All Publications


  • Towards a wraparound model of surgical care: Expanding out-of-hospital phases and integrating health justice considerations to improve health outcomes. American journal of surgery Mukund, A. X., Lu, A., Asamoah, A., Balakrishnan, K. 2024: 115786

    View details for DOI 10.1016/j.amjsurg.2024.115786

    View details for PubMedID 38871551

  • Teaching transgender cultural competency with standardised patients MEDICAL EDUCATION Mukund, A. X., Jia, J. L., Nedelman, M., Rydel, T. A., Bajra, R., Srinivasan, M., Schillinger, E., Laniakea, B. H. 2024

    View details for DOI 10.1111/medu.15325

    View details for Web of Science ID 001161460300001

    View details for PubMedID 38348701

  • High-throughput functional characterization of combinations of transcriptional activators and repressors. Cell systems Mukund, A. X., Tycko, J., Allen, S. J., Robinson, S. A., Andrews, C., Sinha, J., Ludwig, C. H., Spees, K., Bassik, M. C., Bintu, L. 2023

    Abstract

    Despite growing knowledge of the functions of individual human transcriptional effector domains, much less is understood about how multiple effector domains within the same protein combine to regulate gene expression. Here, we measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. In our assay, weak and moderate activation domains synergize to drive strong gene expression, whereas combining strong activators often results in weaker activation. In contrast, repressors combine linearly and produce full gene silencing, and repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small-molecule drug. Altogether, we outline the basic principles of how effector domains combine to regulate gene expression and demonstrate their value in building precise and flexible synthetic biology tools. A record of this paper's transparent peer review process is included in the supplemental information.

    View details for DOI 10.1016/j.cels.2023.07.001

    View details for PubMedID 37543039

  • Large-scale mapping and mutagenesis of human transcriptional effector domains. Nature DelRosso, N., Tycko, J., Suzuki, P., Andrews, C., Mukund, A., Liongson, I., Ludwig, C., Spees, K., Fordyce, P., Bassik, M. C., Bintu, L. 2023

    Abstract

    Human gene expression is regulated by more than 2,000 transcription factors and chromatin regulators1,2. Effector domains within these proteins can activate or repress transcription. However, for many of these regulators we do not know what type of effector domains they contain, their location in the protein, their activation and repression strengths, and the sequences that are necessary for their functions. Here, we systematically measure the effector activity of more than 100,000 protein fragments tiling across most chromatin regulators and transcription factors in human cells (2,047 proteins). By testing the effect they have when recruited at reporter genes, we annotate 374 activation domains and 715 repression domains, roughly 80% of which are new and have not been previously annotated3-5. Rational mutagenesis and deletion scans across all the effector domains reveal aromatic and/or leucine residues interspersed with acidic, proline, serine and/or glutamine residues are necessary for activation domain activity. Furthermore, most repression domain sequences contain sites for small ubiquitin-like modifier (SUMO)ylation, short interaction motifs for recruiting corepressors or are structured binding domains for recruiting other repressive proteins. We discover bifunctional domains that can both activate and repress, some of which dynamically split a cell population into high- and low-expression subpopulations. Our systematic annotation and characterization of effector domains provide a rich resource for understanding the function of human transcription factors and chromatin regulators, engineering compact tools for controlling gene expression and refining predictive models of effector domain function.

    View details for DOI 10.1038/s41586-023-05906-y

    View details for PubMedID 37020022

    View details for PubMedCentralID 4494013

  • Dynamic spreading of chromatin-mediated gene silencing and reactivation between neighboring genes in single cells. eLife Lensch, S., Herschl, M. H., Ludwig, C. H., Sinha, J., Hinks, M. M., Mukund, A., Fujimori, T., Bintu, L. 2022; 11

