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BACTERIA

Update: 2017-01-15 14:55      View:

 

1.     Autofluorescence Quantification of Single Bacteria


Scheme7Introduction

Cellular autofluorescence in the visible region can affect the sensitivity of fluorescence microscopic or flow cytometric assays by interfering with or even precluding the detection of low-level specific fluorescence. On the other side, detection of autofluorescence can provide information for bacterial discrimination and identification. The autofluorescence detected in the green region may have originated from flavins, which comprise a category of molecules that include riboflavin (RF, vitamin B2) and its derivatives flavin adenine dinucleotide (FAD) and flavin mononucleotide (FMN). The oxidized form of flavins all share remarkably similar spectral characteristics with fluorescein isothiocyanate (FITC). Three yellow-green fluorescent Fluospheres beads with different sizes and known fluorescein equivalents were analyzed in parallel with bacterial samples to construct the calibration curve between the mean fluorescence burst area and the FITC equivalents per nanoparticles. Then the burst area distribution histogram of bacterial autofluorescence was converted to the distribution of FITC equivalents per bacterial cell.
 


Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter and green fluorescence (FITC).


Results

 

Figure 1. Detection of three fluorescent nanoparticles with different FITC equivalents.


Figure 2. Bivariate dot plots of autofluorescence burst area versus side scatter burst area for eight different bacteria.

 
 
 
 
 


Discussion

1.      Flow NanoAnalyzer can explicitly detect the autofluorescence of a single bacterium, the green autofluorescence mainly originates from oxidized form of endogenous flavin.
2.      Among the eight bacterial strains tested, it is found that the signal of bacterial autofluorescence is closely related with bacterial size.
3.      Bacterial autofluorescence is quantified in units of FITC equivalents by using fluorescent nanoparticles with known FITC equivalents as the quantitative calibration standards.

 Anal. Chem. 2012, 84, 1526-1532.


 

2.     High-Throughput Single-Cell Analysis of Low Copy Number Protein


Introduction

Single-cell analysis is vital in providing insights into the heterogeneity in molecular content and phenotypic characteristics of complex or clonal cell populations. As many essential proteins and most transcription factors are produced at a low copy number, analytical tools with superior sensitivity to enable the analysis of low abundance proteins in single cells are in high demand. b-galactosidase (b-gal) has been the standard cellular reporter for gene expression in both prokaryotic and eukaryotic cells. Here Flow NanoAnalyzer is used for the development of a high-throughput method for the single-cell analysis of low copy number b-gal proteins. Upon fluorescence staining with a fluorogenic substrate C12FDG, quantitative measurements of the basal and near-basal expression of b-gal in single bacteria is demonstrated. Combined with the quantitative fluorometric assay and the rapid bacterial enumeration, the b-gal expression distribution profile could be converted from arbitrary fluorescence units to protein copy numbers per cell.


Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter and green fluorescence (FITC).


Results

 

Figure 1. Analysis of basal b-gal expression in single bacterial cells.
 

Figure 2. Quantitative analysis of b-gal.
Table 1. Quantification of b-gal  copy numbers expressed in single bacterial cells.

*: Average number of b-gal molecules per cell is determined by the quantitative MUG fluorometric assay integrated with rapid bacterial enumeration on the HSFCM.
**: a and b are the two parameters characterizing the gamma distribution. The mean (n) and standard deviation (s ) of the protein number distribution are calculated from a and b.
 


Discussion

1.      Built upon the sensitivity and speed of the instrument and the good cell retention of the hydrolysis products of C12FDG, b-gal is detected at single bacterial cell level.
2.      Combining with the quantitative MUG fluorometric assay and the rapid bacterial enumeration on the instrument, the distribution profile of b-gal expression is quantified in protein copy numbers per cell.
3.      In addition to the b-gal gene reporter, fluorescent proteins or tetracysteine tags that can be genetically fused with the target protein would further expand the scope of the instrument in the investigation of low abundance gene expression and regulation.

