Measurement Protocol
Figure 1. At day -2 (D-2), the cells are seeded and grown until they reach full confluence. At day 0 (D0), differentiation is initiated by treating the cells with the DMI cocktail, which contains dexamethasone (Dex), IBMX, and insulin. This combination triggers the early pathways required for adipogenic commitment. After three days (D3), the medium is replaced with FI medium, which contains FBS (fetal bovine serum) and insulin, supporting further differentiation and lipid accumulation. At day 6 (D6), the cells are maintained in normal FBS medium (10% FBS) without additional hormones. During this period, lipid droplets continue to enlarge as the cells mature into adipocytes. Finally, at day 9 (D9), the adipocytes are fully differentiated and ready for sampling—for example, for Oil Red O staining, RNA extraction, or protein analysis.
Wetlab Measurement Protocol
Figure 2. Schematic figures of Oil Red O staining of differentiated 3T3-L1 adipocyte
Schematic figures of Oil Red O staining of differentiated 3T3-L1 adipocyte. Lipid accumulations in DMI treated mature adipocytes were clear compared to the undifferentiated cells, suggesting Oil Red O staining is reasonable method to quantify lipid accumulation with colorimetry.
Figure 3. Oil red O stained 3T3-L1 adipocyte in 6-well plates
We validated our proof of concept by inducing lipid accumulation in 3T3-L1 adipocytes using a well-established chemical differentiation cocktail. Following differentiation, intracellular lipids were visualized through Oil Red O staining, and cell morphology was captured via light microscopy. To quantify lipid content, the bound dye was extracted with isopropanol and absorbance was measured at 518 nm using a microplate reader in triplicate.
Measurement of Raw Bacteria (MOI)
Figure 4. Co-culture of mature adipocytes and Lactobacillus delbrueckii subsp. Lactis shows about 25% reduction in lipid accumulation and the difference between the co-culture groups and the negative control were statistically significant. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001). However, degree of lipid reduction was not MOI dependent.
Measurement indicator : MOI (Multiplicity of Infection)
Multiplicity of infection (MOI) is the ratio of infectious agents (like viruses or phages) to the number of target cells in an experiment. It represents the average number of infectious particles that each target cell is exposed to, typically calculated as the number of viral particles divided by the number of cells. Controlling MOI is crucial in experiments to ensure consistent infection conditions for reproducible results, as a high MOI can increase the likelihood of all cells being infected, while a low MOI may lead to incomplete or inconsistent infections.
Figure 5. Co-culture of mature adipocytes and Lactobacillus casei shows about 25% reduction in lipid accumulation. The difference between the co-culture groups and the negative control were statistically significant except the MOI 1 sample. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 6. Co-culture of mature adipocytes and Lactobacillus crispatus shows about 30% reduction in lipid accumulation. The difference between the co-culture groups and the negative control were statistically significant, with MOI 100 being most efficient in lowering lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 7. Co-culture of mature adipocytes and Lactobacillus acidophilus was not effective in reducing lipid accumulation. The difference between the co-culture groups and the negative control were not statistically significant. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 8. Co-culture of mature adipocytes and Lactobacillus rhamnosus shows about 30% reduction in lipid accumulation. The difference between the co-culture groups and the negative control were statistically significant, with MOI 100 being most efficient in lowering lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 9. Co-culture of mature adipocytes and Lactobacillus gaseri shows about 25% reduction in lipid accumulation. The difference between the co-culture groups and the negative control were statistically significant, with MOI 100 being most efficient in lowering lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 10. Most Lactobacillus sub species except Lactobacillus acidophilus shows inhibition in lipid accumulation when co-cultured with DMI induced mature adipocytes. These in vitro data suggest that Lactobacillus sub-species are potential research targets for obesity treatments.
