scholarly journals Simultaneous single-channel multiplex and quantification of carbapenem-resistant genes using multidimensional standard curves

2018 ◽  
Author(s):  
Jesus Rodriguez-Manzano ◽  
Ahmad Moniri ◽  
Kenny Malpartida-Cardenas ◽  
Jyothsna Dronavalli ◽  
Frances Davies ◽  
...  
Keyword(s):  
Real Time ◽  
Single Channel ◽  
Point Of Care ◽  
Absolute Quantification ◽  
Sequencing Analysis ◽  
Agarose Gels ◽  
Carbapenem Resistant ◽  
Resistant Genes ◽  
Time Amplification ◽  
Single Reaction

ABSTRACTMultiplexing and absolute quantification of nucleic acids, both have, in their own right, significant and extensive use in biomedical related fields, especially in point-of-care applications. Currently, the ability to detect several nucleic acid targets in a single-reaction scales linearly with the number of targets; an expensive and time-consuming feat. Here, we propose a new methodology based on multidimensional standard curves that extends the use of real-time PCR data obtained by common qPCR instruments. By applying this novel methodology, we achieve simultaneous single-channel multiplexing and enhanced quantification of multiple targets using only real-time amplification data. This is obtained without the need of fluorescent probes, agarose gels, melting curves or sequencing analysis. Given the importance and demand for tackling challenges in antimicrobial resistance, the proposed method is applied to the four most prominent carbapenem-resistant genes: blaOXA-48, blaNDM, blaVIM and blaKPC, which account for 97% of the UK’s reported carbapenemase-producing Enterobacteriaceae.

scholarly journals Multiple Mechanisms Synergistically Induce Pseudomonas Aeruginosa Multiple Drug Resistance

2021 ◽  
Author(s):  
Lulu Yang ◽  
Fangyan Jiao ◽  
Ousman Bajinka ◽  
Khalid A Abdelhalim ◽  
Guojun Wu ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Drug Resistance ◽  
Multiple Drug Resistance ◽  
Multiple Drug ◽  
Antibacterial Drug ◽  
Sequencing Analysis ◽  
Drug Resistant ◽  
Carbapenem Resistant ◽  
Resistant Genes ◽  
Epidemiological Characteristics

Abstract Background: This study was designed to detect the molecular epidemiological characteristics and resistant mechanism of carbapenem resistant Pseudomonas aeruginosa (CRPA) which provide reference for the prevention and treatment of hospital CRPA infection. Methods: 34 strains of CRPA from 2018 to 2019 were isolated and their resistance to 13 commonly used antibiotics was detected using TDR-300B Plus VitEK-2 compact automatic bacterial identification instrument. Then carbapenemase production was detected using Carbe NP test. The efflux pumps MexA and outer membrane protein OprD proteins were detected using RT-PCR and class Ⅰ integron carried with drug-resistant genes were detected using PCR and sequences analysis. Results: Among 34 strains of CRPA, 22 strains were multiple drug resistance (MDR) and 5 strains were extensively drug-resistant (XDR). The results of class Ⅰ integron carried drug-resistant gene sequencing analysis showed the class Ⅰ integron mainly carried aminoglycoside or quinolone antibacterial drug resistant genes. Conclusion: Multiple mechanisms play an important role in the formation and development of MDR or XDR resistance.

scholarly journals Coupling machine learning and high throughput multiplex digital PCR enables accurate detection of carbapenem-resistant genes in clinical isolates

2021 ◽  
Author(s):  
Luca Miglietta ◽  
Ahmad Moniri ◽  
Ivana Pennisi ◽  
Kenny Malpartida Cardenas ◽  
Hala Abbas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
High Throughput ◽  
Classification Accuracy ◽  
Melting Curve ◽  
Digital Pcr ◽  
Curve Analysis ◽  
Melting Curve Analysis ◽  
Carbapenem Resistant ◽  
Resistant Genes

