LabMedica

Download Mobile App
Recent News Expo Clinical Chem. Molecular Diagnostics Hematology Immunology Microbiology Pathology Technology Industry Focus

New Raman Spectroscopy-Based Method Detects Infections in Cystic Fibrosis Patients in Minutes

By LabMedica International staff writers
Posted on 02 May 2022
Print article
Image: Prototype of the new spectroscopy instrument to detect infection in cystic fibrosis (Photo courtesy of University of Southampton)
Image: Prototype of the new spectroscopy instrument to detect infection in cystic fibrosis (Photo courtesy of University of Southampton)

Cystic fibrosis is an inherited condition that causes sticky mucus to build up in the lungs and digestive system. This causes lung infections and problems with digesting food. Treatments are available to help reduce the problems caused by the condition. Yet recurring infections still dramatically reduce the quality and length of life. The current methods for diagnosing immediate (acute) and longer-term (chronic) infections are complex and time-consuming in the laboratory. For biofilm infections, it can take days from collecting and processing a patient’s sample to achieving a result. This delays effective treatments and impacts patient outcomes. Now, a multi-disciplinary team of researchers has set out to develop a diagnostic tool that would be rapid, accurate and simple-to-use for doctors.

Researchers from the University of Southampton (Southampton, UK) have developed a new chemical analysis technique called multi-excitation Raman spectroscopy. This non-invasive method emits a scattering of multiple colors of light into a patient’s sample. The technique has the potential to detect infections in cystic fibrosis patients in minutes rather than days. In future, the simple analysis could be performed on hospital wards to deliver faster and more effective treatment. The approach could also be expanded to target a variety of diseases and counter anti-microbial resistance.

Long term infections in the lungs of people with cystic fibrosis are extremely hard to treat. There is evidence that the Pseudomonas aeruginosa bacteria exists as biofilms in the body, protecting the bacteria from antibiotic action and driving antimicrobial resistance. This increases the urgency for rapid and effective treatment. The Southampton research showed 99.75% accuracy at identifying Pseudomonas aeruginosa and Staphylococcus aureus across all studied strains. This included 100% accuracy for drug-sensitive and drug-resistant Staphylococcus aureus.

“Our new Raman spectroscopy based method offers many advantages over resource-intensive, culture-based methods, allowing rapid and label-free analysis,” said Prof Sumeet Mahajan, Head of Chemical Biology and the Associate Director of Institute for Life Sciences at the University of Southampton. “It is reagentless and avoids complex sample-preparation steps with sophisticated equipment. Here, we have developed a method that is highly accurate yet rapid and neither requires nanoscale materials for enhancing signals nor fluorophores for detection.”

Related Links:
University of Southampton 

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
POCT Fluorescent Immunoassay Analyzer
FIA Go
New
Gold Member
Liquid Ready-To-Use Lp(a) Reagent
Lipoprotein (a) Reagent

Print article

Channels

Clinical Chemistry

view channel
Image: The 3D printed miniature ionizer is a key component of a mass spectrometer (Photo courtesy of MIT)

3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models

Mass spectrometry is a precise technique for identifying the chemical components of a sample and has significant potential for monitoring chronic illness health states, such as measuring hormone levels... Read more

Hematology

view channel
Image: The CAPILLARYS 3 DBS devices have received U.S. FDA 510(k) clearance (Photo courtesy of Sebia)

Next Generation Instrument Screens for Hemoglobin Disorders in Newborns

Hemoglobinopathies, the most widespread inherited conditions globally, affect about 7% of the population as carriers, with 2.7% of newborns being born with these conditions. The spectrum of clinical manifestations... Read more

Immunology

view channel
Image: The AI predictive model identifies the most potent cancer killing immune cells for use in immunotherapies (Photo courtesy of Shutterstock)

AI Predicts Tumor-Killing Cells with High Accuracy

Cellular immunotherapy involves extracting immune cells from a patient's tumor, potentially enhancing their cancer-fighting capabilities through engineering, and then expanding and reintroducing them into the body.... Read more