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103. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

Author

Zhi Lu, Giltae Song, Troy W. Whitfield, Vishwanath R. Iyer, Teresa Vales, Angelika Merkel, Max Libbrecht, David Haussler, Ting Wang, Kristen Lee, Lingyun Song, Richard M. Myers, Alfonso Valencia, Rachel A. Harte, Xiaoqin Xu, Lucas D. Ward, Hazuki Takahashi, Nathan C. Sheffield, Thomas Derrien, Georgi K. Marinov, Eric D. Nguyen, Bernard B. Suh, Brian J. Raney, Richard Sandstrom, Thomas D. Tullius, Benoit Miotto, Alexander Dobin, Youhan Xu, Lukas Habegger, Ian Dunham, Brian A. Risk, Paul G. Giresi, Morgan C. Giddings, Hualin Xi, Anshul Kundaje, Robert S. Harris, Devin Absher, Peter J. Bickel, Yanbao Yu, Browen Aken, Colin Kingswood, Bryan R. Lajoie, Peter J. Good, Katrina Learned, Laura Elnitski, Shirley Pepke, Brandon King, Piero Carninci, Xinqiong Yang, Ghia Euskirchen, Kathryn Beal, Christelle Borel, Michael Muratet, Robert L. Grossman, David G. Knowles, Zarmik Moqtaderi, Veronika Boychenko, Steven P. Wilder, Michael L. Tress, Florencia Pauli, Alan P. Boyle, Andrea Tanzer, Philipp Kapranov, Serafim Batzoglou, Audra K. Johnson, Jun Neri, Nitin Bhardwaj, Elise A. Feingold, Venkat S. Malladi, Michael M. Hoffman, William Stafford Noble, Andrea Sboner, Mark Gerstein, Stephanie L. Parker, Jacqueline Dumais, Felix Schlesinger, Deborah R. Winter, Randall H. Brown, Thanh Truong, Rebecca F. Lowdon, Paolo Ribeca, Brooke Rhead, Peggy J. Farnham, Krista Thibeault, Terrence S. Furey, Donna Karolchik, Alec Victorsen, Xiaoan Ruan, Rehab F. Abdelhamid, Amy S. Nesmith, Jing Wang, Nicholas M. Luscombe, Alina R. Cao, Diane Trout, Teri Slifer, Peter E. Newburger, Cricket A. Sloan, Dimitra Lotakis, Stephen M. J. Searle, Ali Mortazavi, Alexandra Bignell, Alex Reynolds, Orion J. Buske, Chris Zaleski, Theresa K. Canfield, Ian Bell, Jin Lian, Vanessa K. Swing, Katalin Toth Fejes, Catherine Ucla, Robert E. Thurman, Jacqueline Chrast, Wei Lin, Tim Hubbard, Gary Saunders, Minyi Shi, Vihra Sotirova, Sherman M. Weissman, Jason D. Lieb, Richard Humbert, Kevin M. Bowling, Assaf Gordon, Tarjei S. Mikkelsen, Jing Leng, Thomas R. Gingeras, Fabian Grubert, Nader Jameel, Jost Vielmetter, Hannah Monahan, Preti Jain, Lindsay L. Waite, Tony Shafer, Joel Rozowsky, Michael Coyne, Brian Reed, M. Kay, Harsha P. Gunawardena, Ross C. Hardison, Gavin Sherlock, Alexandra Charos, Joseph D. Fleming, Ann S. Zweig, Jason Gertz, Rajinder Kaul, Xianjun Dong, Alexandre Reymond, Carrie A. Davis, Haiyan Huang, Chao Cheng, Marco Mariotti, Phil Lacroute, Jason A. Dilocker, Kenneth McCue, R. Robilotto, Stylianos E. Antonarakis, Sridar V. Chittur, Justin Jee, Barbara J. Wold, Sudipto K. Chakrabortty, Erica Dumais, Amartya Sanyal, Nathan Boley, Tianyuan Wang, Julien Lagarde, Anthony Kirilusha, Jonathan B. Preall, Kevin Roberts, Erika Giste, Hugo Y. K. Lam, Alvis Brazma, Gregory J. Hannon, Eric Rynes, Philippe Batut, Kevin Struhl, Margus Lukk, Manching Ku, Suganthi Balasubramanian, Sonali Jha, Jorg Drenkow, W. James Kent, Michael Snyder, Jie Wang, Anna Battenhouse, Charles B. Epstein, Rami Rauch, Christopher Shestak, John A. Stamatoyannopoulos, Gaurab Mukherjee, Cédric Howald, Tanya Kutyavin, Huaien Wang, Scott A. Tenenbaum, Wan Ting Poh, Kate R. Rosenbloom, Manolis Kellis, Pauline A. Fujita, Linfeng Wu, Anita Bansal, Molly Weaver, Linda L. Grasfeder, Peter J. Sabo, Qiang Li, Melissa S. Cline, Robert M. Kuhn, Darin London, Seth Frietze, Atif Shahab, Shane Neph, Damian Keefe, James B. Brown, Mark Diekhans, Webb Miller, Katherine Aylor Fisher, Jiang Du, Hadar H. Sheffer, Sarah Djebali, Frank Doyle, Nathan Lamarre-Vincent, Chia-Lin Wei, Laura A.L. Dillon, Jennifer Harrow, Robert C. Altshuler, Tyler Alioto, Raymond K. Auerbach, Adam Frankish, Rebekka O. Sprouse, Patrick J. Collins, E. Christopher Partridge, Zheng Liu, Yoichiro Shibata, Elliott H. Margulies, Abigail K. Ebersol, Kimberly A. Showers, Eric D. Green, Krishna M. Roskin, Job Dekker, Barbara N. Pusey, Ekta Khurana, Gilberto DeSalvo, Yijun Ruan, Hao Wang, Jainab Khatun, Henriette O'Geen, Alexej Abyzov, Brian Williams, Ryan M. McDaniell, Maya Kasowski, Manoj Hariharan, Felix Kokocinski, Gloria Despacio-Reyes, Zhancheng Zhang, Subhradip Karmakar, Ewan Birney, Koon-Kiu Yan, Xian Chen, Shinny Vong, Daniel Sobral, Nick Bild, Seul K.C. Kim, Timo Lassmann, Li Wang, Minerva E. Sanchez, Vaughan Roach, Theodore Gibson, Stephen C. J. Parker, Michael F. Lin, Patrick A. Navas, Laurence R. Meyer, Luiz O. F. Penalva, Bradley E. Bernstein, Kevin P. White, Emilie Aït Yahya Graison, Juan M. Vaquerizas, Sushma Iyengar, Kimberly M. Newberry, Akshay Bhinge, Xiaolan Zhang, Kim Bell, Yoshihide Hayashizaki, Lucas Lochovsky, Noam Shoresh, Hagen Tilgner, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Eric