A Tool to Predict Tuberculosis Drug Resistance Now Available Online
|
By LabMedica International staff writers Posted on 09 Jun 2015 |
|
![Image: Mycobacterium tuberculosis (stained purple) in a tissue specimen (blue) (Photo courtesy of the CDC - [US] Centers for Disease Control and Prevention).](https://globetechcdn.com/mobile_labmedica/images/stories/articles/article_images/2015-06-09/GMS-170.jpg "Image: Mycobacterium tuberculosis (stained purple) in a tissue specimen (blue) (Photo courtesy of the CDC - [US] Centers for Disease Control and Prevention).")
Image: Mycobacterium tuberculosis (stained purple) in a tissue specimen (blue) (Photo courtesy of the CDC - [US] Centers for Disease Control and Prevention).
A new online tool for the rapid analysis of whole genome sequence data is set to aid clinicians predict whether a particular patient's tuberculosis (TB) will be susceptible to frequently prescribed antibiotics.
The World Health Organization (WHO) estimated that 5% of the world's 11 million tuberculosis patients have multi-drug-resistance disease (MDR-TB) and that 480,000 new cases arose during 2013 alone. Of those approximately 9% have extensively resistant tuberculosis (XDR-TB) where, in addition to resistance to at least both of the major first line drugs (isoniazid and rifampicin), they also have resistance to two classes of second line drugs used to treat MDR-TB (the fluoroquinolones and the injectable drugs, amikacin, kanamycin, or capreomycin).
Current molecular tests examine limited numbers of mutations in Mycobacterium tuberculosis, the organism that causes TB, and although whole genome sequencing could fully characterize drug resistance, the complexity of data obtained by this technology has restricted their clinical application.
To help solve this problem investigators at the London School of Hygiene & Tropical Medicine (United Kingdom) have created an online tool that analyses and interprets genome sequence data to predict resistance to 11 drugs used for the treatment of TB. Initially, a library (1,325 mutations) predictive of drug resistance for 15 anti-tuberculosis drugs was compiled and then validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online "TB-Profiler" tool was developed to report drug resistance and strain-type profiles directly from raw sequences. The TB-Profiler tool is available on the Internet (Please see Related Links below).
Senior author Dr. Taane Clark, reader in genetic epidemiology and statistical genomics at the London School of Hygiene & Tropical Medicine, said, "Sequencing already assists patient management for a number of conditions such as HIV, but now that it is possible to sequence M. tuberculosis from sputum from suspected multi-drug resistance patients means it has a role in the management of tuberculosis. We have developed a prototype to guide treatment of patients with drug resistant disease, where personalized medicine and treatment offers improved rates of cure."
Complete information regarding the new online tool was published in the May 27, 2015, online edition of the journal Genome Medicine.
Related Links:
TB-Profiler tool
London School of Hygiene & Tropical Medicine
The World Health Organization (WHO) estimated that 5% of the world's 11 million tuberculosis patients have multi-drug-resistance disease (MDR-TB) and that 480,000 new cases arose during 2013 alone. Of those approximately 9% have extensively resistant tuberculosis (XDR-TB) where, in addition to resistance to at least both of the major first line drugs (isoniazid and rifampicin), they also have resistance to two classes of second line drugs used to treat MDR-TB (the fluoroquinolones and the injectable drugs, amikacin, kanamycin, or capreomycin).
Current molecular tests examine limited numbers of mutations in Mycobacterium tuberculosis, the organism that causes TB, and although whole genome sequencing could fully characterize drug resistance, the complexity of data obtained by this technology has restricted their clinical application.
To help solve this problem investigators at the London School of Hygiene & Tropical Medicine (United Kingdom) have created an online tool that analyses and interprets genome sequence data to predict resistance to 11 drugs used for the treatment of TB. Initially, a library (1,325 mutations) predictive of drug resistance for 15 anti-tuberculosis drugs was compiled and then validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online "TB-Profiler" tool was developed to report drug resistance and strain-type profiles directly from raw sequences. The TB-Profiler tool is available on the Internet (Please see Related Links below).
Senior author Dr. Taane Clark, reader in genetic epidemiology and statistical genomics at the London School of Hygiene & Tropical Medicine, said, "Sequencing already assists patient management for a number of conditions such as HIV, but now that it is possible to sequence M. tuberculosis from sputum from suspected multi-drug resistance patients means it has a role in the management of tuberculosis. We have developed a prototype to guide treatment of patients with drug resistant disease, where personalized medicine and treatment offers improved rates of cure."
Complete information regarding the new online tool was published in the May 27, 2015, online edition of the journal Genome Medicine.