| Bacterial Strain | Measurement Condition | Measurement Value |
|---|---|---|
| Lactobacillus lactis | Raw Bacteria (MOI 1, 10, 100) | 25% inhibition |
| Lactobacillus casei | Raw Bacteria (MOI 1, 10, 100) | 25% inhibition |
| Lactobacillus crispatus | Raw Bacteria (MOI 1, 10, 100) | 30% inhibition |
| Lactobacillus acidophilus | Raw Bacteria (MOI 1, 10, 100) | No inhibition |
| Lactobacillus rhamnosus | Raw Bacteria (MOI 1, 10, 100) | 30% inhibition |
| Lactobacillus gasseri | Raw Bacteria (MOI 1, 10, 100) | 25% inhibition |
Table 1. Lipid accumulation of Lactobacillus spp of Raw Bacteria conditions
Measurement of Bacterial Supernatant (Ratio Volume)
Figure 11. Treatment Lactobacillus delbrueckii subsp. Lactis supernatant on mature adipocytes shows no reduction in lipid accumulation, different from the co-culture experiment which resulted in reduced lipid content. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Measurement indicator : Bacterial Supernatant (Percent of total media volume)
A bacterial supernatant is the cell-free liquid that remains after bacterial cells and other solid components are removed from a liquid culture, typically through centrifugation or sedimentation. This liquid contains secreted metabolites, growth factors, and other components that the bacteria released into their growth medium, making it a valuable source for studying bacterial products or for applications like antibiotic research
Figure 12. Treatment Lactobacillus casei supernatant on mature adipocytes shows no reduction in lipid accumulation, different from the co-culture experiment which resulted in reduced lipid content. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 13. Treatment of mature adipocytes with Lactobacillus casei supernatant resulted in a significant 50% increase in lipid accumulation, in contrast to the co-culture experiment which resulted in reduced lipid content. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 14. Treatment of mature adipocytes with Lactobacillus acidophilus supernatant resulted in a significant 25% increase in lipid accumulation. In the co-culture experiment of Lactobacillus acidophilus, there was no significant change in the lipid storage in the mature adipocytes. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 15. Treatment of mature adipocytes with Lactobacillus rhamnosus supernatant resulted in a significant 45% decrease in lipid accumulation, consistent with the co-culture experiment. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 16. Treatment of mature adipocytes with Lactobacillus gaseri supernatant shows no reduction in lipid accumulation, different from the co-culture experiment which resulted in reduced lipid content. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 17. Only supernatant from Lactobacillus rhamnosus shows inhibition of lipid accumulation. Other strains shows no inhibition or even increase of lipid accumulation. Therefore, specifically extracellular materials from Lactobacillus rhamnosus contains the substance which regulate the fat accumulation rather than other species.
| Bacterial Strain | Measurement Condition | Measurement Value |
|---|---|---|
| Lactobacillus lactis | Bacterial Supernatant (25%, 50%, 75%) | No inhibition |
| Lactobacillus casei | Bacterial Supernatant (25%, 50%, 75%) | No inhibition |
| Lactobacillus crispatus | Bacterial Supernatant (25%, 50%, 75%) | 50% increase |
| Lactobacillus acidophilus | Bacterial Supernatant (25%, 50%, 75%) | 25% increase |
| Lactobacillus rhamnosus | Bacterial Supernatant (25%, 50%, 75%) | 45% inhibition |
| Lactobacillus gasseri | Bacterial Supernatant (25%, 50%, 75%) | No inhibition |
Table 2. Lipid accumulation of Lactobacillus spp of Bacterial Supernatant conditions
Wetlab – Proof of Concept
Measurement of Bacterial Exosome (Nanoparticles/ml)
Figure 18. Treatment of mature adipocytes with exosomes isolated from Lactobacillus delbrueckii subsp. Lactis supernatant shows no reduction in lipid accumulation. In fact, 60% increase of lipid accumulation was observed in the high exosome concentration. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Measurement indicator : Bacterial Exosome (10⁷nanoparticles/ml)
A bacterial exosome, more broadly called a bacterial extracellular vesicle (BEV), is a membrane-bound particle secreted by bacteria that contains various cellular cargo, such as proteins, DNA, and lipids. Unlike host cell-derived exosomes, which originate from endosomes, bacterial exosomes are released from the bacterial cell envelope. These vesicles play roles in inter-bacterial communication, nutrient transfer, and modulating the host’s immune system and are being investigated for therapeutic and diagnostic applications.
