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74 Journal of GXP Compliance
P e e r r e v i e w e d : M i C r o b i o l o G y
MiCrobioloGiCAl dATA Most microbiologists would claim that the recorded numbers of colony forming units (CFU) were raw data. This is not correct. That recorded number is someone’s (presumably a skilled technician’s) inter- pretation of the number of colonies on the plate. ex- perience has shown that different technicians (each skilled) can, and frequently do, come up with differ- ent counts on the same sample. The data recorded in the lab notebook are an interpretation of the number of colonies on the plate that can be influenced by the colony morphology, colony density, and the tem- perament of the counter. However, these are the best data available to us. it must also be remembered that the CFU is only an estimate of the number of cells present. it is a skewed estimate at best as the only cells able to form colonies are those that can grow under the conditions of the test (i.e., incubation media, temperature, time, and oxygen conditions). These do not represent a single cell, but rather those that happened to be well separated on the plate and so can be distinguished after growth. A col- ony could arise from one cell or several thousand cells.
Microbiology has a well-deserved reputation for being highly variable. lax attention to precision and accuracy in measurements helps further this perception. we have allowed specifications for envi- ronmental monitoring, raw material bioburden, in- process bioburden, and finished product bioburden to be imposed by regulation without regard for the ability of the methods to support those specifications specifically in terms of the “countable colonies on a plate” and the requisite number of replicates needed for a reasonably accurate estimate. This discussion looks at the topics of variability, accuracy, and precision in measurements. variability is usually discussed in terms of a normally distrib- uted population, where the range of measurements can be represented by a bell-shaped curve with the true number at the center of the curve. A population of measurements that has little variability will give a narrow bell-shape, and one that is variable will be wider. A method providing these measurements will have two aspects of interest to this discussion: accu- racy and precision. Accuracy can be thought of as the ability of measurements to reflect the true value of the population. Precision is the degree of reproduc- ibility among the measurements. bench technicians will state that replicate plate counts are not precise. replicate plate values will vary widely. The accuracy of the measured values for a population with a high degree of variability will be influenced greatly by chance. even with all plating variables controlled as is feasible (i.e., plating error, dilution error, sampling error, technician counting and transcription error), the level of variability can only be minimized by in- creasing the number of replicate platings.
Microbiology has a well-deserved reputation for being highly variable. lax attention to precision and accu- racy in measurements helps further this perception. The current prevailing confusion between the limit of detection (1 CFU) and limit of quantification (25 CFU) for the plate count method creates a larger degree of variability in microbiology data than is necessary. This discussion looks at the topics of variability, accuracy, and precision in measurements.
The limitations of CFU: Compliance to CGMP
requires Good Science
Scott Sutton
winter 2012 volume 16 Number 1 75
S c o t t S u t t o n
A second aspect of plate count accuracy is its im- portance to the introduction of alternate microbio- logical methods into the lab. The basic requirement for these alternate methods is that they be at least equivalent to the traditional methods. The establish- ment of reasonable acceptance criteria for alternate methods requires that traditional methods be fully understood.