Biosens. Bioelectron. 2013, 48, 49-56.


 

3.     Rapid Detection of Resistant Bacteria Based on b-lactamase Activity


Introduction

Bacterial resistance to antibiotics poses a great clinical challenge in fighting serious infectious diseases due to complicated resistant mechanisms and time-consuming test methods. Among many molecular mechanisms that confer antibiotic resistance, production of b-lactamase that catalyze the hydrolysis of b-lactam antibiotics is a major and threatening mechanism. On the other hand, it has been reported that individuals could be simultaneously infected with multiple strains of different susceptibility levels. Traditional detection method cannot detect minority population of antibiotic-resistant bacteria. Advanced tools are urgently needed to quickly diagnose antibiotic-resistant infections to initiate appropriate treatment. The hydrolyzed probes LBRL1 could attach the enzyme, b-lactamase, and thus facilitated the covalent labeling of drug resistant bacterial strains. Moreover, this b-lactamase-induced covalent labeling provides quantitative analysis of the resistant bacterial population (down to 5%) by Flow NanoAnalyzer.


Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter and green fluorescence (FITC).


Results

 

Figure 1. Analysis of bacteria resistance in single gram negative bacterial cell. (Bacteria are labeled with LBRL1, E. coli JM109 (green), E. coli JM109/pUC19 (red), inhibitor treated E. coli JM109/pUC19 (blue))

Figure 2. Analysis of bacteria resistance in single gram positive bacterial cell. (Unlabeled B. cereus (green), LBRL1 labeled B. cereus (red), inhibitor treated B. cereus (blue))

 
 

Figure 3. Differentiation of resistant E. coli JM109/pUC19 cells in bacterial mixtures.
 
 


Discussion

1.      Flow NanoAnalyzer allows rapid single-cell detection and quantitative observation of the resistant bacterial population (down to 5%) through fluorescent probe LBRL1.
2.      This approach offers great opportunity for the in-depth understanding of the biological basis conferring drug resistance, and for the development of effective diagnostic approaches.
 

Chem. Eur. J. 2013, 19, 10903-10910.


 

4.     Clinical Diagnosis of Bacterial Infection and Resistance


 

Introduction

It has been reported that individuals could be simultaneously infected with multiple strains of different susceptibility levels, and the population of resistant bacteria could be very low. However, if the minority population of resistant bacteria cannot be detected in time, an inappropriate prescription of antibiotics is usually a result. Therefore, detection minority population of antibiotic-resistant bacteria is very important for clinical diagnosis. Employing monoclonal antibody against TEM-1 b-lactamase and Alexa Fluor 488-conjugated secondary antibody to selectively label resistant bacteria green, and nucleic acid dye SYTO 62 to stain all the bacteria, Flow NanoAnalyzer is able to detect and quantify as low as 0.1% of antibiotic-resistant bacteria. Furthermore, this approach is applied to detect antibiotic-resistant infection in clinical urine samples without cultivation, and the bacterial load of susceptible and resistant strains can be faithfully quantified. This method provides a powerful tool for the fundamental studies of antibiotic resistance and holds the potential to provide a rapid and precise guidance in clinical therapies.
 


Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter, green fluorescence (FITC) and red fluorescence (APC).


Results

 
 
 
Figure 1. Track the dynamic population change of antibiotic-resistant bacteria with and without antibiotics.


Figure 2. Analysis of E. coli ATCC 35218 (positive control) and two b-lactamase positive clinical urine samples upon dual fluorescent staining.
 


Discussion

1.      Through fluorescent immunolabeling and nucleic acid staining, detection of minority population of antibiotic-resistant bacteria is achieved.
2.      This method allows real-time track of the dynamic population change of antibiotic-resistant bacteria with and without antibiotics.
3.      Detection of antibiotic-resistant infection in clinical urine samples is achieved without cultivation, and the bacterial load of susceptible and resistant strains is quantified.
4.      This approach offers great promise for clinical investigations and microbiological research.

