Method For Bacterial Identification Research Articles

Water physicochemical quality as driver of spatial and temporal patterns of microbial community composition in lake ecosystems

This study aimed at monitoring and management of the surface water and potentially pathogenic microbes of Lake Tonga (Algeria) with respect to. It characterized the main bacterial diversity patterns of Lake Tonga and predicted from water physicochemical parameters and water quality index (WQI) the distribution of bacterial species and the main indicator groups of faecal water contamination. Water samples were taken monthly at three sampling sites of different water depths. Several physicochemical parameters were measured; of which some were included in computing WQI to characterize the water quality of the lake. Counting, isolation and bacterial identification methods were used to characterize the existing aerobic heterotrophic bacteria. The composition of the microbial community of the waterbody of Lake Tonga included an abundant culturable bacterial flora belonging to several bacterial families and whose specific richness varied between water depths of the sites sampled. Species richness of the bacteria identified phenotypically varied between 7 and 11 per sample. The site with shallow water was the richest in bacterial species, compared to moderate and deep waters. The redundancy analysis showed the main physicochemical drivers of the microbial community composition. Our findings showed that high WQI scores indicated the water quality deterioration which triggered the increase in total load of faecal indicator bacterial groups. This study identified in Lake Tonga an important culturable aerobic bacterial flora whose specific richness and distribution varied spatially following the effects of water physicochemical parameters. Lake Tonga needs an integrated management plan to mitigate human disturbances declining water quality.

A Case of Bacteremia Caused by Raoultella planticola Direct Identification from Blood Culture by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Background: Raoultella planticola is an uncommon gram-negative organism found in the environment. Patients and Methods: The patient, an 81-year-old female who had undergone total cystectomy and bilateral ureteral stoma surgery, presented to the hospital with a fever. It was determined that Raoultella planticola was responsible for the bacteremia. Results: Rapid identification of bacteria using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in blood culture samples and appropriate antibacterial treatment was begun and the patient was discharged three days later. Conclusions: This case emphasizes the presence of a rare pathogen as the cause of bacteremia and underscores the importance of utilizing rapid methods for bacterial identification to establish an accurate diagnosis.

Topical issues of antibiotic resistance: modern methods of identification of bacterial pathogens and determination of their qualities

One of the most urgent problems in medicine today is the problem of antibiotic resistance. Why this problem? After all, scientists around the world proclaimed victory over microorganisms in the 50-60s of the last century? And since the 70s already began to appear information about resistant strains. Everything turned out to be not so simple. Due to uncontrolled and irrational use of antibiotics, mankind is rapidly approaching the so-called "post-antibiotic era". How to stop this "approach"? It is necessary to clearly follow the principles of rational antibiotic therapy.
 Rational antibiotic therapy requires identifying the bacterial nature of the disease, determining the sensitivity of the microorganisms to the antibiotic and starting treatment as soon as possible. To comply with these principles, rapid and accurate methods of identification of microorganisms are necessary, because it is on the basis of these methods that the most effective antimicrobial agent is selected.
 There are standard methods of identification, which include the disk-diffusion method and the serial dilution method. The main disadvantage of these methods is the length of time it takes to obtain results.
 So what are the alternative methods available? There are many methods of microbial identification, but not all of them are suitable for widespread use due to the high cost, the need for expensive equipment.
 Of all the current methods, three methods are emphasized in this review: 16S rRNA gene sequencing, MALDI-TOF MS and EUCAST RAST. Sequencing of the 16S rRNA gene is based on decoding the region of the gene, which in bacteria carries information on resistance mechanisms and structure features. MALDI-TOF MS is a desorption method of "soft" ionization caused by exposure of the matrix with the analyzed substance to pulses of laser radiation. The EUCAST RAST method is an accelerated disk-diffusion method.
 This review describes the problem of antibiotic resistance, mechanisms of bacterial resistance, as well as modern and standard methods of bacterial identification and antibiotic sensitivity.
 The aim of this review was to compare routine methods of identification of species and qualitative properties of microorganisms, causative agents of nosocomial infections, with modern technologies of microbiological testing as an important step in solving the problem of priority selection of effective antimicrobial agents.
 So, the main question of this review is: can modern methods displace standard methods of microorganism identification?

