nucleotide polymorphism (SNP) markers, substantial effort has been made in identifying disease-causing genes using linkage disequilibrium (LD) mapping by haplotype analysis of unrelated individuals. In addition to complex diseases, many continuously distributed quantitative traits are of primary clinical and health significance. However the development of association mapping methods using unrelated individuals for quantitative traits has received relatively less attention. RESULTS: We recently developed an association mapping method for complex diseases by mining the sharing of haplotype segments (i.e., phased genotype pairs) in affected individuals that are rarely present in normal individuals. In this paper, we extend our previous work to address the problem of quantitative trait mapping from unrelated individuals. The method is non-parametric in nature, and statistical significance can be obtained by a permutation test. It can also be incorporated into the one-way ANCOVA (analysis of covariance) framework so that other factors and covariates can be easily incorporated. The effectiveness of the approach is demonstrated by extensive experimental studies using both simulated and real data sets. The results show that our haplotype-based approach is more robust than two statistical methods based on single markers: a single SNP association test (SSA) and the Mann-Whitney U-test (MWU). The algorithm has been incorporated into our existing software package called HapMiner, which is available from our website at http://www.eecs.case.edu/~jxl175/HapMiner.html. CONCLUSION: For QTL (quantitative trait loci) fine mapping, to identify QTNs (quantitative trait nucleotides) with realistic effects (the contribution of each QTN less than 10% of total variance of the trait), large samples sizes (>or= 500) are needed for all the methods. The overall performance of HapMiner is better than that of the other two methods. Its effectiveness further depends on other factors such as recombination rates and the density of typed SNPs. Haplotype-based methods might provide higher power than methods based on a single SNP when using tag SNPs selected from a small number of samples or some other sources (such as HapMap data). Rank-based statistics usually have much lower power, as shown in our study.

Algorithms↗

A small interfering RNA screen for modulators of tumor cell motility identifies MAP4K4 as a promigratory kinase.

Cell motility is a complex biological process, involved in development, inflammation, homeostasis, and pathological processes such as the invasion and metastatic spread of cancer. Here, we describe a genomic screen designed to identify inhibitors of cell migration. A library of 10,996 small interfering RNAs (targeting 5,234 human genes) was screened for their ability to block the migration of a highly motile ovarian carcinoma cell line, SKOV-3, by using a 384-well wound-healing assay coupled with automated microscopy and wound quantification. Two or more small interfering RNAs against four genes, CDK7, DYRK1B, MAP4K4 (NIK/HGK) (MAP4K4, mitogen-activated protein 4 kinase 4), and SCCA-1 (SerpinB3), potently blocked the migration of SKOV-3 cells, concordant with reduced transcript levels. Further studies of the promigratory role of MAP4K4 showed that the knockdown of this transcript inhibited the migration of multiple carcinoma cell lines, indicating a broad role in cell motility and potently suppressed the invasion of SKOV-3 cells in vitro. The effect of MAP4K4 on cellular migration was found to be mediated through c-Jun N-terminal kinase, independent of AP1 activation and downstream transcription. Accordingly, small molecule inhibition of c-Jun N-terminal kinase suppressed SKOV-3 cell migration, underscoring the potential therapeutic utility of mitogen-activated protein kinase pathway inhibition in cancer progression.

Base Sequence↗

An efficient rapid system for profiling the cellular activities of molecular libraries.

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinase-dependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src/abl inhibitor BMS-354825 and exposed the expected side activities for Glivec/STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.

Animals↗

In vivo transcriptome of Plasmodium falciparum reveals overexpression of transcripts that encode surface proteins.

