Evidence map›Paper›PMID 38435822›Full record

ArticleBioengineering & translational medicine2024

A drug-selectable acoustic reporter gene system for human cell ultrasound imaging.

Alessandro R Howells, Phoebe J Welch, John Kim, Craig R Forest, Chengzhi Shi, Xiaojun Lance Lian

Open access · goldAbstract read
In one paragraph

Article in Bioengineering & translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 47% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 2 institutions in 1 country.

Alessandro R HowellsDepartment of Biomedical Engineering Pennsylvania State University Pennsylvania USA.ORCID https://orcid.org/0000-0001-7741-340X
Phoebe J WelchGeorge W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA.ORCID https://orcid.org/0000-0001-9552-6168
John KimGeorge W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA.
Craig R ForestGeorge W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA.
Chengzhi ShiGeorge W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta Georgia USA.
Xiaojun Lance LianDepartment of Biomedical Engineering Pennsylvania State University Pennsylvania USA.ORCID https://orcid.org/0000-0002-9161-1004
Georgia Institute of Technology · USPennsylvania State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A promising new field of genetically encoded ultrasound contrast agents in the form of gas vesicles has recently emerged, which could extend the specificity of medical ultrasound imaging. However, given the delicate genetic nature of how these genes are integrated and expressed, current methods of producing gas vesicle-expressing mammalian cell lines requires significant cell processing time to establish a clonal/polyclonal line that robustly expresses the gas vesicles sufficiently enough for ultrasound contrast. Here, we describe an inducible and drug-selectable acoustic reporter gene system that can enable gas vesicle expression in mammalian cell lines, which we demonstrate using HEK293T cells. Our drug-selectable construct design increases the stability and proportion of cells that successfully integrate all plasmids into their genome, thus reducing the amount of cell processing time required. Additionally, we demonstrate that our drug-selectable strategy forgoes the need for single-cell cloning and fluorescence-activated cell sorting, and that a drug-selected mixed population is sufficient to generate robust ultrasound contrast. Successful gas vesicle expression was optically and ultrasonically verified, with cells expressing gas vesicles exhibiting an 80% greater signal-to-noise ratio compared to negative controls and a 500% greater signal-to-noise ratio compared to wild-type HEK293T cells. This technology presents a new reporter gene paradigm by which ultrasound can be harnessed to visualize specific cell types for applications including cellular reporting and cell therapies.

Indexed as

acoustic reporter genescell engineeringultrasound imaging

Identifiers

PMID38435822
PMCPMC10905554
OpenAlexW4385492659

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.