In-vitro diagnosis of single and poly microbial species targeted for diabetic foot infection using e-nose technology

Abstract

Background: Effective management of patients with diabetic foot infection is a crucial concern. A delay in prescribing appropriate antimicrobial agent can lead to amputation or life threatening complications. Thus, this electronic nose (e-nose) technique will provide a diagnostic tool that will allow for rapid and accurate identification of a pathogen.

Results: This study investigates the performance of e-nose technique performing direct measurement of static headspace with algorithm and data interpretations which was validated by Headspace SPME-GC-MS, to determine the causative bacteria responsible for diabetic foot infection. The study was proposed to complement the wound swabbing method for bacterial culture and to serve as a rapid screening tool for bacteria species identification. The investigation focused on both single and poly microbial subjected to different agar media cultures. A multi-class technique was applied including statistical approaches such as Support Vector Machine (SVM), K Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA) as well as neural networks called Probability Neural Network (PNN). Most of classifiers successfully identified poly and single microbial species with up to 90% accuracy.

Conclusions: The results obtained from this study showed that the e-nose was able to identify and differentiate between poly and single microbial species comparable to the conventional clinical technique. It also indicates that even though poly and single bacterial species in different agar solution emit different headspace volatiles, they can still be discriminated and identified using multivariate techniques.

Figure 1

Odour sniffing setup. Cyranose320 (e-nose) was setup for headspace evaluation of poly and single bacteria species infusions.

Figure 2

Signal response for odour recognition. A surface plot shows the visualized data for single bacteria samples gathered using a Cyranose320 e-nose system.

Figure 3

Supervised LDA plot for ATCC standard and wild-type bacteria in blood agar. The wild-type bacteria obtained from the samples debridement of diabetic foot wound were compared with the ATCC standard bacteria. The sign ‘+’ and ‘O’ in the plot are used to highlight the training and testing phase (blind test).

Figure 4

LDA plot of single bacteria species in three different mediums. This diagram is to show the clear vision of one group of single bacteria in three different mediums (blood agar, Mueller Hinton & MacConkey).

Figure 5

LDA plot of single and poly microbial species in three different media. This combination of single and poly microbial in different media is to study the effectiveness of e-nose to classify the bacteria in a different group region.

Figure 6

Chromatograms of single bacteria species using headspace SPME-GCMS. The GCMS result shows that the different bacteria species emitted different biomarkers which confirm the e-nose result.

Figure 7

Chromatograms of poly microbial species using headspace SPME-GCMS. The GCMS result shows that the VOCs emitted when combine the two bacteria species in one media culture.