Haugen, Katherine E. Varley, M. van Baren, Nathan D. Trinklein, Bum Kyu Lee, Tristan Frum, Marianne Lindahl-Allen, Timothy Durham, Roderic Guigó, Christopher W. Maier, Micha Sammeth, Debasish Raha, Timothy R. Dreszer, Benedict Paten, Robbyn Issner, Michael R. Brent, Kevin Y. Yip, Kim Blahnik, Jason Ernst, Zhiping Weng, Henry Amrhein, Arend Sidow, Javier Herrero, Hui Gao, Stephen G. Landt, Pouya Kheradpour, Galt P. Barber, Gregory E. Crawford, Toby Hunt, HudsonAlpha Institute for Biotechnology [Huntsville, AL], ENCODE Project Consortium : Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B, Crawford GE, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Mikkelsen TS, Kheradpour P, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Lin MF, Kellis M, Gingeras TR, Davis CA, Kapranov P, Dobin A, Zaleski C, Schlesinger F, Batut P, Chakrabortty S, Jha S, Lin W, Drenkow J, Wang H, Bell K, Gao H, Bell I, Dumais E, Dumais J, Antonarakis SE, Ucla C, Borel C, Guigo R, Djebali S, Lagarde J, Kingswood C, Ribeca P, Sammeth M, Alioto T, Merkel A, Tilgner H, Carninci P, Hayashizaki Y, Lassmann T, Takahashi H, Abdelhamid RF, Hannon G, Fejes-Toth K, Preall J, Gordon A, Sotirova V, Reymond A, Howald C, Graison E, Chrast J, Ruan Y, Ruan X, Shahab A, Ting Poh W, Wei CL, Crawford GE, Furey TS, Boyle AP, Sheffield NC, Song L, Shibata Y, Vales T, Winter D, Zhang Z, London D, Wang T, Birney E, Keefe D, Iyer VR, Lee BK, McDaniell RM, Liu Z, Battenhouse A, Bhinge AA, Lieb JD, Grasfeder LL, Showers KA, Giresi PG, Kim SK, Shestak C, Myers RM, Pauli F, Reddy TE, Gertz J, Partridge EC, Jain P, Sprouse RO, Bansal A, Pusey B, Muratet MA, Varley KE, Bowling KM, Newberry KM, Nesmith AS, Dilocker JA, Parker SL, Waite LL, Thibeault K, Roberts K, Absher DM, Wold B, Mortazavi A, Williams B, Marinov G, Trout D, Pepke S, King B, McCue K, Kirilusha A, DeSalvo G, Fisher-Aylor K, Amrhein H, Vielmetter J, Sherlock G, Sidow A, Batzoglou S, Rauch R, Kundaje A, Libbrecht M, Margulies EH, Parker SC, Elnitski L, Green ED, Hubbard T, Harrow J, Searle S, Kokocinski F, Aken B, Frankish A, Hunt T, Despacio-Reyes G, Kay M, Mukherjee G, Bignell A, Saunders G, Boychenko V, Van Baren M, Brown RH, Khurana E, Balasubramanian S, Zhang Z, Lam H, Cayting P, Robilotto R, Lu Z, Guigo R, Derrien T, Tanzer A, Knowles DG, Mariotti M, James Kent W, Haussler D, Harte R, Diekhans M, Kellis M, Lin M, Kheradpour P, Ernst J, Reymond A, Howald C, Graison EA, Chrast J, Tress M, Rodriguez JM, Snyder M, Landt SG, Raha D, Shi M, Euskirchen G, Grubert F, Kasowski M, Lian J, Cayting P, Lacroute P, Xu Y, Monahan H, Patacsil D, Slifer T, Yang X, Charos A, Reed B, Wu L, Auerbach RK, Habegger L, Hariharan M, Rozowsky J, Abyzov A, Weissman SM, Gerstein M, Struhl K, Lamarre-Vincent N, Lindahl-Allen M, Miotto B, Moqtaderi Z, Fleming JD, Newburger P, Farnham PJ, Frietze S, O'Geen H, Xu X, Blahnik KR, Cao AR, Iyengar S, Stamatoyannopoulos JA, Kaul R, Thurman RE, Wang H, Navas PA, Sandstrom R, Sabo PJ, Weaver M, Canfield T, Lee K, Neph S, Roach V, Reynolds A, Johnson A, Rynes E, Giste E, Vong S, Neri J, Frum T, Johnson EM, Nguyen ED, Ebersol AK, Sanchez ME, Sheffer HH, Lotakis D, Haugen E, Humbert R, Kutyavin T, Shafer T, Dekker J, Lajoie BR, Sanyal A, James Kent W, Rosenbloom KR, Dreszer TR, Raney BJ, Barber GP, Meyer LR, Sloan CA, Malladi VS, Cline MS, Learned K, Swing VK, Zweig AS, Rhead B, Fujita PA, Roskin K, Karolchik D, Kuhn RM, Haussler D, Birney E, Dunham I, Wilder SP, Keefe D, Sobral D, Herrero J, Beal K, Lukk M, Brazma A, Vaquerizas JM, Luscombe NM, Bickel PJ, Boley N, Brown JB, Li Q, Huang H, Gerstein M, Habegger L, Sboner A, Rozowsky J, Auerbach RK, Yip KY, Cheng C, Yan KK, Bhardwaj N, Wang J, Lochovsky L, Jee J, Gibson T, Leng J, Du J, Hardison RC, Harris RS, Song G, Miller W, Haussler D, Roskin K, Suh B, Wang T, Paten B, Noble WS, Hoffman MM, Buske OJ, Weng Z, Dong X, Wang J, Xi H, Tenenbaum SA, Doyle F, Penalva LO, Chittur S, Tullius TD, Parker SC, White KP, Karmakar S, Victorsen A, Jameel N, Bild N, Grossman RL, Snyder M, Landt SG, Yang X, Patacsil D, Slifer T, Dekker J, Lajoie BR, Sanyal A, Weng Z, Whitfield TW, Wang J, Collins PJ, Trinklein ND, Partridge EC, Myers RM, Giddings MC, Chen X, Khatun J, Maier C, Yu Y, Gunawardena H, Risk B, Feingold EA, Lowdon RF, Dillon LA, Good PJ, Harrow J, Searle S., Becker, Peter B, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Department of Physics, Kellis, Manolis, Epstein, Charles B., Bernstein, Bradley E., Shoresh, Noam, Ernst, Jason, Mikkelsen, Tarjei Sigurd, Kheradpour, Pouya, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Ward, Lucas D., Altshuler, Robert Charles, Lin, Michael F., ENCODE Project Consortium, Antonarakis, Stylianos, and Miotto, Benoit

