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eBriefing

New Frontiers in CRISPR

CRISPR: New Frontiers
Reported by
Jordana Thibado

Posted April 20, 2020

Jordana Thibado is a New York City-based biophysics PhD candidate and science writer.

Presented By

CRISPR Discussion Group

The New York Academy of Sciences

The use of CRISPR-Cas systems for genome editing has dramatically transformed the biomedical research landscape since its discovery in prokaryotic adaptive immunity. The subsequent development of CRISPR-based tools has both improved our understanding of basic biology and enabled critical advancements in human health. Recent work harnessing these diverse and rapidly growing systems to target and modify specific RNA and DNA sequences has enabled a multitude of applications, such as genome editing, transcriptional modulation, forward genetic screens, lineage tracing, and more. However, many questions remain surrounding the full potential of CRISPR-Cas systems. Learn about the latest advances in CRISPR research in this summary of our February 24, 2020 symposium.

Symposium Highlights

  • CRISPR-Cas immunization requires dead phage DNA. >
  • RNA-guided integration of mobile genetic elements uses CRISPR without introducing double-stranded DNA breaks. >
  • Chromatin is often excluded from nuclear bodies in the cell, unlike dominant thinking that chromatin is pulled into nuclear condensates during transcription. >
  • A novel pooled genetic screen revealed a new Cas9 variant that has improved gene activation at a variety of target sites. >
  • Perturb-seq, which combines single-cell RNA sequencing with CRISPR-induced genetic perturbations, uncovers gene pairs that induce phenotypes like cell differentiation. >
  • CRISPR perturbation of schizophrenia-related genes shows that genes modulated in concert, but not individually, mimic postmortem brain analyses of schizophrenic patients. >
  • In vivo CRISPR screening has identified new cancer immunotherapy targets. >
  • Combining large-scale human RNA sequencing datasets with experimental validation has enabled the discovery of an autoimmune disease-associated locus. >

Speakers

Clifford Brangwynne
Clifford Brangwynne, PhD

Princeton University

Sidi Chen
Sidi Chen, PhD

Yale School of Medicine

Tuuli Lappalainen
Tuuli Lappalainen, PhD

New York Genome Center & Columbia University

Luciano Marraffini
Luciano Marraffini, PhD

The Rockefeller University

Thomas Norman
Thomas Norman, PhD

Memorial Sloan Kettering Cancer Center

Neville Sanjana
Neville Sanjana, PhD

New York Genome Center & New York University

Sanne Klompe
Sanne Klompe

Columbia University

Nadine Schrode
Nadine Schrode, PhD

Mount Sinai School of Medicine

Event Sponsors

Grant Support

This activity was supported by an educational grant from:


Uncovering Mechanisms of CRISPR-Cas Systems

Speakers

Scavenging for Dead DNA: How CRISPR-Cas Systems Make New Memories of Infection

Luciano Marraffini explained how CRISPR-Cas systems carry out an immune response to protect bacteria from phage infection. Phages pose a significant threat to bacteria, with about 1031 viral particles on Earth. To defend themselves, bacteria use CRISPR – clustered, regularly interspaced, short palindromic repeats – which contain specific “spacer” sequences that are identical to phage genomes. “The spacers hold the information to tell the CRISPR what to target. They determine the specificity of the CRISPR-Cas immune reaction,” Marraffini emphasized. CRISPR-associated proteins, or Cas proteins, then execute the immune response to destroy the nucleic acids of the invading phage.

New Frontiers in CRISPR

The CRISPR-based response to infection in bacteria consists of two phases: immunization and targeting.

Together, the immune response can be thought of in two phases. Immunization, or generation of memory, captures part of the phage genome to be inserted within the CRISPR array. Targeting guides the Cas protein to destroy the virus. The Marraffini lab aims to enhance our fundamental understanding of CRISPR immunity using genetic and biochemical approaches. Recent findings include identification of particular “hotspots” of spacer acquisition within the phage genome and the discovery that spacer acquisitions from specific regions in the genome called “restriction sites” prevent infection by modified phages in the future. Marraffini also shared that the CRISPR machinery requires dead phage DNA for spacer acquisition and subsequent immunization of the host.

Scavenging for Dead DNA: How CRISPR-Cas Systems Make New Memories of Infection


Luciano Marraffini (The Rockefeller University)

Transposon-encoded CRISPR-Cas Systems Direct RNA-Guided DNA Integration

Sanne Klompe presented her research studying transposons, which are DNA sequences that can move throughout the genome. Recent work found that CRISPR-Cas sequences exist within these transposons, which led her to wonder whether CRISPR-Cas systems can function as a targeting module for transposition. Through her work in the lab, Klompe discovered that they can, and that even large transposons of greater than ten kilobases can be mobilized. She also found that DNA integration using CRISPR is programmable and occurs without creating double-stranded breaks.

