Rapid label-free detection of E. coli using antimicrobial peptide assisted impedance spectroscopy

Employing the redox species N,N,N′,N′-tetramethyl-para-phenylene-diamine (TMPD), the label-free detection of E. coli, based on an electrochemical “on”-signal during impact electrochemistry, is reported for the first time.

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Label-free quantitative proteomic analysis of the inhibition effect of Lactobacillus rhamnosus GG on Escherichia coli biofilm formation in co-culture

Proteome Science ◽

10.1186/s12953-021-00172-0 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Huiyi Song ◽

Ni Lou ◽

Jianjun Liu ◽

Hong Xiang ◽

Dong Shang

Keyword(s):

Escherichia Coli ◽

Proteomic Analysis ◽

Biofilm Formation ◽

Lactobacillus Rhamnosus ◽

Differentially Expressed ◽

Differentially Expressed Proteins ◽

Label Free ◽

Quantitative Proteomic Analysis ◽

E Coli ◽

Protein Ubiquitination

Abstract Background Escherichia coli (E. coli) is the principal pathogen that causes biofilm formation. Biofilms are associated with infectious diseases and antibiotic resistance. This study employed proteomic analysis to identify differentially expressed proteins after coculture of E. coli with Lactobacillus rhamnosus GG (LGG) microcapsules. Methods To explore the relevant protein abundance changes after E. coli and LGG coculture, label-free quantitative proteomic analysis and qRT-PCR were applied to E. coli and LGG microcapsule groups before and after coculture, respectively. Results The proteomic analysis characterised a total of 1655 proteins in E. coli K12MG1655 and 1431 proteins in the LGG. After coculture treatment, there were 262 differentially expressed proteins in E. coli and 291 in LGG. Gene ontology analysis showed that the differentially expressed proteins were mainly related to cellular metabolism, the stress response, transcription and the cell membrane. A protein interaction network and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis indicated that the differentiated proteins were mainly involved in the protein ubiquitination pathway and mitochondrial dysfunction. Conclusions These findings indicated that LGG microcapsules may inhibit E. coli biofilm formation by disrupting metabolic processes, particularly in relation to energy metabolism and stimulus responses, both of which are critical for the growth of LGG. Together, these findings increase our understanding of the interactions between bacteria under coculture conditions.

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An Aggregation-Induced Emission Material Labeling Antigen-Based Lateral Flow Immunoassay Strip for Rapid Detection of Escherichia coli O157:H7

SLAS TECHNOLOGY Translating Life Sciences Innovation ◽

10.1177/2472630320981935 ◽

2021 ◽

pp. 247263032098193

Author(s):

Cheng Liu ◽

Shuiqin Fang ◽

Yachen Tian ◽

Youxue Wu ◽

Meijiao Wu ◽

...

Keyword(s):

Escherichia Coli ◽

Rapid Detection ◽

Foodborne Pathogen ◽

Test Strip ◽

Lateral Flow ◽

Detection Sensitivity ◽

Lateral Flow Immunoassay ◽

Escherichia Coli O157 ◽

Aggregation Induced Emission ◽

E Coli

Escherichia coli O157:H7 ( E. coli O157:H7) is a dangerous foodborne pathogen, mainly found in beef, milk, fruits, and their products, causing harm to human health or even death. Therefore, the detection of E. coli O157:H7 in food is particularly important. In this paper, we report a lateral flow immunoassay strip (LFIS) based on aggregation-induced emission (AIE) material labeling antigen as a fluorescent probe for the rapid detection of E. coli O157:H7. The detection sensitivity of the strip is 105 CFU/mL, which is 10 times higher than that of the colloidal gold test strip. This method has good specificity and stability and can be used to detect about 250 CFU of E. coli O157:H7 successfully in 25 g or 25 mL of beef, jelly, and milk. AIE-LFIS might be valuable in monitoring food pathogens for rapid detection.

