Virtual colony count

Virtual colony count (VCC) is a kinetic, 96-well microbiological assay originally developed to measure the activity of defensins.[1] It has since been applied to other antimicrobial peptides including LL-37.[2] It utilizes a method of enumerating bacteria called quantitative growth kinetics, which compares the time taken for a bacterial batch culture to reach a threshold optical density with that of a series of calibration curves. The name VCC has also been used to describe the application of quantitative growth kinetics to enumerate bacteria in cell culture infection models.[3] Antimicrobial susceptibility testing (AST) can be done on 96-well plates by diluting the antimicrobial agent at varying concentrations in broth inoculated with bacteria and measuring the minimum inhibitory concentration that results in no growth. However, these methods cannot be used to study some membrane-active antimicrobial peptides, which are inhibited by the broth itself. The virtual colony count procedure takes advantage of this fact by first exposing bacterial cells to the active antimicrobial agent in a low-salt buffer for two hours, then simultaneously inhibiting antimicrobial activity and inducing exponential growth by adding broth. The growth kinetics of surviving cells can then be monitored using a temperature-controlled plate reader.

Quantitative growth kinetics

VCC calibration curves

The method of enumeration[4] of surviving cells used by VCC is termed quantitative growth kinetics (QGK). It relates the kinetic time taken for the turbidity of a bacterial batch microbiological culture in a well of a 96-well microplate to reach a threshold difference in turbidity to a 10-fold dilution series of calibration growth curves.

Quantification of the number of viable cells is done using a process mathematically identical to quantitative real-time polymerase chain reaction (QPCR), except with QGK cells, rather than copies of PCR products, grow exponentially. The time taken to reach the threshold is called the "threshold time", T_t, which is equivalent to the QPCR value "cycle time" or C_t.

There are at least five processes that cause delays in threshold times in VCC assays:

1. Adhesion, causing cells to stick to the microplate and possibly form biofilms. Unless these cells happen to be directly in the light path, their growth will not affect optical density readings.

2. Cohesion, causing cells to aggregate into clumps of various sizes instead of a homogeneous suspension of individual cells undergoing binary fission. Cohesion can cause imprecision and fluctuations in T_t. Cohesive clumps may also be adhesive, leading to both imprecision due to cohesion and inaccuracy (increased T_t) due to adhesion.

3. Bacteriostatic activity, causing cells to become unable to enter exponential growth even though they are not killed. Transient bacteriostatic activity can cause lag times, increasing T_t.

4. The metabolic lag phase of bacterial growth. Such a lag phase would be expected to occur in the assay as cells growing slowly or not at all during the initial exposure to antimicrobial peptides in the low-salt buffer are shifted to exponential growth upon addition of twice-concentrated rich media. If this metabolic lag phase increases in the presence of the antimicrobial peptide, it could be considered a form of transient bacteriostatic activity in category 3, above, although other sources of transient bacteriostatic activity, such as a delay due to the time required for the repair of damaged cell structures such as cell walls or cell membranes, are possible.

5. Bactericidal activity, or killing. Fewer surviving cells cause a delay in T_t as the survivors take longer to produce the same amount of turbidity through exponential growth. If all other processes causing increases in T_t are negligible, the VCC assay becomes a bactericidal assay and T_t can be used to enumerate viable bacteria by QGK. In this simplified case, VCC "virtual survival" results are equivalent to the "survival" results of a traditional colony count bactericidal assay.

Bacteria

VCC was initially employed to quantify the antibacterial activity of peptides against six strains of Escherichia coli, Staphylococcus aureus, Bacillus cereus, and Enterobacter aerogenes.[1] Commonly, a standard Gram-negative and Gram-positive quality control strain are compared. Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 29213 have been used as the standard Gram-negative and Gram-positive strains, respectively. VCC has also been applied to Bacillus anthracis, the causative agent of anthrax.[5]