Figure 19. Treatment of mature adipocytes with exosomes isolated from Lactobacillus casei supernatant shows no reduction in lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 20. Treatment of mature adipocytes with exosomes isolated from Lactobacillus crispatus supernatant resulted in increase of lipid accumulation about 30%. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 21. Treatment of mature adipocytes with exosomes isolated from Lactobacillus acidophilus supernatant shows no reduction in lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 22. Treatment of mature adipocytes with exosomes isolated from Lactobacillus rhamnosus supernatant resulted in a remarkable 80% reduction in lipid accumulation, which was greater than the 45% reduction observed with the supernatant treatment. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 23. Treatment of mature adipocytes with exosomes isolated from Lactobacillus gaseri supernatant shows no reduction in lipid accumulation. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 24. Exosomes isolated from Lactobacillus rhamnosus caused an 80% reduction in lipid accumulation, whereas exosomes from other Lactobacillus strains did not reduce lipid storage. These results suggest that only exosomes from L. rhamnosus may contain specific factors capable of regulating lipid accumulation and adipogenesis-related genes.
| Bacterial Strain | Measurement Condition | Measurement Value |
|---|---|---|
| Lactobacillus lactis | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | 60% increase |
| Lactobacillus casei | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | No inhibition |
| Lactobacillus crispatus | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | 30% increase |
| Lactobacillus acidophilus | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | No inhibition |
| Lactobacillus rhamnosus | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | 80% inhibition |
| Lactobacillus gasseri | Bacterial Exosome (2,5,10 x 10⁷ NP/ml) | No inhibition |
Table 3. Lipid accumulation of Lactobacillus spp of Bacterial Exosome conditions
Software Measurement Tool
Figure 25. Software Measurement Tool Protocol
- ImageJ description
- As an open-source image-based tool, our team incorporated the
software ImageJ to help quantify the size and count of adipocyte cells
- Following Oil Red O staining, we utilized ImageJ code from the “Qualitative and quantitative analysis of lipid droplets in mature 3T3-L1 adipocytes using oil red o STAR Protocols”.¹
- Directions
Figure A. Captured images of Oil Red O–stained adipocytes at consistent magnification and opened images in ImageJ
Figure B. Converted images to grayscale and applied a fixed threshold to highlight stained lipid droplets
Figure C. Applying the ImageJ macro, it generates an outline of the detected droplets, allowing for easier quantification
Figure D. The applied color threshold, the measured sizes of each individual droplet, and a summary of all droplets identified in the image are displayed
Software Measurement (Exosome)
Figure 26. Lipid accumulation of Lactobacillus rhamnosus exosome
Figure 27. Quantitative analysis of lipid accumulation of Exosome treated
Based on Exosome light microscope data, we analyze quantitative values of photos; Total Lipid Area, Average Droplet Size and Droplet Counts are measured Highly thoroughly by using Image J macro code. All quantitative values(TLA, ADS, DC) of 5,10 x 10⁷ nanoparticles/ml condition shows significantly less plotted than NC.
(ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 28. Qualitative analysis of lipid accumulation of Exosome treated
On top of quantitative measurement values, we separate the lipid droplet size into three class; 0-120, 120-240, >240 (um²). Therefore, we measured the lipid droplet’s not only quantitative traits but also qualitative traits.
By the measurements of the data, NC has average 85% of 0-120, 12% of 120-240, and 5% of over 240 um² size lipid droplet. On the other hand, 5,10 x 10⁷ NP/ml conc. Treated shows almost 100% 0-120 lipid size and almost 0% over 240um² lipid size, which means that exosome treatment not only inhibit the number of lipid droplet but also decrease the size of the lipid droplet. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
| x10⁷NP/ml | Total Lipid Area(um²) | Average Droplet Size(um²) | Droplet Counts |
|---|---|---|---|
| NC | 37128.87 | 27.03167 | 1373.301 |
| 2 | 28493.21 | 31.128 | 923.2198 |
| 5 | 447.6873 | 5.502 | 81.22322 |
| 10 | 387.3537 | 4.874667 | 82.10846 |
Table 4. Avereage Quantitative Values of exosome treated lipid droplet
| x10⁷NP/ml | Droplet Size 0-120um²(% total) | Droplet Size 120-240um²(% total) | Droplet Size >240um²(% total) |
|---|---|---|---|
| NC | 85.39373 | 11.68927 | 4.3751 |
| 2 | 90.51683 | 6.324567 | 3.158633 |
| 5 | 98.36677 | 0.898067 | 0.735163 |
| 10 | 99.60643 | 0.2589 | 0.134673 |
Table 5. Avereage Qualitative Values of exosome treated lipid droplet
Measurement of Bacterial Exosome (Nanoparticles/ml)
Figure 29. mRNA expression levels measured by RT-qPCR represented that exosomes isolated from Lactobacillus rhamnosus supernatant downregulate the representative gene of adipogenesis (PPARγ and C/EBPα) by inducing AMPK genes.