Transposon-encoded CRISPR-Cas Systems Direct RNA-Guided DNA Integration


Sanne Klompe (Columbia University)

Liquid Nuclear Condensates: In, On, and Around the Genome

Clifford Brangwynne studies the biophysics of intracellular organization, specifically membrane-less organelles. Liquid nuclear condensates are of particular interest to his lab because they organize gene expression. In particular, Brangwynne’s lab is interested in how phase-separated condensates are able to interact with the genome. To study these phase transitions, the Brangwynne lab has developed tools to optically manipulate liquid organelles in living cells. Interestingly, they found that endogenous and optically induced nuclear bodies exclude chromatin. This is a striking result because it conflicts with current thinking that chromatin is pulled within nuclear condensates during transcription.

Liquid Nuclear Condensates: In, On, and Around the Genome


Clifford Brangwynne (Princeton University)

Further Readings

Marraffini

Hynes AP, Villion M, Moineau S.

Nat. Commun. 2014;5:4399.

Modell JW, Jiang W, Marraffini LA.

Nature 2017;544(7648):101-104.

Garneau JE, Dupuis M-È, Villion M, et al.

Nature 2010;468(7320):67-71

Brouns SJJ, Jore MM, Lundgren M, et al.

Science 2008;321(5891):960-964

Barrangou R, Fremaux C, Deveau H, et al.

Science 2007;315(5819):1709-1712

Marraffini LA, Sontheimer EJ

Science 2008;322(5909):1843-1845

Mojica FJ, Díez-Villaseñor C, Soria E, Juez G.

Mol. Microbiol. 2000;36(1):244-246

Sanne Klompe

Strecker J, Ladha A, Gardner Z, Schmid-Burgk JL, et al.

Science 2019;365(6448):48-53

Halpin-Healy TS, Klompe SE, Sternberg SH, Fernández IS

Nature 2020;577(7789):271-274

Klompe SE, Vo PLH, Halpin-Healy TS, Sternberg SH

Nature 2019;571(7764):219-225

Feschotte C, Pritham EJ

Annu. Rev. Genet. 2007;41:331-368

Bernheim A, Sorek R

Nat. Rev. Microbiol. 2020;18(2):113-119

Clifford Brangwynne

Style RW, Sai T, Fanelli N, et al

Phys. Rev. X 2018;8(1):011028

Shin Y, Chang Y-C, Lee DSW, et al

Cell 2018;175(6):1481-1491.e13

Shin Y, Brangwynne CP

Science 2017;357(6357)

Dine E, Gil AA, Uribe G, et al

Cell Syst. 2018;6(6):655-663.e5

Bracha D, Walls MT, Wei M-T, et al

Cell 2018;175(6):1467-1480.e13

Expanding the Genome Engineering Toolbox

Speakers

New Frontiers in Pooled CRISPR Screens

To gain critical insight into the human genome, Neville Sanjana combines genome engineering and pooled genetic screens. Recently, the Sanjana lab used a pooled genetic screen to examine Cas9 variants for the purpose of optimizing Cas9 function. “[We] discovered that Cas9 variants that were more flexible in target sequence were less productive with genome editing,” Sanjana said. By combining flexibility and productivity traits, they were able to create a new Cas9 variant that exhibited greater activity at a wide range of target sites. The Sanjana lab has also used CRISPR screens to examine noncoding regions of the genome that are integral to regulating gene expression. To improve the feasibility and throughput of the screen, they created a Cas13-based platform for transcriptome screening in human cells that performs similarly to Cas9-based systems.

New Frontiers in Pooled CRISPR Screens


Neville Sanjana (New York Genome Center & New York University)

Finding and Interpreting Genetic Interactions Using Perturb-seq

Thomas Norman presented his research on genetic interactions (GIs), which involves two or more genes working together to create phenotypic outcomes. Due to the massive scale of examining interactions (10,000 genes can lead to ~50 million possible GI pairs), it is critical to use tools that allow for massive parallelization. In the Norman lab, Perturb-seq is used to approach this problem, which allows for many CRISPR-induced genetic perturbations at a time to be examined. “You can imagine that as this approach scales, and you can do this to hundreds or thousands or tens of thousands of gene pairs, you can really start to do automated understanding of gene regulation,” Norman said.

New Frontiers in CRISPR

Genetic interactions are defined as two or more genes working together to create phenotypes. The vast number of possible pairwise interactions requires careful measurements that considers all possible outcomes.

This information can then provide insight into the biological mechanisms that drive genetic interactions. For example, the Norman lab examined GIs in K562 cells using CRISPR and then inspected the strongest interactions using Perturb-seq. From this, they discovered gene pairs that promoted cell differentiation, which enabled the construction of a mathematical model for the prediction of future interactors.

