It is Quality and Quantity Which Matter

Many credit the ancient Roman stoic Seneca the Younger as the first to say “it is quality rather than quantity which matters.” While it is highly doubtful he was the first to make such a statement, he was the first to say it whose words were written down and preserved. Seneca might be dismayed to learn that his “wise” sayings have been so overused that today many are cliches. They include such classics as; money doesn’t buy happiness (Suppose all the belongings of many rich men were piled upon you….What will you learn from these things? Only how to desire more), live in the now (True happiness is… to enjoy the present, without anxious dependence upon the future), use it or lose it (Difficulties strengthen the mind, as labor does the body), you make your own luck (Luck is what happens when preparation meets opportunity), and, things are much better than they seem (we suffer more from imagination than from reality), to name just a few choice examples.

In contrast to Seneca’s assertion, for microbiology at least, both quantity and quality matter, or at least an aspect of them does, and microbiological methods are classified as being either quantitative or qualitative. Which category they fall into is based on what type of data is actually collected. In the vernacular of many scientific disciplines the word “qualitative” refers to descriptions or distinction based on some quality or characteristic in contrast to quantity which is a measured amount. In other words the type of data collected by qualitative methods are descriptions, qualities, or characteristics. In microbiology the specific characteristic being assessed is the absence or presence of a particular organism (typically a pathogen) in a given sample. Qualitative tests are usually very sensitive so they are able to detect the targeted organism(s) at very low population levels (as low as 1 cell per sample being tested). Examples of qualitative tests important in food microbiology include analyses for human pathogens such as Listeria, Salmonella, E. coli O157:H7/STEC. The results of qualitative tests can be reported in several different ways including, “Negative or “Positive”, “Detected or Not Detected”, or “Absent or Present” per the tested weight or volume. For example, Negative/25g or Positive/375g.

The word “quantitative” refers to a type of information based on quantities or otherwise quantifiable data (objective properties). In other words the type of of data collected is a measured, quantifiable (typically numerical) amount. Quantitative testing aims to determine the population size (total numbers) of microorganisms present in a sample. Some quantitative tests are used to count populations of indicator organisms (aerobic plate count, most probable number (MPN), coliform count, total Enterobacteriaceae counts, etc.) while others count populations of specific target organisms (Staphylococcus, Yeast, Mold, etc.). Interestingly and sometimes confusingly a qualitative result is inherent in a quantitative method, after all you cannot count something which isn’t there. Therefore a quantitative value indicates presence of the target organism. These are reported in the form of a number of organisms per unit. To make the matter even more confusing for some qualitative methods (i.e. qPCR) the qualitative result call is based on what is traditionally considered a quantitative output (Ct or Cq value).

Built into all quantitative methods is a “limit of detection (LOD) or “detection limit” — meaning that the method is capable of detecting the target organism(s) at or above that limit. This is sometimes also referred to as the lower limit of detection (LLOD) of the method. Because the limit of detection of any given quantitative method is always greater than zero, results of such tests cannot be reported as negative or absent. Most standard plate count methods have a detection limit of 10 CFU/g and MPN methods have a detection limit of 3 MPN/g (assuming standard ten-fold dilutions). If no growth of the target organism(s) is detected, the result will be reported as “less than” the limit of detection (i.e. <10 CFU/g or < 3 MPN/g). Often the question is asked “Is <10 CFU/g the same as a negative result?” The short answer is no, they are not the same. The longer answer would say that while it is not possible to answer that question in the affirmative, we can say that a “less than” result means that the target organism was not detected in the sample, though we cannot say it is absent from the sample. Regulatory bodies, validation agencies, and others in industry recognize this limitation of quantitative methods and typically treat results that are reported as <LOD as negative for all practical purposes. The concept of LOD is critical to understand for anyone requesting microbiological testing. If the presence of 1 bacterium in a product or process is cause for alarm, then selecting a method with an LOD of 10 could have disastrous consequences.

Compared to qualitative methods, which, for most people, are relatively easy to understand and intuitive, it can be difficult to wrap your head around the concept of quantitative testing methods and the results given by them. To help illustrate the concept of quantitative methods let’s consider an example problem. A sample is processed by diluting it tenfold with a sterile buffer. The diluent-sample mixture is plated (most typically 100ul or 1ml) on the appropriate growth medium and incubated. The plates are then counted. The result is calculated by multiplying the number of colonies on a plate by the dilution factor divided by the volume plated, and by convention is always expressed as CFU/ml. If there is one colony on the plate and 1ml was plated, the result is 10 CFU/ml. If 100ul were plated the result would be 100 CFU/ml. If there are five colonies on the plate, the count is 50 CFU (or 50 CFU/ml if 1ml is plated). Because there can’t be between 0 and 1 colony, the minimum countable result is 10 cfu. For samples with microbial population sizes below 10 CFU it is not mathematically possible to determine an accurate count unless one plates out 10 plates of the 1 to 10 dilution, which would increase the cost of doing a plate count by a factor of 10. If you followed the math and logic of the above you will realize that plating onto ten plates is the same as plating 10ml onto one plate (if each plate is 1ml). For practical reasons this is almost never done. In any case people paying testing would object to such a costly test and they typically understand or can be made to understand the theoretical limitations of the methods when counts are very low. Let’s take another example, assume there are 5 CFU/g of bacteria present in a given food sample. This is a very low level and it is expressed as per gram because the sample being analyzed is a solid in this case. For purposes of this example it is the same thing as 5 CFU/ml. After the initial tenfold dilution, the concentration will be reduced to 0.5 CFU/g of bacteria. Because you cannot count half a bacterium you stand a 50:50 chance of having no growth on the plate. To go even lower, assume the count were 1 CFU/g in the sample. In this case the odds of finding a colony on a plate would be 1 in 9, hence the majority of times you run the assay you would not find countable plates even though there is bacteria present in the sample. For these reasons the method specifies that a plate with no colonies at the lowest dilution shall be reported as <10 CFU. Another way to think about this is to imagine a liquid sample that is 10ml and which contains just a single bacterium. If you pull and plate 1ml ten times you only have a 1 in 9 chance of pulling the 1ml that happens to have the bacterium in it with the first sampling. Assuming you do not get it the first time, with each subsequent sampling and plating event your odds get better. If you want to guarantee detection of the bacterium everytime (i.e. you want to increase the sensitivity of the test) one way is to sample and plate the entire volume. There are other ways to do this too and you may be able to imagine some on your own. If you happen to come up with any great ideas that have never been thought of or tried before you stand a good chance of becoming a very wealthy, and maybe even famous individual. Probably not as famous as Seneca, but one never knows…