A previous study postulated that acetate metabolism was a metabolic sensory mechanism that related information about E. coli’s environment to the formation of biofilms (Prüet al., Arch. Microbiol. 2010). Considering that mutants in pta ackA (no acetyl phosphate) and ackA (high acetyl phosphate) exhibited similarly increased biofilm amounts and three dimensional structures, the hypothesis for this study was that acetyl Co-A was a more likely mediator of the acetate effect than acetyl phosphate. The effect of acetate metabolism on biofilm amounts was detailed by using single carbon sources rather than the previously used mixed amino acid medium, as well as mutations in additional genes that contribute to acetate metabolism (ldhA, pflA, pflB). In summary, the mutations in ackA, pta ackA, and ldhA increased biofilm amounts in the presence of maltose, D-trehalose, D-mannose, and L-rhamnose, all of which get converted to acetyl-CoA. The ackA mutant also exhibited increased biofilm amounts in the presence of inosine and thymidine. The mutation in pflA decreased biofilm amounts in the presence of maltotriose, uridine, D-serine, and acetate. Since ackA, pta ackA, and ldhA mutants are expected to exhibit increased intracellular acetyl-CoA levels, and pflA and pflB mutants likely exhibit decreased acetyl-CoA concentrations, we believe that acetyl-CoA is the activated acetate intermediate that controls biofilm amounts.
For many pathogenic bacteria, the formation of biofilms complicates the disease progression and renders bacteria resistant to antibiotics and the human host defense. Biofilms are bacterial communities that form a slime layer on liquid/solid and air/liquid interfaces and are enclosed in a polymeric matrix (Sachs & Hollowell 2012; Petrova & Sauer 2012). Biofilm formation is of public health importance in that they can form on teeth (Zijnge et al. 2010) and medical implants (Mack et al. 2006), within the gastrointestinal tract (Kleessen & Blaut 2005), and on catheters (Saint & Chenoweth 2003). Progression of many bacterial infections from acute to chronic is often associated with biofilms (Aparna et al. 2008). It is estimated that 99% of all bacteria can form biofilms and over 65% of human bacterial infections involve biofilms (Prakash et al. 2003).
In order to develop novel prevention and treatment options that target the biofilm formation process, understanding the underlying physiology and genetics of biofilm formation is imperative, including the precise environmental conditions under which they form. Using Escherichia coli K-12 as a model system, a recent study by Prüß and coworkers (Prüß et al. 2010) ranked temperature and nutrients as more important than the inoculation density and the incubation time, when determining biofilm amounts. Acetate metabolism was hypothesized as a metabolic sensor of the available nutrients. One of the observations that led to this hypothesis was that mutants in ackA (encoding acetate kinase) and pta (encoding phosphotransacetylase) produced larger amounts of biofilm associated biomass, as well as more three-dimensional structures within the biofilm. Neither of these mutants is capable of producing acetate, the ackA mutant accumulates acetyl phosphate, while the pta mutants is unable to produce acetyl phosphate (Prüß & Wolfe 1994). Both mutants accumulate acetyl-CoA. Acetate formation occurs when the flux of carbon exceeds the capabilities of the tricarboxylic acid (TCA) cycle (Holms 1986), it is also considered a fermentation pathway (Kumari et al. 2000). The enzyme reactions for Pta and AckA are given in Illustration 1 (Brown et al. 1977). The hypothesis for this study was that acetyl-CoA is more likely than acetyl phosphate to be the acetate intermediate that affects E. coli biofilm amounts. To test this hypothesis, we distinguished between the effects of pta ackA (no acetyl phosphate synthesis) and ackA (accumulation of acetyl phosphate) mutants on biofilm that was produced on different carbon sources. We then tested the effect of mutations in two other enzymes that affect acetyl-CoA (but not acetyl phosphate) concentrations. These were lactate dehydrogenase (encoded by ldhA) and pyruvate formate lyase (encoded by pflB and activated by PflA). The enzyme reactions for LdhA and PflB are shown in Illustration 2:
We determined the effect of knock out mutations in each of these four enzymes on E. coli biofilm produced in i) mixed amino acid medium, analyzed with scanning electron microscopy and on ii) 95 different single carbon sources, analyzed with Phenotype MicroArray technology (BioLog, Hayward CA). Our data supports the idea that increases in intracellular acetyl-CoA levels will cause increased biofilm amounts. The long-term goal of our research is to identify small molecules that control biofilm formation through acetate metabolism.