Related Links:
TB-Profiler tool
London School of Hygiene & Tropical Medicine
New
Gold Member
Neonatal Heel Incision Device
Tenderfoot
New
Blood Grouping & Compatibility Reagent
Microcolumn Gel Blood Type Test Card
New
Rapid Sepsis Test
SeptiCyte RAPID
Latest Microbiology News
- Breath Analysis Approach Offers Rapid Detection of Bacterial Infection
- Study Highlights Accuracy Gaps in Consumer Gut Microbiome Kits
- WHO Recommends Near POC Tests, Tongue Swabs and Sputum Pooling for TB Diagnosis
- New Imaging Approach Could Help Predict Dangerous Gut Infection
- Rapid Sequencing Could Transform Tuberculosis Care
- Blood-Based Viral Signature Identified in Crohn’s Disease
- Hidden Gut Viruses Linked to Colorectal Cancer Risk
- Three-Test Panel Launched for Detection of Liver Fluke Infections
- Rapid Test Promises Faster Answers for Drug-Resistant Infections
- CRISPR-Based Technology Neutralizes Antibiotic-Resistant Bacteria
- Comprehensive Review Identifies Gut Microbiome Signatures Associated With Alzheimer’s Disease
- AI-Powered Platform Enables Rapid Detection of Drug-Resistant C. Auris Pathogens
- New Test Measures How Effectively Antibiotics Kill Bacteria
- New Antimicrobial Stewardship Standards for TB Care to Optimize Diagnostics
- New UTI Diagnosis Method Delivers Antibiotic Resistance Results 24 Hours Earlier
- Breakthroughs in Microbial Analysis to Enhance Disease Prediction
Channels
Clinical Chemistry
view channel
New Plasma Tau Assay Improves Prediction of Alzheimer’s Progression
Predicting which patients with early symptomatic Alzheimer’s disease will decline more rapidly remains a key challenge in both research and patient care. Growing interest in tau biology, along with advances... Read more
Routine Blood Markers Predict Heart Failure Risk in Prediabetes
Heart failure prevention relies on finding high-risk adults before symptoms appear, yet effective stratification remains difficult in routine care. Prediabetes affects an estimated 115.2 million U.... Read more
Molecular Diagnostics
view channel
Blood Biomarker Predicts Cognitive Outcomes After Cardiac Arrest
Long-term cognitive impairment is a frequent consequence of out-of-hospital cardiac arrest yet early prediction remains difficult. Clinicians commonly use blood-based markers to estimate brain injury risk... Read more
Liquid Biopsy Enables Faster Diagnosis of Childhood Cancer in Africa
Burkitt lymphoma is the most common childhood cancer in Africa and progresses rapidly, making fast, accurate diagnosis essential to survival. Although survival can exceed 90% when therapy starts quickly,... Read more
Hematology
view channel
Rapid Cartridge-Based Test Aims to Expand Access to Hemoglobin Disorder Diagnosis
Sickle cell disease and beta thalassemia are hemoglobin disorders that often require referral to specialized laboratories for definitive diagnosis, delaying results for patients and clinicians.... Read more
New Guidelines Aim to Improve AL Amyloidosis Diagnosis
Light chain (AL) amyloidosis is a rare, life-threatening bone marrow disorder in which abnormal amyloid proteins accumulate in organs. Approximately 3,260 people in the United States are diagnosed... Read more
Immunology
view channel
Microfluidic Chip Detects Cancer Recurrence from Immune Response Signals
Early identification of treatment response and relapse remains a major challenge in solid tumors, where minimal residual disease is difficult to detect with routine imaging and blood tests.... Read more
Cancer Mutation ‘Fingerprints’ to Improve Prediction of Immunotherapy Response
Cancer cells accumulate thousands of genetic mutations, but not all mutations affect tumors in the same way. Some make cancer cells more visible to the immune system, while others allow tumors to evade... Read more
Pathology
view channel
AI-Powered Tool to Transform Dermatopathology Workflow
Skin cancer accounts for the largest number of cancer diagnoses in the United States, placing sustained pressure on pathology services. Diagnostic interpretation can be variable for challenging melanocytic... Read more
New Chromogenic Culture Media Enable Rapid Detection of Candida Infections
Invasive Candida infections are challenging for healthcare systems, with some strains spreading rapidly in hospitals and showing resistance to multiple antifungal drugs. Candida auris is associated with... Read more
Technology
view channel
Portable Breath Sensor Detects Pneumonia Biomarkers in Minutes
Pneumonia is commonly confirmed with chest X-rays or laboratory assays that can take hours, delaying clinical decisions in acute and outpatient settings. Breath-based diagnostics promise faster answers... Read more
New Electronic Pipette Enhances Workflows with Touchscreen Control
Manual pipetting remains a routine yet error-prone step that can affect reproducibility and throughput in clinical and research laboratories. Training demands and ergonomic strain also add variability... Read more
AI Model Outperforms Clinicians in Rare Disease Detection
Rare diseases affect an estimated 300 million people worldwide, yet diagnosis is often protracted and error-prone. Many conditions present with heterogeneous signs that overlap with common disorders, leading... Read more
AI-Driven Diagnostic Demonstrates High Accuracy in Detecting Periprosthetic Joint Infection
Periprosthetic joint infection (PJI) is a rare but serious complication affecting 1% to 2% of primary joint replacement surgeries. The condition occurs when bacteria or fungi infect tissues around an implanted... Read moreIndustry
view channel
Automated MSI Test Gains IVDR Certification to Guide CRC Therapy
Treatment selection for metastatic colorectal cancer often requires knowledge of a tumor’s microsatellite instability (MSI) status. Timely results can help clinicians decide on immunotherapy options.... Read more
