Optical scatter patterns facilitate rapid differentiation of Enterobacteriaceae on CHROMagar™ Orientation medium

Deciphering assembly processes, network complexity and stability of potential pathogenic communities in two anthropogenic coastal regions of a highly urbanized estuary

The existence of potential pathogens may lead to severe water pollution, disease transmission, and the risk of infectious diseases, posing threats to the stability of aquatic ecosystems and human health. In-depth research on the dynamic of potential pathogenic communities is of significant importance, it can provide crucial support for assessing the health status of aquatic ecosystems, maintaining ecological balance, promoting sustainable economic development, and safeguarding human health. Nevertheless, the current understanding of the distribution and geographic patterns of potential pathogens in coastal ecosystems remains rather limited. Here, we investigated the diversity, assembly, and co-occurrence network of potential pathogenic communities in two anthropogenic coastal regions, i.e., the eight mouths (EPR) and nearshore region (NSE), of the Pearl River Estuary (PRE) and a total of 11 potential pathogenic types were detected. The composition and diversity of potential pathogenic communities exhibited noteworthy distinctions between the EPR and NSE, with 6 shared potential pathogenic families. Additionally, in the NSE, a significant pattern of geographic decay was observed, whereas in the EPR, the pattern of geographic decay was not significant. Based on the Stegen null model, it was noted that undominant processes (53.36%/ 69.24%) and heterogeneous selection (27.35%/ 25.19%) dominated the assembly of potential pathogenic communities in EPR and NSE. Co-occurrence network analysis showed higher number of nodes, a lower average path length and graph diameter, as well as higher level of negative co-occurrences and modularity in EPR than those in NSE, indicating more complex and stable correlations between potential pathogens in EPR. These findings lay the groundwork for the effective management of potential pathogens, offering essential information for ecosystem conservation and public health considerations in the anthropogenic coastal regions.

Petri-plate, bacteria, and laser optical scattering sensor

Classical microbiology has paved the path forward for the development of modern biotechnology and microbial biosensing platforms. Microbial culturing and isolation using the Petri plate revolutionized the field of microbiology. In 1887, Julius Richard Petri invented possibly the most important tool in microbiology, the Petri plate, which continues to have a profound impact not only on reliably isolating, identifying, and studying microorganisms but also manipulating a microbe to study gene expression, virulence properties, antibiotic resistance, and production of drugs, enzymes, and foods. Before the recent advances in gene sequencing, microbial identification for diagnosis relied upon the hierarchal testing of a pure culture isolate. Direct detection and identification of isolated bacterial colonies on a Petri plate with a sensing device has the potential for revolutionizing further development in microbiology including gene sequencing, pathogenicity study, antibiotic susceptibility testing , and for characterizing industrially beneficial traits. An optical scattering sensor designated BARDOT (bacterial rapid detection using optical scattering technology) that uses a red-diode laser, developed at the beginning of the 21^st century at Purdue University, some 220 years after the Petri-plate discovery can identify and study bacteria directly on the plate as a diagnostic tool akin to Raman scattering and hyperspectral imaging systems for application in clinical and food microbiology laboratories.

Rapid, Low-Complexity, Simultaneous Bacterial Group Identification and Antimicrobial Susceptibility Testing Performed Directly on Positive Blood Culture Bottles Using Chromogenic Agar

The use of positive blood culture bottles for direct disk diffusion susceptibility testing (dDD), together with chromogenic culture limited to groups of pathogens for antimicrobial susceptibility testing interpretation may provide a means for laboratories-in-development to introduce rapid abbreviated blood culture testing. We assessed the performance of dDD on Chromatic MH agar using contrived positive blood culture bottles and compared findings with current standard practice. Furthermore, we characterized the growth of 24 bacterial and 3 yeast species on Chromatic MH agar with the aid of rapid spot tests for same-day identification. The coefficient of variation for reproducibility of dDD of four reference strains in 4 to 10 replicates (238 data points) ranged from 0% to 16.3%. Together with an additional 10 challenge isolates, the overall categorical agreement was 91.7% (351 data points). The following bacteria were readily identifiable: cream/white Staphylococcus aureus, coagulase-negative staphylococci, Streptococcus pyogenes; turquoise Streptococcus agalactiae, enterococci, Listeria monocytogenes; mauve Escherichia coli, Shigella sonnei, Citrobacter freundii; dark-blue Klebsiella and Enterobacter; green Pseudomonas aeruginosa; and brown Proteus. Clear colonies were seen with Salmonella, Acinetobacter, Burkholderia, and Yersinia enterocolitica (turns pink). Our study suggests that Chromatic MH for dDD may show promise as a rapid, clinically useful presumptive method for overnight simultaneous identification and antimicrobial susceptibility testing. However, there is a need to optimize the medium formulation to allow the recovery of Streptococcus pneumoniae and Haemophilus influenzae.