Rapid detection of Pseudomonas syringae pv. actinidiae by electrochemical surface-enhanced Raman spectroscopy

Bacterial cancer caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to kiwifruit in the world, and there is still a lack of effective control measures. The field of bacterial detection needs a fast, easy-to-use and sensitive identification platform. The current bacterial identification methods are lack of time efficiency, which brings problems to many sectors of society. Surface-enhanced Raman spectroscopy (SERS) and electrochemistry (EC) have been studied as possible candidates for bacterial detection because of their high sensitivity for the detection of biomolecules. In this work, SERS, EC and electrochemical surface-enhanced Raman spectroscopy (EC-SERS) were used for the first time to study the adsorption and EC behavior of Psa on the surface of nanostructured silver electrodes. Two different Raman spectra of a single analyte were obtained, and this dual detection was realized. Silver nanoparticles with iodide and calcium ions (Ag@ICNPs) were synthesized as SERS substrates significantly enhanced the characteristic signal peaks of Psa, and the limit of detection (LOD) is as low as 1.0 × 102 cfu/mL. Chemical imaging results show that the application of negative voltage can significantly improve the spectrum quality, showing a higher signal at −0.8 V, indicating that Psa molecules may have potential-induced reorientation on the electrode surface. Therefore, EC-SERS has the ability to greatly improve the SERS performance of bacteria in terms of peak intensity and spectral richness.

Presence of blaCTXM-1, blaCTXM-9, and blaTEM-1 Genes in Extended-spectrum β-lactamase-producing Escherichia coli Isolates from Hospital Wastewater

BACKGROUND: Extended-spectrum β-lactamase-producing Escherichia coli (ESBL-EC) are selectively proliferated in the human gut, excreted through feces, and deposited through wastewater lines, with hospital wastewater acting as a major reservoir of antibiotic resistance genes and resistant bacteria, thus pose adverse effects to human health. This study aimed to determine the presence of blaCTXM-1, blaCTXM-9, blaTEM-1, and blaSHV-1 genes in ESBL-EC in wastewater from selected hospitals in Manila and Quezon City, the Philippines.METHODS: Influent and effluent in twelve hospital wastewater treatment plants were collected, screened for cefotaxime-resistant E. coli, and examined for the ESBL production through phenotypic characterization using conventional bacterial identification, disk diffusion method, and VITEK® 2 Compact system and genotypic identification of ESBL-EC blaCTXM-1, blaCTXM-9, blaTEM-1, blaSHV-1 genes using multiplex polymerase chain reaction (PCR).RESULTS: Conventional bacterial identification methods and the VITEK® 2 Compact system results showed that both influent and effluent samples were positive for ESBL-EC at 33.3% and 16.7%, respectively. Multiplex PCR results revealed that various E. coli isolates were of ESBL-EC blaCTXM-1, blaCTXM-9, and blaTEM-1 genes. Multi-drug resistance was observed among all ESBL-EC isolates with resistance being highest against ampicillin, cefuroxime, ceftazidime, ceftriaxone, cefepime, piperacillin, and aztreonam.CONCLUSION: As the study revealed the presence of ESBL-producing bacteria, efforts must be made to ensure the prudent antimicrobial use with possible emphasis on antibiotic rotation accompanied by intensified infection prevention and control in hospital settings.KEYWORDS: antimicrobial resistance, beta-lactams, blaCTXM, blaTEM, extended-spectrum beta-lactamase, E. coli, hospital wastewater

Comparison of nine extraction methods for bacterial identification using the ONT MinION sequencer.

