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

Area of Science:

• Biotechnology
• Cell Biology
• Bioinformatics

Background:

• The Baculovirus Expression Vector System (BEVS) is widely used in gene engineering.
• Manual host cell counting in BEVS protocols is time-consuming, labor-intensive, and error-prone.
• Developing an efficient and accurate insect cell counting method is crucial for BEVS applications.

Purpose of the Study:

• To develop a reliable and accurate bright field insect cell counting protocol.
• To improve the efficiency of Baculovirus Expression Vector System (BEVS) workflows.
• To replace manual cell counting with an automated method.

Main Methods:

• A novel nonlinear Transformed Sliding Band Filter (TSBF) method was proposed for insect cell counting.
• Sf9 insect cell image datasets were used for method evaluation.
• Ground truth was established by three independent collaborators performing manual cell counts.

Main Results:

• The TSBF method achieved an average error rate of 2.21%, with a range of 0.89% to 3.97%.
• The method demonstrated high accuracy and a lower error rate compared to traditional and manual counting techniques.
• Generated growth curves using the TSBF method closely matched those from manual counting.

Conclusions:

• The proposed TSBF method accurately detects insect cells with a low error rate.
• This automated method is suitable for replacing manual cell counting in BEVS.
• The TSBF method enhances the overall efficiency of BEVS by providing accurate cell counts and reliable growth curve data.