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Michael Snyder

Publications and source records attributed to Michael Snyder.

At least 19 recordsLinked to original sources
PubMed2026

A distinct effector B cell population drives autoantibody production in SARS-CoV-2 infection.

Autoantibodies (autoAbs) are linked to mortality and Long COVID, yet their cellular origins remain unclear. We analyzed the INCOV cohort and identified 12 age- and sex-matched participants with varying autoAb abundance and integrated single-cell RNA-seq and ATAC-seq data from B cells, plasma proteomics, proteome-wide autoAb profiling, clinical data, and in vitro assays. AutoAb abundance inversely correlated with neutralizing IgG and declined as infection resolved, paralleling the contraction of atypical memory B cells (AtMs). In vitro, AtMs preferentially differentiated into autoAb-producing antibody-secreting cells upon TLR7/8 stimulation. CD11c+ AtMs (double-negative 2, DN2s) in autoAb-high individuals exhibited increased TLR7 signaling, oxidative stress, and isotype switching, regulated by transcription factors T-bet and XBP1. Integrated genetic and genomic analyses showed that DN2s had the strongest enrichment for autoimmune trait heritability and inferred regulatory effects of autoimmune risk variants among B cell subsets. These findings identify DN2s as key precursors of autoAb-producing cells during SARS-CoV-2 infection.

B cell↗
PubMed2003

ExpressYourself: A modular platform for processing and visualizing microarray data.

DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself.

Algorithms↗
PubMed2003

Protein analysis on a proteomic scale.

The long-term challenge of proteomics is enormous: to define the identities, quantities, structures and functions of complete complements of proteins, and to characterize how these properties vary in different cellular contexts. One critical step in tackling this goal is the generation of sets of clones that express a representative of each protein of a proteome in a useful format, followed by the analysis of these sets on a genome-wide basis. Such studies enable genetic, biochemical and cell biological technologies to be applied on a systematic level, leading to the assignment of biochemical activities, the construction of protein arrays, the identification of interactions, and the localization of proteins within cellular compartments.

Animals↗
PubMed2003

The transcriptional activity of human Chromosome 22.

A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)(+) RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice as many transcribed bases as have been reported previously. Many of the newly discovered expressed fragments were verified by RNA blot analysis and a novel technique called differential hybridization mapping (DHM). Interestingly, a significant fraction of these novel fragments are expressed antisense to previously annotated introns. The coding potential of these novel expressed regions is supported by their sequence conservation in the mouse genome. This study has greatly increased our understanding of the biological information encoded on a human chromosome. To facilitate the dissemination of these results to the scientific community, we have developed a comprehensive Web resource to present the findings of this study and other features of human Chromosome 22 at http://array.mbb.yale.edu/chr22.

Amino Acid Sequence↗
PubMed2003

Protein chip technology.

Microarray technology has become a crucial tool for large-scale and high-throughput biology. It allows fast, easy and parallel detection of thousands of addressable elements in a single experiment. In the past few years, protein microarray technology has shown its great potential in basic research, diagnostics and drug discovery. It has been applied to analyse antibody-antigen, protein-protein, protein-nucleic-acid, protein-lipid and protein-small-molecule interactions, as well as enzyme-substrate interactions. Recent progress in the field of protein chips includes surface chemistry, capture molecule attachment, protein labeling and detection methods, high-throughput protein/antibody production, and applications to analyse entire proteomes.

Protein Array Analysis↗
PubMed2003

Specific protein targeting during cell differentiation: polarized localization of Fus1p during mating depends on Chs5p in Saccharomyces cerevisiae.

In budding yeast, chs5 mutants are defective in chitin synthesis and cell fusion during mating. Chs5p is a late-Golgi protein required for the polarized transport of the chitin synthase Chs3p to the membrane. Here we show that Chs5p is also essential for the polarized targeting of Fus1p, but not of other cell fusion proteins, to the membrane during mating.

