Accurate Bacterial Identification Research Articles

Rapid alignment-free bacteria identification via optical scattering with LEDs and YOLOv8

Rapid and accurate bacterial identification is essential for timely treatment of infections like sepsis. While traditional methods are reliable, they lack speed, and advanced molecular techniques often suffer from cost and complexity. The bacterial detection technology based on optical scattering system offers a rapid, label-free alternative but traditionally relies on complex lasers and analysis. Our enhanced approach utilizes RGB light emitting diodes (LEDs) as the light source. Three diffraction images of bacterial colonies from different LED colors are separately captured by a USB camera and combined using an image registration algorithm to enhance image sharpness. Our approach utilizes an object detection model, i.e., YOLOv8, for analysis achieving high-accuracy differentiation between bacterial strains. We demonstrate the effectiveness of this approach, achieving an average accuracy of 97% (mAP50 of 0.97), including accurate discrimination of closely related strains and the significant pathogen Staphylococcus aureus MRSA 1320. Our enhancement offers advantages in affordability, usability, and seamless integration into existing workflows, providing an alternative for rapid bacterial identification.

Performance of 16S rRNA Gene Next-Generation Sequencing and the Culture Method in the Detection of Bacteria in Clinical Specimens.

Effective treatment of infectious diseases requires prompt and accurate bacterial identification and tailored antimicrobial treatments. Traditional culture methods are considered the gold standard, but their effectiveness diminishes for fastidious and hard-to-grow microorganisms. In recent years, molecular diagnostic tools such as 16S rRNA gene next-generation sequencing (16S NGS) have gained popularity in the field. We analysed data from samples submitted for 16S NGS between July 2022 and July 2023 at the Department of Advanced Translational Microbiology in Trieste, Italy. The study included samples submitted for both culture-based identification and 16S NGS. Conventional media were used for culture, and bacterial identification was performed using MALDI-TOF mass spectrometry. The V3 region of the 16S rRNA gene was sequenced using the Ion PGM platform. Among the 123 samples submitted, drainage fluids (38%) and blood (23%) were the most common, with requests predominantly from the Infectious Diseases (31.7%) and Orthopedic (21.13%) Units. In samples collected from patients with confirmed infections, 16S NGS demonstrated diagnostic utility in over 60% of cases, either by confirming culture results in 21% or providing enhanced detection in 40% of instances. Among the 71 patients who had received antibiotic therapies before sampling (mean 2.3 prior antibiotic days), pre-sampling antibiotic consumption did not significantly affect the sensitivity of 16S NGS. In routine microbiology laboratories, combining 16S NGS with culture method enhances the sensitivity of microbiological diagnostics, even when sampling is conducted during antibiotic therapy.

Low-depth Raw Reads of Nanopore Sequencing Enables Rapid and Accurate Bacterial Identification

Low-depth Raw Reads of Nanopore Sequencing Enables Rapid and Accurate Bacterial Identification

Nano-Biotechnology for Bacteria Identification and Potent Anti-bacterial Properties: A Review of Current State of the Art.

Sepsis is a critical disease caused by the abrupt increase of bacteria in human blood, which subsequently causes a cytokine storm. Early identification of bacteria is critical to treating a patient with proper antibiotics to avoid sepsis. However, conventional culture-based identification takes a long time. Polymerase chain reaction (PCR) is not so successful because of the complexity and similarity in the genome sequence of some bacterial species, making it difficult to design primers and thus less suitable for rapid bacterial identification. To address these issues, several new technologies have been developed. Recent advances in nanotechnology have shown great potential for fast and accurate bacterial identification. The most promising strategy in nanotechnology involves the use of nanoparticles, which has led to the advancement of highly specific and sensitive biosensors capable of detecting and identifying bacteria even at low concentrations in very little time. The primary drawback of conventional antibiotics is the potential for antimicrobial resistance, which can lead to the development of superbacteria, making them difficult to treat. The incorporation of diverse nanomaterials and designs of nanomaterials has been utilized to kill bacteria efficiently. Nanomaterials with distinct physicochemical properties, such as optical and magnetic properties, including plasmonic and magnetic nanoparticles, have been extensively studied for their potential to efficiently kill bacteria. In this review, we are emphasizing the recent advances in nano-biotechnologies for bacterial identification and anti-bacterial properties. The basic principles of new technologies, as well as their future challenges, have been discussed.

