Amy E. Keating - US grants

Abstract:
A grant has been awarded to the BioMicro Center at MIT to acquire high-performance computers for research in biology and biological engineering. The systems will be among the most powerful at MIT and will be dedicated to advancing the research programs of an active group of young faculty. These Assistant and Associate Professors lead research teams working on a wide range of problems in computational biology. The teams are united in their interest in the application of numerical models, computational simulations and large-scale computation to biological problems. The completion of the human genome sequence has emphasized the remarkable complexity of biological processes. While traditional molecular biology and molecular medicine will continue to play an important role in unraveling how these processes work, it seems almost certain that fundamental advances will come from the application of quantitative and rigorous analytic methods.
The research includes Professor Amy Keating's work on protein design. Dr. Keating's goal is to discern the rules governing protein-protein interactions through calculation and simulation and to then apply the rules to actual experiments. Professor Mike Yaffe will use computation to mine the human genome for proteins that play crucial roles in the transmission of signals within cells. Dr. Yaffe hopes to determine how circuits are constructed in cells, and to compare these circuits to electronic and mechanical circuits. Professor Tidor will use large-scale calculations to try to determine how proteins interact with each other and with small molecules (such as drugs). This is a long-standing problem in structural biology, but Dr. Tidor has recently shown that approximations drawn from engineering can be successfully applied to the problems that have proven to be impossible to calculate using conventional methods.
The new facility will not only enhance novel research but also graduate and undergraduate education. A new set of courses have the unusual distinction of being in the curriculum of three different departments: biology, biological engineering, and computer science. The group's intention is to expose students to the very latest computational methods and computer systems. Thus, high-performance computing will not only have a direct impact on world-class science, but also on education and training. With the help of Prof. Amy Keating, the group is working hard to attract additional women to computational biology. In the physical sciences women are significantly under-represented. Computational biology holds great promise as a discipline in which the historically inequitable under-representation of women in physical sciences can be overcome by association with biology.

DESCRIPTION (provided by applicant): The goal of this proposal is to predict and design specific protein interactions by using a combination of computational and experimental methods. To reduce the complexity of the problem, we target interactions mediated by the coiled coil. The coiled coil is a simple and important interaction motif estimated to occur in roughly 3-5% of all proteins, including many important for human disease. It has been studied extensively over the past 15 years. Consequently, existing knowledge provides a framework in which to attempt the challenging problems of interaction prediction and design. The specific aims of the proposal are: (1) To measure the pairings that occur among coiled coils found in human and yeast bZIP transcription factors. This will be accomplished using a large-scale protein microarray assay. The resulting data will be used to develop computational methods for predicting coiled-coil interactions from sequence. The bZIP interaction screen will also provide a wealth of data for the study of transcriptional regulatory networks that involve human oncogenes, including Fos and Jun. (2) To improve computational methods that have been developed for protein design so that these are more suitable for the problem of designing interaction specificity. 3) To use computationally-guided methods from Aim 2 to design peptides that bind specifically to targeted human bZIP coiled-coil domains, and to test these designs experimentally. This will provide a comparison of designed peptides with naturally occurring ones (Aim 1) that share similar interaction properties. It will also constitute a rigorous test of our basic understanding of coiled-coil recognition, and it will provide useful reagents for perturbing transcriptional regulatory networks. (4) To design a peptide that acts as an inhibitor of the oligomerization of BcrAbl, a human oncoprotein. The coiled coil-mediated dimerization of Bcr is implicated in more than 95% of chronic myelogenous leukemias. Together, these studies will improve our understanding of the molecular basis of protein interaction specificity and provide tools that can be used to rationally alter protein structure and function. The methods proposed can be applied to a wide range of different domain-domain interactions, so the insights that we achieve will have broad significance for the study of protein-protein associations generally.

The research objective of this project is to use computational methods to link the molecular properties of protein-protein interactions to their broader biological roles in the genome. The project aims to demonstrate that a structural understanding of protein interaction motifs can contribute to the interpretation of high-throughput studies of protein-protein interactions, and can lead to specific and testable hypotheses about protein associations and function. The work tests this idea using the alpha-helical coiled coil, a common and important interaction motif, as an example. The specific research objectives are: (1) To build a database containing the coiled-coil sequences from numerous genomes, along with the properties of the coiled coils, the functions of the proteins, and other annotation; (2) To combine these data with structural considerations to validate high-throughput protein-protein interaction studies and to predict coiled coil-mediated interactions; and (3) To experimentally verify putative coiled coil mediated interactions predicted to have important biological roles.

