{"id":1131,"date":"2022-08-04T12:07:00","date_gmt":"2022-08-04T12:07:00","guid":{"rendered":"https:\/\/lee-lab.engineering.dartmouth.edu\/?page_id=1131"},"modified":"2022-08-05T19:36:23","modified_gmt":"2022-08-05T19:36:23","slug":"research","status":"publish","type":"page","link":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/research\/","title":{"rendered":"Research"},"content":{"rendered":"<div  data-label=\"Content\" data-id=\"content--1\" data-export-id=\"content-12\" data-category=\"content\" class=\"content-12 content-section content-section-spacing content-relative\" id=\"content-1\" style=\"background-color: rgb(255, 255, 255);\"><div  class=\"gridContainer\"> <div  class=\"row text-center\"><div  class=\"section-title-col\" data-type=\"column\"> <h2  class=\"\"><span  style=\"color: rgb(0, 0, 0);\">Research<\/span><\/h2> <h3  class=\"\" style=\"text-align: left;\">Overview<\/h3><p  class=\"lead\" style=\"text-align: left;\">Our research is focused on understanding how the antibody repertoire against infectious agents in circulation and mucosal sites develop in response to various diseases and exposures. This knowledge can be applied to engineer personalized vaccines and immunotherapies. By developing and implementing innovative high-throughput technologies,&nbsp; proteomic analytical methods, and big data analytics tools and modeling tools, the group aims to gain clinically relevant insights regarding the precise protective features of antibodies and their protective mechanisms in unprecedented details.<\/p><\/div> <\/div> <div  class=\"row center-xs middle-xs\"> <div  class=\"col-sm-9\" data-type=\"column\"> <img decoding=\"async\"  loading=\"lazy\" class=\"custom-image\" src=\"https:\/\/i0.wp.com\/lee-lab.engineering.dartmouth.edu\/wp-content\/uploads\/2022\/08\/cropped-Screenshot-2022-08-04-171402.png?w=3840&amp;ssl=1\" title=\"cropped-Screenshot-2022-08-04-171402.png\" alt=\"\" data-recalc-dims=\"1\"><\/div> <\/div><\/div> <\/div><div  data-label=\"Content\" data-id=\"content--2\" data-export-id=\"content-12\" data-category=\"content\" class=\"content-12 content-section content-section-spacing\" id=\"content-2\" style=\"background-color: rgb(245, 250, 253);\"><div  class=\"\"> <div  class=\"row text-center\"><div  class=\"section-title-col\" data-type=\"column\"> <h3  class=\"\" style=\"text-align: left;\">Immune Repertoire Profiling and Therapeutics<\/h3><p  class=\"lead\" style=\"text-align: left;\">The repertoire of antibody molecules circulating in blood or coating mucosal surfaces is one of the pillars of protection against infectious agents, and it is shaped through various exposures to pathogens and vaccines encountered during one\u2019s lifetime. Using high-throughput sequencing of B cell transcripts and bottom-up high-resolution mass spectrometry, we focus on understanding the dynamics of antibody repertoires in infectious disease, with an emphasis on Influenza and SARS-CoV-2. Using these studies we aim to design next-generation therapeutics precisely tailored to maximize antibody-mediated protection in specific disease contexts.<\/p> <h3  class=\"\" style=\"text-align: left;\">Protein Engineering<\/h3><p  class=\"lead\" style=\"text-align: left;\">\nVaccination remains one of the most successful interventions for global human health. A primary reason a vaccine fails to elicit protective responses is that only a small fraction of the generated antibodies bind to specific epitopes where the pathogen is vulnerable to antibody-mediated functions. Next-generation vaccine engineering relies on an antibody-guided rational vaccine design approach aimed at focusing immune responses towards the protective epitopes. Examining the diversity and function of the antibody repertoire enables us to design immunogens that can elicit well-defined antibody responses, giving rise to next-generation vaccines that are tailored for individuals. We have been working on computational methods to assist in the development of this, as highlighted in our recent Neukom<span  style=\"font-weight: 700;\"><span  style=\"font-weight: 300;\"> award<\/span><\/span><span  style=\"font-weight: 300;\">.<\/span><\/p><h3  class=\"\" style=\"text-align: left;\">Platform Development for Antibody Discovery and Engineering<\/h3><p  class=\"lead\" style=\"text-align: left;\">Isolating antibody species from highly heterogenous immune cell populations to generate an antibody therapeutic poses a distinct challenge. We have been developing a technology to screen for antibody function on native mammalian cell lines, facilitating the discovery of effective antibodies from large libraries. With therapeutic antibodies we and others have identified, our recent awards from th<span  style=\"font-weight: 700;\"><span  style=\"font-weight: 300;\">e 2021<\/span><\/span> and 2022<span  style=\"font-weight: 700;\"><\/span> cancer accelerator, is enabling us to create an antibody engineering platform allow for faster development of novel therapeutic antibodies \u2014 in short, getting more potent drugs to patients who need them in order to improve the current standard of care and solve critical unmet medical needs.<\/p><\/div> <\/div> <div  class=\"row center-xs middle-xs\"> <div  class=\"col-sm-9\" data-type=\"column\"> <\/div> <\/div><\/div> <\/div>","protected":false},"excerpt":{"rendered":"<p>Research OverviewOur research is focused on understanding how the antibody repertoire against infectious agents in circulation and mucosal sites develop in response to various diseases and exposures. This knowledge can be applied to engineer personalized vaccines and immunotherapies. By developing and implementing innovative high-throughput technologies,&nbsp; proteomic analytical methods, and big data analytics tools and modeling&hellip; <br \/> <a class=\"read-more\" href=\"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/research\/\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"pro\/page-templates\/full-width-page.php","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"ngg_post_thumbnail":0,"cybocfi_hide_featured_image":"","footnotes":""},"class_list":["post-1131","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/pages\/1131","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/comments?post=1131"}],"version-history":[{"count":20,"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/pages\/1131\/revisions"}],"predecessor-version":[{"id":2222,"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/pages\/1131\/revisions\/2222"}],"wp:attachment":[{"href":"https:\/\/lee-lab.engineering.dartmouth.edu\/index.php\/wp-json\/wp\/v2\/media?parent=1131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}