Antimicrobial peptides

The initial virtual colony count study measured the activity of all six human alpha defensins concurrently on the same 96-well plate: HNP1, HNP2, HNP3, HNP4, HD5, and HD6.[1] Subsequently, mutated forms of some of those six defensins were studied by VCC. A conserved glycine in a beta bulge in HNP2 was replaced with a series of D-amino acids resulting in VCC activity proportional to side chain hydrophobicity and charge.[6] VCC showed that N-terminally acetylated and/or C-terminally amidated HNP2 activity is proportional to electrostatic charge.[7] VCC results were again proportional to charge for a series of salt bridge-disrupting mutants, suggesting that the salt bridge is not required for HNP2 function.[8] VCC measured the importance of N-terminal natural and artificial pro segments of the propeptide HNP1, dramatically altering activity against Escherichia coli and Staphylococcus aureus.[9][10] Enantiomer forms of HNP1, HNP4, HD5 and the beta defensin HBD2 composed entirely of D-amino acids suggested differing mechanisms of defensin activity against Gram-positive and Gram-negative bacteria.[11] VCC results of dimerization-impaired monomer and tethered dimer forms of HNP1 demonstrated the importance of dimerization.[12] Replacing the conserved glycine with L-alanine resulted in subtle VCC differences.[13] Comprehensive alanine scanning mutagenesis of HNP1[14][15] and HD5[16] demonstrated the importance of bulky hydrophobic residues. These studies have recently been expanded to include additional beta defensins, theta defensins,[5] and the human cathelicidin LL-37 and related peptides.[2]

Safe and effective pipetting technique

VCC users are cautioned to transfer cells in a small volume such as 10 microliters beneath a larger volume such as 90 microliters, similar to the QGK calibration curves shown above and the calibration curves reported in the initial VCC publication,[1] but unlike the experimental procedure used to test defensin activity in that same paper. The improved pipetting technique was described in 2011 in the study of the biosafety level 3 (BSL-3) pathogen Bacillus anthracis.[5] The original method published in 2005 involved the transfer of 50 microliters of cell suspensions to 50 microliters of liquid, which generates froth, bubbles and turbidity that is incompatible with a turbidimetric method when cells are transferred directly to the bottoms of the wells beneath the phosphate buffer solutions. Avoiding this problem by adding cell suspensions as droplets from above can cause aerosols that result in cross-contamination.[17] Bioaerosols of hazardous bacteria can also pose safety risks that can be reduced by conducting experiments within a biosafety cabinet.