Material and Methods
Bacterial strains used for this study were the E. coli K-12 strain AJW678 and several isogenic mutants in genes that contribute to acetate metabolism. AJW678 is characterized by its ability to form biofilm (Kumari et al. 2000). Mutants in ackA, pta ackA, ldhA, pflA, and pflB were isogenic to their AJW678 parent. The ackA::kn strain AJW1939 and the (ackA pta hisJ hisP dhu) zej223-Tn10 strain AJW2013 were described in (Kumari et al. 2000) and (Wolfe et al. 2003), respectively, and kindly provided by Dr. Alan J. Wolfe from Loyola University Chicago (Maywood, IL). They are designated mutants in ackA and pta ackA, respectively, throughout this manuscript. The lhdA::kn, pflA::kn, and pflB::kn mutations were provided through the Coli Genetic Stock Center (CGSC; http://www. cgsc.biology.yale.edu). Mutations were moved into AJW678 using the P1 phage (Silhavy et al. 1984). All bacterial strains were maintained as freezer stocks in 15% glycerol and plated onto Luria Bertani broth agar plates (LB; 1% tryptone, 0.5% NaCl, 1% yeast extract) prior to each experiment.
The AJW678 parent strain had previously been analyzed with Phenotype MicroArrayTM (PM) technology (Prüß et al. 2010). The ackA, pta ackA, ldhA, and pflA mutant strains were analyzed as part of this study. The PM technology from BioLog (Hayward, CA) consists of 96 well plates in which a single nutrient is dried onto the bottom of each well. When used in combination with a tetrazolium dye, respiration can be monitored. This is considered indicative of growth (Bochner 2009; Bochner et al. 2001; Bochner et al. 2008). In combination with the ATP assay, PM technology can be used to determine biofilm biomass (Sule et al. 2011). For this particular study, PM1 plates were used which consist of 95 different carbon sources and a negative control. The bacteria were first grown on R2A agar plates in agreement with recommendations by the manufacturer of the PM technology (BioLog). This was done to deplete nutrient stores. Bacteria were collected with a nylon flocked swab, and then diluted in IF-0a GN/GP base inoculating fluid to a final concentration of 0.1 at an OD600. Threonine, methionine, leucine and thiamine were used as supplements, each at a concentration of 20 ?g/ml to allow growth of the auxotrophic strains. To each well of the plate, 100 ?l of the inoculum solution was added. The plates were wrapped in parafilm and incubated at 37°C for 48 h. Four independent experiments were done per each strain. Bacterial growth on different carbon sources was determined as an optical density (OD600) from a PM1 plate that was inoculated the same way, incubated with the tetrazolium dye, and read with a micro plate reader. Biofilm amounts were analyzed only for carbon sources that permitted growth to at least an OD600 of 0.7. To quantify the biofilm amounts formed by the mutants on the different carbon sources, the BacTiterGloTM assay (Promega, Madison, WI) was used to determine concentrations of ATP which are indicative of bacterial biomass (Sule et al. 2009). In this assay, ATP is converted by the enzyme luciferase into a bioluminescence signal. Briefly, the growth medium from the incubated plate was carefully removed using a multichannel pipette in order to maintain the biofilms that had formed at the bottom of the wells, as well as the pellicles that formed at the air/liquid interface. The plates were washed twice with 100 µl phosphate buffered saline (PBS) and allowed to air dry for 15 minutes. 100 ?l of BacTiter GloTM (Promega) were added to each well. Bioluminescence was measured after 10 min incubation at room temperature with a TD 20-20 bioluminometer from Turner Design (Sunnyvale, CA). Biofilm amounts formed on each well were measured as relative bioluminescence units (RLU).
