Comparison of different quantitative biofilm assays
Biofilms are defined as sessile communities of bacteria that form on surfaces and are entrapped in a matrix that they themselves produce. Biofilms cause severe problems in many natural (Ferris et al., 1989; Nyholm et al., 2002), clinical (Nicolle, 2005; Rice, 2006), and industrial settings (Brink et al., 1994; McLean et al., 2001; Wood et al., 2006), while being beneficial for waste water treatment and biofuel production (Wang and Chen, 2009). In addition, the bioremediation of crude oil spills involves a biofilm of oil degrading microbes, potentially supplemented by marine flagellates and ciliates (Gertler et al., 2010). Identifying the environmental conditions that prevent or support biofilm formation, as well as understanding the regulatory pathways that signal these conditions, is a pre-requisite to both, the solving of biofilm-associated problems and the use for beneficial purposes. In a previous study by our laboratory (Prüβ et al., 2010), it was determined that nutrition ranked among the more important environmental factors affecting biofilm-associated biomass in
The global regulators included in our previous study (Prüβ et al., 2010) are involved in the co-ordinate expression and synthesis of biofilm-associated cell surface organelles. Many of them are components of two-component systems (2CSTS), each consisting of a histidine kinase and a response regulator (for reviews on 2CSTS signaling, please, see Galperin, 2004; Parkinson, 1993; West & Stock, 2001). In response to an environmental stimulus, the sensor kinase uses ATP as a phosphodonor to auto-phosphorylate at a conserved histidine, then transferring the phosphate to the response regulator at a conserved aspartate residue. In addition, many response regulators can be phosphorylated in a kinase independent manner by the activated acetate intermediate acetyl phosphate (for a review on acetyl phosphate as a signaling molecule, please, see Wolfe, 2005). One 2CSTS that is involved in the formation of biofilms is EnvZ/OmpR, regulating the synthesis of flagella (Shin and Park, 1995), type I fimbriae (Oshima et al., 2002), and curli (Jubelin et al., 2005). RcsCDB is involved in the formation of biofilms, serving as an activator of colanic acid production (Gottesman et al., 1985). RcsCDB constitutes a rare phosphorelay, consisting of three proteins and four signaling domains (Appleby et al., 1996). Much of the effect of EnvZ/OmpR, and RcsCDB upon biofilm formation involves FlhD/FlhC (Prüβ et al., 2006), which was initially described as a flagella master regulator (Bartlett et al., 1988) and later recognized as a global regulator of bacterial gene expression (Prüβ & Matsumura, 1996; Prüβ et al., 2001, 2003).
An early review article (Prüβ et al., 2006) summarized the portion of the transcriptional network of regulation that centered around FlhD/FlhC. This partial network contained 16 global regulators, among them many 2CSTSs, such as EnvZ/OmpR, RcsCDB, and CpxR. The regulation of approximately 800 genes was affected by the network. Since many of these encoded components of the biofilm-associated cell surface organelles, it was hypothesized that the network may affect biofilm formation. This hypothesis was confirmed by the high-throughput study that led to the identification of nutrition as one of the more instrumental factors in determining biofilm biomass (Prüβ et al., 2010). The global regulators that were part of the network led to the mutant collection for the experiment. Among the tested environmental conditions were temperature, nutrition, inoculation density, and incubation time. Temperature and nutrition were more important in determining biofilm biomass than were inoculation density and incubation time. The mutant screen was consistent with the idea that acetate metabolism may act as a nutritional sensor, relaying information about the environment to the development of biofilms. This hypothesis was confirmed by scanning electron microscopy. A new 2CSTS, DcuS/DcuR, was identified as important in determining the amount of biofilm-associated biomass (Prüβ et al., 2010).