Recent advances and perspectives of functionalized carbon dots in bacteria sensing.

Bacterial infectious diseases are severe threats to human health and increase substantial financial burdens. Nanomaterials have shown great potential in timely and accurate bacterial identification, detection, and monitoring to improve the cure rate and reduce mortality. Recently, carbon dots have been evidenced to be ideal candidates for bacterial identification and detection due to their superior physicochemical properties and biocompatibility. This review outlines the detailed recognition elements and recognition strategies with functionalized carbon dots (FCDs) for bacterial identification and detection. The advantages and limitations of different kinds of FCDs-based sensors will be critically discussed. Meanwhile, the ongoing challenges and perspectives of FCDs-based sensors for bacteria sensing are put forward.

Synovial sepsis diagnostics and antimicrobial resistance: a one-health perspective.

This article, as part of the Currents in One Health series, reviews the current state of diagnostics for synovial sepsis. Synovial sepsis is a condition that affects veterinary and human medicine and requires coordinated efforts from both parties, as well as environmental considerations to accurately diagnose and preserve effective treatments. The article discusses best practices to identify the causative agent in septic synovitis, trends in bacterial identification and antimicrobial resistance patterns across common bacterial species, and a one-health perspective to optimize diagnostics across species. Antimicrobial resistance is a challenge facing both human and veterinary medicine and requires mindful and attentive prescribing to reduce the development of antimicrobial resistance and preserve antimicrobials for future application. The current standard of care for bacterial identification in veterinary practice is culture and antimicrobial susceptibility; however, positive culture rates from synovial sepsis cases often remain < 50%. Recent developments in advanced bacterial identification present opportunities for improved bacterial identification in synovial sepsis. Increased bacterial isolation will also help guide empirical antimicrobial therapy. Utilizing information and recommendations from both the human and veterinary literature will improve timely and accurate bacterial identification and therefore rapid and effective treatment of synovial sepsis across species and limit the development of antimicrobial resistance.

Ultrafast and Cost-Effective Pathogen Identification and Resistance Gene Detection in a Clinical Setting Using Nanopore Flongle Sequencing.

Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology’s (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000–3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.

Investigating the Growth of Pseudomonas aeruginosa and Its Influence on Osteolysis in Human Bone: An In Vitro Study.

BackgroundIsolation of the causal microorganisms in osteomyelitis presents a major challenge for treating clinicians. Several methods have been proposed to rapidly and accurately identify microorganisms. There has been an increasing interest in using Raman spectroscopy in the field of microbial detection and characterisation. This paper explores the use of Raman spectroscopy identification as one of the most difficult-to-isolate microorganisms causing osteomyelitis.Methods and resultsFresh healthy human bone samples were collected from patients undergoing a total knee replacement. These samples were then inoculated with fresh overnight Pseudomonas aeruginosa (PAO) cultures. Bacteria growth and bone ultrastructural changes were monitored over a period of 6 weeks. The experiment demonstrated ultrastructural bony destruction caused by osteolytic PAO secretions. Raman-specific spectral signatures related to the cellular membranes of PAO structures were spotted indicating survival of bacteria on the bone surface.ConclusionThis study showed the promising ability of Raman spectroscopy to identify the presence of bacteria on the surface of inoculated bone samples over time. It was able to detect the osteolytic activity of the bacteria as well as ultrastructure specific to PAO virulence. This method may have a role as an aid to existing diagnostic methods for fast and accurate bacterial identification in bone infection.How to cite this articleAl Ghaithi A, Al Bimani A, Al Maskari S. Investigating the Growth of Pseudomonas aeruginosa and Its Influence on Osteolysis in Human Bone: An In Vitro Study. Strategies Trauma Limb Reconstr 2021;16(3):127–131.