The Anthrax mailings bioterrorism attack in 2001 revealed the need for universal and rapid microbial forensic analyses on unknown biological evidence. However, the gold standard for bacterial identification includes culturing isolates, which is laborious. Molecular approaches for bacterial identification revolve around 16S ribosomal gene sequencing using Sanger or next generation sequencing (NGS) platforms, but these techniques are laboratory-based and can also be time-consuming. The Oxford Nanopore Technologies (ONT) MinION sequencer can generate long read lengths that span the entire bacterial 16S rRNA gene and accurately identify the species level. This platform can be used in the field, allowing on-site evidence analysis. However, it requires higher quantities of pure DNA compared to other sequencing platforms; thus, the extraction method for bacterial DNA is critical for downstream analysis, which to date are tailored toward a priori knowledge of the species' taxonomic grouping. During an attack, the investigative team may not know what species they are handling; therefore, identifying an extraction method that can handle all bacterial groups and generate clean DNA for the MinION is useful for microbial forensic analysis. The purpose of this study was to identify a "universal" extraction method that can be coupled with ONT MinION sequencing for use in forensic situations for rapid identification. It also evaluated the cloud-based data analysis software provided by ONT, EPI2ME. No "universal" extraction method was identified as optimal for downstream MinION sequencing. However, the DNeasy PowerSoil Kit and Noda et al. Chelex-100 method gave comparable sequencing results and could be used as rapid extraction techniques. This study showed that the ONT 16S Barcoding Kit 1-24 coupled with the 16S FASTQ workflow might not be the best for use in forensic situations where species-level identification needs to be obtained, as most alignments were approximately 89% accurate. In all seven test organisms and nine extraction methods, accurate species identification was onlyobtained in 63% of the cases.

Classification and prediction of Klebsiella pneumoniae strains with different MLST allelic profiles via SERS spectral analysis.

The Gram-negative non-motile Klebsiella pneuomoniae is currently a major cause of hospital-acquired (HA) and community-acquired (CA) infections, leading to great public health concern globally, while rapid identification and accurate tracing of the pathogenic bacterium is essential in facilitating monitoring and controlling of K. pneumoniae outbreak and dissemination. Multi-locus sequence typing (MLST) is a commonly used typing approach with low cost that is able to distinguish bacterial isolates based on the allelic profiles of several housekeeping genes, despite low resolution and labor intensity of the method. Core-genome MLST scheme (cgMLST) is recently proposed to sub-type and monitor outbreaks of bacterial strains with high resolution and reliability, which uses hundreds or thousands of genes conserved in all or most members of the species. However, the method is complex and requires whole genome sequencing of bacterial strains with high costs. Therefore, it is urgently needed to develop novel methods with high resolution and low cost for bacterial typing. Surface enhanced Raman spectroscopy (SERS) is a rapid, sensitive and cheap method for bacterial identification. Previous studies confirmed that classification and prediction of bacterial strains via SERS spectral analysis correlated well with MLST typing results. However, there is currently no similar comparative analysis in K. pneumoniae strains. In this pilot study, 16 K. pneumoniae strains with different sequencing typings (STs) were selected and a phylogenetic tree was constructed based on core genome analysis. SERS spectra (N = 45/each strain) were generated for all the K. pneumoniae strains, which were then comparatively classified and predicted via six representative machine learning (ML) algorithms. According to the results, SERS technique coupled with the ML algorithm support vector machine (SVM) could achieve the highest accuracy (5-Fold Cross Validation = 100%) in terms of differentiating and predicting all the K. pneumoniae strains that were consistent to corresponding MLSTs. In sum, we show in this pilot study that the SERS-SVM based method is able to accurately predict K. pneumoniae MLST types, which has the application potential in clinical settings for tracing dissemination and controlling outbreak of K. pneumoniae in hospitals and communities with low costs and high rapidity.

Bacteria detection and species identification at the single-cell level using super-resolution fluorescence imaging and AI analysis

The skin microbiome is thought to play a critical role in maintaining skin health and protecting against infection. While most microorganisms that live on the skin are harmless or even beneficial, some can cause skin infections or other health problems, emphasizing the importance of diagnosis of the composition and diversity of the skin flora. However, conventional diagnostic methods for evaluation of the skin microbiome are not sensitive enough to detect bacteria at low concentrations and suffer from poor specificity, thus limiting early diagnosis of bacterial infections. In this study, we developed novel approaches for bacterial species detection and identification methods with single-cell sensitivity using super-resolution microscopy and AI-based image analysis: a protein quantification-based method and an AI-based bacterial image analysis method. We demonstrate that these methods can differentiate between common bacterial members of the skin flora, including Staphylococcus aureus and Staphylococcus epidermidis, and different ribotypes of Cutibacterium acnes, both in purified bacterial samples and in scaling skin samples. The advantages of these methods, including the lack of time-consuming amplification or purification steps and single-cell level detection sensitivity, allow early diagnosis of bacterial infections, even from bacterial samples at extremely low concentrations, thus showing promise as a next-generation platform for microbiome detection as single-cell diagnostics.