CoUNTAble rANGe oN A PlATe The general ranges in common acceptance for count- able numbers of colonies on a plate are 30–300 and 25–250. The origin of those ranges is worth exami- nation. breed and dotterrer published a seminal paper on this topic in 1916. They set out to determine the “limit in the number of colonies that may be allowed to grow on a plate without introducing serious errors in connection with the proposed revisions of stan- dard methods of milk analysis.” They note that “the kind of bacteria in the material under examination will have an influence on the size of the colonies, and consequently, on the number that can develop on a plate.” They also note that food supply can be an issue, colonies close to each other on the plate may merge, and that neighbor colonies may inhibit growth or conversely stimulate growth. “because of these and other difficulties, certain plates in any series made from a given sample are more satisfac- tory for use in computing a total than are others. The matter of selecting plates to be used in computing a count becomes, therefore, a matter requiring consid- erable judgment” (1). breed and dotterrer chose their countable plates from triplicate platings of each dilution, requiring acceptable plates to be within 20% of the average. on this analysis, plates with more than 400 CFU were unsatisfactory as were those of less than 30 CFU, with best results in the range of 50-200 CFU per plate. The major paper from Tomasiewicz et al. provides an excellent review of the continued evolution of the appropriate number of CFU per plate from milk. They took data from colony counts of raw milk from three different experiments (each dilution plated
in triplicate) and used them to determine a mean- squared-error of the estimate for all plates. Their recommendation at the end of the study was for a countable range of 25-250 CFU per plate in tripli- cate. Although the authors note that CFU follow a Poisson distribution, no mention is made of any data transformation used to approximate a normal distribution prior to the use of normal statistical analytical tools. Tomasiewicz et al. provide excel- lent cautionary advice: “The data presented herein are not necessarily applicable to other systems. For automated equipment, the optimum range may well vary with the instrument. Furthermore, even if auto- mation is not used appropriate numbers of colonies that should be on a countable plate can very widely, depending on many other variables. with soil fungi for example…” (2). The compendia have recently harmonized a mi- crobial enumeration test, and in this test recommend to “select the plates corresponding to a given dilu- tion and showing the highest number of colonies less than 250 for Total Aerobic Microbial Count (TAMC) and 50 for Total yeast and Mold Count (TyMC)” (3). in determination of the resistance of biological indi- cators, the United States Pharmacopeia (USP) recom- mends a range of “20 to 300 colonies, but not less than 6” (4). However, the most complete description of the countable range is found in the USP informa- tional chapter <1227> (5): “The accepted range for countable colonies on a standard agar plate is between 25 and 250 for most bacteria and Candida albicans. This range was estab- lished in the food industry for counting coliform bacteria in milk. The range is acceptable for com- pendial organisms, except for fungi. it is not optimal for counting all environmental monitoring isolates. The recommended range for Aspergillus niger is be- tween 8 to 80 CFU per plate. The use of membrane filtration to recover challenge organisms, or the use of environmental isolates as challenge organisms in the antimicrobial effectiveness testing, requires vali- dation of the countable range.” ASTM provides excellent review of countable ranges on a plate, recommending 20-80 CFU/mem- brane (when plating membrane filters for determi-
winter 2012 volume 16 Number 1 77
S c o t t S u t t o n
counts of 18 and 12 would be reported out as <2,500. This is, in my opinion, the prudent course. The crux of the argument is that experimental studies have shown very poor accuracy in plate counts below 25 (see above). Theoretically, we can argue that because the CFU follow the Poisson distribution, the error of the estimate is the square root of the average (5). This leads to graphs such as in Figure 2, which shows us that as the CFU per plate drops below the countable range, the error as a percent of the mean increases rap- idly. This confusion between the lod and the loQ for plate counts has led to some difficult situations.
UNUSUAl SiTUATioNS The following are some unusual situations that should be addressed in the laboratory’s SoP on “Plate Count- ing” to encourage consistent counting of colonies.
Two dilutions with Countable Colonies ideally you would never see two separate dilutions with counts in the countable range as the countable ranges cover a 10-fold range of CFU. However, this is microbiology and this situation is seen. ASTM recommendations urge you to take both dilutions into account, determining the CFU/ml (or gram) separately for each, and then averaging the re- sults for the final result (6). breed and dotterrer also used several dilutions if the numbers fit the quality control (QC) requirements (see below) (1). FdA bAM has no recommendations in this situation. while argument can be made to use all counts, this is a stronger argument if triplicate plates are used and QC limits are in place to discard erroneous plates. An- other approach can also be made to use the dilution
providing the larger number of CFU in the countable range to estimate the original number of CFU in the sample. This approach minimizes concerns that the errors in the estimates are increased with increasing serial dilutions, and the error in the estimate increases with decreasing plate counts. Use of the smaller dilu- tion (e.g., 1:10 vs. 1:100) could be justified from this perspective. Alternately, the USdA procedure recom- mends determining the deduced CFU (taking into ac- count the dilution factor) for each dilution separate- ly, then averaging the two estimates (8). whichever method used should be documented and justified in the “Counting CFU” SoP.