Assessment of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF- MS) for Accurate Bacterial Identification in Clinical Labs

Abstract Introduction/Objective On behalf of the diagnostic Medical Laboratory rapid, and accurate identification of bacteria with their one-to-one anti-microbial susceptibility outlines is of ultimate importance for the management of infected patients. Contemporary microbial identification methods employed in routine clinical diagnostic laboratories relies on the use of conventional phenotypic methods. Phenotypic methods are time consuming with minimum turn-around times of at least 24 hrs and in many occurrences of 48hrs. With the intention of accelerate laboratory processes the MALDI-TOF MS was familiarized. MALDI-TOF MS is established on proteomic profiling and permits for rapid identification of bacteria. This technology has not been widely used in Egypt, but has been regularly used in Europe for the past few years. Methods Two hundred forty three positive non duplicate blood cultures were accrued over a period of six months. Experimental aliquots were taken from excess sample material that was collected as part of routine clinical care. 105 were positive for Gram negative bacilli, 123 were positive for Gram positive cocci, 3 positive for Gram positive bacilli, and 7 were positive for yeast. MALDI-TOF identification was compared to conventional identification. Conventional identification consisted of a combination of MALDI-TOF identification of a subcultures colony by direct smear, biochemical reactions, Vitek 2, and molecular identification. Results Ninety seven of the one hundred and five blood cultures positive for Gram negative bacilli were monomicrobial. The majority of these were identified as Escherichia coli by conventional methods, followed by Klebsiella pneumoniae and Pseudomonas aeruginosa. Eighty-four of these monomicrobial cultures were identified by MALDI-TOF to the species level. Eighty-one of the eighty-four were concordant with the conventional identification (96.4%). Conclusion The MALDI-TOF proved to be useful for the rapid and reliable identification of g-ve bacteria from the clinical specimens. The difference in turnaround time for bacterial identification was significant between MALDI-TOF MS and VITEK 2 with minimal preparation for the blood cultures.

NanoCLUST: a species-level analysis of 16S rRNA nanopore sequencing data.

NanoCLUST is an analysis pipeline for the classification of amplicon-based full-length 16S rRNA nanopore reads. It is characterized by an unsupervised read clustering step, based on Uniform Manifold Approximation and Projection (UMAP), followed by the construction of a polished read and subsequent Blast classification. Here, we demonstrate that NanoCLUST performs better than other state-of-the-art software in the characterization of two commercial mock communities, enabling accurate bacterial identification and abundance profile estimation at species-level resolution. Source code, test data and documentation of NanoCLUST are freely available at https://github.com/genomicsITER/NanoCLUST under MIT License. Supplementary data are available at Bioinformatics online.

Validation of MALDI-TOF MS devices in reanalysis of unidentified pathogenic bacteria detected in blood cultures.

In hospital microbial laboratories, morphological and biochemical analyses are performed to identify pathogenic microbes;however, these procedures lack rapidity and accuracy. Recently, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has been clinically utilized, and is expected to enable rapid and accurate microbial identification. We aimed to validate two MALDI-TOF MS devices available in Japan: the VITEK-MS (BioMérieux) and the Microflex LT (Bruker Daltonics). Clinically isolated bacteria, 100 samples in all, detected in blood cultures but incompletely identified by conventional procedures, were reanalyzed using the two devices. The VITEK-MS and Microflex LT, respectively, identified 49% (49/100) and 80% (80/100) of the tested bacteria at the species level, as well as 96% (96/100) and 95% (95/100) at the genus level. Among those reidentified strains, 26% (26/100) at the species level and 88% (88/100) at the genus level were concordant with each other, though three strains were unmatched. Moreover, four bacterial strains were unable to be identified using the VITEK-MS, versus five using the Microflex LT. MALDI-TOF MS devices can provide more rapid and accurate bacterial identification than ever before;however, the characteristics of each system were slightly different;therefore, it is necessary to understand the difference in performance of MALDI-TOF MS models.

TARGETING THE 16S RRNA GENE FOR BACTERIAL IDENTIFICATION IN COMPLEX MIXED SAMPLES: COMPARATIVE EVALUATION OF SECOND (ILLUMINA) AND THIRD (OXFORD NANOPORE TECHNOLOGIES) GENERATION SEQUENCING TECHNOLOGIES.

Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although >99% of reads were correctly classified at the genus level, up to ≈40% were misclassified at the species level. Both technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.

The role of 'atypical' Brucella in amphibians: are we facing novel emerging pathogens?

To discuss together the novel cases of Brucella infections in frogs with the results of published reports to extend our current knowledge on 'atypical' brucellae isolated from amphibians and to discuss the challenges we face on this extraordinary emerging group of pathogens. Since our first description, an additional 14 isolates from four different frog species were collected. Novel isolates and a subset of Brucella isolates previously cultured from African bullfrogs were characterized by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), Fourier transform-infrared (FT-IR) spectroscopy and broth microdilution susceptibility testing. MALDI-TOF MS worked very efficiently for an accurate bacterial identification to the genus level. Within the cluster analysis, 'atypical' brucellae grouped distant from Brucella melitensis and were even more separated by FT-IR spectroscopy with respect to their geographical origin. Minimum inhibitory concentrations of 14 antimicrobial substances are provided as baseline data on antimicrobial susceptibility. The case history of Brucella infections in amphibians reveals a variety of pathologies ranging from localized manifestations to systemic infections. Some isolates seem to be capable of causing high mortality in zoological exhibitions putting higher demands on the management of endangered frog species. There is considerable risk in overlooking and misidentifying 'atypical' Brucella in routine diagnostics. Brucella have only recently been described in cold-blooded vertebrates. Their presence in frog species native to Africa, America and Australia indicates a more common occurrence in amphibians than previously thought. This study provides an extensive overview of amphibian brucellae by highlighting the main features of their clinical significance, diagnosis and zoonotic potential.

Optimized genotyping method for identification of bacterial contaminants in pharmaceutical industry.

Microbiological control is of crucial importance in the pharmaceutical industry regarding the possible bacterial contamination of the environment, water, raw materials and finished products. Molecular identification of bacterial contaminants based on DNA sequencing of the hypervariable 16SrRNA gene has been introduced recently. The aim of this study is to investigate the suitability of gene sequencing using our selection of PCR primers and conditions for rapid and accurate bacterial identification in pharmaceutical industry quality control. DNA was extracted from overnight incubated colonies from 10 bacterial ATCC strains, which are common contaminants in the pharmaceutical industry. A region of bacterial 16SrRNA gene was analyzed by bidirectional DNA sequencing. Bacterial identification based on partial sequencing of the 16SrRNA gene is the appropriate method that could be used in the pharmaceutical industry after adequate validations. We have successfully identified all tested bacteria with more than 99 % similarity to the already published sequences.

Rapid and Accurate Bacterial Identification in Probiotics and Yoghurts by MALDI‐TOF Mass Spectrometry

Probiotic food is manufactured by adding probiotic strains simultaneously with starter cultures in fermentation tanks. Here, we investigate the accuracy and feasibility of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) for bacterial identification at the species level in probiotic food and yoghurts. Probiotic food and yoghurts were cultured in Columbia and Lactobacillus specific agar and tested by quantitative real-time PCR (qPCR) for the detection and quantification of Lactobacillus sp. Bacterial identification was performed by MALDI-TOF analysis and by amplification and sequencing of tuf and 16S rDNA genes. We tested 13 probiotic food and yoghurts and we identified by qPCR that they presented 10(6) to 10(7) copies of Lactobacillus spp. DNA/g. All products contained very large numbers of living bacteria varying from 10(6) to 10(9) colony forming units/g. These bacteria were identified as Lactobacillus casei, Lactococcus lactis, Bifidobacterium animalis, Lactobacillus delbrueckii, and Streptococcus thermophilus. MALDI-TOF MS presented 92% specificity compared to the molecular assays. In one product we found L. lactis, instead of Bifidus spp. which was mentioned on the label and for another L. delbrueckii and S. thermophilus instead of Bifidus spp. MALDI-TOF MS allows a rapid and accurate bacterial identification at the species level in probiotic food and yoghurts. Although the safety and functionality of probiotics are species and strain dependent, we found a discrepancy between the bacterial strain announced on the label and the strain identified. Practical Application: MALDI-TOF MS is rapid and specific for the identification of bacteria in probiotic food and yoghurts. Although the safety and functionality of probiotics are species and strain dependent, we found a discrepancy between the bacterial strain announced on the label and the strain identified.

