# Bielectroanalytical Detection of Lactic Acid Bacteria
## 3 Results and Discussion  
_E. faecalis_ can easily be detected and enumerated using the proposed detection framework described previously [7; 13]. Chronoamperometric analysis of _E. faecalis_ reveals that all test inocula, with the exception of 10\({}^{7}\) CFU mL\({}^{-1}\) where the current onset is almost instant, produce a distinctive curve showing an initial flat period of baseline current representing lag phase growth followed by a sharp increase in current generation resulting from increased metabolic activity (and thus EET) as the culture enters the exponential growth phase (Figure 2A). A previously reported method defines a detection event when the slope of the chronoamperometric readout exceeds five standard deviations of the baseline current for more than five consecutive time points [13]. We apply a more conservative definition here and define detection as the time at which the current passes a threshold value (20 \(\mu\)A). This is an objective and robust way to define a detection time and yields a linear calibration curve that inversely correlates with inoculum size. For every log fold increase in inoculum size ranging from 10,000 to 10,000,000 CFU mL\({}^{-1}\), the detection time increased linearly, yielding mean detection times of 235 (\(\pm\)16), 148 (\(\pm\)12), 62 (\(\pm\)12), and 32 (\(\pm\)8) min for 10\({}^{4}\), 10\({}^{5}\), 10\({}^{6}\), and 10\({}^{7}\) CFU mL\({}^{-1}\), respectively, where the values in parentheses represents the standard deviation of three replicates. This observation is easily interpreted from the relationship between inoculum density and the duration of the lag phase in classical growth curve theory. This property can be used to construct a linear standard curve with a regression coefficient (r\({}^{2}\)) of 0.96 (Figure 2B). Additionally, the standard deviation of the mean detection time for three replicates is between 7 and 23%, which is comparable to previous reports and also to commercially available systems for bacterial detection [4; 7; 20]. In short, the bioelectroanalytical system is an effective means of enumerating _E. faecalis_ and should be further developed to effect real world detection of lactobacilli in the multitude of settings for which they are relevant. This will require development of selective medium to suppress non-target organisms that are specific to the individual settings. The detection compounds used here are electroactive glycosides comprising glucose conjugated to resorufin. When the glycosidic bond is cleaved by native glucosidases expressed by _E. faecalis_, the electroactive resorufin is liberated from the pyranose ring and subsequently reduced by microbial electron carriers to dihydroresorufin [21]. Following its reduction by microbes, the mobile dihydroresorufin in turn reduces the electrode generating a current proportional to the metabolic activity of the culture [22]. Microbial metabolic coupling to an electrode via a mobile redox mediator is well documented and usually described as a component of an energy-yielding type of respiration called mediated EET [23]. The quantitative importance of respiration compared to fermentation in a similar bioelectroanalytical detector was recently demonstrated by contrasting mediated detection times achieved with wildtype _E. coli_ vs. a mutant, _E. coli_ SHSP 18--an _E. coli_ K12 derivative that is auxotrophic for \(\delta\)-aminolevulinic acid, a growth factor critical in heme synthesis and therefore respiration [13; 24]. The wildtype _E. coli_ detection time, for an inoculum sizeof 5000 CF, was about 6 h compared with the detection time of around 14 h for the SHSP 18 mutant that was unable to respire. Thus, from this previously reported study, it appears that fermentative metabolism is not ideally compatible with bioelectroanalytical detection even in the presence of mediators. The detection time for _E. faecalis_ observed here (Figure 2A) cannot be directly compared to the previous studies, but it is likely to be similar.