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Biology subjects

Miguelez, M. H. M.

Publications and source records attributed to Miguelez, M. H. M..

2 recordsLinked to original sources

Rapid Automated Isolation and Concentration of Bacteria from Blood Samples

Sepsis is a major global health challenge associated with high mortality rates, with approximately 50 million cases yearly and 13 million deaths. For every hour a patient with septic shock remains untreated, survival decreases by 8%. Challenges persist in the rapid isolation of bacterial pathogens from blood, leading to delays in microorganism identification and antimicrobial susceptibility testing. In this study, we report a centrifuge-based device for the automated isolation and concentration of bacteria from blood samples within 40 min. The device starts with 3 ml of blood or 7.5 ml of blood culture and yields 0.7 mL of optically clear sample with a more than three-fold increased bacterial concentration, rejecting 99.97 {+/-} 0.01% of red blood cells, 97 {+/-} 1% of white blood cells, and 94 {+/-} 4% of platelets. We successfully demonstrated how this process prepares blood culture samples for subsequent: sub-culturing from as low as 10 CFU/mL initial bacterial concentration; matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS)-based identification from 5 x 108 CFU/ml initial bacterial concentration; and microtrap-based detection within 1 h from 5 x 104 CFU/ml initial bacterial concentration. These results demonstrate the potential of this device to automate and accelerate the diagnostic pipeline for sepsis, enabling faster detection and identification of the causative microorganism.

bioengineering↗

Culture-free Rapid Isolation and Detection of Bacteria from Whole Blood at Clinically Relevant Concentrations

Approximately 50 million people suffer from sepsis yearly, and 13 million die from it. For every hour a patient with septic shock is untreated, their survival rate decreases by 8%. Therefore, rapid detection and antibiotic susceptibility profiling of bacterial agents in the blood of sepsis patients are crucial for determining appropriate treatment. The low bacteria concentrations and high abundance of blood cells currently necessitate culture-based diagnostic methods, which can take several days. Here, we introduce a method to isolate bacteria from whole blood with high separation efficiency through smart centrifugation, followed by microfluidic trapping and subsequent detection using deep learning applied to microscopy images.

bioengineering↗