The high-throughput experiment merely determined that nutrient rich bacterial growth media are more supportive of biofilm formation than are nutrient poor media. Specific nutrients that are supportive or inhibitory to biofilm formation were not determined and are the next logical step. This will be dependent on an assay system that quantifies biofilm biomass in the presence of an array of single nutrients. With this study, we will introduce such a system that quantifies biofilm biomass formed by
The BioLog Phenotype MicroArray (PM) technology has been developed for the determination of bacterial growth phenotypes (Bochner, 2009; Bochner et al., 2001, 2008). The PM technology consists of 96 well plates with 95 single nutrients dried to the base of each of 95 wells (the additional well constitutes the negative control). When used with the tetrazolium dye that is provided by the manufacturer and indicative of respiration, the PM system is used to determine growth of bacterial strains on single nutrients. Since the total system consists of 20 of such plates, the user is enabled to screen growth under close to 2,000 conditions. The plates are designated PM1 through PM20, with PM1 and PM2 containing carbon sources, PM3 containing nitrogen sources, and PM4 containing sulfur and phosphorous sources. The remaining plates can be used to determine the pH range of growth or resistance to antibiotics or other harsh conditions. Liquid growth media are supplied together with the respective plates.
With respect to bacterial growth, PMs have been used in numerous previous studies (Baba et al., 2008; Edwards et al., 2009; Mascher et al., 2007; Mukherjee et al., 2008; Zhou et al., 2003). However, use of this technology for the investigation of biofilms has been limited (Boehm et al., 2009). In
Crystal violet is a non-specific protein dye that stains the bacterial cells and their exopolysaccharide matrix for dead and live bacteria alike. Biofilms are cultivated on 96 well plates and stained with 0.1% crystal violet in H2O. In a second step, crystal violet is solubilized with a mix of ethanol and acetone (80:20) and measured spectrophotometrically (O’Toole et al., 1999; Pratt & Kolter, 1998). The assay was developed as a high-throughput assay that is suitable for robotic instrumentation (Kugel et al., 2009; Stafslien et al., 2006, 2007). ATP (adenosine triphosphate) (Sule et al., 2008, 2009) and XTT (4-nitro-5-sulfophenyl-5-[(phenylamino) carbonyl]-2H-tetrazolium hydroxide) (Cerca et al., 2005) are both assays that quantify the energy metabolism of the bacteria. Therefore, only biomass of live bacteria is considered. ATP is converted by the enzyme luciferase into a bioluminescence signal, XTT is reduced by NADH to an orange colored water-soluble formazan derivative. Similar to crystal violet, fluoro-conjugated lectins quantify the biomass of live and dead bacteria alike (Burton et al., 2006). Lectins are highly-specific carbohydrate binding proteins that have been utilized to quantify different cell wall components, as well as extracellular matrix (Stoitsova et al., 2004)
|Crystal violet||Live and dead cells||Exopolysaccharide||Yes||(Kugel et al., 2009; Stafslien et al., 2006, 2007)|
|ATP||Live cells||Energy (ATP)||Yes||(Sule et al., 2008, 2009)|
|XTT||Live cells||Energy (NADH)||Yes||(Cerca et al., 2005)|
|WGA||Live and dead cells||Lipooligosaccharide||Not tested||(Burton et al., 2006; Stoitsova et al., 2004)|
|SBA||Live and dead cells||Colanic acid||Not tested||(Burton et al., 2006; Stoitsova et al., 2004)|
In the past, ATP has been used as a measure of biomass (Monzón et al., 2001; Romanova et al., 2007; Takahashi et al., 2007) because its concentration is relatively constant across many growth conditions (Schneider & Gourse, 2004). For the quantification of biofilms, the BacTiter GloTM assay from Promega (Madison WI) has been used for biomass determination in
The protocol involves the formation of the biofilms on 96 well micro titer plates, incubation at the desired temperature, and washing of the biofilms with phosphate buffered saline (PBS). Special attention is needed to distinguish the pellicle that forms at the air-liquid interface from the biofilm that forms at the bottom of the wells. In particular, the AJW678 derivatives that we are working with form a solid pellicle that covers the entire surface of the culture (Wolfe et al., 2003). For users who like to include the pellicle into their study, the growth medium and the PBS will be pipetted off carefully from each well. Users who wish to discard of the pellicle can flip the entire 96 well plate over and remove the liquid this way. Eventually, 100 µl of BacTiter Glo reagent are added to each well. After 5 min of incubation, bioluminescence is measured.
