{"id":5175,"date":"2020-02-18T15:58:30","date_gmt":"2020-02-18T20:58:30","guid":{"rendered":"https:\/\/biomol.umontreal.ca\/research\/les-professeurs\/knapp-david-ph-d\/"},"modified":"2026-02-01T14:32:22","modified_gmt":"2026-02-01T19:32:22","slug":"knapp-david-ph-d","status":"publish","type":"page","link":"https:\/\/biomol.umontreal.ca\/en\/research\/les-professeurs\/knapp-david-ph-d\/","title":{"rendered":"Knapp, David, Ph.D."},"content":{"rendered":"<h3>Coordonn\u00e9es<\/h3>\n<p>IRIC<br \/>\nPavillon Marcelle-Coutu, 3306-15<br \/>\n<strong>T<\/strong> 514343-6111 #5265<br \/>\ndavid.knapp@umontreal.ca<\/p>\n<hr\/>\n<div class=\"one-half first \">\n<h2>Axes de recherche<\/h2>\n<ul>\n<li>Signalisation intracellulaire<\/li>\n<li>D\u00e9veloppement et diff\u00e9renciation tissulaire<\/li>\n<li>Cellules souches<\/li>\n<li>Bioinformatique<\/li>\n<\/ul>\n<h2>Description de la recherche<\/h2>\n<p>Les identit\u00e9s cellulaires peuvent \u00eatre consid\u00e9r\u00e9es comme un paysage d&#8217;\u00e9tats attracteurs. Dans ce mod\u00e8le, l&#8217;espace total de tous les \u00e9tats mol\u00e9culaires possibles est rythm\u00e9 par un petit nombre d&#8217;\u00e9tats stables (&#8220;\u00e9tats attracteurs&#8221;), d\u00e9finis par des r\u00e9seaux de r\u00e9gulation g\u00e9n\u00e9tique auto-renfor\u00e7ants. Comme la probabilit\u00e9 qu&#8217;une cellule \u00e0 un moment donn\u00e9 existe dans un \u00e9tat mol\u00e9culaire donn\u00e9 est proportionnelle \u00e0 la stabilit\u00e9 de cet \u00e9tat, nous pouvons visualiser l&#8217;espace mol\u00e9culaire comme un paysage de probabilit\u00e9 similaire au concept des paysages de Waddington. Comprendre les r\u00e9seaux associ\u00e9s \u00e0 ces \u00e9tats attracteurs et comment ils changent au cours des transitions identitaires permettrait de manipuler les cellules dans des \u00e9tats avantageux, ou loin des nuisibles. L&#8217;objectif principal de mon programme de recherche est de questionner plusieurs questions li\u00e9es \u00e0 ces concepts: Y a-t-il un seul chemin entre deux \u00e9tats ou y en a-t-il plusieurs? Comment un \u00e9tat de d\u00e9part donn\u00e9 influence-t-il la probabilit\u00e9 de transition et le chemin? Existe-t-il des \u00e9tats attracteurs interm\u00e9diaires communs dans plusieurs transitions?<\/p>\n<p>La reprogrammation cellulaire \/ diff\u00e9renciation directe n\u00e9cessite une perte des caract\u00e9ristiques diff\u00e9renci\u00e9es existantes, suivie de l&#8217;activation d&#8217;un nouveau programme permettant d&#8217;\u00e9tablir la nouvelle identit\u00e9 cellulaire fonctionnelle. Ce processus contient toutes les \u00e9tapes m\u00e9caniques n\u00e9cessaires pour comprendre la d\u00e9termination de l&#8217;identit\u00e9 et repr\u00e9sente donc un mod\u00e8le id\u00e9al pour comprendre la base mol\u00e9culaire de l&#8217;identit\u00e9 cellulaire. Nous utilisons une combinaison de techniques analytiques monocellulaires et de circuits g\u00e9n\u00e9tiques synth\u00e9tiques pour manipuler les d\u00e9terminants mol\u00e9culaires de l&#8217;identit\u00e9 cellulaire et mesurer les effets de ces perturbations. Les connaissances acquises gr\u00e2ce \u00e0 ces \u00e9tudes am\u00e9lioreront notre capacit\u00e9 \u00e0 produire des types de cellules th\u00e9rapeutiquement pertinents, \u00e0 mieux comprendre comment l&#8217;identit\u00e9 cellulaire peut \u00eatre perturb\u00e9e lors de l&#8217;oncogen\u00e8se et \u00e0 identifier de nouvelles cibles pour une intervention th\u00e9rapeutique.