Back

STRAIGHT-IN Dual: a platform for dual, single-copyintegrations of DNA payloads and gene circuits into human induced pluripotent stem cells

Blanch Asensio, A.; Ploessl, D.; Wang, N. B.; Mummery, C. L.; Galloway, K. E.; Davis, R. P.

2024-10-17 synthetic biology
10.1101/2024.10.17.616637 bioRxiv
Show abstract

Targeting DNA payloads into human (h)iPSCs involves multiple time-consuming, inefficient steps that must be repeated for each construct. Here, we present STRAIGHT-IN Dual, which enables simultaneous, allele-specific, single-copy integration of two DNA payloads with 100% efficiency within one week. Notably, STRAIGHT-IN Dual leverages the STRAIGHT-IN platform to allow near-scarless cargo integration, facilitating the recycling of components for subsequent cellular modifications. Using STRAIGHT-IN Dual, we investigated how promoter choice and gene syntax influence transgene silencing, demonstrating the impact these design features have on reporter gene expression and forward programming of hiPSCs into neurons, motor neurons, and endothelial cells. Furthermore, we designed a grazoprevir-inducible synZiFTR system to complement the widely used tetracycline-inducible system, providing independent, tunable, and temporally controlled expression of different transcription factors within the same cell. The unprecedented efficiency and speed with which STRAIGHT-IN Dual generates homogenous genetically engineered hiPSC populations represents a major advancement for synthetic biology in stem cell applications and opens opportunities for precision cell engineering.

Published in Nature Biomedical Engineering (predicted rank #16) · training set

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 5%
25.5%
Similar papers in this journal
2
Cell Systems
○ 201 papers in training set
Top 0.4%
7.6%
Similar papers in this journal
3
Cell Reports Methods
○ 165 papers in training set
Top 0.3%
5.3%
Similar papers in this journal
4
Nucleic Acids Research
◐ 1281 papers in training set
Top 4%
5.3%
Similar papers in this journal
5
ACS Synthetic Biology
● 287 papers in training set
Top 0.7%
4.7%
Similar papers in this journal
6
eLife
● 5828 papers in training set
Top 29%
4.2%
50% of probability mass above
7
Cell
○ 431 papers in training set
Top 2%
4.1%
8
Science
● 477 papers in training set
Top 2%
3.9%
9
Nature Chemical Biology
○ 119 papers in training set
Top 0.9%
3.1%
10
Molecular Systems Biology
○ 162 papers in training set
Top 0.9%
2.5%
11
Nature Biotechnology
○ 172 papers in training set
Top 2%
2.0%
12
Science Advances
● 1243 papers in training set
Top 18%
2.0%
13
Cell Stem Cell
○ 62 papers in training set
Top 0.8%
2.0%
14
Neuron
○ 337 papers in training set
Top 4%
1.7%
15
Advanced Science
○ 286 papers in training set
Top 5%
1.7%
Nature Biomedical Engineering · published here
○ 47 papers in training set
Top 0.9%
1.7%
17
The EMBO Journal
○ 309 papers in training set
Top 4%
1.4%
18
Cell Reports
○ 1498 papers in training set
Top 22%
1.3%
19
Stem Cell Reports
○ 130 papers in training set
Top 1%
1.3%
20
Science Translational Medicine
● 127 papers in training set
Top 2%
1.3%
21
Communications Biology
○ 993 papers in training set
Top 24%
1.1%
22
iScience
○ 1154 papers in training set
Top 29%
1.1%
23
Nature Methods
○ 385 papers in training set
Top 6%
1.1%
24
Molecular Cell
○ 350 papers in training set
Top 5%
1.0%
25
Trends in Biotechnology
○ 12 papers in training set
Top 0.2%
0.8%
26
Journal of Biological Engineering
○ 12 papers in training set
Top 0.1%
0.8%
27
Cancer Cell
○ 42 papers in training set
Top 1%
0.8%
28
Cell Reports Medicine
○ 153 papers in training set
Top 5%
0.8%
29
BMC Biology
○ 265 papers in training set
Top 6%
0.8%
30
Nature Cell Biology
○ 118 papers in training set
Top 4%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.