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Miriam Adam

Bio: Miriam Adam is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Induced pluripotent stem cell & Medicine. The author has an hindex of 6, co-authored 13 publications receiving 545 citations.

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Journal ArticleDOI
Alexandra B Keenan1, Sherry L. Jenkins1, Kathleen M. Jagodnik1, Simon Koplev1, Edward He1, Denis Torre1, Zichen Wang1, Anders B. Dohlman1, Moshe C. Silverstein1, Alexander Lachmann1, Maxim V. Kuleshov1, Avi Ma'ayan1, Vasileios Stathias2, Raymond Terryn2, Daniel J. Cooper2, Michele Forlin2, Amar Koleti2, Dusica Vidovic2, Caty Chung2, Stephan C. Schürer2, Jouzas Vasiliauskas3, Marcin Pilarczyk3, Behrouz Shamsaei3, Mehdi Fazel3, Yan Ren3, Wen Niu3, Nicholas A. Clark3, Shana White3, Naim Al Mahi3, Lixia Zhang3, Michal Kouril3, John F. Reichard3, Siva Sivaganesan3, Mario Medvedovic3, Jaroslaw Meller3, Rick J. Koch1, Marc R. Birtwistle1, Ravi Iyengar1, Eric A. Sobie1, Evren U. Azeloglu1, Julia A. Kaye4, Jeannette Osterloh4, Kelly Haston4, Jaslin Kalra4, Steve Finkbiener4, Jonathan Z. Li5, Pamela Milani5, Miriam Adam5, Renan Escalante-Chong5, Karen Sachs5, Alexander LeNail5, Divya Ramamoorthy5, Ernest Fraenkel5, Gavin Daigle6, Uzma Hussain6, Alyssa Coye6, Jeffrey D. Rothstein6, Dhruv Sareen7, Loren Ornelas7, Maria G. Banuelos7, Berhan Mandefro7, Ritchie Ho7, Clive N. Svendsen7, Ryan G. Lim8, Jennifer Stocksdale8, Malcolm Casale8, Terri G. Thompson8, Jie Wu8, Leslie M. Thompson8, Victoria Dardov7, Vidya Venkatraman7, Andrea Matlock7, Jennifer E. Van Eyk7, Jacob D. Jaffe9, Malvina Papanastasiou9, Aravind Subramanian9, Todd R. Golub, Sean D. Erickson10, Mohammad Fallahi-Sichani10, Marc Hafner10, Nathanael S. Gray10, Jia-Ren Lin10, Caitlin E. Mills10, Jeremy L. Muhlich10, Mario Niepel10, Caroline E. Shamu10, Elizabeth H. Williams10, David Wrobel10, Peter K. Sorger10, Laura M. Heiser11, Joe W. Gray11, James E. Korkola11, Gordon B. Mills12, Mark A. LaBarge13, Mark A. LaBarge14, Heidi S. Feiler11, Mark A. Dane11, Elmar Bucher11, Michel Nederlof11, Damir Sudar11, Sean M. Gross11, David Kilburn11, Rebecca Smith11, Kaylyn Devlin11, Ron Margolis, Leslie Derr, Albert Lee, Ajay Pillai 
TL;DR: The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders.
Abstract: The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

300 citations

Journal ArticleDOI
TL;DR: The CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.
Abstract: The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas–based knockouts and RNA-interference–based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.

216 citations

Journal ArticleDOI
TL;DR: This work developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics that can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases.
Abstract: High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics. Examining compounds with beneficial effects in models of Huntington’s Disease, we found common MoAs for compounds with unrelated structures, connectivity scores, and binding targets. The approach also predicted highly divergent MoAs for two FDA-approved antihistamines. We experimentally validated these effects, demonstrating that one antihistamine activates autophagy, while the other targets bioenergetics. The use of multiple omics was essential, as some MoAs were virtually undetectable in specific assays. Our approach does not require reference compounds or large databases of experimental data in related systems and thus can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases.

56 citations

Journal ArticleDOI
TL;DR: These findings identify a mechanism that may promote aberrant neurodevelopment and adult neurogenesis in adult-onset HD striatal neurons with the potential for therapeutic compensation.
Abstract: Aberrant neuronal development and the persistence of mitotic cellular populations have been implicated in a multitude of neurological disorders, including Huntington's disease (HD). However, the mechanism underlying this potential pathology remains unclear. We used a modified protocol to differentiate induced pluripotent stem cells (iPSCs) from HD patients and unaffected controls into neuronal cultures enriched for medium spiny neurons, the cell type most affected in HD. We performed single-cell and bulk transcriptomic and epigenomic analyses and demonstrated that a persistent cyclin D1+ neural stem cell (NSC) population is observed selectively in adult-onset HD iPSCs during differentiation. Treatment with a WNT inhibitor abrogates this NSC population while preserving neurons. Taken together, our findings identify a mechanism that may promote aberrant neurodevelopment and adult neurogenesis in adult-onset HD striatal neurons with the potential for therapeutic compensation.

