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1. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

Author

Yao, Zizhen, van Velthoven, Cindy T. J., Kunst, Michael, Zhang, Meng, McMillen, Delissa, Lee, Changkyu, Jung, Won, Goldy, Jeff, Abdelhak, Aliya, Aitken, Matthew, Baker, Katherine, Baker, Pamela, Barkan, Eliza, Bertagnolli, Darren, Bhandiwad, Ashwin, Bielstein, Cameron, Bishwakarma, Prajal, Campos, Jazmin, Carey, Daniel, Casper, Tamara, Chakka, Anish Bhaswanth, Chakrabarty, Rushil, Chavan, Sakshi, Chen, Min, Clark, Michael, Close, Jennie, Crichton, Kirsten, Daniel, Scott, DiValentin, Peter, Dolbeare, Tim, Ellingwood, Lauren, Fiabane, Elysha, Fliss, Timothy, Gee, James, Gerstenberger, James, Glandon, Alexandra, Gloe, Jessica, Gould, Joshua, Gray, James, Guilford, Nathan, Guzman, Junitta, Hirschstein, Daniel, Ho, Windy, Hooper, Marcus, Huang, Mike, Hupp, Madie, Jin, Kelly, Kroll, Matthew, Lathia, Kanan, Leon, Arielle, Li, Su, Long, Brian, Madigan, Zach, Malloy, Jessica, Malone, Jocelin, Maltzer, Zoe, Martin, Naomi, McCue, Rachel, McGinty, Ryan, Mei, Nicholas, Melchor, Jose, Meyerdierks, Emma, Mollenkopf, Tyler, Moonsman, Skyler, Nguyen, Thuc Nghi, Otto, Sven, Pham, Trangthanh, Rimorin, Christine, Ruiz, Augustin, Sanchez, Raymond, Sawyer, Lane, Shapovalova, Nadiya, Shepard, Noah, Slaughterbeck, Cliff, Sulc, Josef, Tieu, Michael, Torkelson, Amy, Tung, Herman, Valera Cuevas, Nasmil, Vance, Shane, Wadhwani, Katherine, Ward, Katelyn, Levi, Boaz, Farrell, Colin, Young, Rob, Staats, Brian, Wang, Ming-Qiang Michael, Thompson, Carol L., Mufti, Shoaib, Pagan, Chelsea M., Kruse, Lauren, Dee, Nick, Sunkin, Susan M., Esposito, Luke, Hawrylycz, Michael J., Waters, Jack, Ng, Lydia, Smith, Kimberly, Tasic, Bosiljka, Zhuang, Xiaowei, and Zeng, Hongkui

Published
2023
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2. Molecular hallmarks of Alzheimer’s disease with a multimodal single cell atlas of the cortex

Author

Travaglini, Kyle J, primary, Gabitto, Mariano I, additional, Ariza, Jeanelle, additional, Ding, Yi, additional, Mahoney, Joseph T, additional, Casper, Tamara, additional, Chakrabarty, Rushil, additional, Clark, Michael, additional, Crane, Paul K, additional, Dee, Nick, additional, Ferrer, Rebecca, additional, Gatto, Nicole M, additional, Gloe, Jessica, additional, Goldy, Jeff, additional, Grabowski, Thomas J, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hawrylycz, Michael J, additional, Hodge, Rebecca D, additional, Jayadev, Suman, additional, Kaplan, Eitan S, additional, Keene, C Dirk, additional, Larson, Eric B, additional, Latimer, Caitlin S, additional, Levi, Boaz P, additional, Melief, Erica J, additional, Meyerdierks, Emma, additional, Mukherjee, Shubhabrata, additional, Pham, Thanh, additional, Rachleff, Victoria M, additional, Smith, Kimberly, additional, Torkelson, Amy, additional, Lein, Ed S, additional, and Miller, Jeremy A, additional

Published
2023
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3. Multimodal and multiregional atlas of Alzheimer’s disease changes

Author

Gabitto, Mariano I, primary, Travaglini, Kyle J, additional, Ariza, Jeanelle, additional, Close, Jennie, additional, Ding, Yi, additional, Long, Brian, additional, Rachleff, Victoria M, additional, Chakrabarty, Rushil, additional, Crane, Paul K, additional, Ferrer, Rebecca, additional, Gatto, Nicole M, additional, Goldy, Jeff, additional, Grabowski, Thomas J, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hawrylycz, Michael J, additional, Hodge, Rebecca D, additional, Jayadev, Suman, additional, Kaplan, Eitan S, additional, Keene, C Dirk, additional, Larson, Eric B, additional, Latimer, Caitlin S, additional, Levi, Boaz P, additional, Mahoney, Joseph T, additional, Melief, Erica J, additional, Miller, Jeremy A, additional, Mukherjee, Shubhabrata, additional, Pham, Thanh, additional, Smith, Kimberly, additional, Torkelson, Amy, additional, Chakka, Anish Bhaswanth, additional, and Lein, Ed S, additional