Multi-resistant Bacteria to Antibiotics in Hospitals: The Case of Neonatology Services of the University Hospitals Centers of Abidjan, Côte d'Ivoire

Background: Multidrug-resistant bacteria (MDR) represent a global health scourge. Their emergence in hospital services complicates the clinical management of infections caused in particular in immunocompromised persons. The objective of our work was to evaluate the prevalence of MDR in the neonatal services of the University Hospitals Centers of Abidjan.
 Materials and Methods: The present study took place from September to November 2020 and from January to June 2021. The samples collected consisted of venous blood samples for blood cultures, rectal swabs from newborns, nasal and hand swabs from health care workers, and swabs from inert surfaces and neonatal care equipment. Bacterial identification methods, antibiotic susceptibility testing, and Chi-square testing were performed.
 Results: A total of 513 samples were obtained from which 215 organisms were isolated and identified. These bacteria consisted of 52.1% Gram-negative bacilli, of which 77.7% were Enterobacteriaceae and 47.9% Gram-positive cocci. Klebsiella pneumoniae (K. pneumoniae) (25.6%), coagulase-Negative Staphylococcus (CoNS) (24.6%), and Staphylococcus aureus (S. aureus) (23.2%) were the most isolated bacteria. The overall prevalence of MDR was 73.9%. The main antibiotic resistance phenotypes described were the production of Broad Spectrum β-lactamases (ESBL) in 71.9% of Enterobacteriaceae and methicillin resistance (Meti-R) in 75.6% of Staphylococcus. ESBL-producing Enterobacteriaceae (E-ESBL) were mainly observed in rectal carriage and Meti-R strains in blood cultures in newborns in the respective proportions of 45.6% and 56.4%.
 Conclusion: In our work, the results obtained showed a high prevalence of MDR in neonatal services and newborns are the most affected subjects. Improving hygiene rules and control and rationalizing the use of antibiotics are highly recommended control strategies to reduce the hospital dissemination of MDR.

Characterization and in vitro assessment of probiotic potential of Lactiplantibacillus plantarum BXM2 from fermented honey passion fruit beverage

AbstractA potential probiotic strain BXM2 was isolated from naturally fermented honey passion fruit beverage, and identified as Lactiplantibacillus plantarum using 16S rDNA sequence analysis, rpoA gene sequence analysis combined with API bacterial identification method. BXM2 was evaluated for its probiotic and technological properties, such as growth efficiency, gastrointestinal tolerance, antibacterial activity and antibiotic resistance. The results showed that the optimum growth efficiency of BXM2 was achieved under the fermentation temperature ranged from 30°C to 37°C. The initial content of BXM2 (8.50 log CFU/mL) was decreased to 7.53 log CFU/mL after 3 h treatment in simulated gastric fluid (pH = 3.0) and 8.12 log CFU/mL after 6 h treatment in simulated intestinal fluid (pH = 8.0) (p < .05). BXM2 showed active antibacterial activity against oral pathogens (Streptococcus mutans, Prevotella intermedia) and foodborne pathogens (Escherichia coli, Staphylococcus aureus, Shigella sonnei, Salmonella Typhimurium, Proteus mirabilis) with average diameters of inhibition zones ranging from 11.00 to 21.67 mm. Autoaggregation rate of BXM2 was 55.41% and coaggregation rates with the tested pathogens ranged from 34.05% to 86.42%. The antibiotic resistance test showed that BXM2 was safe and sensitive to most of the antibiotics. This study provides valuable information for future investigation and industrial application of this selected strain BXM2.

Evaluation of a sterile, filter-based, in-house method for rapid direct bacterial identification and antimicrobial susceptibility testing using positive blood culture.

