Back

Delivery of novel replicating vectors to Synechococcus sp. PCC 7002 via natural transformation of plasmid multimers

Kamoku, C.; Cooper, C.; Straub, A.; Miller, N.; Nielsen, D. R.

2024-07-31 synthetic biology
10.1101/2024.07.31.606084 bioRxiv
Show abstract

In most cyanobacteria, genetic engineering efforts currently rely upon chromosomal integration; a time-consuming process due to their polyploid nature. To enhance strain construction, here we develop and characterize two novel replicating plasmids for use in Synechococcus sp. PCC 7002. Following an initial screen of plasmids comprising seven different origins of replication, two were found capable of replication: one based on the WVO1 broad host range plasmid and the other a shuttle vector derived from pCB2.4 from Synechocystis sp. PCC 6803. These were then used to construct a set of new replicating plasmids, which were shown to be both co-transformable and stably maintained in PCC 7002 at copy numbers between 0.6-1.4 and 7-16, respectively. Lastly, we demonstrate the importance of using multimeric plasmids during natural transformation of PCC 7002, with higher order multimers providing a 30-fold increase in transformation efficiency relative to monomeric plasmids. Useful considerations and methods for enhancing multimer content in plasmid samples are also presented.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
ACS Synthetic Biology
● 287 papers in training set
Top 0.2%
22.1%
Similar papers in this journal
2
PLOS ONE
● 5266 papers in training set
Top 14%
13.0%
Similar papers in this journal
3
Microbial Cell Factories
○ 27 papers in training set
Top 0.1%
12.0%
Similar papers in this journal
4
Synthetic Biology
◐ 24 papers in training set
Top 0.1%
4.3%
Similar papers in this journal
50% of probability mass above
5
Microbial Biotechnology
○ 34 papers in training set
Top 0.2%
4.1%
Similar papers in this journal
6
Philosophical Transactions of the Royal Society B
● 51 papers in training set
Top 0.1%
3.2%
7
Nucleic Acids Research
◐ 1281 papers in training set
Top 7%
2.5%
8
Genes
○ 144 papers in training set
Top 1%
2.5%
9
BMC Biotechnology
○ 14 papers in training set
Top 0.1%
2.1%
10
Metabolic Engineering Communications
○ 22 papers in training set
Top 0.2%
2.1%
11
Frontiers in Bioengineering and Biotechnology
○ 98 papers in training set
Top 0.8%
2.1%
12
New Biotechnology
○ 12 papers in training set
Top 0.1%
2.1%
13
Life
○ 29 papers in training set
Top 0.2%
1.9%
14
Synthetic and Systems Biotechnology
○ 11 papers in training set
Top 0.1%
1.7%
15
Scientific Reports
○ 3612 papers in training set
Top 51%
1.7%
16
MicrobiologyOpen
○ 24 papers in training set
Top 0.1%
1.7%
17
Journal of Molecular Biology
○ 232 papers in training set
Top 2%
1.7%
18
Metabolic Engineering
○ 75 papers in training set
Top 0.5%
1.5%
19
International Journal of Molecular Sciences
○ 494 papers in training set
Top 10%
1.3%
20
Applied and Environmental Microbiology
● 339 papers in training set
Top 4%
1.3%
21
Biotechnology and Bioengineering
○ 53 papers in training set
Top 0.6%
1.1%
22
ChemBioChem
○ 55 papers in training set
Top 0.8%
1.1%
23
Trends in Biotechnology
○ 12 papers in training set
Top 0.1%
1.0%
24
PeerJ
◐ 308 papers in training set
Top 10%
0.8%
25
Biotechnology for Biofuels
○ 14 papers in training set
Top 0.4%
0.6%
26
Algal Research
○ 21 papers in training set
Top 0.4%
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.