Published
2023
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4. Cell-type specific molecular signatures of aging revealed in a brain-wide transcriptomic cell-type atlas

Author

Jin, Kelly, primary, Yao, Zizhen, additional, van Velthoven, Cindy T. J., additional, Kaplan, Eitan S., additional, Glattfelder, Katie, additional, Barlow, Samuel T., additional, Boyer, Gabriella, additional, Carey, Daniel, additional, Casper, Tamara, additional, Chakka, Anish Bhaswanth, additional, Chakrabarty, Rushil, additional, Clark, Michael, additional, Departee, Max, additional, Desierto, Marie, additional, Gary, Amanda, additional, Gloe, Jessica, additional, Goldy, Jeff, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hirschstein, Daniel, additional, Lee, Changkyu, additional, Liang, Elizabeth, additional, Pham, Trangthanh, additional, Reding, Melissa, additional, Ronellenfitch, Kara, additional, Ruiz, Augustin, additional, Sevigny, Josh, additional, Shapovalova, Nadiya, additional, Shulga, Lyudmila, additional, Sulc, Josef, additional, Torkelson, Amy, additional, Tung, Herman, additional, Levi, Boaz, additional, Sunkin, Susan M., additional, Dee, Nick, additional, Esposito, Luke, additional, Smith, Kimberly, additional, Tasic, Bosiljka, additional, and Zeng, Hongkui, additional

Published
2023
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5. Integrated multimodal cell atlas of Alzheimer’s disease

Author

Gabitto, Mariano, primary, Travaglini, Kyle, additional, Ariza, Jeannelle, additional, Kaplan, Eitan, additional, Long, Brian, additional, Rachleff, Victoria, additional, Ding, Yi, additional, Mahoney, Joseph, additional, Dee, Nick, additional, Goldy, Jeff, additional, Melief, Erica, additional, Brouner, Krissy, additional, Compos, Jazmin, additional, Campos, John, additional, Carr, Ambrose, additional, Casper, Tamara, additional, Chakrabarty, Rushil, additional, Clark, Michael, additional, Cool, Jonah, additional, Dalley, Rachel, additional, Darvas, Martin, additional, Dolbeare, Tim, additional, Ding, Song-Lin, additional, Egdorf, Tom, additional, Esposito, Luke, additional, Ferrer, Rebecca, additional, Gala, Rohan, additional, Gary, Amanda, additional, Gloe, Jessica, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Ho, Windy, additional, Jarsky, Tim, additional, Johansen, Nelson, additional, Kalmbach, Brian, additional, Keene, Lisa, additional, Khawand, Sarah, additional, Kilgore, Mitchell, additional, Kirkland, Amanda, additional, Kunst, Michael, additional, Lee, Brian, additional, Donald, Christine Mac, additional, Malone, Jocelin, additional, Maltzer, Zoe, additional, Martin, Naomi, additional, McCue, Rachel, additional, McMillen, Delissa, additional, Meyerdierks, Emma, additional, Meyers, Kelly, additional, Mollenkopf, Tyler, additional, Montine, Mark, additional, Nolan, Amber, additional, Nyhus, Julie, additional, Olsen, Paul, additional, Pacleb, Maiya, additional, Pham, Trangthanh, additional, Pom, Christina, additional, Postupna, Nadia, additional, Ruiz, Augustin, additional, Schantz, Aimee, additional, Sorensen, Staci, additional, Staats, Brian, additional, Sullivan, Matt, additional, Sunkin, Susan, additional, Thompson, Carol, additional, Tieu, Michael, additional, Ting, Jonathan, additional, Torkelson, Amy, additional, Tran, Tracy, additional, Cuevas, Nasmil Valera, additional, Wang, Ming-Qiang, additional, Waters, Jack, additional, Wilson, Angela, additional, Haynor, David, additional, Gatto, Nicole, additional, Jayadev, Suman, additional, Mufti, Shoaib, additional, Ng, Lydia, additional, Mukherjee, Shubhabrata, additional, Crane, Paul, additional, Latimer, Caitlin, additional, Levi, Boaz, additional, Smith, Kimberly, additional, Close, Jennie, additional, Miller, Jeremy, additional, Hodge, Rebecca, additional, Larson, Eric, additional, Grabowski, Thomas, additional, Hawrylycz, Michael, additional, Keene, C., additional, and Lein, Ed, additional

Published
2023
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6. Integrated multimodal cell atlas of Alzheimer’s disease

