Laser optical sensor, a label-free on-plate Salmonella enterica colony detection tool

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.

On-Site Fluorescent Detection of Sepsis-Inducing Bacteria using a Graphene-Oxide CRISPR-Cas12a (GO-CRISPR) System

Sepsis is an extremely dangerous medical condition that emanates from the body's response to a pre-existing infection. Early detection of sepsis-inducing bacterial infections can greatly enhance the treatment process and potentially prevent the onset of sepsis. However, current point-of-care (POC) sensors are often complex and costly or lack the ideal sensitivity for effective bacterial detection. Therefore, it is crucial to develop rapid and sensitive biosensors for the on-site detection of sepsis-inducing bacteria. Herein, we developed a graphene oxide CRISPR-Cas12a (GO-CRISPR) biosensor for the detection of sepsis-inducing bacteria in human serum. In this strategy, single-stranded (ssDNA) FAM probes were quenched with single-layer graphene oxide (GO). Target-activated Cas12a trans-cleavage was utilized for the degradation of the ssDNA probes, detaching the short ssDNA probes from GO and recovering the fluorescent signals. Under optimal conditions, we employed our GO-CRISPR system for the detection of Salmonella Typhimurium (S. Typhimurium) with a detection sensitivity of as low as 3 × 103 CFU/mL in human serum, as well as a good detection specificity toward other competing bacteria. In addition, the GO-CRISPR biosensor exhibited excellent sensitivity to the detection of S. Typhimurium in spiked human serum. The GO-CRISPR system offers superior rapidity for the detection of sepsis-inducing bacteria and has the potential to enhance the early detection of bacterial infections in resource-limited settings, expediting the response for patients at risk of sepsis.

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.

Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria

Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling.

Advancement in Salmonella Detection Methods: From Conventional to Electrochemical-Based Sensing Detection

Large-scale food-borne outbreaks caused by Salmonella are rarely seen nowadays, thanks to the advanced nature of the medical system. However, small, localised outbreaks in certain regions still exist and could possess a huge threat to the public health if eradication measure is not initiated. This review discusses the progress of Salmonella detection approaches covering their basic principles, characteristics, applications, and performances. Conventional Salmonella detection is usually performed using a culture-based method, which is time-consuming, labour intensive, and unsuitable for on-site testing and high-throughput analysis. To date, there are many detection methods with a unique detection system available for Salmonella detection utilising immunological-based techniques, molecular-based techniques, mass spectrometry, spectroscopy, optical phenotyping, and biosensor methods. The electrochemical biosensor has growing interest in Salmonella detection mainly due to its excellent sensitivity, rapidity, and portability. The use of a highly specific bioreceptor, such as aptamers, and the application of nanomaterials are contributing factors to these excellent characteristics. Furthermore, insight on the types of biorecognition elements, the principles of electrochemical transduction elements, and the miniaturisation potential of electrochemical biosensors are discussed.

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

Mammalian Cell-Based Immunoassay for Detection of Viable Bacterial Pathogens

Rapid detection of live pathogens is of paramount importance to ensure food safety. At present, nucleic acid-based polymerase chain reaction and antibody-based lateral flow assays are the primary methods of choice for rapid detection, but these are prone to interference from inhibitors, and resident microbes. Moreover, the positive results may neither assure virulence potential nor viability of the analyte. In contrast, the mammalian cell-based assay detects pathogen interaction with the host cells and is responsive to only live pathogens, but the short shelf-life of the mammalian cells is the major impediment for its widespread application. An innovative approach to prolong the shelf-life of mammalian cells by using formalin was undertaken. Formalin (4% formaldehyde)-fixed human ileocecal adenocarcinoma cell line, HCT-8 on 24-well tissue culture plates was used for the capture of viable pathogens while an antibody was used for specific detection. The specificity of the Mammalian Cell-based ImmunoAssay (MaCIA) was validated with Salmonella enterica serovar Enteritidis and Typhimurium as model pathogens and further confirmed against a panel of 15 S. Enteritidis strains, 8 S. Typhimurium, 11 other Salmonella serovars, and 14 non-Salmonella spp. The total detection time (sample-to-result) of MaCIA with artificially inoculated ground chicken, eggs, milk, and cake mix at 1-10 CFU/25 g was 16-21 h using a traditional enrichment set up but the detection time was shortened to 10-12 h using direct on-cell (MaCIA) enrichment. Formalin-fixed stable cell monolayers in MaCIA provide longer shelf-life (at least 14 weeks) for possible point-of-need deployment and multi-sample testing on a single plate.

