Evidence map›Paper›PMID 37130969›Full record

ArticleEuropean biophysics journal : EBJ2023

Optimizing high-throughput viral vector characterization with density gradient equilibrium analytical ultracentrifugation.

Shawn M Sternisha, Abraham D Wilson, Emilie Bouda, Akash Bhattacharya, Ross VerHeul

Open access · hybridAbstract read
In one paragraph

Article in European biophysics journal : EBJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
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

6 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Shawn M Sternisha *Beckman Coulter Life Sciences, Indianapolis, IN, USA. ssternisha@beckman.com.ORCID http://orcid.org/0000-0002-7560-2765
Abraham D Wilson *Beckman Coulter Life Sciences, Indianapolis, IN, USA.
Emilie BoudaBeckman Coulter Life Sciences, Indianapolis, IN, USA.
Akash BhattacharyaBeckman Coulter Life Sciences, Indianapolis, IN, USA.
Ross VerHeulBeckman Coulter Life Sciences, Indianapolis, IN, USA.
Beckman Coulter Foundation · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral vector-based gene therapies and vaccines require accurate characterization of capsid species. The current gold standard for assessing capsid loading of adeno-associated virus (AAV) is sedimentation velocity analytical ultracentrifugation (SV-AUC). However, routine SV-AUC analysis is often size-limited, especially without the use of advanced techniques (e.g., gravitational-sweep) or when acquiring the multiwavelength data needed for assessing the loading fraction of viral vectors, and requires analysis by specialized software packages. Density gradient equilibrium AUC (DGE-AUC) is a highly simplified analytical method that provides high-resolution separation of biologics of different densities (e.g., empty and full viral capsids). The analysis required is significantly simpler than SV-AUC, and larger viral particles such as adenovirus (AdV) are amenable to characterization by DGE-AUC using cesium chloride gradients. This method provides high-resolution data with significantly less sample (estimated 56-fold improvement in sensitivity compared to SV-AUC). Multiwavelength analysis can also be used without compromising data quality. Finally, DGE-AUC is serotype-agnostic and amenable to intuitive interpretation and analysis (not requiring specialized AUC software). Here, we present suggestions for optimizing DGE-AUC methods and demonstrate a high-throughput AdV packaging analysis with the AUC, running as many as 21 samples in 80 min.

Indexed as

UltracentrifugationAdenovirusAnalytical ultracentrifugationAUCDensity gradientGene therapy

Identifiers

PMID37130969
PMCPMC10444642
OpenAlexW4367692986

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.