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In vitro activity of antimicrobial peptide CDP-B11 alone and in combination with colistin against colistin-resistant and multidrug-resistant Escherichia coli

Scientific Reports ◽

10.1038/s41598-021-81140-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kaitlin S. Witherell ◽

Jason Price ◽

Ashok D. Bandaranayake ◽

James Olson ◽

Douglas R. Call

Keyword(s):

Escherichia Coli ◽

Antimicrobial Peptide ◽

Membrane Integrity ◽

Antibiotic Resistance Genes ◽

Multidrug Resistant ◽

Resistant Bacteria ◽

Multidrug Resistant Bacteria ◽

E Coli ◽

Minimal Media

AbstractMultidrug-resistant bacteria are a growing global concern, and with increasingly prevalent resistance to last line antibiotics such as colistin, it is imperative that alternative treatment options are identified. Herein we investigated the mechanism of action of a novel antimicrobial peptide (CDP-B11) and its effectiveness against multidrug-resistant bacteria including Escherichia coli #0346, which harbors multiple antibiotic-resistance genes, including mobilized colistin resistance gene (mcr-1). Bacterial membrane potential and membrane integrity assays, measured by flow cytometry, were used to test membrane disruption. Bacterial growth inhibition assays and time to kill assays measured the effectiveness of CDP-B11 alone and in combination with colistin against E. coli #0346 and other bacteria. Hemolysis assays were used to quantify the hemolytic effects of CDP-B11 alone and in combination with colistin. Findings show CDP-B11 disrupts the outer membrane of E. coli #0346. CDP-B11 with colistin inhibits the growth of E. coli #0346 at ≥ 10× lower colistin concentrations compared to colistin alone in Mueller–Hinton media and M9 media. Growth is significantly inhibited in other clinically relevant strains, such as Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae. In rich media and minimal media, the drug combination kills bacteria at a lower colistin concentration (1.25 μg/mL) compared to colistin alone (2.5 μg/mL). In minimal media, the combination is bactericidal with killing accelerated by up to 2 h compared to colistin alone. Importantly, no significant red blood hemolysis is evident for CDP-B11 alone or in combination with colistin. The characteristics of CDP-B11 presented here indicate that it can be used as a potential monotherapy or as combination therapy with colistin for the treatment of multidrug-resistant infections, including colistin-resistant infections.

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Label-Free Detection of Escherichia coli from Mixed Bacterial Cultures Using Bacteriophage T4 on Plasmonic Fiber-Optic Sensor

ACS Sensors ◽

10.1021/acssensors.1c00801 ◽

2021 ◽

Author(s):

Pallavi Halkare ◽

Nirmal Punjabi ◽

Jigme Wangchuk ◽

Santhosh Madugula ◽

Kiran Kondabagil ◽

...

Keyword(s):

Escherichia Coli ◽

Fiber Optic ◽

Bacteriophage T4 ◽

Fiber Optic Sensor ◽

Label Free ◽

Bacterial Cultures ◽

Optic Sensor ◽

Label Free Detection

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BS4.2 - Label-free detection of nucleic acids and proteins using impedance spectroscopy and surface plasmon resonance

10.5162/imcs2018/bs4.2 ◽

2018 ◽

Author(s):

F. Lisdat ◽

M. Riedel ◽

F. Heinrich

Keyword(s):

Surface Plasmon Resonance ◽

Impedance Spectroscopy ◽

Nucleic Acids ◽

Surface Plasmon ◽

Plasmon Resonance ◽

Label Free ◽

Label Free Detection

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Functionalized Polymers as Receptors for Detection of Cells

Australian Journal of Chemistry ◽

10.1071/ch11181 ◽

2011 ◽

Vol 64 (9) ◽

pp. 1256 ◽

Cited By ~ 9

Author(s):

Miroslava Polreichova ◽

Usman Latif ◽

Franz L. Dickert

Keyword(s):

Soft Lithography ◽

Quartz Crystal ◽

Coli Strain ◽

Yeast Cells ◽

Label Free ◽

Sensitive Material ◽

E Coli ◽

Label Free Detection ◽

Quartz Crystal Microbalances ◽

Cell Strains

Mass sensitive sensors were applied for fast and label-free detection of bio-analytes. Robust and miniaturized sensor devices were fabricated by combining bio-mimetic imprinted surfaces with quartz crystal microbalances for the analysis of yeast and bacteria cells. These sensors allow us to differentiate between different growing stages of yeast cells. Moreover, the viability of cells was detected by structuring quartz crystal microbalance electrodes like a grid. Artificial yeast cells were produced to pattern the recognition layer, giving reversible enrichment of the respective bio-analytes. This approach was followed to ensure the reproducibility of the identical sensitive material in each case, because the properties of each cell depend on its growth stage, which varies over time. The strategy was further applied to develop a sensitive system for Escherichia coli. Structuring of these materials by soft lithography allows differentiation between cell strains, e.g. E. coli (strain W & B) with a five-fold selectivity.