Advances in Optical Detection of Human-Associated Pathogenic Bacteria

Bacterial infection is a global burden that results in numerous hospital visits and deaths annually. The rise of multi-drug resistant bacteria has dramatically increased this burden. Therefore, there is a clinical need to detect and identify bacteria rapidly and accurately in their native state or a culture-free environment. Current diagnostic techniques lack speed and effectiveness in detecting bacteria that are culture-negative, as well as options for in vivo detection. The optical detection of bacteria offers the potential to overcome these obstacles by providing various platforms that can detect bacteria rapidly, with minimum sample preparation, and, in some cases, culture-free directly from patient fluids or even in vivo. These modalities include infrared, Raman, and fluorescence spectroscopy, along with optical coherence tomography, interference, polarization, and laser speckle. However, these techniques are not without their own set of limitations. This review summarizes the strengths and weaknesses of utilizing each of these optical tools for rapid bacteria detection and identification.

Multi-directional Morphological Assessment of Single Bacterial Colonies Through Non-invasive Optical Imaging

A bacterium in bacterial colony is a basal component of bacterial studies and is therefore of considerable importance. The morphological characteristics of a single colony have been widely used as the standard to identify diverse bacterial species. However, the conventional methods for obtaining morphological information, such as microscopic techniques, cannot provide tomographic views. This study utilizes spectral-domain optical coherence tomography (SD-OCT) to observe both external and internal structures for single colonies. OCT imaging provided a clear top (projection) and lateral (cross-sectional) images, which can identify distinct features in the fifteen different bacterial species examined. Through the acquired OCT images, the elevation type in each genus was confirmed, and the quantitative measurements for morphology including a diameter, height, and elevation angle were achieved. Moreover, the OCT raw data was used to build three-dimensional images to observe outer appearances in all direction. As a result, the averaged angles of 7.92°, 14.40°, 6.78°, and 11.92° of the genus Hymenobacter, Spirosoma, Bacillus, and Deinococcus, respectively, were calculated. In conclusion, we have demonstrated that OCT is a highly feasible, non-invasive method for the identification of bacterial species, providing detailed morphological and visual information. It thus has strong potential for applications in bacteriology, as well as biomedical and food sciences.

Generalized spectral light scatter models of diverse bacterial colony morphologies

An optical forward-scatter model was generalized to encompass the diverse nature of bacterial colony morphologies and the spectral information. According to the model, the colony shape and the wavelength of incident light significantly affect the characteristics of a forward elastic-light-scattering pattern. To study the relationship between the colony morphology and the scattering pattern, three-dimensional colony models were generated in various morphologies. The propagation of light passing through the colony model was then simulated. In validation of the theoretical modeling, the scattering patterns of three bacterial genera, Staphylococcus, Exiguobacterium and Bacillus, which grow into colonies having convex, crateriform and flat elevations, respectively, were qualitatively compared to the simulated scattering patterns. The strong correlations observed between simulated and experimental patterns validated the scatter model. In addition, spectral effect on the scattering pattern was studied using the scatter model, and experimentally investigated using Staphylococcus, whose colony has circular form and convex elevation. Both simulation and experiment showed that changes in wavelength affected the overall pattern size and the number of rings.

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.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

Tunicamycin Mediated Inhibition of Wall Teichoic Acid Affects Staphylococcus aureus and Listeria monocytogenes Cell Morphology, Biofilm Formation and Virulence