Analysis of Phenotype MicroArrays:
To account for variations in overall bioluminescence between the four data sets from each strain, data were normalized to the experiment that yielded the lowest bioluminescence across all 95 carbon sources. This was done for each strain separately and prior to any comparisons. Specifically, bioluminescence values (RLU) were added for all the carbon sources from one experiment (one plate). A fold variation was calculated using the smallest of the four replicate experiments as the norm (1 fold). The remaining experiments were normalized to the smallest one. Average and standard deviations were determined for the normalized data sets. Biofilm amounts formed on the different carbon sources by the four tested mutants were compared to those previously determined for AJW678 (Prüß et al. 2010). This was done separately for carbon sources that were previously described as good promoters of biofilm (> 1,300 RLU) and carbon sources that were considered moderately good supporters of biofilm (800 RLU to 1,300 RLU) for the AJW678 parent strain (Prüß et al. 2010). A two sample t-test was performed to determine the statistical significance of the difference between AJW678 and each mutant. This was done for all carbon sources. Differences were considered significant if the p-value was < 0.05.
Scanning Electron Microscopy:
Biofilms produced by the ackA and pta ackA mutants had been compared to their isogenic AJW678 parent strain previously (Prüß et al. 2010). For this study, biofilms were compared between the ldhA, pflA, and pflB mutants and AJW678. Biofilms were prepared for scanning electron microscopy (SEM) as previously described (Sule et al. 2009). Biofilms were grown on 12 mm cover slips (Assistant Germany) in 6 well plates. Briefly, 40 µl of bacteria from an overnight culture were added to each well containing the cover slips and 4 ml of LB. The plate was incubated at 32°C for 48 h in a non-shaking incubator. The medium was removed carefully and the biofilms were washed twice with phosphate buffered saline (PBS). Biofilms on the cover slips were allowed to air dry and fixed with 2 ml of 2.5% glutaralydehyde (Tousimis, Research cooperation Rockville MD) in 0.1 mol/1 phosphate buffer. Biofilms were rinsed in the same buffer and deionized water, then dehydrated using a graded alcohol series (15 minutes each in 30%, 50%, 70%, 90% and two changes of 100% ethanol). Samples were critically point dried in an Autosamdri-810 critical point drier (Tousimis, Rockville MD) with liquid carbon dioxide as transitional fluid. The cover slips were then attached to aluminum mounts with adhesive carbon tabs or silver paint and coated with gold/palladium using a Balzers SCD 030 sputter coater (Balzers Union Ltd., Liechtenstein). Images were obtained with a JEOL JSM-6490LV scanning electron microscope (JEOL Ltd Japan) at 1,000 X, 3,000 X, and 6,500 X magnification. The experiments were repeated at least three times per strain. Between 24 and 27 images were obtained per strain. Representative images were selected.
Mutants in ackA and pta ackA produced increased biofilm amounts on several C6 sugars:
Comparing biofilm amounts of the ackA and pta ackA mutants to AJW678, the most notable difference was a general increase in biofilm amounts across all carbon sources (Illustration 3). In close approximation, the total RLU across all carbon sources was 3 fold higher for the ackA mutant than for its parent strain. Interestingly, maltotriose which had yielded the largest amount of biofilm for AJW678 still yielded about the same RLU for the two mutants. More intriguingly, several C6 sugars gave rise to just about these same 5,000 to 6,000 RLU for both, ackA and pta ackA mutants. These were maltose, D-glucose, D-trehalose, and D-mannose (Panel A). In addition, biofilm amounts on L-rhamnose (Panel B) were also increased for the two mutants, though only to about 3,000 RLU (up from 1,000 RLU for AJW678). The t-test yielded p-values that were higher than the cut off for maltose (0.1) and D-glucose (0.133) for the pta ackA mutant. For both carbon sources, this was due to one outlyer value in the mutant data set. The p-values for D-trehalose, D-mannose, and L-rhamnose were below 0.05 (0.037, 0.0037, and 0.039, respectively). Across most of the carbon sources, biofilm amounts were increased for both, pta ackA (grey bars) and ackA (white bars) mutants. In many cases, biofilm amounts were slightly higher for the pta ackA mutant. The exceptions from this were thymidine and inosine (Panel B). For these two carbon sources, biofilm amounts were higher than for AJW678 only for the ackA mutant. For thymidine, this amounted to a 4 fold increase, relative to AJW678. The p-values from the t-test were 0.048 for thymidine and 0.16 for inosine.