    Abstract

    In mammalian cells genes that are in close proximity can be transcriptionally coupled: silencing or activating one gene can affect its neighbors. Understanding these dynamics is important for natural processes, such as heterochromatin spreading during development and aging, and when designing synthetic gene regulation circuits. Here, we systematically dissect this process in single cells by recruiting and releasing repressive chromatin regulators at dual-gene synthetic reporters, and measuring how fast gene silencing and reactivation spread as a function of intergenic distance and configuration of insulator elements. We find that silencing by KRAB, associated with histone methylation, spreads between two genes within hours, with a time delay that increases with distance. This fast KRAB-mediated spreading is not blocked by the classical cHS4 insulators. Silencing by histone deacetylase HDAC4 of the upstream gene can also facilitate background silencing of the downstream gene by PRC2, but with a days-long delay that does not change with distance. This slower silencing can sometimes be stopped by insulators. Gene reactivation of neighboring genes is also coupled, with strong promoters and insulators determining the order of reactivation. Our data can be described by a model of multi-gene regulation that builds upon previous knowledge of heterochromatin spreading, where both gene silencing and gene reactivation can act at a distance, allowing for coordinated dynamics via chromatin regulator recruitment.

    View details for DOI 10.7554/eLife.75115

    View details for PubMedID 35678392

  • Temporal signaling, population control, and information processing through chromatin-mediated gene regulation. Journal of theoretical biology Mukund, A., Bintu, L. 1800: 110977

    Abstract

    Chromatin regulation is a key pathway cells use to regulate gene expression in response to temporal stimuli, and is becoming widely used as a platform for synthetic biology applications. redHere, we build a mathematical framework for analyzing the response of genetic circuits containing chromatin regulators to temporal signals in mammalian cell populations. Chromatin regulators can silence genes in an all-or-none fashion at the single-cell level, with individual cells stochastically transitioning between active, reversibly silent, and irreversibly silent gene states at constant rates over time. redWe integrate this mode of regulation with classical gene regulatory motifs, such as autoregulatory and incoherent feedforward loops, to determine the types of responses achievable with duration-dependent signaling. We demonstrate that repressive regulators without long-term epigenetic memory can filter out high frequency noise, and as part of an autoregulatory loop can precisely tune the fraction of cells in a population that expresses a gene of interest. redAdditionally, we find that repressive regulators with epigenetic memory can sum up and encode the total duration of their recruitment in the fraction of cells irreversibly silenced and, when included in a feed forward loop, enable perfect adaptation. redLast, we use an information theoretic approach to show that all-or-none stochastic silencing can be used by populations to transmit information reliably and with high fidelity even in very simple genetic circuits. redAltogether, we show that chromatin-mediated gene control enables a repertoire of complex cell population responses to temporal signals and can transmit higher information levels than previously measured in gene regulation.

    View details for DOI 10.1016/j.jtbi.2021.110977

    View details for PubMedID 34919934

  • High-Throughput Discovery and Characterization of Human Transcriptional Effectors. Cell Tycko, J. n., DelRosso, N. n., Hess, G. T., Aradhana, n. n., Banerjee, A. n., Mukund, A. n., Van, M. V., Ego, B. K., Yao, D. n., Spees, K. n., Suzuki, P. n., Marinov, G. K., Kundaje, A. n., Bassik, M. C., Bintu, L. n. 2020

    Abstract

    Thousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit, a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover that Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several domains of unknown function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as ten amino acids. Finally, we report new activator domains, including a divergent KRAB. These results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.

    View details for DOI 10.1016/j.cell.2020.11.024

    View details for PubMedID 33326746

  • OSPREY 3.0: Open-source protein redesign for you, with powerful new features JOURNAL OF COMPUTATIONAL CHEMISTRY Hallen, M. A., Martin, J. W., Ojewole, A., Jou, J. D., Lowegard, A. U., Frenkel, M. S., Gainza, P., Nisonoff, H. M., Mukund, A., Wang, S., Holt, G. T., Zhou, D., Dowd, E., Donald, B. R. 2018; 39 (30): 2494-2507

    Abstract

    We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein-protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software. © 2018 Wiley Periodicals, Inc.

    View details for DOI 10.1002/jcc.25522

    View details for Web of Science ID 000450304900001

    View details for PubMedID 30368845

    View details for PubMedCentralID PMC6391056