Figure 30. Western blot analysis representing correlations between adipogenesis-related proteins and Lactobacillus rhamnosus exosome concentrations. The master regulators of adipogenesis (PPARγ and C/EBPα) were significantly inhibited in a concentration-dependent manner, while AMPK expression was upregulated. β-Actin was used as a housekeeping protein, and the similar β-Actin band intensities indicate that the observed differences in PPARγ, C/EBPα, and AMPK expression were not due to unequal protein loading in SDS-PAGE.
Measurement of Bacterial hisF Protein (ug/ml)
Figure 31. BCA assay of hisF expressed matrix
| OD | 0.239 | 0.368 | 0.58 | 0.805 | 0.927 | 1.271 | 1.577 | 0.11 | 2.442 | 3.275 |
| OD | 0.216 | 0.33 | 0.541 | 0.616 | 0.946 | 1.186 | 1.495 | 0.1 | 1.924 | 2.657 |
| Protein Conc. (ug/ml) (average) | 57.85 | 231.4 | 533.5 | 747.8 | 1070 | 1487 | 1927 | 3824 | 3012 |
Table 6. OD Value (562nm) of BSA standard and acquired four hisF samples and converted protein concentration by using BSA standard graph
Measurement indicator : Bacterial hisF Protein (ppm)
The BCA (bicinchoninic acid) assay is a biochemical method to determine the total protein concentration in a solution. It uses a two-step process: first, the biuret reaction reduces copper ions by proteins, and second, bicinchoninic acid reacts with the cuprous cations to produce an intense purple-colored product, the absorbance of which is measured at 562 nm to quantify the protein. The BCA assay is known for its high sensitivity, accuracy, and compatibility with detergents, making it a popular choice in protein research.
Figure 32. BSA standard graph for calculating unknown protein concentration
Figure 33. Expressed hisF inhibit lipid accumulation by 50%
Engineered hisF alone treating to adipocyte during adipogenesis lead to 50% inhibition of lipid accumulation.
Measurement indicator : Bacterial hisF Protein (ppm)
The HisF subunit is one half of the Imidazole Glycerol Phosphate Synthase (IGPS) complex, a heterodimeric enzyme responsible for a key step in the biosynthesis of histidine and purines. While the HisH subunit generates ammonia from glutamine, the HisF subunit, a cyclcase ,uses this ammonia to form imidazole glycerol phosphate (ImGP) and 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR)
Software Measurement (hisF)
Figure 34. Quantitative analysis of lipid accumulation of hisF treated
Based on hisF light microscope data, we analyze quantitative values of photos; Total Lipid Area, Average Droplet Size and Droplet Counts are measured thoroughly by using Image J macro code. All quantitative values(TLA, ADS, DC) of 100, 500 ppm condition shows significantly less plotted than NC.
(ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
Figure 35. Qualitative analysis of lipid accumulation of hisF treated
On top of quantitative measurement values, we separate the lipid droplet size into three class; 0-120, 120-240, >240 (um²). Therefore, we measured the lipid droplet’s not only quantitative traits but also qualitative traits.