Infections with the human parasite Plasmodium falciparum continue to present a great challenge to global health. Fundamental questions regarding the molecular basis of virulence and immune evasion in P. falciparum have been only partially answered. Because of the parasite's intracellular location and complex life cycle, standard genetic approaches to the study of the pathogenesis of malaria have been limited. The present study presents a novel approach to the identification of the biological processes involved in host-pathogen interactions, one that is based on the analysis of in vivo P. falciparum transcripts. We demonstrate that a sufficient quantity of P. falciparum RNA transcripts can be derived from a small blood sample from infected patients for whole-genome microarray analysis. Overall, excellent correlation was observed between the transcriptomes derived from in vivo samples and in vitro samples with ring-stage P. falciparum 3D7 reference strain. However, gene families that encode surface proteins are overexpressed in vivo. Moreover, this analysis has identified a new family of hypothetical genes that may encode surface variant antigens. Comparative studies of the transcriptomes derived from in vivo samples and in vitro 3D7 samples may identify important strategies used by the pathogen for survival in the human host and highlight, for vaccine development, new candidate antigens that were not previously identified through the use of in vitro cultures.

Adaptation, Physiological↗

The Plasmodium falciparum sexual development transcriptome: a microarray analysis using ontology-based pattern identification.

The sexual stages of malarial parasites are essential for the mosquito transmission of the disease and therefore are the focus of transmission-blocking drug and vaccine development. In order to better understand genes important to the sexual development process, the transcriptomes of high-purity stage I-V Plasmodium falciparum gametocytes were comprehensively profiled using a full-genome high-density oligonucleotide microarray. The interpretation of this transcriptional data was aided by applying a novel knowledge-based data-mining algorithm termed ontology-based pattern identification (OPI) using current information regarding known sexual stage genes as a guide. This analysis resulted in the identification of a sexual development cluster containing 246 genes, of which approximately 75% were hypothetical, exhibiting highly-correlated, gametocyte-specific expression patterns. Inspection of the upstream promoter regions of these 246 genes revealed putative cis-regulatory elements for sexual development transcriptional control mechanisms. Furthermore, OPI analysis was extended using current annotations provided by the Gene Ontology Consortium to identify 380 statistically significant clusters containing genes with expression patterns characteristic of various biological processes, cellular components, and molecular functions. Collectively, these results, available as part of a web-accessible OPI database (http://carrier.gnf.org/publications/Gametocyte), shed light on the components of molecular mechanisms underlying parasite sexual development and other areas of malarial parasite biology.

Animals↗

In silico gene function prediction using ontology-based pattern identification.

MOTIVATION: With the emergence of genome-wide expression profiling data sets, the guilt by association (GBA) principle has been a cornerstone for deriving gene functional interpretations in silico. Given the limited success of traditional methods for producing clusters of genes with great amounts of functional similarity, new data-mining algorithms are required to fully exploit the potential of high-throughput genomic approaches. RESULTS: Ontology-based pattern identification (OPI) is a novel data-mining algorithm that systematically identifies expression patterns that best represent existing knowledge of gene function. Instead of relying on a universal threshold of expression similarity to define functionally related groups of genes, OPI finds the optimal analysis settings that yield gene expression patterns and gene lists that best predict gene function using the principle of GBA. We applied OPI to a publicly available gene expression data set on the life cycle of the malarial parasite Plasmodium falciparum and systematically annotated genes for 320 functional categories based on current Gene Ontology annotations. An ontology-based hierarchical tree of the 320 categories provided a systems-wide biological view of this important malarial parasite.

Algorithms↗

In vivo transcriptional profiling of Plasmodium falciparum.

BACKGROUND: Both host and pathogen factors contribute to disease outcome in Plasmodium falciparum infection. The feasibility of studying the P. falciparum in vivo transcriptome to understand parasite transcriptional response while it resides in the human host is presented. METHODS: A custom made oligonucleotide array with probes based on the P. falciparum 3D7 laboratory strain chromosome 2 sequence was used to detect in vivo P. falciparum transcripts. This study analyzed transcripts from total RNA derived from small blood samples of P. falciparum infected patients and compared the in vivo expression profile to the in vitro cultivated 3D7 strain transcriptome. RESULTS: The data demonstrated that in vivo transcription can be studied from a small blood sample, despite the abundance of human RNA. The in vivo transcriptome is similar to the 3D7 ring stage transcriptome, but there are significant differences in genes encoding a sexual stage antigen and surface proteins. CONCLUSIONS: Whole genome transcription analysis of P. falciparum can be carried out successfully and further studies in selected patient cohorts may provide insight into parasite in vivo biology and defense against host immunity.