Author

Gabitto, Mariano I., primary, Travaglini, Kyle J., additional, Rachleff, Victoria M., additional, Kaplan, Eitan S., additional, Long, Brian, additional, Ariza, Jeanelle, additional, Ding, Yi, additional, Mahoney, Joseph T., additional, Dee, Nick, additional, Goldy, Jeff, additional, Melief, Erica J., additional, Brouner, Krissy, additional, Campos, Jazmin, additional, Campos, John, additional, Carr, Ambrose J., additional, Casper, Tamara, additional, Chakrabarty, Rushil, additional, Clark, Michael, additional, Cool, Jonah, additional, Valera Cuevas, Nasmil J., additional, Dalley, Rachel, additional, Darvas, Martin, additional, Ding, Song-Lin, additional, Dolbeare, Tim, additional, Mac Donald, Christine L., additional, Egdorf, Tom, additional, Esposito, Luke, additional, Ferrer, Rebecca, additional, Gala, Rohan, additional, Gary, Amanda, additional, Gloe, Jessica, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hirschstein, Daniel, additional, Ho, Windy, additional, Jarksy, Tim, additional, Johansen, Nelson, additional, Kalmbach, Brian E., additional, Keene, Lisa M., additional, Khawand, Sarah, additional, Kilgore, Mitch, additional, Kirkland, Amanda, additional, Kunst, Michael, additional, Lee, Brian R., additional, Malone, Jocelin, additional, Maltzer, Zoe, additional, Martin, Naomi, additional, McCue, Rachel, additional, McMillen, Delissa, additional, Meyerdierks, Emma, additional, Meyers, Kelly P., additional, Mollenkopf, Tyler, additional, Montine, Mark, additional, Nolan, Amber L., additional, Nyhus, Julie, additional, Olsen, Paul A., additional, Pacleb, Maiya, additional, Peña, Nicholas, additional, Pham, Thanh, additional, Pom, Christina Alice, additional, Postupna, Nadia, additional, Ruiz, Augustin, additional, Schantz, Aimee M., additional, Shapovalova, Nadiya V., additional, Sorensen, Staci A., additional, Staats, Brian, additional, Sullivan, Matt, additional, Sunkin, Susan M., additional, Thompson, Carol, additional, Tieu, Michael, additional, Ting, Jonathan, additional, Torkelson, Amy, additional, Tran, Tracy, additional, Wang, Ming-Qiang, additional, Waters, Jack, additional, Wilson, Angela M., additional, Haynor, David, additional, Gatto, Nicole, additional, Jayadev, Suman, additional, Mufti, Shoaib, additional, Ng, Lydia, additional, Mukherjee, Shubhabrata, additional, Crane, Paul K., additional, Latimer, Caitlin S., additional, Levi, Boaz P., additional, Smith, Kimberly, additional, Close, Jennie L., additional, Miller, Jeremy A., additional, Hodge, Rebecca D., additional, Larson, Eric B., additional, Grabowski, Thomas J., additional, Hawrylycz, Michael, additional, Dirk Keene, C., additional, and Lein, Ed S., additional

Published
2023
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7. Integrated multimodal cell atlas of Alzheimer’s disease

Author

Gabitto, Mariano I., Travaglini, Kyle J., Rachleff, Victoria M., Kaplan, Eitan S., Long, Brian, Ariza, Jeanelle, Ding, Yi, Mahoney, Joseph T., Dee, Nick, Goldy, Jeff, Melief, Erica J., Agrawal, Anamika, Kana, Omar, Zhen, Xingjian, Barlow, Samuel T., Brouner, Krissy, Campos, Jazmin, Campos, John, Carr, Ambrose J., Casper, Tamara, Chakrabarty, Rushil, Clark, Michael, Cool, Jonah, Dalley, Rachel, Darvas, Martin, Ding, Song-Lin, Dolbeare, Tim, Egdorf, Tom, Esposito, Luke, Ferrer, Rebecca, Fleckenstein, Lynn E., Gala, Rohan, Gary, Amanda, Gelfand, Emily, Gloe, Jessica, Guilford, Nathan, Guzman, Junitta, Hirschstein, Daniel, Ho, Windy, Hupp, Madison, Jarsky, Tim, Johansen, Nelson, Kalmbach, Brian E., Keene, Lisa M., Khawand, Sarah, Kilgore, Mitchell D., Kirkland, Amanda, Kunst, Michael, Lee, Brian R., Leytze, Mckaila, Mac Donald, Christine L., Malone, Jocelin, Maltzer, Zoe, Martin, Naomi, McCue, Rachel, McMillen, Delissa, Mena, Gonzalo, Meyerdierks, Emma, Meyers, Kelly P., Mollenkopf, Tyler, Montine, Mark, Nolan, Amber L., Nyhus, Julie K., Olsen, Paul A., Pacleb, Maiya, Pagan, Chelsea M., Peña, Nicholas, Pham, Trangthanh, Pom, Christina Alice, Postupna, Nadia, Rimorin, Christine, Ruiz, Augustin, Saldi, Giuseppe A., Schantz, Aimee M., Shapovalova, Nadiya V., Sorensen, Staci A., Staats, Brian, Sullivan, Matt, Sunkin, Susan M., Thompson, Carol, Tieu, Michael, Ting, Jonathan T., Torkelson, Amy, Tran, Tracy, Valera Cuevas, Nasmil J., Walling-Bell, Sarah, Wang, Ming-Qiang, Waters, Jack, Wilson, Angela M., Xiao, Ming, Haynor, David, Gatto, Nicole M., Jayadev, Suman, Mufti, Shoaib, Ng, Lydia, Mukherjee, Shubhabrata, Crane, Paul K., Latimer, Caitlin S., Levi, Boaz P., Smith, Kimberly A., Close, Jennie L., Miller, Jeremy A., Hodge, Rebecca D., Larson, Eric B., Grabowski, Thomas J., Hawrylycz, Michael, Keene, C. Dirk, and Lein, Ed S.