Finding and Interpreting Genetic Interactions Using Perturb-seq


Thomas Norman (Memorial Sloan Kettering Cancer Center)

Integration of CRISPR-Engineering and hiPSC-based Models of Psychiatric Genomics

Nadine Schrode uses CRISPR engineering to study psychiatric disorders such as schizophrenia. Schizophrenia is particularly difficult to study because it is genetically variable, including hundreds of associated genetic variants. To tackle this problem, Schrode developed a human induced pluripotent stem cell (hiPSC)-based approach in which CRISPR was used to perturb schizophrenia-related genes. She discovered that combinatorial, rather than individual, perturbations of genes mimicked genetic changes observed in postmortem brain tissue of schizophrenic patients. This result provides important insight that will help direct future research avenues. “There are still open questions,” said Schrode,  “for example, if synergistic effects are more impactful within one pathway or several different pathways.”

Integration of CRISPR-Engineering and hiPSC-based Models of Psychiatric Genomics


Nadine Schrode (Mount Sinai School of Medicine)

In Vivo Gene Editing and Immunotherapy

Sidi Chen spoke about his work to improve immunotherapy treatment for cancer patients. He shared that there is still a lack of response in many patients, which is difficult to change because the genetic mechanism of therapy response is still largely unknown. To address this gap in understanding, the Chen lab used in vivo CRISPR screens in CD8 cytotoxic T cells to identify cancer immunotherapy targets. Their screen was validated with the identification of known targets and was also able to successfully identify new targets that they subsequently characterized in mouse and human cells.

New Frontiers in CRISPR

An in vivo CRISPR screen seeking to identify cancer immunotherapy targets discovered both known and new targets in T cells.

The Chen lab has also developed CRISPRa-mediated Multiplexed Activation of Endogenous Genes as an Immunotherapy (MAEGI) in which large gene pools can be targeted. MAEGI was shown to be therapeutically effective in three tumor types, and they plan to continue to optimize this technology for treatment.

In Vivo Gene Editing and Immunotherapy


Sidi Chen (Yale School of Medicine)

Further Readings

Sanjana

Nishimasu H, Shi X, Ishiguro S, et al

Science 2018;361(6408):1259-1262

Hu JH, Miller SM, Geurts MH, et al

Nature 2018;556(7699):57-63

Doench JG, Fusi N, Sullender M, et al

Nat. Biotechnol. 2016;34(2):184-191

Hsu PD, Scott DA, Weinstein JA, et al

Nat. Biotechnol. 2013;31(9):827-832

Wessels H-H, Méndez-Mancilla A, Guo X, et al

BioRxiv 2019

Norman

Norman TM, Horlbeck MA, Replogle JM, et al

Science 2019;365(6455):786-793

Datlinger P, Rendeiro AF, Schmidl C, et al

Nat. Methods 2017;14(3):297-301

Jaitin DA, Weiner A, Yofe I, et al

Cell 2016;167(7):1883-1896.e15

Schrode

Schrode N, Ho S-M, Yamamuro K, et al

Nat. Genet. 2019;51(10):1475-1485

Chen

Wang G, Chow RD, Bai Z, et al

Nat. Immunol. 2019;20(11):1494-1505

Chow RD, Guzman CD, Wang G, et al

Nat. Neurosci. 2017;20(10):1329-1341

Dai X, Park JJ, Du Y, et al

Nat. Methods 2019;16(3):247-254

Marrone KA, Brahmer JR

Cancer J. 2016;22(2):81-91

Harnessing Big Data for Human Genome Insight

Speaker

Functional Genetic Variation in Humans: From Population Associations to Experimental Follow-up

Tuuli Lappalainen studies genetic variation in human populations using genetic sequencing data and experimental approaches. In particular, the Lappalainen lab uses data from the Genotype Tissue Expression project, which contains nearly 18,000 RNA-sequencing samples from 54 tissues of 838 post-mortem human donors. She has used this data to identify expression quantitative trait loci, or eQTLs, which are genomic regions that explain variation in a genetic phenotype.

New Frontiers in CRISPR

The Genotype Tissue Expression project contains valuable sequencing data from human donors that scientists can use to better understand gene expression.

The Lappalainen lab then uses this type of information to inform genome editing experiments. For example, her lab was able to experimentally validate an autoimmune disease-associated locus near the IRF1 gene using CRISPR-based approaches in cells.

Functional Genetic Variation in Humans: From Population Associations to Experimental Follow-up


Tuuli Lappalainen (New York Genome Center & Columbia University)

Further Readings

Lappalainen

Kim-Hellmuth S, Bechheim M, Pütz B, et al

Nat. Commun. 2017;8(1):266

Aguet F, Barbeira AN, Bonazzola R, et al

BioRxiv 2019

GTEx Consortium

Nat. Genet. 2013;45(6):580-585