Related Experiment Video
Updated: Aug 11, 2026
Detection of Human Leukocyte Antigen Biomarkers in Breast Cancer Utilizing Label-free Biosensor Technology
Published on: March 24, 2015
Fast and Accurate Pneumocystis Pneumonia Diagnosis in Human Samples Using a Label-Free Plasmonic Biosensor
Olalla Calvo-Lozano1, Anna Aviñó2, Vicente Friaza3
1Nanobiosensors and Bioanalytical Applications Group (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, CIBER in Bioengineering, Biomaterials and Nanomedicine and BIST, Campus UAB Bellaterra, 08193 Barcelona, Spain.
Abstract:
Pneumocystis jirovecii is a fungus responsible for human Pneumocystis pneumonia, one of the most severe infections encountered in immunodepressed individuals. The diagnosis of Pneumocystis pneumonia continues to be challenging due to the absence of specific symptoms in infected patients. Moreover, the standard diagnostic method employed for its diagnosis involves mainly PCR-based techniques, which besides being highly specific and sensitive, require specialized personnel and equipment and are time-consuming. Our aim is to demonstrate an optical biosensor methodology based on surface plasmon resonance to perform such diagnostics in an efficient and decentralized scheme. The biosensor methodology employs poly-purine reverse-Hoogsteen hairpin probes for the detection of the mitochondrial large subunit ribosomal RNA (mtLSU rRNA) gene, related to P. jirovecii detection. The biosensor device performs a real-time and label-free identification of the mtLSU rRNA gene with excellent selectivity and reproducibility, achieving limits of detection of around 2.11 nM. A preliminary evaluation of clinical samples showed rapid, label-free and specific identification of P. jirovecii in human lung fluids such as bronchoalveolar lavages or nasopharyngeal aspirates. These results offer a door for the future deployment of a sensitive diagnostic tool for fast, direct and selective detection of Pneumocystis pneumonia disease.
Insights
A new optical biosensor offers a faster, decentralized method for diagnosing Pneumocystis pneumonia (PCP). This surface plasmon resonance (SPR) technique efficiently detects the fungus in patient samples, improving upon traditional PCR methods.
Area of Science:
- Biomedical Engineering
- Infectious Diseases
- Molecular Diagnostics
Background:
- Pneumocystis pneumonia (PCP) is a severe opportunistic infection in immunocompromised individuals.
- Current diagnostic methods like PCR are sensitive but time-consuming and require specialized facilities.
- Lack of specific symptoms complicates early and accurate PCP diagnosis.
Purpose of the Study:
- To develop and validate an optical biosensor for rapid, decentralized detection of *Pneumocystis jirovecii*.
- To utilize surface plasmon resonance (SPR) with specific hairpin probes for efficient fungal detection.
- To offer an alternative diagnostic approach that overcomes limitations of current methods.
Main Methods:
- Development of an SPR-based optical biosensor.
- Design of poly-purine reverse-Hoogsteen hairpin probes for detecting the *P. jirovecii* mitochondrial large subunit ribosomal RNA (mtLSU rRNA) gene.
- Real-time, label-free detection and analysis of target nucleic acid sequences.
- Testing with clinical samples including bronchoalveolar lavages and nasopharyngeal aspirates.
Main Results:
- The biosensor achieved real-time, label-free detection of the *P. jirovecii* mtLSU rRNA gene.
- Demonstrated excellent selectivity and reproducibility with a limit of detection around 2.11 nM.
- Successfully identified *P. jirovecii* in preliminary clinical samples from human lung fluids.
- Preliminary evaluation showed rapid and specific identification in patient samples.
Conclusions:
- The SPR biosensor provides a sensitive, selective, and rapid diagnostic tool for *Pneumocystis pneumonia*.
- This technology enables efficient and decentralized diagnostics, overcoming limitations of conventional PCR.
- The developed biosensor holds potential for fast, direct detection of PCP in clinical settings.