Biosen. Bioelectron. 2016, 80, 323-330.


 

5.     Detection and Quantification of Total Bacterial Cells in Water and Drink


Introduction

Safe and secure supply of drinking water is an essential requirement for human health. Because many different microbiological contaminants may occur in drinking water and beverages, the total bacterial count represents one of the key parameters for quality assessment. Currently water dispenser is fairly common used, the fluctuation of water quality, especially the bacterial count of the unsealed barreled water has attracted much attention. The cultivation-based heterotrophic plate count (HPC) has long become a firmly established tool for the assessment of water quality, but it is labor-intensive, time-consuming, and of limited usage in certain circumstances. On the other hand, bacteria that are in a state of very low metabolic activity, such as those viable but non-cultivable (VBNC) bacteria, can be overlooked by HPC. Employing nucleic acid dye PicoGreen to label the particles in water, particles show burst traces in both side scatter and fluorescent channels simultaneously are recognized as bacteria. Compared with HPC, Flow NanoAnalyzer based approach not only shortens the analysis time, but also reveals the presence of dead and VBNC bacterial cells.
 


Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter and green fluorescence (FITC).


Results

 

Figure 1. Total bacterial quantification of bottled/barreled drinking water.
 

Figure 2. Total bacterial quantification in Jasmine Green Tea drinks.
 
 

Discussion

1.      Combined with PicoGreen nucleic acid fluorescence staining, rapid and accurate quantification of total bacterial in drinking water and tea beverages is achieved, and the results correlate well with conventional HPC method.
2.      Compared to the conventional plate counting assay which is limited to viable and culturable bacteria, Flow NanoAnalyzer can also detect dead and VBNC cells, which reflects more accurately the total bacteria concentration in water samples.
3.      It is expected that this instrument can be applied to monitor various processes in drinking water, diary, beer, and wine production, and wastewater treatment.
 

Anal. Methods 2015, 7, 3072-3079.


 

6.     Absolute and Simultaneous Quantification of Specific Pathogenic Strain and Total Bacterial Cells


Introduction

Detection Principle-finalIdentification and quantification of infectious disease agents is important for medical diagnosis, public health, food safety, environment monitoring, and antibioterrorism. However, traditional culture-based methods are laborious, time-consuming, and only suitable for viable and cultivable cells. Though flow cytometry is emerging as one of the best choices for microbe quantification, its applications to bacteria detection are frequently hindered by bacteria’s small sizes and consequently the low contents of specific cellular constituents. Here Alexa Fluor 647-R-PE is used as the fluorescent probe for the monoclonal antibody of pathogenic E. coli O157:H7, the green fluorophore SYTO 9 is used to stain all the bacterial cells. Double-stained E. coli O157:H7, can be specifically identified and enumerated using two-color fluorescence coincidence detection, while non-pathogenic bacteria can be quantified by green fluorescence detection.
 

Instrument configuration

The Flow NanoAnalyzer is equipped with a 488 nm CW laser, and the detection channels are side scatter, green fluorescence (FITC) and red fluorescence (APC).


Results

 

Figure 1. Analysis of a double-stained mixture with the percentage of E. coli O157:H7/total bacterial cells of 51/100.


 


Discussion

1.     By integrating with antigen and nucleic acid double fluorescence staining, a sensitive approach for the rapid, absolute, and simultaneous quantification of specific pathogenic strain and total bacteria cells in mixture is developed.
2.     For a bacterial cell mixture, this approach can specifically identify the pathogenic bacteria and simultaneously quantify both pathogenic and total bacteria cells accurately.
3.     By using selective antibodies to other pathogens, the Flow NanoAnalyzer holds potential for rapid detection of a wide variety of pathogenic bacteria in biomedical and biotechnological areas.

Anal. Chem. 2010, 82, 1109-1116.