Subjects
RNA, Messenger/genetics, [SDV]Life Sciences [q-bio], Messenger, Genoma humà, Genome, Medical and Health Sciences, 0302 clinical medicine, Models, ddc:576.5, Biology (General), Conserved Sequence, Genetics, 0303 health sciences, General Neuroscience, RNA-Binding Proteins, Genomics, Biological Sciences, Chromatin, 3. Good health, [SDV] Life Sciences [q-bio], DNA-Binding Proteins, Gene Components, 030220 oncology & carcinogenesis, DNA methylation, Encyclopedia, HIV/AIDS, Proteïnes de la sang -- Aspectes genètics, General Agricultural and Biological Sciences, Databases, Nucleic Acid, Human, Research Article, Quality Control, Process (engineering), QH301-705.5, 1.1 Normal biological development and functioning, Computational biology, Biology, ENCODE, General Biochemistry, Genetics and Molecular Biology, Chromatin/metabolism, Vaccine Related, 03 medical and health sciences, Databases, Genetic, Underpinning research, Humans, RNA, Messenger, RNA-Binding Proteins/genetics/metabolism, Vaccine Related (AIDS), Gene, 030304 developmental biology, Internet, General Immunology and Microbiology, Nucleic Acid, Agricultural and Veterinary Sciences, Base Sequence, Models, Genetic, Genome, Human, Prevention, Human Genome, Computational Biology, DNA Methylation, ENCODE Project Consortium, Gene Expression Regulation, DNA-Binding Proteins/genetics/metabolism, RNA, Human genome, Immunization, Generic health relevance, Developmental Biology
Abstract