Mutants in pflA produced decreased amounts of biofilm on maltotriose, acetic acid, uridine, and D-serine:
SEM was performed for AJW678, and mutants in ldhA, pflA, and pflB to compare biofilms produced in mixed amino acid medium (Illustration 4). AJW678 and the ldhA mutant formed biofilms that were thick, three dimensionally structured, and almost indistinguishable from one another. It appeared possible, though, that the biofilm that was produced by the ldhA mutant was slightly more densely packed than the AJW678 biofilm. Biofilms produced by both, AJW678 and its isogenic ldhA mutant contained those filamentous structures that were observed on multiple previous occasions (Sule et al. 2009; Sule et al. 2008; Sule et al. 2011). These are of unidentified origin. Biofilm produced by the pflA and pflB mutants looked to be a bit denser than the AJW678 biofilm. It exhibited a ‘cheese cake’ like structure in a sense that it was flat and contained gaps, possibly water channels. This was more pronounced for the pflB mutant. To identify individual carbon sources on which the ldhA and pflA mutants formed biofilm amounts different from AJW678, we performed Phenotype MicroArrays on PM1 plates. Biofilm associated biomass produced by the two mutants was compared to that of AJW678. For the ldhA mutant (grey bars), biofilm biomass was increased relative to AJW678 for all carbon sources (Illustration 5). As seen for the pta ackA and ackA mutants, the sum of the RLU for all carbon sources totaled 3 times as much for the ldhA mutant as for AJW678. In further analogy to the pta ackA and ackA mutants, biofilm amounts formed on maltose, D-trehalose, D-mannose, and L-rhamnose reached levels of biofilms produced on maltotriose. This did not hold true for D-glucose. The highest level of biofilm was seen for the TCA cycle intermediate fumaric acid. The p-values from the t-test for maltose, D-trehalose, D-mannose, L-rhamnose, and fumaric acid were below 0.05 (0.014, 0.025, 0.014, 0.002, and 0.000789, respectively). For the pflA mutant (white bars), the amount of biofilm that formed on maltotriose was reduced by about 50% at a p-value of 0.002. The only other carbon sources that yielded biofilm amounts different from AJW678 for this mutant were acetic acid (Panel A, p-value of 0.004), uridine (Panel A, p-value of 0.015), and D-serine (Panel B, p-value of 0.02). For these three carbon sources, the reduction was approximately three fold.
A previous study had postulated that acetate metabolism was a metabolic sensory mechanism that related information about E. coli’s environment to the formation of biofilms (Prüß et al. 2010). Considering that mutants in pta ackA (no acetyl phosphate) and ackA (high acetyl phosphate) exhibited similarly increased biofilm amounts and three dimensional structures, it was hypothesized that acetyl Co-A was more likely the mediator of this effect than acetyl phosphate (or acetate). In the current study, the effect of acetate metabolism on biofilm amounts was detailed by using single carbon sources rather than the previously used mixed amino acid medium, as well as mutations in additional genes that contribute to acetate metabolism (ldhA, pflA, pflB). The part of central metabolism that summarizes the four enzyme reactions that are investigated in this study is described in Illustration 6. According to this schematic, mutations in ldhA, ackA and pta (with or without the additional mutation in ackA) would all lead to an accumulation of acetyl-CoA. In contrast, knocking out either the pyruvate formate lyase gene pflB or the activator gene pflA would lead to a decrease in intracellular acetyl-CoA levels.
Data presented in this study are in agreement with the idea that the accumulation of acetyl-coA leads to increased biofilm amounts. Mutants in ldhA, ackA, and pta ackA exhibited rather similar patterns of biofilm amounts across the 95 carbon sources tested. In contrast, the profile for the pflA mutant was considerably different. For the ldhA, ackA, and pta ackA mutant, total biofilm amounts (from all 95 carbon sources) were increased by about 3 fold, relative to AWJ678. This was not the case for the pflA mutant. With respect to specific carbon sources, biofilm amounts on D-glucose, maltose, D-mannose, D-fructose, and L-rhamnose were brought up to the level of maltotriose for the ldhA, ackA, and pta ackA mutants. Maltotriose had been the carbon source that gave rise to the largest amount of biofilm in AJW678 previously (Prü? et al., 2010) and now appears to give rise to about the largest amount of biofilm in any strain, while D-glucose, maltose, D-mannose, D-fructose, and L-rhamnose depend upon the accumulation of acetyl-CoA that is provided by the mutations in either ldhA, ackA, or pta ackA in order to support full biofilm amounts. For the pflA mutant, in contrast, biofilm amounts were reduced in the presence of the favored carbon source for AJW678 biofilm, maltotriose. This was also true for acetic acid and D-serine, which are also expected to increase the acetyl-CoA pool.
