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2. Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment

Author

Massachusetts Institute of Technology. Department of Biology, Hodis, Eran, Triglia, Elena Torlai, Kwon, John YH, Biancalani, Tommaso, Zakka, Labib R, Parkar, Saurabh, Hütter, Jan-Christian, Buffoni, Lorenzo, Delorey, Toni M, Phillips, Devan, Dionne, Danielle, Nguyen, Lan T, Schapiro, Denis, Maliga, Zoltan, Jacobson, Connor A, Hendel, Ayal, Rozenblatt-Rosen, Orit, Mihm, Martin C, Garraway, Levi A, Regev, Aviv, Massachusetts Institute of Technology. Department of Biology, Hodis, Eran, Triglia, Elena Torlai, Kwon, John YH, Biancalani, Tommaso, Zakka, Labib R, Parkar, Saurabh, Hütter, Jan-Christian, Buffoni, Lorenzo, Delorey, Toni M, Phillips, Devan, Dionne, Danielle, Nguyen, Lan T, Schapiro, Denis, Maliga, Zoltan, Jacobson, Connor A, Hendel, Ayal, Rozenblatt-Rosen, Orit, Mihm, Martin C, Garraway, Levi A, and Regev, Aviv

Abstract

Establishing causal relationships between genetic alterations of human cancers and specific phenotypes of malignancy remains a challenge. We sequentially introduced mutations into healthy human melanocytes in up to five genes spanning six commonly disrupted melanoma pathways, forming nine genetically distinct cellular models of melanoma. We connected mutant melanocyte genotypes to malignant cell expression programs in vitro and in vivo, replicative immortality, malignancy, rapid tumor growth, pigmentation, metastasis, and histopathology. Mutations in malignant cells also affected tumor microenvironment composition and cell states. Our melanoma models shared genotype-associated expression programs with patient melanomas, and a deep learning model showed that these models partially recapitulated genotype-associated histopathological features as well. Thus, a progressive series of genome-edited human cancer models can causally connect genotypes carrying multiple mutations to phenotype.

Published
2023

3. Cell-type specialization is encoded by specific chromatin topologies

Author

Winick-Ng, Warren, Kukalev, Alexander, Harabula, Izabela, Zea-Redondo, Luna, Szab��, Dominik, Meijer, Mandy, Serebreni, Leonid, Zhang, Yingnan, Bianco, Simona, Chiariello, Andrea M, Irastorza-Azcarate, Ibai, Thieme, Christoph J, Sparks, Thomas M, Carvalho, S��lvia, Fiorillo, Luca, Musella, Francesco, Irani, Ehsan, Triglia, Elena Torlai, Kolodziejczyk, Aleksandra A, Abentung, Andreas, Apostolova, Galina, Paul, Eleanor J, Franke, Vedran, Kempfer, Rieke, Akalin, Altuna, Teichmann, Sarah, Dechant, Georg, Ungless, Mark A, Nicodemi, Mario, Welch, Lonnie, Castelo-Branco, Gon��alo, Pombo, Ana, Winick-Ng, Warren [0000-0002-8716-5558], Meijer, Mandy [0000-0003-3314-1224], Bianco, Simona [0000-0001-5819-060X], Chiariello, Andrea M [0000-0002-6112-0167], Thieme, Christoph J [0000-0002-1566-0971], Fiorillo, Luca [0000-0003-2967-0123], Triglia, Elena Torlai [0000-0002-6059-0116], Paul, Eleanor J [0000-0003-1183-9285], Franke, Vedran [0000-0003-3606-6792], Akalin, Altuna [0000-0002-0468-0117], Teichmann, Sarah [0000-0002-6294-6366], Castelo-Branco, Gonçalo [0000-0003-2247-9393], Pombo, Ana [0000-0002-7493-6288], Apollo - University of Cambridge Repository, UCIBIO - Applied Molecular Biosciences Unit, DCV - Departamento de Ciências da Vida, Winick-Ng, W., Kukalev, A., Harabula, I., Zea-Redondo, L., Szabo, D., Meijer, M., Serebreni, L., Zhang, Y., Bianco, S., Chiariello, A. M., Irastorza-Azcarate, I., Thieme, C. J., Sparks, T. M., Carvalho, S., Fiorillo, L., Musella, F., Irani, E., Triglia, E. T., Kolodziejczyk, A. A., Abentung, A., Apostolova, G., Paul, E. J., Franke, V., Kempfer, R., Akalin, A., Teichmann, S. A., Dechant, G., Ungless, M. A., Nicodemi, M., Welch, L., Castelo-Branco, G., Pombo, A., Torlai Triglia, Elena [0000-0002-6059-0116], and Teichmann, Sarah A [0000-0002-6294-6366]