Abstract

Alzheimer’s disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies. This cohort includes 33 male donors and 51 female donors, with an average age at time of death of 88 years. We used quantitative neuropathology to place donors along a disease pseudoprogression score. Pseudoprogression analysis revealed two disease phases: an early phase with a slow increase in pathology, presence of inflammatory microglia, reactive astrocytes, loss of somatostatin+inhibitory neurons, and a remyelination response by oligodendrocyte precursor cells; and a later phase with exponential increase in pathology, loss of excitatory neurons and Pvalb+and Vip+inhibitory neuron subtypes. These findings were replicated in other major AD studies.

Published
2024
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8. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

Author

Yao, Zizhen, primary, van Velthoven, Cindy T. J., additional, Kunst, Michael, additional, Zhang, Meng, additional, McMillen, Delissa, additional, Lee, Changkyu, additional, Jung, Won, additional, Goldy, Jeff, additional, Abdelhak, Aliya, additional, Baker, Pamela, additional, Barkan, Eliza, additional, Bertagnolli, Darren, additional, Campos, Jazmin, additional, Carey, Daniel, additional, Casper, Tamara, additional, Chakka, Anish Bhaswanth, additional, Chakrabarty, Rushil, additional, Chavan, Sakshi, additional, Chen, Min, additional, Clark, Michael, additional, Close, Jennie, additional, Crichton, Kirsten, additional, Daniel, Scott, additional, Dolbeare, Tim, additional, Ellingwood, Lauren, additional, Gee, James, additional, Glandon, Alexandra, additional, Gloe, Jessica, additional, Gould, Joshua, additional, Gray, James, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hirschstein, Daniel, additional, Ho, Windy, additional, Jin, Kelly, additional, Kroll, Matthew, additional, Lathia, Kanan, additional, Leon, Arielle, additional, Long, Brian, additional, Maltzer, Zoe, additional, Martin, Naomi, additional, McCue, Rachel, additional, Meyerdierks, Emma, additional, Nguyen, Thuc Nghi, additional, Pham, Trangthanh, additional, Rimorin, Christine, additional, Ruiz, Augustin, additional, Shapovalova, Nadiya, additional, Slaughterbeck, Cliff, additional, Sulc, Josef, additional, Tieu, Michael, additional, Torkelson, Amy, additional, Tung, Herman, additional, Cuevas, Nasmil Valera, additional, Wadhwani, Katherine, additional, Ward, Katelyn, additional, Levi, Boaz, additional, Farrell, Colin, additional, Thompson, Carol L., additional, Mufti, Shoaib, additional, Pagan, Chelsea M., additional, Kruse, Lauren, additional, Dee, Nick, additional, Sunkin, Susan M., additional, Esposito, Luke, additional, Hawrylycz, Michael J., additional, Waters, Jack, additional, Ng, Lydia, additional, Smith, Kimberly A., additional, Tasic, Bosiljka, additional, Zhuang, Xiaowei, additional, and Zeng, Hongkui, additional

Published
2023
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9. A multimodal atlas of the molecular and cellular changes to cortex driven by Alzheimer’s disease

Author

Travaglini, Kyle J, primary, Gabitto, Mariano, additional, Ding, Yi, additional, Ariza, Jeanelle, additional, Chakrabarty, Rushil, additional, Crane, Paul K., additional, Ferrer, Rebecca, additional, Goldy, Jeff, additional, Grabowski, Thomas J, additional, Guilford, Nathan, additional, Guzman, Junitta, additional, Hawrylycz, Michael J, additional, Hodge, Rebecca D, additional, Jayadev, Suman, additional, Kaplan, Eitan S, additional, Keene, C Dirk, additional, Larson, Eric B, additional, Latimer, Caitlin S, additional, Levi, Boaz, additional, Mahoney, Joseph, additional, Melief, Erica J, additional, Mukherjee, Shubhabrata, additional, Pham, Thanh, additional, Rachleff, Victoria M, additional, Smith, Kimberly A, additional, Torkelson, Amy, additional, Lein, Ed S, additional, and Miller, Jeremy A, additional

Published
2022
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10. Inter-individual variation in human cortical cell type abundance and expression