All Plates have Fewer Colonies than the Minimum of the Countable range if the average of the plates is below the lod, then report out the result as less than the lod. For ex- ample, plating out duplicates of 1 ml of a 1:10 dilu- tion, the lod is 10 CFU/ml. if no colonies grew on the 1:10 dilution plates, or if one colony grew on one plate (average of 0.5 CFU/plate), this should be reported out as <10 CFU/ml. The second situation is where the plates have col- onies but less than the countable range. The FdA bAM recommends reporting this out as <25 x dilu- tion Factor. in other words, if the best we had was a 1:1000 dilution with an average of 16 CFU/plate, this would be reported out as <25,000. USdA rec- ommends calculating the CFU as normal, but noting this as an estimate.
CFU/Plate
Error as % of Mean (^00)
1
5 10 15 20 25 30 35
Figure 2: error estimates of low plate counts. 10000 1000
CFU/Plate
100 10
1 Dilution
Expected Observed
Figure 1: estimated vs. observed plate counts.
78 Journal of GXP Compliance
P e e r r e v i e w e d : M i c r o b i o l o g y
while this particular situation may seem academ- ic, it is one that has significance for determination of adherence to quality specifications (see below).
QC limits on replicate Plate Counts Periodically, there are recommendations to estab- lish quality control limits on replicate plate counts. breed and dotterrer, in their 1916 paper, required valid plate counts from triplicate plates to provide estimates of CFU/ml within 20% of the mean (1). in other words, all plates were counted and each plate’s CFU count was used to estimate the original CFU/ ml. each estimate was evaluated, and if the estimate for each plate was within 30% of the mean, it was deemed acceptable. establishment of QC limits for plate counts works best if there are at least three replicate plates for each dilution and the relationship between accuracy and the number of CFU/plate is understood. weenk developed these discussions in an understandable discussion in relation to media growth promotion studies (9). His analysis assumed a 5.5% dilution er- ror from pipetting, and estimated the ability of par- allel plating experiments (new media vs. standard) to distinguish between two populations. The results are shown in Figure 3 (recalculated from weenk’s equations). This treatment clearly shows the effects of increas- ing the number of plates in replicate—increasing our ability to distinguish between similar populations. in a similar manner, we are able to distinguish small- er differences (the counting becomes more accurate) as the number of CFU per plate increases. Therefore, trying to establish a QC guideline for CFU/replicate (e.g., each replicate must be within 30% of the mean) may be problematic at lower CFU per plate counts. The method used to QC individual plate counts, if used, should be documented and justified in SoP, along with the response to finding variant counts.
Plating 10 x 1 ml Samples to Plate a Total of one 10 ml Sample There have been suggestions that a larger volume of material may be plated across several plates, and the results reported out for the larger volume. For
example, plating 10 x 1 ml samples on 10 different plates, and then reporting it as if a 10 ml sample was plated. This approach is flawed in that it ig- nores several sources of variability in plating includ- ing sampling, growth, and counting errors (9, 10). The correct interpretation for this situation is that you have just plated 1 ml 10 times, not 10 ml once. The numbers might be averaged—they cannot be added.
roUNdiNG ANd AverAGiNG discussion of rounding and averaging requires de- termination of what significant figures might be in the measure. For raw colony counts, common prac- tice determines that the CFU observed determine the significant figure, and that the average is one decimal place to the right of that number (sticklers for accuracy will report the geometric mean rather than the arithmetic mean given the Poisson distri- bution followed by CFU). That number is then mul- tiplied by the dilution factor. in other words, if the 10 -2^ plates have 125 and 114 colonies, the average is 119.5 times 10^2 , or 11950. in reporting, it is common practice to report out as scientific notation using two significant figures (in our example, 1.2 x 10 4 ). This requires rounding. ASTM and USP both round up at 5 if 5 is the num- ber to the right of the last significant figure (6, 11). FdA bAM has a more elaborate scheme, rounding up if the number is 6 or higher, down if 4 or lower (7). if the number is 5, bAM looks to the next number to the right and rounds up if it is odd, down if it is even.
