# Spotting method as a high throughput alternative to the conventional spread plating method

Vincent Aranzana-Climent, Laure Prouvensier, Tom Collet, Sandrine Marchand, Nicolas Grégoire, Julien M Buyck

## ► To cite this version:

Vincent Aranzana-Climent, Laure Prouvensier, Tom Collet, Sandrine Marchand, Nicolas Grégoire, et al.. Spotting method as a high throughput alternative to the conventional spread plating method. 34th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID), Apr 2024, Barcelona, Spain. [hal-04575530](https://hal-INRAeS.cdn.s3.eu-france.soclet.com/hal-04575530)

HAL Id: hal-04575530

https://univ-poitiers.hal.science/hal-04575530

Submitted on 15 May 2024

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Distributed under a Creative Commons Attribution 4.0 International License
# Spotting method as a high throughput alternative to the conventional spread plating method

Vincent Aranzana-Climent, Laure Prouvensier, Tom Collet, Sandrine Marchand, Nicolas Grégoire, Julien M Buyck

## ► To cite this version:

Vincent Aranzana-Climent, Laure Prouvensier, Tom Collet, Sandrine Marchand, Nicolas Grégoire, et al.. Spotting method as a high throughput alternative to the conventional spread plating method. 34th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID), Apr 2024, Barcelona, Spain. [hal-04575530](https://hal-04575530v1)

HAL Id: hal-04575530

https://univ-poitiers.hal.science/hal-04575530v1

Submitted on 15 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Spotting method as a high throughput alternative to the conventional spread plating method for bacterial time-kill experiments.

V. Aranzana-Climent¹, L. Prouvensier¹,², T. Collet¹, S. Marchand¹,², N. Grégoire¹,², J.M. Buyck¹

Contact : vincent.aranzana.climent@univ-poitiers.fr

¹Université de Poitiers, INSERM U1070, France

²CHU de Poitiers, Laboratoire de Toxicologie et de Pharmacocinétique, France

## Introduction

*In vitro* time-kill experiments are commonly performed to obtain information about the dynamics of a drug antimicrobial activity. It is however labor intensive due to the conventional spread plating method used to count bacteria. In this work we compare a spotting method with the conventional spread plating method.

## Materials and Methods

<figure><img src="image_2.png" /><figcaption>**Figure 1:** Experimental protocol.</figcaption></figure>

### Correction of colony counts to account for overcrowding

* Colony forming unit counts were converted to bacterial densities after correcting for overcrowding (Figure 2) by the « most probable number » method from Martini *et al.* (1)

* Under this method, for a given measurement, the probability of overcrowding is higher when the number of counted colonies (Figure 3) is close to the maximal number of countable colonies.

### Validation of the spotting method

* To validate the spotting method against the conventional plating method we applied correlated bivariate least square regression developed by Francq and Govaerts (2) on $log_{10}$ transformed bacterial densities after exclusion of measurements below $10^3$ CFU/mL (limit of detection of the spotting method)

### Mathematical methods and software

* Optimization of the likelihood function of the « most probable number » (1) method was performed using the R function optim (3). Correlated bivariate least square regression was performed using the BivRegBLS package (4). Data wrangling and graphing was performed with the tidyverse package (5)

<figure><img src="image_3.png" /><figcaption>**Figure 2:** Illustration of the overcrowding problem.</figcaption></figure>

A. Number of bacteria at time of plating.

B. Number of colonies after incubation

<figure><img src="image_4.png" /><figcaption>**Figure 3:** Illustration of how the maximal number of countable colonies was determined.</figcaption></figure>

A. Conventional plating B. Spotting

## Results

<figure><img src="image_5.png" /><figcaption>**Figure 4:** Bland-Altman plot (n=551).</figcaption></figure>

<table><caption>**Table 1:** Performance of the two plating methods</caption><thead><tr><th></th><th>Conventional plating</th><th>Spotting</th></tr></thead><tbody><tr><td>Number of time-kill per week</td><td>8-12</td><td>48-96</td></tr><tr><td>Mean maximal number of colonies per plating</td><td>675</td><td>7.84</td></tr><tr><td>Limit of detection (CFU/mL)</td><td>4*10<sup>1</sup></td><td>10<sup>3</sup></td></tr><tr><td>Average bias (log<sub>10</sub> CFU/mL)</td><td></td><td>6.6 * 10<sup>-4</sup></td></tr><tr><td>Repeatability standard deviation (log<sub>10</sub> CFU/mL)</td><td>0.105</td><td>0.445</td></tr></tbody></table>

<figure><img src="image_6.png" /><figcaption>**Figure 5:** Typical time-kill results. A. Conventional plating B. Spotting</figcaption></figure>

* As seen in **Table 1** spotting method was accurate but exhibited lower precision than the conventional plating method.

* The accuracy was confirmed over the whole range of measurements as evidenced by the red regression line on **Figure 4**.

* The two measurement methods were considered in agreement when the difference was between -1 and +1 $log_{10}$ CFU/mL (Figure 4 green area). In our experiment they agreed since the 95% prediction interval of the differences (Figure 4 purple lines) lied inside the agreement interval (Figure 4 green area).

