Portable bacterial identification system based on elastic light scatter patterns

Identifying antibiotic-resistant strains via cell sorting and elastic-light-scatter phenotyping

The proliferation and dissemination of antimicrobial-resistant bacteria is an increasingly global challenge and is attributed mainly to the excessive or improper use of antibiotics. Currently, the gold-standard phenotypic methodology for detecting resistant strains is agar plating, which is a time-consuming process that involves multiple subculturing steps. Genotypic analysis techniques are fast, but they require pure starting samples and cannot differentiate between viable and non-viable organisms. Thus, there is a need to develop a better method to identify and prevent the spread of antimicrobial resistance. This work presents a novel method for detecting and identifying antibiotic-resistant strains by combining a cell sorter for bacterial detection and an elastic-light-scattering method for bacterial classification. The cell sorter was equipped with safety mechanisms for handling pathogenic organisms and enabled precise placement of individual bacteria onto an agar plate. The patterning was performed on an antibiotic-gradient plate, where the growth of colonies in sections with high antibiotic concentrations confirmed the presence of a resistant strain. The antibiotic-gradient plate was also tested with an elastic-light-scattering device where each colony's unique colony scatter pattern was recorded and classified using machine learning for rapid identification of bacteria. Sorting and patterning bacteria on an antibiotic-gradient plate using a cell sorter reduced the number of subculturing steps and allowed direct qualitative binary detection of resistant strains. Elastic-light-scattering technology is a rapid, label-free, and non-destructive method that permits instantaneous classification of pathogenic strains based on the unique bacterial colony scatter pattern. KEY POINTS: • Individual bacteria cells are placed on gradient agar plates by a cell sorter • Laser-light scatter patterns are used to recognize antibiotic-resistant organisms • Scatter patterns formed by colonies correspond to AMR-associated phenotypes.

Identification of colonies of cultured shellfish-associated Arcobacter species by Elastic Light Scatter Analysis

An increasing number of Arcobacter species (including several regarded as emerging human foodborne pathogens) have been isolated from shellfish, an important food commodity. A method to distinguish these species and render viable isolates for further analysis would benefit epidemiological and ecological studies. We describe a method based on Elastic Light Scatter analysis (ELSA) for the detection and discrimination of eleven shellfish-associated Arcobacter species. Although substantive differences in the growth rates of some taxa were seen, ELSA was able to differentiate all the species studied, apart from some strains of A. butzleri and A. cryaerophilus, which were nonetheless distinguished from all other species examined. ELSA appears to be a promising new approach for the detection and identification of Arcobacter species in shellfish and may also be applicable for studies in other foods and matrices.

Elastic Light Scatter Pattern Analysis for the Expedited Detection of Yersinia Species in Pork Mince: Proof of Concept

Isolation of the pathogens Yersinia enterocolitica and Yersinia pseudotuberculosis from foods typically rely on slow (10–21 day) “cold enrichment” protocols before confirmed results are obtained. We describe an approach that yields results in 39 h that combines an alternative enrichment method with culture on a non-selective medium, and subsequent identification of suspect colonies using elastic light scatter (ELS) analysis. A prototype database of ELS profiles from five Yersinia species and six other bacterial genera found in pork mince was established, and used to compare similar profiles of colonies obtained from enrichment cultures from pork mince samples seeded with representative strains of Y. enterocolitica and Y. pseudotuberculosis. The presumptive identification by ELS using computerised or visual analyses of 83/90 colonies in these experiments as the target species was confirmed by partial 16S rDNA sequencing. In addition to seeded cultures, our method recovered two naturally occurring Yersinia strains. Our results indicate that modified enrichment combined with ELS is a promising new approach for expedited detection of foodborne pathogenic yersiniae.

Integrated multi-channel optical system for bacteria characterization and its potential use for monitoring of environmental bacteria

The potential use of a novel multichannel optical system towards fast and non-destructive bacteria identification and its application for environmental bacteria characterisation on the strain level is presented. It is the first attempt to use the proposed optical method to study various bacteria species (Gram-negative, Gram-positive) commonly present in the environment. The novel configuration of the optical system enables multichannel examination of bacterial colonies and provides additional functionality such as registration of two-dimensional (2D) distribution of monochromatic transmission coefficient of examined colonies, what can be used as a novel optical signature for bacteria characterization. Performed statistical analysis indicates that it is possible to identify representatives of environmental soil bacteria on the species level with the 98.51% accuracy and in case of two strains of Rahnella aquatilis bacteria on the strain level with the 98.8% accuracy. The proposed method is an alternative to the currently used preliminary bacteria examination in environment safety control with the advantage of being fast, reliable, non-destructive and requiring minimal sample preparation.

Automated Visualization of Genetic Designs Using DNAplotlib

Visualization of complex genetic systems can help efficiently communicate important design features and clearly illustrate overall structures. To aid in the creation of such diagrams, standards such as the Synthetic Biology Open Language Visual (SBOLv) have been established to ensure that specific symbols and shapes convey the same meaning for genetic parts across the field. Here, we describe several ways that the computational tool DNAplotlib can be used to automate the generation of SBOLv standard-compliant diagrams covering simple genetic designs to large libraries of genetic constructs.

Patterns in Saccharomyces cerevisiae yeast colonies via magnetic resonance imaging

We report the use of high-resolution magnetic resonance imaging methods to observe pattern formation in colonies of Saccharomyces cerevisiae. Our results indicate substantial signal loss localized in specific regions of the colony rendering useful imaging contrast. This imaging contrast is recognizable as being due to discontinuities in magnetic susceptibility (χ) between different spatial regions. At the microscopic pixel level, the local variations in the magnetic susceptibility (Δχ) induce a loss in the NMR signal, which was quantified via T₂ and T₂* maps, permitting estimation of Δχ values for different regions of the colony. Interestingly the typical petal/wrinkling patterns present in the colony have a high degree of correlation with the estimated susceptibility distribution. We conclude that the presence of magnetic susceptibility inclusions, together with their spatial arrangement within the colony, may be a potential cause of the susceptibility distribution and therefore the contrast observed on the images.

Current status and future prospects of using advanced computer-based methods to study bacterial colonial morphology

Despite the advancement of recent molecular technologies, culturing is still considered the gold standard for microbial sample analysis. Here we review three different bacterial colony-based screening modalities that provide significant information beyond the simple shape and color of the colony. The plate imaging technique provides numeration and quantitative spectral reflectance information for each colony, while Raman spectroscopic analysis of bacteria colonies relates the Raman-shifted peaks to specific chemical bonding. Finally, the elastic-light-scatter technique provides a volumetric interaction of the whole colony through laser-bacteria interactions, instantly capturing the morphological traits of the colony and allowing quantitative classifications.

Bacteria identification in an optical system with optimized diffraction pattern registration condition supported by enhanced statistical analysis

It is possible to identify bacteria species basing on their diffraction patterns followed by statistical analysis. The new approach exploits two steps: optimization of the recording conditions and introduction of new interpretable features for the identification. First, optimal diffraction registration plane, was determined. Next, results were verified by the analysis workflow based on ANOVA and Fisher divergence for feature selection, QDA and SVM models for classification and identification and CV with stratified sampling, sensitivity and specificity for performance assessment of the identification process. The proposed approach resulted in high sensitivity 0.9759 and specificity 0.9903 with very small identification error 1.34%.