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Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter.

Sui D, Wang K, Park H, Chae J - Biomed Eng Online (2014)

Bottom Line: An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments.However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals.This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS.

View Article: PubMed Central - PubMed

Affiliation: Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. wangkq@hit.edu.cn.

ABSTRACT

Background: The Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals. This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS.

Method: To develop a reliable and accurate counting method for the host cells in the bright field, such as Sf9 insect cells, a novel method based on a nonlinear Transformed Sliding Band Filter (TSBF) was proposed. And 3 collaborators counted cells at the same time to produce the ground truth for evaluation. The performance of TSBF method was evaluated with the image datasets of Sf9 insect cells according to the different periods of cell cultivation on the cell density, error rate and growth curve.

Results: The average error rate of our TSBF method is 2.21% on average, ranging from 0.89% to 3.97%, which exhibited an excellent performance with its high accuracy in lower error rate compared with traditional methods and manual counting. And the growth curve was much the manual method well.

Conclusion: Results suggest the proposed TSBF method can detect insect cells with low error rate, and it is suitable for the counting task in BEVS to take the place of manual counting by humans. Growth curve results can reflect the cells' growth manner, which was generated by our proposed TSBF method in this paper can reflected the similar manner with it's from the manual method. All of these proven that the proposed insect cell counting method can clearly improve the efficiency of BEVS.

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Scheme of Hemacytometer with nine 1 × 1 mm2squares with 0.1 mm depth. The A1 toA5 region is divided into 1/25 mm2 regions, and the B1 to B4 region is divided into1/16 mm2 regions.
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Fig3: Scheme of Hemacytometer with nine 1 × 1 mm2squares with 0.1 mm depth. The A1 toA5 region is divided into 1/25 mm2 regions, and the B1 to B4 region is divided into1/16 mm2 regions.

Mentions: Typically, visual evaluation for insect cells is calculated from 4 or 5 regions. An example of the 4 regions and 5 regions are B1, B2, B3, B4 and A1, A2, A3, A4, A5, respectively, as shown in Figure 3. In this paper, we mainly focus on region A1 through A5.Figure 3


Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter.

Sui D, Wang K, Park H, Chae J - Biomed Eng Online (2014)

Scheme of Hemacytometer with nine 1 × 1 mm2squares with 0.1 mm depth. The A1 toA5 region is divided into 1/25 mm2 regions, and the B1 to B4 region is divided into1/16 mm2 regions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4221726&req=5

Fig3: Scheme of Hemacytometer with nine 1 × 1 mm2squares with 0.1 mm depth. The A1 toA5 region is divided into 1/25 mm2 regions, and the B1 to B4 region is divided into1/16 mm2 regions.
Mentions: Typically, visual evaluation for insect cells is calculated from 4 or 5 regions. An example of the 4 regions and 5 regions are B1, B2, B3, B4 and A1, A2, A3, A4, A5, respectively, as shown in Figure 3. In this paper, we mainly focus on region A1 through A5.Figure 3

Bottom Line: An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments.However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals.This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS.

View Article: PubMed Central - PubMed

Affiliation: Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. wangkq@hit.edu.cn.

ABSTRACT

Background: The Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals. This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS.

Method: To develop a reliable and accurate counting method for the host cells in the bright field, such as Sf9 insect cells, a novel method based on a nonlinear Transformed Sliding Band Filter (TSBF) was proposed. And 3 collaborators counted cells at the same time to produce the ground truth for evaluation. The performance of TSBF method was evaluated with the image datasets of Sf9 insect cells according to the different periods of cell cultivation on the cell density, error rate and growth curve.

Results: The average error rate of our TSBF method is 2.21% on average, ranging from 0.89% to 3.97%, which exhibited an excellent performance with its high accuracy in lower error rate compared with traditional methods and manual counting. And the growth curve was much the manual method well.

Conclusion: Results suggest the proposed TSBF method can detect insect cells with low error rate, and it is suitable for the counting task in BEVS to take the place of manual counting by humans. Growth curve results can reflect the cells' growth manner, which was generated by our proposed TSBF method in this paper can reflected the similar manner with it's from the manual method. All of these proven that the proposed insect cell counting method can clearly improve the efficiency of BEVS.

Show MeSH
Related in: MedlinePlus