By the measurements of the data, NC has average 95% of 0-120, 4% of 120-240, and 1% of over 240 um² size lipid droplet. On the other hand, 100, 500 ppm treated shows almost 100% 0-120 lipid size and almost 0% over 240um² lipid size, which means that hisF treatment not only inhibit the number of lipid droplet but also decrease the size of the lipid droplet. (ns p≥0.05, * p<0.5, ** p<0.01, *** p<0.001, **** p<0.0001).
| hisF (ppm) | Total Lipid Area(um²) | Average Droplet Size(um²) | Droplet Counts |
|---|---|---|---|
| NC | 28931.81 | 32.43267 | 877.3321 |
| 20 | 17051.79 | 21.95833 | 813.9498 |
| 100 | 7050.625 | 16.44033 | 434.6861 |
| 500 | 3288.167 | 16.826 | 201.342 |
Table 6. Avereage Quantitative Values of hisF treated lipid droplet
| hisF (ppm) | Droplet Size 0-120um²(% total) | Droplet Size 120-240um²(% total) | Droplet Size >240um²(% total) |
|---|---|---|---|
| NC | 94.43333 | 4.308 | 1.261667 |
| 20 | 97.74 | 1.556667 | 0.706667 |
| 100 | 98.41333 | 0.703333 | 0.89 |
| 500 | 98.56667 | 1.226667 | 0.216667 |
Table 7. Avereage Qualitative Values of hisF treated lipid droplet
Measurement of Bacterial hisF (ppm)
Figure 36. mRNA expression levels measured by RT-qPCR showed that engineered hisF proteins successfully inhibited the master regulators of adipogenesis and lipid accumulation (PPARγ and C/EBPα). At the same time, AMPK expression was upregulated in a concentration-dependent manner with increasing hisF.
Figure 29. Western blot analysis showing different levels of protein expression in engineered hisF-treated adipocytes compared with the negative control. The master regulators of adipogenesis (PPARγ and C/EBPα) were significantly inhibited, while AMPK expression was upregulated. β-Actin was used as a housekeeping protein, and the similar β-Actin band intensities indicate that the observed differences in PPARγ, C/EBPα, and AMPK expression were not due to unequal protein loading in SDS-PAGE.
Measurement Colabfold
Figure 38. hisF of Lactobacillus Rhamnosus GG and human AMPK
Top right figure (PAE plot): PAE shows predicted error (in Å) in the relative position of residue i when the model is aligned on residue j
middle predicted IDDT plot: per-residue confidence of prediction on a 0 – 100 scale. Tells whether each region of the sequence is predicted well
-
90 : very high confidence
- 70–90 : generally reliable
- 50–70 : low confidence / possibly flexible
- < 50 : likely disordered / unreliable
Bottom right figure (coverage plot): shows the multiple sequence alignment (MSA) used for prediction.
- * First row: sequences aligned to the both hisF and AMPK
- * Second & Third row: sequences aligned to either hisF or AMPK exclusively
iPTM: interfacial predicted TM-score: a metric AlphaFold-Multimer uses to quantify confidence in the predicted interface between chains
Figure 39. hisF of Staphylococcus epidermis and human AMPK
Figure 40. hisF of Escherichia coli k12 and human AMPK
Figure 41. hisF of Staphylococcus simulans and human AMPK
Measurement of Structural difference of hisFs
Figure 46. Each Bacterial strain’s hisFs are superposed and compare any noticeable structural differences which means wetlab results may not caused by hisF’s structural differences but how efficiently produce the AICAR to trigger the AMPK activity.
Measurement Alphafold3
Figure 42. hisF of Lactobacillus Rhamnosus GG and human AMPK (AlphaFold3)
Figure 43. hisF of Staphylococcus epidermis and human AMPK (AlphaFold3)
Figure 44. hisF of Escherichia coli k12 and human AMPK (AlphaFold3)
Figure 45. hisF of Staphylococcus simulans and human AMPK (AlphaFold3)
Test Measurement
| Bacterial Strain | iPTM |
|---|---|
| Lactobacillus Rhamnosus GG | 0.28 |
| Staphylococcus epidermis | 0.21 |
| Escherichia coli k12 | 0.17 |
| Staphylococcus simulans | 0.21 |
Table 8. iPTM of each bacterial strain calculated in Colabfold
| Bacterial Strain | iPTM |
|---|---|
| Lactobacillus Rhamnosus GG | 0.28 |
| Staphylococcus epidermis | 0.13 |
| Escherichia coli k12 | 0.15 |
| Staphylococcus simulans | 0.13 |
Table 9. iPTM of each bacterial strain calculated in Alphafold3
Conclusion
1. Quantitative Screening of Lactobacillus Strains
Initial measurements of intracellular lipids using Oil Red O staining quantified the anti-adipogenic potential of various Lactobacillus species. Our data showed that while several strains were effective, Lactobacillus rhamnosus and Lactobacillus crispatus yielded the highest measured inhibition of lipid accumulation at 30%. Other strains, including L. lactis, L. casei, and L. gasseri, produced a 25% reduction, whereas L. acidophilus showed no measurable inhibition. These initial measurements successfully identified L. rhamnosus as a prime candidate for further quantitative analysis.
