Enhanced yeast one-hybrid screens to identify transcription factor binding to human DNA sequences

Identifying the sets of transcription factors (TFs) that regulate each human gene is a daunting task that requires integrating numerous experimental and computational approaches. One such method is the yeast one-hybrid (Y1H) assay, in which interactions between TFs and DNA regions are tested in the milieu of the yeast nucleus using reporter genes. Y1H assays involve two components: a 'DNA-bait' (e.g., promoters, enhancers, silencers, etc.) and a 'TF-prey,' which can be screened for reporter gene activation. Most published protocols for performing Y1H screens are based on transforming TF-prey libraries or arrays into DNA-bait yeast strains. Here, we describe a pipeline, called enhanced Y1H (eY1H) assays, where TF-DNA interactions are interrogated by mating DNA-bait strains with an arrayed collection of TF-prey strains using a high density array (HDA) robotic platform that allows screening in a 1,536 colony format. This allows for a dramatic increase in throughput (60 DNA-bait sequences against >1,000 TFs takes two weeks per researcher) and reproducibility. We illustrate the different types of expected results by testing human promoter sequences against an array of 1,086 human TFs, as well as examples of issues that can arise during screens and how to troubleshoot them.Accepted manuscrip

Uncovering human transcription factor interactions associated with genetic variants, novel DNA motifs, and repetitive elements using enhanced yeast one-hybrid assays

Identifying transcription factor (TF) binding to noncoding variants, uncharacterized DNA motifs, and repetitive genomic elements has been difficult due to technical and computational challenges. Indeed, current experimental methods such as chromatin immunoprecipitation are capable of only testing one TF at a time and motif prediction algorithms often lead to false positive and false negative predictions. Here, we address these limitations by developing two approaches based on enhanced yeast one-hybrid assays. The first approach allows to interrogate the binding of >1,000 human TFs to single nucleotide variant alleles, short insertions and deletions (indels), and novel DNA motifs; while the second approach allows for the identification of TFs that bind to repetitive DNA elements. Using the former approach, we identified gain of TF interactions to a GG→AA mutation in the TERT promoter and an 18 bp indel in the TAL1 super-enhancer, both of which are associated with cancer, and identified the TFs that bind to three uncharacterized DNA motifs identified by the ENCODE Project in footprinting assays. Using the latter approach, we detected the binding of 75 TFs to the highly repetitive Alu elements. We anticipate that these approaches will expand our capabilities to study genetic variation and under-characterized genomic regions.https://doi.org/10.1101/459305First author draf

Global landscape of mouse and human cytokine transcriptional regulation

Cytokines are cell-to-cell signaling proteins that play a central role in immune development, pathogen responses, and diseases. Cytokines are highly regulated at the transcriptional level by combinations of transcription factors (TFs) that recruit cofactors and the transcriptional machinery. Here, we mined through three decades of studies to generate a comprehensive database, CytReg, reporting 843 and 647 interactions between TFs and cytokine genes, in human and mouse respectively. By integrating CytReg with other functional datasets, we determined general principles governing the transcriptional regulation of cytokine genes. In particular, we show a correlation between TF connectivity and immune phenotype and disease, we discuss the balance between tissue-specific and pathogen-activated TFs regulating each cytokine gene, and cooperativity and plasticity in cytokine regulation. We also illustrate the use of our database as a blueprint to predict TF–disease associations and identify potential TF–cytokine regulatory axes in autoimmune diseases. Finally, we discuss research biases in cytokine regulation studies, and use CytReg to predict novel interactions based on co-expression and motif analyses which we further validated experimentally. Overall, this resource provides a framework for the rational design of future cytokine gene regulation studies.National Institutes of Health (NIH) [R00 GM114296 and R35 GM128625 to J.I.F.B., 5T32HL007501-34 to J.A.S.]; National Science Foundation [NSF-REU BIO-1659605 to M.M.]. Funding for open access charge: NIH [R35 GM128625]. (R00 GM114296 - National Institutes of Health (NIH); R35 GM128625 - National Institutes of Health (NIH); 5T32HL007501-34 - National Institutes of Health (NIH); NSF-REU BIO-1659605 - National Science Foundation; R35 GM128625 - NIH)Published versio