Author

Johansen, Nelson, primary, Somasundaram, Saroja, additional, Travaglini, Kyle J., additional, Yanny, Anna Marie, additional, Shumyatcher, Maya, additional, Casper, Tamara, additional, Cobbs, Charles, additional, Dee, Nick, additional, Ellenbogen, Richard, additional, Ferreira, Manuel, additional, Goldy, Jeff, additional, Guzman, Junitta, additional, Gwinn, Ryder, additional, Hirschstein, Daniel, additional, Jorstad, Nikolas L., additional, Keene, C. Dirk, additional, Ko, Andrew, additional, Levi, Boaz P., additional, Ojemann, Jeffrey G., additional, Pham, Thanh, additional, Shapovalova, Nadiya, additional, Silbergeld, Daniel, additional, Sulc, Josef, additional, Torkelson, Amy, additional, Tung, Herman, additional, Smith, Kimberly, additional, Lein, Ed S., additional, Bakken, Trygve E., additional, Hodge, Rebecca D., additional, and Miller, Jeremy A., additional

Published
2022
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11. Anthranilic amide and imidazobenzothiadiazole compounds disrupt Mycobacterium tuberculosis membrane potential† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c9md00088g

Author

Smith, Jake, Wescott, Heather, Early, Julie, Mullen, Steven, Guzman, Junitta, Odingo, Joshua, Lamar, Jason, and Parish, Tanya

Subjects
Chemistry
Abstract

Compounds 1 and 2 disrupt M. tuberculosis membrane potential and demonstrate bactericidal activity against non-replicating M. tuberculosis in pH 4.5 buffer., A family of compounds typified by an anthranilic amide 1 was identified from a whole-cell screening effort targeted at identifying compounds that disrupt pH homeostasis in Mycobacterium tuberculosis. 1 demonstrated bactericidal activity against non-replicating M. tuberculosis in pH 4.5 buffer (MBC4.5 = 6.3 μM). Exploration of the structure–activity relations failed to simplify the scaffold. The antitubercular activity proved dependent on the lipophilicity and planarity of the molecule and directly correlated with mammalian cytotoxicity. Further studies revealed a pH-dependent correlation between the family's disruption of M. tuberculosis membrane potential and antitubercular activity, with active compounds causing a drop in membrane potential at concentrations below their MBC4.5. A second compound family, identified in the same screening effort and typified by imidazo(4,5-e)(2,1,3)benzothiadiazole 2, provided a contrasting profile. As with 1, structure–activity profiling of 2 (MBC4.5 = 25 μM) failed to minimize the initial scaffold, mammalian cytotoxicity was observed for a majority of the active compounds, and many of the active compounds disrupted M. tuberculosis membrane potential. However, unlike the anthranilic amide compounds, the benzothiadiazole compounds disrupted M. tuberculosis membrane potential primarily at concentrations above the MBC4.5 in a pH-independent fashion. These differences suggest an alternative mechanism of action for the benzothiadiazole compounds. As a result, while the cytotoxicity of the anthranilic amides limits their utility to tool compounds, benzothiadiazole 2 presents an attractive target for more focused SAR exploration.

Published
2019

12. INTER-INDIVIDUAL VARIATION IN HUMAN CORTICAL CELL TYPE ABUNDANCE AND EXPRESSION

Author

Johansen, Nelson, Somasundaram, Saroja, Travaglini, Kyle, Yanny, Anna Marie, Shumyatcher, Maya, Casper, Tamara, Cobbs, Charles, Dee, Nick, Ellenbogen, Richard, Ferreira, Manuel, Goldy, Jeff, Guzman, Junitta, Gwinn, Ryder, Hirschstein, Daniel, Jorstad, Nikolas, Keene, C. Dirk, Ko, Andrew, Levi, Boaz, Ojemann, Jeffrey, Pham, Thanh, Shapovalova, Nadiya, Silbergeld, Daniel, Sulc, Josef, Torkelson, Amy, Tung, Herman, Smith, Kimberly, Lein, Ed, Bakken, Trygve, Hodge, Rebecca, and Miller, Jeremy

Published
2023
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13. Novel Trifluoromethyl Pyrimidinone Compounds With Activity Against Mycobacterium tuberculosis

Author

Hembre, Erik, primary, Early, Julie V., additional, Odingo, Joshua, additional, Shelton, Catherine, additional, Anoshchenko, Olena, additional, Guzman, Junitta, additional, Flint, Lindsay, additional, Dennison, Devon, additional, McNeil, Matthew B., additional, Korkegian, Aaron, additional, Ovechkina, Yulia, additional, Ornstein, Paul, additional, Masquelin, Thierry, additional, Hipskind, Philip A., additional, and Parish, Tanya, additional

Published
2021
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14. A New Class of Linezolid‐Based Molecules as Potential Antimicrobial and Antitubercular Agents: A Rational Approach

Author

Kushwaha, Babita, primary, Kushwaha, Narva Deshwar, additional, Parish, Tanya, additional, Guzman, Junitta, additional, Kajee, Afsana, additional, Shaikh, Mahamadhanif S., additional, Kehinde, Idowu, additional, Obakachi, Vincent A., additional, Pathan, Tabasum Khan, additional, Shinde, Suraj Raosaheb, additional, and Karpoormath, Rajshekhar, additional

Published
2021
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16. 8‐Hydroxyquinolines are bactericidal againstMycobacterium tuberculosis

Author

Odingo, Joshua O., primary, Early, Julie V., additional, Smith, Jake, additional, Johnson, James, additional, Bailey, Mai A., additional, Files, Megan, additional, Guzman, Junitta, additional, Ollinger, Juliane, additional, Korkegian, Aaron, additional, Kumar, Anuradha, additional, Ovechkina, Yulia, additional, and Parish, Tanya, additional

Published
2019
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18. SEA‐AD: Scientific analysis and open access resources targeting early changes in Alzheimer's disease.