Background: The emergence and spread of carbapenemase-producing organisms (CPO) are a significant clinical and public health concern. Rapid and accurate identification of patients colonised with CPO is essential to adopt prompt prevention measures in order to reduce the risk of transmission. Recent proof-of-concept studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex assays. From this, we sought to determine if this ML based methodology could accurately identify five major carbapenem-resistant genes in clinical CPO-isolates. Methods: We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex assay for detection of blaVIM, blaOXA-48, blaNDM, blaIMP and blaKPC. Combining the recently reported ML method "Amplification and Melting Curve Analysis" (AMCA) with the abovementioned multiplex assay, we assessed the performance of the methodology in detecting these five carbapenem-resistant genes. The classification accuracy relies on the usage of real-time data from a single fluorescent channel and benefits from the kinetic and thermodynamic information encoded in the thousands of amplification events produced by high throughput dPCR. Results: The 5-plex showed a lower limit of detection of 100 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8-99.9%) accuracy (only one misclassified sample out of the 253, with a total of 163,966 positive amplification events), which represents a 7.9% increase compared to the conventional ML-based melting curve analysis (MCA) method. Conclusion: This work demonstrates the utility of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, reducing costs without any changes to instrument hardware. Our findings suggest that, pending additional validation directly from clinical samples, advanced data-driven multiplex dPCR could potentially be integrated in routine clinical diagnostic workflows.

scholarly journals Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates

2021 ◽  
Vol 8 ◽  
Author(s):  
Luca Miglietta ◽  
Ahmad Moniri ◽  
Ivana Pennisi ◽  
Kenny Malpartida-Cardenas ◽  
Hala Abbas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
High Throughput ◽  
Classification Accuracy ◽  
Melting Curve ◽  
Digital Pcr ◽  
Curve Analysis ◽  
Melting Curve Analysis ◽  
Carbapenem Resistant ◽  
Resistant Genes

Rapid and accurate identification of patients colonised with carbapenemase-producing organisms (CPOs) is essential to adopt prompt prevention measures to reduce the risk of transmission. Recent studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex PCR assays when using synthetic DNA templates. We sought to determine if this novel methodology could be applied to improve identification of the five major carbapenem-resistant genes in clinical CPO-isolates, which would represent a leap forward in the use of PCR-based data-driven diagnostics for clinical applications. We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex PCR assay for detection of blaIMP, blaKPC, blaNDM, blaOXA-48, and blaVIM. Combining the recently reported ML method “Amplification and Melting Curve Analysis” (AMCA) with the abovementioned multiplex assay, we assessed the performance of the AMCA methodology in detecting these genes. The improved classification accuracy of AMCA relies on the usage of real-time data from a single-fluorescent channel and benefits from the kinetic/thermodynamic information encoded in the thousands of amplification events produced by high throughput real-time dPCR. The 5-plex showed a lower limit of detection of 10 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8–99.9%) accuracy (only one misclassified sample out of the 253, with a total of 160,041 positive amplification events), which represents a 7.9% increase (p-value <0.05) compared to conventional melting curve analysis. This work demonstrates the use of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, without hardware modifications and additional costs, thus potentially providing substantial clinical utility on screening patients for CPO carriage.

scholarly journals Simultaneous Single-Channel Multiplexing and Quantification of Carbapenem-Resistant Genes Using Multidimensional Standard Curves

2019 ◽  
Vol 91 (3) ◽  
pp. 2013-2020 ◽  
Author(s):  
Jesus Rodriguez-Manzano ◽  
Ahmad Moniri ◽  
Kenny Malpartida-Cardenas ◽  
Jyothsna Dronavalli ◽  
Frances Davies ◽  
...  
Keyword(s):  
Single Channel ◽  
Carbapenem Resistant ◽  
Resistant Genes

scholarly journals Multiplex Real-Time PCR for Detection of an Epidemic KPC-Producing Klebsiella pneumoniae ST258 Clone

2012 ◽  
Vol 56 (6) ◽  
pp. 3444-3447 ◽  
Author(s):  
Liang Chen ◽  
Kalyan D. Chavda ◽  
José R. Mediavilla ◽  
Yanan Zhao ◽  
Henry S. Fraimow ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
Real Time ◽  
Real Time Pcr ◽  
Clinical Isolates ◽  
Pcr Assay ◽  
Content Type ◽  
Carbapenem Resistant ◽  
Sequence Types ◽  
Single Reaction

ABSTRACTWe describe a multiplex real-time PCR assay capable of identifying both the epidemicKlebsiella pneumoniaeST258 clone andblaKPCcarbapenemase genes in a single reaction. The assay displayed excellent sensitivity (100%) and specificity (100%) for identification of ST258 clone andblaKPCin a collection of 75K. pneumoniaeisolates comprising 41 sequence types. Our results suggest that this assay is an effective tool for surveillance of this clone among carbapenem-resistantK. pneumoniaeclinical isolates.

scholarly journals A miniaturized optoelectronic biosensor for real-time point-of-care total protein analysis.

