Rapid identification and classification of Campylobacter spp. using laser optical scattering technology

Whole Genome Sequences, De Novo Assembly, and Annotation of Antibiotic Resistant Campylobacter jejuni Strains S27, S33, and S36 Newly Isolated from Chicken Meat

Campylobacter is a leading bacterial cause of gastrointestinal infections in humans and has imposed substantial medical and public health burdens worldwide. Among a total of 39 species in the Campylobacter genus, C. jejuni is the most important species responsible for approx. 90% of human Campylobacter illness. Most cases of the infection were acquired by ingesting undercooked poultry meat due to the high prevalence of Campylobacter in the products. Here, we reported the dataset of raw sequences, de novo assembled and annotated genomes of C. jejuni strains S27, S33, and S36 recently isolated from retail chicken by using PacBio highly accurate long-read sequencing technology combined with bioinformatics tools. Our data revealed several virulence and antibiotic resistance genes in each of the chromosomes, a type IV secretion system in the plasmid (pCjS33) of C. jejuni S33, and a type VI secretion system and a phage in the plasmid (pCjS36) of C. jejuni S36. This study not only provides new sequence data but also extends the knowledge pertaining to the genomic and functional aspects of this important foodborne pathogen, including the genetic determinants of virulence and antibiotic resistance.

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.

Complete Genome Sequences of Multidrug-Resistant Campylobacter coli Strains YH501, YH503, and YH504, from Retail Chicken

Campylobacter coli is an important foodborne pathogen that can cause inflammation of the intestine and diarrhea in humans. The complete genomes, including megaplasmids, of C. coli strains YH501, YH503, and YH504 from retail chicken were sequenced and de novo assembled. Whole-genome analysis revealed a number of virulence and antibiotic resistance genes, suggesting significant potential for these poultry-originating isolates to cause human disease.

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis

Images of laser scattering patterns generated by bacteria in urine are promising resources for deep learning. However, floating bacteria in urine produce dynamic scattering patterns and require deep learning of spatial and temporal features. We hypothesized that bacteria with variable bacterial densities and different Gram staining reactions would generate different speckle images. After deep learning of speckle patterns generated by various densities of bacteria in artificial urine, we validated the model in an independent set of clinical urine samples in a tertiary hospital. Even at a low bacterial density cutoff (1,000 CFU/mL), the model achieved a predictive accuracy of 90.9% for positive urine culture. At a cutoff of 50,000 CFU/mL, it showed a better accuracy of 98.5%. The model achieved satisfactory accuracy at both cutoff levels for predicting the Gram staining reaction. Considering only 30 min of analysis, our method appears as a new screening tool for predicting the presence of bacteria before urine culture. IMPORTANCE This study performed deep learning of multiple laser scattering patterns by the bacteria in urine to predict positive urine culture. Conventional urine analyzers have limited performance in identifying bacteria in urine. This novel method showed a satisfactory accuracy taking only 30 min of analysis without conventional urine culture. It was also developed to predict the Gram staining reaction of the bacteria. It can be used as a standalone screening tool for urinary tract infection.

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.

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.

Comparative Genomic Analysis of a Multidrug-Resistant Campylobacter jejuni Strain YH002 Isolated from Retail Beef Liver

Campylobacter jejuni is a major cause of bacterial gastroenteritis worldwide. In this study, we report the comparative genomic and functional characteristics of C. jejuni YH002 recently isolated from retail beef liver. Whole-genome sequencing and annotation of the strain revealed novel genetic features, including an integrated intact phage element, multiple antimicrobial resistance (AMR) genes, virulence factors, and a Phd-Doc type toxin-antitoxin (TA) system. Phenotypic tests of AMR showed that C. jejuni YH002 was resistant to amoxicillin and tetracycline, which correlates with the AMR genes found in the strain. Comparative analysis of cell motility at genotypic and phenotypic levels identified discernible patterns of amino acid changes, which could explain the variations of motility among C. jejuni strains. Together, these results provide important clues to the genetic mechanisms of AMR and cell motility in C. jejuni. The finding of a Phd-Doc TA system in the genome of C. jejuni YH002 is the first report of this TA system in Campylobacter spp.

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.

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.

Whole genome sequencing and analysis of Campylobacter coli YH502 from retail chicken reveals a plasmid-borne type VI secretion system

Campylobacter is a major cause of foodborne illnesses worldwide. Campylobacter infections, commonly caused by ingestion of undercooked poultry and meat products, can lead to gastroenteritis and chronic reactive arthritis in humans. Whole genome sequencing (WGS) is a powerful technology that provides comprehensive genetic information about bacteria and is increasingly being applied to study foodborne pathogens: e.g., evolution, epidemiology/outbreak investigation, and detection. Herein we report the complete genome sequence of Campylobacter coli strain YH502 isolated from retail chicken in the United States. WGS, de novo assembly, and annotation of the genome revealed a chromosome of 1,718,974 bp and a mega-plasmid (pCOS502) of 125,964 bp. GC content of the genome was 31.2% with 1931 coding sequences and 53 non-coding RNAs. Multiple virulence factors including a plasmid-borne type VI secretion system and antimicrobial resistance genes (beta-lactams, fluoroquinolones, and aminoglycoside) were found. The presence of T6SS in a mobile genetic element (plasmid) suggests plausible horizontal transfer of these virulence genes to other organisms. The C. coli YH502 genome also harbors CRISPR sequences and associated proteins. Phylogenetic analysis based on average nucleotide identity and single nucleotide polymorphisms identified closely related C. coli genomes available in the NCBI database. Taken together, the analyzed genomic data of this potentially virulent strain of C. coli will facilitate further understanding of this important foodborne pathogen most likely leading to better control strategies. The chromosome and plasmid sequences of C. coli YH502 have been deposited in GenBank under the accession numbers CP018900.1 and CP018901.1, respectively.

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.

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.