Table of Contents
ISRN Microbiology
Volume 2013, Article ID 257313, 11 pages
Research Article

Acoustic Emission Signal of Lactococcus lactis before and after Inhibition with NaN3 and Infection with Bacteriophage c2

1Tribo Flow Separations, 2324 Lilac Park, Lexington, KY 40509, USA
2Ferm Solutions Inc. 445 Roy Arnold Avenue, Danville, KY 40423, USA
3Department of Animal & Food Sciences, University of Kentucky, Lexington, KY 40546, USA
4Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, KY 40546, USA
5Department of Civil and Materials Engineering, University of Illinois at Chicago, Chicago, IL 60607-7023, USA

Received 2 August 2013; Accepted 29 August 2013

Academic Editors: T. Alatossava and H. Asakura

Copyright © 2013 Debasish Ghosh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The detection of acoustic emission (AE) from Lactococcus lactis, ssp lactis is reported in which emission intensities are used to follow and define metabolic activity during growth in nutrient broths. Optical density (OD) data were also acquired during L. lactis growth at 32°C and provided insight into the timing of the AE signals relative to the lag, logarithmic, and stationary growth phases of the bacteria. The inclusion of a metabolic inhibitor, NaN3, into the nutrient broth eliminated bacteria metabolic activity according to the OD data, the absence of which was confirmed using AE data acquisition. The OD and AE data were also acquired before and after the addition of Bacteriophage c2 in L. lactis containing nutrient broths during the early or middle logarithmic phase; c2 phage m.o.i. (Multiplicity of infection) was varied to help differentiate whether the detected AE was from bacteria cells during lysis or from the c2 phage during genome injection into the cells. It is proposed that AE measurements using piezoelectric sensors are sensitive enough to detect bacteria at the amount near  cfu/mL, to provide real time data on bacteria metabolic activity and to dynamically monitor phage infection of cells.