Animals↗

A Plasmodium gene family encoding Maurer's cleft membrane proteins: structural properties and expression profiling.

Upon invasion of the erythrocyte cell, the malaria parasite remodels its environment; in particular, it establishes a complex membrane network, which connects the parasitophorous vacuole to the host plasma membrane and is involved in protein transport and trafficking. We have identified a novel subtelomeric gene family in Plasmodium falciparum that encodes 11 transmembrane proteins localized to the Maurer's clefts. Using coimmunoprecipitation and shotgun proteomics, we were able to enrich specifically for these proteins and detect distinct peptides, allowing us to conclude that four to 10 products were present at a given time. Nearly all of the Pfmc-2tm genes are transcribed during the trophozoite stage; this narrow time frame of transcription overlaps with the specific stevor and rif genes that are differentially expressed during the erythrocyte cycle. The description of the structural properties of the proteins led us to manually reannotate published sequences, and to detect potentially homologous gene families in both P. falciparum and Plasmodium yoelii yoelii, where no orthologs were predicted uniquely based on sequence similarity. These basic proteins with two transmembrane domains belong to a larger superfamily, which includes STEVORs and RIFINs.

Amino Acid Sequence↗

Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arrays.

BACKGROUND: To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summary of probe-level expression data for each probe set and compare replicates of these values across conditions using a form of the t-test or rank sum test. Here we propose the use of a statistical method that takes advantage of the built-in redundancy architecture of high-density oligonucleotide arrays. RESULTS: We employ parametric and nonparametric variants of two-way analysis of variance (ANOVA) on probe-level data to account for probe-level variation, and use the false-discovery rate (FDR) to account for simultaneous testing on thousands of genes (multiple testing problem). Using publicly available data sets, we systematically compared the performance of parametric two-way ANOVA and the nonparametric Mack-Skillings test to the t-test and Wilcoxon rank-sum test for detecting differentially expressed genes at varying levels of fold change, concentration, and sample size. Using receiver operating characteristic (ROC) curve comparisons, we observed that two-way methods with FDR control on sample sizes with 2-3 replicates exhibits the same high sensitivity and specificity as a t-test with FDR control on sample sizes with 6-9 replicates in detecting at least two-fold change. CONCLUSIONS: Our results suggest that the two-way ANOVA methods using probe-level data are substantially more powerful tests for detecting differential gene expression than corresponding methods for probe-set level data.

Analysis of Variance↗

Global analysis of transcript and protein levels across the Plasmodium falciparum life cycle.

To investigate the role of post-transcriptional controls in the regulation of protein expression for the malaria parasite, Plasmodium falciparum, we have compared mRNA transcript and protein abundance levels for seven different stages of the parasite life cycle. A moderately high positive relationship between mRNA and protein abundance was observed for these stages; the most common discrepancy was a delay between mRNA and protein accumulation. Potentially post-transcriptionally regulated genes are identified, and families of functionally related genes were observed to share similar patterns of mRNA and protein accumulation.

Animals↗

Discovery of gene function by expression profiling of the malaria parasite life cycle.

The completion of the genome sequence for Plasmodium falciparum, the species responsible for most malaria human deaths, has the potential to reveal hundreds of new drug targets and proteins involved in pathogenesis. However, only approximately 35% of the genes code for proteins with an identifiable function. The absence of routine genetic tools for studying Plasmodium parasites suggests that this number is unlikely to change quickly if conventional serial methods are used to characterize encoded proteins. Here, we use a high-density oligonucleotide array to generate expression profiles of human and mosquito stages of the malaria parasite's life cycle. Genes with highly correlated levels and temporal patterns of expression were often involved in similar functions or cellular processes.

Animals↗

Genetic diversity in yeast assessed with whole-genome oligonucleotide arrays.

The availability of a complete genome sequence allows the detailed study of intraspecies variability. Here we use high-density oligonucleotide arrays to discover 11,115 single-feature polymorphisms (SFPs) existing in one or more of 14 different yeast strains. We use these SFPs to define regions of genetic identity between common laboratory strains of yeast. We assess the genome-wide distribution of genetic variation on the basis of this yeast population. We find that genome variability is biased toward the ends of chromosomes and is more likely to be found in genes with roles in fermentation or in transport. This subtelomeric bias may arise through recombination between nonhomologous sequences because full-gene deletions are more common in these regions than in more central regions of the chromosome.

