Keywords
Corynebacterium glutamicum, Single-cell protein
Commentary
In the previous study, Park et al. reported the efficacy of a single-cell protein manufactured from a growth-accelerated high-vital Corynebacterium glutamicum strain and potential strain selection strategy for development of non-GMO industrial strains harboring enriched target nutritional component, named as growth?acceleration?targeted evolution (G.A.T.E.) strategy [1]. This commentary manuscript provides further comments and discussions on the nutritional properties of the high-vital C. glutamicum protein (heme-SCP), plausible defects of G.A.T.E strategy and the possible overcome ways, the G.A.T.E. strategy in the viewpoint of regulation, and the differences of mouse gut microbiota by the supplementation of hemin and the heme-single-cell protein (SCP).
In the viewpoint of nutrition, protein extracts or biomasses from edible microbial cell cultures have high protein quantity (40-60%), one of nutritional factors of food ingredient. Amino acid score (AAS) is another factor that determine protein quality indicating the completeness of protein by their unique composition of essential amino acids, and a protein ingredient will meet all amino acid needs of the human body [2]. A food having AAS of 100 is considered as high-quality protein that does not require additional nutrition. The AAS of the C. glutamicum heme-SCP that has led the lowering blood lipids of mouse in the focal paper were as follows: His 115; Ile 96; Leu 92; Lys 111; SAA (sulfur containing AA) 135; AAA (aromatic AA) 154; Thr 144; Trp 132; Val 100 (Table 1). Compared with the SCPs from yeast, spirulina, and chlorella [3-6], the Corynebacterium glutamicum heme-SCP in the focal paper is thought to be a good ingredient supplying a balanced amino acid for human need (Table 1). Additionally, by using the target component responding promoters in the G.A.T.E. strategy of the focal paper, one would be able to isolate a natural mutant strain that enable us to manufacture a SCP that is fortified a specific nutritional component.
|
C. glutamicum- SCP [3] |
Yeast extract |
Spirulina (Arthrospira platensis) [5] |
Chlorella vulgaris [6] |
|
|
Histidine |
115 |
97 |
68 |
101 |
|
Isoleucine |
96 |
130 |
100 |
112 |
|
Leucine |
92 |
93 |
84 |
143 |
|
Lysine |
111 |
129 |
62 |
119 |
|
SAA |
135 |
86 |
125 |
181 |
|
AAA |
154 |
141 |
136 |
277 |
|
Threonine |
144 |
132 |
124 |
237 |
|
Tryptophan |
132 |
145 |
447 |
35 |
|
Valine |
100 |
108 |
91 |
177 |
|
SSA, Methionine + Cysteine; AAA, Phenylalanine + Tyrosine |
||||
Though the G.A.T.E. strategy of the focal paper could evolve strains more effectively, design and construction of a proper-working genetic algorithm (combinations of a target component responding promoters and growth-stimulating genes) still requires much effort considering the complexity of microbial physiology. This plausible limitation could be overcome by introducing a biofoundry facility that combines artificial intelligence (AI) and robotics [8], which would allow to build optimal genetic algorithm combinations and evolution protocols even more efficient with less research labor. Even though the G.A.T.E. strategy does not perform artificial genetic manipulation, the possibility that plasmid DNA is inserted into the strain's genome during evolution cannot be ruled out. In addition, even if no foreign DNA is observed in the genome of the final mutant strain from which the plasmid has been removed, food safety assessment may be varied depending on each country's regulation policy. For example, according to the cases of EFSA and FDA, the final product should be recombinant DNA-free. However, even if it is present, it is considered safe if it is not a gene that poses concerns about antibiotic resistance, toxicity, or pathogenicity [9]. The authors have reported in the focal paper that the C. glutamicum heme-SCP derived from a gradually increased growth rate in continuous culture showed a health-favorable effect on the ingested mice’s blood fat levels along with slim bodies [1,7], and the possible reason of the lowering blood fat level by the C. glutamicum heme-SCP diet would be linked to the host intestinal health which led by flourishing health-beneficial anaerobic bacteria, especially anti-obese bacteria [7]. According to the recent Lee’s Ph. D. dissertation research, the intestinal flora of the mice fed free heme showed different flora along with lower microbial diversity compared to those fed complex nutrition of the C. glutamicum heme-SCP [3] (Tables 2, quoted and rearranged from the Lee’s Ph. D. dissertation). Therefore, the authors have reckoned that there should have been unknown components in the C. glutamicum heme-SCP besides heme that has influenced on the construction of beneficial bacteria in gut. In this regard, it is necessary to identify additional interactions and molecular mechanisms between intestinal bacterial community. Consequently, the authors further suggest that ‘high-vital C. glutamicum SCP’ would be more appropriate term than the name of the C. glutamicum heme-SCP, considering there are unknown components beside heme affecting gut microbial flora among the components of the protein ingredient. The authors currently suspect that high amino acid scored sulfur containing AA (SAA) might be the one of the unknown factors in the ingredient for constructing beneficial anaerobic bacterial flora in the host gut because SAA could be used for cellular redox balancing component such as glutathione that could strengthen the oxidative stress in the strict anaerobic bacteria.
