Evaluation of cell distribution density during seeding and growth required to maintain cell traits

Evaluation of cell distribution density during seeding and growth required to maintain cell traits

Point

In order to reliably culture cells, it is important to maintain a uniform cell density in culture surface during seeding and proliferation. Different operators and culture conditions introduce variability. However, by quantifying cell density and visually monitoring cell status at the same time, this process can be improved.

Overview

hPSCs can be passaged either as clumps or as single cells.
When they are dispersed in clumps, it is extremely difficult to seed in a spatially uniform manner.
It can be difficult to ensure uniform cell proliferation and formation of colonies, making even cell seeding indispensable for successful cell culture.
If the cell distribution at the time of seeding is non-uniform, it will result in areas of higher and lower colony density once cells begin to proliferate .
Such non-uniformities will affect how well the undifferentiated state can be maintained.
In human somatic stem cell culture, cells in areas of especially high density become stressed and are more likely to transform.
For these reasons, it is important to quantitatively measure the distribution of cells in culture in order to understand how culture conditions affect cell state.
The quality of seeding is greatly affected by operator skill, and therefore, operator training plays an important role.
To efficiently improve operator technique, it is important to understand critical cell culture process parameters, and introduce procedures that enable quantitative evaluation.

Current

Issue-1
Cell density distribution cannot easily be measured.

The entire culture vessel needs to be thoroughly checked to ensure that cells were distributed homogenously at the time seeding , a process that relies upon the human eye. Until now, an accepted metric for quantifying the uniformity of cell density has not been available.

Issue-2
Seeding  accuracy varies with operator skill and experience.

Cells need to be uniformly dispersed across the entire vessel surface at the time of seeding , but the accuracy of this process varies with operator skill and experience.

Issue-3
Seeding  accuracy affects the quality of cultured cells.

Non-uniformities in cell density distribution due to operator handling during the seeding process significantly affects cell quality following proliferation.

Solution

Quantification of cell density in culture vessels allows for non-uniformities in cell density due to seeding to be identified.Phase contrast imaging and image analysis of cells in culture allows operators to identify regions of cells that are seeded or proliferating. Quantification of cell density based on region allows for the creation of density maps, which are useful for evaluating the uniformity of cell seeding and proliferation.
Using the BioStation CT, a cell culture observation system with a built-in microscope and camera inside its incubator , and the BioStudio-T, a cell observation system that can be installed inside an incubator , phase contrast images can be captured over a long period without perturbing the culture environment.

A cell growth curve generated using image analysis

A cell growth curve generated using image analysis. It is evident that cell proliferation efficiency significantly varies with different operators.

Comparison image of image analysis identifies cell region (green mask) automatically from phase contrast imaging data.

Image analysis identifies cell region (green mask) automatically from phase contrast imaging data.
Left: 12 hrs. after seeding Right: 108 hrs. after seeding

Cell density in each region is represented by a heat map, where density scales from blue (no cells) to red (areas of high cell density), generated using image analysis.

Cell density in each region is represented by a heat map, where density scales from blue (no cells) to red (areas of high cell density), generated using image analysis.
Left: 12 hrs. after seeding Right: 108 hrs. after seeding

Utilization scene

For evaluation index to establish culture processes

  • To study process conditions in order to achieve uniform seeding and proliferation densities

Cell image analysis software
CL-Quant Custom Order

CL-Quant

Custom CL-Quant is the image analysis software created together with customers. We will build an image analysis and evaluation system according to the challenges you have and the characteristics of the cells you use. Because it is customized, we can tailor it to meet a wide range of analysis needs on site.

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Cell culture observation device
BioStation CT

BioStation CT

Up to 30 culture vessels can be automatically observed by phase contrast/fluorescence in a stable culture environment of an incubator, reducing the burden on developers. Its excellent position repeatability expands the possibility of live cell imaging for a wide range of cell types.

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Cell observation device
BioStudio-T

BioStudio-T

The BioStudio-T offers a unique imaging platform with a stationary sample surface and moving objective lens. This configuration allows observation of mechanically sensitive samples, such as stem cells, with minimal perturbation.

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With image analysis technology and quality evaluation know-how
Contributes to solving cell culture issues.

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