This study aimed to assess the performance of our in-house method for rapid direct bacterial identification (ID) and antimicrobial susceptibility testing (AST) using a positive blood culture (BC) broth. For Gram-negative bacteria, 4mL of BC broth was aspirated and passed through a Sartorius Minisart syringe filter with a pore size of 5µm. The filtrate was then centrifuged and washed. A small volume of the pellet was used for ID, using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and for AST, using automated broth microdilution. For Gram-positive cocci, 4mL of BC broth was passed through the Minisart syringe filter. Then, 4mL of sterile distilled water was injected in the direction opposite to that of the filtration to collect the bacterial residue trapped in the filter. Compared with the conventional method performed with pure colonies on agar plates, 94.0% (234/249) were correctly identified using the in-house method, with rates of 91.4% (127/139) and 97.3% (107/110) for Gram-positive and Gram-negative isolates, respectively. Of 234 correctly identified isolates, 230 were assessed by AST. Categorical agreement and essential agreement were 93.3% and 94.5%, respectively, with a minor error rate of 3.8%, a major error rate of 3.4%, and a very major error rate of 1.6%. Our in-house preparation method showed good performance in rapid direct ID and AST using positive BC broths compared to the conventional method. This simple method can shorten the conventional turnaround time for ID and AST by at least 1day, potentially contributing to better patient management.

Investigating Catheter-Related Infections in Southern Benin Hospitals: Identification, Susceptibility, and Resistance Genes of Involved Bacterial Strains.

The use of catheters and bladder catheters in hospitals can increase the risk of bacterial infections. This study aimed to identify the bacterial strains involved in catheter-related infections (CRI) in southern Benin hospitals. The study included 407 samples, including 95 catheter tip samples and 312 urine samples collected from bladder catheters from patients on the first day and 48 h after admission. The catheter tip samples were analyzed using traditional bacterial isolation and identification methods, while the urine samples were analyzed using VITEK-2. Antibiotic sensitivity was tested using the Kirby Bauer method, and virulence and resistance genes were detected through standard PCR. The results showed a predominance of Escherichia coli (53.5%), Klebsiella pneumoniae (23.3%), and Enterobacter aerogenes (7.0%) among Gram-negative bacilli, and coagulase-negative Staphylococcus as the most identified cocci. Bacterial susceptibility to antibiotics showed variable levels of resistance, with blaTEM being detected in 42.9% of identified bacterial species, followed by blaSHV (26.2%) and blaCTX-M-15 (16.7%). The blaNDM gene was only found in three identified bacterial strains, while vanA and vanB genes were detected in 3.2% of strains with a prevalence of 55% for the mecA gene. A prevalence of 18.8% for fimH was noted for the virulence genes. In conclusion, this study highlights the importance of following proper hygiene and aseptic practices during catheterization to effectively prevent CRIs. These findings should be used to improve interventions in hospitals and reduce healthcare-associated infections in developing countries.

GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification.

Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.

A simple double differential centrifugation-wash procedure to rapidly obtain bacterial identification and direct antimicrobial susceptibility testing from positive blood cultures

IntroductionThis study proposes a simple and rapid method for both bacterial identification and direct antimicrobial susceptibility testing (AST) by using MALDI-TOF and a double differential centrifugation-wash procedure from positive blood cultures. MethodsFifty-two positive blood cultures (37 gramnegative bacilli and 15 grampositive cocci) were studied by two methods for identification and AST: a reference method, and the rapid MALDI-TOF method obtaining a purified pellet by using a double differential centrifugation procedure. ResultsA total of 1101 MIC values (mg/l) were interpreted according to EUCAST clinical breakpoints and compared using the two methods simultaneously. Discrepancies in 81 MIC values (7.35%) were detected. By analyzing standard parameters, we obtained 98.28% essential agreement and 92.65% categorical agreement considering all isolates tested. ConclusionThis method provides rapid bacterial identification and AST, offering definitive results 24–48h earlier than the conventional method (p<0.001) and improving the turnaround time in blood culture diagnostics, especially in laboratories without 24-h on-call.

Devascularized Bone Surface Culture: A Novel Strategy for Identifying Osteomyelitis-Related Pathogens.