Chromosome Mapping↗

Algorithms for high-density oligonucleotide array.

As a global gene expression-monitoring tool, high-density oligonucleotide arrays (HDAs), accelerate biological and drug discovery processes. Computational considerations affect several key issues, from array design and accurate gene expression level determination to various aspects of the biological analysis of cell functions and gene networks. This review highlights recent progress in ideas and algorithms that are specific to HDAs. Replacing a large number of specific 'mismatch' oligonucleotides by a small number of general noise control oligonucleotides and using dynamic probe-to-gene mapping were some of the ideas proposed. Several novel mismatch-free probe-to-gene condensation algorithms have demonstrated the ability to take advantage of such designs, and provide higher density and equivalent or better calculation accuracy than previous algorithms. Algorithms to be developed in the future should significantly increase both the quality and quantity of information revealed by a single array; therefore, a single array containing the whole mammalian genome or even multiple genomes could soon become a standard tool.

Algorithms↗

Excess polymorphisms in genes for membrane proteins in Plasmodium falciparum.

The detection of single-nucleotide polymorphisms in pathogenic microorganisms has normally been carried out by trial and error. Here we show that DNA hybridization with high-density oligonucleotide arrays provides rapid and convenient detection of single-nucleotide polymorphisms in Plasmodium falciparum, despite its exceptionally high adenine-thymine (AT) content (82%). A disproportionate number of polymorphisms are found in genes encoding proteins associated with the cell membrane. These genes are targets for only 22% of the oligonucleotide probes but account for 69% of the polymorphisms. Genetic variation is also enriched in subtelomeric regions, which account for 22% of the chromosome but 76% of the polymorphisms.

Animals↗

Match-only integral distribution (MOID) algorithm for high-density oligonucleotide array analysis.

BACKGROUND: High-density oligonucleotide arrays have become a valuable tool for high-throughput gene expression profiling. Increasing the array information density and improving the analysis algorithms are two important computational research topics. RESULTS: A new algorithm, Match-Only Integral Distribution (MOID), was developed to analyze high-density oligonucleotide arrays. Using known data from both spiking experiments and no-change experiments performed with Affymetrix GeneChip arrays, MOID and the Affymetrix algorithm implemented in Microarray Suite 4.0 (MAS4) were compared. While MOID gave similar performance to MAS4 in the spiking experiments, better performance was observed in the no-change experiments.MOID also provides a set of alternative statistical analysis tools to MAS4. There are two main features that distinguish MOID from MAS4. First, MOID uses continuous P values for the likelihood of gene presence, while MAS4 resorts to discrete absolute calls. Secondly, MOID uses heuristic confidence intervals for both gene expression levels and fold change values, while MAS4 categorizes the significance of gene expression level changes into discrete fold change calls. CONCLUSIONS: The results show that by using MOID, Affymetrix GeneChip arrays may need as little as ten probes per gene without compromising analysis accuracy.

Algorithms↗

Monitoring the chromosome 2 intraerythrocytic transcriptome of Plasmodium falciparum using oligonucleotide arrays.

To test the feasibility of using short oligonucleotide probes to monitor transcript levels in Plasmodium falciparum, a microarray was manufactured containing 4,167 (25 base single-stranded) probes derived from the predicted coding region of P. falciparum chromosome 2. RNA samples from three asexual stages (rings, trophozoites, and schizonts) were labeled and hybridized to the arrays. These results were reproducible, and transcripts were detected for 69% of the 210 genes on chromosome 2. In addition, of the 145 expressed genes, 1/3 appeared to be differentially transcribed during the asexual cycle. Some regions of the chromosome appeared to be transcriptionally silent. Results were confirmed by Northern blot analysis and by quantitative reverse transcriptase-polymerase chain reaction. These data validate the use of relatively short 25-mers for monitoring the expression of a genome that is 82% AT rich.

Animals↗