Cell Compartmentation↗
PubMed2003

Molecular dissection of a yeast septin: distinct domains are required for septin interaction, localization, and function.

The septins are a family of cytoskeletal proteins present in animal and fungal cells. They were first identified for their essential role in cytokinesis, but more recently, they have been found to play an important role in many cellular processes, including bud site selection, chitin deposition, cell compartmentalization, and exocytosis. Septin proteins self-associate into filamentous structures that, in yeast cells, form a cortical ring at the mother bud neck. Members of the septin family share common structural domains: a GTPase domain in the central region of the protein, a stretch of basic residues at the amino terminus, and a predicted coiled-coil domain at the carboxy terminus. We have studied the role of each domain in the Saccharomyces cerevisiae septin Cdc11 and found that the three domains are responsible for distinct and sometimes overlapping functions. All three domains are important for proper localization and function in cytokinesis and morphogenesis. The basic region was found to bind the phosphoinositides phosphatidylinositol 4-phosphate and phosphatidylinositol 5-phosphate. The coiled-coil domain is important for interaction with Cdc3 and Bem4. The GTPase domain is involved in Cdc11-septin interaction and targeting to the mother bud neck. Surprisingly, GTP binding appears to be dispensable for Cdc11 function, localization, and lipid binding. Thus, we find that septins are multifunctional proteins with specific domains involved in distinct molecular interactions required for assembly, localization, and function within the cell.

Amino Acid Sequence↗
PubMed2003

Recent developments in analytical and functional protein microarrays.

In recent years, the genomes of many different organisms have been fully sequenced and annotated. As a consequence of this information, a number of methods have emerged to study the function of many genes and proteins in parallel. One recent approach for the large-scale analysis of proteins is the use of protein microarrays in which hundreds to thousands of proteins are arrayed and assayed simultaneously. Protein arrays can be used for assessing protein levels and following disease markers, identifying biochemical activities, analyzing post-translational modifications, building interaction networks, and for drug discovery and development. In this review, we discuss the construction of different types of protein arrays, and their numerous and diverse applications.

Antibodies↗
PubMed2002

Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae.

In the yeast Saccharomyces cerevisiae, SBF (Swi4-Swi6 cell cycle box binding factor) and MBF (MluI binding factor) are the major transcription factors regulating the START of the cell cycle, a time just before DNA replication, bud growth initiation, and spindle pole body (SPB) duplication. These two factors bind to the promoters of 235 genes, but bind less than a quarter of the promoters upstream of genes with peak transcript levels at the G1 phase of the cell cycle. Several functional categories, which are known to be crucial for G1/S events, such as SPB duplication/migration and DNA synthesis, are under-represented in the list of SBF and MBF gene targets. SBF binds the promoters of several other transcription factors, including HCM1, PLM2, POG1, TOS4, TOS8, TYE7, YAP5, YHP1, and YOX1. Here, we demonstrate that these factors are targets of SBF using an independent assay. To further elucidate the transcriptional circuitry that regulates the G1-to-S-phase progression, these factors were epitope-tagged and their binding targets were identified by chIp-chip analysis. These factors bind the promoters of genes with roles in G1/S events including DNA replication, bud growth, and spindle pole complex formation, as well as the general activities of mitochondrial function, transcription, and protein synthesis. Although functional overlap exists between these factors and MBF and SBF, each of these factors has distinct functional roles. Most of these factors bind the promoters of other transcription factors known to be cell cycle regulated or known to be important for cell cycle progression and differentiation processes indicating that a complex network of transcription factors coordinates the diverse activities that initiate a new cell cycle.

Binding Sites↗
PubMed2002

A novel mitochondrial protein, Tar1p, is encoded on the antisense strand of the nuclear 25S rDNA.

