Current Detection Methods in Complex Samples: History
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Fany Reffuveille
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Pierre Prada
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Benjamin Brunel
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Sophie Gangloff

Several detection methods of microorganisms are routinely used in industry. The choice of method or combination of methods depends on the characteristics of the medium of interest. Indeed, its composition can physically hinder some methods. Similarly, culture medium and incubation times must be chosen accordingly to promote the growth of specific microorganisms (molds, yeasts, or bacteria). The most commonly used technique for detection of microorganisms in complex biological samples is microbiological growth, either on solid agar plate or in liquid medium, i.e., blood culture, which refers to automated methods based on the growth of microorganisms in liquid media. This historical model tends to be replaced by faster methods.

  • pathogen detection
  • biosensors

1. Methods Based on Growth Monitoring

The following methods need a growth step, either to have a detectable signal or a change in signal due to microorganism growth.

1.1. Measurement of Gas Production

Microorganisms in an active multiplication and metabolism phase can produce or consume gas. One of the possible approaches is to monitor changes in the composition of the gaseous state in closed culture flasks, using pressure transducers that react to the production (e.g., CO2) or to the consumption of a gas (e.g., O2). Blood culture is an example of application of this method and is the reference method for microorganism detection in patient blood samples [1]; it is widely used at the hospital in sepsis diagnosis, but also for all sorts of biomedical culture such as cell therapy products [2]. The blood culture technique only allows to detect the presence or absence of a pathogen through the release of CO2. A false negative can occur if the bottle is not filled with enough medium. The method only works for culturable microorganisms. The detection of viable but non-culturable (VBNC) pathogens [3], as well as non-viable ones, requires a complementary method [4]. While non-viable microorganisms are less hazardous than viable ones, they can be associated with the presence of pathogenic metabolites, toxins, or membrane debris.

1.2. Electrochemical Methods

When microorganisms multiply, their metabolism transforms weakly charged organic nutrients into highly charged ionic metabolites. This process modifies different electrical properties of the culture medium, such as its electrical potential, conductance, capacitance, or impedance. Impedance-based methods are the most numerous, in which an alternative voltage is applied to the medium using two electrodes, and the resulting current is measured. The binding of bacteria to ligands (see Section 3.1) can also be detected through impedance-based measurement as it changes the surface potential of the substrate. For further details, refer the reader to following reviews [5][6].

1.3. Bioluminescence

This method makes use of the luciferase enzyme, which actively emits light and depends on the presence of adenosine triphosphate (ATP). The bioluminescence light is proportional to the amount of ATP and is used as a marker of microorganism viability [7]. By lysing the cells, ATP is released which allows to decrease the limit of detection. This method cannot detect a low level of contamination without an incubation step to increase the number of microorganisms. In addition, filtration is required to distinguish bacterial ATP from any other ATP source.

1.4. Microcalorimetry

Microbial catabolism generates heat that can be measured accurately by microcalorimetry [8]. A minimum number of microorganisms is required to generate thermal measurements above the baseline, which is generally achieved using an enrichment medium.

1.5. Turbidimetry

The more microorganisms there are, the more opaque the medium is. This change in optical density can be measured by a spectrophotometer at a wavelength usually between 420 and 615 nm to detect microorganism growth. This method requires a calibration step to be quantitative. Applied to the monitoring of a cell therapy product, measuring the optical density spectrum allows to distinguish between an increase in optical density due to cell growth or an increase due to contamination [9]. Recent works have also shown the possibility of developing portable systems suitable for in situ measurements [10][11].
To be detectable, these techniques often require the presence of a minimum number of target cells to obtain a measurable signal, which implies enrichment.
The choice of the method is guided by the suspected microorganisms. Indeed, the sensitivity of each method depends on the type of microorganisms, whether they produce gas, heat, or significantly change the electrical impedance or the opacity of the medium. All these methods are only semi-quantitative because the relationship between the measured physical cue (light emission, pressure, heat, and impedance) and the number of microorganisms depend on the type of microorganism and experimental conditions. Therefore, the initial number of microorganisms cannot always be accurately quantified. In addition, the complexity of analytical medium can lead to a bias in the results. As these methods rely on the growth of microorganisms, they are limited to culturable bacteria and the detection time is limited by the growth step, even if considerable improvements have been achieved over the years, with or without labelling as detailed in [12][13].

2. Individual Cells Detection Methods

If single cells can be detected, a growth step is no longer needed, and the detection time can be shorter. This was the improvement step of cytometry applications.

2.1. Solid Phase Cytometry

Microorganisms are trapped on a filter membrane and stained with a fluorophore that only emits light for viable cells. Viable microorganisms are detected by epifluorescence, with a single-cell resolution. Due to this high sensitivity, the usual incubation step is not required. Microbial contaminants can be detected within a few hours, even the viable and non-culturable ones. A wider field of view allows a faster scanning of the membrane [14]. Appropriate software is required to distinguish between viable microorganisms and auto-fluorescent particles. Otherwise, the confusion leads to false positives. The more general version of this method is named direct epifluorescent filtration technique (DEFT), in which other fluorescent dyes can be used (DAPI, CTC, etc.).