Broader Impacts: Dr. Keating's research and teaching at MIT are carried out in the emerging areas of computational and systems biology. These fields will have a tremendous impact on science and society in the next several decades. The sequencing of the human genome, as well as that of important pathogens, crops and scientific model organisms, has provided an opportunity for fundamentally new kinds of research combining biology, computer science, math, engineering and other quantitative fields. This interdisciplinary approach promises a deeper understanding of biology, as well as breakthroughs in biotechnology and molecular therapeutics. It is critically important to develop foundational methods for this kind of science and to provide appropriate training for undergraduate and graduate students who want to work in this area. The research described above, coupled with Dr. Keating's active role in CSBi, MIT's educational, research and outreach initiative in Computational and Systems Biology, will bring us closer to these goals.

DESCRIPTION (provided by applicant): Proteins of the Bcl-2 family are critical for regulating apoptosis and are promising therapeutic targets for treating a wide variety of cancers. Importantly, interaction specificity among pro- and anti-apoptotic family members is known to be critical to how they function. Although high-resolution structures have been solved for several Bcl-2 family complexes, these do not explain why interactions occur between some family members and not others, or how a range of binding affinities is achieved through variations in sequence and structure. A better understanding of the molecular basis for interaction specificity is necessary if we wish to predict, design or disrupt these and other protein interactions using rational methods. The goal of this proposal is to use an integrated program of computational and experimental methods to decipher the interactions of the Bcl-2 family of proteins and to probe their biophysical origins. The specific aims are to: (1) Carry out systematic experimental interaction studies of native, mutant and designed Bcl-2 proteins in order to relate their sequences to their binding properties and provide data for testing and improving computational models, (2) Use computational protein design to identify a wide variety of new peptides that bind to Bcl-2 family members, (3) Develop approaches for combining computational design with experimental selection to engineer peptides with desired interaction specificities (i.e. the ability to interact with some Bcl-2 family proteins but not others) and (4) Use insights into sequence requirements from Aims 1-3 to identify new mammalian and viral Bcl-2 family members that may play a role in apoptosis. Designed or selected peptides from this work could be used as reagents for the dissection of the complex signaling networks that regulate apoptosis, or as leads for the development of more targeted therapies. A longer-term goal is to apply these methods to other proteins with interesting interaction characteristics and an important role in apoptosis. A lasting outcome of this work will be a more comprehensive understanding of the relationship between protein sequence, structure and interaction specificity that will help shape the way we think about molecular recognition in the context of the proteome. PUBLIC HEALTH RELEVANCE Imbalances between pro-life and pro-death Bcl-2 family proteins are important in cancer, and interactions among these proteins provide promising therapeutic targets. The objective of this study is to understand at a high level of detail the molecular basis for the interaction specificity of the Bcl-2 family. This will contribute to our understanding of the biology of regulated cell death, support the development of therapeutic inhibitors and provide insights into the biophysics of protein-protein recognition.

The Center for Cell Decision Processes at MIT (CDP Center; www.cdpcenter.org) applies a modiry-measuremine- model paradigm to study receptor-mediated death and survival signaling in human cells. Pro-apoptotic and inflammatory pathways downstream of TNF, TRAIL and Fas death receptors are of particular interest, as are the pro-survival and mitogenic pathways activated by the six interacting ErbBl-4, IGF-1 and cMet growth factor receptors and by the T-cell receptor. The primary goal of the Center is to build mathematical models of signal transduction using a variety of methods ranging from statistical to physicochemical. All models incorporate empirical data and are subjected to rigorous experimental validation. To collect and systematize the data necessary to train and test models, the Center develops new mass spectrometry, microsystems and imaging methods as well as software to link data and models. Education, outreach and community development are core activities of the Center, and it will continue to support activities ranging from summer courses for high school students to sabbaticals for established scientists and engineers from minority-serving institutions, international conferences in systems biology and interdisciplinary communities it has established including CSBi at MIT and the Council for Systems Biology in Boston. CDP will build on its success in research through a five-part program that stresses (1) construction, calibration and validation of models of mammalian signaling processes in accessible cell-culture systems, (2) development of new experimental methods to gather quantitative and dynamic data from small cell populations and single-cells via array-based measurement, development of microfluidic devices and new approaches to live-cell imaging, (3) an emphasis on the systems biology of specialized cells, as it applies to primary T-cells, human hepatocytes and human neutrophils and to differences between healthy and diseased states in inflammatory disease and cancer, (4) continued development of electronically enabled research cores and information technologies, particularly those that enhance data sharing and collaboration, and (5) continued commitment to outreach and education through balanced programs with broad impact and those with the potential to substantially enhance individual careers