Author

Miller, Jeremy A, Hawrylycz, Michael J, Aitken, Matthew, Ariza, Jeannelle, Chakrabarty, Rushil, Ding, Song‐Lin, Ding, Yi, Ferrer, Rebecca, Goldy, Jeff, Gratiy, Sergey, Guilford, Nathan, Guzman, Junitta, Kaplan, Eitan S, Mei, Nicholas, Melief, Erica J, Nyhus, Julie, Pham, Thanh, Rachleff, Victoria M, Samson, Jake, and Smith, Kimberly

Abstract

Background: Alzheimer's disease (AD) is the most common form of dementia, representing ∼70% of all dementia cases, and affecting much of the aged population. Currently our understanding of AD neuropathology is largely centered on characteristic deposition of certain neuropathological proteins and identification of histologically defined neuronal populations. Molecular tools to characterize the transcriptome, epigenome, and spatial organization of single cells in complex brain tissues allow a more refined look at how the neurotypical brain changes in AD than had been possible previously. Linking molecular, cellular, genomic, cognitive, and pathological indicators of AD progression will be essential for understanding disease mechanisms. Methods: The Seattle Alzheimer's Disease Brain Cell Atlas (SEA‐AD) brings together experts in AD research and large‐scale molecular/anatomical brain mapping to modernize AD tissue banking methods, and to combine traditional and quantitative neuropathology with emerging genotyping, single nucleus transcriptomics, single nucleus epigenomics, and spatial transcriptomics technologies. Applied to multiple brain regions in donors spanning different stages of AD pathology, these techniques will identification of cell type specific molecular pathways and yield valuable insights into selective vulnerability or resistance to pathology. Two well characterized cohorts (Adult Changes in Thought (ACT) and the University of Washington ADRC) provided 84 subjects of varying degrees of AD severity, including cognitively normal subjects. Results: The initial focus of SEA‐AD was on integrating and interpreting relationships between all collected multimodal data in middle temporal gyrus (MTG). Identified cell types and molecular pathways of interest are presented separately and are both consistent with and expand upon results found from ROSMAP and other cohorts. The complete SEA‐AD MTG atlas is now freely and publicly available at brain‐map.org and includes access to all data and associated donor metadata, tools for visualization and exploration of molecular data, exploration of pathology images, a tool for assigning cell types to community‐based ‐omics datasets, comprehensive documentation, and user support. Conclusions: SEA‐AD has developed a high resolution, high‐quality, publicly accessible atlas of aging and AD, and is designed to better understand the complex and likely heterogenous nature of AD. [ABSTRACT FROM AUTHOR]

Published
2023
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19. 8‐Hydroxyquinolines are bactericidal against Mycobacterium tuberculosis.

Author

Odingo, Joshua O., Early, Julie V., Smith, Jake, Johnson, James, Bailey, Mai A., Files, Megan, Guzman, Junitta, Ollinger, Juliane, Korkegian, Aaron, Kumar, Anuradha, Ovechkina, Yulia, and Parish, Tanya

Subjects
MYCOBACTERIUM tuberculosis, STRUCTURE-activity relationships, TUBERCULOSIS
Abstract

There is an urgent need for new treatments effective against Mycobacterium tuberculosis, the causative agent of tuberculosis. The 8‐hydroxyquinoline series is a privileged scaffold with anticancer, antifungal, and antibacterial activities. We conducted a structure–activity relationship study of the series regarding its antitubercular activity using 26 analogs. The 8‐hydroxyquinolines showed good activity against M. tuberculosis, with minimum inhibitory concentrations (MIC90) of <5 μM for some analogs. Small substitutions at C5 resulted in the most potent activity. Substitutions at C2 generally decreased potency, although a sub‐family of 2‐styryl‐substituted analogs retained activity. Representative compounds demonstrated bactericidal activity against replicating M. tuberculosis with >4 log kill at 10× MIC over 14 days. The majority of the compounds demonstrated cytotoxicity (IC50 of <100 μM). Further development of this series as antitubercular agents should address the cytotoxicity liability. However, the 8‐hydroxyquinoline series represents a useful tool for chemical genomics to identify novel targets in M. tuberculosis. [ABSTRACT FROM AUTHOR]

Published
2019
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20. Interindividual variation in human cortical cell type abundance and expression.