In eukaryotes, it is widely assumed that genes coding for proteins and structural RNAs do not overlap. Using a transposon-tagging strategy to globally analyze the Saccharomyces cerevisiae genome for expressed genes, we identified multiple insertions in an open reading frame that is contained fully within and transcribed antisense to the 25S rRNA gene in the nuclear rDNA repeat region on Chromosome XII. Expression of this gene, TAR1 (Transcript Antisense to Ribosomal RNA), can be detected at the RNA and protein levels, and the primary sequence of the corresponding 124-amino-acid protein is conserved in several yeast species. Tar1p was found to localize to mitochondria, and overexpression of the protein suppresses the respiration-deficient petite phenotype of a point mutation in mitochondrial RNA polymerase that affects mitochondrial gene expression and mtDNA stability. These findings indicate that coding information for protein and structural RNAs can overlap, raising issues regarding the coevolution of such complex genes, and also suggest that rDNA transcription and mitochondrial function are coordinately regulated in eukaryotic cells.

Amino Acid Sequence↗
PubMed2002

Functional profiling of the Saccharomyces cerevisiae genome.

Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.

Cell Size↗
PubMed2002

Global analysis of gene expression in yeast.

In the past decade, there has been an intense effort to comprehensively catalogue the expressed genes in the yeast Saccharomyces cerevisiae and to determine the absolute and relative abundance of transcript and protein levels under different cellular conditions. Several methods have been developed to monitor gene expression: DNA microarray analysis, Serial Analysis of Gene Expression (SAGE), kinetic RT-PCR and monitoring expression of beta-galactosidase fusion proteins. These techniques have been used to measure transcript and protein abundance in different developmental states and under different environmental stimuli. A wealth of expression data for yeast is now publicly available through several web sites. The expression information that exists has the obvious benefits of providing a better understanding of the gene expression patterns that accompany changes in a yeast cell's environmental and developmental states. This data has also, however, provided clues to unraveling the complicated questions surrounding gene regulation: why and how is gene expression controlled?

Gene Expression Regulation, Fungal↗
PubMed2002

Subcellular localization of the yeast proteome.

Protein localization data are a valuable information resource helpful in elucidating eukaryotic protein function. Here, we report the first proteome-scale analysis of protein localization within any eukaryote. Using directed topoisomerase I-mediated cloning strategies and genome-wide transposon mutagenesis, we have epitope-tagged 60% of the Saccharomyces cerevisiae proteome. By high-throughput immunolocalization of tagged gene products, we have determined the subcellular localization of 2744 yeast proteins. Extrapolating these data through a computational algorithm employing Bayesian formalism, we define the yeast localizome (the subcellular distribution of all 6100 yeast proteins). We estimate the yeast proteome to encompass approximately 5100 soluble proteins and >1000 transmembrane proteins. Our results indicate that 47% of yeast proteins are cytoplasmic, 13% mitochondrial, 13% exocytic (including proteins of the endoplasmic reticulum and secretory vesicles), and 27% nuclear/nucleolar. A subset of nuclear proteins was further analyzed by immunolocalization using surface-spread preparations of meiotic chromosomes. Of these proteins, 38% were found associated with chromosomal DNA. As determined from phenotypic analyses of nuclear proteins, 34% are essential for spore viability--a percentage nearly twice as great as that observed for the proteome as a whole. In total, this study presents experimentally derived localization data for 955 proteins of previously unknown function: nearly half of all functionally uncharacterized proteins in yeast. To facilitate access to these data, we provide a searchable database featuring 2900 fluorescent micrographs at http://ygac.med.yale.edu.

Algorithms↗
PubMed2002

A question of size: the eukaryotic proteome and the problems in defining it.