Emotion Regulation in Consumption: Antecedents and Consequences

While people often feel “ruled by their passions,” individuals can and do exert substantial control over their emotional experiences. A growing body of literature in psychology suggests that the various ways emotions are regulated can have considerable impact on both the emotional experience and other psychological processes. Over three essays, this work examines how individuals regulate their emotions, when they are motivated to do so, and why these concepts are important for consumer behavior. In the first essay, I investigate how emotions are managed by looking at one specific emotion regulation strategy: attention deployment. Using experimental methods, I determine that individuals naturally use attention deployment to regulate their emotions, but the effectiveness varies with the emotion being regulated. After establishing attention deployment as a viable emotion regulation strategy, the second essay asks when individuals are motivated to change their emotions. I propose that identities are associated with discrete emotions, and that these associations give rise to emotion profiles that describe appropriate emotional experiences for individuals with that active identity. The studies reported in the second essay establish that social identities have associations to specific emotions, these associations differ between identities, and the emotion-identity relationships lead to outcomes in cognition, affect, motivation, and regulation. Additional experiments demonstrate that individuals engage in emotion regulation to reduce (enhance) their experience of emotions which are inconsistent (consistent) with the identity’s emotion profile. In the third and final essay, I connect emotion regulation and emotion profiles to marketing and consumer outcomes. Four studies show that experiencing emotions consistent with the identity’s emotion profile enhances persuasion, product choice, and consumption—even for identity-unrelated products and advertisements. Ultimately, consequences for the framing and positioning of identity-relevant products are drawn. Across the three essays, I investigate how, when and why emotion regulation processes influence consumer outcomes. From identifying a specific emotion regulation strategy, to introducing the concept of emotion profiles, new insights into the emotion regulation process are provided. These findings suggest that emotion regulation has widespread impact on consumer outcomes, and represents a new viewpoint on how the emotion experience varies by individual

Epitope-Evaluator: an interactive web application to study predicted T-cell epitopes

Multiple immunoinformatic tools have been developed to predict T-cell epitopes from protein amino acid sequences for different major histocompatibility complex (MHC) alleles. These prediction tools output hundreds of potential peptide candidates which require further processing; however, these tools are either not graphical or not friendly for non-programming users. We present Epitope-Evaluator, a web tool developed in the Shiny/R framework to interactively analyze predicted T-cell epitopes. Epitope-Evaluator contains six tools providing the distribution of epitopes across a selected set of MHC alleles, the promiscuity and conservation of epitopes, and their density and location within antigens. Epitope-Evaluator requires as input the fasta file of protein sequences and the output prediction file coming out from any predictor. By choosing different cutoffs and parameters, users can produce several interactive plots and tables that can be downloaded as JPG and text files, respectively. Using Epitope-Evaluator, we found the HLA-B*40, HLA-B*27:05 and HLA-B*07:02 recognized fewer epitopes from the SARS-CoV-2 proteome than other MHC Class I alleles. We also identified shared epitopes between Delta, Omicron, and Wuhan Spike variants as well as variant-specific epitopes. In summary, Epitope-Evaluator removes the programming barrier and provides intuitive tools, allowing a straightforward interpretation and graphical representations that facilitate the selection of candidate epitopes for experimental evaluation. The web server Epitope-Evaluator is available at https://fuxmanlab.shinyapps.io/Epitope-Evaluator/.R35 GM128625 - NIGMS NIH HHSPublished versio

Construcción de estrategia de mitigación y adaptación al cambio climático municipal, caso de estudio Hidalgo, México