Author

Johansen, Nelson, Somasundaram, Saroja, Travaglini, Kyle J., Yanny, Anna Marie, Shumyatcher, Maya, Casper, Tamara, Cobbs, Charles, Dee, Nick, Ellenbogen, Richard, Ferreira, Manuel, Goldy, Jeff, Guzman, Junitta, Gwinn, Ryder, Hirschstein, Daniel, Jorstad, Nikolas L., Keene, C. Dirk, Ko, Andrew, Levi, Boaz P., Ojemann, Jeffrey G., and ThanhPham

Published
2023
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22. Enhancer AAVs for targeting spinal motor neurons and descending motor pathways in rodents and macaque.

Author

Kussick E, Johansen N, Taskin N, Wynalda B, Martinez R, Groce EL, Reding M, Liang E, Shulga L, Huang C, Casper T, Clark M, Ho W, Gao Y, van Velthoven CTJ, Sobieski C, Ferrer R, Berg MR, Curtis BC, English C, Day JC, Fortuna M, Donadio N, Newman D, Yao S, Chakka AB, Goldy J, Torkelson A, Guzman JB, Chakrabarty R, Nguy B, Guilford N, Pham TH, Wright V, Ronellenfitch K, Gudsnuk K, Thyagarajan B, Smith KA, Dee N, Zeng H, Yao Z, Tasic B, Levi BP, Hodge R, Bakken TE, Lein ES, Ting JT, and Daigle TL

Abstract

Experimental access to cell types within the mammalian spinal cord is severely limited by the availability of genetic tools. To enable access to lower motor neurons (LMNs) and LMN subtypes, which function to integrate information from the brain and control movement through direct innervation of effector muscles, we generated single cell multiome datasets from mouse and macaque spinal cords and discovered putative enhancers for each neuronal population. We cloned these enhancers into adeno-associated viral vectors (AAVs) driving a reporter fluorophore and functionally screened them in mouse. The most promising candidate enhancers were then extensively characterized using imaging and molecular techniques and further tested in rat and macaque to show conservation of LMN labeling. Additionally, we combined enhancer elements into a single vector to achieve simultaneous labeling of upper motor neurons (UMNs) and LMNs. This unprecedented LMN toolkit will enable future investigations of cell type function across species and potential therapeutic interventions for human neurodegenerative diseases., Competing Interests: Declaration of interests T.L.D., B.P.L, B.T., E.S.L, H.Z, J.T.T., N.J., Y.G., Z.Y., are inventors on one or more U.S. provisional patent applications related to this work. All authors declare no other competing interests.

Published
2024
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23. The transcriptomic and spatial organization of telencephalic GABAergic neuronal types.

Author

van Velthoven CTJ, Gao Y, Kunst M, Lee C, McMillen D, Chakka AB, Casper T, Clark M, Chakrabarty R, Daniel S, Dolbeare T, Ferrer R, Gloe J, Goldy J, Guzman J, Halterman C, Ho W, Huang M, James K, Nguy B, Pham T, Ronellenfitch K, Thomas ED, Torkelson A, Pagan CM, Kruse L, Dee N, Ng L, Waters J, Smith KA, Tasic B, Yao Z, and Zeng H

Abstract

The telencephalon of the mammalian brain comprises multiple regions and circuit pathways that play adaptive and integrative roles in a variety of brain functions. There is a wide array of GABAergic neurons in the telencephalon; they play a multitude of circuit functions, and dysfunction of these neurons has been implicated in diverse brain disorders. In this study, we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished by utilizing 611,423 single-cell transcriptomes from the comprehensive and high-resolution transcriptomic and spatial cell type atlas for the adult whole mouse brain we have generated, supplemented with an additional single-cell RNA-sequencing dataset containing 99,438 high-quality single-cell transcriptomes collected from the pre- and postnatal developing mouse brain. We present a hierarchically organized adult telencephalic GABAergic neuronal cell type taxonomy of 7 classes, 52 subclasses, 284 supertypes, and 1,051 clusters, as well as a corresponding developmental taxonomy of 450 clusters across different ages. Detailed charting efforts reveal extraordinary complexity where relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types can often be found in distant and diverse brain regions indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Additionally, we find various spatial dimensions of both discrete and continuous variations among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal and most pallidal GABAergic neuronal types emerge simultaneously during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell type taxonomy can serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community., Competing Interests: Competing Interests H.Z. is on the scientific advisory board of MapLight Therapeutics, Inc. The other authors declare no competing interests.

Published
2024
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24. Cell-type specific molecular signatures of aging revealed in a brain-wide transcriptomic cell-type atlas.