We discuss the problems in defining the extent of the proteomes for completely sequenced eukaryotic organisms (i.e. the total number of protein-coding sequences), focusing on yeast, worm, fly and human. (i) Six years after completion of its genome sequence, the true size of the yeast proteome is still not defined. New small genes are still being discovered, and a large number of existing annotations are being called into question, with these questionable ORFs (qORFs) comprising up to one-fifth of the 'current' proteome. We discuss these in the context of an ideal genome-annotation strategy that considers the proteome as a rigorously defined subset of all possible coding sequences ('the orfome'). (ii) Despite the greater apparent complexity of the fly (more cells, more complex physiology, longer lifespan), the nematode worm appears to have more genes. To explain this, we compare the annotated proteomes of worm and fly, relating to both genome-annotation and genome evolution issues. (iii) The unexpectedly small size of the gene complement estimated for the complete human genome provoked much public debate about the nature of biological complexity. However, in the first instance, for the human genome, the relationship between gene number and proteome size is far from simple. We survey the current estimates for the numbers of human genes and, from this, we estimate a range for the size of the human proteome. The determination of this is substantially hampered by the unknown extent of the cohort of pseudogenes ('dead' genes), in combination with the prevalence of alternative splicing. (Further information relating to yeast is available at http://genecensus.org/yeast/orfome)

Animals↗
PubMed2002

GATA-1 binding sites mapped in the beta-globin locus by using mammalian chIp-chip analysis.

The expression of the beta-like globin genes is intricately regulated by a series of both general and tissue-restricted transcription factors. The hemapoietic lineage-specific transcription factor GATA-1 is important for erythroid differentiation and has been implicated in regulating the expression of the erythroid-specific genes including the genes of the beta-globin locus. In the human erythroleukemic K562 cell line, only one DNA region has been identified previously as a putative site of GATA-1 interaction by in vivo footprinting studies. We mapped GATA-1 binding throughout the beta-globin locus by using chIp-chip analysis of K562 cells. We found that GATA-1 binds in a region encompassing the HS2 core element, as was previously identified, and an additional region of GATA-1 binding upstream of the gammaG gene. This approach will be of general utility for mapping transcription factor binding sites within the beta-globin locus and throughout the genome.

Animals↗
PubMed2002

A small reservoir of disabled ORFs in the yeast genome and its implications for the dynamics of proteome evolution.

We surveyed the sequenced Saccharomyces cerevisiae genome (strain S288C) comprehensively for open reading frames (ORFs) that could encode full-length proteins but contain obvious mid-sequence disablements (frameshifts or premature stop codons). These pseudogenic features are termed disabled ORFs (dORFs). Using homology to annotated yeast ORFs and non-yeast proteins plus a simple region extension procedure, we have found 183 dORFs. Combined with the 38 existing annotations for potential dORFs, we have a total pool of up to 221 dORFs, corresponding to less than approximately 3% of the proteome. Additionally, we found 20 pairs of annotated ORFs for yeast that could be merged into a single ORF (termed a mORF) by read-through of the intervening stop codon, and may comprise a complete ORF in other yeast strains. Focussing on a core pool of 98 dORFs with a verifying protein homology, we find that most dORFs are substantially decayed, with approximately 90% having two or more disablements, and approximately 60% having four or more. dORFs are much more yeast-proteome specific than live yeast genes (having about half the chance that they are related to a non-yeast protein). They show a dramatically increased density at the telomeres of chromosomes, relative to genes. A microarray study shows that some dORFs are expressed even though they carry multiple disablements, and thus may be more resistant to nonsense-mediated decay. Many of the dORFs may be involved in responding to environmental stresses, as the largest functional groups include growth inhibition, flocculation, and the SRP/TIP1 family. Our results have important implications for proteome evolution. The characteristics of the dORF population suggest the sorts of genes that are likely to fall in and out of usage (and vary in copy number) in a strain-specific way and highlight the role of subtelomeric regions in engendering this diversity. Our results also have important implications for the effects of the [PSI+] prion. The dORFs disabled by only a single stop and the mORFs (together totalling 35) provide an estimate for the extent of the sequence population that can be resurrected readily through the demonstrated ability of the [PSI+] prion to cause nonsense-codon read-through. Also, the dORFs and mORFs that we find have properties (e.g. growth inhibition, flocculation, vanadate resistance, stress response) that are potentially related to the ability of [PSI+] to engender substantial phenotypic variation in yeast strains under different environmental conditions. (See genecensus.org/pseudogene for further information.)

Chromosomes, Fungal↗