36 citations

Journal Article
01 May 2016-Nature
TL;DR: The aim was to develop a protocol for freezing neurons differentiated from induced pluripotent stem cells (iMNs) from a patient affected by spinal muscular atrophy, and it was found that while flash-frozen iMNs are not suitable for ATAC-Seq, the assay is successful with slow-cooled cryopreserved cells.
Abstract: In recent years, the assay for transposase-accessible chromatin using sequencing (ATAC-Seq) has become a fundamental tool of epigenomic research. However, it has proven difficult to perform this technique on frozen samples because freezing cells before extracting nuclei impairs nuclear integrity and alters chromatin structure. We describe a protocol for freezing cells that is compatible with ATAC-Seq, producing results that compare well with those generated from fresh cells. We found that while flash-frozen samples are not suitable for ATAC-Seq, the assay is successful with slow-cooled cryopreserved samples. Using this method, we were able to isolate high quality, intact nuclei, and we verified that epigenetic results from fresh and cryopreserved samples agree quantitatively. We developed our protocol on a disease-relevant cell type, namely motor neurons differentiated from induced pluripotent stem cells from a patient affected by spinal muscular atrophy.

35 citations


Cited by
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TL;DR: A new dedicated aspect of BioGRID annotates genome-wide CRISPR/Cas9-based screens that report gene–phenotype and gene–gene relationships, and captures chemical interaction data, including chemical–protein interactions for human drug targets drawn from the DrugBank database and manually curated bioactive compounds reported in the literature.
Abstract: The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org) is an open access database dedicated to the curation and archival storage of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2018 (build 3.4.164), BioGRID contains records for 1 598 688 biological interactions manually annotated from 55 809 publications for 71 species, as classified by an updated set of controlled vocabularies for experimental detection methods. BioGRID also houses records for >700 000 post-translational modification sites. BioGRID now captures chemical interaction data, including chemical-protein interactions for human drug targets drawn from the DrugBank database and manually curated bioactive compounds reported in the literature. A new dedicated aspect of BioGRID annotates genome-wide CRISPR/Cas9-based screens that report gene-phenotype and gene-gene relationships. An extension of the BioGRID resource called the Open Repository for CRISPR Screens (ORCS) database (https://orcs.thebiogrid.org) currently contains over 500 genome-wide screens carried out in human or mouse cell lines. All data in BioGRID is made freely available without restriction, is directly downloadable in standard formats and can be readily incorporated into existing applications via our web service platforms. BioGRID data are also freely distributed through partner model organism databases and meta-databases.

1,046 citations

Journal ArticleDOI
TL;DR: Recent advances of the three major genome editing technologies are reviewed and the applications of their derivative reagents as gene editing tools in various human diseases and potential future therapies are discussed, focusing on eukaryotic cells and animal models.
Abstract: Based on engineered or bacterial nucleases, the development of genome editing technologies has opened up the possibility of directly targeting and modifying genomic sequences in almost all eukaryotic cells. Genome editing has extended our ability to elucidate the contribution of genetics to disease by promoting the creation of more accurate cellular and animal models of pathological processes and has begun to show extraordinary potential in a variety of fields, ranging from basic research to applied biotechnology and biomedical research. Recent progress in developing programmable nucleases, such as zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeat (CRISPR)–Cas-associated nucleases, has greatly expedited the progress of gene editing from concept to clinical practice. Here, we review recent advances of the three major genome editing technologies (ZFNs, TALENs, and CRISPR/Cas9) and discuss the applications of their derivative reagents as gene editing tools in various human diseases and potential future therapies, focusing on eukaryotic cells and animal models. Finally, we provide an overview of the clinical trials applying genome editing platforms for disease treatment and some of the challenges in the implementation of this technology.

858 citations

Journal ArticleDOI
TL;DR: In this article, a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system is described, where custom or ready-made guide RNA libraries are constructed and packaged into lentiviral vectors for delivery into cells for screening.
Abstract: Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial CRISPR (clustered regularly interspaced short palindromic repeats) immune system has been adapted for genome-scale screening by combining Cas9 with pooled guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom- or ready-made guide RNA libraries are constructed and packaged into lentiviral vectors for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified by the screen, we further describe strategies for confirming the screening phenotype, as well as genetic perturbation, through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 9-15 weeks, followed by 4-5 weeks of validation.

733 citations

Journal ArticleDOI
23 Sep 2016-eLife
TL;DR: A comprehensive algorithm that incorporates chromatin, position, and sequence features to accurately predict highly effective single guide RNAs (sgRNAs) for targeting nuclease-dead Cas9-mediated transcriptional repression (CRISPRi) and activation ( CRISPRa) is built.
Abstract: We recently found that nucleosomes directly block access of CRISPR/Cas9 to DNA (Horlbeck et al., 2016). Here, we build on this observation with a comprehensive algorithm that incorporates chromatin, position, and sequence features to accurately predict highly effective single guide RNAs (sgRNAs) for targeting nuclease-dead Cas9-mediated transcriptional repression (CRISPRi) and activation (CRISPRa). We use this algorithm to design next-generation genome-scale CRISPRi and CRISPRa libraries targeting human and mouse genomes. A CRISPRi screen for essential genes in K562 cells demonstrates that the large majority of sgRNAs are highly active. We also find CRISPRi does not exhibit any detectable non-specific toxicity recently observed with CRISPR nuclease approaches. Precision-recall analysis shows that we detect over 90% of essential genes with minimal false positives using a compact 5 sgRNA/gene library. Our results establish CRISPRi and CRISPRa as premier tools for loss- or gain-of-function studies and provide a general strategy for identifying Cas9 target sites.

584 citations