Subjects
Male, Genetics of the nervous system, Cells, Molecular Conformation, 45/22, Nucleic Acid Denaturation, Chromosomes, 38/91, 14/32, Mice, 14/56, 13/100, 38/23, 631/208/200, Animals, 14/19, General, Neurons, Nuclear organization, Binding Sites, 45, article, Brain, polymer physics, Chromatin Assembly and Disassembly, Regulatory networks, Chromatin, Chromatin architecture, Gene regulation, Computer models of chromosome, 13/31, Gene Expression Regulation, Genes, 631/553/2711, Cardiovascular and Metabolic Diseases, Multigene Family, 14/63, 631/114/2401, 38/77, Data integration, 631/337/386, 64/60, Technology Platforms, 119, 631/378/2583, Transcription Factors
Abstract

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1–3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4–6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased probability of co-segregation of contacting loci across a collection of nuclear slices. ImmunoGAM expands the scope of GAM to enable the selection of specific cell types using low cell numbers (approximately 1,000 cells) within a complex tissue and avoids tissue dissociation2,10. We report cell-type specialized 3D chromatin structures at multiple genomic scales that relate to patterns of gene expression. We discover extensive ‘melting’ of long genes when they are highly expressed and/or have high chromatin accessibility. The contacts most specific of neuron subtypes contain genes associated with specialized processes, such as addiction and synaptic plasticity, which harbour putative binding sites for neuronal transcription factors within accessible chromatin regions. Moreover, sensory receptor genes are preferentially found in heterochromatic compartments in brain cells, which establish strong contacts across tens of megabases. Our results demonstrate that highly specific chromatin conformations in brain cells are tightly related to gene regulation mechanisms and specialized functions., A new technique called immunoGAM, which combines genome architecture mapping (GAM) with immunoselection, enabled the discovery of specialized chromatin conformations linked to gene expression in specific cell populations from mouse brain tissues.

Published
2021

4. Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment

Author

Hodis, Eran, primary, Triglia, Elena Torlai, additional, Kwon, John Y. H., additional, Biancalani, Tommaso, additional, Zakka, Labib R., additional, Parkar, Saurabh, additional, Hütter, Jan-Christian, additional, Buffoni, Lorenzo, additional, Delorey, Toni M., additional, Phillips, Devan, additional, Dionne, Danielle, additional, Nguyen, Lan T., additional, Schapiro, Denis, additional, Maliga, Zoltan, additional, Jacobson, Connor A., additional, Hendel, Ayal, additional, Rozenblatt-Rosen, Orit, additional, Mihm, Martin C., additional, Garraway, Levi A., additional, and Regev, Aviv, additional

Published
2022
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5. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Author

Muus, Christoph, Luecken, Malte D., Eraslan, Gokcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit Dhaval, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik A., Duong, Elizabeth Thu, Fiskin, Evgenij, Triglia, Elena Torlai, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam L., Chung, Hattie, Montoro, Daniel T., Adams, Taylor, Aliee, Hananeh, Allon, Samuel J., Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Becavin, Christophe, Benhar, Inbal, Bergenstrahle, Joseph, Bergenstrahle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh T., Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David S., Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin J., Habermann, Arun C., Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros S., Kuo, Christin S., Larsson, Ludvig, Leney-Greene, Michael A., Lim, Kyungtae, Litvinukova, Monika, Ludwig, Leif S., Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph H., Mbano, Ian M., McAdams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Penland, Lolita, Poirion, Olivier B., Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas C., Shea, Conor, Shi, Xingyi, Sinha, Rahul, Sit, Rene, Slowikowski, Kamil, Slyper, Michal, Smith, Neal P., Sountoulidis, Alex, Strunz, Maximilian, Sullivan, Travis B., Sun, Dawei, Talavera-Lopez, Carlos, Tan, Peng, Tantivit, Jessica, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Waldman, Julia, Wang, Xiuting, Xu, Ke, Yan, Wenjun, Zhao, William, Ziegler, Carly G. K., Muus, Christoph, Luecken, Malte D., Eraslan, Gokcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit Dhaval, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik A., Duong, Elizabeth Thu, Fiskin, Evgenij, Triglia, Elena Torlai, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam L., Chung, Hattie, Montoro, Daniel T., Adams, Taylor, Aliee, Hananeh, Allon, Samuel J., Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Becavin, Christophe, Benhar, Inbal, Bergenstrahle, Joseph, Bergenstrahle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh T., Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David S., Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin J., Habermann, Arun C., Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros S., Kuo, Christin S., Larsson, Ludvig, Leney-Greene, Michael A., Lim, Kyungtae, Litvinukova, Monika, Ludwig, Leif S., Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph H., Mbano, Ian M., McAdams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Penland, Lolita, Poirion, Olivier B., Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas C., Shea, Conor, Shi, Xingyi, Sinha, Rahul, Sit, Rene, Slowikowski, Kamil, Slyper, Michal, Smith, Neal P., Sountoulidis, Alex, Strunz, Maximilian, Sullivan, Travis B., Sun, Dawei, Talavera-Lopez, Carlos, Tan, Peng, Tantivit, Jessica, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Waldman, Julia, Wang, Xiuting, Xu, Ke, Yan, Wenjun, Zhao, William, and Ziegler, Carly G. K.