Through a grant from the National Science Foundation to the Massachusetts Institute of Technology, six faculty members will collaborate in the purchase and use of high-performance computing equipment for research and education in computational and systems biology. The advent of high-throughput technologies in the life sciences has provided many genome sequences, protein structures and biological interaction networks. The amount of such data will continue to grow, compelling the development of rigorous and quantitative approaches to decipher and understand it. Simultaneously, advances in computing technology are enabling new ways of attacking complex biological problems using modeling and simulation. The projects to be supported cover a wide range of exciting areas, including the study of gene and organism evolution, transcriptional and post-transcriptional gene regulation, molecular signaling, protein conformational modeling, protein design, and the analysis of complex networks. The work will lead to advances in computational methods and provide basic biological insights.

This award will support MIT?s active role in developing computational and systems biology in the United States. The university is establishing novel programs and curricula to train students at the interface of the life sciences, engineering and the physical sciences. The investigators on this award are deeply involved in these activities. Shared computing resources will help attract talented students and provide them with modern, cross-disciplinary training. These students, who come from diverse backgrounds, will assume leadership positions in American universities and companies.

DESCRIPTION (provided by applicant): Specific protein-protein interactions are responsible for organizing the cell, for processing biological signals and information, and for the chemistry of life. Thus, understanding biological mechanism relies on understanding the interactions that occur between proteins. An important long-term goal is to develop methods for reliably predicting and rationally modifying protein-protein interactions. Such capabilities would provide insight into the molecular details of pathology and highlight opportunities for disease treatment. This proposal describes an integrated experimental/computational technology platform that will provide predictive models of protein interaction specificity. The experimental component involves constructing randomized libraries of proteins or peptides that will be sorted according to their affinities for binding a particular receptor. The identities and binding affinities for very large numbers of library members will be decoded using high-throughput sequencing methods. The data, consisting of up to 107 {sequence, affinity} pairs per sequencing run, will be used as input to computational machine learning methods. Models will be generated that capture the relationship between sequence and interactions, and the predictive power of these models will be tested experimentally. The work described in this proposal emphasizes technology development and application of the new platform to study two general types of protein complexes. First are interactions of short helical ligands with mid-sized globular proteins, here studied using anti-apoptotic Bcl-2 and Ca2+ binding EF-hand proteins. Second are interactions of short linear peptides with modular interaction domains, here PDZ and SH3 domains. These four protein families mediate an enormous number of important molecular recognition events in human cells, and the resulting models will provide valuable support to study of their biological functions. This work will also provide a stringent test of the capabilities of the proposed technology, which can then be applied to a much wider variety of molecular complexes, e.g., protein-protein, protein-small molecule and protein-nucleic acid assemblies. Given the paucity of high- throughput methods for accurately measuring protein-protein interactions, and the primitive capabilities of most computational models for predicting protein binding, the proposed technology platform has the potential to dramatically transform the study of protein interaction specificity. PUBLIC HEALTH RELEVANCE: Specific protein-protein interactions underlie all biological processes. Knowledge of interactions that occur in healthy vs. diseased tissues, coupled with methods for inhibiting such interactions, would dramatically expand opportunities to treat human disease. This proposal describes a new technology for advancing the measurement, prediction and design of protein complexes.