MethodsX ◽  
2021 ◽  
pp. 101414
Author(s):  
Ophir Vermesh ◽  
Fariah Mahzabeen ◽  
Jelena Levi ◽  
Marilyn Tan ◽  
Israt S. Alam ◽  
...  
Keyword(s):  
Real Time ◽  
Total Protein ◽  
Point Of Care ◽  
Protein Analysis ◽  
Time Point

scholarly journals Evaluation of mobile real-time polymerase chain reaction tests for the detection of severe acute respiratory syndrome coronavirus 2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chukwunonso Onyilagha ◽  
Henna Mistry ◽  
Peter Marszal ◽  
Mathieu Pinette ◽  
Darwyn Kobasa ◽  
...  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Real Time ◽  
Point Of Care ◽  
Middle Eastern ◽  
Turnaround Time ◽  
Cross Reactivity ◽  
Clinical Samples ◽  
Diarrhea Virus ◽  
Highly Sensitive ◽  
Transmissible Gastroenteritis

AbstractThe coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), calls for prompt and accurate diagnosis and rapid turnaround time for test results to limit transmission. Here, we evaluated two independent molecular assays, the Biomeme SARS-CoV-2 test, and the Precision Biomonitoring TripleLock SARS-CoV-2 test on a field-deployable point-of-care real-time PCR instrument, Franklin three9, in combination with Biomeme M1 Sample Prep Cartridge Kit for RNA 2.0 (M1) manual extraction system for rapid, specific, and sensitive detection of SARS-COV-2 in cell culture, human, and animal clinical samples. The Biomeme SARS-CoV-2 assay, which simultaneously detects two viral targets, the orf1ab and S genes, and the Precision Biomonitoring TripleLock SARS-CoV-2 assay that targets the 5′ untranslated region (5′ UTR) and the envelope (E) gene of SARS-CoV-2 were highly sensitive and detected as low as 15 SARS-CoV-2 genome copies per reaction. In addition, the two assays were specific and showed no cross-reactivity with Middle Eastern respiratory syndrome coronavirus (MERS-CoV), infectious bronchitis virus (IBV), porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis (TGE) virus, and other common human respiratory viruses and bacterial pathogens. Also, both assays were highly reproducible across different operators and instruments. When used to test animal samples, both assays equally detected SARS-CoV-2 genetic materials in the swabs from SARS-CoV-2-infected hamsters. The M1 lysis buffer completely inactivated SARS-CoV-2 within 10 min at room temperature enabling safe handling of clinical samples. Collectively, these results show that the Biomeme and Precision Biomonitoring TripleLock SARS-CoV-2 mobile testing platforms could reliably and promptly detect SARS-CoV-2 in both human and animal clinical samples in approximately an hour and can be used in remote areas or health care settings not traditionally serviced by a microbiology laboratory.

Real-time medication prices at the point of care: Experiences of prescribers

2021 ◽  
Author(s):  
Foster R Goss ◽  
Anna Sinaiko ◽  
Tim Podhajsky ◽  
Chen-Tan Lin
Keyword(s):  
Real Time ◽  
Point Of Care

scholarly journals Haemophilus influenzae Meningitis Direct Diagnosis by Metagenomic Next-Generation Sequencing: A Case Report

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Madjid Morsli ◽  
Quentin Kerharo ◽  
Jeremy Delerce ◽  
Pierre-Hugues Roche ◽  
Lucas Troude ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Haemophilus Influenzae ◽  
Real Time ◽  
Real Time Pcr ◽  
Point Of Care ◽  
Next Generation ◽  
Oxford Nanopore ◽  
Sequence Encoding ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

Current routine real-time PCR methods used for the point-of-care diagnosis of infectious meningitis do not allow for one-shot genotyping of the pathogen, as in the case of deadly Haemophilus influenzae meningitis. Real-time PCR diagnosed H. influenzae meningitis in a 22-year-old male patient, during his hospitalisation following a more than six-metre fall. Using an Oxford Nanopore Technologies real-time sequencing run in parallel to real-time PCR, we detected the H. influenzae genome directly from the cerebrospinal fluid sample in six hours. Furthermore, BLAST analysis of the sequence encoding for a partial DUF417 domain-containing protein diagnosed a non-b serotype, non-typeable H.influenzae belonging to lineage H. influenzae 22.1-21. The Oxford Nanopore metagenomic next-generation sequencing approach could be considered for the point-of-care diagnosis of infectious meningitis, by direct identification of pathogenic genomes and their genotypes/serotypes.

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