The emergence of bacterial resistance to therapeutic antibiotics limits options for treatment of common microbial diseases. Subinhibitory antibiotics dosing, often aid in the emergence of resistance, but its impact on pathogen’s physiology and pathogenesis is not well understood. Here we investigated the effect of tunicamycin, a cell wall teichoic acid (WTA) biosynthesis inhibiting antibiotic at the subinhibitory dosage on Staphylococcus aureus and Listeria monocytogenes physiology, antibiotic cross-resistance, biofilm-formation, and virulence. Minimum inhibitory concentration (MIC) of tunicamycin to S. aureus and L. monocytogenes was 20–40 μg/ml and 2.5–5 μg/ml, respectively, and the subinhibitory concentration was 2.5–5 μg/ml and 0.31–0.62 μg/ml, respectively. Tunicamycin pre-exposure reduced cellular WTA levels by 18–20% and affected bacterial cell wall ultrastructure, cell membrane permeability, morphology, laser-induced colony scatter signature, and bacterial ability to form biofilms. It also induced a moderate level of cross-resistance to tetracycline, ampicillin, erythromycin, and meropenem for S. aureus, and ampicillin, erythromycin, vancomycin, and meropenem for L. monocytogenes. Pre-treatment of bacterial cells with subinhibitory concentrations of tunicamycin also significantly reduced bacterial adhesion to and invasion into an enterocyte-like Caco-2 cell line, which is supported by reduced expression of key virulence factors, Internalin B (InlB) and Listeria adhesion protein (LAP) in L. monocytogenes, and a S. aureus surface protein A (SasA) in S. aureus. Tunicamycin-treated bacteria or the bacterial WTA preparation suppressed NF-κB and inflammatory cytokine production (TNFα, and IL-6) from murine macrophage cell line (RAW 264.7) indicating the reduced WTA level possibly attenuates an inflammatory response. These results suggest that at the subinhibitory dosage, tunicamycin-mediated inhibition of WTA biosynthesis interferes with cell wall structure, pathogens infectivity and inflammatory response, and ability to form biofilms but promotes the development of antibiotic cross-resistance.

Angular photodiode array-based device to detect bacterial pathogens in a wound model

We have developed a device that is able to rapidly and specifically diagnose bacterial pathogens in a wound model based on Mie scatter spectra from a tissue surface. The Mie scatter spectra collected is defined as the intensity of Mie scatter over the angle of detection from a tissue surface. A 650 nm LED perpendicular to the surface illuminates a tissue sample (90°) and photodiodes positioned in 10° increments from 10° to 80° of backscatter act as the detectors to collect these Mie scatter spectra. Through principal component analysis of the Mie scatter spectra collected, we have shown significant differences between Mie scatter spectra of tissues with bacterial pathogens versus those without, as well as significant differences between each species of bacteria tested. The device developed has been tested with a porcine dermis wound model, with samples inoculated with one of three bacterial species (Staphylococcus aureus, Escherichia coli, or Salmonella Typhimurium). Such a device could be critical in the monitoring of a wound for infection and rapid, specific diagnosis of a bacterial wound infection, which would significantly reduce the time and cost associated with specific diagnosis of a bacterial wound infection currently.

Mie scatter spectra-based device for instant, contact-free, and specific diagnosis of bacterial skin infection

Rapid and specific diagnostic techniques are needed to expedite specific treatment of bacterial skin infections with narrow-spectrum antibiotics, rather than broad-spectrum. Through this work a device was developed to determine the presence of and species responsible for a bacterial skin infection using differences in Mie scatter spectra created by different bacterial species. A 650 nm LED at five different incident angles is used to illuminate the tissue, with Mie scatter being detected by PIN photodiodes at eight different detection angles. Mie scatter patterns are collected at all photodiode angles for each of the incident light angles, resulting in a Mie scatter spectra. Detectable differences in Mie scatter spectra were found using the device developed between commensal bacteria (no infection) and bacteria inoculated (infection) on the surface of both porcine and human cadaveric epidermis. Detectable differences were found between species of infection, specifically Escherichia coli and Staphylococcus aureus, with differences summarized through principle component analysis. Mie scatter spectra can be detected within a few seconds without skin contact. This device is the first to rapidly and specifically diagnose bacterial skin infections in a contact-less manner, allowing for initial treatment with narrow spectrum antibiotics, and helping to reduce the likelihood of resistance.

Development of a multispectral light-scatter sensor for bacterial colonies

We report a multispectral elastic-light-scatter instrument that can simultaneously detect three-wavelength scatter patterns and associated optical densities from individual bacterial colonies, overcoming the limits of the single-wavelength predecessor. Absorption measurements on liquid bacterial samples revealed that the spectroscopic information can indeed contribute to sample differentiability. New optical components, including a pellicle beam splitter and an optical cage system, were utilized for robust acquisition of multispectral images. Four different genera and seven shiga toxin producing E. coli serovars were analyzed; the acquired images showed differences in scattering characteristics among the tested organisms. In addition, colony-based spectral optical-density information was also collected. The optical model, which was developed using diffraction theory, correctly predicted wavelength-related differences in scatter patterns, and was matched with the experimental results. Scatter-pattern classification was performed using pseudo-Zernike (GPZ) polynomials/moments by combining the features collected at all three wavelengths and selecting the best features via a random-forest method. The data demonstrate that the selected features provide better classification rates than the same number of features from any single wavelength. Three wavelength-merged scatter pattern from E. coli.

