SCFI™

Antibiotic Susceptibility Testing in 30 minutes

SCFI™ detects metabolic changes within bacterial cells that occur in response to antibiotics.

SCFI is a machine-learning enabled microscope that measures nanoscale fluctuations of subcellular movement. By detecting fluctuations in the presence of antibiotics, SCFI can determine which antibiotics are most effective for the patient.

The Technology behind SCFI™

SCFI detects metabolic changes within bacterial cells that occur in response to antibiotics as a light scattering signal

In metabolically active cells (Live/resistant to antibiotic treatment) subcellular movement is increased, detectable as a high frequency light scattering signal

In metabolically inactive cells (dead/ susceptible to antibiotics) subcellular movement is decreased, detectable as a low frequency/ no light scattering signal

To date we have demonstrated that nanoscale fluctuations of bacteria are measurable despite differences in cell wall structure (Gram positive/ negative), shape (cocci/rod) and antibiotic activity (bactericidal/ bacteriostatic)

The SCFI™ Assay

1. Immobilise

Bacteria is extracted from the sample

2. Add Antibiotic

Antibiotics are added to the sample for 20-30 minutes

3. Image

Bacterial metabolism is measured using light scattering

4. Analyse

Bacterial resistance/ susceptibilities are determined

Scientific Publications

BioRxiv 2018- Paper

Imaging of sub-cellular fluctuations provides a rapid way to observe bacterial viability and response to antibiotics

C. Bermingham, I. Murillo, A. Payot, K. Balram, M. Kloucek, S. Hanna, N. Redmond, H. BAxter, R. Oulton, M. Avison, M. Antognozzi

Cantliever Based Sensors 2021- Journal

Towards a Fully Automated Scanning Probe Microscope for Biomedical Applications

W. Szeremeta, R. Harniman, C. Bermingham and M. Antognozzi

Biophysical Journal 2022- Journal

Use of sub-cellular fluctuation imaging (SCFI) as a rapid antimicrobial susceptibility test

K. Phonrat, C. Bermingham, C. Frapwell, C. Zorn-Singh, G. Gibb, M. Avison and M. Antognozzi

BEAM Alliance 7th AMR Conference – Poster

Development of Deep Learning Models for Sub-Cellular Fluctuation Imaging (SCFI): a 30-minute antibiotic susceptibility test

S. Rama, M. Antognozzi, W. Szeremeta, K. Phonrat, A. Eley, M. Kyriakides, H. Newman, K. Bonney-Bhanadal, J. Preece, N. Dorh and J. Dorh

BSAC The challenge of Urinary Tract Infections 2023 – Poster

Development of Deep Learning Models for Sub-Cellular Fluctuation Imaging (SCFI): a 30-minute antibiotic susceptibility test for Urinary Tract Infections

S. Rama, M. Antognozzi, W. Szeremeta, K. Phonrat, A. Eley, M. Kyriakides, H. Newman, K. Bonney-Bhanadal, J. Preece, N. Dorh and J. Dorh

Learn more about SCFI

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