Evidence map›Paper›PMID 31780559›Full record

ArticleScience (New York, N.Y.)2019

Comprehensive AAV capsid fitness landscape reveals a viral gene and enables machine-guided design.

Pierce J Ogden, Eric D Kelsic, Sam Sinai, George M Church

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 228 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
228citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

228 citing papers in PubMed, 1 synthesis or guideline pooled it.

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168 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Pierce J Ogden *Harvard Medical School, Boston, MA 02115, USA.ORCID 0000-0003-3444-6214
Eric D Kelsic *Harvard Medical School, Boston, MA 02115, USA. eric.kelsic@dynotx.com gchurch@genetics.med.harvard.edu.ORCID 0000-0002-5331-5204
Sam SinaiHarvard Medical School, Boston, MA 02115, USA.ORCID 0000-0003-0301-9201
George M ChurchHarvard Medical School, Boston, MA 02115, USA. eric.kelsic@dynotx.com gchurch@genetics.med.harvard.edu.ORCID 0000-0002-0775-2913

Funding

Causal Transcriptional Consequences of Human Genetic VariationP50HG005550 · NHGRI · HARVARD MEDICAL SCHOOL · PI CHURCH, GEORGE M · 2010 to 2014
$19.0M
Center for Genomically Engineered OrgansRM1HG008525 · NHGRI · HARVARD MEDICAL SCHOOL · PI CHURCH, GEORGE M · 2015 to 2019
$10.2M
NHGRI NIH HHS P50 HG005550NHGRI NIH HHS RM1 HG008525
6 · The paper itself

Abstract

Adeno-associated virus (AAV) capsids can deliver transformative gene therapies, but our understanding of AAV biology remains incomplete. We generated the complete first-order AAV2 capsid fitness landscape, characterizing all single-codon substitutions, insertions, and deletions across multiple functions relevant for in vivo delivery. We discovered a frameshifted gene in the VP1 region that expresses a membrane-associated accessory protein that limits AAV production through competitive exclusion. Mutant biodistribution revealed the importance of both surface-exposed and buried residues, with a few phenotypic profiles characterizing most variants. Finally, we algorithmically designed and experimentally verified a diverse in vivo targeted capsid library with viability far exceeding random mutagenesis approaches. These results demonstrate the power of systematic mutagenesis for deciphering complex genomes and the potential of empirical machine-guided protein engineering.

Indexed as

CapsidGenetic TherapyCapsid ProteinsDependovirusGenes, ViralHEK293 CellsHumansMutagenesis, InsertionalProtein EngineeringSequence DeletionTransfectionCapsid Proteins

Identifiers

PMID31780559
PMCPMC7197022

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.