Abstract

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2(+)TMPRSS2(+) cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention. An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

Published
2021
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6. Cell-type specialization in the brain is encoded by specific long-range chromatin topologies

Author

Winick-Ng, Warren, primary, Kukalev, Alexander, additional, Harabula, Izabela, additional, Redondo, Luna Zea, additional, Szabo, Dominik, additional, Meijer, Mandy, additional, Serebreni, Leonid, additional, Zhang, Yingnan, additional, Bianco, Simona, additional, Chiariello, Andrea M., additional, Irastorza-Azcarate, Ibai, additional, Fiorillo, Luca, additional, Musella, Francesco, additional, Thieme, Christoph J., additional, Irani, Ehsan, additional, Triglia, Elena Torlai, additional, Kolodziejczyk, Aleksandra A., additional, Abentung, Andreas, additional, Apostolova, Galina, additional, Paul, Eleanor J., additional, Franke, Vedran, additional, Kempfer, Rieke, additional, Akalin, Altuna, additional, Teichmann, Sarah A., additional, Dechant, Georg, additional, Ungless, Mark A., additional, Nicodemi, Mario, additional, Welch, Lonnie, additional, Castelo-Branco, Gonçalo, additional, and Pombo, Ana, additional

Published
2020
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8. Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression.

Author

Kar, Gozde, Jong Kyoung Kim, Kolodziejczyk, Aleksandra A., Natarajan, Kedar Nath, Triglia, Elena Torlai, Mifsud, Borbala, Elderkin, Sarah, Marioni, John C., Pombo, Ana, and Teichmann, Sarah A.

Abstract

Polycomb repressive complexes (PRCs) are important histone modifiers, which silence gene expression; yet, there exists a subset of PRC-bound genes actively transcribed by RNA polymerase II (RNAPII). It is likely that the role of Polycomb repressive complex is to dampen expression of these PRC-active genes. However, it is unclear how this flipping between chromatin states alters the kinetics of transcription. Here, we integrate histone modifications and RNAPII states derived from bulk ChIP-seq data with single-cell RNA-sequencing data. We find that Polycomb repressive complex-active genes have greater cell-to-cell variation in expression than active genes, and these results are validated by knockout experiments. We also show that PRC-active genes are clustered on chromosomes in both two and three dimensions, and interactions with active enhancers promote a stabilization of gene expression noise. These findings provide new insights into how chromatin regulation modulates stochastic gene expression and transcriptional bursting, with implications for regulation of pluripotency and development. [ABSTRACT FROM AUTHOR]

Published
2017
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10. TIM-4 Identifies Effector B cells Expressing a RORγT-driven Proinflammatory Cytokine Module That Promotes Immune responsiveness.

Author

Ding Q, Wu Y, Triglia ET, Subramanian A, Kuchroo VK, and Rothstein DM

Abstract

B cells can express pro-inflammatory cytokines that promote a wide variety of immune responses. Here we show that B cells expressing the phosphatidylserine receptor TIM-4, preferentially express IL-17A, as well as IL-22, IL-6, IL-1β, and GM-CSF - a collection of cytokines reminiscent of pathogenic Th17 cells. Expression of this proinflammatory module requires IL-23R signaling and selective expression of RORγt and IL-17A by TIM-4+ B cells. TIM-4+ B cell-derived-IL-17A not only enhances the severity of experimental autoimmune encephalomyelitis (EAE) and promotes allograft rejection, but also acts in an autocrine manner to prevent their conversion into IL-10-expressing B cells with regulatory function. Thus, IL-17A acts as an inflammatory mediator and also enforces the proinflammatory activity of TIM-4+ B cells. Thus, TIM-4 serves as a broad marker for RORγt+ effector B cells (Beff) and allows further study of the signals regulating Beff differentiation and effector molecule expression.

Published
2024
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