Antibiotic resistance profiling (ARP) is a potentially useful method for distinguishing faecal bacteria according to host source. This phenotypic approach has cost benefits over genotypic methods, but existing protocols are time-consuming and manual data handling is open to human error. A simplified, low-cost approach to the ARP technique was developed that used automated data recording techniques combined with simple statistical analyses to compare isolates of the genus Enterococcus from various faecal sources. An initial battery of 21 antibiotics (at up to four concentrations) was chosen for source discrimination. Images of growth or non-growth in microplate wells were stored as bitmaps and converted to binary data to form a database of known antibiotic resistance profiles. Discriminant function analysis (DFA) showed that the average rate of isolates correctly classified by the database (wastewater vs non-wastewater) was 86%. Once the more discriminating antibiotics and their concentrations had been identified, it was possible to reduce the number of tests from 80 to 18 whilst increasing the number of correctly classified human isolates. ARP could offer a low-cost and rapid means of identifying sources of faecal pollution. As such, the technique may be of particular benefit to developing countries, where water quality may have a significant impact on health and where cost is a major factor when choosing environmental management technology.
Multiscale additive manufacturing of polymers using 3D photo-printable self-assembling ionic liquid monomers