Reflected scatterometry for noninvasive interrogation of bacterial colonies

A phenotyping of bacterial colonies on agar plates using forward-scattering diffraction-pattern analysis provided promising classification of several different bacteria such as Salmonella, Vibrio, Listeria, and E. coli. Since the technique is based on forward-scattering phenomena, light transmittance of both the colony and the medium is critical to ensure quality data. However, numerous microorganisms and their growth media allow only limited light penetration and render the forward-scattering measurement a challenging task. For example, yeast, Lactobacillus, mold, and several soil bacteria form colorful and dense colonies that obstruct most of the incoming light passing through them. Moreover, blood agar, which is widely utilized in the clinical field, completely blocks the incident coherent light source used in forward scatterometry. We present a newly designed reflection scatterometer and validation of the resolving power of the instrument. The reflectance-type instrument can acquire backward elastic scatter patterns for both highly opaque media and colonies and has been tested with three different bacterial genera grown on blood agar plates. Cross-validation results show a classification rate above 90% for four genera.

The effect of a novel low temperature-short time (LTST) process to extend the shelf-life of fluid milk

Pasteurization has long been the standard method to extend the shelf-life of dairy products, as well as a means to reduce microbial load and the risk of food-borne pathogens. However, the process has limitations, which include cost effectiveness, high energy input, and reduction of product quality/organoleptic characteristics. In an effort to reduce these limitations and extend shelf-life, this study examined a novel low temperature, short time (LTST) method in which dispersed milk in the form of droplets was treated with low heat/pressure variation over a short treatment time, in conjunction with pasteurization. Lactobacillus fermentum and Pseudomonas fluorescens Migula were exposed to conventional pasteurization treatments with and without LTST. Using these organisms, the LTST addition was able to reduce microbial load below detection limits; 1.0 × 10¹ cfu/mL, from approximately 1.2 × 10⁸ and 1.0 × 10⁷ cfu/mL for L. fermentum and P. fluorescens Migula, respectively. In addition, the shelf-life of the treated, raw, and uninoculated product was prolonged from 14 to 35 days, compared with standard pasteurization, to as long as 63 days with the LTST amendment. Sensory analysis of samples also demonstrated equal or greater preference for LTST + pasteurization treated milk when compared to pasteurization alone (α = 0.05). Conventional pasteurization was effective at reducing the above mentioned microorganisms by as much as 5.0 log10 cfu/mL. However, LTST was able to achieve 7.0–8.0 log10 cfu/mL reduction of the same microorganisms. In addition, BActerial Rapid Detection using Optical scattering Technology detected and identified microorganisms isolated both pre- and post-treatment, of which the only organisms surviving LTST were Bacillus spp. Increased lethality, improved shelf-life, and equal or better organoleptic characteristics without increased energy consumption demonstrate the effectiveness of the incorporation of LTST. The improved shelf-life may potentially have major impacts in the dairy industry in terms of shipping and overall sustainability.

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.

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

Enterobacteriaceae family comprised pathogens and commensals and has a significant impact on food safety and public health. Enterobacteriaceae is often enumerated and presumptively identified on chromogenic media, such as CHROMagar(TM) Orientation medium based on colony profile; however, classification is highly arbitrary, and some could not be differentiated due to similar chromogen production. Here, we investigated the ability of the laser optical sensor, BARDOT (bacterial rapid detection using optical scattering technology) for rapid screening and differentiation of colonies of the major bacterial genera from Enterobacteriaceae on CHROMagar(TM) Orientation. A total of 36 strains representing 12 genera and 15 species were used to generate colony scatter image library that comprised 1683 scatter images. This library was used to differentiate mixed cultures of Enterobacteriaceae family - Klebsiella pneumoniae, Enterobacter spp., Citrobacter freundii and Serratia marcescens (KECS group); Proteus mirabilis, Morganella morganii and Providencia rettgeri (PMP group); and non-Enterobacteriaceae family: Pseudomonas aeruginosa, Acinetobacter spp. and Staphylococcus aureus (PAS group) - and data show high accuracy (83-100%) for intra-group classification of colonies in 10-22 h or even before visible production of chromogens. BARDOT successfully differentiated the major genera, including the ones that do not produce visually distinguishable chromogens on CHROMagar(TM) Orientation, providing a label-free, real-time on-plate colony screening tool for Enterobacteriaceae.