For this study, we will use the ATP assay to quantify biofilm biomass that forms on the PM1 plate of BioLog’s PM system. The PM1 plate contains 95 single carbon sources in addition to the negative control. Besides the fact that the use of PM technology for the determination of the nutritional requirements of biofilm has not been reported in
2. Materials and methods
2.1. Bacterial strains and growth conditions
The bacterial strains used in this study were the
|AJW678||(Kumari et al., 2000)|
|BP1094||AJW678 ||(Prüß et al., 2010)|
|AJW2145||AJW678 ||(Wolfe et al., 2003)|
|AJW2063||AJW678 Δ||(Wolfe et al., 2003)|
|AJW2061||AJW678 ||(Wolfe et al., 2003)|
2.2. Strain selection for the biofilm experiment
For this study, a mutation was needed that would abolish one of the early cell surface organelles that contribute to the biofilm, while still permitting the formation of biofilms. We performed scanning electron microscopy (SEM) to determine the ability of the five bacterial strains (parental strain,
2.3. Biofilm quantification with PM technology and the ATP assay
We used the PM1 plate of the BioLog PM system that contains 95 single carbon sources. When used with the tetrazolium dye that is provided by the manufacturer and indicative of respiration (Bochner et al., 2001), the PM system can be used for measuring growth of bacterial strains on single nutrients. We here describe a protocol for the determination of biofilm amounts (Figure 2).
As recommended by the manufacturer for the determination of growth phenotypes, the bacterial cultures were streaked from LB plates onto R2A plates (to deplete nutrient stores) and incubated at 37C for 48 hours. Bacteria were removed from the plates with a flocked swab (Copan, Murrieta CA), resuspended and then further diluted with IF-0a GN/GP Base (BioLog, Hayward CA) inoculation fluid to an optical density (OD600) of 0.1. Leucine, methionine, threonine and thiamine were added at a final concentration of 20 μg/ml, the redox dye that is used for the determination of growth phenotypes was omitted for biofilm quantification. 100 μl of the inoculum was then dispensed into each of the 96 wells of the PM1 plates. The inoculated plates were wrapped with parafilm to minimize evaporation and incubated at 37C for 48 hours. Biofilm amounts were quantified using the previously described ATP based technique (Sule et al., 2008, 2009). Briefly, the growth medium was carefully aspirated out of each well, minimizing loss of biofilm at the air liquid interface. The biofilms were then washed twice with phosphate buffered saline (PBS) in order to remove any residual media components. The biofilms were air dried and quantified using 100 μl BacTiter Glo™ reagent (Promega, Wisconsin, WI). The biofilms were incubated with the reagent for 10 min at room temperature and the bioluminescence was recorded using a TD 20/20 luminometer from Turner Design (Sunnyvale, CA). The bioluminescence was reported as relative lux units (RLU).
The determination of biofilm amounts in the presence of single nutrients was performed four times for each strain. In addition, growth on these carbon sources was determined in three independent replicate experiments, following the protocol that is described for the determination of growth phenotypes and including the redox dye (Bochner et al., 2001). Carbon sources on which both strains grew to an average OD600 of 0.5 or more were selected for the
2.4. Data analysis
Prior to the statistical analysis, the biofilm amounts from each strain were normalized for experiment specific variation; total bioluminescence across each experiment was summed up and the fold variation was calculated, using the lowest experiment as a norm (1 fold). Data points in each experiment were divided by the respective fold variation. The normalized experimental data sets were subjected to two independent types of statistical analysis, all done using SAS software (SAS Institute Inc., 2009). First, we performed Student’s
Performing Duncan’s test on the parent strain, two carbon sources formed groups A and B. Among the remaining carbon sources, we determined those that were structurally related to group A and B carbon sources. This was done after a determination of the respective chemical structures with the Kyoto Encyclopedia of Genes and Genomes (KEGG; Kanehisa & Goto, 2000; KEGG, 2006). Biofilm amounts formed by the
2.5. Metabolic modeling
Metabolic pathways that lead to the degradation of all the carbon sources that are discussed in this study were determined with KEGG. Metabolic intermediates that were common between different pathways were used to construct metabolic maps. Pathways for both strains were combined in Figures 5 and 6.
