Back

SpoVG and the Kre-ComK Regulatory Module Orchestrate Production of the EPE Toxin in Bacillus subtilis

Miercke, S.; Schaubruch, K.; Maass, S.; Russeck, A. K.; Lawaetz, A. C.; Denham, E. L.; Heermann, R.; Mascher, T.

2026-04-03 molecular biology
10.64898/2026.04.02.716078 bioRxiv
Show abstract

Survival of bacteria in their natural habitat requires dynamic responses and adaptation to environmental cues. In Bacillus subtilis, one adaptive strategy is cannibalism, a form of programmed cell death during post-exponential development. Cannibalism enhances multicellular differentiation by prolonging or preventing commitment to endospore formation under starvation conditions. B. subtilis produces three cannibalism toxins: the sporulation delay protein, the sporulation killing factor, and the epipeptide EPE. Production of the latter is encoded in the epeXEPAB operon. Expression of this operon is transcriptionally controlled by the stationary phase regulators Spo0A and AbrB. Here, we demonstrate that EPE production is also post-transcriptionally regulated by two RNA binding proteins, Kre and SpoVG. Deletion of comK, the master regulator of competence development, abolished EPE production. This defect was reversed by additionally deleting kre. The RNA-binding protein, Kre, binds the epeX transcript and acts as a bidirectional ComK repressor, indicating that ComK indirectly regulates EPE biosynthesis via Kre. A second RNA-binding protein, SpoVG, also binds to the epeX mRNA. While Kre acts as a negative regulator, SpoVG was essential for EPE production. These findings reveal a novel regulatory connection between competence and cannibalism, expanding our understanding of how programmed cell death is coordinated in B. subtilis. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/716078v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@57e20dorg.highwire.dtl.DTLVardef@1b9f4e5org.highwire.dtl.DTLVardef@17cfbc9org.highwire.dtl.DTLVardef@76824d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Nucleic Acids Research
1128 papers in training set
Top 0.3%
22.7%
2
PLOS Genetics
756 papers in training set
Top 1%
10.2%
3
Molecular Microbiology
66 papers in training set
Top 0.1%
7.2%
4
mBio
750 papers in training set
Top 2%
6.9%
5
PLOS Pathogens
721 papers in training set
Top 3%
4.0%
50% of probability mass above
6
Frontiers in Microbiology
375 papers in training set
Top 3%
3.6%
7
eLife
5422 papers in training set
Top 25%
3.6%
8
PLOS Biology
408 papers in training set
Top 4%
3.1%
9
mSystems
361 papers in training set
Top 3%
2.8%
10
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 24%
2.8%
11
Nature Communications
4913 papers in training set
Top 44%
2.6%
12
Cell Reports
1338 papers in training set
Top 20%
2.4%
13
Journal of Bacteriology
190 papers in training set
Top 0.4%
2.1%
14
Environmental Microbiology
119 papers in training set
Top 2%
1.7%
15
Molecular Cell
308 papers in training set
Top 7%
1.7%
16
PLOS ONE
4510 papers in training set
Top 54%
1.7%
17
Journal of Molecular Biology
217 papers in training set
Top 2%
1.5%
18
iScience
1063 papers in training set
Top 21%
1.2%
19
Genetics
225 papers in training set
Top 3%
1.1%
20
mSphere
281 papers in training set
Top 5%
0.9%
21
Microbiology Spectrum
435 papers in training set
Top 4%
0.9%
22
Communications Biology
886 papers in training set
Top 23%
0.8%
23
RNA
169 papers in training set
Top 0.4%
0.8%
24
Scientific Reports
3102 papers in training set
Top 74%
0.8%
25
International Journal of Molecular Sciences
453 papers in training set
Top 16%
0.7%
26
Computational and Structural Biotechnology Journal
216 papers in training set
Top 11%
0.6%
27
Microbiology
57 papers in training set
Top 1%
0.6%
28
microLife
19 papers in training set
Top 0.3%
0.6%
29
Molecular Biology of the Cell
272 papers in training set
Top 3%
0.5%
30
RNA Biology
70 papers in training set
Top 0.7%
0.5%