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Biofilms help unravel health enigma

Since biofilms contribute to disease and are difficult to treat, understanding them and their formation could lie at the heart of better treatment (1). In a preprint article, Holden and colleagues (2) have identified changes in gene expression during biofilm formation of the bacterium Escherichia coli, providing valuable insight into this process.

Bacterial cells tend to attach to surfaces and form three-dimensional aggregations, known as biofilms, rather than floating as single, planktonic, cells (3). In this way bacterial cells confer considerable resistance to antibiotics, one reason being that the biofilm hinders antibiotics from effectively reaching the bacterial cells (3). Needless to say, this poses a problem when trying to treat such bacterial infections. Biofilms can form on almost any surface, including biomedical implants and catheters, and are associated with a number of diseases, such as infections of the heart and gum, as well as chronic airway infections in cystic fibrosis patients 4). 

Having a greater understanding of biofilm formation could contribute to better treatment and better patient outcomes (1).

Looking into how gene expression changes during biofilm formation is interesting because genes encode proteins. Proteins make up the building blocks of each cell and carry out many of the cell’s functions (5). In this way, a change in gene expression could lead to a change in protein expression which could, in turn, affect the cell (5). By better understanding gene expression in biofilms, we might start to better understand, for instance, how they can effectively withstand many antibiotic treatments (1).

Previous studies have already shown the importance of certain genes in biofilms (1). In recent years, these are often identified using high throughput methods, which allow the testing of high quantities of sample in a short time span (6,7). A commonly used format is the microtiter dish array, which is a plate that can take 96, 384 or even 1536 or more samples at once (6,7). However, biofilms grown in microtiter dish arrays do not fully mature (7). The composition and development of biofilms, as well as their relationship with disease have also been researched (3). A deeper understanding of biofilm formation can be reached by looking into gene expression over time of a developing biofilm, as Holden and colleagues have done (2).

They did so with a high throughput system called TraDIS-Xpress, of which the workflow is visualised by steps 1 to 5 in Figure 1. Pieces of DNA, known as transposons, are inserted into the bacterial genome; this disrupts the gene and results in a mutant cell. Repeating this for other genes generates an array of different mutant cells, known as a mutant library, in which each cell has a different non-functional gene. The cells are then grown either as single floating, planktonic cells or as a biofilm. The DNA from the cells is extracted at set timepoints, in this case 12, 24 and 48 hours, and is amplified and sequenced. The sequenced reads are mapped back onto a reference genome to determine where they came from in the bacterial genome. By looking at how many reads are recorded for each location on the genome, an estimate can be made of how many mutant cells are present in either planktonic or biofilm condition. In practise, this means that if there are no reads for a mutant in the biofilm condition, but there are reads for that mutant in planktonic condition, that gene is necessary for biofilm formation. 

Using TraDIS-Xpress, the researchers identified 48 genes important in biofilm formation of E. coli, of which six had predicted negative effects on the biofilm and its development. Also, six genes not yet associated with biofilm formation were shown to be involved: two DNA housekeeping genes, which encode proteins that are important for cells to live and be healthy (8), two genes involved in cell division and two with unknown functions. Moreover, they identified a number of genes whose effects depended on the stage of the biofilm.

Once Holden and colleagues identified genes of interest that they predicted to be involved in biofilm formation, they did what’s called ‘phenotypic validation’. They used cells from an established collection of mutants, known as the Keio collection (9), whereby in each cell a gene of interest is deleted. By growing these in planktonic and biofilm conditions, they then looked for observable features, known as the phenotype (Fig. 1 steps 6 and 7). The four features they looked into are: the biomass of the biofilm, the production of the protein curli, the extent of cell aggregation, and the ability of cells to adhere. Curli are produced by intestinal-residing bacteria like E. coli, and are fibres of protein that are part of the network surrounding the cells in the biofilm, known as the extracellular polymeric substance (EPS) (10). The EPS makes up the majority of the biomass of the biofilm. Curli enable the biofilm to be three-dimensional and confer considerable resistance to degrading substances (10). Another important part of the EPS is DNA that exists outside of a cell (extracellular DNA) which appears to contribute to biomass and adhesion (2,10).

The researchers confirmed the involvement of three important features of bacterial cells for biofilm formation: adhesion to the surface, ability to move (motility) and the production of matrix. The importance of these features was dependent on the developmental stage of the biofilm. For instance, in early biofilms of 12 hours, adhesion plays the largest role, at 24 hours, adhesion and matrix production, and for mature 48 hour biofilms the most important feature is matrix production. Motility was found to be necessary throughout the process, not just in the early phase, but is also inversely associated with curli production. The researchers suggested regulation is key as both motility and curli production are considered important. Guttenplan and Kearns (11) suggested that motility is needed at early biofilm stages when finding a surface, but is then inhibited while curli synthesis is activated. Once mature, curli synthesis could be decreased so motility can start up again so cells from the biofilm can be released and dispersed to form new biofilms elsewhere.

