Showing papers by "Michael Snyder published in 2006"

Global Analysis of Protein Phosphorylation in Yeast

Abstract: Protein phosphorylation is estimated to affect 30% of the proteome and is a major regulatory mechanism that controls many basic cellular processes. Until recently, our biochemical understanding of protein phosphorylation on a global scale has been extremely limited; only one half of the yeast kinases have known in vivo substrates and the phosphorylating kinase is known for less than 160 phosphoproteins. Here we describe, with the use of proteome chip technology, the in vitro substrates recognized by most yeast protein kinases: we identified over 4,000 phosphorylation events involving 1,325 different proteins. These substrates represent a broad spectrum of different biochemical functions and cellular roles. Distinct sets of substrates were recognized by each protein kinase, including closely related kinases of the protein kinase A family and four cyclin-dependent kinases that vary only in their cyclin subunits. Although many substrates reside in the same cellular compartment or belong to the same functional category as their phosphorylating kinase, many others do not, indicating possible new roles for several kinases. Furthermore, integration of the phosphorylation results with protein-protein interaction and transcription factor binding data revealed novel regulatory modules. Our phosphorylation results have been assembled into a first-generation phosphorylation map for yeast. Because many yeast proteins and pathways are conserved, these results will provide insights into the mechanisms and roles of protein phosphorylation in many eukaryotes.

HTRA1 Promoter Polymorphism in Wet Age-Related Macular Degeneration

Abstract: Age-related macular degeneration (AMD), the most common cause of irreversible vision loss in individuals aged older than 50 years, is classified as either wet (neovascular) or dry (nonneovascular). Inherited variation in the complement factor H gene is a major risk factor for drusen in dry AMD. Here we report that a single-nucleotide polymorphism in the promoter region of HTRA1, a serine protease gene on chromosome 10q26, is a major genetic risk factor for wet AMD. A whole-genome association mapping strategy was applied to a Chinese population, yielding a P value of <10(-11). Individuals with the risk-associated genotype were estimated to have a likelihood of developing wet AMD 10 times that of individuals with the wild-type genotype.

TOS9 regulates white-opaque switching in Candida albicans.

Abstract: In Candida albicans, the a1-2 complex represses white-opaque switching, as well as mating. Based upon the assumption that the a1-2 corepressor complex binds to the gene that regulates white-opaque switching, a chromatin immunoprecipitation-microarray analysis strategy was used to identify 52 genes that bound to the complex. One of these genes, TOS9, exhibited an expression pattern consistent with a “master switch gene.” TOS9 was only expressed in opaque cells, and its gene product, Tos9p, localized to the nucleus. Deletion of the gene blocked cells in the white phase, misexpression in the white phase caused stable mass conversion of cells to the opaque state, and misexpression blocked temperature-induced mass conversion from the opaque state to the white state. A model was developed for the regulation of spontaneous switching between the opaque state and the white state that includes stochastic changes of Tos9p levels above and below a threshold that induce changes in the chromatin state of an as-yet-unidentified switching locus. TOS9 has also been referred to as EAP2 and WOR1.

Target hub proteins serve as master regulators of development in yeast

Abstract: To understand the organization of the transcriptional networks that govern cell differentiation, we have investigated the transcriptional circuitry controlling pseudohyphal development in Saccharomyces cerevisiae. The binding targets of Ste12, Tec1, Sok2, Phd1, Mga1, and Flo8 were globally mapped across the yeast genome. The factors and their targets form a complex binding network, containing patterns characteristic of autoregulation, feedback and feed-forward loops, and cross-talk. Combinatorial binding to intergenic regions was commonly observed, which allowed for the identification of a novel binding association between Mga1 and Flo8, in which Mga1 requires Flo8 for binding to promoter regions. Further analysis of the network showed that the promoters of MGA1 and PHD1 were bound by all of the factors used in this study, identifying them as key target hubs. Overexpression of either of these two proteins specifically induced pseudohyphal growth under noninducing conditions, highlighting them as master regulators of the system. Our results indicate that target hubs can serve as master regulators whose activity is sufficient for the induction of complex developmental responses and therefore represent important regulatory nodes in biological networks.

