Publications by authors named "Steven Haney"

The discovery and use of fluorescent proteins revolutionized cell biology by allowing the visualization of proteins in living cells. Advances in fluorescent proteins, primarily through genetic engineering, have enabled more advanced analyses, including Förster resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy (FLIM) and the development of genetically encoded fluorescent biosensors. These fluorescence protein-based sensors are highly effective in cells grown in monolayer cultures.

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Screening arrayed libraries of reagents, particularly small molecules began as a vehicle for drug discovery, but the in last few years it has become a cornerstone of biological investigation, joining RNAi and CRISPR as methods for elucidating functional relationships that could not be anticipated, and illustrating the mechanisms behind basic and disease biology, and therapeutic resistance. However, these approaches share some common challenges, especially with respect to specificity or selectivity of the reagents as they are scaled to large protein families or the genome. High-content screening (HCS) has emerged as an important complement to screening, mostly the result of a wide array of specific molecular events, such as protein kinase and transcription factor activation, morphological changes associated with stem cell differentiation or the epithelial-mesenchymal transition of cancer cells.

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Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow.

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When investigators monitor effects on a population of cells following a perturbation, these events rarely occur in a classical normal (or Gaussian) distribution. A normal distribution is, however, explicitly assumed for events within a single well, in which mean values per well are used as an assay metric and, in general, measures of assay robustness, such as the Z' score and the V factor. Such analysis is not possible for many technologies; however, high-content screening (HCS) measures events of individual cells, which are averaged over the well.

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Genome-wide association (GWA) studies have described a large number of new candidate genes that contribute to of Type 2 Diabetes (T2D). In some cases, small clusters of genes are implicated, rather than a single gene, and in all cases, the genetic contribution is not defined through the effects on a specific organ, such as the pancreas or liver. There is a significant need to develop and use human cell-based models to examine the effects these genes may have on glucose regulation.

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Hypoxia induces changes to cancer cells that make them more resistant to treatment. We have looked at signaling pathways that facilitate these changes by screening the human kinome for effects on hypoxic responses in SW480 colon cancer cells. Hits identified in the screen were examined for effects on multiple molecular responses to hypoxia, including the endoplasmic reticulum stress and DNA damage responses in colon, melanoma, and renal cancer lines.

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Small interfering RNAs (siRNAs) are routinely used to reduce mRNA levels for a specific gene with the goal of studying its function. Several studies have demonstrated that siRNAs are not always specific and can have many off-target effects. The 3' UTRs of off-target mRNAs are often enriched in sequences that are complementary to the seed-region of the siRNA.

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Background: Many important biological processes are controlled through cell-cell interactions, including the colonization of metastatic tumor cells and the control of differentiation of stem cells within their niche. Despite the crucial importance of the cellular environment in regulating cellular signaling, in vitro methods for the study of such interactions are difficult and/or indirect.

Methodology/principal Findings: We report on the development of an image-based method for distinguishing two cell types grown in coculture.

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Background: High Content Screening has been shown to improve results of RNAi and other perturbations, however significant intra-sample heterogeneity is common and can complicate some analyses. Single cell cytometry can extract important information from subpopulations within these samples. Such approaches are important for immune cells analyzed by flow cytometry, but have not been broadly available for adherent cells that are critical to the study of solid-tumor cancers and other disease models.

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RNA interference (RNAi) screening for cancer drug target identification has been growing, in both the number of laboratories carrying out screens and in the scale of the screens themselves, from the first screens that were published a few years ago. This growth is directly related to the significant new insights into cancer cell biology that have been defined by relatively few studies. Recently, such screens have moved from general studies of cancer cell function (finding new mechanisms of malignancy and tumor suppression), to screens that explain the clinical problems, such as resistance to chemotherapeutics.

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RNAi screening in mammalian cells has become a valuable method to identify and describe genetic relationships in both basic biology and disease mechanisms. Multiple efforts are underway to standardize how RNAi screening data are reported, including establishing experimental criteria for defining a validated hit from a screen, and the extent to which the primary screening data themselves are reported. These discussions have identified several key areas that require consistency, or at least understanding, before RNAi screening data can be used generally.

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Background: Human mammary epithelial cells (HMEC) overcome two well-characterized genetic and epigenetic barriers as they progress from primary cells to fully immortalized cell lines in vitro. Finite lifespan HMEC overcome an Rb-mediated stress-associated senescence barrier (stasis), and a stringent, telomere-length dependent, barrier (agonescence or crisis, depending on p53 status). HMEC that have overcome the second senescence barrier are immortalized.

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High-content screening (HCS) has been used in late-stage drug discovery for a decade. In the past few years, technological advances have expanded the role of HCS into the early stages of drug discovery, including high-throughput screening and hit-to-lead studies. More recently, computational advances in image analysis and technological advancements in general cell biology have extended the utility of HCS into target validation and basic biological studies, including RNAi screening.

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RNA interference (RNAi) and high-content screening (HCS) are powerful technologies that have converged on the early drug discovery process within the last year. RNAi emerged from basic science, where it has become a standard and accepted method for examining gene function. RNAi has achieved this level of recognition because it is a robust technology; however, it is not simple to use, and care needs to be taken to manage the sources of artifacts that can occur when using RNAi.

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The development of effective novel therapeutic agents faces many significant challenges, such as demonstrating that a candidate target plays a critical role in disease progression. RNA interference (RNAi) has proven to be a robust and highly scalable technology, and as such, has become an essential method for studying targets in many disease models. High-content screening (HCS) is a platform for quantitatively measuring cellular features such as transcription factor localization.

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The ZipA-FtsZ protein-protein interaction is a potential target for antibacterial therapy. The design and parallel synthesis of a combinatorial library of small molecules, which target the FtsZ binding area on ZipA are described. Compounds were demonstrated to bind to the FtsZ binding domain of ZipA by HSQC NMR and to inhibit cell division in a cell elongation assay.

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Background: Cloning of genes in expression libraries, such as the yeast two-hybrid system (Y2H), is based on the assumption that the loss of target genes is minimal, or at worst, managable. However, the expression of genes or gene fragments that are capable of interacting with E. coli or yeast gene products in these systems has been shown to be growth inhibitory, and therefore these clones are underrepresented (or completely lost) in the amplified library.

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Whole chromosome sequence of prokaryotes has provided the availability of multiple bacterial pathogen sequence data and it has become a widely used tool in the drug discovery process. However the sequence data in itself is merely a starting point for drug discovery of novel antibacterial targets and, eventually, drugs. In order to leverage this large amount of data it is necessary to match an understanding of the microbial physiology of pathogenic bacteria to disease processes and identifying the gene products for which intervention may reduce or eliminate the infectious state.

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