Back

Characterization of acetate catabolism in Chlamydomonas reinhardtii reveals distinct roles for ACS1 and ACK2 in regulating cell growth and carbon storage

Alrefaie, A.;Lee, Y.;Li, Y.

2026-06-26 Molecular Biology
10.64898/2026.06.25.734523 bioRxiv
Show abstract

Acetate metabolism drives mixotrophic and heterotrophic growth in some microalgae. Acetyl-CoA synthetase (ACS) and acetate kinase (ACK) are often considered the main enzymes involved in acetate catabolism in microalgae; however, their contributions to metabolic flux and carbon allocation are not fully understood. In this study, the functions of cytosolic ACS1 and mitochondrial ACK2 were characterized using two knockout mutants of the model microalga Chlamydomonas reinhardtii. The acs1 mutant exhibited a growth-oriented phenotype, characterized by 29.8% faster cell growth at 96 h and up to a 15.5% higher acetate depletion rate, yet showed a 38.3% lower triacylglycerol (TAG) content at 48 h under heterotrophic conditions. By contrast, the ack2 mutant exhibited an altered carbon-allocation phenotype under heterotrophic conditions. Despite an up to 32.4% lower respiratory oxygen consumption rate and a 27.7% reduction in cell density, ack2 exhibited a 39.3% higher biomass concentration and a 90.4% greater dry weight per cell than the wild type at 96 h. Biochemical analysis revealed that ack2 accumulated 23.3% more carbohydrate than the wild type at 120 h under heterotrophic conditions, whereas its TAG level remained comparable to that of the wild type. These findings suggest that, under heterotrophic conditions, the loss of cytosolic ACS1 facilitates cell growth and division at the expense of TAG biosynthesis, whereas the loss of mitochondrial ACK2 regulates growth by affecting carbon flux toward biomass and carbohydrate accumulation. This work provides insight into acetate catabolism in C. reinhardtii and suggests targets for engineering microalgae for production of biomass and bioproducts.

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
Algal Research
21 papers in training set
Top 0.1%
15.5%
2
Scientific Reports
3612 papers in training set
Top 14%
5.6%
3
Metabolic Engineering
75 papers in training set
Top 0.2%
5.6%
4
Bioresource Technology
12 papers in training set
Top 0.1%
5.0%
5
PLOS ONE
5266 papers in training set
Top 32%
4.5%
6
Plant Physiology
238 papers in training set
Top 1%
4.4%
7
Frontiers in Microbiology
427 papers in training set
Top 4%
2.5%
8
Metabolic Engineering Communications
22 papers in training set
Top 0.2%
2.2%
9
New Phytologist
346 papers in training set
Top 3%
2.2%
10
BMC Plant Biology
57 papers in training set
Top 0.6%
2.2%
11
Applied and Environmental Microbiology
339 papers in training set
Top 3%
1.8%
50% of probability mass above
12
Plant Biotechnology Journal
64 papers in training set
Top 0.7%
1.8%
13
International Journal of Molecular Sciences
494 papers in training set
Top 7%
1.8%
14
BMC Genomics
406 papers in training set
Top 4%
1.8%
15
Biotechnology for Biofuels
14 papers in training set
Top 0.2%
1.8%
16
Microbiology Spectrum
469 papers in training set
Top 7%
1.7%
17
mBio
833 papers in training set
Top 8%
1.7%
18
Frontiers in Plant Science
256 papers in training set
Top 3%
1.5%
19
The Plant Journal
215 papers in training set
Top 3%
1.5%
20
The FEBS Journal
93 papers in training set
Top 0.9%
1.5%
21
Environmental Microbiology
133 papers in training set
Top 2%
1.5%
22
Plant Physiology and Biochemistry
20 papers in training set
Top 0.5%
1.5%
23
ACS Synthetic Biology
287 papers in training set
Top 2%
1.4%
24
Journal of Experimental Botany
219 papers in training set
Top 3%
1.2%
25
Plant and Cell Physiology
52 papers in training set
Top 1%
1.2%
26
Communications Biology
993 papers in training set
Top 20%
1.2%
27
mSystems
394 papers in training set
Top 5%
1.2%
28
Journal of Phycology
14 papers in training set
Top 0.3%
1.0%
29
Journal of Biotechnology
11 papers in training set
Top 0.2%
0.9%
30
Science of The Total Environment
186 papers in training set
Top 3%
0.6%