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome., National Human Genome Research Institute (U.S.), National Institutes of Health (U.S.)

Published
2011

104. Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibiotics.

Author

Romano KP, Bagnall J, Warrier T, Sullivan J, Ferrara K, Orzechowski M, Nguyen P, Raines K, Livny J, Shoresh N, and Hung D

Abstract

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wildtype or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three new molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small molecule inhibition resemble those resulting from genetic depletion of essential targets by CRISPRi by PerSpecTM, demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.

Published
2024
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105. "Multiplexed screen identifies a Pseudomonas aeruginosa -specific small molecule targeting the outer membrane protein OprH and its interaction with LPS".

Author

Poulsen BE, Warrier T, Barkho S, Bagnall J, Romano KP, White T, Yu X, Kawate T, Nguyen PH, Raines K, Ferrara K, Golas A, Fitzgerald M, Boeszoermenyi A, Kaushik V, Serrano-Wu M, Shoresh N, and Hung DT

Abstract

The surge of antimicrobial resistance threatens efficacy of current antibiotics, particularly against Pseudomonas aeruginosa , a highly resistant gram-negative pathogen. The asymmetric outer membrane (OM) of P. aeruginosa combined with its array of efflux pumps provide a barrier to xenobiotic accumulation, thus making antibiotic discovery challenging. We adapted PROSPECT 1 , a target-based, whole-cell screening strategy, to discover small molecule probes that kill P. aeruginosa mutants depleted for essential proteins localized at the OM. We identified BRD1401, a small molecule that has specific activity against a P. aeruginosa mutant depleted for the essential lipoprotein, OprL. Genetic and chemical biological studies identified that BRD1401 acts by targeting the OM β-barrel protein OprH to disrupt its interaction with LPS and increase membrane fluidity. Studies with BRD1401 also revealed an interaction between OprL and OprH, directly linking the OM with peptidoglycan. Thus, a whole-cell, multiplexed screen can identify species-specific chemical probes to reveal novel pathogen biology.

Published
2024
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106. Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements.

Author

Hu Y, Ma S, Kartha VK, Duarte FM, Horlbeck M, Zhang R, Shrestha R, Labade A, Kletzien H, Meliki A, Castillo A, Durand N, Mattei E, Anderson LJ, Tay T, Earl AS, Shoresh N, Epstein CB, Wagers A, and Buenrostro JD