High-resolution mapping of DNA copy alterations in human chromosome 22 using high-density tiling oligonucleotide arrays

Abstract: Deletions and amplifications of the human genomic sequence (copy number polymorphisms) are the cause of numerous diseases and a potential cause of phenotypic variation in the normal population. Comparative genomic hybridization (CGH) has been developed as a useful tool for detecting alterations in DNA copy number that involve blocks of DNA several kilobases or larger in size. We have developed high-resolution CGH (HR-CGH) to detect accurately and with relatively little bias the presence and extent of chromosomal aberrations in human DNA. Maskless array synthesis was used to construct arrays containing 385,000 oligonucleotides with isothermal probes of 45–85 bp in length; arrays tiling the β-globin locus and chromosome 22q were prepared. Arrays with a 9-bp tiling path were used to map a 622-bp heterozygous deletion in the β-globin locus. Arrays with an 85-bp tiling path were used to analyze DNA from patients with copy number changes in the pericentromeric region of chromosome 22q. Heterozygous deletions and duplications as well as partial triploidies and partial tetraploidies of portions of chromosome 22q were mapped with high resolution (typically up to 200 bp) in each patient, and the precise breakpoints of two deletions were confirmed by DNA sequencing. Additional peaks potentially corresponding to known and novel additional CNPs were also observed. Our results demonstrate that HR-CGH allows the detection of copy number changes in the human genome at an unprecedented level of resolution.

Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray

Abstract: To monitor severe acute respiratory syndrome (SARS) infection, a coronavirus protein microarray that harbors proteins from SARS coronavirus (SARS-CoV) and five additional coronaviruses was constructed These microarrays were used to screen ≈400 Canadian sera from the SARS outbreak, including samples from confirmed SARS-CoV cases, respiratory illness patients, and healthcare professionals A computer algorithm that uses multiple classifiers to predict samples from SARS patients was developed and used to predict 206 sera from Chinese fever patients The test assigned patients into two distinct groups: those with antibodies to SARS-CoV and those without The microarray also identified patients with sera reactive against other coronavirus proteins Our results correlated well with an indirect immunofluorescence test and demonstrated that viral infection can be monitored for many months after infection We show that protein microarrays can serve as a rapid, sensitive, and simple tool for large-scale identification of viral-specific antibodies in sera

Predicting essential genes in fungal genomes.

Abstract: Essential genes are required for an organism’s viability, and the ability to identify these genes in pathogens is crucial to directed drug development. Predicting essential genes through computational methods is appealing because it circumvents expensive and difficult experimental screens. Most such prediction is based on homology mapping to experimentally verified essential genes in model organisms. We present here a different approach, one that relies exclusively on sequence features of a gene to estimate essentiality and offers a promising way to identify essential genes in unstudied or uncultured organisms. We identified 14 characteristic sequence features potentially associated with essentiality, such as localization signals, codon adaptation, GC content, and overall hydrophobicity. Using the well-characterized baker’s yeast Saccharomyces cerevisiae, we employed a simple Bayesian framework to measure the correlation of each of these features with essentiality. We then employed the 14 features to learn the parameters of a machine learning classifier capable of predicting essential genes. We trained our classifier on known essential genes in S. cerevisiae and applied it to the closely related and relatively unstudied yeast Saccharomyces mikatae. We assessed predictive success in two ways: First, we compared all of our predictions with those generated by homology mapping between these two species. Second, we verified a subset of our predictions with eight in vivo knockouts in S. mikatae, and we present here the first experimentally confirmed essential genes in this species.

Linking DNA-binding proteins to their recognition sequences by using protein microarrays

Abstract: Analyses of whole-genome sequences and experimental data sets have revealed a large number of DNA sequence motifs that are conserved in many species and may be functional. However, methods of sufficient scale to explore the roles of these elements are lacking. We describe the use of protein arrays to identify proteins that bind to DNA sequences of interest. A microarray of 282 known and potential yeast transcription factors was produced and probed with oligonucleotides of evolutionarily conserved sequences that are potentially functional. Transcription factors that bound to specific DNA sequences were identified. One previously uncharacterized DNA-binding protein, Yjl103, was characterized in detail. We defined the binding site for this protein and identified a number of its target genes, many of which are involved in stress response and oxidative phosphorylation. Protein microarrays offer a high-throughput method for determining DNA–protein interactions.

Proteome chips for whole-organism assays.

Abstract: Over the past 5 years, protein-chip technology has emerged as a useful tool for the study of many kinds of protein interactions and biochemical activities. The construction of Saccharomyces cerevisiae whole-proteome arrays has enabled further studies of such interactions in a proteome-wide context. Here, we explore some of the recent advances that have been made at the '-omic' level using protein microarrays.