Author

Jin K, Yao Z, van Velthoven CTJ, Kaplan ES, Glattfelder K, Barlow ST, Boyer G, Carey D, Casper T, Chakka AB, Chakrabarty R, Clark M, Departee M, Desierto M, Gary A, Gloe J, Goldy J, Guilford N, Guzman J, Hirschstein D, Lee C, Liang E, Pham T, Reding M, Ronellenfitch K, Ruiz A, Sevigny J, Shapovalova N, Shulga L, Sulc J, Torkelson A, Tung H, Levi B, Sunkin SM, Dee N, Esposito L, Smith K, Tasic B, and Zeng H

Abstract

Biological aging can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function. Aging is a complex and dynamic process which influences distinct cell types in a myriad of ways. The cellular architecture of the mammalian brain is heterogeneous and diverse, making it challenging to identify precise areas and cell types of the brain that are more susceptible to aging than others. Here, we present a high-resolution single-cell RNA sequencing dataset containing ~1.2 million high-quality single-cell transcriptomic profiles of brain cells from young adult and aged mice across both sexes, including areas spanning the forebrain, midbrain, and hindbrain. We find age-associated gene expression signatures across nearly all 130+ neuronal and non-neuronal cell subclasses we identified. We detect the greatest gene expression changes in non-neuronal cell types, suggesting that different cell types in the brain vary in their susceptibility to aging. We identify specific, age-enriched clusters within specific glial, vascular, and immune cell types from both cortical and subcortical regions of the brain, and specific gene expression changes associated with cell senescence, inflammation, decrease in new myelination, and decreased vasculature integrity. We also identify genes with expression changes across multiple cell subclasses, pointing to certain mechanisms of aging that may occur across wide regions or broad cell types of the brain. Finally, we discover the greatest gene expression changes in cell types localized to the third ventricle of the hypothalamus, including tanycytes, ependymal cells, and Tbx3 + neurons found in the arcuate nucleus that are part of the neuronal circuits regulating food intake and energy homeostasis. These findings suggest that the area surrounding the third ventricle in the hypothalamus may be a hub for aging in the mouse brain. Overall, we reveal a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal aging that will serve as a foundation for the investigation of functional changes in the aging process and the interaction of aging and diseases., Competing Interests: Competing Interests H.Z. is on the scientific advisory board of MapLight Therapeutics, Inc. The other authors declare no competing interests.

Published
2023
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25. Integrated multimodal cell atlas of Alzheimer's disease.

Author

Gabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy J, Melief EJ, Brouner K, Campos J, Carr AJ, Casper T, Chakrabarty R, Clark M, Compos J, Cool J, Valera Cuevas NJ, Dalley R, Darvas M, Ding SL, Dolbeare T, Mac Donald CL, Egdorf T, Esposito L, Ferrer R, Gala R, Gary A, Gloe J, Guilford N, Guzman J, Ho W, Jarksy T, Johansen N, Kalmbach BE, Keene LM, Khawand S, Kilgore M, Kirkland A, Kunst M, Lee BR, Malone J, Maltzer Z, Martin N, McCue R, McMillen D, Meyerdierks E, Meyers KP, Mollenkopf T, Montine M, Nolan AL, Nyhus J, Olsen PA, Pacleb M, Pham T, Pom CA, Postupna N, Ruiz A, Schantz AM, Sorensen SA, Staats B, Sullivan M, Sunkin SM, Thompson C, Tieu M, Ting J, Torkelson A, Tran T, Wang MQ, Waters J, Wilson AM, Haynor D, Gatto N, Jayadev S, Mufti S, Ng L, Mukherjee S, Crane PK, Latimer CS, Levi BP, Smith K, Close JL, Miller JA, Hodge RD, Larson EB, Grabowski TJ, Hawrylycz M, Keene CD, and Lein ES

Abstract

Alzheimer's disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research at SEA-AD.org., Competing Interests: Additional Declarations: There is NO Competing Interest.

Published
2023
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26. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain.

Author

Yao Z, van Velthoven CTJ, Kunst M, Zhang M, McMillen D, Lee C, Jung W, Goldy J, Abdelhak A, Baker P, Barkan E, Bertagnolli D, Campos J, Carey D, Casper T, Chakka AB, Chakrabarty R, Chavan S, Chen M, Clark M, Close J, Crichton K, Daniel S, Dolbeare T, Ellingwood L, Gee J, Glandon A, Gloe J, Gould J, Gray J, Guilford N, Guzman J, Hirschstein D, Ho W, Jin K, Kroll M, Lathia K, Leon A, Long B, Maltzer Z, Martin N, McCue R, Meyerdierks E, Nguyen TN, Pham T, Rimorin C, Ruiz A, Shapovalova N, Slaughterbeck C, Sulc J, Tieu M, Torkelson A, Tung H, Cuevas NV, Wadhwani K, Ward K, Levi B, Farrell C, Thompson CL, Mufti S, Pagan CM, Kruse L, Dee N, Sunkin SM, Esposito L, Hawrylycz MJ, Waters J, Ng L, Smith KA, Tasic B, Zhuang X, and Zeng H

Abstract

The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain., Competing Interests: Competing Interests X.Z. is a co-founder and consultant of Vizgen.

Published
2023
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