El trabajo presenta los elementos más importantes para la integración de un Plan Municipal de mitigación y Adaptación ante el Cambio Climático, bajo un modelo regional que integra las fuentes antropogénicas de emisiones de Gases Efecto Invernadero (GEI), los volúmenes de emisiones, tipo de gas, localización y sector, por lo tanto, se puede evaluar el inventario de gases a nivel local y la línea base. Bajo estos elementos se definen las acciones, su jerarquización y responsabilidades, para así integrar un Plan de intervención y la construcción de la Estrategia de Mitigación de los gases efectos invernadero. Esta estrategia, al integrarla con un modelo de resiliencia se construye la adaptación ante los efectos del cambio climático. Estos planes y acciones son diseñados para su implementación a través de la metodología que construimos y probado en el estado de Hidalgo, en sus regiones geoculturales y sus 84 municipios. La metodología para el desarrollo de una Agenda Nacional de Cambio Climático (CC), desde la base municipal y con modelos sólidos de análisis de la emisión de Gases Efecto Invernadero (GEI) y las fuentes generadoras a nivel local, cuenta con una base jurídica e institucional de gran importancia y en la que México ha confirmado a través de la firma de los convencidos internacionales. El valor de nuestra metodología, se sustenta en la construcción de Sistema de Indicadores Ambientales y focalización del sistema de resiliencia para incidir con certeza sobre las fuentes y actores generadoras de GEI y sus efectos sobre el CC. Esta metodología es la base para la construcción de políticas públicas, por ello parte del diseño del Plan Estatal de Acciones para el Cambio Climático (PEACCH), el cual debe ser guía para las grandes líneas de trabajo, modelar el comportamiento de la temperatura, y definir sus efectos sobre el territorio y la población, las proyecciones del incremento de temperatura, la huella ecológica, las grandes fuentes de emisiones de GEI y el inventario de emisiones. Para el caso de la experiencia en el estado de Hidalgo, se diseñó la Estrategia de Mitigación y Adaptación ante el Cambio Climático en Hidalgo (EEMyACCH), la cual armonizó en forma operativa la legislación sobre cambio climático en Hidalgo, definió las instancias institucionales y construyó la estrategia de mitigación y adaptación por municipios y regiones, tipo de recursos, la focalización de acciones de mayor impacto y la jerarquización actualización del Inventario de GEI, y acompañado de un modelo de riesgo para la definición de la vulnerabilidad que facilite la jerarquización de acciones a nivel regional, municipios y áreas de impacto y la definición de niveles de resiliencia de los Sistemas de vulnerabilidad (S1, S2, S3). Finalmente, estos modelos se integran a un Sistema de Indicadores de Impacto Ambiental que funcionan bajo una plataforma propia y que es la base para la elaboración de acciones de intervención y toma de decisiones, con base a las responsabilidades bien definidas, maximizando los beneficios y sus resultados. Esta experiencia, bajo su propia ruta crítica de diseño de políticas públicas y la experiencia integrada para el estado de Hidalgo, posibilita y da certeza para la construcción de la política pública a nivel municipal y la elaboración de su agenda ambiental nacional

Transcription factor binding to Caenorhabditis elegans first introns reveals lack of redundancy with gene promoters

Gene expression is controlled through the binding of transcription factors (TFs) to regulatory genomic regions. First introns are longer than other introns in multiple eukaryotic species and are under selective constraint. Here we explore the importance of first introns in TF binding in the nematode Caenorhabditis elegans by combining computational predictions and experimentally derived TF-DNA interaction data. We found that first introns of C. elegans genes, particularly those for families enriched in long first introns, are more conserved in length, have more conserved predicted TF interactions and are bound by more TFs than other introns. We detected a significant positive correlation between first intron size and the number of TF interactions obtained from chromatin immunoprecipitation assays or determined by yeast one-hybrid assays. TFs that bind first introns are largely different from those binding promoters, suggesting that the different interactions are complementary rather than redundant. By combining first intron and promoter interactions, we found that genes that share a large fraction of TF interactions are more likely to be co-expressed than when only TF interactions with promoters are considered. Altogether, our data suggest that C. elegans gene regulation may be additive through the combined effects of multiple regulatory regions

El sistema de cohesión social y sus efectos en la tasa de delincuencia

Se describe el comportamiento de la tasa de delincuencia a partir de la cohesión social. Se toma como referencia la teoría general de sistemas y tiene como elemento base el cálculo con geometría analítica, pues a través de esta herramienta matemática pudo predecirse teóricamente que el nivel de cohesión es un factor detonante del dinamismo de la tasa de delincuencia, es decir, "a mayor cohesión social, menor tasa de delincuencia".This article gives a description of the behavior of the crime rate from the social cohesion, by reference to the General Systems Theory and having as a base element calculations with analytical geometry. While using this mathematical tool it was predicted theoretically that the level of cohesion is a trigger factor of the dynamism of the crime rate, so it means that "the greater the social cohesion, the lower the crime rate". (author's abstract