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Rapid Method for Prediction of Escherichia coli Numbers Using an Electronic Sensor Array and an Artificial Neural Network

Journal of Food Protection ◽

10.4315/0362-028x-67.8.1604 ◽

2004 ◽

Vol 67 (8) ◽

pp. 1604-1609 ◽

Cited By ~ 10

Author(s):

UBONRATANA SIRIPATRAWAN ◽

JOHN E. LINZ ◽

BRUCE R. HARTE

Keyword(s):

Neural Network ◽

Escherichia Coli ◽

Artificial Neural Network ◽

Transfer Function ◽

Sensor Array ◽

E Coli ◽

Output Layer ◽

Electronic Sensor ◽

Artificial Neural ◽

Hidden Layer

An electronic sensor array with 12 nonspecific metal oxide sensors was evaluated for its ability to monitor volatile compounds in super broth alone and in super broth inoculated with Escherichia coli (ATCC 25922) at 37°C for 2 to 12 h. Using discriminant function analysis, it was possible to differentiate super broth alone from that containing E. coli when cell numbers were 105 CFU or more. There was a good agreement between the volatile profiles from the electronic sensor array and a gas chromatography–mass spectrometer method. The potential to predict the number of E. coli and the concentration of specific metabolic compounds was investigated using an artificial neural network (ANN). The artificial neural network was composed of an input layer, one hidden layer, and an output layer, with a hyperbolic tangent sigmoidal transfer function in the hidden layer and a linear transfer function in the output layer. Good prediction was found as measured by a regression coefficient (R2 = 0.999) between actual and predicted data.

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Global Lysine Acetylation in Escherichia coli Results from Growth Conditions That Favor Acetate Fermentation

Journal of Bacteriology ◽

10.1128/jb.00768-18 ◽

2019 ◽

Vol 201 (9) ◽

Cited By ~ 6

Author(s):

Birgit Schilling ◽

Nathan Basisty ◽

David G. Christensen ◽

Dylan Sorensen ◽

James S. Orr ◽

...

Keyword(s):

Escherichia Coli ◽

Enzyme Activity ◽

Regulatory Mechanism ◽

Growth Conditions ◽

Lysine Acetylation ◽

Label Free ◽

Content Type ◽

E Coli ◽

Regulatory Mode ◽

Specific Sugar

ABSTRACT Lysine acetylation is thought to provide a mechanism for regulating metabolism in diverse bacteria. Indeed, many studies have shown that the majority of enzymes involved in central metabolism are acetylated and that acetylation can alter enzyme activity. However, the details regarding this regulatory mechanism are still unclear, specifically with regard to the signals that induce lysine acetylation. To better understand this global regulatory mechanism, we profiled changes in lysine acetylation during growth of Escherichia coli on the hexose glucose or the pentose xylose at both high and low sugar concentrations using label-free mass spectrometry. The goal was to see whether lysine acetylation differed during growth on these two different sugars. No significant differences, however, were observed. Rather, the initial sugar concentration was the principal factor governing changes in lysine acetylation, with higher sugar concentrations causing more acetylation. These results suggest that acetylation does not target specific metabolic pathways but rather simply targets accessible lysines, which may or may not alter enzyme activity. They further suggest that lysine acetylation principally results from conditions that favor accumulation of acetyl phosphate, the principal acetate donor in E. coli. IMPORTANCE Bacteria alter their metabolism in response to nutrient availability, growth conditions, and environmental stresses using a number of different mechanisms. One is lysine acetylation, a posttranslational modification known to target many metabolic enzymes. However, little is known about this regulatory mode. We investigated the factors inducing changes in lysine acetylation by comparing growth on glucose and xylose. We found that the specific sugar used for growth did not alter the pattern of acetylation; rather, the amount of sugar did, with more sugar causing more acetylation. These results imply that lysine acetylation is a global regulatory mechanism that is responsive not to the specific carbon source per se but rather to the accumulation of downstream metabolites.

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