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Detection of host-bacterial pathogen interactions based on phenotypic adherence using high-throughput fluorescence labeling imaging along with automated statistical analysis methods enables rapid evaluation of potential bacterial interactions with host cells.
Identification of emerging bacterial pathogens is critical for human health and security. Bacterial adherence to host cells is an essential step in bacterial infections and constitutes a hallmark of potential threat. Therefore, examining the adherence of bacteria to host cells can be used as a component of bacterial threat assessment. A standard method for enumerating bacterial adherence to host cells is to co-incubate bacteria with host cells, harvest the adherent bacteria, plate the harvested cells on solid media, and then count the resultant colony forming units (CFU). Alternatively, bacterial adherence to host cells can be evaluated using immunofluorescence microscopy-based approaches. However, conventional strategies for implementing these approaches are time-consuming and inefficient. Here, a recently developed automated fluorescence microscopy-based imaging method is described. When combined with high-throughput image processing and statistical analysis, the method enables rapid quantification of bacteria that adhere to host cells. Two bacterial species, Gram-negative Pseudomonas aeruginosa and Gram-positive Listeria monocytogenes and corresponding negative controls, were tested to demonstrate the protocol. The results show that this approach rapidly and accurately enumerates adherent bacteria and significantly reduces experimental workloads and timelines.
Bacterial adhesion is a process whereby bacteria attach to other cells or surfaces. Successful establishment of infection by bacterial pathogens requires adhesion to host cells, colonization of tissues, and in some cases, invasion of host cells1,2,3. Emerging infectious diseases constitute major public health threats, as evidenced by the recent COVID-19 pandemic4,5,6. Importantly, new or emerging pathogens may not be readily discerned using genomic-based approaches, especially in cases where the pathogen has been engineered to evade detection or does not contain genomic signatures that identify it as pathogenic. Therefore, the identification of potential pathogens using methods that directly assess hallmarks of pathogenicity, like bacterial adherence to host cells, can play a critical role in pathogen identification.
Bacterial adherence to host cells has been used to evaluate mechanisms of bacterial pathogenesis for decades1,7. Microscopic imaging8,9 and the enumeration of bacterial colony-forming unit (CFU)10,11,12,13 by post-infection plating are two well-developed laboratory methods for testing microbial adherence and/or infection of host cells14. Considering the micrometer scale size of bacterial cells, the enumeration of the adherent bacterial cells generally requires the use of advanced high-magnification microscopy techniques, as well as high-resolution imaging approaches, including electron microscopy, expansion microscopy (ExM)15,16, and three-dimensional imaging17. Alternatively, the enumeration of bacteria bound to or internalized within host cells can be performed by plating the dilution series of harvested bacteria on solid agar and counting the resultant CFUs10,12,13. This method is laborious and includes many manual steps, which introduces difficulties in establishing a standardized or automated procedure required for high-throughput analyses18,19. Therefore, the development of new methods for evaluating host cell attachment would address current limitations in the field.
One such method is described here that uses automated high throughput microscopy, combined with high throughput image processing and statistical analysis. To demonstrate the approach, experiments with several bacterial pathogens were performed, including Pseudomonas aeruginosa, an opportunistic Gram-negative bacterial pathogen of humans, animals, and plants14,20, which is frequently found to colonize the respiratory tract of patients with impaired host defense functions. This approach optimized the microscopic imaging process described in previous studies14,20. The imaging detection was simplified by fluorescence-labeled host cells and bacteria to rapidly track the proximity of them, which dramatically reduced the microscopy workload to get high-resolution images for distinguishing bacteria. In addition, the automated statistical analysis of images in counting host cells and bacteria replaced the hand-on experiment of bacterial CFU plating to estimate the ratio of adherent bacterial counts per host cell. To confirm the compatibility of this method, multiple bacterial strains and host cell types have also been tested, like Listeria monocytogenes, Staphylococcus aureus, Bacillus cereus, and Klebsiella pneumoniae, as well as human umbilical vein endothelial cells (HUVECs), and the results support the diversity and effectiveness of the method.
1. A549 cell culture
2. Bacterial growth and staining
3. Bacterial adherence and host cell staining
4. Automated fluorescence imaging, processing, and analysis
To develop the fluorescence imaging-based bacterial adherence assay, P. aeruginosa strain PAO1 and its negative-adherence counterpart E. coli were used to test the protocol effectiveness, as the adherence of these bacteria to A549 cells had been reported14,20,22. First, GFP- labeled P. aeruginosa (PAO1) and GFP-labeled E. coli were co-incubated with a human immortalized epithelial cell line A5...
The protocol describes an automated approach for enumerating bacterial attachment to host cells. The described approach has several attractive advantages over conventional methods. First, this approach enables the precise quantification of the number of microbial pathogen cells that are attached to individual host cells. Importantly, this quantification can be performed without the need for laborious bacterial harvesting, serial dilutions, plating on solid media, and determination of CFUs10,<...
All authors have no conflicts of interest to disclose.
We are thankful to Dr. Kaite Zlotkowski of Biotek Inc. for their technical support. We also thank Dr. Lori Burrows, McMaster University, for the generous gift of the Pseudomonas strains.This work was supported by the Department of Defense under contract number W911NF1920013 to PdF; the Defense Advanced Research Projects Agency (DARPA) and the Department of Interior under Contract No. 140D6319C0029 to PdF. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Name | Company | Catalog Number | Comments |
10x PBS | VWR | 45001-130 | |
4′,6-diamidino-2-phenylindole (DAPI) | Thermo Fisher | 62248 | Host cell staining dye |
96 well plate | Corning | 3882 | Half area well, flat clear bottom |
A549 cells | ATCC | CCL 185 | Mammalian cell line |
BactoView Live Red | Biotium | 40101 | Bacteria staning dye |
Centrifuge | Eppendorf | 5810R | |
CFSE cell division tracker | BioLegend | 423801 | |
Cytation 5 | BioTek | Cytation 5 | Cell imaging multi-mode reader |
E. coli | Laboratory stock | ||
EGM bulletKit | Lonza | CC-3124 | HUVEC cell culture medium |
EHEC | NIST collections | ||
F-12k medium | ATCC | 302004 | A549 cell culture medium |
Fetal bovine serum | Corning | 35-016-CV | |
HUVEC | Laboratory stock | ||
L. monocytogenes | NIST collections | ||
OD600 DiluPhotometer | IMPLEN | ||
P. aeruginosa | Dr. Lori Burrows laboratory stock | ||
P. aeruginosa ΔpilA | Dr. Lori Burrows laboratory stock | ||
S. agalactiae | NIST collections | ||
S. aureus | BEI | NR-46543 | |
S. aureus ΔsaeR | BEI | NR-48164 | |
S. rubidaea | NIST collections | ||
Typical soy broth | Growcells | MBPE-4040 |
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