3.1. Strain selection using electron micrographs
To determine the ability to form biofilm, electron microscopy was performed with the five strains that were listed in Materials and Methods. Figure 3 depicts one representative illustration of the 10 to 15 images that were obtained per bacterial strain. Most of these strains formed biofilm despite mutations affecting cell surface organelles of either reversible (flagella) or irreversible (type I fimbriae) attachment. The sole exception was the
We wanted a strain for the phenotype microarray experiment that was able to form biofilm on complex media, while lacking one of the cell surface organelles. Since the amount of biofilm formed by the
3.2. Biofilm quantification with PM technology and statistical analysis
Biofilms that formed on the PM1 plates were quantified with the ATP assay and compared between the two strains with the
3.2.1. Carbon sources that formed their own duncan’s group for the parent strain
The normalized data set from the parent strain was subjected to Duncan’s multiple range test. According to this test, the two carbon sources that were the best biofilm supporters for the parent
forming its own Duncan group, ribose was the carbon source that supported the smallest amount of biofilm among all carbon sources tested, while still supporting growth. The parent strain also formed good amounts of biofilm on the remaining C6-sugars. Interestingly, the amount of biofilm that formed on maltotriose (trisaccharide of glucose) was roughly three times the amount of biofilm that formed on glucose. The amount of biofilm that formed on maltose (disaccharide of glucose) was about twice the amount that formed on glucose. The C5-sugars xylose and lyxose did not support growth of the parental strain to the cutoff of 0.5 OD600. For all these carbon sources, biofilm amounts formed by the
|Sugar phosphates||Glucose 6-P|
|Sugar acids||D-galacturonic acid|
3.2.2. Carbon source that formed its own duncan’s group for the
The amount of biofilm formed on each carbon source by the
On N-acetyl-D-glucosamine, the
3.3. Metabolic modeling
Metabolic pathways were drawn for the degradation of all those carbon sources that supported amounts of biofilm larger than 1,000 RLU for one of the tested strains. These are carbon sources of the nutrient categories C6-sugars, sugar phosphates, sugar acids, and sugar amines. C6-sugars all have pathways that feed into the Embden-Meyerhof pathway, sugar phosphates are intermediates of this pathway. As shown in Figure 5, mannose, fructose, and N-acetyl D-glucosamine feed into fructose 6-phosphate. Gluconate, glucuronate, galacturonate, and rhamnose feed into glyceraldehyde 3-phosphate. This leads to the production of acetyl-CoA, acetyl phosphate and acetate (Figure 6).
4.1. Development of the combination assay
Altogether, we present an assay that builds upon two previous assays, the PM technology and the ATP assay. Both assays have been used in much different contexts previously. PM plates have been commonly used to discover various bacterial characteristics based on phenotypic changes (Bochner et al., 2008). Studies involving PM plates include the evaluation of the alkaline stress response induced changes in the metabolism of
limited to a study of the ability of
Here we report for the first time a combination of the established ATP assay along with the PM technology to assess nutritional dependence of
4.2. Biological analysis of the data
In the described study, we observed that the FlhD mutants made quantitatively higher amounts of biofilms on numerous carbon sources. Interestingly, the parental strain did not form higher quantities of biofilm than the mutant on any of the tested carbon sources. These observations shed light into the ongoing controversial debate, elucidating the role of motility in biofilm formation. In certain bacterial species including
As a second observation, carbon sources that supported maximal biofilm formation by either strain all fed into glycolysis eventually, and produced actetate. Although the carbon sources that promoted the highest biofilm amounts were different for the two strains, they still were in the same pathway. The previous high-throughput experiment that had pointed towards nutriition as instrumental in determining biofilm associated biomass had also postulated acetate metabolism as one of the key players in biofilm formation (Prüß et al., 2010). Phosphorylation of OmpR and RcsB by the activated acetate intermediate acetyl phosphate (Kenney et al., 1995) and acetylation of RcsB by acetyl-CoA (Thao et al., 2010) have been described in the past. These activated 2CSTS response regulators then affect the expression level of biofilm associated cell surface organelles, such as flagella, type I fimbriae, curli, and capsule (Ferrieres & Clarke, 2003; Francez-Charlot et al., 2003; Oshima et al., 2002; Prüß, 1998; Shin & Park, 1995) (Figure 6). The positive effect on biofilm amounts of carbon sources that lead to the production of acetate can be explained with the combined inhibitory effect of acetyl phosphate and acetyl-CoA on flagella through OmpR and RcsB and the above described disadvantage of flagella and motility during biofilm formation. We however do not state that acetate is the sole controlling mechanism as the complexity of the bacterial system cannot be explained based on a small number of signaling molecules.
