Binding of nontarget microorganisms from food washes to anti-Salmonella and anti-E. coli O157 immunomagnetic beads: minimizing the errors of random sampling in extreme dilute systems.

For most applications, 3-5 observations, or samplings (n), are utilized to estimate total aerobic plate count in an average population (μ) that is greater than about 50 cells, or colony forming units (CFU), per sampled volume. We have chosen to utilize a 6 × 6 drop plate method for bacterial colony selection because it offers the means to rapidly perform all requisite dilutions in a 96-well format and plate these dilutions on solid media using minimal materials. Besides traditional quantitative purposes, we also need to select colonies which are well-separated from each other for the purpose of bacterial identification. To achieve this goal using the drop plate format requires the utilization of very dilute solutions (μ < 10 CFUs per sampled drop). At such low CFU densities the sampling error becomes problematic. To address this issue we produced both observed and computer-generated colony count data and divided a large sample of individual counts randomly into N subsamples each with n = 2-24 observations (N × n = 360). From these data we calculated the average total mean-normalized (x⁻(tot), n = 360) deviation of the total standard deviation (s (tot)) from each jth subsample's estimate (s ( j )), which we call Δ. When either observed or computer-generated Δ values were analyzed as a function of x⁻(tot), a set of relationships (∞ ₋₂√ ⁻x(tot)) were generated which appeared to converge at an n of about 18 observations. This finding was verified analytically at even lower CFU concentrations (⁻x(tot) ≈ 1 − 10 CFUs per observation). Additional experiments using the drop plate format and n = 18 samplings were performed on food samples along with most probable number (MPN) analyses and it was found that the two enumeration methods did not differ significantly.