Standard Practice for Automated Colony Forming Unit (CFU) Assays—Image Acquisition and Analysis Method for Enumerating and Characterizing Cells and Colonies in Culture

Importancia y uso:

4.1 The Manual Observer-Dependent Assay—The manual quantification of cell and CFU cultures based on observer-dependent criteria or judgment is an extremely tedious and time-consuming task and is significantly impacted by user bias. In order to maintain consistency in data acquisition, pharmacological and drug discovery and development studies utilizing cell- and colony-based assays often require that a single observer count cells and colonies in hundreds, and potentially thousands of cultures. Due to observer fatigue, both accuracy and reproducibility of quantification suffer severely (5). When multiple observers are employed, observer fatigue is reduced, but the accuracy and reproducibility of cell and colony enumeration is still significantly compromised due to observer bias and significant intra- and inter-observer variability (2, 4) . Use of quantitative automated image analysis provides data for both the number of colonies as well as the number of cells in each colony. These data can also be used to calculate mean cells per colony. Traditional methods for quantification of colonies by hand-counting coupled with an assay for cell number (for example, DNA or mitochondrial) remains a viable method that can be used to calculate the mean number of cells per colony. These traditional methods have the advantage that they are currently less labor intensive and less technically demanding (8, 9). However, the traditional assays do not, provide colony level information (for example, variation and skew), nor do they provide a means for excluding cells that are not part of a colony from the calculation of mean colony size. As a result, the measurement of the mean number of cells per colony that is obtained from these alternative methods may differ when substantial numbers of cells in a sample are not associated with colony formation. By employing state-of-the-art image acquisition, processing and analysis hardware and software, an accurate, precise, robust and automated analysis system is realized.

4.1.1 Areas of Application—Cell and colony enumeration (CFU assay) is becoming particularly important in the manufacture, quality assurance/control (QA/QC), and development of product safety and potency release criteria for cell-based regenerative medicine and cellular therapy. The U.S. Food and Drug Administration (FDA) has a guidance document that indicates that the CFU assay may be appropriate for testing stability of placental and umbilical cord blood-derived stem cells (7). Since cell source validation and QA/QC comprise approximately 50 % of the manufacturing cost of cellular therapies (10), developing a precise, robust, and cost-effective means for enumerating cells and colonies is vital to sustainability and growth in this industry. The broad areas of use for automated analysis of colony forming unit assays include:

4.1.1.1 Characterization of a cell source by correlating biological potential and functional potency with CFU formation.

4.1.1.2 Characterization of the effect of processing steps or biological or physical manipulation (for example, stimuli) on cells or colony formation.

4.1.1.3 Cell and colony characterization using specific fluorescent and non-fluorescent (differentiation) markers.

4.1.1.4 Extrapolation of the biological potency (for example, differentiation, proliferative, and so forth) of a larger sample from application of colony forming assay to sub-samples.

4.1.1.5 Provision of criteria for sub-colony selection of preferred colonies (specific tissue type, proliferation rate, and so forth) for use and/or further expansion.

4.2 The Technology (image acquisition, processing, and analysis)—Current standards utilize user input for defining the presence and location of colonies based on visualization of an entire culture surface at low magnification through the eyepieces of a microscope. In this case, the sample may be viewed in transmission light mode (unstained or with a histochemical marker) or fluorescently with a dye or antibody. For this practice, the colony count is the only measurable output parameter. Utilizing a microscope-based imaging system to stitch together high resolution image tiles into a single mosaic image of the entire culture surface and subsequently “clustering” segmented cells using image processing algorithms to delineate colonies, provides a fully automated, accurate, and precise method for characterizing the biological potential and functional potency of the cultured cells. Furthermore, extracted parameters in addition to colony number provide means of further characterization and sub-classification of colony level statistics. These parameters include, but are not limited to, cell/nuclear count, cell/nuclear density, colony morphology (shape and size parameters), secondary marker coverage, effective proliferation rates, and so forth (Fig. A1.2). In addition to human connective tissue progenitors (CTPs) derived from bone, bone marrow, cartilage, adipose tissue, muscle, periosteum, and synovium, this practice and technology has been implemented in the cell and colony identification and characterization of several cell and tissue types including: umbilical cord blood hematopoietic stem cells (Fig. X1.2); adipose-derived stem cells (Fig. X1.3); and human epidermal (Fig. X1.4) and dermal (Fig. X1.5) stem cells.