An example of genes affecting the biofilm differently depending on when they are expressed are dsbA and dksA. dsbA is necessary in early biofilms, likely involved in adhesion. However, the biofilm at 48 hours was improved when dsbA was deleted, with better aggregation and more curli synthesis. On the other hand, deletion of dksA was better for early biofilms, but in mature biofilms the biomass was decreased and there was less curli synthesis and aggregation when dksA was deleted. So, for bacteria to form a better biofilm, they need to control their gene expression at different phases (2).

TraDIS-Xpress is a promising technique that could help advance our understanding of gene expression in complex systems such as biofilms, but also, for instance, the workings of antibiotics and antifungals as Yasir and colleagues have done previously (12). Efficacy of TraDIS-Xpress was validated by identifying certain genes and pathways that were also identified in other studies on biofilms. By comparing the TraDIS-Xpress data with mutant phenotypes from the Keio collection, Holden and colleagues further improved the reliability of their data. For some genes the data did not match up, such as truA: when mutated, TraDIS-Xpress data showed this gene had few reads in the biofilm compared to planktonic condition, meaning that truA-mutated cells were less present in the biofilm, thus indicating their importance in biofilms. However, when looking at features such as biofilm biomass and curli production there were no changes when this gene was deleted. In such cases the researchers speculated the gene does indeed play a role, but the precise workings of it are yet to be explained. Future research suggested by Holden and colleagues includes combining gene expression information over time with spatial information, as well as studying other species and on different surfaces to help fill in the gaps.

All in all, this study utilises an exciting new technique to further our understanding of the unravelling world of biofilm formation over time. Holden and colleagues confirmed the involvement of previously identified genes and pathways, identified six genes not previously associated with biofilm formation and showed the importance of gene regulation during the development. TraDIS-Xpress has the potential to be used in a variety of settings as a high throughput technique to identify genes of interest for further research. Armed with a better understanding of biofilms, more effective treatments for those affected are hopefully on the horizon.

Figure 1 Workflow of Holden and colleagues’ (2) research. Steps 1-5: TraDIS-Xpress is used as a high throughput method to identify genes of interest that are predicted to be involved in biofilm formation. Steps 6+7: These genes are subsequently validated using mutants from the Keio collection.


1.         Hall CW, Mah T-F. Molecular mechanisms of biofilm-based antibiotic resistance and tolerance in pathogenic bacteria. FEMS Microbiol Rev. 2017;41(3):276–301. Available from: doi:10.1093/femsre/fux010

2.         Holden ER, Muhammad Y, Turner AK, Wain J, Charles IG, Webber MA. Massively parallel transposon mutagenesis identifies temporally essential genes for biofilm formation in Escherichia coliBiorxiv [Preprint]. 2020; Available from: [Accessed 19th Jan 2021].

3.         Rabin N, Zheng Y, Opoku-Temeng C, Du Y, Bonsu E, Sintim HO. Biofilm formation mechanisms and targets for developing antibiofilm agents. Future Med Chem. 2015;7(4):493–512. Available from: doi:10.4155/fmc.15.6

4.         Pozo JLD. Biofilm-related disease. Expert Rev Anti Infect Ther. 2018;16(1):51–65. Available from: doi:10.1080/14787210.2018.1417036

5.         Alberts B, Johnson A, Lewis J, Morgan D, Raff M, Roberts K, et al. Chapter 3: Proteins. In: Molecular Biology of The Cell. 6th ed. New York: Garland Science; 2015. 

6.         Entzeroth M, Flotow H, Condron P. Overview of High-Throughput Screening. Curr Protoc Pharmacol. 2009;44(1):9.4.1-9.4.27. Available from: doi:10.1002/0471141755.ph0904s44

7.         O’Toole GA. Microtiter Dish Biofilm Formation Assay. J Vis Exp JoVE. 2011;(47):2437. Available from: doi:10.3791/2437

8.         Alberts B, Johnson A, Lewis J, Morgan D, Raff M, Roberts K, et al. Chapter 7: Control of Gene Expression. In: Molecular Biology of The Cell. 6th ed. New York: Garland Science; 2015. 

9.         Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol. 2006;2:2006.0008. Available from: doi:10.1038/msb4100050

10.       Tursi SA, Tükel Ç. Curli-Containing Enteric Biofilms Inside and Out: Matrix Composition, Immune Recognition, and Disease Implications. Microbiol Mol Biol Rev. 2018;82(4):e00028-18. Available from: doi:10.1128/MMBR.00028-18

11.       Guttenplan SB, Kearns DB. Regulation of flagellar motility during biofilm formation. FEMS Microbiol Rev. 2013;37(6):849–71. Available from: doi:10.1111/1574-6976.12018

12.       Yasir M, Turner AK, Bastkowski S, Baker D, Page AJ, Telatin A, et al. TraDIS-Xpress: a high-resolution whole-genome assay identifies novel mechanisms of triclosan action and resistance. Genome Res. 2020;30(2):239–49. Available from: doi:10.1101/gr.254391.119

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Written By

Aisling is an MSc student in Applied Biosciences and Biotechnology at Imperial College London. She completed her BSc at Maastricht University in The Netherlands where she focussed on medical biology.

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