References

1. Ericksen B, Wu Z, Lu W, Lehrer RI (2005). "Antibacterial Activity and Specificity of the Six Human α-Defensins". Antimicrob. Agents Chemother. 49 (1): 269–75. doi:10.1128/AAC.49.1.269-275.2005. PMC 538877. PMID 15616305.
2. Pazgier M, Ericksen B, Ling M, Toth EA, Shi J, Li X, Galliher-Beckley A, Lan L, Zou G, Zhan C, Yuan W, Pozharski E, Lu W (2013). "Structural and functional analysis of the pro-domain of human cathelicidin, LL-37". Biochemistry. 52 (9): 1547–58. doi:10.1021/bi301008r. PMC 3634326. PMID 23406372.
3. Hoffmann S, Walter S, Blume AK, Fuchs S, Schmidt C, Scholz A, Gerlach RG (2018). "High-Throughput Quantification of Bacterial-Cell Interactions Using Virtual Colony Counts". Front Cell Infect Microbiol. 8 (43). doi:10.3389/fcimb.2018.00043. PMC 5818393. PMID 29497603.
4. Brewster, JD. (2003). "A simple micro-growth assay for enumerating bacteria". J Microbiol Methods. 53 (1): 77–86. doi:10.1016/S0167-7012(02)00226-9. PMID 12609726.
5. Welkos S, Cote CK, Hahn U, Shastak O, Jedermann J, Bozue J, Jung G, Ruchala P, Pratikhya P, Tang T, Lehrer RI, Beyer W (2011). "Humanized theta-defensins (retrocyclins) enhance macrophage performance and protect mice from experimental anthrax infections". Antimicrob. Agents Chemother. 55 (9): 4238–50. doi:10.1128/AAC.00267-11. PMC 3165295. PMID 21768520.
6. Xie C, Prahl A, Ericksen B, Wu Z, Zeng P, Li X, Lu WY, Lubkowski J, Lu W (2005). "Reconstruction of the conserved beta-bulge in mammalian defensins using D-amino acids". J Biol Chem. 280 (38): 32921–9. doi:10.1074/jbc.M503084200. PMID 15894545.
7. Xie C, Zeng P, Ericksen B, Wu Z, Lu WY, Lu W (2005). "Effects of the terminal charges in human neutrophil alpha-defensin 2 on its bactericidal and membrane activity". Peptides. 26 (12): 2377–83. doi:10.1016/j.peptides.2005.06.002. PMID 16009464.
8. Wu Z, Li X, de Leeuw E, Ericksen B, Lu W (2005). "Why is the Arg5-Glu13 salt bridge conserved in mammalian alpha-defensins?". J Biol Chem. 280 (52): 43039–47. doi:10.1074/jbc.M510562200. PMID 16246847.
9. Wu Z, Li X, Ericksen B, de Leeuw E, Zou G, Zeng P, Xie C, Li C, Lubkowski J, Lu WY, Lu W (2007). "Impact of pro segments on the folding and function of human neutrophil alpha-defensins". J Mol Biol. 368 (2): 537–49. doi:10.1016/j.jmb.2007.02.040. PMC 2754399. PMID 17355880.
10. Zou G, de Leeuw E, Lubkowski J, Lu W (2008). "Molecular determinants for the interaction of human neutrophil alpha defensin 1 with its propeptide". J Mol Biol. 381 (5): 1281–91. doi:10.1016/j.jmb.2008.06.066. PMC 2754386. PMID 18616948.
11. Wei G, de Leeuw E, Pazgier M, Yuan W, Zou G, Wang J, Ericksen B, Lu WY, Lehrer RI, Lu W (2009). "Through the looking glass, mechanistic insights from enantiomeric human defensins". J Biol Chem. 284 (42): 29180–92. doi:10.1074/jbc.M109.018085. PMC 2781462. PMID 19640840.
12. Pazgier M, Wei G, Ericksen B, Jung G, Wu Z, de Leeuw E, Yuan W, Szmacinski H, Lu WY, Lubkowski J, Lehrer RI, Lu W (2012). "Sometimes it takes two to tango: contributions of dimerization to functions of human α-defensin HNP1 peptide". J Biol Chem. 287 (12): 8944–53. doi:10.1074/jbc.M111.332205. PMC 3308808. PMID 22270360.
13. Zhao L, Ericksen B, Wu X, Zhan C, Yuan W, Li X, Pazgier M, Lu W (2012). "Invariant gly residue is important for α-defensin folding, dimerization, and function: a case study of the human neutrophil α-defensin HNP1". J Biol Chem. 287 (23): 18900–12. doi:10.1074/jbc.M112.355255. PMC 3365925. PMID 22496447.
14. Wei G, Pazgier M, de Leeuw E, Rajabi M, Li J, Zou G, Jung G, Yuan W, Lu WY, Lehrer RI, Lu W (2010). "Trp-26 imparts functional versatility to human alpha-defensin HNP1". J Biol Chem. 285 (21): 16275–85. doi:10.1074/jbc.M110.102749. PMC 2871495. PMID 20220136.
15. Zhao L, Tolbert WD, Ericksen B, Zhan C, Wu X, Yuan W, Li X, Pazgier M, Lu W (2013). "Single, Double and Quadruple Alanine Substitutions at Oligomeric Interfaces Identify Hydrophobicity as the Key Determinant of Human Neutrophil Alpha Defensin HNP1 Function". PLOS ONE. 8 (11): e78937. doi:10.1371/journal.pone.0078937. PMC 3827289. PMID 24236072.
16. Rajabi M, Ericksen B, Wu X, de Leeuw E, Zhao L, Pazgier M, Lu W (2012). "Functional determinants of human enteric α-defensin HD5: crucial role for hydrophobicity at dimer interface". J Biol Chem. 287 (26): 21615–27. doi:10.1074/jbc.M112.367995. PMC 3381126. PMID 22573326.
17. Ericksen B (2014). "Safety, efficacy and utility of methods of transferring adhesive and cohesive Escherichia coli cells to microplates to avoid aerosols". F1000Res. 3: 267. doi:10.12688/f1000research.5659.2. PMC 4309163. PMID 25671086.

External links

• Centers for Disease Control Biosafety in Microbiological and Biomedical Laboratories (BMBL) 5th Edition