Abstract

Cis -regulatory elements control gene expression and are dynamic in their structure, reflecting changes to the composition of diverse effector proteins over time 1-3 . Here we sought to connect the structural changes at cis- regulatory elements to alterations in cellular fate and function. To do this we developed PRINT, a computational method that uses deep learning to correct sequence bias in chromatin accessibility data and identifies multi-scale footprints of DNA-protein interactions. We find that multi-scale footprints enable more accurate inference of TF and nucleosome binding. Using PRINT with single-cell multi-omics, we discover wide-spread changes to the structure and function of candidate cis -regulatory elements (cCREs) across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Activity segmentation using the co-variance across cell states identifies "sub-cCREs" as modular cCRE subunits of regulatory DNA. We apply this single-cell and PRINT approach to characterize the age-associated alterations to cCREs within hematopoietic stem cells (HSCs). Remarkably, we find a spectrum of aging alterations among HSCs corresponding to a global gain of sub-cCRE activity while preserving cCRE accessibility. Collectively, we reveal the functional importance of cCRE structure across cell states, highlighting changes to gene regulation at single-cell and single-base-pair resolution., Competing Interests: Declaration of Interests J. Buenrostro holds patents related to ATAC-seq and is an SAB member of Camp4 and seqWell. J. Buenrostro and S. Ma holds a patent based on SHARE-seq. A.J.W. is a scientific advisor for Frequency Therapeutics and Kate Therapeutics. A.J.W. is also a co-founder and scientific advisory board member and holds private equity in Elevian, Inc., a company that aims to develop medicines to restore regenerative capacity. Elevian also provides sponsored research to the Wagers lab.

Published
2023
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107. At-home Testing and Risk Factors for Acquisition of SARS-CoV-2 Infection in a Major US Metropolitan Area.

Author

Woolley AE, Dryden-Peterson S, Kim A, Naz-McLean S, Kelly C, Laibinis HH, Bagnall J, Livny J, Ma P, Orzechowski M, Shoresh N, Gabriel S, Hung DT, and Cosimi LA

Abstract

Importance: Unbiased assessment of risks associated with acquisition of SARS-CoV-2 is critical to informing mitigation efforts during pandemics., Objective: Understand risk factors for acquiring COVID-19 in a large, prospective cohort of adult residents recruited to be representative of a large US metropolitan area., Design: Fully remote longitudinal cohort study launched in October 2020 and ongoing; Study data reported through June 15, 2021., Setting: Brigham and Women’s Hospital, Boston MA., Participants: Adults within 45 miles of Boston, MA., Intervention: Monthly at-home SARS-CoV-2 viral and antibody testing., Main Outcomes: Between October 2020 and January 2021, we enrolled 10,289 adults reflective of Massachusetts census data. At study entry, 567 (5.5%) participants had evidence of current or prior SARS-CoV-2 infection. This increased to 13.4% by June 15, 2021. Compared to whites, Black non-Hispanic participants had a 2.2 fold greater risk of acquiring COVID-19 (HR 2.19, 95% CI 1.91-2.50; p=<0.001) and Hispanics had a 1.5 fold greater risk (HR 1.52, 95% CI 1.32-1.71; p=<0.016). Individuals aged 18-29, those who worked outside the home, and those living with other adults and children were at an increased risk. Individuals in the second and third lowest disadvantaged neighborhood communities, as measured by the area deprivation index as a marker for socioeconomic status by census block group, were associated with an increased risk in developing COVID-19. Individuals with medical risk factors for severe COVID-19 disease were at a decreased risk of SARS-CoV-2 acquisition., Conclusions: These results demonstrate that race/ethnicity and socioeconomic status are not only risk factors for severity of disease but are also the biggest determinants of acquisition of infection. Importantly, this disparity is significantly underestimated if based on PCR data alone as noted by the discrepancy in serology vs. PCR detection for non-white participants, and points to persistent disparity in access to testing. Meanwhile, medical conditions and advanced age that increase the risk for severity of SARS-CoV-2 disease were associated with a lower risk of acquisition of COVID-19 suggesting the importance of behavior modifications. These findings highlight the need for mitigation programs that overcome challenges of structural racism in current and future pandemics., Trial Registration: N/A., Question: What population and occupational groups in the United States are at increased risk for acquiring COVID-19?, Findings: In this remote, longitudinal cohort study involving monthly PCR and serology self-testing of 10,289 adult residents of the Boston metropolitan area, 9257 (90.0%) of TestBoston participants acquired evidence of immunity to SARS-CoV-2 through vaccination, infection, or both as of June 15, 2021. Residents identifying as Black, Hispanic/Latinx had an increased risk of acquisition of COVID-19. Healthcare workers were not at increased risk of SARS-CoV-2 acquisition. Individuals with medical risk factors for severe COVID-19 disease were at a decreased risk of SARS-CoV-2 acquisition., Meaning: These results demonstrate that race/ethnicity and socioeconomic status are not only risk factors for severity of disease but also are the biggest determinants of acquisition of infection. These findings highlight the need to address the consequences of structural racism during the development of mitigation programs for current and future pandemics.

Published
2022
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