High-throughput methods of regulatory element discovery.

Abstract: With the number of organisms whose genomes have been sequenced, a vast amount of information concerning the genetic structure of an organism's genome has been collected. However, effective experime...

Design optimization methods for genomic DNA tiling arrays

Abstract: A recent development in microarray research entails the unbiased coverage, or tiling, of genomic DNA for the large-scale identification of transcribed sequences and regulatory elements. A central issue in designing tiling arrays is that of arriving at a single-copy tile path, as significant sequence cross-hybridization can result from the presence of non-unique probes on the array. Due to the fragmentation of genomic DNA caused by the widespread distribution of repetitive elements, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included in the design. This becomes increasingly problematic when considering complex eukaryotic genomes that contain many thousands of interspersed repeats. The general problem of sequence tiling can be framed as finding an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a DNA sequence comprising repetitive and non-repetitive regions. Exact solutions to the tiling problem become computationally infeasible when applied to large genomes, but successive optimizations are developed that allow their practical implementation. These include an efficient method for determining the degree of similarity of many oligonucleotide sequences over large genomes, and two algorithms for finding an optimal tile path composed of longer sequence tiles. The first algorithm, a dynamic programming approach, finds an optimal tiling in linear time and space; the second applies a heuristic search to reduce the space complexity to a constant requirement. A Web resource has also been developed, accessible at http://tiling.gersteinlab.org, to generate optimal tile paths from user-provided DNA sequences.

ProCAT: a data analysis approach for protein microarrays

Abstract: Protein microarrays provide a versatile method for the analysis of many protein biochemical activities. Existing DNA microarray analytical methods do not translate to protein microarrays due to differences between the technologies. Here we report a new approach, ProCAT, which corrects for background bias and spatial artifacts, identifies significant signals, filters nonspecific spots, and normalizes the resulting signal to protein abundance. ProCAT provides a powerful and flexible new approach for analyzing many types of protein microarrays.

Yeast as a Model for Human Disease

Abstract: The sequencing of the human genome promised the identification of disease-causing genes and, subsequently, therapies for those diseases. However, when identifying the genetic basis of a disease, it is not uncommon to discover an abnormal protein whose normal function is unknown. The genetic manipulations required to assign function to genes is often extremely difficult, if not impossible, in human cells. Model organisms have been used to facilitate understanding of gene function because of the ease of genetic manipulations and because many features of eukaryotic physiology have been conserved across phyla. Yeast is a simple eukaryote with a tractable genome, a short generation time, and a large network of researchers who have generated a vast arsenal of research tools. These traits make yeast ideally suited to help reveal the function of genes implicated in human disease.

A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge

Abstract: Motivation: Large-scale tiling array experiments are becoming increasingly common in genomics. In particular, the ENCODE project requires the consistent segmentation of many different tiling array datasets into 'active regions' (e.g. finding transfrags from transcriptional data and putative binding sites from ChIP-chip experiments). Previously, such segmentation was done in an unsupervised fashion mainly based on characteristics of the signal distribution in the tiling array data itself. Here we propose a supervised framework for doing this. It has the advantage of explicitly incorporating validated biological knowledge into the model and allowing for formal training and testing. Methodology: In particular, we use a hidden Markov model (HMM) framework, which is capable of explicitly modeling the dependency between neighboring probes and whose extended version (the generalized HMM) also allows explicit description of state duration density. We introduce a formal definition of the tiling-array analysis problem, and explain how we can use this to describe sampling small genomic regions for experimental validation to build up a gold-standard set for training and testing. We then describe various ideal and practical sampling strategies (e.g. maximizing signal entropy within a selected region versus using gene annotation or known promoters as positives for transcription or ChIP-chip data, respectively). Results: For the practical sampling and training strategies, we show how the size and noise in the validated training data affects the performance of an HMM applied to the ENCODE transcriptional and ChIP-chip experiments. In particular, we show that the HMM framework is able to efficiently process tiling array data as well as or better than previous approaches. For the idealized sampling strategies, we show how we can assess their performance in a simulation framework and how a maximum entropy approach, which samples sub-regions with very different signal intensities, gives the maximally performing gold-standard. This latter result has strong implications for the optimum way medium-scale validation experiments should be carried out to verify the results of the genome-scale tiling array experiments. Supplementary information: The supplementary data are available at http://tiling.gersteinlab.org/hmm/ Contact: mark.gerstein@yale.edu