|
Biomarker |
Characteristic |
HFD + 0 % heme-SCP |
HFD + hemin 25 µM |
HFD + 0.05 % heme-SCP |
HFD + 0.5 % heme-SCP |
|
Number of OTU |
330 |
349 |
386 |
492 |
|
|
Shannon diversity index |
Diversity |
2.924 |
3.88 |
4.226 |
4.117 |
|
Lachnospiraceae |
Produce butyrate and other SCFAs |
6% |
40% |
36% |
17% |
|
Ruminococcaceae |
Butyrate producers |
5% |
15% |
17% |
11% |
|
Pseudoflavonifractor |
Encompasses butyrate-producing bacteria |
1% |
5% |
6% |
3% |
|
Christensenellaceae |
Inversely related to host BMI |
0.3% |
0.3% |
2% |
3% |
|
Oscillibacter. |
Anti-obesity |
1% |
0% |
4% |
3% |
|
Akkermansia muciniphila |
Prevents obesity |
4% |
3% |
15% |
11% |
|
Bacteroides acidifaciens |
Prevents obesity, improves insulin |
0.2% |
2% |
1% |
3% |
|
Parabacteroides goldsteinii |
Prevents obesity |
0.2% |
0.2% |
0.3% |
0.3% |
|
Number of species |
|
336 |
349 |
378 |
431 |
|
Shannon diversity index |
Measuring biological diversity |
3.7 |
3.8 |
4.024 |
4.187 |
|
Lachnospiraceae |
Produce butyrate and other SCFAs |
19% |
40% |
35% |
43% |
|
Ruminococcaceae |
Butyrate producers |
14% |
15% |
26% |
26% |
|
Pseudoflavonifractor |
Encompasses butyrate-producing bacteria |
5% |
5% |
12% |
8% |
|
Oscillibacter. |
Prevents obesity |
3% |
5% |
9% |
10% |
|
Bilophila wadsworthia |
Aggravates high fat diet induced metabolic dysfunctions in mice |
4% |
1% |
2% |
3% |
|
Bacteroides vulgatus |
Inflammatory bowel disease |
18% |
6% |
13% |
1% |
|
After obese C57BL/6N mice were fed a high-fat diet supplemented with h-SCP for 28 days and 10 days, feces were obtained and analyzed using 16srRNA. (Courtesy to HL) The feces were analyzed by mixing feces from each group rather than separating each mouse's feces. Data quoted from Lee’s Ph. D. dissertation [3]. |
|||||
After obese C57BL/6N mice were fed a high-fat diet supplemented with h-SCP for 28 days and 10 days, feces were obtained and analyzed using 16srRNA. (Courtesy to HL) The feces were analyzed by mixing feces from each group rather than separating each mouse's feces.
Data quoted from Lee’s Ph. D. dissertation [3].
Credit Authorship Contribution Statement
Sehyeon Park: Investigation, Visualization, Writing-Original Draft. Seungki Lee: Investigation, Validation, Visualization. Taeyeon Kim: Investigation, Validation. Visualization. Soyeon Lee: Resources. Pil Kim: Conceptualization, Formal analysis, Writing-Review & Editing, Funding acquisition, Project administration.
Conflict of Interest Statement
The authors declare no conflict of interest. The funders had no role in the design of the study and the interpretation of data.
Funding Information
This research financially supported by the fundings from the Korean Ministry of Science and ICT (2022M3A9I3018121 and 2022R1A2C1005085).
References
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