A new institution for curiosity-driven biomedical science and technology.

Headquartered in Palo Alto, California, Arc is a nonprofit research organization founded on the belief that many important scientific programs can be enabled by new organizational models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley.

Arc gives scientists no-strings-attached, multi-year funding, so that they don’t have to apply for external grants, and invests in the rapid development of experimental and computational technological tools.

As individuals, Arc researchers collaborate across diverse disciplines to study complex diseases, including cancer, neurodegeneration, and immune dysfunction. As an organization, Arc strives to enable ambitious, long-term research agendas.

Arc’s mission is to accelerate scientific progress, understand the root causes of disease, and narrow the gap between discoveries and impact on patients.

The Arc Model

Arc is organized around three core concepts, each consisting of an institutional experiment in how research can be enabled.
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Core investigators

We fully fund investigators and their labs with complete freedom to pursue curiosity-driven research agendas. Arc investigators may hold faculty positions at our partner institutions, and graduate students at Stanford, UC Berkeley, and UCSF can pursue their PhD studies at Arc labs.

Technology Development

Our Technology Centers provide long-term career options for Arc scientists beyond their training period, enabling them to develop, optimize and deploy rapidly advancing experimental and computational technologies. Initial Centers will focus on machine learning, genome engineering, cellular and animal models of human disease, and multi-omics.

Translational Programs

In addition to curiosity-driven knowledge building, producing medically useful discoveries is a core mission of the Institute. We believe the current system for real-world impact of the life sciences can be greatly optimized. Arc will build translational infrastructure to accelerate the advancement of new biological insights or biotechnologies into impact on patients.

Arc Institute headquarters in Palo Alto, CaliforniaArc Institute headquarters in Palo Alto, California

Open positions

We have open positions for Technology Center group leaders, research scientists, and operational staff. We have open calls for Core Investigators as well as Science Fellows on a yearly basis. In the initial phase of the Institute, we will scale to a total headcount of approximately 250 scientific personnel. We expect to get there within three years.

Investigators

Silvana Konermann

Silvana Konermann

Stanford University

Patrick Hsu

Patrick Hsu

University of California, Berkeley

Lingyin Li

Lingyin Li

Stanford University

Luke Gilbert

Luke Gilbert

University of California, San Francisco

Recent work

Arc seeks to get important discoveries into the public domain as quickly as possible. Below is some recent work from labs led by Arc’s Core Investigators.

Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome

Nature Biotechnology (2022)

Matthew G. Durrant, Alison Fanton, Josh Tycko, Michaela Hinks, Sita S. Chandrasekaran, Nicholas T. Perry, Julia Schaepe, Peter P. Du, Peter Lotfy, Michael C. Bassik, Lacramioara Bintu, Ami S. Bhatt, Patrick D. Hsu

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Abstract

Large serine recombinases (LSRs) are DNA integrases that facilitate the site-specific integration of mobile genetic elements into bacterial genomes. Only a few LSRs, such as Bxb1 and PhiC31, have been characterized to date, with limited efficiency as tools for DNA integration in human cells. In this study, we developed a computational approach to identify thousands of LSRs and their DNA attachment sites, expanding known LSR diversity by >100-fold and enabling the prediction of their insertion site specificities. We tested their recombination activity in human cells, classifying them as landing pad, genome-targeting or multi-targeting LSRs. Overall, we achieved up to seven-fold higher recombination than Bxb1 and genome integration efficiencies of 40–75% with cargo sizes over 7 kb. We also demonstrate virus-free, direct integration of plasmid or amplicon libraries for improved functional genomics applications. This systematic discovery of recombinases directly from microbial sequencing data provides a resource of over 60 LSRs experimentally characterized in human cells for large-payload genome insertion without exposed DNA double-stranded breaks.

Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting

Preprint

Jingyi Wei, Peter Lotfy, Kian Faizi, Eleanor Wang, Hannah Slabodkin, Emily Kinnaman, Sita Chandrasekaran, Hugo Kitano, Matthew G. Durrant, Connor V. Duffy, Patrick D. Hsu, Silvana Konermann

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Abstract

Transcriptome engineering technologies that can effectively and precisely perturb mammalian RNAs are needed to accelerate biological discovery and RNA therapeutics. However, the broad utility of programmable CRISPR-Cas13 ribonucleases has been hampered by an incomplete understanding of the design rules governing guide RNA activity as well as cellular toxicity resulting from off-target or collateral RNA cleavage. Here, we sought to characterize and develop Cas13d systems for efficient and specific RNA knockdown with low cellular toxicity in human cells. We first quantified the performance of over 127,000 RfxCas13d (CasRx) guide RNAs in the largest-scale screen to date and systematically evaluated three linear, two ensemble, and two deep learning models to build a guide efficiency prediction algorithm validated across multiple human cell types in orthogonal secondary screens (https://www.RNAtargeting.org). Deep learning model interpretation revealed specific sequence motifs at spacer position 15-24 along with favored secondary features for highly efficient guides. We next identified 46 novel Cas13d orthologs through metagenomic mining for activity screening, discovering that the metagenome-derived DjCas13d ortholog achieves low cellular toxicity and high transcriptome-wide specificity when deployed against high abundance transcripts or in sensitive cell types, including hESCs. Finally, our Cas13d guide efficiency model successfully generalized to DjCas13d, highlighting the utility of a comprehensive approach combining machine learning with ortholog discovery to advance RNA targeting in human cells.

IFITM proteins assist cellular uptake of diverse linked chemotypes

SCIENCE (2022)

Kevin Lou, Douglas R. Wassarman, Tangpo Yang, YiTing Paung, Ziyang Zhang, Thomas A. O'Loughlin, Megan K. Moore, Regina K. Egan, Patricia Greninger, Cyril H Benes, Markus A. Seeliger, Jack Taunton, Luke A. Gilbert, Kevan M. Shokat

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Abstract

The search for cell-permeable drugs has conventionally focused on low-molecular weight (MW), nonpolar, rigid chemical structures. However, emerging therapeutic strategies break traditional drug design rules by employing flexibly linked chemical entities composed of more than one ligand. Using complementary genome-scale chemical-genetic approaches we identified an endogenous chemical uptake pathway involving interferon-induced transmembrane proteins (IFITMs) that modulates the cell permeability of a prototypical biopic inhibitor of MTOR (RapaLink-1, MW: 1784 g/mol). We devised additional linked inhibitors targeting BCR-ABL1 (DasatiLink-1, MW: 1518 g/mol) and EIF4A1 (BisRoc-1, MW: 1466 g/mol), uptake of which was facilitated by IFITMs. We also found that IFITMs moderately assisted some proteolysis-targeting chimeras and examined the physicochemical requirements for involvement of this uptake pathway.

Extracellular cGAMP is a cancer-cell-produced immunotransmitter involved in radiation-induced anticancer immunity

NATURE CANCER (2020)

Jacqueline A. Carozza, Volker Böhnert, Khanh C. Nguyen, Gemini Skariah, Kelsey E. Shaw, Jenifer A. Brown, Marjan Rafat, Rie von Eyben, Edward E. Graves, Jeffrey S. Glenn, Mark Smith, Lingyin Li

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Abstract

2′3′-Cyclic GMP-AMP (cGAMP) is an intracellular second messenger that is synthesized in response to cytosolic double-stranded DNA and activates the innate immune STING pathway. Our previous discovery of its extracellular hydrolase ENPP1 hinted at the existence of extracellular cGAMP. Here we detected that cGAMP is continuously exported but then efficiently cleared by ENPP1, explaining why it has previously escaped detection. By developing potent, specific and cell-impermeable ENPP1 inhibitors, we found that cancer cells continuously export cGAMP in culture at steady state and at higher levels when treated with ionizing radiation (IR). In mouse tumors, depletion of extracellular cGAMP decreased tumor-associated immune cell infiltration and abolished the curative effect of IR. Boosting extracellular cGAMP with ENPP1 inhibitors synergized with IR to delay tumor growth. In conclusion, extracellular cGAMP is an anticancer immunotransmitter that could be harnessed to treat cancers with low immunogenicity.