Intellectual Merit: Understanding how amino-acid sequences determine the structure and function of proteins provides an opportunity to engineer molecular tools at the nanoscale level. The alpha helical coiled coil is a simple protein structure made up of two or more chains that associate into a rod-like super-helix. Several decades of research have provided insights into the principles that determine whether two protein chains can associate to form a coiled coil. This process can now be controlled, to a certain extent, by manipulating protein sequence using rational molecular design techniques. This project aims to exploit current understanding of coiled-coil sequence-structure relationships, along with powerful molecular engineering techniques, to develop reagents suitable for building new materials and re-engineering cellular circuits using coiled coil motifs. The goal is to generate a list of fully described molecular parts that will allow other scientists to use these as modular units in bioengineering projects. The research builds on the prior identification of 23 synthetic proteins that participate in a variety of complex interaction patterns. Goals for the project are to (1) test whether these peptides, previously characterized in solution in the laboratory, maintain their interaction properties inside bacteria and yeast, (2) refine and tune the interaction strengths and specificities of these 23 proteins through rational molecular design, (3) explore how the modular coiled-coil units can be used to alter information processing in laboratory yeast, specifically by modifying MAP-kinase signaling, and (4) explore the use of modular coiled-coil proteins for constructing artificial DNA-binding proteins. Success in these areas will pave the way for broad use of synthetic coiled coils in molecular engineering applications. As modular design blocks adapted from the natural world, coiled coils have the potential to advance materials science, provide new capabilities for engineering microbial cells, and interface with nanoscale inorganic materials, enabling advanced information processing and smart devices.

Broader Impacts: Beyond the scientific impact, this project will enhance integrated educational/research opportunities for a diverse group of young scientists. The proposed work will be carried out in the Keating laboratory in the MIT biology department, where education and research activities are tightly coupled. The Keating research group of 12 individuals is composed of graduate students, postdoctoral scientists and undergraduate students. Laboratory members with diverse scientific, economic, ethnic and cultural backgrounds are involved in all group activities, and Dr. Keating additionally participates in mentoring activities for women and under-represented students in science. Undergraduate students will be recruited to work on this project, with summer invitations extended particularly to individuals not likely otherwise to be exposed to modern research. Protein engineering and synthetic biology are appealing research subjects for undergraduates, because these provide the opportunity to rationally construct something entirely new in the molecular world. This will enhance the spirit of exploration and discovery that is critical for engaging and retaining young scientists.

? DESCRIPTION (provided by applicant): This proposal is for continuing support of the pre-doctoral training grant in biology at the Massachusetts Institute of Technology (MIT). This training grant (in its 40th year) continues to be the most important source of support for graduate students studying biological science at MIT. The mission of this program is to train the next generation of biological/biomedical scientists, many of whom will be innovators and leaders in research and education. Specifically, in this training program we strive to educate our students: to understand the fundamental underlying principles of modern biology including genetics, biochemistry, cell biology, molecular biology and quantitative data analysis; to be ethical decision makers; to flexibly adapt to the rapidly changing modern biomedical sciences landscape; to become creative, effective, rigorous researchers; to become excellent communicators of science, and to become thoughtful teachers and mentors. We seek out, recruit and train talented students from majority, underrepresented minority, and disadvantaged populations, and help them initiate successful research careers. Trainees admitted to our program have outstanding undergraduate academic records and have demonstrated strong motivation to pursue research. A key feature of our program is an intensive, focused curriculum required of all first-semester students. Students work together in lecture and discussion-style courses taught by dedicated faculty to master a fundamental set of approaches that underpin all modern molecular biological science. The training program exposes students to the research interests of all faculty members in the Biology Department prior to the critical choice of a thesis lab and topic. Responsible conduct in research is taught in three phases, including an intense mini-course for 2nd year students. We aim to support 46 predoctoral students per year, primarily in their first and second years of training; the complete Ph.D. program takes trainees approximately 5.8 years to complete. Students' progress through the program is monitored in regular thesis committee meetings with faculty members, with oversight provided by the graduate committee. Our students perform research of outstanding quality, and most trainees go on to careers in biomedical research. Many of our former trainees are now leaders in their chosen fields.