The gold standard for identifying pathogens causing osteomyelitis (OM) is intraoperative tissue sampling culture (TSC). However, its positive rate remains inadequate. Here, we evaluated the efficiency of a novel strategy, known as devitalized bone surface culture (BSC), for detecting OM-related microorganisms and compared it to TSC. Between December 2021 and July 2022, patients diagnosed with OM and received both methods for bacterial identification were screened for analysis. In total, 51 cases were finally recruited for analysis. The mean age was 43.6 years, with the tibia as the top infection site. The positive rate of BSC was relatively higher than that of TSC (74.5% vs. 58.8%, p = 0.093), though no statistical difference was achieved. Both BSC and TSC detected definite pathogens in 29 patients, and their results were in accordance with each other. The most frequent microorganism identified by the BSC method was Staphylococcus aureus. Moreover, BSC took a significantly shorter median culture time than TSC (1.0 days vs. 3.0 days, p &lt; 0.001). In summary, BSC may be superior to TSC for identifying OM-associated pathogens, with a higher detectable rate and a shorter culture time.

Application of Microfluidics for Bacterial Identification.

Bacterial infections continue to pose serious public health challenges. Though anti-bacterial therapeutics are effective remedies for treating these infections, the emergence of antibiotic resistance has imposed new challenges to treatment. Often, there is a delay in prescribing antibiotics at initial symptom presentation as it can be challenging to clinically differentiate bacterial infections from other organisms (e.g., viruses) causing infection. Moreover, bacterial infections can arise from food, water, or other sources. These challenges have demonstrated the need for rapid identification of bacteria in liquids, food, clinical spaces, and other environments. Conventional methods of bacterial identification rely on culture-based approaches which require long processing times and higher pathogen concentration thresholds. In the past few years, microfluidic devices paired with various bacterial identification methods have garnered attention for addressing the limitations of conventional methods and demonstrating feasibility for rapid bacterial identification with lower biomass thresholds. However, such culture-free methods often require integration of multiple steps from sample preparation to measurement. Research interest in using microfluidic methods for bacterial identification is growing; therefore, this review article is a summary of current advancements in this field with a focus on comparing the efficacy of polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and emerging spectroscopic methods.

Culture-Independent Raman Spectroscopic Identification of Bacterial Pathogens from Clinical Samples Using Deep Transfer Learning.

The rapid identification of bacterial pathogens in clinical samples like blood, urine, pus, and sputum is the need of the hour. Conventional bacterial identification methods like culturing and nucleic acid-based amplification have limitations like poor sensitivity, high cost, slow turnaround time, etc. Raman spectroscopy, a label-free and noninvasive technique, has overcome these drawbacks by providing rapid biochemical signatures from a single bacterium. Raman spectroscopy combined with chemometric methods has been used effectively to identify pathogens. However, a robust approach is needed to utilize Raman features for accurate classification while dealing with complex data sets such as spectra obtained from clinical isolates, showing high sample-to-sample heterogeneity. In this study, we have used Raman spectroscopy-based identification of pathogens from clinical isolates using a deep transfer learning approach at the single-cell level resolution. We have used the data-augmentation method to increase the volume of spectra needed for deep-learning analysis. Our ResNet model could specifically extract the spectral features of eight different pathogenic bacterial species with a 99.99% classification accuracy. The robustness of our model was validated on a set of blinded data sets, a mix of cultured and noncultured bacterial isolates of various origins and types. Our proposed ResNet model efficiently identified the pathogens from the blinded data set with high accuracy, providing a robust and rapid bacterial identification platform for clinical microbiology.

Ribosomal MLST nucleotide identity (rMLST-NI), a rapid bacterial species identification method: application to Klebsiella and Raoultella genomic species validation.