2.2. Flow Cytometry

The principle is similar to solid phase cytometry, except microorganisms are in suspension [15]. Using a viability-activated fluorophore, viable and nonviable cells are sorted into different channels from their epifluorescence detection. This method allows fast counting and cells can be characterized by multiple fluorophores simultaneously. The development of more specific or intense fluorescent probes (e.g., quantum dots) has improved the sensitivity and specificity of the method [16]. However, it is not as sensitive as solid phase cytometry and an incubation step in culture medium is often required [17]. This brings the method back to the category of growth-based methods. Moreover, agglomeration of bacteria can be problematic. More details about current developments in flow cytometry can be found in the review published by Zand et al. [16].
In theory, a single cell can be detected, but in practice the signal is weak and can be missed or confused with auto fluorescent particles. The former decreases the sensitivity while the latter decreases the specificity.

3. Cellular Components Detection and Analytical Methods

Instead of detecting cells as a whole, their specific components can be detected by the different methods described below. This specificity improvement allows to distinguish the signal coming from eukaryotic cells, which are part of the ATMP, from the signal coming from microorganisms, which are contaminants.

3.1. Immunological Methods

Microorganisms can be detected or identified by their specific antigens using antibodies. The antibody-antigen reactions can result in agglutination, colorimetric or fluorimetric changes, allowing both qualitative and quantitative detection. A good example is Enzyme-linked immunosorbent assays (ELISA) [18].

3.2. Infrared Spectroscopy

The infrared spectrum of all microorganism components is a specific pattern that can be recognized by comparison with a library of spectra of known species [19]. Detection of microorganisms directly in blood samples is also possible with the latest technical advances currently being developed [20]. For the pattern to match the library, a high degree of standardization is required. Simultaneous identification of multiple microorganisms is possible, but measurements are often not quantitative.

3.3. Mass Spectrometry

By exposing microbial cells to a laser beam in a vacuum, its molecules are ionized and vaporized. Recording the time of flight of the different molecules provides a mass spectrum, distinctive of the species. As for infrared spectroscopy, the mass spectrum can be compared with known spectra for identification [21]. Matrix-assisted laser desorption-ionization time of flight (MALDI-TOF) mass spectroscopy allows for minimal fragmentation during the ionization. A growth phase on agar may be required before the mass spectrum acquisition and the culture conditions must be standardized. The method is destructive but quantitative.

3.4. Nucleic Acid Amplification Techniques

This method consists in detecting the presence or the absence of a specific nucleic acid fragment. The targeted nucleic acid is amplified exponentially by repeating DNA polymerization. The most widely used method is the polymerase chain reaction (PCR), in which a thermostable DNA polymerase copies the fragment using nucleotides primers [22]. The result can be analyzed through DNA sequencing, fragment size analysis in gel electrophoresis, or fluorescent-labelled probes. Depending on the method of analysis chosen, the amplification technique may be qualitative, semi-quantitative, or quantitative. False negatives may occur if inhibitors of the DNA polymerase are present. False positives are also prone to happen because of cross-contamination from background DNA. PCR is a proven and robust technique that is currently widely used for the detection of COVID-19 in particular [23][24].
PCR has been a reference technique in molecular biology for a long time, and a new technique seems promising: isothermal amplification [25][26]. This method seems to be robust and allows to amplify nucleic acids in an exponential way at a constant temperature. Isothermal amplification is a technique adapted to the monitoring of pathogens and in situations of low quantities of DNA [27][28][29]. The researchers can briefly quote different techniques such as: nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP), helicase-dependent amplification (HDA), and recombinase polymerase amplification (RPA).
These methods do not necessarily differentiate between viable and non-viable microorganisms. Contrary to the methods presented in the previous sections, cellular component analysis requires prior knowledge on the microorganisms. Specific antigen, spectral signature, or a DNA fragment must be used to detect the corresponding pathogen. While this is adapted for identification purposes, multiple specific analyses are necessary for broad-spectrum detection. Cultivation of microorganisms is often necessary to obtain a detectable signal.
To conclude on the current detection methods, they are routinely used in laboratories as a valuable tool for controlling biological complex medium and ensuring their microbiological safety. However, most of them are considered as slow, results being delivered only after an incubation time up to several days or with too many preparation steps not in accordance with the final use of the sample. Therefore, conventional microbiological controls rarely allow for proactive corrective action. The culture step is usually needed for reasons of sensitivity of the methods. In complex media, a small number of bacteria is hard to detect because the signal-to-noise ratio is low. Recently, innovative detection methods proposed solutions to this issue.

This entry is adapted from the peer-reviewed paper 10.3390/app12125892

References

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