Ultrafast and Ultrasensitive Naked-Eye Detection of Urease-Positive Bacteria with Plasmonic Nanosensors

Abstract

Identifying the pathogen responsible for an infection is a requirement in order to personalize antimicrobial treatments. Detecting bacterial enzymes, such as proteases, lipases, and oxidoreductases, is a winning approach for detecting pathogens at the point of care. In this Article, a new method for detecting urease-producing bacteria rapidly and at ultralow concentrations is reported. In this method, longsome bacteriological culture steps are substituted for a 10 min capture procedure with positively charged magnetic beads. The presence of urease-positive bacteria on the particles is then queried with a plasmonic signal generation step that generates blue-or red-colored nanoparticle suspensions upon addition of the enzyme substrate. These colorimetric signals, which can be easily identified by eye, are generated by the NH 3 -dependent assembly of gold nanoparticles in the presence of bovine serum albumin (BSA). The proposed method can detect Proteus mirabilis with a limit of detection of 10 1 cells mL −1 , with a total assay time of 40 min, even in the presence of a large excess of urease-negative bacteria (Pseudomonas aeruginosa). Furthermore, it does not require bulky equipment, and it can detect P. mirabilis at clinically relevant concentrations within minutes, making it suitable for detecting urease-positive pathogens at the point of care.

Contrast between traditional and machine learning algorithms based on a urine culture predictive model: a multicenter retrospective study in patients with urinary calculi

“…However, current reports concerning urine culture predictive models are based on logistic regression algorithms, and their results are insufficiently accurate as a consequence of the algorithm's inherent limitations (11,21). One of the prerequisites to determine the accuracy of the (22)(23)(24). The characteristics of machine learning algorithms are that they allow the use of as many features as desired from all available data to construct individual predictive models in a nonlinear pattern, and they do not need to consider the collinearity among features.…”

Nanotechnology for Targeted Detection and Removal of Bacteria: Opportunities and Challenges

“…[ 38 ] A plasmonic sensor array was developed to detect urease‐positive and ‐negative bacteria such as Proteus mirabilis and P. aeruginosa , respectively. [ 39 ] This sensor array consisted of magnetic beads coated with a positively charged polymer, mediating the electrostatic interaction with negatively charged bacteria. The magnetic bead–bacteria complex rapidly aggregated in the presence of bovine serum albumin at acidic pH.…”

Nanotools for Sepsis Diagnosis and Treatment

“…Naked eye detection of pathogens and metabolic activity assessment of pathogens [29][30][31][32][35][36][37][38]72] Lens-free interferometric microscopy (LIM) Au nanohole substrates Enhancement of optical signals [ 39,40] Fluorescence resonance energy transfer (FRET) Silica NPs, QDs Fluorescent signal amplification [48][49][50][51][52] Magnetic resonance imaging (MRI) Magnetic NPs, SPIONs Contrast agents [55][56][57][58][59]61,64,74] Surface-enhanced Raman scattering (SERS) Au-coated MNPs, Magnetic core-polymeric shell biomimetic NPs Sepsis biomarkers capturing [ 62,63] Mass spectrometry MS) MNPs, Liposomes Mass spectrum enrichment [ 65,70] Polymerase chain reaction (PCR) SPIONs, AuNPs, MNPs DNA amplification [30][31][32][34][35][36][55][56][57]59,60] studied for NP-enabled sepsis diagnosis are based on PCR, colorimetric biosensing, surface-enhanced Raman scattering (SERS), lens-free interferometric microscopy (LIM), mass spectrometry (MS), and magnetic resonance imaging (MRI) ( Table 1,2 and Figure 1). Herein, we strictly focus on the "nano"diagnosis of sepsis and therefore of microbial infections induced by certain pathogens (e....…”

“…More recently, a naked-eye detection method of urease-positive bacteria using magnetic beads and plasmonic AuNP sensors was proposed. [37] Following magnetic capturing of bacteria and urea addition in solution, the pH-dependent assembly of AuNPs induced red-or blue-colored NP suspensions, reflecting the presence or not, respectively, of urease-positive bacteria. As ureasenegative bacteria did not increase the pH upon urea addition, the acidic conditions of the solution led to AuNPs clustering and a blue colored test.…”