0 0
50 100 n=2 n=3 n=5 n=
Average Plate Counts
95% Confidence Interval 150 200 250 300 350
Figure 3: Accuracy as a function of CFU/Plate and number of replicate plates.
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CoNClUSioNS All methods have limitations. one of the major limi- tations to the plate count method is the relatively narrow countable range (generally considered to be 25-250 CFU bacteria on a standard petri dish). The current prevailing confusion between the lod ( CFU) and loQ (25 CFU) for the plate count method creates a larger degree of variability in microbiol- ogy data than is necessary. An unfortunate regula- tory trend in recent years is to establish expectations (e.g., specifications, limits, levels) for data generated by the plate count method that the accuracy of the method cannot be supported. Compliance with the spirit of CGMP requires good science in observa- tion of the regulations. This is a real opportunity for modification of current practice to approach the goal of “science-based regulations.”
reFereNCeS
- breed, r and wd dotterrer, “The Number of Colonies Al- lowable on Satisfactory Agar Plates,” J bacteriol. 1:321-331,
- Tomasiewicz, d.M. et al., “The Most Suitable Number of Colonies on Plates for Counting,” J Food Prot. 43(4):282- 286, 1980.
- USP, <61> Microbial examination of Nonsterile Products: Microbial enumeration Tests, USP 34, United States Phar- macopeial Convention. pp. 52-56, 2011.
- USP, <55> biological indicators – resistance Performance Tests, USP 34, United States Pharmacopeial Convention, pp. 50-52, 2011.
- USP, <1227> validation of Microbial recovery from Phar- macopeial Articles, USP 34, United States Pharmacopeial Convention, pp. 783-786, 2011.
- ASTM, d5465-93(1998) Standard Practice for determining Microbial Colony Counts from waters Analyzed by Plating Methods, 1998.
- FdA, bacterial Analytical Manual, Maturin, lJ and JT Peeler. Chapter 3: Aerobic Plate Count. http://www.fda.gov/Food/ Scienceresearch/laboratoryMethods/bacteriologicalAna- lyticalManualbAM/ucm063346.htm (June 28, 2011) 8. USdA, laboratory Guidebook MlG 3.01 Quantitative Analysis of bacteria in Foods as Sanitary indicators, 2011 http://www.fsis.usda.gov/PdF/MlG_3_01.pdf (June 28, 2011). 9. weenk, G.H., “Microbiological Assessment of Culture Media: Comparison and Statistical evaluation of Methods,” int J Food Microbiol. 17:159-181, 1992. 10. Jennison, Mw and GP wadsworth, “evaluation of the errors involved in estimating bacterial Numbers by the Plating Method,” J bacteriol. 39:389-397, 1940. 11. USP, General Notices: 7.20 rounding rules, USP 34, United States Pharmacopeial Convention, p. 8, 2011. 12. Hussong, d and re Madsen, “Analysis of environmental Microbiology data From Cleanroom Samples,” Pharm Tech- nol. Aseptic Proc issue: 10-15, 2004. 13. Farrington, JK., “environmental Monitoring in Pharmaceu- tical Manufacturing-A Product risk issue,” Amer Pharm rev. 8(4):26-30, 2005. GXP
ArTiCle ACroNyM liSTiNG bAM bacterial Analytical Manual CFU Colony Forming Unit eM environmental Monitoring FdA US Food and drug Administration lod limit of detection loQ limit of Quantification QC Quality Control SoP Standard operating Procedure TAMC Total Aerobic Microbial Count TyMC Total yeast and Mold Count USdA US department of Agriculture USP United States Pharmacopeia
AboUT THe AUTHor Scott Sutton is the founder and principal consultant of Micro- biology Network, inc (http://bit.ly/n62yFG). He is a recognized consultant and trainer with emphasis in GMP, investigations, environmental monitoring, and contamination control as well as microbiology laboratory audits and operations. He may be reached by e-mail at scott.sutton@microbiol.org.