DESCRIPTION (provided by applicant): Protein-protein interactions regulate all cellular processes and are attractive targets for therapeutic inhibition. The long-term goal of the proposed work is to accelerate the discovery of modified helical peptides that can be used as protein-protein interaction inhibitors in research, diagnosis and therapy. The short-term goals are to develop new, integrated computational and experimental methods that will deliver potent and selective inhibitors of Bcl-2 proteins. Anti-apoptotic Bcl-2 proteins are important in many cancers, where their over- expression counteracts cell-death signaling. Bcl-2 proteins provide resistance to chemotherapy, making them high-priority oncology targets. Many Bcl-2 protein interactions involve a well-conserved binding groove that engages short alpha helices of ~20 residues, called BH3 helices, in partner proteins. Synthetic peptides that mimic BH3 helices can inhibit anti-apoptotic function and lead to cell death. However, there are multiple members of the Bcl-2 family, and not all BH3 peptides are equally effective inhibitors of all Bcl-2 proteins. An important goal is to discover high-affinity and selective inhibitors for each family member. Another challenge is that engineered peptides are highly susceptible to proteases and have trouble crossing cell membranes, limiting their utility as reagents. Recent work has shown that chemical modifications that stabilize helices can improve their properties. The specific aims of this proposal are organized around tightly coupled computational and experimental techniques that will deepen our understanding of what makes a good helical-peptide inhibitor and help us discover useful molecules more efficiently. The first step will be to use computational structure- based methods to design peptides predicted to bind tightly and selectively to Bcl-2 family members Bfl-1 and BHRF1. This information will be used to design combinatorial libraries of ~107 peptides focused on high-priority candidates. Libraries will be screened for molecules with desired properties in a yeast-surface display procedure that will provide feedback about the quality of the computational library design methods. The best peptides from yeast display will be further characterized using biophysical measurements in solution and x-ray crystallography. Computational model building and analysis will help establish determinants of binding affinity and specificity. Finally, the best peptides resulting from these procedures will be further optimized using chemical techniques that introduce stabilizing crosslinks into helices. Current insights into what makes good vs. poor crosslinking modifications are limited. In this work, detailed molecular dynamics simulations of modified and unmodified peptides will be carried out to build our understanding of how altered peptide structure affects binding. Overall, this work wil deliver new molecules that target important cancer-regulating proteins, new computational methods that will speed the discovery of selective peptide binders, and a better understanding of the biophysical determinants of helical-peptide interactions.

Many protein-protein interactions are mediated by short, linear motifs that bind selectively to modular, conserved protein domains. It is a long-standing goal of modern biology to understand the molecular recognition code for these types of interactions, because this would help elucidate mechanisms of signal transduction and predict cellular localization, targeting, and substrate selectivity of proteins that contain peptide-recognition domains. The ability to re-design domain-peptide interactions would lead to protein- interaction inhibitors useful for research and therapy. Recent advances in protein and peptide library screening and sequencing provide exciting opportunities to measure domain-peptide interactions in high throughput. In parallel with such measurements, computational methods are needed to interpret screening results and build models that can be used for protein interaction prediction and design. This proposal describes an integrated experimental/computational program for measuring, modeling and designing interactions mediated by structurally conserved EVH1 domains that bind to short, proline-rich motifs. The proposed studies focus on Ena/VASP family proteins critical for regulation of the actin cytoskeleton. Three human paralogs, Mena, VASP and EVL, act as scaffolds to assemble complexes at the ends of actin fibers. Ena/VASP proteins are critical for the formation of filopodia and lamellipodia and for regulation of actin- based cell motility; they also have newly discovered roles in neural development. Mena, and particularly its isoform Mena invasive, control cancer cell invasion and promote resistance to chemotherapy; the EVH1 binding activity of Mena is therefore an attractive therapeutic target. The peptide binding determinants for EVH1 domains are poorly understood. Short consensus binding motifs have been identified in earlier work but are not sufficient to predict which sequences will bind, or with what paralog specificity. Sequence that flanks known motifs modulates binding to EVH1 domains, but this phenomenon has not been systematically studied. In three specific aims, we propose to (1) experimentally identify Ena/VASP EVH1 domain-binding peptides in the human proteome, determine the sequence requirements for binding, and postulate new biologically relevant interaction partners, (2) apply computational structural modeling and experimental structure determination to understand the mechanisms of binding specificity, including the contributions of core-motif and flanking sequences, and (3) design high affinity and paralog- and/or isoform-selective inhibitors of EVH1 domain interactions. Deeper insight into how EVH1 domains engage their partners will advance our understanding of how these proteins contribute to cell motility, including in invasive cancer cells. Inhibitor design will provide reagents for perturbing Ena/VASP protein functions, including the role of Mena in regulating local mRNA translation in neurons. This work will establish a path for mapping and inhibiting domain-peptide interactions that can be applied to many other peptide-recognition domains.