Cover Caption

On the cover: Gram stain of yogurt, from “Rapid and Accurate Bacterial Identification in Probiotics and Yoghurts by MALDI‐TOF Mass Spectrometry” by Emmanouil Angelakis, Matthieu Million, Mireille Henry and Didier Raoult; p M571.

Highly Efficient Classification and Identification of Human Pathogenic Bacteria by MALDI-TOF MS

Accurate and rapid identification of pathogenic microorganisms is of critical importance in disease treatment and public health. Conventional work flows are time-consuming, and procedures are multifaceted. MS can be an alternative but is limited by low efficiency for amino acid sequencing as well as low reproducibility for spectrum fingerprinting. We systematically analyzed the feasibility of applying MS for rapid and accurate bacterial identification. Directly applying bacterial colonies without further protein extraction to MALDI-TOF MS analysis revealed rich peak contents and high reproducibility. The MS spectra derived from 57 isolates comprising six human pathogenic bacterial species were analyzed using both unsupervised hierarchical clustering and supervised model construction via the Genetic Algorithm. Hierarchical clustering analysis categorized the spectra into six groups precisely corresponding to the six bacterial species. Precise classification was also maintained in an independently prepared set of bacteria even when the numbers of m/z values were reduced to six. In parallel, classification models were constructed via Genetic Algorithm analysis. A model containing 18 m/z values accurately classified independently prepared bacteria and identified those species originally not used for model construction. Moreover bacteria fewer than 10(4) cells and different species in bacterial mixtures were identified using the classification model approach. In conclusion, the application of MALDI-TOF MS in combination with a suitable model construction provides a highly accurate method for bacterial classification and identification. The approach can identify bacteria with low abundance even in mixed flora, suggesting that a rapid and accurate bacterial identification using MS techniques even before culture can be attained in the near future.

Strain and phase identification of the U.S. category B agent Coxiella burnetii by matrix assisted laser desorption/ionization time-of-flight mass spectrometry and multivariate pattern recognition

Accurate bacterial identification is important in diagnosing disease and in microbial forensics. Coxiella burnetii, a highly infective microorganism causative of the human disease Q fever, is now considered a U.S. category B potential bioterrorism agent. We report here an approach for the confirmatory identification of C. burnetii at the strain level which involves the combined use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and supervised pattern recognition via Partial Least Squares-Discriminant Analysis (PLS-DA). C. burnetii isolates investigated in this study included the following prototype strains from different geographical and/or historical origins and with different antigenic properties: Nine Mile I, Australian QD, M44, KAV, PAV, Henzerling, and Ohio. After culture and purification following standard protocols, linear MALDI-TOF mass spectra of pure bacterial cultures were acquired in positive ion mode. Mass spectral data were normalized, baseline-corrected, denoised, binarized and modeled by PLS-DA under crossvalidation conditions. Robustness with respect to uncontrolled variations in the sample preparation and MALDI analysis protocol was assessed by repeating the experiment on five different days spanning a period of 6 months. The method was validated by the prediction of unknown C. burnetii samples in an independent test set with 100% sensitivity and specificity for five out of six strain classes.

Rapid identification of Streptococcus and Enterococcus species using diffuse reflectance-absorbance Fourier transform infrared spectroscopy and artificial neural networks

Diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR) was used to analyse 19 hospital isolates which had been identified by conventional means to one of Enterococcus faecalis, E. faecium, Streptococcus bovis, S. mitis, S. pneumoniae, or S. pyogenes. Principal components analysis of the FT-IR spectra showed that this ‘unsupervised’ learning method failed to form six separable clusters (one for each species) and thus could not be used to identify these bacteria based on their FT-IR spectra. By contrast, artificial neural networks (ANNs) could be trained by ‘supervised’ learning (using the back-propagation algorithm) with the principal components scores of derivatised spectra to recognise the strains from their FT-IR spectra. These results demonstrate that the combination of FT-IR and ANNs provides a rapid, novel and accurate bacterial identification technique.