Genomic analysis of insertion behavior and target specificity of mini-Tn7 and Tn3 transposons in Saccharomyces cerevisiae

Abstract: Transposons are widely employed as tools for gene disruption. Ideally, they should display unbiased insertion behavior, and incorporate readily into any genomic DNA to which they are exposed. However, many transposons preferentially insert at specific nucleotide sequences. It is unclear to what extent such bias affects their usefulness as mutagenesis tools. Here, we examine insertion site specificity and global insertion behavior of two mini-transposons previously used for large-scale gene disruption in Saccharomyces cerevisiae: Tn3 and Tn7. Using an expanded set of insertion data, we confirm that Tn3 displays marked preference for the AT-rich 5 bp consensus site TA[A/T]TA, whereas Tn7 displays negligible target site preference. On a genome level, both transposons display marked non-uniform insertion behavior: certain sites are targeted far more often than expected, and both distributions depart drastically from Poisson. Thus, to compare their insertion behavior on a genome level, we developed a windowed Kolmogorov–Smirnov (K–S) test to analyze transposon insertion distributions in sequence windows of various sizes. We find that when scored in large windows (.300 bp), both Tn3 and Tn7 distributions appear uniform, whereas in smaller windows, Tn7 appears uniform while Tn3 does not. Thus, both transposons are effective tools for gene disruption, but Tn7 does so with less duplication and a more uniform distribution, better approximating the behavior of the ideal transposon.

Extrapolating traditional DNA microarray statistics to tiling and protein microarray technologies.

Abstract: A credit to microarray technology is its broad application. Two experiments--the tiling microarray experiment and the protein microarray experiment--are exemplars of the versatility of the microarrays. With the technology's expanding list of uses, the corresponding bioinformatics must evolve in step. There currently exists a rich literature developing statistical techniques for analyzing traditional gene-centric DNA microarrays, so the first challenge in analyzing the advanced technologies is to identify which of the existing statistical protocols are relevant and where and when revised methods are needed. A second challenge is making these often very technical ideas accessible to the broader microarray community. The aim of this chapter is to present some of the most widely used statistical techniques for normalizing and scoring traditional microarray data and indicate their potential utility for analyzing the newer protein and tiling microarray experiments. In so doing, we will assume little or no prior training in statistics of the reader. Areas covered include background correction, intensity normalization, spatial normalization, and the testing of statistical significance.

Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool

Abstract: Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the ‘chip artifact’. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the ‘plate artifact’. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool— COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at http:// bioinfo.mbb.yale.edu/ExpressYourself/. Together, the two can eliminate most of the common noises in microarray data.

Novel transcribed regions in the human genome

Abstract: We have used genomic tiling arrays to identify transcribed regions throughout the human genome. Analysis of the mapping results of RNA isolated from five cell/tissue types, NB4 cells, NB4 cells treated with retinoic acid (RA), NB4 cells treated with 12-O-tetradecanoylphorbol-13 acetate (TPA), neutrophils, and placenta, throughout the ENCODE region reveals a large number of novel transcribed regions. Interestingly, neutrophils exhibit a great deal of novel expression in several intronic regions. Comparison of the hybridization results of NB4 cells treated with different stimuli relative to untreated cells reveals that many new regions are expressed upon cell differentiation. One such region is the Hox locus, which contains a large number of novel regions expressed in a number of cell types. Analysis of the trinucleotide composition of the novel transcribed regions reveals that it is similar to that of known exons. These results suggest that many of the novel transcribed regions may have a functional role.

Virus protein microarray and uses therefor

Abstract: A virus protein micorarray that can serve as a rapid, sensitive and simple tool for identification of viral specific antibodies in sera, such as a SARS coronavirus protein microarray and methods of using the protein microarray.

BoCaTFBS: a boosted cascade learner to refine the binding sites suggested by ChIP-chip experiments

Abstract: Comprehensive mapping of transcription factor binding sites is essential in postgenomic biology. For this, we propose a mining approach combining noisy data from ChIP (chromatin immunoprecipitation)-chip experiments with known binding site patterns. Our method (BoCaTFBS) uses boosted cascades of classifiers for optimum efficiency, in which components are alternating decision trees; it exploits interpositional correlations; and it explicitly integrates massive negative information from ChIP-chip experiments. We applied BoCaTFBS within the ENCODE project and showed that it outperforms many traditional binding site identification methods (for instance, profiles).