The most striking observation obtained from our studies pertains to the pattern of growth and biofilm formation on sugar acids. It was observed that the FlhD mutants grew to lower optical densities on sugar acids, but formed much higher amounts of biofilm as compared to the parental strain. Previous work from the Prüß lab had shown similar defects in growth of
Among the carbon sources that were the least supportive of biofilm formation, the inability of the C5-sugars to support growth and/or biofilm formation was the most striking. Ribose supported growth by the parent strain, but yielded the lowest biofilm amount of all tested carbon sources. The
The inability to grow on lyxose is also consistent with previous observations, where only a mutation in the
In summary, we developed an assay system that quantifies biofilm biomass in the presence of distinct nutrients. The assay enables the user to screen a large number of such nutrients for their effect on biofilm amounts. Examples of metabolic analysis relate back to previous literature, as well as giving raise to new hypotheses. Yielding further evidence for the previous hypothesis that acetate metabolism was important in determining biofilm amounts can serve as a positive control that the assay actually yields data of biological significance. Particularly with respect to life in the intestine and the production of biofuels, the data open new avenues of research by providing testable hypotheses. Overall, there is no limit to extensions of the assay into different bacterial species or serving the development of high-throughput data mining algorithms that will computerize the statistic/metabolic analysis that we started in this study.
The authors like to thank Dr. Alan J. Wolfe (Loyola University Chicago, Maywood IL) for providing the bacterial strains that were used for this study, Dr. Jayma Moore (Electron Microscopy Lab, NDSU) for help with the scanning electron microscopy, Dr. Barry Bochner (BioLog, Hayward CA) for helpful discussions during the development of the combination assay, and Curt Doetkott (Department of Statistics, NDSU) for performing the statistical analyses of our data and helping us with their interpretation. The work was funded by an earmark grant on Agrosecurity: Disease Surveillance and Public Health through USDA/APHIS and the North Dakota State Board of Agricultural Research and Education. Figure 2 was created using Motifolio (Motifolio Inc., Ellicott MD).
Al-Khaldi S. Mossoba M. 2004Gene and bacterial identification using high-throughput technologies: genomics, proteomics, and phenomics.
Appleby J. Parkinson J. Bourret R. 1996Signal transduction via the multi-step phosphorelay: not necessarily a road less traveled.
Baba T. Huan H. Datsenko K. Wanner B. Mori H. 2008The applications of systematic in-frame, single-gene knockout mutant collection of
Badia J. Gimenez R. Baldomá L. Fessner W. Aguilar J. 1991L-lyxose metabolism employs the L-rhamnose pathway in mutant cells of
Balderas-Hernández V. Hernández-Montalvo V. Bolivar F. Gosset G. Martinez A. 2010Adaptive evolution of
Bartlett D. Frantz B. Matsumura P. 1988Flagellar transcriptional activators FlbB and FlaI: gene sequences and 5’ consensus sequences of operons under FlbB and FlaI control.
Bochner B. Gadzinski P. Panomitros E. 2001Phenotype microarrays for high-throughput phenotypic testing and assay of gene function.
Bochner B. Giovannetti L. Viti C. 2008Important discoveries from analysing bacterial phenotypes.
Bochner B. 2009Global phenotypic characterization of bacteria.
Boehm A. Steiner S. Zaehringer F. Casanova A. Hamburger F. Ritz D. Keck W. Ackermann M. Schirmer T. Jenal U. 2009Second messenger signalling governs
Brink D. Vance I. White D. 1994Detection of
Burton E. Yakandawala N. Lo Vetri K. Madhyastha M. 2006A microplate spectrofluorometric assay for bacterial biofilms.