Bacterial genomics is making an increasing contribution to the fields of medicine and public health microbiology. Consequently, accurate species identification of bacterial genomes is an important task, particularly as the number of genomes stored in online databases increases rapidly and new species are frequently discovered. Existing database entries require regular re-evaluation to ensure that species annotations are consistent with the latest species definitions. We have developed an automated method for bacterial species identification that is an extension of ribosomal multilocus sequence typing (rMLST). The method calculates an 'rMLST nucleotide identity' (rMLST-NI) based on the nucleotides present in the protein-encoding ribosomal genes derived from bacterial genomes. rMLST-NI was used to validate the species annotations of 11839 publicly available Klebsiella and Raoultella genomes based on a comparison with a library of type strain genomes. rMLST-NI was compared with two whole-genome average nucleotide identity methods (OrthoANIu and FastANI) and the k-mer based Kleborate software. The results of the four methods agreed across a dataset of 11839 bacterial genomes and identified a small number of entries (n=89) with species annotations that required updating. The rMLST-NI method was 3.5 times faster than Kleborate, 4.5 times faster than FastANI and 1600 times faster than OrthoANIu. rMLST-NI represents a fast and generic method for species identification using type strains as a reference.

Quality of MALDI-TOF mass spectra in routine diagnostics: results from an international external quality assessment including 36 laboratories from 12 countries using 47 challenging bacterial strains

ObjectivesMatrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) is a widely used method for bacterial species identification. Incomplete databases and mass spectral quality (MSQ) still represent major challenges. Important proxies for MSQ are the number of detected marker masses, reproducibility, and measurement precision. We aimed to assess MSQs across diagnostic laboratories and the potential of simple workflow adaptations to improve it. MethodsFor baseline MSQ assessment, 47 diverse bacterial strains, which are challenging to identify by MALDI-TOF MS, were routinely measured in 36 laboratories from 12 countries, and well-defined MSQ features were used. After an intervention consisting of detailed reported feedback and instructions on how to acquire MALDI-TOF mass spectra, measurements were repeated and MSQs were compared. ResultsAt baseline, we observed heterogeneous MSQ between the devices, considering the median number of marker masses detected (range = [2–25]), reproducibility between technical replicates (range = [55%–86%]), and measurement error (range = [147 parts per million (ppm)–588 ppm]). As a general trend, the spectral quality was improved after the intervention for devices, which yielded low MSQs in the baseline assessment as follows: for four out of five devices with a high measurement error, the measurement precision was improved (p-values <0.001, paired Wilcoxon test); for six out of ten devices, which detected a low number of marker masses, the number of detected marker masses increased (p-values <0.001, paired Wilcoxon test). DiscussionWe have identified simple workflow adaptations, which, to some extent, improve MSQ of poorly performing devices and should be considered by laboratories yielding a low MSQ. Improving MALDI-TOF MSQ in routine diagnostics is essential for increasing the resolution of bacterial identification by MALDI-TOF MS, which is dependent on the reproducible detection of marker masses. The heterogeneity identified in this external quality assessment (EQA) requires further study.

Metagenomics of Cariogenic Microbiota in Primary Teeth with Deep Dentinal Caries: An Illumina-Based Sequencing Study

Discrepancy in the dynamic metabolic progression of the dental biofilm leads to dental caries, which is a polymicrobial infection. The homeostasis of the biofilm is unaffected and is not apparent unless there is an imbalance in the mineralization pattern of the supragingival biofilm. Literature provides numerous facts on microorganisms related to dental caries. Pathologic colonizers in the early stages of tooth decay involve organisms like Streptococcus oralis, subsequent adherence of Streptococcus sobrinus, and Streptococcus mutans[1]. Reports suggest the association of highly complex, variable, and uncultivable microbial population with dental caries, even though prime organisms are commonly known to be allied with disease succession. Association of mutans group streptococci and lactobacilli with the initiation of caries and early caries development have been well documented [2]. Studies have shown transition of early caries causing gram-positive primary facultative bacteria to anaerobic gram-positive rods and cocci and gram-negative rods as the lesion progresses to deep carious lesion[3]. Mapping of bacterial taxa revealed up to 14 phyla along with 101 genera. This comprised around 706 diverse OTUs (Operational Taxonomic Units). Caries progression at various stages and bacterial profile of different species associated with several disease have been observed. Some of the observed species found abundantly in whitespot lesion and dentin lesion of both dentitions were S. Parasanguinis and S. salivarius[4]. Molecular methods for bacterial identification and enumeration are performed routinely to precisely study bacterial species associated with dental caries, including those that are not presently cultivable.