Since maltotriose supports about three times as much of AJW678 biofilm as glucose (Prü? et al., 2010), the question arises whether the concentrations of carbon sources on the PM plates are normalized to the number of molecules or the number of carbon (maltotriose is the trisaccharide of D-glucose, maltose is the disaccharide). According to the manufacturer of the PM technology, concentrations are normalized to carbons (B. Bochner, unpublished comments).
Another open question relates to the effects that mutations in ldhA, ackA, pta ackA, and pflA (or pflB) really have on acetyl-CoA, rather than just making the following assumptions that are based on published metabolic pathways and diagrammed in Illustration 6. Illustration 7 summarizes these predictions.
As was previously reviewed (Wolfe 2005), acetyl-CoA has a long and interesting history. It was researched heavily in the 50s, 60s, and 70s as a metabolic intermediate and then almost ignored for some 20 or 30 years. Interestingly, research on acetyl-CoA and flux of carbon has been intensified over the past 10 years in the context of genetically engineering E. coli to produce useful substrates, such as succinate (Singh et al. 2011). Succinate is being used to make plastics, drugs, solvents and food additives (Wang et al. 2011).
Pyruvate is indeed a branch point between LdhA and PflB, while the lactate pathway and the acetate pathway share common, as well as competing characteristics. Early research by the senior author of this study has shown that mutants in ackA accumulate acetyl phosphate, while mutants in pta or pta ackA don’t synthesize acetyl phosphate (Prüß & Wolfe 1994). Both, ackA and pta ackA mutants fail to excrete acetate (Prüß & Wolfe 1994), but accumulate pyruvate (Tomar et al. 2003). Interestingly, ackA pta mutants excrete increased amounts of lactate (Yang, et al. 1999; Yang et al. 1999), while ldhA mutants excrete excessive amounts of acetate (Kabir et al. 2005). This indicates that the lactate pathway may compete with the acetate pathway at the level of pyruvate. In addition, overexpression of LdhA results in an increased flux of carbon through acetyl-CoA (Yang et al. 1999) under depletion of the pyruvate pool (Yang et al. 2001). With respect to PflA, a single-knock out mutant in pflA overexpresses LdhA and increases lactate production as a compensation for acetyl-CoA limitation (Zhu & Shimizu 2005). A triple knock-out strain, carrying mutations in pflB, adhE, and frdA, causes a similar increase in the flux of carbon to lactate, due to a decreased ATP/ADP ratio (Utrilla et al. 2009). Altogether, many metabolic studies lend credibility to our assumption from Illustration 4 that mutations in ackA, pta ackA, and ldhA lead to an increase in intracellular acetyl-CoA concentrations, while mutations in pflA or pflB decrease acetyl-CoA levels.
The pathway downstream of acetyl-CoA and acetyl phosphate has been described previously (Prüß et al. 2010). Briefly, acetyl phosphate can serve as a phosphor donor for response regulators of two-component signaling systems, including the osmoregulator OmpR (Prüß & Wolfe 1994; Shin & Park 1995) and the colanic acid activator RcsB (Fredericks et al. 2006). As a matter of fact, biofilm formation by Salmonella is dependent on the phosphorylation state of Rcs B (Latasa et al. 2012). Both, OmpR and RcsB regulate a myriad of biofilm-associated cell surface organelles that were reviewed by (Prüß et al. 2006) and are included in Illustration 4. Intriguingly, RcsB can also be activated by means of acetylation by acetyl-CoA (Thao et al. 2010). According to the current study, acetylation may be more important than phosphorylation for the production of highest biofilm amounts.
The authors wish to thank Dr. Alan J. Wolfe from Loyola University Chicago (Maywood, IL) for providing strains, Barry Bochner from BioLog (Hayward, CA) for helpful discussion and providing unpublished comments, and Priyankar Samanta (NDSU) for critically reading the manuscript. The work was funded by an earmark grant on Agrosecurity, Food Safety, and Public Health through USDA/APHIS and grant 1R15AI089403-01A1 from the NIH/NIAID. R.M. was funded by grant FAR0013949 from the USAID/HED.
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Source(s) of Funding
FAR0013949 from the USAID/HED
1R15AI089403 from the NIH/NIAID
Earmark grant through USDA/APHIS
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