2. Measurement of Secreted Components: From Supernatant to Exosomes
To identify the source of the inhibitory effect, subsequent experiments measured the activity of bacterial secretions.
- Supernatant Measurements: Quantitative analysis of lipid content after treatment with bacterial supernatant revealed that only the supernatant from L. rhamnosus produced a significant, 45% inhibition. In contrast, measurements for other strains showed no inhibitory effect or even an increase in lipids, with L. crispatus supernatant causing a measured 50% increase.
- Exosome Measurements: Further investigation focused on exosomes as the key active vector. Our initial measurements based on absorbance showed a powerful, dose-dependent effect, with L. rhamnosus exosomes achieving a maximum lipid accumulation inhibition of 80% at a concentration of 10 x 10⁷ nanoparticles/ml of exosomes compared to the negative control. This was the highest inhibitory value recorded in our study, confirming that the active compounds are concentrated within bacterial extracellular vesicles.
To further quantify this, we used the software ImageJ to analyze microscope images. This software-based measurement confirmed that the Total Lipid Area, Average Droplet Size, and Droplet Counts were all significantly lower in cells treated with 5 and 10 x 10⁷ nanoparticles/ml of exosomes compared to the negative control. Moreover, qualitative analysis of droplet size revealed that at these higher concentrations, nearly 100% of the lipid droplets were in the smallest size class (0-120 um²), demonstrating that exosome treatment not only inhibits the number of lipid droplets but also decreases their size.
3. Quantifying the Molecular Mechanism of Action
To elucidate the underlying mechanism, we performed quantitative measurements of gene and protein expression.
- mRNA Expression Levels: Quantitative PCR (qPCR) measurements showed that treatment with L. rhamnosus exosomes resulted in a dramatic downregulation of the master adipogenesis genes Ppary and C/ebpa, with their relative mRNA expression reduced to near-zero levels at the highest concentration. Concurrently, we measured a significant upregulation of key metabolic regulators, with Ampk1 mRNA expression increasing approximately 20-fold compared to the control.
- Protein Expression Levels: These gene expression measurements were validated at the protein level. Western blot analysis provided semi-quantitative data showing a clear, dose-dependent decrease in C/EBPα and PPARγ protein levels and a corresponding increase in AMPK1 protein.
4. Validation with Engineered hisF Protein and In Silico Measurements
Finally, we measured the effect of a specific bacterial protein, hisF, and quantified its predicted interaction with the human AMPK target.
- Engineered Protein Activity: Direct treatment with engineered hisF protein resulted in a measured 50% inhibition of lipid accumulation. This was further quantified using ImageJ, which showed that the Total Lipid Area, Average Droplet Size, and Droplet Counts were all significantly lower at 100 and 500 ppm of hisF. Qualitative measurement also showed that at these concentrations, nearly 100% of droplets were in the smallest size class (0-120 um²).
qPCR measurements confirmed that this was achieved through the same mechanism, recording a greater than 5-fold increase in AMPK1 mRNA expression at a concentration of 500 ppm.
- Computational Measurements: In silico measurements using AlphaFold3 predicted the binding confidence between bacterial hisF and human AMPK. The interfacial Predicted TM-score (iPTM), a metric for interface accuracy, was measured to be 0.28 for L. rhamnosus hisF. This value was significantly higher than the scores for hisF from other bacteria, such as E. coli (0.17 or 0.15) and S. epidermis (0.21 or 0.13), providing a quantitative structural basis for its observed biological specificity.
In conclusion, our collective measurements provide a robust, data-driven validation of our hypothesis. From cellular assays to molecular quantification and computational modeling, the data consistently indicate that exosomes from Lactobacillus rhamnosus are a potent inhibitor of adipogenesis, acting via the measurable upregulation of the AMPK signaling pathway.