Binding of nontarget microorganisms from food washes to anti-<Emphasis Type="Italic">Salmonella</Emphasis> and anti-<Emphasis Type="Italic">E. coli</Emphasis> 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 (, 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 , a set of relationships () were generated which appeared to converge at an n of about 18 observations. This finding was verified analytically at even lower CFU concentrations (). 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. Any reference to a particular brand or company name does not constitute an endorsement of it by the U.S. Department of Agriculture over other similar brands or companies that are not mentioned.     

Seasonal dynamics of dimethylarsinic‐acid‐decomposing bacteria dominating in Lake Kahokugata

Decomposition processes of organoarsenic compounds significantly influence arsenic cycles in aquatic environments, and such processes depend on bacterial activity. However, the bacterial characteristics in these environments are obscure. Accordingly, we observed seasonal variations of arsenic species and the bacterial population decomposing dimethylarsinic acid (DMAA) in Lake Kahokugata from April 2002 to January 2003. Monitoring of bacterial biomass involving DMAA decomposition using the most probable number procedure showed that the bacterial cell densities ranged from 36 to 3600 ml^?1. On the other hand, methylated arsenic was not detected during the experimental period, although the inorganic arsenic concentration was over 4 nM . This suggests that bacteria remineralized methylated arsenic species to inorganic arsenic. Furthermore, the composition of bacterial communities involving DMAA decomposition was examined by restriction‐fragment‐length polymorphism analysis of the 16S rDNA nucleotide. As a result, a total of 49 isolates were classified into 10 type groups, and 32 of these isolates belonged to three dominant type groups. Phylogenetic analysis using 16S rDNA partial sequences (ca 320 bp) suggests that the representative isolates of the dominant type groups are specific to the summer or winter season. Moreover, as a result of the culture experiments to examine DMAA decomposition activity, the representative isolates decomposed 1 µM DMAA at a decomposition percentage of below 80%. In conclusion, some bacterial communities in a specific season can decompose DMAA to varying degrees, contributing to the annual cycle of arsenic species. Copyright © 2005 John Wiley & Sons, Ltd.     

The Effects of Surfactants on the Estimation of Bacterial Density in Petroleum Samples

The effect of the surfactants polyoxyethylene monostearate (Tween 60), polyoxyethylene monooleate (Tween 80), cetyl trimethyl ammonium bromide (CTAB), and sodium dodecyl sulfate (SDS) on the estimation of bacterial density (sulfate-reducing bacteria [SRB] and general anaerobic bacteria [GAnB]) was examined in petroleum samples. Three different compositions of oil and water were selected to be representative of the real samples. The first one contained a high content of oil, the second one contained a medium content of oil, and the last one contained a low content of oil. The most probable number (MPN) was used to estimate the bacterial density. The results showed that the addition of surfactants did not improve the SRB quantification for the high or medium oil content in the petroleum samples. On other hand, Tween 60 and Tween 80 promoted a significant increase on the GAnB quantification at 0.01% or 0.03% m/v concentrations, respectively. CTAB increased SRB and GAnB estimation for the sample with a low oil content at 0.00005% and 0.0001% m/v, respectively.