* This agreement is qualitatively shown by **Figure 5** where typical time-kill profiles obtained by plating (Figure 5A) and by spotting (Figure 5B) are comparable.

## Conclusion

The spotting method yields bacterial counting results comparable with the conventional plating method while being significantly higher throughput.

## References

1) Martini et al. 10.1101/2023.05.18.541301 3) R Core Team (2023) www.R-project.org 5) Wickham et al. 10.21105/joss.01686

2) Francq and Govaerts, 10.1002/sim.6872 4) Francq et al. 10.1002/sim.8709

<figure><img src="image_7.png" /></figure>

This work was supported by the Agence Nationale de research as part of its "Investissement d'Avenir" research program grant n°ANR-20-PAMR-0010
# Spotting method as a high throughput alternative to the conventional spread plating method for bacterial time-kill experiments.

V. Aranzana-Climent¹, L. Prouvensier¹,², T. Collet¹, S. Marchand¹,², N. Grégoire¹,², J.M. Buyck¹

Contact : vincent.aranzana.climent@univ-poitiers.fr

¹Université de Poitiers, INSERM U1070, France

²CHU de Poitiers, Laboratoire de Toxicologie et de Pharmacocinétique, France

## Introduction

*In vitro* time-kill experiments are commonly performed to obtain information about the dynamics of a drug antimicrobial activity. It is however labor intensive due to the conventional spread plating method used to count bacteria. In this work we compare a spotting method with the conventional spread plating method.

## Materials and Methods

<figure><img src="image_2.png" /><figcaption>**Figure 1:** Experimental protocol.</figcaption></figure>

### Correction of colony counts to account for overcrowding

* Colony forming unit counts were converted to bacterial densities after correcting for overcrowding (Figure 2) by the « most probable number » method from Martini *et al.* (1)

* Under this method, for a given measurement, the probability of overcrowding is higher when the number of counted colonies (Figure 3) is close to the maximal number of countable colonies.

### Validation of the spotting method

* To validate the spotting method against the conventional plating method we applied correlated bivariate least square regression developed by Francq and Govaerts (2) on $log_{10}$ transformed bacterial densities after exclusion of measurements below $10^3$ CFU/mL (limit of detection of the spotting method)

### Mathematical methods and software

* Optimization of the likelihood function of the « most probable number » (1) method was performed using the R function optim (3). Correlated bivariate least square regression was performed using the BivRegBLS package (4). Data wrangling and graphing was performed with the tidyverse package (5)

<figure><img src="image_3.png" /><figcaption>**Figure 2:** Illustration of the overcrowding problem.</figcaption></figure>

A. Number of bacteria at time of plating.

B. Number of colonies after incubation

<figure><img src="image_4.png" /><figcaption>**Figure 3:** Illustration of how the maximal number of countable colonies was determined.</figcaption></figure>

A. Conventional plating B. Spotting

## Results

<figure><img src="image_5.png" /><figcaption>**Figure 4:** Bland-Altman plot (n=551).</figcaption></figure>

<table><caption>**Table 1:** Performance of the two plating methods</caption><thead><tr><th></th><th>Conventional plating</th><th>Spotting</th></tr></thead><tbody><tr><td>Number of time-kill per week</td><td>8-12</td><td>48-96</td></tr><tr><td>Mean maximal number of colonies per plating</td><td>675</td><td>7.84</td></tr><tr><td>Limit of detection (CFU/mL)</td><td>4*10<sup>1</sup></td><td>10<sup>3</sup></td></tr><tr><td>Average bias (log<sub>10</sub> CFU/mL)</td><td></td><td>6.6 * 10<sup>-4</sup></td></tr><tr><td>Repeatability standard deviation (log<sub>10</sub> CFU/mL)</td><td>0.105</td><td>0.445</td></tr></tbody></table>

<figure><img src="image_6.png" /><figcaption>**Figure 5:** Typical time-kill results. A. Conventional plating B. Spotting</figcaption></figure>

* As seen in **Table 1** spotting method was accurate but exhibited lower precision than the conventional plating method.

* The accuracy was confirmed over the whole range of measurements as evidenced by the red regression line on **Figure 4**.

* The two measurement methods were considered in agreement when the difference was between -1 and +1 $log_{10}$ CFU/mL (Figure 4 green area). In our experiment they agreed since the 95% prediction interval of the differences (Figure 4 purple lines) lied inside the agreement interval (Figure 4 green area).

* This agreement is qualitatively shown by **Figure 5** where typical time-kill profiles obtained by plating (Figure 5A) and by spotting (Figure 5B) are comparable.

## Conclusion

The spotting method yields bacterial counting results comparable with the conventional plating method while being significantly higher throughput.

## References

1) Martini et al. 10.1101/2023.05.18.541301 3) R Core Team (2023) www.R-project.org 5) Wickham et al. 10.21105/joss.01686

2) Francq and Govaerts, 10.1002/sim.6872 4) Francq et al. 10.1002/sim.8709

<figure><img src="image_7.png" /></figure>

This work was supported by the Agence Nationale de research as part of its "Investissement d'Avenir" research program grant n°ANR-20-PAMR-0010