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.

Novel PCR Assays Complement Laser Biosensor-Based Method and Facilitate Listeria Species Detection from Food

The goal of this study was to develop the Listeria species-specific PCR assays based on a house-keeping gene (lmo1634) encoding alcohol acetaldehyde dehydrogenase (Aad), previously designated as Listeria adhesion protein (LAP), and compare results with a label-free light scattering sensor, BARDOT (bacterial rapid detection using optical scattering technology). PCR primer sets targeting the lap genes from the species of Listeria sensu stricto were designed and tested with 47 Listeria and 8 non-Listeria strains. The resulting PCR primer sets detected either all species of Listeria sensu stricto or individual L. innocua, L. ivanovii and L. seeligeri, L. welshimeri, and L. marthii without producing any amplified products from other bacteria tested. The PCR assays with Listeria sensu stricto-specific primers also successfully detected all species of Listeria sensu stricto and/or Listeria innocua from mixed culture-inoculated food samples, and each bacterium in food was verified by using the light scattering sensor that generated unique scatter signature for each species of Listeria tested. The PCR assays based on the house-keeping gene aad (lap) can be used for detection of either all species of Listeria sensu stricto or certain individual Listeria species in a mixture from food with a detection limit of about 10⁴ CFU/mL.

Streptomycin Induced Stress Response in Salmonella enterica Serovar Typhimurium Shows Distinct Colony Scatter Signature

We investigated the streptomycin-induced stress response in Salmonella enterica serovars with a laser optical sensor, BARDOT (bacterial rapid detection using optical scattering technology). Initially, the top 20 S. enterica serovars were screened for their response to streptomycin at 100 μg/mL. All, but four S. enterica serovars were resistant to streptomycin. The MIC of streptomycin-sensitive serovars (Enteritidis, Muenchen, Mississippi, and Schwarzengrund) varied from 12.5 to 50 μg/mL, while streptomycin-resistant serovar (Typhimurium) from 125–250 μg/mL. Two streptomycin-sensitive serovars (Enteritidis and Mississippi) were grown on brain heart infusion (BHI) agar plates containing sub-inhibitory concentration of streptomycin (1.25–5 μg/mL) and a streptomycin-resistant serovar (Typhimurium) was grown on BHI containing 25–50 μg/mL of streptomycin and the colonies (1.2 ± 0.1 mm diameter) were scanned using BARDOT. Data show substantial qualitative and quantitative differences in the colony scatter patterns of Salmonella grown in the presence of streptomycin than the colonies grown in absence of antibiotic. Mass-spectrometry identified overexpression of chaperonin GroEL, which possibly contributed to the observed differences in the colony scatter patterns. Quantitative RT-PCR and immunoassay confirmed streptomycin-induced GroEL expression while, aminoglycoside adenylyltransferase (aadA), aminoglycoside efflux pump (aep), multidrug resistance subunit acrA, and ribosomal protein S12 (rpsL), involved in streptomycin resistance, were unaltered. The study highlights suitability of the BARDOT as a non-invasive, label-free tool for investigating stress response in Salmonella in conjunction with the molecular and immunoassay methods.

One day to one hour: how quickly can foodborne pathogens be detected?

Foodborne pathogens pose serious public health risks. Rapid, accurate technologies to detect a low number of target cells (1 cell/25-325 g sample) and microbial toxins are in demand in order to assess product safety in hours to up to 1 day. Varied pathogen loads and the complexity of food present a major challenge. Current culture methods, while accurate, are lengthy. New methods, using brief culturing and detection kits (antibody based, nucleic acid amplification or nano/biosensors) or a culture-independent approach coupled with nucleic acid amplification, traditionally used for viruses/parasites, can be used to obtain results in hours. A strategic approach involving two-step, rapid, high-throughput screening to rule out negatives followed by a confirmatory test could accomplish product testing in 1 h to 1 day.

Classification of foodborne pathogens using near infrared (NIR) laser scatter imaging system with multivariate calibration

An optical sensor system, namely NIR laser scatter imaging system, was developed for rapid and noninvasive classification of foodborne pathogens. This developed system was used for images acquisition. The current study is focused on exploring the potential of this system combined with multivariate calibrations in classifying three categories of popular bacteria. Initially, normalization and Zernike moments extraction were performed, and the resultant translation, scale and rotation invariances were applied as the characteristic variables for subsequent discriminant analysis. Both linear (LDA, KNN and PLSDA) and nonlinear (BPANN, SVM and OSELM) pattern recognition methods were employed comparatively for modeling, and optimized by cross validation. Experimental results showed that the performances of nonlinear tools were superior to those of linear tools, especially for OSELM model with 95% discrimination rate in the prediction set. The overall results showed that it is extremely feasible for rapid and noninvasive classifying foodborne pathogens using this developed system combined with appropriate multivariate calibration.