Current State of Development of Biosensors and Their Application in Foodborne Pathogen Detection

ABSTRACT

Foodborne disease outbreaks continue to be a major public health and food safety concern. Testing products promptly can protect consumers from foodborne diseases by ensuring the safety of food before retail distribution. Fast, sensitive, and accurate detection tools are in great demand. Therefore, various approaches have been explored recently to find a more effective way to incorporate antibodies, oligonucleotides, phages, and mammalian cells as signal transducers and analyte recognition probes on biosensor platforms. The ultimate goal is to achieve high specificity and low detection limits (1 to 100 bacterial cells or piconanogram concentrations of toxins). Advancements in mammalian cell-based and bacteriophage-based sensors have produced sensors that detect low levels of pathogens and differentiate live from dead cells. Combinations of biotechnology platforms have increased the practical utility and application of biosensors for detection of foodborne pathogens. However, further rigorous testing of biosensors with complex food matrices is needed to ensure the utility of these sensors for point-of-care needs and outbreak investigations.

HIGHLIGHTS

Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor

Recently proposed methods of bacteria identification in optical biosensors based on the phenomenon of light diffraction on macro-colonies offer over 98% classification accuracy. However, such high accuracy relies on the comparable and repeatable spatial intensity distribution of diffraction patterns. Therefore, it is essential to eliminate all non-species/strain-dependent factors affecting the diffraction patterns. In this study, the impact of the bacterial colony and illuminating beam misalignment on the variation of classification features extracted from diffraction patterns was examined. It was demonstrated that misalignment introduced by the scanning module significantly affected diffraction patterns and extracted classification features used for bacteria identification. Therefore, it is a crucial system-dependent factor limiting the identification accuracy. The acceptable misalignment level, when the accuracy and quality of the classification features are not affected, was determined as no greater than 50 µm. Obtained results led to development of image-processing algorithms for determination of the direction of misalignment and concurrent alignment of the bacterial colonies’ diffraction patterns. The proposed algorithms enable the rigorous monitoring and controlling of the measurement’s conditions in order to preserve the high accuracy of bacteria identification.

Simultaneous detection of Salmonella enterica, Escherichia coli and Listeria monocytogenes in food using a light scattering sensor

AIM

To investigate the use of a light scattering sensor, BActerial Rapid Detection using Optical scattering Technology (BARDOT) coupled with a multipathogen selective medium, Salmonella, Escherichia and Listeria (SEL), for concurrent detection of the three major foodborne pathogens in a single assay.

METHODS AND RESULTS

BARDOT was used to detect and distinguish the three major pathogens, Salmonella enterica, Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes from food based on colony scatter signature patterns on SEL agar (SELA). Multiple strains of three test pathogens were grown on SELA, and BARDOT was used to generate colony scatter image libraries for inclusive (SEL Library) and exclusive (non-SEL Library) bacterial group. These pathogens were further differentiated using the SEL scatter image library. Raw chicken and hotdog samples were artificially inoculated with pathogens (100 CFU per 25 g each), and enriched in SEL broth at 37°C for 18 h and colonies were grown on SELA for 11-22 h before screening with BARDOT. The BARDOT sensor successfully detected and differentiated Salmonella, STEC and Listeria on SELA with high classification accuracy 92-98%, 91-98% and 83-98% positive predictive values (PPV) respectively; whereas the nontarget strains showed only 0-13% PPV. BARDOT-identified colonies were further confirmed by multiplex PCR targeting inlB gene of L. monocytogenes, stx2 of STEC and sefA of S. enterica serovar Enteritidis.

CONCLUSIONS

The results show that BARDOT coupled with SELA can efficiently screen for the presence of three major pathogens simultaneously in a test sample within 29-40 h.

SIGNIFICANCE AND IMPACT OF THE STUDY

This innovative SELA-BARDOT detection platform can reduce turnaround time and economic burden on food industries by offering a label-free, noninvasive on-plate multipathogen screening technology for reducing microbial food safety and public health concerns.

Virulence Gene-Associated Mutant Bacterial Colonies Generate Differentiating Two-Dimensional Laser Scatter Fingerprints

In this study, we investigated whether a laser scatterometer designated BARDOT (bacterial rapid detection using optical scattering technology) could be used to directly screen colonies of Listeria monocytogenes, a model pathogen, with mutations in several known virulence genes, including the genes encoding Listeria adhesion protein (LAP; lap mutant), internalin A (ΔinlA strain), and an accessory secretory protein (ΔsecA2 strain). Here we show that the scatter patterns of lap mutant, ΔinlA, and ΔsecA2 colonies were markedly different from that of the wild type (WT), with >95% positive predictive values (PPVs), whereas for the complemented mutant strains, scatter patterns were restored to that of the WT. The scatter image library successfully distinguished the lap mutant and ΔinlA mutant strains from the WT in mixed-culture experiments, including a coinfection study using the Caco-2 cell line. Among the biophysical parameters examined, the colony height and optical density did not reveal any discernible differences between the mutant and WT strains. We also found that differential LAP expression in L. monocytogenes serotype 4b strains also affected the scatter patterns of the colonies. The results from this study suggest that BARDOT can be used to screen and enumerate mutant strains separately from the WT based on differential colony scatter patterns.

IMPORTANCE

In studies of microbial pathogenesis, virulence-encoding genes are routinely disrupted by deletion or insertion to create mutant strains. Screening of mutant strains is an arduous process involving plating on selective growth media, replica plating, colony hybridization, DNA isolation, and PCR or immunoassays. We applied a noninvasive laser scatterometer to differentiate mutant bacterial colonies from WT colonies based on forward optical scatter patterns. This study demonstrates that BARDOT can be used as a novel, label-free, real-time tool to aid researchers in screening virulence gene-associated mutant colonies during microbial pathogenesis, coinfection, and genetic manipulation studies.