4.3 Benefits of Automated Analysis of CFU Assays—Automated analysis is expected to provide more rapid, reproducible, and precise results in comparison to the manual enumeration of cells and colonies utilizing a microscope and hemocytometer. In addition to being time consuming, labor intensive, and subjective, manual enumeration has been shown to have a significant degree of intra- and inter-observer variability, with coefficients of variation (CV) ranging from 8.1 % to 40.0 % and 22.7 % to 80 %, respectively. Standard CVs for cell viability assessment and progenitor (colony) type enumeration have been shown to range from 19.4 % to 42.9 % and 46.6 % to 100 %, respectively (4, 11, 12). In contrast, studies focusing on bacteria, bone marrow-derived stem cells and osteogenic progenitor cells have collectively concluded that automated enumeration provides significantly greater accuracy, precision, and/or speed for counting and sizing cells and colonies, relative to conventional manual methodologies (4-6). Automated methods for enumerating cells and colonies are less biased, less time consuming, less laborious, and provide greater qualitative and quantitative data for intrinsic characteristics of cell and colony type and morphology.

4.4 Selection of Cell Culture Surface Area and Optimal Cell Seeding Density—When performing a CFU assay, optimizing the cell culture surface area and cell seeding density is critical to developing methods for generating reliable and reproducible colony- and cell-level data. If seeding density is too low, then the frequency of observed colonies is decreased. This can result in a sampling size that is inadequate to characterize the population of CFUs in the sample. If seeding density is too high, the colonies that are formed may be too closely spaced. Overlapping colony footprints compromise colony counting and characterization. Because the intrinsic range of CFU prevalence in a given cell source may vary widely, in many cases, a trial and error approach to optimizing cell seeding density (or range of densities) that are needed for a given cell source will be necessary. It is important to note that the more heterogeneous the cell source (for example, bone marrow), the more colonies that are needed to accurately represent the stem and progenitor cell constituents. Further, the cell type, effective proliferation rate (EPR) and specific cell culture conditions (for example, media, serum, factors, oxygen tension, and so forth) can impact colony formation. For example, the automated CFU assay depicted in Fig. A1.2 employs a six-day culture period, two media changes, 20 % oxygen tension, alpha-MEM media (with 25 % fetal bovine serum, ascorbate, dexamethasone and streptomycin), an optimized cell seeding density of 250 000 nucleated cells per cm² (250 000 cells per 1 mL of cell culture medium) and a cell culture surface area of 22 mm by 22 mm (dual-chamber Lab-Tek culture slides) (12, 13).

4.5 Useful Documents—A number of useful documents are available that address best practices for conducting quantitative measurements of cells using imaging approaches: Guide F2998, Guide F3294, ISO 20391-1, ISO 20391-2, and “FDA Guidance on Technical Performance Assessment of Digital Pathology Whole Slide Imaging Devices,” (14).

Subcomité:

F04.43

Referida por:

F3106-22, F3088-22, F3294-18

Volúmen:

13.02

Número ICS:

07.100.01 (Microbiology in general), 11.100.10 (In vitro diagnostic test systems)

Palabras clave:

automated cell and colony enumeration; automated colony forming unit assays; biological potential; cells; cell-based assays; cell source validation; cell therapies; CFU; colonies; colony area; colony cell density; colony morphology; colony size; counting; differentiation markers; drug developments; drug discoveries; FDA; image acquisition; image analysis; image processing; pharmaceuticals; progenitor cells; proliferation rates; quality control; quality assurance; QA/QC; stem cells;