Method for high throughput screening for antibodies and proteins inducing apoptosis

Abstract: High throughput assays used to identify antibodies and proteins that induce cell death are described herein. It is not necessary to identify the antigens the antibodies are reactive with prior to performing the assays. Instead, libraries of antibodies and proteins, including murine, human, humanized, single chain, and synthetic antibodies, are screened using high throughput assays to identify those antibodies and proteins which cause cell death. Standard technology is then used to screen for cell viability. Antibodies and proteins which induce apoptosis preferentially or exclusively of cancer cells are then isolated, characterized, and may be cloned. A method for cloning antibodies and proteins has been developed, which provides means for rapid identification of the antibody or protein and the gene encoding the antibody or protein, based on the presence of a 'bar code' or 'unique sequence.' A method for high throughput production of antibodies to human proteins has also been developed.

Design Issues in Implementing a Portable Sample Tracking and Analysis Research Support (STARS) System for PCR Based Microarray Research

Abstract: Using a PCR (polymerase chain reaction) process to design and produce DNA microarray slides necessitates tracking thousands of samples over a long period of time. In addition, up-to-date information about the samples must be readily available when analyzing experiments done with the resulting microarray slides. A human chromosome 22 project (HC22) at Yale's Center for Excellence in Genomic Sciences (CEGS) used manual sample tracking and handcrafted data files for analyzing the array. The difficulties of manual sample tracking on this project limited the array layout and increased the development time. For subsequent microarray development projects at the Yale CEGS it was decided to build the comprehensive Sample Tracking and Analysis Research Support (STARS) System described herein. The system had to be portable since there are many projects at Yale and elsewhere that require automated microarray sample tracking. Informatics issues in designing and implementing CEGS/STARS are described. The system tracks plates, PCR scoring, microarray slides, and slide printings as core features. CEGS/STARS can support multiple projects and currently there are three sample tracking projects based on the same code and data base design: HC22 and HPR (human promoter) for projects in the Yale CEGS Center, and FLY for projects in the Yale School of Medicine Drosophila Center. In addition to the core tracking features, CEGS/STARS also tracks the biological experiments performed with the resulting microarrays. CEGS/STARS enhances the PCR-based array production protocol with a "cherry picking" algorithm that supports dynamic spot site decisions. Other features include: laboratory robot script generation, lab equipment file generation, automated PCR process scoring, automated links to bioinformatics data analysis tools, annotation and re-annotation of DNA fragments, links to genome databases, and publishing results to GEO. The advanced features of the system are currently being used to produce a human genome promoter array, a drosophila tiling array, and a drosophila promoter array. The source code is available to interested researchers.

Method for High Throughput Screening for Anitbodies and Proteins Inducing Apoptosis

Abstract: High throughput assays used to identify antibodies and proteins that induce cell death are described herein It is not necessary to identify the antigens the antibodies are reactive with prior to performing the assays Instead, libraries of antibodies and proteins, including murine, human, humanized, single chain, and synthetic antibodies, are screened using high throughput assays to identify those antibodies and proteins which cause cell death Standard technology is then used to screen for cell viability Antibodies and proteins which induce apoptosis preferentially or exclusively of cancer cells are then isolated, characterized, and may be cloned A method for cloning antibodies and proteins has been developed, which provides means for rapid identification of the antibody or protein and the gene encoding the antibody or protein, based on the presence of a “bar code” or “unique sequence” A method for high throughput production of antibodies to human proteins has also been developed

Large-Scale Protein Localization in Yeast

Abstract: Publisher Summary Genome-wide protein localization data is helpful in identifying the constituent proteins of each cellular organelle and, potentially, mechanisms by which some of these proteins are regulated. Yeast proteins may be localized through any of the several approaches. By one common strategy, antibodies against a target protein can be used to immunolocalize that protein within a fixed cell. As an alternative to immunolocalization, proteins may be localized by fluorescence microscopy using yeast open reading frame (ORF)-fluorescent protein chimeras. The HA-tagging cassette consists of a sequence encoding three copies of the HA epitope, the S. cerevisiae ADH1 terminator, and the kanMX6 module encoding resistance to G418. Strains containing HA-tagged proteins may be immunolocalized by indirect immunofluorescence using monoclonal antibodies directed against the HA epitope (primary antibody) and the Cy3-conjugated secondary antibody. Immunolocalization in yeast necessitates permeabilization of the cell wall; yeast cells are spheroplasted using the trademarked enzyme preparations glusulase and Zymolyase-100T.