Evaluation of the BacterioScan 216Dx for Standalone Preculture Screen of Preserved Urine Specimens in a Clinical Setting

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.

Fast antibiotic susceptibility testing of urine microflora using a microbiological analyzer based on coherent fluctuation nephelometry

BACKGROUND

Traditional culture-based microbiological methods remain the most used for defining the etiology of urinary tract infections and antibiotic susceptibility testing (AST) of isolated uropathogens. They are time-consuming and lead to delays of several days when obtaining the final results of microbiological tests.

OBJECTIVES

In this study, we validate the possibility of using a microbiological CFN analyzer combined with MALDI-TOF mass spectrometry (MS) for fast conclusive urine testing (1 day) without obtaining pure cultures.

MATERIALS AND METHODS

The study included three stages: detection of urine microflora growth using the CFN analyzer to separate positive and negative samples within 2-4 h; fast MS identification of positive samples without isolating uropathogens; fast AST using CFN analyzer within 3-6 h. In parallel, all urine samples were tested by traditional culture-based microbiological methods.

RESULT

In total, 194 urine samples were tested, and 22 urine cultures were identified by MS, among them, 20 monocultures with bacterial counts ≥ 10⁵ and 2 mixed cultures. The AST of these 22 urine cultures and additional 88 pure clinical cultures was performed using eight antibiotics. Overall, 276 tests were performed. The results of AST obtained using the CFN analyzer and traditional methods were in good agreement (98.2%). Although two mixed cultures were falsely identified as monocultures, their susceptibility determined by the CFN analyzer was correct.

CONCLUSIONS

The CFN analyzer is promising and effective for fast AST. Combined with MS identification, it allows to perform full urine analysis in 1 day without the lengthy isolation of pure cultures.

Rapid Antimicrobial Susceptibility Testing on Clinical Urine Samples by Video-Based Object Scattering Intensity Detection

To combat the ongoing public health threat of antibiotic-resistant infections, a technology that can quickly identify infecting bacterial pathogens and concurrently perform antimicrobial susceptibility testing (AST) in point-of-care settings is needed. Here, we develop a technology for point-of-care AST with a low-magnification solution scattering imaging system and a real-time video-based object scattering intensity detection method. The low magnification (1-2×) optics provides sufficient volume for direct imaging of bacteria in urine samples, avoiding the time-consuming process of culture-based bacterial isolation and enrichment. Scattering intensity from moving bacteria and particles in the sample is obtained by subtracting both spatial and temporal background from a short video. The time profile of scattering intensity is correlated with the bacterial growth rate and bacterial response to antibiotic exposure. Compared to the image-based bacterial tracking and counting method we previously developed, this simple image processing algorithm accommodates a wider range of bacterial concentrations, simplifies sample preparation, and greatly reduces the computational cost of signal processing. Furthermore, development of this simplified processing algorithm eases implementation of multiplexed detection and allows real-time signal readout, which are essential for point-of-care AST applications. To establish the method, 130 clinical urine samples were tested, and the results demonstrated an accuracy of ∼92% within 60-90 min for UTI diagnosis. Rapid AST of 55 positive clinical samples revealed 98% categorical agreement with both the clinical culture results and the on-site parallel AST validation results. This technology provides opportunities for prompt infection diagnosis and accurate antibiotic prescriptions in point-of-care settings.

A rapid, antibiotic susceptibility test for multidrug-resistant, Gram-negative bacterial uropathogens using the biochemical assay, DETECT

The increasing prevalence of extended spectrum β-lactamases (ESBLs) and plasmid-mediated AmpC (pAmpC) β-lactamases among Enterobacterales threatens our ability to treat urinary tract infections (UTIs). These organisms are resistant to most β-lactam antibiotics and are frequently multidrug-resistant (MDR). Consequently, they are often resistant to antibiotics used to empirically treat UTIs. The lack of rapid diagnostic and antibiotic susceptibility tests (AST) makes clinical management of UTIs caused by such organisms difficult, as standard culture and susceptibility assays require several days. We have adapted a biochemical detection assay, termed dual-enzyme trigger-enabled cascade technology (DETECT) for rapid detection of resistance (time-to-result of 3 h) to other antibiotics commonly used in treatment of UTIs. DETECT is activated by the presence of CTX-M and pAmpC β-lactamases. In this proof-of-concept study, the adapted DETECT assay (AST-DETECT) has been performed on pure-cultures of Klebsiella pneumoniae and Escherichia coli (48 isolates) expressing ESBL or pAmpC β-lactamases to perform AST for ciprofloxacin (sensitivity 96.9%, specificity 100%, accuracy 97.9%) nitrofurantoin (sensitivity 95.7%, specificity 91.7%, accuracy 94%) and trimethoprim/sulfamethoxazole (sensitivity 83.3%, specificity 100%, accuracy 89.4%). These results suggest that AST-DETECT may be adapted as a potential diagnostic platform to rapidly detect multidrug-resistant E. coli and K. pneumoniae that cause UTI.