<\/p>\n<\/div>\n<div class=\"one-half  \">\n<h2>Research axis<\/h2>\n<ul>\n<li>Intracellular Signaling<\/li>\n<li>Tissue Development and Differentiation<\/li>\n<li>Stem Cells<\/li>\n<li>Bioinformatics<\/li>\n<\/ul>\n<h2>Research description<\/h2>\n<p>Cellular identities can be thought of as a landscape of attractor states. In this model, the total space of all possible molecular states is punctuated by a small number of stable states (\u2018attractor states\u2019), defined by self-reinforcing gene regulatory networks. As the probability of a cell at a given time existing in a given molecular state will be proportional to the stability of that state, one can visualize the molecular space as a probability landscape similar to the concept of Waddington landscapes. Understanding the networks associated with these attractor states and how they change during identity transitions would enable the manipulation of cells into advantageous states, or away from harmful ones. The overarching goal of my research program is to interrogate several questions tied to these concepts: Is there just one path between two states or are there many? How does a given starting state influence transition probability and path? Are there common intermediate attractor states in multiple transitions?<\/p>\n<p>Cellular reprogramming\/direct differentiation requires a loss of existing differentiated characteristics, followed by the activation of a new program allowing the establishment of the new functional cell identity. This process contains all of the mechanistic steps needed to understand identity determination, and thus represents an ideal model for understanding the molecular basis of cell identity. We use a combination of single-cell analytical techniques together with synthetic gene circuits to manipulate the molecular determinants of cell identity and measure the effects of these perturbations. Knowledge gained from these studies will improve our ability to produce therapeutically relevant cell types, gain insight into how cell identity may be disrupted in oncogenesis, and identify new targets for therapeutic intervention.<\/p>\n<\/div>\n<hr\/>\n<h3>Publications<\/h3>\n<ul>\n<li>Knapp, D.J.H.F., Michaels, Y.S., Jamilly, M., Ferry, Q.R.V., Barbosa, H., Milne, T.A., and Fulga, T.A. (2019). Decoupling tRNA promoter and processing activities enables specific Pol-II Cas9 guide RNA expression. Nature Communications <em>10<\/em>, 1490.<\/li>\n<li>Knapp, D.J.H.F., Hammond, C.A., Wang, F., Aghaeepour, N., Miller, P.H., Beer, P.A., Pellacani, D., VanInsberghe, M., Hansen, C., Bendall, S.C., et al. (2019). A topological view of human CD34+ cell state trajectories from integrated single-cell output and proteomic data. Blood <em>133<\/em>, 927\u2013939.<\/li>\n<li>Knapp, D.J.H.F., Hammond, C.A., Hui, T., van Loenhout, M.T.J., Wang, F., Aghaeepour, N., Miller, P.H., Moksa, M., Rabu, G.M., Beer, P.A., et al. (2018). Single-cell analysis identifies a CD33+ subset of human cord blood cells with high regenerative potential. Nat. Cell Biol. <em>20<\/em>, 710\u2013720.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Coordonn\u00e9es IRIC Pavillon Marcelle-Coutu, 3306-15 T 514343-6111 #5265 david.knapp@umontreal.ca Publications Knapp, D.J.H.F., Michaels, Y.S., Jamilly, M., Ferry, Q.R.V., Barbosa, H., Milne, T.A., and Fulga, T.A. (2019). Decoupling tRNA promoter and [&hellip;]<\/p>\n","protected":false},"author":216,"featured_media":0,"parent":3557,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-5175","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Knapp, David, Ph.D. - Programmes de biologie mol\u00e9culaire<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/biomol.umontreal.ca\/en\/research\/les-professeurs\/knapp-david-ph-d\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Knapp, David, Ph.D. - Programmes de biologie mol\u00e9culaire\" \/>\n<meta property=\"og:description\" content=\"Coordonn\u00e9es IRIC Pavillon Marcelle-Coutu, 3306-15 T 514343-6111 #5265 david.knapp@umontreal.ca Publications Knapp, D.J.H.F., Michaels, Y.S., Jamilly, M., Ferry, Q.R.V., Barbosa, H., Milne, T.A., and Fulga, T.A. 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