Cerca N. Martins S. Cerca F. Pier G. Oliveira R. Azeredo J. 2005Comparative assessment of antibiotic susceptibility of coagulase-negative staphylococci in biofilm versus planktonic culture as assessed by bacterial enumeration or rapid XTT colorimetry.
Edwards R. Dalebroux Z. Swanson M. 2009
Comparison of carbon nutrients for pathogenic and commensal Fabich A. Jones S. Chowdhury F. Cernosek A. Anderson A. Smalley D. Mc Hargue W. Hightower G. Smith J. Autieri S. Leatham M. Lins J. Allen R. Laux D. Cohen P. Conway T.
Ferrieres L. Clarke D. 2003The RcsC sensor kinase is required for normal biofilm formation in
Ferris F. Schultz S. Witten T. Fyfe W. Beveridge T. 1989Metal interactions with microbial biofilms in acidic and neutral pH environments.
Francez-Charlot A. Laugel B. Van Gemert A. Dubarry N. Wiorowski F. Castanié-Cornet M. Gutierrez C. Cam K. 2003RcsCDB His-Asp phosphorelay system negatively regulates the
Galperin M. 2004Bacterial signal transduction network in a genomic perspective.
Gertler C. Näther D. Gerdts G. Malpass M. Golyshin P. 2010A mesocosm study of the changes in marine flagellate and ciliate communities in a crude oil bioremediation trial.
Gottesman S. Trisler P. Torres-Cabassa A. 1985Regulation of capsular polysaccharide synthesis in
Hanly T. Henson M. 2011Dynamic flux balance modeling of microbial co-cultures for efficient batch fermentation of glucose and xylose mixtures.
Horne S. Mattson K. Prüß B. 2009An
Jubelin G. Vianny A. Beloin C. Ghigo J. Lazzaroni J. Lejeune P. Dorel C. 2005CpxR/OmpR interplay regulates curli gene expression in response to osmolarity in
Junker L. Clardy J. 2007High-throughput screens for small-molecule inhibitors of
Kanehisa M. Goto S. 2000KEGG: kyoto encyclopedia of genes and genomes.
KEGG 2006Kyoto Encyclopedia of Genes and Genomes, KEGG, In:
Kenney L. Bauer M. Silhavy T. 1995Phosphorylation-dependent conformational changes in OmpR, an osmoregulatory DNA-binding protein of
Kugel A. Jarabek L. Daniels J. Vander Wal. L. Ebert S. Jepperson M. Stafslien S. Pieper R. Webster D. Bahr J. Chisholm B. 2009Combinatorial materials research applied to the development of new surface coatings XII: Novel, environmentally friendly antimicrobial coatings derived from biocide-functional acrylic polyols and isocyanates.
Kumari S. Beatty C. Browning D. Busby S. Simel E. Hovel-Miner G. Wolfe A. 2000Regulation of acetyl coenzyme A synthetase in
Leatham M. Stevenson S. Gauger E. Krogfelt K. Lins J. Haddock T. Autieri S. Conway T. Cohen P. 2005Mouse intestine selects non-motile
Malakooti J. 1989Molecular analysis of the
Mascher T. Hachmann A. Helmann J. 2007Regulatory overlap and functional redundancy among
Mc Dermott P. Ciacci-Woolwine F. Snipes J. Mizel S. 2000High-affinity interaction between gram-negative flagellin and a cell surface polypeptide results in human monocyte activation.
Mc Lean R. Cassanto J. Barnes M. Koo J. 2001Bacterial biofilm formation under microgravity conditions.
Monzón M. Oteiza C. Leiva J. Amorena B. 2001Synergy of different antibiotic combinations in biofilms of S
Mukherjee A. Mammel M. Le Clerc J. Cebula T. 2008Altered utilization of N-acetyl-D-galactosamine by
Nicolle L. 2005Catheter-related urinary tract infection.