Biofilm formation and extracellular microvesicles-The way of foodborne pathogens toward resistance

Almost all known foodborne pathogens are able to form biofilms as one of the strategies for survival under harsh living conditions, to ward off the inhibition and the disinfection during food production, transport and storage, as well as during cleaning and sanitation of corresponding facilities. Biofilms are communities where microbial cells live under constant intracellular interaction and communication. Members of the biofilm community are embedded into extracellular matrix that contains polysaccharides, DNA, lipids, proteins, and small molecules that protect microorganisms and enable their intercellular communication under stress conditions. Membrane vesicles (MVs) are produced by both Gram positive and Gram negative bacteria. These lipid membrane-enveloped nanoparticles play an important role in biofilm genesis and in communication between different biofilm members. Furthermore, MVs are involved in other important steps of bacterial life like cell wall modeling, cellular division, and intercellular communication. They also carry toxins and virulence factors, as well as nucleic acids and different metabolites, and play a key role in host infections. After entering host cells, MVs can start many pathologic processes and cause serious harm and cell death. Prevention and inhibition of both biofilm formation and shedding of MVs by foodborne pathogens has a very important role in food production, storage, and food safety in general. Better knowledge of biofilm formation and maintaining, as well as the role of microbial vesicles in this process and in the process of host cells' infection is essential for food safety and prevention of both food spoilage and host infection.

Evaluation of BacterioScan 216Dx in Comparison to Urinalysis as a Screening Tool for Diagnosis of Urinary Tract Infections in Children

Urinalysis (UA) has routinely been used as a screening tool prior to urine culture set up. BacterioScan 216Dx is an FDA-cleared semiautomated system to detect bacterial growth in urine. The aim of this study was to evaluate 216Dx in comparison to UA for diagnosis of urinary tract infection (UTI) in children. Clean-catch, unpreserved urine samples from children aged <18 years were tested by 216Dx, and positive urine samples in media were processed for direct bacterial identification by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry. Sensitivity and specificity of 216Dx and urinalysis (UA) were determined against urine culture. Of 287 urine samples obtained from children (median age, 108 months), 44.0% and 56.0% were UA positive and negative, respectively, while 216Dx detected 27% and 73% as positive and negative, respectively. Compared to culture, the overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 216Dx versus UA were 92.1% versus 97.3%, 82.7% versus 63.8%, 44.8% versus 29.1%, and 98.6% versus 99.3%, respectively. Among 216Dx true-positive (TP) samples (n = 35), 77.0% were successfully identified directly from broth by MALDI-TOF. Among urine samples that were identified as contaminated by culture (n = 127; 44%), the 216Dx detected 93 (73.0%) as negative while UA detected 69 (54.0%) as negative. Although the sensitivities of 216Dx and UA are comparable, the specificity of 216Dx was higher than that of UA. The 216Dx can be used as an alternative/adjunct screening tool to UA to rule out urinary tract infection (UTI) in children. Compared to culture, the faster turnaround time (3 hours) of 216Dx has the potential to reduce unnecessary antibiotic use and improve patient management.

Coherent fluctuation nephelometry as a promising method for diagnosis of bacteriuria

Objectives

Specialized analyzers are used to automate the diagnosis of bacteriuria in laboratory practice. They are based on analysis of microorganisms concentration in urine samples or recording the growth of urine microflora. Coherent fluctuation nephelometry (CFN) has high sensitivity and allows analyzing both parameters simultaneously. The aim of the study is to compare the effectiveness of CFN-based and flow cytometry based analyzers.

Design and methods

Total 117 urine samples from children were studied in parallel using the CFN-analyzer and UF-1000i (Sysmex), the results were confirmed by conventional microbiological methods.

Results

In 21 urine samples (18%), significant bacteriuria was determined (≥10⁴ CFU/ml). The best diagnostic indicators were obtained while testing urine samples using the CFN-analyzer. The most efficient bacteriuria diagnosis is achieved by simultaneous analyses of microorganisms concentration in urine and growth of urine microflora (sensitivity - 95.2%, specificity - 96.9%, positive predictive value - 87%, negative predictive value - 98.9%, diagnostic odds ratio - 81.7, positive likelihood ratio - 30.5, negative likelihood ratio- 0.049, area under curve in ROC-analysis - 0.987). The CFN-analyzer allows the preliminary selection of negative urine samples, which do not require further analysis by conventional microbiological methods, thereby decreasing the number of cultures by 80.3%.

Conclusions

This study suggests that the CFN-analyzer is the effective tool for bacteriuria screening in children.