Protein-protein interactions control myriad biological processes important for human health. Tools for discovering, predicting and designing such interactions can provide insights into biological mechanisms and highlight possible routes to therapeutic intervention. This project will integrate computational and experimental approaches to advance our understanding of the relationships between sequence and function for protein interactions among Bcl-2 family proteins. The Bcl-2 family regulates apoptosis and autophagy by forming specific complexes, some of which inhibit and some of which promote cell death. Competition between pro- and anti-apoptotic Bcl-2 family proteins for binding to short alpha helices encoded by a Bcl-2 homology 3 (BH3) motif controls key cell survival decisions. It is now well established that peptides and small molecules can mimic or inhibit BH3 interactions. Such molecules provide a way to control signaling outcomes using exogenous reagents, as demonstrated by the first drug approved for treating cancer by targeting Bcl-2. Despite exciting progress, open questions about Bcl-2 protein interactions with BH3 motifs provide additional opportunities for discovery. In particular: Do as-yet undiscovered BH3 motif-containing proteins in the human proteome influence signaling through Bcl-2 family proteins? Why do some proteins that contain BH3 motifs trigger mitochondrial pore formation by pro-apoptotic BAK and BAX whereas others do not? What are the mechanisms of BH3 binding-induced conformational changes that lead to mitochondrial membrane pore formation and cell death? What opportunities exist for promoting or blocking such processes using designed peptides or proteins? Answers to these questions will impact analysis of Bcl-2 pathways important for multiple human diseases, provide new reagents, and guide development of therapies for cancer and other diseases. Building on the substantial successes that we realized in the previous funding period, we will drive progress in these areas by applying new methodology that integrates interaction screening with structural modeling and prediction. We will apply novel computational methods for predicting new Bcl-2 binding partners, test predictions of our models, and highlight candidate new interaction partners of biological significance. We will propose molecular mechanisms of BAK and BAX activation and test them using libraries of BH3 motif variants. We will apply new computational design methods to make peptides and mini-proteins that activate or inhibit BAK and BAX-mediated cell death. Collectively, our contributions will provide a map of the sequence-function landscape of BH3 motifs, which are critical factors controlling cell survival. The methods and tools developed in this work will also be useful for discovering and inhibiting other protein-protein interactions. !

This proposal is for support of the pre-doctoral program in Cellular, Biochemical and Molecular Science at the Massachusetts Institute of Technology (MIT). Our mission is to train the next generation of biological/biomedical scientists, many of whom will be innovators and leaders in research, education, and other fields. This proposal builds on an outstanding training record developed over a 46-year partnership with NIGMS. Our aims are to: educate students to understand the fundamental and underlying principles of molecular, biochemical, and cellular biology, train students to be critical and creative thinkers, prepare students to be ethical decision makers, teach and provide practice in written and oral communication, provide experience with teaching and mentoring younger students, mentor students to become effective and rigorous researchers, guide students through completion and publication of research projects, advise students as they determine the best-fit careers for their interests and skills, provide an inclusive learning and research environment, and broaden participation of individuals with diverse backgrounds in biomedical research careers. We recruit and train talented students from majority, underrepresented minority, disabled, and disadvantaged populations. Trainees admitted to our program have outstanding academic records and strong motivation and aptitude to pursue research. A key feature of our program is an intensive, focused curriculum required of all first-year students. Students work together in lecture and discussion-style courses taught by dedicated faculty to master a fundamental set of approaches that underpin molecular biological science. The training program exposes students to the research interests of all faculty members in the Biology Department prior to a sequence of rotations that, in combination with first-semester courses, support an informed choice of a thesis advisor and topic. Students gain experience in scientific communication and in teaching and mentoring junior students. Responsible conduct of research is taught in both classroom and laboratory settings, including an intense mini-course for 2nd year students. Students have many opportunities to learn about career paths open to them following doctoral training. Students? progress through the program is monitored in regular thesis committee meetings with faculty members, with oversight by the graduate committee. We seek to build and maintain a welcoming and supportive community in which all students are valued and included. This training grant would constitute a critical source of support for ~50% of training-grant eligible graduate students in our program during their first two years. Our students perform research of outstanding quality, and most trainees go on to careers in biomedical research. Many of our former trainees are now leaders in their chosen fields and bring to their positions the knowledge, rigor, thoughtful perspectives, and values of equity and inclusion that we emphasize at MIT Biology. We anticipate exciting futures for our alumni as they help transform the US biomedical landscape.