| Literature DB >> 29439680 |
Joo Shun Tan1, Sahar Abbasiliasi2, Saeid Kadkhodaei3, Yew Joon Tam4, Teck-Kim Tang4, Yee-Ying Lee4, Arbakariya B Ariff5.
Abstract
BACKGROUND: Demand for high-throughput bioprocessing has dramatically increased especially in the biopharmaceutical industry because the technologies are of vital importance to process optimization and media development. This can be efficiently boosted by using microtiter plate (MTP) cultivation setup embedded into an automated liquid-handling system. The objective of this study was to establish an automated microscale method for upstream and downstream bioprocessing of α-IFN2b production by recombinant Escherichia coli. The extraction performance of α-IFN2b by osmotic shock using two different systems, automated microscale platform and manual extraction in MTP was compared.Entities:
Keywords: Automated system; Extraction; Fermentation; Microscale; α-interferon2b
Mesh:
Substances:
Year: 2018 PMID: 29439680 PMCID: PMC5810150 DOI: 10.1186/s12866-017-1145-9
Source DB: PubMed Journal: BMC Microbiol ISSN: 1471-2180 Impact factor: 3.605
Comparison of two different methods of osmotic extraction of α-IFN2b, manual and automated microscale platform
| Type of osmotic shock extraction | DCW | α-IFN2b release | Volume of sample |
|---|---|---|---|
| (g/L) | (μg/L) | (mL) | |
| Automated | 3.05 ± 0.08 | 49.2 ± 0.55 | 1 |
| Manual | 2.94 ± 0.12 | 48.8 ± 1.34 | 1 |
The results of DCW and α-IFN2b release are the average of triplicate experiments
Effect of inoculum size on α-IFN2b production by E. coli in MTP fermentations
| Inoculum size | Maximum DCW | Time to achieve maximum DCW | Maximum α-IFN2b | Fermentation time | Specific yield | Volumetric productivity |
|---|---|---|---|---|---|---|
| % (v/v) | (g/L) | (h) | (μg/L) | (h) | (μg/g cell) | (μg/L/h) |
| MTP | ||||||
| 2 | 2.83 (0.01) | 8 | 25.7 (0.01) | 10 | 9.1 | 2.57 |
| 4 | 2.89 (0.03) | 8 | 31.4 (0.03) | 10 | 10.9 | 3.14 |
| 6 | 2.95 (0.03) | 8 | 37.3 (0.01) | 10 | 12.7 | 3.73 |
| 8 | 3.10 (0.01) | 8 | 49.5 (0.01) | 10 | 15.9 | 4.95 |
The results of maximum DCW and maximum α-IFN2b are the average of triplicate experiments. The value in bracket is the standard deviation. Specific yield and volumetric productivity are calculated with the average values. Fermentation time is the time taken from inoculation to reach a maximum concentration of α-IFN2b
Effect of induction points on α-IFN2b production by E. coli in MTP fermentations
| Induction point | Maximum DCW | Time to achieve maximum DCW | Maximum α-IFN2b | Fermentation time | Specific yield | Volumetric productivity |
|---|---|---|---|---|---|---|
| (h) | (g/L) | (h) | (μg/L) | (h) | (μg/g cell) | (μg/L/h) |
| MTP | ||||||
| 4 | 3.05 (0.08) | 8 | 50.4 (0.31) | 10 | 16.5 | 5.04 |
| 6 | 3.64 (0.04) | 8 | 29.2 (0.01) | 12 | 8.0 | 2.43 |
| 8 | 4.37 (0.06) | 8 | 32.2 (0.04) | 14 | 7.4 | 2.30 |
| 10 | 5.02 (0.06) | 8 | 34.8 (0.04) | 16 | 6.9 | 2.18 |
The results of maximum DCW and maximum α-IFN2b are the average of triplicate experiments. The value in bracket is the standard deviation. Specific yield and volumetric productivity are calculated with the average values. Fermentation time is the time taken from inoculation to reach a maximum concentration of α-IFN2b
Fig. 1Effects of different agitation speeds on growth of E. coli Rosetta-gami2 (DE3) and the ability to produce α-IFN2b in MTP fermentation
Fig. 2Effects of different working volumes on growth of E. coli Rosetta-gami2 (DE3) and the ability to produce α-IFN2b in MTP fermentation
Fig. 3Time course of E. coli Rosetta-gami2 (DE3) fermentation for α-IFN2b production in MTP and shake flask systems