Nyholm S. Deplancke B. Gaskins H. Apicella M. Mc Fall-Ngai M. 2002Roles of
Oshima T. Aiba H. Masuda Y. Kanaya S. Sugiura M. Wanner B. Mori H. Mizuno T. 2002Transcriptome analysis of all two-component regulatory system mutants of
O’Toole G. Pratt L. Watnick P. Newman D. Weaver V. Kolter R. 1999Genetic approaches to study of biofilms, In:
Parkinson J. 1993Signal transduction schemes of bacteria.
Peekhaus N. Conway T. 1998What’s for dinner?: entner-doudoroff metabolism in
Pratt L. Kolter R. 1998Genetic analysis of
Prüß B. Matsumura P. 1996A regulator of the flagellar regulon of
Prüß B. 1998Acetyl phosphate and the phosphorylation of OmpR are involved in the regulation of the cell division rate in
Prüß B. Liu X. Hendrickson W. Matsumura P. 2001FlhD/FlhC-regulated promoters analyzed by gene array and
Prüß B. Campbell J. Van Dyk T. Zhu C. Kogan Y. Matsumura P. 2003FlhD/FlhC is a regulator of anaerobic respiration and the Entner-Doudoroff pathway through induction of the methyl-accepting chemotaxis protein Aer.
Prüß B. Basemann C. Denton A. Wolfe A. 2006A complex transcription network controls the early stages of biofilm development by
Prüß B. Verma K. Samanta P. Sule P. Kumar S. Wu J. Christianson D. Horne S. Stafslien S. Wolfe A. Denton A. 2010Environmental and genetic factors that contribute to
Rice L. 2006Unmet medical needs in antibacterial therapy.
Romanova N. Gawande P. Brovko L. Griffiths M. 2007Rapid methods to assess sanitizing efficacy of benzalkonium chloride to
Sauer K. Camper A. Ehrlich G. Costerton J. Davies D. 2002
Schneider D. Gourse R. 2004Relationship between growth rate and ATP concentration in
Shin S. Park C. 1995Modulation of flagellar expression in
Stafslien S. Bahr J. Feser J. Weisz J. Chisholm B. Ready T. Boudjouk P. 2006Combinatorial materials research applied to the development of new surface coatings I: a multiwell plate screening method for the high-throughput assessment of bacterial biofilm retention on surfaces.
Stafslien S. Daniels J. Chisholm B. Christianson D. 2007Combinatorial materials research applied to the development of new surface coatings III. Utilisation of a high-throughput multiwell plate screening method to rapidly assess bacterial biofilm retention on antifouling surfaces.
Stoitsova S. Ivanova R. Dimova I. 2004Lectin-binding epitopes at the surface of
Stolyar S. He Q. Joachimiak M. He Z. Yang Z. Borglin S. Joyner D. Huang K. Alm E. Hazen T. Zhou J. Wall J. Arkin A. Stahl D. 2007Response of
Sule P. Wadhawan T. Wolfe A. Prüß B. 2008Use of the BacTiter-GloTM microbial cell viability assay to study bacterial attachment in biofilm formation.
Sule P. Wadhawan T. Carr N. Horne S. Wolfe A. Prüß B. 2009A combination of assays reveals biomass differences in biofilms formed by
Takahashi N. Ishihara K. Kato T. Okuda K. 2007Susceptibility of
Thao S. Chen C. Zhu H. Escalante-Semerena J. 2010Nε-lysine acetylation of a bacterial transcription factor inhibits its DNA-binding activity.
Wang Y. Ding L. Hu Y. Zhang Y. Yang B. Chen S. 2007The
Wang Z. Chen S. 2009Potential of biofilm-based biofuel production.
West A. Stock A. 2001Histidine kinases and response regulator proteins in two-component signaling systems.
Wolfe A. 2005The acetate switch.
Wolfe A. Chang D. Walker J. Seitz-Partridge J. Vidaurri M. Lange C. Prüß B. Henk M. Larkin J. Conway T. 2003Evidence that acetyl phosphate functions as a global signal during biofilm development.
Wood T. Gonzalez Barrios. A. Herzberg M. Lee J. 2006Motility influences biofilm architecture in
Zhou L. Lei X. Bochner B. Wanner B. 2003Phenotype microarray analysis of