Scalar diffraction modeling of multispectral forward scatter patterns from bacterial colonies

A theoretical model for spectral forward scatter patterns from a bacterial colony based on elastic light scatter is presented. The spectral forward scatter patterns are computed by scalar diffraction theory, and compared with experimental results of three discrete wavelengths (405 nm, 635 nm, and 904 nm). To provide quantitative analysis, spectral dependence of diffraction ring width, gap, maxima, minima, and the first deflection point are monitored. Both model and experiment results show an excellent agreement; a longer wavelength induces a wider ring width, a wider ring gap, a smaller pattern size, and smaller numbers of rings. Further analysis using spatial fast Fourier transform (SFFT) shows a good agreement; the spatial frequencies are increasing towards the inward direction, and the slope is inversely proportional to the incoming wavelength.

Laser-induced speckle scatter patterns in Bacillus colonies

Label-free bacterial colony phenotyping technology called BARDOT (Bacterial Rapid Detection using Optical scattering Technology) provided successful classification of several different bacteria at the genus, species, and serovar level. Recent experiments with colonies of Bacillus species provided strikingly different characteristics of elastic light scatter (ELS) patterns, which were comprised of random speckles compared to other bacteria, which are dominated by concentric rings and spokes. Since this laser-based optical sensor interrogates the whole volume of the colony, 3-D information of micro- and macro-structures are all encoded in the far-field scatter patterns. Here, we present a theoretical model explaining the underlying mechanism of the speckle formation by the colonies from Bacillus species. Except for Bacillus polymyxa, all Bacillus spp. produced random bright spots on the imaging plane, which presumably dependent on the cellular and molecular organization and content within the colony. Our scatter model-based analysis revealed that colony spread resulting in variable surface roughness can modify the wavefront of the scatter field. As the center diameter of the Bacillus spp. colony grew from 500 to 900 μm, average speckles area decreased two-fold and the number of small speckles increased seven-fold. In conclusion, as Bacillus colony grows, the average speckle size in the scatter pattern decreases and the number of smaller speckle increases due to the swarming growth characteristics of bacteria within the colony.

Light scattering sensor for direct identification of colonies of Escherichia coli serogroups O26, O45, O103, O111, O121, O145 and O157

Background

Shiga-toxin producing Escherichia coli (STEC) have emerged as important foodborne pathogens, among which seven serogroups (O26, O45, O103, O111, O121, O145, O157) are most frequently implicated in human infection. The aim was to determine if a light scattering sensor can be used to rapidly identify the colonies of STEC serogroups on selective agar plates.

Methodology/Principal Findings

Initially, a total of 37 STEC strains representing seven serovars were grown on four different selective agar media, including sorbitol MacConkey (SMAC), Rainbow Agar O157, BBL CHROMagarO157, and R&F E. coli O157:H7, as well as nonselective Brain Heart Infusion agar. The colonies were scanned by an automated light scattering sensor, known as BARDOT (BActerial Rapid Detection using Optical scattering Technology), to acquire scatter patterns of STEC serogroups, and the scatter patterns were analyzed using an image classifier. Among all of the selective media tested, both SMAC and Rainbow provided the best differentiation results allowing multi-class classification of all serovars with an average accuracy of more than 90% after 10–12 h of growth, even though the colony appearance was indistinguishable at that early stage of growth. SMAC was chosen for exhaustive scatter image library development, and 36 additional strains of O157:H7 and 11 non-O157 serovars were examined, with each serogroup producing unique differential scatter patterns. Colony scatter images were also tested with samples derived from pure and mixed cultures, as well as experimentally inoculated food samples. BARDOT accurately detected O157 and O26 serovars from a mixed culture and also from inoculated lettuce and ground beef (10-h broth enrichment +12-h on-plate incubation) in the presence of natural background microbiota in less than 24 h.

Conclusions

BARDOT could potentially be used as a screening tool during isolation of the most important STEC serovars on selective agar plates from food samples in less than 24 h.